diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..b6e4761 --- /dev/null +++ b/.gitignore @@ -0,0 +1,129 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ diff --git a/.readthedocs.yaml b/.readthedocs.yaml new file mode 100644 index 0000000..cd93e8c --- /dev/null +++ b/.readthedocs.yaml @@ -0,0 +1,21 @@ +version: 2 + +build: + os: ubuntu-22.04 + tools: + python: "3.10" + +sphinx: + builder: html + configuration: docs/conf.py + fail_on_warning: false + +python: + install: + - method: pip + path: . + extra_requirements: [docs] + +submodules: + include: [docs/notebooks] + recursive: true \ No newline at end of file diff --git a/GRCh38_resources/HLA_regions.bed b/GRCh38_resources/HLA_regions.bed new file mode 100644 index 0000000..f30d088 --- /dev/null +++ b/GRCh38_resources/HLA_regions.bed @@ -0,0 +1,21 @@ +chr6 29722775 29738528 +chr6 29726601 29749049 +chr6 29826967 29831125 +chr6 29941260 29945884 +chr6 30489509 30494194 +chr6 31268749 31272130 +chr6 31269491 31357188 +chr6 32439878 32445046 +chr6 32517353 32530287 +chr6 32578769 32589848 +chr6 32628179 32647062 +chr6 32659467 32668383 +chr6 32659880 32660729 +chr6 32741391 32747198 +chr6 32756098 32763532 +chr6 32812763 32820466 +chr6 32934629 32941028 +chr6 32948613 32969094 +chr6 33004182 33009591 +chr6 33064569 33080775 +chr6 33075990 33089696 diff --git a/GRCh38_resources/genetic_map_GRCh38_merged.tab.gz b/GRCh38_resources/genetic_map_GRCh38_merged.tab.gz new file mode 100644 index 0000000..f587a6c Binary files /dev/null and b/GRCh38_resources/genetic_map_GRCh38_merged.tab.gz differ diff --git a/GRCh38_resources/hgTables_hg38_gencode.txt b/GRCh38_resources/hgTables_hg38_gencode.txt new file mode 100644 index 0000000..6a16be7 --- /dev/null +++ b/GRCh38_resources/hgTables_hg38_gencode.txt @@ -0,0 +1,36601 @@ + name2 chrom cdsStart cdsEnd +7 FAM138A chr1 34554 36081 +15 OR4F5 chr1 65419 71585 +34 AL627309.1 chr1 89295 133723 +57 AL627309.3 chr1 89551 91105 +61 AL627309.2 chr1 139790 140339 +65 AL627309.5 chr1 141474 173862 +93 AL627309.4 chr1 160446 161525 +97 AP006222.2 chr1 266855 268655 +101 AL732372.1 chr1 358857 366052 +111 OR4F29 chr1 450703 451697 +119 AC114498.1 chr1 587629 594768 +126 OR4F16 chr1 685679 686673 +134 AL669831.2 chr1 760911 761989 +138 LINC01409 chr1 778747 810065 +282 FAM87B chr1 817371 819837 +286 LINC01128 chr1 825138 868202 +447 LINC00115 chr1 826206 827522 +450 FAM41C chr1 868071 876903 +464 AL645608.6 chr1 904834 915976 +468 AL645608.2 chr1 911435 914948 +472 AL645608.4 chr1 914171 914971 +476 LINC02593 chr1 916865 921016 +487 SAMD11 chr1 923928 944581 +844 NOC2L chr1 944203 959309 +926 KLHL17 chr1 960584 965719 +1000 PLEKHN1 chr1 966482 975865 +1125 PERM1 chr1 975204 982093 +1154 AL645608.7 chr1 995966 998051 +1157 HES4 chr1 998962 1000172 +1196 ISG15 chr1 1001138 1014540 +1226 AL645608.1 chr1 1011997 1013193 +1230 AGRN chr1 1020120 1056118 +1570 AL645608.5 chr1 1055033 1056116 +1574 AL645608.8 chr1 1062208 1063288 +1578 RNF223 chr1 1070967 1074306 +1588 C1orf159 chr1 1081818 1116361 +1907 AL390719.3 chr1 1097585 1104598 +1911 LINC01342 chr1 1137017 1144056 +1916 AL390719.2 chr1 1169357 1170343 +1919 TTLL10-AS1 chr1 1173056 1179555 +1923 TTLL10 chr1 1173884 1197935 +2046 TNFRSF18 chr1 1203508 1206592 +2101 TNFRSF4 chr1 1211340 1214153 +2132 SDF4 chr1 1216908 1232067 +2247 B3GALT6 chr1 1232237 1235041 +2255 C1QTNF12 chr1 1242446 1246722 +2291 AL162741.1 chr1 1249777 1251334 +2294 UBE2J2 chr1 1253909 1273885 +2569 LINC01786 chr1 1275223 1280420 +2577 SCNN1D chr1 1280436 1292029 +2796 ACAP3 chr1 1292390 1309609 +2998 PUSL1 chr1 1308597 1311677 +3050 INTS11 chr1 1311585 1324691 +3888 AL139287.1 chr1 1317581 1318689 +3892 CPTP chr1 1324756 1328896 +3916 TAS1R3 chr1 1331280 1335314 +3934 DVL1 chr1 1335276 1349418 +4077 MXRA8 chr1 1352689 1361777 +4202 AURKAIP1 chr1 1373730 1375495 +4259 CCNL2 chr1 1385711 1399335 +4519 MRPL20-AS1 chr1 1399520 1402046 +4549 MRPL20 chr1 1401909 1407293 +4595 AL391244.2 chr1 1409096 1410618 +4598 ANKRD65 chr1 1418420 1421769 +4651 AL391244.1 chr1 1420245 1422691 +4655 TMEM88B chr1 1426128 1427787 +4664 LINC01770 chr1 1430539 1434573 +4677 VWA1 chr1 1434861 1442882 +4714 ATAD3C chr1 1449689 1470163 +4762 ATAD3B chr1 1471765 1497848 +4869 ATAD3A chr1 1512162 1534685 +5061 TMEM240 chr1 1534778 1540624 +5099 SSU72 chr1 1541673 1574863 +5132 AL645728.1 chr1 1574102 1577075 +5138 FNDC10 chr1 1598012 1600135 +5146 AL691432.4 chr1 1600314 1602703 +5151 AL691432.2 chr1 1613758 1615795 +5154 MIB2 chr1 1615415 1630610 +5803 MMP23B chr1 1632163 1635263 +5926 CDK11B chr1 1635227 1659012 +6303 FO704657.1 chr1 1659325 1662602 +6307 SLC35E2B chr1 1659529 1692795 +6385 CDK11A chr1 1702379 1724357 +6833 SLC35E2A chr1 1724838 1745999 +6894 NADK chr1 1751232 1780457 +7114 GNB1 chr1 1785285 1891117 +7269 AL109917.1 chr1 1891471 1892658 +7273 CALML6 chr1 1915108 1917296 +7314 TMEM52 chr1 1917590 1919279 +7375 CFAP74 chr1 1921951 2003837 +7602 AL391845.2 chr1 2013213 2015639 +7610 GABRD chr1 2019329 2030758 +7856 AL391845.1 chr1 2049203 2050070 +7864 PRKCZ chr1 2050411 2185395 +8269 AL590822.2 chr1 2141084 2145279 +8272 PRKCZ-AS1 chr1 2181794 2184389 +8280 FAAP20 chr1 2184461 2212720 +8426 AL590822.1 chr1 2212523 2220738 +8430 SKI chr1 2228319 2310213 +8460 AL590822.3 chr1 2315040 2323085 +8470 MORN1 chr1 2321253 2391707 +8604 AL589739.1 chr1 2326201 2326693 +8607 AL513477.2 chr1 2363061 2363628 +8610 RER1 chr1 2391775 2405442 +8738 PEX10 chr1 2403964 2413797 +8858 PLCH2 chr1 2425980 2505532 +9090 AL139246.1 chr1 2492300 2493258 +9094 AL139246.4 chr1 2493437 2494479 +9098 PANK4 chr1 2508537 2526611 +9340 HES5 chr1 2528745 2530263 +9352 AL139246.5 chr1 2530064 2547460 +9358 TNFRSF14-AS1 chr1 2549920 2557031 +9384 TNFRSF14 chr1 2555639 2565382 +9550 AL139246.3 chr1 2581560 2584533 +9555 PRXL2B chr1 2586491 2591469 +9739 MMEL1 chr1 2590639 2633016 +9915 AL831784.1 chr1 2632568 2636620 +9919 TTC34 chr1 2635976 2801717 +9962 AC242022.2 chr1 2768091 2784733 +9967 AC242022.1 chr1 2773603 2776473 +9979 AL592464.2 chr1 2811850 2812692 +9983 AL592464.3 chr1 2814056 2817767 +9987 AL592464.1 chr1 2814432 2814998 +9991 AL589702.1 chr1 2960658 2968707 +10000 ACTRT2 chr1 3021467 3022903 +10008 PRDM16-DT chr1 3059615 3068437 +10052 PRDM16 chr1 3069168 3438621 +10272 AL008733.1 chr1 3132927 3133709 +10276 AL590438.1 chr1 3306636 3310096 +10279 AL354743.2 chr1 3313052 3323149 +10283 AL354743.1 chr1 3367815 3373928 +10287 ARHGEF16 chr1 3454665 3481113 +10420 AL512413.1 chr1 3487246 3487627 +10423 MEGF6 chr1 3487951 3611508 +10676 AL513320.1 chr1 3623190 3624743 +10681 TPRG1L chr1 3625015 3630127 +10710 WRAP73 chr1 3630767 3652761 +10841 TP73 chr1 3652516 3736201 +11174 AL136528.1 chr1 3658938 3668772 +11179 AL136528.2 chr1 3712200 3714298 +11183 CCDC27 chr1 3746460 3771645 +11249 SMIM1 chr1 3772761 3775982 +11292 LRRC47 chr1 3778559 3796498 +11330 AL365330.1 chr1 3785008 3785538 +11333 CEP104 chr1 3812086 3857214 +11489 DFFB chr1 3857267 3885429 +11684 C1orf174 chr1 3889125 3900293 +11708 LINC01134 chr1 3900352 3917225 +11724 LINC01346 chr1 3940486 3955262 +11740 LINC01345 chr1 3944547 3949024 +11760 LINC02780 chr1 3976133 4012704 +11777 AL805961.1 chr1 4012921 4019508 +11781 LINC01777 chr1 4412027 4424689 +11857 AL355602.1 chr1 4479131 4484375 +11861 Z98747.1 chr1 4551735 4552145 +11865 LINC01646 chr1 4571481 4594016 +11901 AJAP1 chr1 4654609 4792534 +11939 Z98886.1 chr1 4730211 4734992 +11946 BX005132.1 chr1 4963954 4973298 +11951 LINC02781 chr1 4973381 4981568 +11958 LINC02782 chr1 5086459 5090899 +11964 AL139823.1 chr1 5301928 5307394 +11970 Z98259.3 chr1 5478736 5493057 +11984 Z98259.2 chr1 5480787 5482028 +11988 Z98259.1 chr1 5492978 5494674 +11991 AL365255.1 chr1 5561709 5668295 +11999 NPHP4 chr1 5862811 5992473 +12300 KCNAB2 chr1 5990927 6101193 +13296 CHD5 chr1 6101787 6180321 +13592 RPL22 chr1 6185020 6209389 +13671 AL031847.1 chr1 6204840 6205780 +13676 RNF207 chr1 6205475 6221299 +13761 ICMT chr1 6221193 6235972 +13811 LINC00337 chr1 6234692 6239444 +13826 HES3 chr1 6244179 6245578 +13840 GPR153 chr1 6247353 6261098 +13858 ACOT7 chr1 6264269 6394391 +14070 AL031848.2 chr1 6393555 6394391 +14073 HES2 chr1 6412418 6424670 +14136 ESPN chr1 6424776 6461367 +14364 AL031848.1 chr1 6443034 6447006 +14369 TNFRSF25 chr1 6460786 6466195 +14683 PLEKHG5 chr1 6466092 6520061 +15242 NOL9 chr1 6521347 6554513 +15287 TAS1R1 chr1 6555307 6579755 +15338 ZBTB48 chr1 6579994 6589280 +15431 KLHL21 chr1 6590724 6614607 +15501 PHF13 chr1 6613731 6624030 +15518 THAP3 chr1 6624866 6635586 +15603 DNAJC11 chr1 6634168 6701924 +15759 LINC01672 chr1 6724637 6730012 +15780 AL591163.1 chr1 6767954 6770038 +15785 CAMTA1-DT chr1 6783892 6784843 +15790 CAMTA1 chr1 6785454 7769706 +15995 AL512330.1 chr1 7008376 7014279 +15999 CAMTA1-IT1 chr1 7368942 7370270 +16003 Z97987.1 chr1 7382487 7389754 +16011 AL365194.1 chr1 7441096 7441554 +16015 AL359881.3 chr1 7693124 7694844 +16018 AL359881.2 chr1 7698303 7698872 +16021 AL359881.1 chr1 7700704 7700970 +16024 VAMP3 chr1 7771296 7781432 +16059 Z98884.2 chr1 7776383 7776775 +16062 PER3 chr1 7784320 7845177 +16296 Z98884.1 chr1 7810242 7827342 +16301 UTS2 chr1 7843083 7853512 +16348 TNFRSF9 chr1 7915894 7943165 +16415 PARK7 chr1 7954291 7985505 +16558 AL034417.4 chr1 7991134 8005312 +16569 AL034417.3 chr1 7998187 7999934 +16573 ERRFI1 chr1 8004404 8026309 +16631 AL034417.2 chr1 8026738 8122702 +16636 LINC01714 chr1 8201518 8215210 +16653 AL358876.2 chr1 8218190 8220529 +16657 SLC45A1 chr1 8317826 8344167 +16711 RERE chr1 8352397 8848921 +17088 RERE-AS1 chr1 8424645 8435013 +17103 AL357552.2 chr1 8805860 8807051 +17107 ENO1 chr1 8861000 8879190 +17348 ENO1-AS1 chr1 8878835 8879894 +17352 CA6 chr1 8945867 8975092 +17445 SLC2A7 chr1 9003300 9026345 +17474 SLC2A5 chr1 9035106 9088478 +17630 GPR157 chr1 9100305 9129102 +17652 MIR34AHG chr1 9148011 9198906 +17664 LNCTAM34A chr1 9182004 9196284 +17690 H6PD chr1 9234775 9271337 +17724 SPSB1 chr1 9292894 9369532 +17763 BX323043.1 chr1 9421098 9422862 +17766 LINC02606 chr1 9425094 9440564 +17776 AL928921.1 chr1 9501092 9503471 +17780 SLC25A33 chr1 9539465 9585173 +17800 TMEM201 chr1 9588911 9614877 +17882 PIK3CD chr1 9651731 9729114 +18159 PIK3CD-AS1 chr1 9652610 9654586 +18163 PIK3CD-AS2 chr1 9672426 9687555 +18168 CLSTN1 chr1 9729026 9824526 +18333 CTNNBIP1 chr1 9848276 9910336 +18396 AL357140.1 chr1 9848318 9850154 +18401 AL357140.4 chr1 9900614 9908034 +18406 LZIC chr1 9922113 9943407 +18484 AL357140.2 chr1 9942923 9949974 +18488 NMNAT1 chr1 9943428 9985501 +18546 AL603962.1 chr1 9983141 9984568 +18550 RBP7 chr1 9997206 10016021 +18579 UBE4B chr1 10032832 10181239 +18823 KIF1B chr1 10210805 10381603 +19473 AL139424.3 chr1 10381906 10387150 +19483 AL139424.2 chr1 10395416 10397432 +19496 PGD chr1 10398592 10420511 +19617 AL139424.1 chr1 10429881 10430677 +19620 CENPS chr1 10430433 10442808 +19669 CORT chr1 10449719 10451902 +19679 DFFA chr1 10456522 10472529 +19727 AL354956.1 chr1 10458555 10459338 +19731 PEX14 chr1 10472288 10630758 +19778 AL139423.2 chr1 10612222 10616452 +19782 CASZ1 chr1 10636604 10796650 +19902 AL139423.1 chr1 10639241 10654333 +19906 C1orf127 chr1 10946471 10982037 +19993 TARDBP chr1 11012344 11026420 +20391 MASP2 chr1 11026523 11047239 +20441 AL109811.2 chr1 11029659 11030528 +20447 SRM chr1 11054584 11060020 +20510 EXOSC10 chr1 11066618 11099869 +20676 AL109811.1 chr1 11068471 11073097 +20680 EXOSC10-AS1 chr1 11099675 11102100 +20687 MTOR chr1 11106535 11262551 +20895 MTOR-AS1 chr1 11143898 11149537 +20906 ANGPTL7 chr1 11189355 11195981 +20926 UBIAD1 chr1 11273206 11296049 +20967 AL031291.1 chr1 11311734 11319093 +20973 DISP3 chr1 11479155 11537551 +21039 AL590989.1 chr1 11500803 11502016 +21043 LINC01647 chr1 11609468 11613358 +21048 AL031731.1 chr1 11623558 11643416 +21052 FBXO2 chr1 11637018 11655785 +21106 FBXO44 chr1 11654375 11663327 +21248 FBXO6 chr1 11664200 11674354 +21282 MAD2L2 chr1 11674480 11691650 +21444 DRAXIN chr1 11691710 11725857 +21464 AGTRAP chr1 11736084 11754802 +21622 C1orf167 chr1 11761787 11789585 +21762 AL953897.1 chr1 11777077 11779619 +21767 MTHFR chr1 11785723 11806920 +22095 CLCN6 chr1 11806096 11848079 +22358 NPPA chr1 11845709 11848345 +22394 NPPB chr1 11857464 11858945 +22406 AL021155.5 chr1 11907940 11914298 +22425 KIAA2013 chr1 11919591 11926428 +22459 PLOD1 chr1 11934205 11975538 +22572 AL096840.2 chr1 11979533 11980127 +22575 MFN2 chr1 11980181 12013514 +22685 MIIP chr1 12019466 12032045 +22745 TNFRSF8 chr1 12063303 12144207 +22867 AL357835.1 chr1 12088441 12092264 +22873 TNFRSF1B chr1 12166991 12209228 +22928 VPS13D chr1 12230030 12512047 +23574 LINC02766 chr1 12527724 12528420 +23578 DHRS3 chr1 12567910 12618210 +23621 AC254633.1 chr1 12618900 12619244 +23624 AADACL4 chr1 12644547 12667086 +23637 AADACL3 chr1 12716110 12728760 +23655 C1orf158 chr1 12746200 12763699 +23683 PRAMEF12 chr1 12774841 12777906 +23695 PRAMEF1 chr1 12791397 12796628 +23712 LINC01784 chr1 12822686 12823159 +23716 PRAMEF11 chr1 12824605 12831410 +23730 HNRNPCL1 chr1 12847408 12848725 +23740 PRAMEF2 chr1 12857086 12861909 +23754 PRAMEF4 chr1 12879212 12886201 +23768 PRAMEF10 chr1 12892896 12898270 +23782 PRAMEF7 chr1 12916610 12920482 +23806 PRAMEF6 chr1 12938472 12947580 +23833 PRAMEF27 chr1 13049476 13056491 +23847 HNRNPCL3 chr1 13060869 13062229 +23857 PRAMEF25 chr1 13068677 13077884 +23884 HNRNPCL2 chr1 13115488 13116854 +23894 AC245056.1 chr1 13146981 13147460 +23898 PRAMEF26 chr1 13148905 13155961 +23912 HNRNPCL4 chr1 13164586 13165467 +23919 PRAMEF9 chr1 13172455 13179464 +23933 PRAMEF13 chr1 13196188 13201409 +23956 PRAMEF18 chr1 13222705 13226106 +23967 PRAMEF5 chr1 13254212 13263314 +23981 PRAMEF8 chr1 13281035 13285174 +24018 PRAMEF33 chr1 13303539 13308907 +24032 PRAMEF15 chr1 13315581 13322598 +24046 AC243961.1 chr1 13324039 13324518 +24050 PRAMEF14 chr1 13341892 13347134 +24067 PRAMEF19 chr1 13369067 13371900 +24078 PRAMEF17 chr1 13389632 13392629 +24090 PRAMEF20 chr1 13410450 13421328 +24115 LRRC38 chr1 13474973 13514003 +24125 AL354712.1 chr1 13513220 13516270 +24130 PDPN chr1 13583465 13617957 +24325 AL359771.1 chr1 13657311 13659910 +24329 PRDM2 chr1 13700198 13825079 +24519 KAZN chr1 13892792 15118043 +24712 AL357873.1 chr1 14221887 14304445 +24722 KAZN-AS1 chr1 14338825 14419973 +24761 AL031293.1 chr1 14774469 14777727 +24765 TMEM51-AS1 chr1 15111815 15153618 +24795 TMEM51 chr1 15152532 15220478 +24866 C1orf195 chr1 15164344 15171317 +24873 FHAD1 chr1 15247272 15400283 +25278 AL031283.2 chr1 15326680 15343876 +25282 AL031283.3 chr1 15334166 15335464 +25286 AL031283.1 chr1 15402979 15409433 +25295 EFHD2 chr1 15409888 15430339 +25322 CTRC chr1 15438442 15449242 +25370 CELA2A chr1 15456728 15472091 +25400 CELA2B chr1 15465909 15491395 +25442 CASP9 chr1 15490832 15526534 +25624 DNAJC16 chr1 15526813 15592379 +25831 AL121992.3 chr1 15565611 15565956 +25834 AGMAT chr1 15571699 15585051 +25854 AL121992.1 chr1 15586136 15603626 +25858 DDI2 chr1 15617458 15669044 +25925 RSC1A1 chr1 15659869 15661722 +25932 AL121992.2 chr1 15682873 15683128 +25935 PLEKHM2 chr1 15684320 15734769 +26085 AL450998.3 chr1 15720312 15736896 +26101 SLC25A34 chr1 15736258 15741392 +26125 SLC25A34-AS1 chr1 15740051 15749896 +26129 TMEM82 chr1 15742499 15747982 +26151 FBLIM1 chr1 15756607 15786594 +26340 UQCRHL chr1 15807169 15809348 +26348 AL450998.2 chr1 15834474 15848147 +26352 SPEN chr1 15847707 15940456 +26420 ZBTB17 chr1 15941869 15976132 +26601 SRARP chr1 16004236 16008807 +26611 AL355994.3 chr1 16006160 16006671 +26615 HSPB7 chr1 16014028 16019594 +26685 CLCNKA chr1 16018875 16034050 +26866 CLCNKB chr1 16043736 16057308 +26989 FAM131C chr1 16057769 16073651 +27016 EPHA2 chr1 16124337 16156069 +27069 AL451042.2 chr1 16155211 16157329 +27073 AL451042.1 chr1 16159266 16161883 +27077 ARHGEF19-AS1 chr1 16197854 16198357 +27081 ARHGEF19 chr1 16197854 16212652 +27161 AL109627.1 chr1 16228674 16231335 +27164 CPLANE2 chr1 16231692 16237183 +27189 FBXO42 chr1 16246840 16352480 +27239 SZRD1 chr1 16352575 16398145 +27327 SPATA21 chr1 16387117 16437424 +27444 NECAP2 chr1 16440721 16460078 +27621 LINC01772 chr1 16460948 16468481 +27625 AL137802.2 chr1 16514645 16515754 +27628 AL137802.1 chr1 16520694 16521796 +27632 LINC01783 chr1 16533886 16536172 +27639 NBPF1 chr1 16562319 16613562 +27822 AL137798.1 chr1 16617391 16617729 +27825 AL137798.2 chr1 16656879 16667524 +27830 AL021920.1 chr1 16701546 16705594 +27835 AL021920.3 chr1 16739938 16750589 +27840 CROCC chr1 16740273 16972964 +28070 BX284668.1 chr1 16851257 16853129 +28080 BX284668.2 chr1 16870945 16883659 +28111 BX284668.5 chr1 16887577 16889706 +28132 BX284668.6 chr1 16904339 16904776 +28135 MFAP2 chr1 16974502 16980632 +28205 AL049569.2 chr1 16976302 16977792 +28209 AL049569.1 chr1 16978926 17005091 +28213 ATP13A2 chr1 16985958 17011928 +28570 SDHB chr1 17018722 17054170 +28644 PADI2 chr1 17066761 17119451 +28722 LINC02783 chr1 17189783 17197617 +28732 AL590644.1 chr1 17193232 17201733 +28739 PADI1 chr1 17205128 17246007 +28789 PADI3 chr1 17249098 17284233 +28827 PADI4 chr1 17308195 17364004 +28892 PADI6 chr1 17372196 17401699 +28930 RCC2-AS1 chr1 17406760 17407382 +28934 RCC2 chr1 17406760 17439677 +28998 ARHGEF10L chr1 17539698 17697874 +29238 LINC02810 chr1 17717625 17749978 +29257 ACTL8 chr1 17755333 17827063 +29278 AL357509.1 chr1 18015712 18045612 +29284 LINC01654 chr1 18065657 18074412 +29289 IGSF21 chr1 18107798 18378483 +29332 IGSF21-AS1 chr1 18166929 18179346 +29338 AL591896.1 chr1 18385829 18388514 +29342 KLHDC7A chr1 18480982 18486126 +29349 PAX7 chr1 18630846 18748866 +29415 TAS1R2 chr1 18839599 18859682 +29433 ALDH4A1 chr1 18871430 18902724 +29594 IFFO2 chr1 18904280 18956676 +29646 AL137127.1 chr1 19072110 19075511 +29649 UBR4 chr1 19074510 19210266 +30142 EMC1-AS1 chr1 19210501 19240704 +30146 EMC1 chr1 19215660 19251527 +30371 MRTO4 chr1 19251805 19260128 +30401 AKR7A3 chr1 19282573 19288770 +30421 AKR7A2 chr1 19303965 19312146 +30486 SLC66A1 chr1 19312326 19329300 +30607 CAPZB chr1 19338775 19485539 +30746 MICOS10 chr1 19484403 19629821 +30824 AL031727.2 chr1 19591802 19596832 +30828 NBL1 chr1 19596979 19658456 +30997 HTR6 chr1 19664875 19680966 +31009 TMCO4 chr1 19682213 19799945 +31122 RNF186 chr1 19814029 19815283 +31130 AL391883.1 chr1 19814367 19819502 +31134 OTUD3 chr1 19882395 19912945 +31163 PLA2G2E chr1 19920009 19923617 +31177 PLA2G2A chr1 19975431 19980416 +31252 PLA2G5 chr1 20028179 20091911 +31326 PLA2G2D chr1 20111939 20119566 +31351 PLA2G2F chr1 20139326 20150386 +31370 Z98257.1 chr1 20154171 20160568 +31383 PLA2G2C chr1 20161253 20177424 +31410 UBXN10-AS1 chr1 20184242 20186486 +31414 UBXN10 chr1 20186096 20196050 +31424 LINC01757 chr1 20243095 20244664 +31432 Z98257.2 chr1 20272018 20275005 +31440 VWA5B1 chr1 20290919 20354894 +31681 AL020998.1 chr1 20294211 20323187 +31685 LINC01141 chr1 20360579 20431234 +31771 AL139254.1 chr1 20412304 20413253 +31776 AL139254.2 chr1 20476222 20478937 +31783 AL139254.3 chr1 20478779 20480397 +31787 CAMK2N1 chr1 20482391 20486210 +31800 MUL1 chr1 20499448 20508151 +31814 FAM43B chr1 20552573 20555020 +31822 CDA chr1 20589086 20618903 +31840 PINK1 chr1 20633458 20651511 +31873 PINK1-AS chr1 20642657 20652193 +31878 DDOST chr1 20651767 20661544 +31977 KIF17 chr1 20664014 20718017 +32120 SH2D5 chr1 20719731 20732837 +32230 AL663074.1 chr1 20732880 20733952 +32234 HP1BP3 chr1 20742679 20787323 +32424 EIF4G3 chr1 20806292 21176888 +32892 AL031005.2 chr1 21177054 21178164 +32895 ECE1 chr1 21217247 21345572 +33214 AL031005.1 chr1 21266082 21267251 +33219 AL031728.1 chr1 21293290 21299874 +33228 AL592309.2 chr1 21415898 21417492 +33237 NBPF3 chr1 21440128 21485005 +33514 ALPL chr1 21509397 21578410 +33647 LINC02596 chr1 21586472 21591187 +33651 RAP1GAP chr1 21596215 21669363 +34121 USP48 chr1 21678298 21783606 +34438 LDLRAD2 chr1 21812265 21825225 +34474 HSPG2 chr1 21822244 21937310 +34792 CELA3B chr1 21977022 21998642 +34838 CELA3A chr1 22001657 22012542 +34876 LINC01635 chr1 22023990 22026048 +34897 LINC00339 chr1 22024558 22031223 +34946 CDC42 chr1 22025511 22101360 +35130 CDC42-AS1 chr1 22028317 22052927 +35135 CDC42-IT1 chr1 22059197 22064199 +35139 WNT4 chr1 22117313 22143969 +35171 AL445253.1 chr1 22142850 22157401 +35178 ZBTB40 chr1 22428838 22531157 +35338 ZBTB40-IT1 chr1 22517474 22519708 +35342 EPHA8 chr1 22563489 22603595 +35397 C1QA chr1 22636628 22639678 +35427 C1QC chr1 22643633 22648110 +35461 C1QB chr1 22652762 22661637 +35504 EPHB2 chr1 22710839 22921500 +35683 AL512444.1 chr1 22835713 22836849 +35687 LACTBL1 chr1 22953043 22965338 +35718 TEX46 chr1 23010834 23015852 +35746 KDM1A chr1 23019443 23083689 +35899 AL031428.1 chr1 23020147 23088058 +35903 LUZP1 chr1 23084023 23177808 +35965 HTR1D chr1 23191895 23194729 +35973 LINC01355 chr1 23281307 23287488 +35992 AL109936.6 chr1 23297797 23302866 +35996 HNRNPR chr1 23303771 23344336 +36191 ZNF436 chr1 23359448 23369836 +36216 ZNF436-AS1 chr1 23368997 23371839 +36239 AL109936.2 chr1 23378380 23379029 +36242 TCEA3 chr1 23380909 23424748 +36335 ASAP3 chr1 23428563 23484568 +36634 E2F2 chr1 23506438 23531233 +36657 AL021154.1 chr1 23549139 23550915 +36661 ID3 chr1 23557926 23559501 +36679 AL450043.1 chr1 23576436 23593621 +36685 MDS2 chr1 23581495 23640568 +36706 RPL11 chr1 23691742 23696835 +36784 ELOA-AS1 chr1 23706901 23778296 +36807 ELOA chr1 23743155 23762059 +36894 PITHD1 chr1 23778418 23788232 +36934 LYPLA2 chr1 23791145 23795539 +37100 GALE chr1 23795599 23800781 +37298 HMGCL chr1 23801885 23838620 +37391 FUCA1 chr1 23845077 23868294 +37413 CNR2 chr1 23870515 23913362 +37423 AL590609.3 chr1 23907111 23907885 +37427 PNRC2 chr1 23956839 23963462 +37480 SRSF10 chr1 23964347 23980927 +37659 AL591178.1 chr1 24040835 24086799 +37665 MYOM3 chr1 24056035 24112135 +37788 AL591178.2 chr1 24066774 24083565 +37793 IL22RA1 chr1 24119771 24143140 +37813 IFNLR1 chr1 24154168 24187959 +37897 LINC02800 chr1 24200240 24211693 +37902 AL138902.1 chr1 24307556 24321901 +37909 GRHL3 chr1 24319322 24364482 +38116 STPG1 chr1 24356999 24416934 +38240 NIPAL3 chr1 24415802 24472976 +38371 RCAN3AS chr1 24496254 24535400 +38392 RCAN3 chr1 24502351 24541040 +38531 NCMAP-DT chr1 24538802 24556024 +38536 NCMAP chr1 24556087 24609328 +38555 SRRM1 chr1 24631716 24673281 +38843 AL445648.1 chr1 24704894 24717596 +38849 CLIC4 chr1 24745382 24844321 +38896 RUNX3 chr1 24899511 24965121 +38958 AL445471.1 chr1 24961345 24963097 +38963 AL445471.2 chr1 24968423 24970865 +38966 LINC02793 chr1 25041136 25047404 +38974 AL050344.1 chr1 25043707 25113120 +38982 AL031432.1 chr1 25208139 25209437 +38986 SYF2 chr1 25222276 25232502 +39029 AL031432.4 chr1 25232586 25234775 +39032 AL031432.5 chr1 25239494 25240253 +39035 RSRP1 chr1 25242249 25338213 +39193 AL031432.3 chr1 25247837 25248321 +39196 RHD chr1 25272393 25330445 +39415 TMEM50A chr1 25338317 25362361 +39465 RHCE chr1 25362249 25430192 +39641 MACO1 chr1 25430858 25500209 +39723 LDLRAP1 chr1 25543580 25568886 +39775 AL606491.1 chr1 25581478 25590356 +39779 MAN1C1 chr1 25617468 25786207 +39920 AL031280.1 chr1 25644544 25659111 +39924 SELENON chr1 25800176 25818221 +40038 AL020996.1 chr1 25816749 25820797 +40051 MTFR1L chr1 25818640 25832942 +40382 AL020996.3 chr1 25831913 25832134 +40385 AUNIP chr1 25831913 25859458 +40413 AL033528.2 chr1 25859613 25863420 +40417 PAQR7 chr1 25861210 25871253 +40427 STMN1 chr1 25884181 25906991 +40525 PAFAH2 chr1 25959767 25998117 +40626 EXTL1 chr1 26019884 26036464 +40670 SLC30A2 chr1 26037252 26046118 +40715 AL391650.2 chr1 26046665 26049099 +40719 TRIM63 chr1 26051304 26068436 +40747 PDIK1L chr1 26111165 26125555 +40792 FAM110D chr1 26159079 26163962 +40802 C1orf232 chr1 26164161 26168581 +40827 AL391650.1 chr1 26169516 26171831 +40880 ZNF593 chr1 26169908 26170873 +40901 CNKSR1 chr1 26177484 26189884 +41212 CATSPER4 chr1 26190561 26202968 +41283 CEP85 chr1 26234200 26278808 +41422 SH3BGRL3 chr1 26280086 26281522 +41443 UBXN11 chr1 26281328 26318363 +41807 CD52 chr1 26317958 26320523 +41824 CRYBG2 chr1 26321698 26360080 +42029 ZNF683 chr1 26361634 26374522 +42151 LIN28A chr1 26410817 26429728 +42180 DHDDS chr1 26432282 26471306 +42492 AL513365.2 chr1 26462756 26468014 +42502 HMGN2 chr1 26472440 26476642 +42584 RPS6KA1 chr1 26529761 26575030 +43013 AL512408.1 chr1 26692132 26694131 +43016 ARID1A chr1 26693236 26782104 +43354 PIGV chr1 26787472 26798398 +43423 ZDHHC18 chr1 26826688 26857604 +43501 SFN chr1 26863149 26864456 +43509 GPN2 chr1 26876132 26890283 +43560 AL034380.1 chr1 26876133 26878245 +43564 GPATCH3 chr1 26890488 26900467 +43602 NUDC chr1 26900238 26946871 +43659 NR0B2 chr1 26911489 26913975 +43669 KDF1 chr1 26949562 26960468 +43698 TRNP1 chr1 26993692 27000886 +43715 TENT5B chr1 27005020 27012850 +43725 SLC9A1 chr1 27098809 27166981 +43799 AL590640.1 chr1 27229106 27234352 +43804 WDTC1 chr1 27234632 27308636 +43936 TMEM222 chr1 27322145 27336400 +44099 SYTL1 chr1 27342020 27353937 +44289 MAP3K6 chr1 27354067 27366961 +44491 FCN3 chr1 27369112 27374824 +44539 CD164L2 chr1 27379176 27383333 +44576 GPR3 chr1 27392622 27395814 +44586 WASF2 chr1 27404230 27490167 +44631 FO393419.2 chr1 27457198 27459582 +44635 BX293535.1 chr1 27525805 27530561 +44639 AHDC1 chr1 27534035 27604431 +44793 FGR chr1 27612064 27635185 +44943 LINC02574 chr1 27660328 27662722 +44947 IFI6 chr1 27666064 27672198 +44993 AL445490.1 chr1 27669468 27703063 +45020 AL020997.5 chr1 27724822 27725756 +45023 FAM76A chr1 27725979 27763122 +45167 STX12 chr1 27773219 27824443 +45220 AL020997.2 chr1 27773858 27774041 +45223 AL020997.3 chr1 27819983 27820341 +45226 AL020997.4 chr1 27827812 27831209 +45230 PPP1R8 chr1 27830782 27851676 +45306 THEMIS2 chr1 27872543 27886685 +45415 RPA2 chr1 27891524 27914746 +45511 SMPDL3B chr1 27935000 27959157 +45615 AL512288.1 chr1 27938875 27960193 +45622 XKR8 chr1 27959462 27968096 +45638 EYA3 chr1 27970344 28088637 +45861 PTAFR chr1 28147166 28193936 +45891 DNAJC8 chr1 28199456 28233029 +45953 ATP5IF1 chr1 28236109 28246906 +45996 AL353622.1 chr1 28239509 28241453 +45999 AL353622.2 chr1 28247144 28247568 +46002 SESN2 chr1 28259518 28282491 +46028 MED18 chr1 28329002 28335965 +46064 PHACTR4 chr1 28369582 28500364 +46249 RCC1 chr1 28505943 28539300 +46524 SNHG3 chr1 28505980 28510892 +46535 TRNAU1AP chr1 28553085 28578545 +46617 SNHG12 chr1 28578538 28583132 +46710 TAF12 chr1 28589323 28643085 +46757 RAB42 chr1 28592200 28595443 +46776 LINC01715 chr1 28643228 28648581 +46783 AL360012.1 chr1 28648600 28648730 +46786 GMEB1 chr1 28668732 28719353 +46872 YTHDF2 chr1 28736621 28769775 +46959 OPRD1 chr1 28812142 28871267 +46984 AL009181.1 chr1 28870483 28877336 +46989 EPB41 chr1 28887091 29120046 +48180 TMEM200B chr1 29119429 29123903 +48199 AL357500.1 chr1 29144494 29146994 +48204 SRSF4 chr1 29147743 29181900 +48283 MECR chr1 29192657 29230942 +48451 AL590729.1 chr1 29223933 29224816 +48456 PTPRU chr1 29236516 29326813 +48766 LINC01756 chr1 29329620 29350114 +48771 AC092265.1 chr1 29708851 29709547 +48775 AL645944.2 chr1 29755175 29790597 +48782 LINC01648 chr1 30013952 30037612 +48791 AL137076.1 chr1 30140263 30141607 +48795 AL161638.2 chr1 30409560 30411638 +48800 AL161638.1 chr1 30415825 30421108 +48805 MATN1 chr1 30711277 30723585 +48835 MATN1-AS1 chr1 30718504 30726827 +48858 AL137857.1 chr1 30731693 30733427 +48862 LAPTM5 chr1 30732469 30757774 +48896 AL137027.1 chr1 30810378 30815553 +48900 LINC01778 chr1 30824217 30834864 +48973 AL445235.1 chr1 30858158 30860254 +48977 SDC3 chr1 30869466 30908758 +49013 PUM1 chr1 30931506 31065991 +49575 NKAIN1 chr1 31179745 31239887 +49627 SNRNP40 chr1 31259568 31296788 +49686 ZCCHC17 chr1 31296982 31364953 +49856 AL451070.1 chr1 31333067 31346799 +49861 FABP3 chr1 31365253 31376850 +49909 SERINC2 chr1 31409565 31434680 +50030 LINC01226 chr1 31506226 31583306 +50069 AC114488.1 chr1 31571585 31577898 +50078 TINAGL1 chr1 31576485 31587686 +50214 HCRTR1 chr1 31617686 31632518 +50290 PEF1 chr1 31629866 31644896 +50338 AC114488.2 chr1 31644049 31660162 +50468 AC114488.3 chr1 31644694 31649371 +50472 COL16A1 chr1 31652263 31704319 +50925 ADGRB2 chr1 31727117 31764893 +51474 AL354919.2 chr1 31789130 31791322 +51478 SPOCD1 chr1 31790422 31816051 +51690 AL354919.1 chr1 31842019 31855568 +51694 AL136115.2 chr1 31851913 31921841 +51698 PTP4A2 chr1 31906421 31944856 +51902 AL136115.1 chr1 31933020 31933975 +51906 AL136115.3 chr1 31972189 31987034 +51910 KHDRBS1 chr1 32013868 32060850 +51976 AL445248.1 chr1 32052291 32073474 +51981 TMEM39B chr1 32072031 32102866 +52090 KPNA6 chr1 32108056 32176563 +52186 AL049795.2 chr1 32170733 32176568 +52190 TXLNA chr1 32179675 32198285 +52243 CCDC28B chr1 32200386 32205387 +52309 AL049795.1 chr1 32204769 32206814 +52318 IQCC chr1 32205661 32208687 +52354 DCDC2B chr1 32209094 32216196 +52385 TMEM234 chr1 32214472 32222359 +52553 EIF3I chr1 32221928 32231604 +52626 FAM167B chr1 32247222 32248856 +52636 LCK chr1 32251239 32286165 +52868 HDAC1 chr1 32292083 32333635 +52968 MARCKSL1 chr1 32333839 32336233 +52978 AL109945.1 chr1 32349194 32350663 +52982 TSSK3 chr1 32351521 32364312 +53006 FAM229A chr1 32361270 32364278 +53032 BSDC1 chr1 32365103 32394731 +53291 ZBTB8B chr1 32465072 32496686 +53305 ZBTB8A chr1 32539427 32605941 +53336 ZBTB8OS chr1 32600172 32650903 +53521 RBBP4 chr1 32651142 32686211 +53820 SYNC chr1 32679906 32703596 +53863 AC114489.1 chr1 32717734 32725237 +53867 KIAA1522 chr1 32741830 32774970 +53945 YARS chr1 32775237 32818153 +54048 S100PBP chr1 32816767 32858875 +54177 FNDC5 chr1 32862268 32872482 +54254 HPCA chr1 32885994 32898441 +54283 TMEM54 chr1 32894594 32901438 +54338 AL031602.2 chr1 32925454 32951638 +54343 RNF19B chr1 32936445 32964685 +54410 AL020995.1 chr1 32987075 33032469 +54414 AK2 chr1 33007940 33080996 +54627 AZIN2 chr1 33081104 33123492 +54852 TRIM62 chr1 33145399 33182059 +54891 AL662907.3 chr1 33194788 33200353 +54898 ZNF362 chr1 33256492 33300719 +54960 AL513327.3 chr1 33261212 33261680 +54963 A3GALT2 chr1 33306766 33321098 +54978 AL513327.1 chr1 33307348 33349245 +55016 PHC2 chr1 33323623 33431052 +55172 AL513327.2 chr1 33350352 33363245 +55177 ZSCAN20 chr1 33472645 33496507 +55217 CSMD2 chr1 33513999 34165842 +55919 HMGB4 chr1 33860475 33864791 +55949 CSMD2-AS1 chr1 33868953 33893726 +56076 C1orf94 chr1 34166883 34219131 +56115 AC099565.1 chr1 34640157 34685732 +56119 SMIM12 chr1 34712737 34859755 +56182 GJB5 chr1 34755047 34758512 +56192 GJB4 chr1 34759740 34762327 +56202 AL121988.1 chr1 34761426 34788097 +56206 GJB3 chr1 34781214 34786369 +56225 GJA4 chr1 34792999 34795747 +56242 AL122010.1 chr1 34850694 34851555 +56246 DLGAP3 chr1 34865436 34929650 +56304 TMEM35B chr1 34981535 34985353 +56316 ZMYM6 chr1 34986165 35031945 +56429 ZMYM1 chr1 35032172 35115859 +56608 AL590434.1 chr1 35141515 35146435 +56613 SFPQ chr1 35176378 35193145 +56704 ZMYM4 chr1 35268709 35422058 +56846 ZMYM4-AS1 chr1 35358822 35366077 +56850 KIAA0319L chr1 35433492 35557950 +57142 NCDN chr1 35557473 35567274 +57227 AC004865.2 chr1 35569813 35577729 +57235 TFAP2E chr1 35573314 35595328 +57261 PSMB2 chr1 35599541 35641526 +57300 C1orf216 chr1 35713877 35718894 +57317 CLSPN chr1 35720218 35769978 +57545 AL354864.1 chr1 35739389 35743576 +57549 AGO4 chr1 35808016 35857890 +57598 AGO1 chr1 35869808 35930532 +57722 AL139286.3 chr1 35908980 35910872 +57726 AL139286.2 chr1 35929720 35930115 +57729 AGO3 chr1 35930718 36072500 +57902 AL138787.2 chr1 35992109 36013630 +57910 TEKT2 chr1 36084094 36088275 +57970 ADPRHL2 chr1 36088892 36093932 +57988 COL8A2 chr1 36095239 36125222 +58020 TRAPPC3 chr1 36136570 36156053 +58136 MAP7D1 chr1 36155579 36180849 +58329 THRAP3 chr1 36224432 36305357 +58429 SH3D21 chr1 36306368 36329340 +58570 EVA1B chr1 36322031 36324154 +58586 AL591845.1 chr1 36329630 36335406 +58590 STK40 chr1 36339624 36385896 +58720 LSM10 chr1 36391238 36397908 +58738 OSCP1 chr1 36415827 36450451 +58895 MRPS15 chr1 36455718 36464384 +58929 CSF3R chr1 36466043 36483278 +59200 AL596257.1 chr1 36703953 36710582 +59204 AC117945.2 chr1 36768122 36769725 +59208 AC117945.1 chr1 36769812 36775768 +59216 GRIK3 chr1 36795527 37034515 +59297 AL031430.1 chr1 37133489 37136146 +59301 AL353604.1 chr1 37154761 37325100 +59317 LINC01137 chr1 37350934 37474411 +59325 ZC3H12A chr1 37474580 37484377 +59368 MEAF6 chr1 37492575 37514774 +59496 SNIP1 chr1 37534449 37554293 +59531 DNALI1 chr1 37556919 37566857 +59581 GNL2 chr1 37566816 37595937 +59656 AL513220.1 chr1 37596126 37607336 +59660 RSPO1 chr1 37611350 37634892 +59737 C1orf109 chr1 37681570 37692249 +59859 CDCA8 chr1 37692481 37709719 +59912 EPHA10 chr1 37713880 37765133 +60160 MANEAL chr1 37793802 37801137 +60218 AL929472.3 chr1 37799720 37800879 +60222 YRDC chr1 37802945 37808208 +60238 C1orf122 chr1 37806979 37809454 +60273 MTF1 chr1 37809574 37859592 +60304 AL929472.2 chr1 37860697 37861580 +60308 INPP5B chr1 37860697 37947057 +60594 SF3A3 chr1 37956975 37990075 +60680 FHL3 chr1 37996770 38005606 +60719 UTP11 chr1 38009258 38024820 +60758 POU3F1 chr1 38043829 38046793 +60766 MIR3659HG chr1 38047314 38119025 +60778 LINC02786 chr1 38129464 38140593 +60785 AL390839.1 chr1 38149544 38162545 +60790 AL390839.2 chr1 38193619 38210340 +60794 LINC01343 chr1 38209034 38214806 +60805 LINC01685 chr1 38474825 38516520 +60867 AL354702.2 chr1 38754216 38815979 +60880 RRAGC chr1 38838198 38859772 +60912 AL139260.1 chr1 38859912 38965038 +60931 MYCBP chr1 38862493 38873368 +60970 GJA9 chr1 38874069 38881587 +60987 RHBDL2 chr1 38885807 38941830 +61041 AKIRIN1 chr1 38991276 39006059 +61094 NDUFS5 chr1 39026318 39034636 +61117 MACF1 chr1 39081316 39487177 +62906 AL356055.1 chr1 39206512 39206957 +62909 AL442071.2 chr1 39226670 39238620 +62913 AL442071.1 chr1 39249838 39257649 +62918 BMP8A chr1 39491636 39529869 +62938 PABPC4 chr1 39560816 39576790 +63249 PABPC4-AS1 chr1 39565052 39573860 +63260 HEYL chr1 39623435 39639643 +63276 AL035404.2 chr1 39633416 39633903 +63280 NT5C1A chr1 39659121 39672038 +63297 HPCAL4 chr1 39678648 39691485 +63337 PPIE chr1 39692182 39763914 +63591 BMP8B chr1 39757182 39788865 +63611 OXCT2 chr1 39769523 39771348 +63619 BMP8B-AS1 chr1 39779969 39781418 +63623 AL033527.3 chr1 39788976 39790171 +63626 AL033527.4 chr1 39799422 39809450 +63635 LINC02811 chr1 39801414 39817460 +63641 TRIT1 chr1 39838110 39883511 +63920 MYCL chr1 39895426 39902256 +63957 AL033527.2 chr1 39897745 39899098 +63961 MFSD2A chr1 39955112 39969968 +64120 CAP1 chr1 40040233 40072649 +64496 PPT1 chr1 40071461 40097727 +64840 RLF chr1 40161387 40240921 +64862 TMCO2 chr1 40245947 40251684 +64876 AL050341.2 chr1 40256427 40257967 +64879 ZMPSTE24 chr1 40258236 40294180 +64918 COL9A2 chr1 40300489 40317813 +65141 SMAP2 chr1 40344850 40423326 +65262 AL031985.4 chr1 40436199 40450039 +65269 ZFP69B chr1 40450102 40463718 +65323 AL031985.3 chr1 40464319 40466767 +65326 ZFP69 chr1 40477290 40496343 +65365 AL603839.3 chr1 40493157 40508661 +65369 EXO5 chr1 40508741 40516556 +65458 AL603839.1 chr1 40514461 40515057 +65462 AL603839.2 chr1 40515754 40517174 +65466 ZNF684 chr1 40531573 40548167 +65541 AL356379.2 chr1 40559666 40584335 +65546 RIMS3 chr1 40620680 40665682 +65589 AL031289.2 chr1 40659848 40667480 +65593 AL031289.1 chr1 40669089 40687588 +65600 NFYC-AS1 chr1 40690380 40692066 +65603 NFYC chr1 40691648 40771603 +66003 KCNQ4 chr1 40783787 40840452 +66108 CITED4 chr1 40861054 40862363 +66116 AC119677.1 chr1 40863914 40876670 +66121 AL391730.2 chr1 40939294 40945524 +66125 CTPS1 chr1 40979688 41012565 +66585 SLFNL1-AS1 chr1 41014590 41043890 +66591 SLFNL1 chr1 41015597 41023237 +66665 SCMH1 chr1 41027200 41242154 +67059 AC093151.8 chr1 41241772 41338644 +67063 AC093151.3 chr1 41242373 41284861 +67079 FOXO6 chr1 41361922 41383590 +67091 AC093151.2 chr1 41375004 41375669 +67095 EDN2 chr1 41478775 41484683 +67135 HIVEP3 chr1 41506365 42035925 +67222 AL445933.2 chr1 41535443 41535868 +67226 AC119676.1 chr1 41585306 41628816 +67235 AL158216.1 chr1 42036143 42051784 +67241 GUCA2B chr1 42153410 42155820 +67253 GUCA2A chr1 42162690 42164745 +67265 FOXJ3 chr1 42176539 42335877 +67469 AC096540.1 chr1 42335386 42338376 +67473 RIMKLA chr1 42380792 42424232 +67502 ZMYND12 chr1 42430329 42456253 +67557 PPCS chr1 42456117 42473385 +67613 CCDC30 chr1 42463221 42657190 +68791 PPIH chr1 42658423 42676758 +68892 AC098484.4 chr1 42658687 42682160 +68902 AC098484.2 chr1 42678735 42681659 +68906 YBX1 chr1 42682418 42703805 +68964 CLDN19 chr1 42733093 42740254 +69004 P3H1 chr1 42746335 42767084 +69197 C1orf50 chr1 42767249 42779491 +69221 AC098484.1 chr1 42775813 42776790 +69225 TMEM269 chr1 42785007 42816619 +69293 SVBP chr1 42807052 42817397 +69320 ERMAP chr1 42817122 42844991 +69437 AL512353.1 chr1 42832522 42846422 +69463 ZNF691 chr1 42846573 42852477 +69564 SLC2A1 chr1 42925375 42958868 +69661 SLC2A1-AS1 chr1 42959049 42996814 +69680 AC099795.1 chr1 42959065 42961864 +69699 FAM183A chr1 43145153 43156396 +69757 EBNA1BP2 chr1 43164175 43270936 +69846 CFAP57 chr1 43172149 43254358 +70047 TMEM125 chr1 43269983 43274002 +70086 C1orf210 chr1 43281877 43285617 +70109 TIE1 chr1 43300982 43323108 +70213 MPL chr1 43337849 43352772 +70290 AL139289.3 chr1 43348288 43348844 +70293 AL139289.2 chr1 43354684 43358658 +70298 CDC20 chr1 43358981 43363203 +70360 ELOVL1 chr1 43363398 43368074 +70521 MED8 chr1 43383917 43389808 +70589 AL139289.1 chr1 43385113 43389155 +70595 SZT2 chr1 43389882 43454247 +71127 SZT2-AS1 chr1 43447776 43448644 +71131 HYI chr1 43451003 43453989 +71332 HYI-AS1 chr1 43453927 43456995 +71336 PTPRF chr1 43525187 43623666 +71792 KDM4A chr1 43650149 43705518 +71887 KDM4A-AS1 chr1 43685123 43708138 +71921 ST3GAL3 chr1 43705824 43931165 +73689 AL451062.1 chr1 43709392 43727343 +73695 ARTN chr1 43933320 43937240 +73825 AL357079.1 chr1 43937918 43946551 +73839 IPO13 chr1 43946950 43968022 +73922 AL357079.2 chr1 43968351 43974821 +73928 DPH2 chr1 43970000 43973369 +74079 ATP6V0B chr1 43974487 43978295 +74244 B4GALT2 chr1 43978943 43991170 +74338 CCDC24 chr1 43991359 43996528 +74494 SLC6A9 chr1 43991500 44031467 +74716 AL139220.2 chr1 44030437 44115913 +74827 KLF17 chr1 44118821 44135140 +74854 KLF18 chr1 44137821 44141631 +74863 DMAP1 chr1 44213455 44220681 +75058 ERI3 chr1 44221070 44355260 +75202 ERI3-IT1 chr1 44243408 44244273 +75206 RNF220 chr1 44405194 44651724 +75456 TMEM53 chr1 44635238 44674481 +75536 ARMH1 chr1 44674692 44725591 +75773 KIF2C chr1 44739818 44767767 +75946 AL592166.1 chr1 44759037 44775810 +75955 RPS8 chr1 44775251 44778779 +76016 BEST4 chr1 44783585 44788170 +76040 PLK3 chr1 44800377 44805990 +76118 TCTEX1D4 chr1 44805913 44806675 +76126 BTBD19 chr1 44808482 44815585 +76213 PTCH2 chr1 44819844 44843253 +76327 EIF2B3 chr1 44850522 44986722 +76474 HECTD3 chr1 45002540 45011324 +76583 UROD chr1 45010950 45015575 +76948 ZSWIM5 chr1 45016399 45306209 +76986 LINC01144 chr1 45303910 45305619 +76989 HPDL chr1 45326895 45328679 +76997 MUTYH chr1 45329163 45340893 +77973 TOE1 chr1 45340052 45343973 +78025 TESK2 chr1 45343883 45491163 +78091 CCDC163 chr1 45493866 45500079 +78190 MMACHC chr1 45500300 45513382 +78222 PRDX1 chr1 45511036 45523047 +78302 AKR1A1 chr1 45550543 45570049 +78458 NASP chr1 45583846 45618904 +78894 CCDC17 chr1 45620044 45624057 +79051 GPBP1L1 chr1 45627304 45688113 +79158 TMEM69 chr1 45688181 45694436 +79173 IPP chr1 45694324 45750653 +79229 AL604028.1 chr1 45694684 45697075 +79233 MAST2 chr1 45786987 46036122 +79422 PIK3R3 chr1 46040140 46133036 +79552 AL358075.1 chr1 46046818 46048368 +79556 AL358075.2 chr1 46134531 46139081 +79560 TSPAN1 chr1 46175073 46185962 +79633 P3R3URF chr1 46175486 46176478 +79643 POMGNT1 chr1 46188682 46220305 +79824 LURAP1 chr1 46203334 46221256 +79834 RAD54L chr1 46246461 46278480 +80230 LRRC41 chr1 46261196 46303608 +80383 UQCRH chr1 46303698 46316776 +80431 NSUN4 chr1 46340177 46365152 +80549 FAAH chr1 46394317 46413848 +80628 LINC01398 chr1 46446600 46451317 +80646 DMBX1 chr1 46506996 46514226 +80673 TMEM275 chr1 46532166 46543969 +80683 MKNK1-AS1 chr1 46538611 46570255 +80700 KNCN chr1 46545644 46551527 +80732 MKNK1 chr1 46557408 46616843 +81190 MOB3C chr1 46607715 46616891 +81232 ATPAF1 chr1 46632737 46673867 +81469 TEX38 chr1 46668855 46673594 +81504 EFCAB14-AS1 chr1 46674036 46692098 +81514 EFCAB14 chr1 46675159 46719114 +81632 CYP4B1 chr1 46757838 46819413 +81894 CYP4A11 chr1 46929177 46941484 +82102 CYP4X1 chr1 47023669 47050751 +82136 CYP4Z1 chr1 47067231 47118318 +82170 CYP4A22-AS1 chr1 47096653 47179271 +82176 CYP4A22 chr1 47137435 47149735 +82336 LINC00853 chr1 47179250 47180339 +82340 PDZK1IP1 chr1 47183582 47191044 +82376 TAL1 chr1 47216290 47232220 +82420 AL135960.1 chr1 47225797 47230750 +82424 STIL chr1 47250139 47314147 +82652 CMPK1 chr1 47333797 47378839 +82713 LINC01389 chr1 47380928 47408477 +82718 FOXE3 chr1 47416285 47418052 +82726 FOXD2-AS1 chr1 47432133 47434641 +82729 FOXD2 chr1 47436017 47440691 +82737 LINC01738 chr1 47688463 47704029 +82742 TRABD2B chr1 47760528 47997385 +82767 AL691459.1 chr1 47761132 47765547 +82771 AC096541.1 chr1 47818066 47820237 +82775 LINC02794 chr1 48050659 48091736 +82792 AL356289.1 chr1 48078787 48082196 +82796 AL109659.1 chr1 48172972 48206857 +82803 SLC5A9 chr1 48222685 48248644 +82999 AL109659.2 chr1 48227888 48229561 +83002 SPATA6 chr1 48295373 48472208 +83180 AGBL4 chr1 48532854 50023954 +83297 AL391844.1 chr1 48552991 48558106 +83301 BEND5 chr1 48727519 48776969 +83339 AL645507.1 chr1 48926021 48936734 +83343 AC099788.1 chr1 49025595 49187585 +83349 AL590432.1 chr1 49257411 49269285 +83355 AGBL4-IT1 chr1 49374201 49472085 +83361 ELAVL4 chr1 50024029 50203786 +83655 AL592182.2 chr1 50174306 50175868 +83659 AL592182.1 chr1 50206084 50223127 +83663 LINC02808 chr1 50229662 50321192 +83702 AL592182.3 chr1 50252569 50258994 +83707 DMRTA2 chr1 50417550 50423443 +83728 AL049637.2 chr1 50423609 50425316 +83733 FAF1 chr1 50437028 50960267 +83863 AL049637.1 chr1 50461469 50471150 +83870 CDKN2C chr1 50960745 50974634 +83904 C1orf185 chr1 51102221 51148086 +83964 LINC01562 chr1 51195095 51235096 +83968 RNF11 chr1 51236273 51273447 +83986 AL162430.2 chr1 51264916 51266074 +83990 TTC39A chr1 51287258 51345116 +84402 TTC39A-AS1 chr1 51329654 51335324 +84411 EPS15 chr1 51354263 51519266 +84576 AC104170.2 chr1 51461721 51463416 +84580 AC104170.1 chr1 51518309 51561629 +84588 OSBPL9 chr1 51577179 51798427 +85333 NRDC chr1 51789191 51878937 +85715 AL050343.2 chr1 51793934 51799154 +85728 AL050343.3 chr1 51801028 51801307 +85731 RAB3B chr1 51907956 51990700 +85746 TXNDC12 chr1 52020131 52056171 +85805 KTI12 chr1 52032103 52033810 +85813 AL445685.1 chr1 52033391 52044279 +85817 TXNDC12-AS1 chr1 52050918 52052683 +85822 BTF3L4 chr1 52056199 52090716 +85920 ZFYVE9 chr1 52142094 52346686 +86057 CC2D1B chr1 52345723 52366193 +86318 AL513218.1 chr1 52353487 52353877 +86321 AL513218.2 chr1 52365443 52367865 +86325 ORC1 chr1 52372829 52404423 +86404 PRPF38A chr1 52404602 52420836 +86443 TUT4 chr1 52408282 52553487 +86847 AL591167.1 chr1 52554818 52555273 +86850 GPX7 chr1 52602371 52609051 +86865 SHISAL2A chr1 52633168 52669683 +86894 COA7 chr1 52684449 52698347 +86910 ZYG11B chr1 52726453 52827336 +86977 ZYG11A chr1 52842511 52894998 +87075 AC099677.4 chr1 52881216 52881730 +87079 ECHDC2 chr1 52895910 52927212 +87350 SCP2 chr1 52927276 53051698 +87706 PODN chr1 53062052 53085502 +87824 AL445183.1 chr1 53069938 53085502 +87828 SLC1A7 chr1 53087179 53142632 +87972 AL445183.2 chr1 53114576 53118609 +87976 CPT2 chr1 53196792 53214197 +88118 AL606760.2 chr1 53209783 53213775 +88126 CZIB chr1 53214099 53220634 +88176 AL606760.3 chr1 53220663 53224253 +88179 MAGOH chr1 53226900 53238518 +88216 AL606760.1 chr1 53238550 53246482 +88229 LRP8 chr1 53242364 53328469 +89144 AL355483.3 chr1 53267935 53268601 +89148 AL355483.1 chr1 53288024 53289706 +89152 AL355483.2 chr1 53304536 53307462 +89160 LINC01771 chr1 53328233 53336509 +89165 AC119428.2 chr1 53344031 53365473 +89171 AC119428.1 chr1 53348488 53349233 +89175 LINC02812 chr1 53366656 53368245 +89183 DMRTB1 chr1 53459399 53467488 +89201 GLIS1 chr1 53506237 53738106 +89252 NDC1 chr1 53765478 53838463 +89300 YIPF1 chr1 53851719 53889798 +89413 DIO1 chr1 53891239 53911086 +89614 HSPB11 chr1 53916574 53945929 +89680 LRRC42 chr1 53946085 53968168 +89755 LDLRAD1 chr1 54007298 54018186 +89814 TMEM59 chr1 54026681 54053504 +89958 TCEANC2 chr1 54053584 54112519 +90017 CDCP2 chr1 54132968 54153770 +90047 AL357673.2 chr1 54137746 54142980 +90051 CYB5RL chr1 54169651 54200036 +90179 MRPL37 chr1 54184041 54225464 +90255 SSBP3 chr1 54225432 54413479 +90565 SSBP3-AS1 chr1 54236440 54239063 +90568 AL161644.1 chr1 54285405 54287371 +90572 AL035415.1 chr1 54416256 54420860 +90576 AC099796.2 chr1 54514417 54517383 +90581 LINC02784 chr1 54516412 54517259 +90585 ACOT11 chr1 54542257 54639192 +90690 FAM151A chr1 54609181 54623556 +90731 AL590093.1 chr1 54621477 54628438 +90735 MROH7 chr1 54641754 54710266 +91183 TTC4 chr1 54715861 54742657 +91227 PARS2 chr1 54756898 54764523 +91237 TTC22 chr1 54779712 54801323 +91292 AC096536.1 chr1 54792885 54794905 +91296 LEXM chr1 54806063 54842252 +91349 DHCR24 chr1 54849627 54887195 +91554 AC096536.3 chr1 54874672 54883664 +91560 AC096536.2 chr1 54886875 54888001 +91564 DHCR24-DT chr1 54887563 54888850 +91578 AL590440.2 chr1 54974900 54980464 +91598 TMEM61 chr1 54980628 54992288 +91610 AL590440.1 chr1 54980950 54992274 +91614 BSND chr1 54998933 55017172 +91628 PCSK9 chr1 55039548 55064852 +91667 USP24 chr1 55066359 55215364 +91851 MIR4422HG chr1 55217645 55324691 +91858 AL603840.1 chr1 55329288 56070513 +91924 LINC01755 chr1 55868254 55950119 +91937 LINC01753 chr1 55915603 55944980 +91952 AL353681.1 chr1 56145721 56155224 +91957 AC119674.1 chr1 56154545 56477687 +92065 LINC01767 chr1 56414935 56417137 +92093 PLPP3 chr1 56494761 56645301 +92127 PRKAA2 chr1 56645314 56715335 +92175 FYB2 chr1 56718789 56819696 +92258 AL360295.1 chr1 56823679 56826920 +92262 C8A chr1 56854806 56918221 +92290 C8B chr1 56929207 56966140 +92394 AL161740.1 chr1 56963886 56996757 +92400 DAB1 chr1 56994778 58546734 +92625 AL390243.1 chr1 57386576 57387450 +92629 DAB1-AS1 chr1 57860532 57880905 +92740 AL445193.2 chr1 58060139 58080274 +92747 OMA1 chr1 58415384 58546802 +92864 AL035411.3 chr1 58546168 58563897 +92868 TACSTD2 chr1 58575433 58577252 +92876 MYSM1 chr1 58643440 58700077 +93185 AL136985.3 chr1 58715609 58771295 +93199 JUN chr1 58780791 58784047 +93207 LINC01135 chr1 58785128 58901109 +93227 AL136985.2 chr1 58812808 58813342 +93230 AL136985.1 chr1 58838448 58851254 +93235 LINC02777 chr1 58882868 58931897 +93286 LINC01358 chr1 58933643 59240555 +93439 AL592431.2 chr1 59054397 59056049 +93443 AL592431.1 chr1 59055999 59078116 +93448 AC093425.1 chr1 59131932 59296491 +93502 AC093424.1 chr1 59289303 59289640 +93505 FGGY chr1 59296638 59810647 +94007 AL035416.1 chr1 59754747 59789182 +94011 HOOK1 chr1 59814786 59876370 +94112 CYP2J2 chr1 59893308 59926773 +94216 C1orf87 chr1 59987269 60073770 +94285 LINC02778 chr1 60114875 60149784 +94296 LINC01748 chr1 60515716 60640507 +94465 AC099792.1 chr1 60659631 60868009 +94537 NFIA chr1 60865259 61462788 +95001 NFIA-AS2 chr1 60912675 61056885 +95030 NFIA-AS1 chr1 61248945 61253510 +95060 AC099791.3 chr1 61481087 61533271 +95065 AC099791.4 chr1 61588049 61589904 +95069 TM2D1 chr1 61681046 61725423 +95225 AC099791.2 chr1 61741998 61742424 +95228 PATJ chr1 61742406 62178675 +95937 L1TD1 chr1 62194849 62212328 +95951 KANK4 chr1 62236165 62319434 +96032 USP1 chr1 62436297 62451804 +96101 DOCK7 chr1 62454298 62688386 +97113 ANGPTL3 chr1 62597520 62606313 +97140 AC103923.1 chr1 62688482 62710694 +97144 ATG4C chr1 62784132 62865516 +97238 AC099794.1 chr1 62896009 62901639 +97242 LINC01739 chr1 62975751 63022504 +97261 AL162400.3 chr1 63011197 63018614 +97268 AL162400.1 chr1 63024207 63025658 +97272 AL162400.2 chr1 63078081 63079031 +97276 AC096543.1 chr1 63139250 63163153 +97281 LINC00466 chr1 63159083 63317274 +97563 AC096543.2 chr1 63249920 63251771 +97567 FOXD3-AS1 chr1 63320884 63324441 +97588 FOXD3 chr1 63322567 63325128 +97596 ALG6 chr1 63367575 63438553 +97841 ITGB3BP chr1 63440770 63593721 +97979 BX004807.1 chr1 63487957 63508204 +97983 EFCAB7 chr1 63523372 63572693 +98043 DLEU2L chr1 63547082 63550636 +98046 PGM1 chr1 63593411 63660245 +98163 ROR1 chr1 63774017 64181498 +98233 ROR1-AS1 chr1 64094442 64171297 +98252 AL445205.1 chr1 64186791 64192685 +98256 UBE2U chr1 64203627 64267368 +98358 CACHD1 chr1 64470129 64693058 +98594 RAVER2 chr1 64745095 64833232 +98674 JAK1 chr1 64833229 65067754 +99436 LINC01359 chr1 64972225 65002489 +99588 AL357078.2 chr1 65003470 65004087 +99591 AK4 chr1 65147549 65232145 +99681 DNAJC6 chr1 65248219 65415871 +99858 AL139294.1 chr1 65279456 65306521 +99862 LEPROT chr1 65420587 65436007 +99930 LEPR chr1 65420652 65641559 +100211 AC119800.1 chr1 65486406 65494188 +100215 AL513493.1 chr1 65703962 65714847 +100220 PDE4B chr1 65792514 66374579 +100482 AL590783.1 chr1 66042500 66050718 +100487 SGIP1 chr1 66533383 66751139 +100748 AL139147.1 chr1 66665864 66677027 +100752 TCTEX1D1 chr1 66752459 66779047 +100803 INSL5 chr1 66797741 66801256 +100813 WDR78 chr1 66812885 66924856 +101010 AL592161.1 chr1 66826942 66828558 +101014 MIER1 chr1 66924895 66988619 +101315 SLC35D1 chr1 66999350 67054148 +101345 C1orf141 chr1 67092165 67231853 +101487 AL133320.2 chr1 67121605 67123956 +101490 IL23R chr1 67138907 67259979 +101586 IL12RB2 chr1 67307364 67397090 +101782 SERBP1 chr1 67407810 67430415 +101886 LINC01702 chr1 67522299 67532612 +101929 GADD45A chr1 67685201 67688334 +101993 GNG12 chr1 67701475 67833467 +102010 GNG12-AS1 chr1 67832303 68202987 +102040 DIRAS3 chr1 68045886 68051631 +102063 WLS chr1 68098473 68233120 +102262 RPE65 chr1 68428822 68449954 +102296 DEPDC1 chr1 68474152 68497221 +102400 AL138789.1 chr1 68479129 68483539 +102404 DEPDC1-AS1 chr1 68496676 68538627 +102409 AL035412.1 chr1 68633701 68640425 +102414 AL033530.1 chr1 68679202 68943452 +102429 AL691520.1 chr1 68974010 69023558 +102435 LINC01707 chr1 69055838 69229607 +102479 LINC02791 chr1 69215835 69249477 +102488 LINC01758 chr1 69433255 69435409 +102492 AL359894.1 chr1 69551848 69563715 +102500 LRRC7 chr1 69568261 70151945 +102797 AL117353.1 chr1 69706950 69710274 +102801 AL158840.1 chr1 70013982 70031222 +102810 LRRC40 chr1 70144805 70205579 +102846 SRSF11 chr1 70205682 70253052 +103050 AL353771.1 chr1 70218589 70221023 +103054 ANKRD13C chr1 70258999 70354734 +103131 HHLA3 chr1 70354805 70385339 +103207 AL158839.1 chr1 70359562 70360437 +103211 CTH chr1 70411218 70439851 +103306 AL354872.2 chr1 70445071 70445536 +103309 LINC01788 chr1 70706441 70786468 +103330 AL513285.1 chr1 70715933 70720289 +103334 PTGER3 chr1 70852353 71047808 +103499 AL031429.1 chr1 70947379 70951493 +103504 AL031429.2 chr1 71005854 71006502 +103507 ZRANB2-AS1 chr1 71048855 71067184 +103514 ZRANB2 chr1 71063291 71081289 +103606 ZRANB2-AS2 chr1 71081324 71489976 +103921 NEGR1 chr1 71395943 72282539 +103971 AL354949.1 chr1 71570956 71573558 +103975 NEGR1-IT1 chr1 71794232 71837012 +103980 AL513166.1 chr1 72283170 72753772 +104017 AL583808.1 chr1 72636547 72899240 +104069 LINC02796 chr1 72765031 72791282 +104078 LINC02797 chr1 72793104 72854475 +104088 LINC01360 chr1 73305609 73355253 +104161 LINC02238 chr1 73635216 73715214 +104169 AL591463.1 chr1 73787370 73915340 +104182 LRRIQ3 chr1 74026015 74198187 +104298 FPGT chr1 74198212 74234086 +104396 TNNI3K chr1 74235387 74544428 +104505 AC093158.1 chr1 74341579 74378802 +104514 AC105271.1 chr1 74468195 74469543 +104521 LRRC53 chr1 74469878 74512614 +104537 ERICH3 chr1 74568117 74673792 +104616 ERICH3-AS1 chr1 74577430 74626098 +104628 AC135803.1 chr1 74698769 74699333 +104631 CRYZ chr1 74705482 74733408 +104757 TYW3 chr1 74733152 74766678 +104836 AC133865.1 chr1 74963314 74965118 +104840 AC099786.3 chr1 75122518 75123927 +104843 AC099786.1 chr1 75127830 75133058 +104847 LHX8 chr1 75128434 75161533 +104898 AC099786.2 chr1 75129974 75132576 +104902 SLC44A5 chr1 75202131 75611116 +105020 ACADM chr1 75724347 75787575 +105330 RABGGTB chr1 75786197 75795086 +105445 MSH4 chr1 75796882 75913242 +105491 ASB17 chr1 75918873 75932404 +105503 AC092813.1 chr1 75926454 76019356 +105695 AC092813.2 chr1 76041691 76066349 +105703 ST6GALNAC3 chr1 76074746 76634603 +105730 AC104458.1 chr1 76636877 76637339 +105733 LINC02567 chr1 76758124 76779267 +105738 ST6GALNAC5 chr1 76867480 77067546 +105780 AL035409.1 chr1 77067920 77086402 +105790 PIGK chr1 77088989 77219430 +105887 AC093433.2 chr1 77248633 77250826 +105891 AK5 chr1 77282019 77559966 +106033 AC095030.1 chr1 77346046 77349585 +106037 AC093575.1 chr1 77431314 77437604 +106041 AC118549.1 chr1 77562416 77683419 +106180 USP33 chr1 77695987 77759852 +106524 MIGA1 chr1 77779624 77879539 +106826 NEXN-AS1 chr1 77881348 77889539 +106831 NEXN chr1 77888513 77943895 +106973 FUBP1 chr1 77944055 77979110 +107173 DNAJB4 chr1 77979175 78017964 +107209 GIPC2 chr1 77979542 78138444 +107231 AC103591.3 chr1 78004346 78004554 +107234 AC103591.4 chr1 78022565 78024861 +107238 AC096531.2 chr1 78229599 78369464 +107253 PTGFR chr1 78303884 78540701 +107306 IFI44L chr1 78619922 78646145 +107394 IFI44 chr1 78649796 78664078 +107476 ADGRL4 chr1 78889764 79282124 +107824 AL353651.2 chr1 79323769 79324852 +107828 AL353651.1 chr1 79323769 79324863 +107832 LINC02792 chr1 79325008 79346445 +107836 AC099671.1 chr1 79967733 80051404 +107841 AC098657.2 chr1 80114943 80116918 +107844 AL606519.1 chr1 80373364 80374621 +107848 AL136234.1 chr1 80534978 80584363 +107852 LINC01781 chr1 80535755 80646791 +107870 AC093154.1 chr1 81209834 81222076 +107874 ADGRL2 chr1 81306160 81992436 +108591 AL138799.2 chr1 81505099 81506296 +108595 AL138799.4 chr1 81513880 81557702 +108601 AC117944.1 chr1 81585941 81625713 +108606 AL157944.1 chr1 82212413 82848205 +108640 LINC01362 chr1 82903183 83166815 +108674 LINC01361 chr1 82970820 82986208 +108689 AC116099.1 chr1 83397555 83425353 +108699 LINC01712 chr1 83445967 83480024 +108715 LINC01725 chr1 83575776 83861023 +108746 AL035706.1 chr1 83790280 83801465 +108751 TTLL7 chr1 83865024 83999150 +109050 TTLL7-IT1 chr1 83979118 83984300 +109054 AC104454.2 chr1 84038529 84065031 +109058 AL359504.2 chr1 84076331 84077931 +109061 PRKACB chr1 84078062 84238498 +109492 SAMD13 chr1 84298366 84389957 +109586 DNASE2B chr1 84398532 84415018 +109617 AL844170.1 chr1 84477039 84479157 +109621 RPF1 chr1 84479259 84498352 +109656 GNG5 chr1 84498325 84506581 +109685 SPATA1 chr1 84506300 84566194 +109740 CTBS chr1 84549611 84574480 +109803 AL359762.1 chr1 84574129 84583620 +109812 AL359762.2 chr1 84607099 84610697 +109817 LINC01555 chr1 84628230 84635020 +109822 SSX2IP chr1 84643707 84690803 +110027 AC104169.1 chr1 84785427 84786714 +110031 LPAR3 chr1 84811602 84893206 +110056 MCOLN2 chr1 84925583 84997113 +110171 WDR63 chr1 84999147 85133138 +110394 MCOLN3 chr1 85018082 85048500 +110514 SYDE2 chr1 85156889 85201016 +110538 C1orf52 chr1 85249953 85259672 +110570 BCL10 chr1 85265776 85276632 +110610 AL078459.1 chr1 85276388 85448124 +110625 DDAH1 chr1 85318481 85578363 +110706 AL360219.1 chr1 85467295 85467660 +110709 AC092807.3 chr1 85482281 85578250 +110731 AC092807.2 chr1 85578500 85578742 +110734 CCN1 chr1 85580761 85583950 +110753 AC092807.1 chr1 85599131 85600734 +110757 ZNHIT6 chr1 85649417 85708433 +110810 COL24A1 chr1 85729233 86156943 +111085 LINC02795 chr1 86288704 86320711 +111100 ODF2L chr1 86346824 86396342 +111447 CLCA2 chr1 86424171 86456553 +111490 CLCA1 chr1 86468368 86500289 +111559 CLCA4 chr1 86547078 86580754 +111596 CLCA4-AS1 chr1 86571181 86696311 +111608 AL049597.2 chr1 86703502 86704462 +111611 SH3GLB1 chr1 86704570 86748184 +111712 AL355981.1 chr1 86821558 86834169 +111717 SELENOF chr1 86862445 86914424 +111841 HS2ST1 chr1 86914635 87109982 +111889 AL121989.1 chr1 86932199 86934891 +111893 LINC01140 chr1 87129765 87169198 +111937 LINC02801 chr1 87212669 87264741 +111952 LMO4 chr1 87328880 87348923 +111993 LINC01364 chr1 87353521 87371683 +111999 PKN2-AS1 chr1 87620803 88685204 +112076 AL445438.1 chr1 88462936 88464079 +112080 PKN2 chr1 88684222 88836255 +112227 GTF2B chr1 88852633 88891944 +112299 KYAT3 chr1 88935773 88992953 +112400 RBMXL1 chr1 88979456 88992960 +112441 GBP3 chr1 89006679 89022894 +112607 GBP1 chr1 89052319 89065230 +112658 GBP2 chr1 89106132 89150456 +112733 AC104459.1 chr1 89128432 89144695 +112737 GBP7 chr1 89131742 89176009 +112786 GBP4 chr1 89181144 89198942 +112821 AC099063.4 chr1 89198714 89207040 +112825 GBP5 chr1 89258950 89272804 +112884 AC099063.1 chr1 89260582 89269754 +112888 GBP6 chr1 89364058 89386461 +112916 AL596214.1 chr1 89427533 89525472 +112933 LRRC8B chr1 89524836 89597864 +113038 LRRC8C-DT chr1 89581291 89632916 +113084 AC093423.2 chr1 89629725 89676386 +113090 LRRC8C chr1 89633072 89769903 +113123 AC099568.1 chr1 89788914 89790492 +113127 AC099568.2 chr1 89820174 89820868 +113130 LRRC8D chr1 89821014 89936611 +113196 AL391497.1 chr1 89939601 89940147 +113199 ZNF326 chr1 89995110 90035533 +113296 AL161797.1 chr1 90045998 90047109 +113300 AC098656.1 chr1 90242088 90284188 +113308 AL627316.1 chr1 90388193 90420396 +113320 LINC02787 chr1 90510910 90533472 +113326 BARHL2 chr1 90711539 90717302 +113338 AC092805.1 chr1 90719576 90725620 +113349 LINC02609 chr1 90769086 90851658 +113440 LINC02788 chr1 90835660 90849472 +113451 LINC01763 chr1 90851122 90855253 +113458 AC091614.1 chr1 90860550 90862920 +113462 ZNF644 chr1 90915298 91022272 +113559 HFM1 chr1 91260766 91404856 +113773 CDC7 chr1 91500851 91525764 +113857 TGFBR3 chr1 91680343 91906335 +114129 BRDT chr1 91949371 92014426 +114514 EPHX4 chr1 92029985 92063538 +114537 SETSIP chr1 92074533 92075441 +114550 BTBD8 chr1 92080305 92184725 +114710 AC104836.1 chr1 92189237 92190707 +114714 C1orf146 chr1 92217915 92245813 +114751 GLMN chr1 92246402 92298987 +114883 RPAP2 chr1 92299059 92402056 +114930 GFI1 chr1 92473043 92486925 +114992 EVI5 chr1 92508696 92792404 +115121 RPL5 chr1 92832013 92841924 +115231 DIPK1A chr1 92832737 92961522 +115303 AC093577.1 chr1 92978265 92987367 +115307 MTF2 chr1 93079235 93139079 +115533 TMED5 chr1 93149742 93180516 +115592 CCDC18 chr1 93179919 93278730 +115873 CCDC18-AS1 chr1 93262186 93346025 +116085 DR1 chr1 93345907 93369493 +116113 FNBP1L chr1 93448131 93554661 +116288 BCAR3 chr1 93561741 93847150 +116454 AL109613.1 chr1 93592199 93605573 +116473 AL049796.1 chr1 93847174 93848939 +116476 DNTTIP2 chr1 93866284 93879918 +116535 GCLM chr1 93885199 93909456 +116582 ABCA4 chr1 93992834 94121148 +116817 AC093579.1 chr1 94145111 94145619 +116821 ARHGAP29 chr1 94148988 94275068 +116971 ARHGAP29-AS1 chr1 94247819 94411036 +117036 AC097059.1 chr1 94318479 94324569 +117040 AC118469.2 chr1 94417743 94418228 +117043 ABCD3 chr1 94418389 94518666 +117200 F3 chr1 94529173 94541759 +117242 AC093117.1 chr1 94585556 94592297 +117246 SLC44A3 chr1 94820342 94895246 +117517 CNN3 chr1 94896949 94927223 +117605 AC105942.1 chr1 94927361 94963616 +117649 ALG14 chr1 94974405 95072951 +117671 AC095033.1 chr1 95061596 95067545 +117675 TLCD4 chr1 95117355 95197607 +117732 AC092802.3 chr1 95120147 95138554 +117736 AC092802.1 chr1 95161676 95233982 +117753 RWDD3 chr1 95234210 95247225 +117801 AC092802.2 chr1 95243167 95278940 +117824 AC092802.4 chr1 95282233 95287702 +117828 LINC01760 chr1 95310928 95318263 +117832 LINC01650 chr1 95351251 95352676 +117842 AL445218.1 chr1 95356229 95381000 +117852 LINC01761 chr1 95474737 95479356 +117858 LINC02607 chr1 95510059 95782342 +117899 AL683887.1 chr1 95743096 95759470 +117903 LINC02790 chr1 95937901 96022890 +118039 LINC01787 chr1 96254069 96374125 +118047 PTBP2 chr1 96721665 96823738 +118237 DPYD chr1 97077743 97995000 +118322 DPYD-AS1 chr1 97095923 97322955 +118335 DPYD-IT1 chr1 97394154 97420141 +118339 DPYD-AS2 chr1 97796921 97798066 +118347 MIR137HG chr1 97933474 98049863 +118377 BX005019.1 chr1 97967005 97968814 +118380 AC104453.1 chr1 98052077 98054592 +118384 LINC01776 chr1 98210747 98272658 +118389 SNX7 chr1 98661701 98760500 +118472 PLPPR5 chr1 98890245 99005032 +118529 AL445433.2 chr1 99004276 99244794 +118557 PLPPR4 chr1 99263953 99309590 +118607 LINC01708 chr1 99472332 99600995 +118625 PALMD chr1 99646113 99694541 +118697 FRRS1 chr1 99708632 99766631 +118787 AGL chr1 99850361 99924023 +119261 AC118553.1 chr1 99968383 99969864 +119265 SLC35A3 chr1 99969351 100035634 +119695 MFSD14A chr1 100038095 100083377 +119729 AC093019.2 chr1 100057990 100084471 +119733 SASS6 chr1 100083563 100132955 +119790 TRMT13 chr1 100133150 100150498 +119874 LRRC39 chr1 100148449 100178273 +119975 DBT chr1 100186919 100249834 +120023 AL445928.2 chr1 100220488 100253414 +120028 RTCA-AS1 chr1 100251528 100266179 +120055 RTCA chr1 100266207 100292769 +120135 AC104457.2 chr1 100344477 100345242 +120139 CDC14A chr1 100345001 100520277 +120541 AL589990.1 chr1 100462399 100485997 +120545 GPR88 chr1 100538139 100542021 +120555 LINC01349 chr1 100627049 100640613 +120560 AC099670.3 chr1 100628230 100641723 +120565 VCAM1 chr1 100719742 100739045 +120677 EXTL2 chr1 100872372 100895179 +120754 AC104506.1 chr1 100894928 100895356 +120757 SLC30A7 chr1 100896076 100981757 +120823 DPH5 chr1 100989623 101026088 +120976 AC093157.2 chr1 100995473 100996260 +120980 AC093157.1 chr1 101025844 101090513 +121102 AL109741.1 chr1 101235683 101236528 +121106 S1PR1 chr1 101236865 101243713 +121154 LINC01307 chr1 101323337 101390303 +121167 LINC01709 chr1 101639509 101787572 +121267 OLFM3 chr1 101802574 101997030 +121340 AC114485.1 chr1 102199739 102389630 +121352 AC099567.1 chr1 102763322 102853842 +121361 COL11A1 chr1 102876467 103108872 +122321 AC095032.2 chr1 103414879 103425465 +122325 AC095032.1 chr1 103415980 103525511 +122350 RNPC3 chr1 103525691 103555239 +122522 AMY2B chr1 103553815 103579534 +122640 AMY2A chr1 103616811 103625780 +122708 AMY1A chr1 103655290 103664554 +122768 AMY1B chr1 103687415 103696680 +122850 AMY1C chr1 103750406 103758690 +122876 AL591888.1 chr1 104998406 105032365 +122883 LINC01676 chr1 105587575 105618991 +123002 LINC01677 chr1 105927620 106028277 +123057 AL355306.2 chr1 105956694 106124564 +123129 LINC01661 chr1 106818224 106865316 +123149 PRMT6 chr1 107056674 107067636 +123169 NTNG1 chr1 107140007 107483458 +123321 VAV3 chr1 107571161 107965180 +123659 VAV3-AS1 chr1 107964443 107994607 +123664 LINC02785 chr1 108040263 108076020 +123694 SLC25A24 chr1 108134043 108200849 +123802 AL359258.2 chr1 108199926 108201491 +123805 NBPF4 chr1 108223341 108244081 +123878 AL359258.1 chr1 108261196 108273689 +123882 AL390038.1 chr1 108420689 108433184 +123886 NBPF6 chr1 108450282 108471002 +123990 FAM102B chr1 108560089 108644900 +124050 HENMT1 chr1 108648290 108661526 +124166 AL160171.1 chr1 108661533 108666246 +124171 PRPF38B chr1 108692310 108702928 +124232 FNDC7 chr1 108712908 108742749 +124283 AL591719.2 chr1 108734256 108734725 +124287 STXBP3 chr1 108746674 108809523 +124359 AKNAD1 chr1 108815898 108963484 +124568 SPATA42 chr1 108857217 108858524 +124579 GPSM2 chr1 108875350 108934545 +124791 CLCC1 chr1 108929508 108963457 +124959 WDR47 chr1 108970214 109042113 +125177 TAF13 chr1 109062486 109076003 +125206 AL356488.3 chr1 109087971 109090858 +125209 TMEM167B chr1 109089803 109096934 +125240 AL356488.2 chr1 109100193 109100619 +125243 C1orf194 chr1 109105951 109113857 +125314 KIAA1324 chr1 109113679 109206781 +125602 SARS chr1 109213918 109238182 +125674 CELSR2 chr1 109249539 109275751 +125768 PSRC1 chr1 109279556 109283186 +125941 MYBPHL chr1 109292365 109307011 +125975 SORT1 chr1 109309568 109397918 +126128 PSMA5 chr1 109399042 109426448 +126196 SYPL2 chr1 109466546 109482134 +126217 ATXN7L2 chr1 109483479 109492804 +126297 CYB561D1 chr1 109494052 109502932 +126399 AMIGO1 chr1 109504178 109509738 +126418 GPR61 chr1 109539872 109548406 +126484 AL355310.3 chr1 109539906 109543837 +126488 GNAI3 chr1 109548615 109618324 +126512 AL355310.1 chr1 109596225 109597781 +126516 GNAT2 chr1 109603254 109619929 +126551 AMPD2 chr1 109616104 109632053 +127175 AL355310.2 chr1 109628417 109630305 +127180 GSTM4 chr1 109656099 109674836 +127325 GSTM2 chr1 109668022 109709551 +127526 GSTM1 chr1 109687814 109709039 +127644 AC000032.1 chr1 109693117 109693742 +127648 GSTM5 chr1 109711780 109775428 +127740 AL158847.1 chr1 109725820 109775252 +127746 GSTM3 chr1 109733932 109741038 +127846 EPS8L3 chr1 109750080 109764027 +128035 LINC01768 chr1 109828355 109871436 +128041 AL450468.1 chr1 109884176 109886264 +128045 AL450468.2 chr1 109895973 109897861 +128048 CSF1 chr1 109910242 109930992 +128198 AHCYL1 chr1 109984765 110023742 +128333 STRIP1 chr1 110031577 110074641 +128511 AL160006.1 chr1 110058340 110062555 +128514 ALX3 chr1 110059870 110070672 +128539 LINC01397 chr1 110082688 110109719 +128545 UBL4B chr1 110112443 110113947 +128553 SLC6A17 chr1 110150494 110202202 +128586 AL355990.1 chr1 110165948 110172489 +128597 AL355990.2 chr1 110177643 110178719 +128601 LINC02586 chr1 110208834 110209987 +128605 KCNC4 chr1 110211343 110283100 +128678 RBM15-AS1 chr1 110286375 110339171 +128684 RBM15 chr1 110338506 110346681 +128768 LAMTOR5-AS1 chr1 110347116 110443817 +129023 SLC16A4 chr1 110362851 110391082 +129202 AL355488.1 chr1 110370154 110373003 +129205 LAMTOR5 chr1 110401249 110407942 +129292 PROK1 chr1 110451149 110457358 +129304 AL358215.1 chr1 110456505 110457354 +129308 AL358215.2 chr1 110472543 110474980 +129318 CYMP-AS1 chr1 110487680 110490258 +129322 KCNA10 chr1 110517217 110519175 +129330 KCNA2 chr1 110519837 110631474 +129476 AL365361.1 chr1 110653560 110657040 +129479 KCNA3 chr1 110672465 110674940 +129487 CD53 chr1 110871188 110899922 +129548 AL360270.2 chr1 110936369 110942353 +129551 AL360270.1 chr1 110943467 110952848 +129555 LRIF1 chr1 110947190 110963965 +129591 AL360270.3 chr1 110963302 110964649 +129594 DRAM2 chr1 111117333 111140216 +129720 CEPT1 chr1 111139627 111185104 +129840 AL355816.1 chr1 111181374 111181491 +129843 AL355816.2 chr1 111184415 111185061 +129846 DENND2D chr1 111185969 111204535 +129940 CHI3L2 chr1 111200771 111243440 +130213 CHIA chr1 111290851 111320566 +130442 AL356387.1 chr1 111317600 111323981 +130446 PIFO chr1 111346600 111353013 +130489 OVGP1 chr1 111414319 111427735 +130524 AL390195.2 chr1 111431046 111433068 +130527 AL390195.1 chr1 111438638 111441364 +130534 WDR77 chr1 111439890 111449256 +130598 ATP5PB chr1 111448864 111462773 +130658 C1orf162 chr1 111473792 111478512 +130697 TMIGD3 chr1 111483348 111563962 +130764 ADORA3 chr1 111499429 111503760 +130789 RAP1A chr1 111542218 111716691 +130859 LINC01160 chr1 111599655 111608723 +130876 INKA2 chr1 111680630 111755824 +130911 INKA2-AS1 chr1 111739579 111747798 +130923 AL049557.1 chr1 111745299 111755537 +130933 DDX20 chr1 111755245 111768000 +131007 KCND3 chr1 111770662 111989155 +131065 KCND3-IT1 chr1 111853762 111856905 +131069 KCND3-AS1 chr1 111909336 111910931 +131083 LINC01750 chr1 111989770 111998842 +131093 AL445426.1 chr1 112177234 112360625 +131111 CTTNBP2NL chr1 112396214 112463456 +131150 WNT2B chr1 112466541 112530165 +131201 AL354760.1 chr1 112517799 112518441 +131204 ST7L chr1 112523514 112620825 +131629 CAPZA1 chr1 112619805 112671616 +131686 MOV10 chr1 112673141 112700746 +131966 AL603832.1 chr1 112693688 112696621 +131971 RHOC chr1 112701106 112707434 +132233 PPM1J chr1 112709994 112715477 +132329 AL603832.2 chr1 112715672 112717796 +132332 TAFA3 chr1 112720419 112727235 +132363 LINC01356 chr1 112820170 112850643 +132392 LINC01357 chr1 112849821 112877871 +132403 SLC16A1 chr1 112911847 112957013 +132475 SLC16A1-AS1 chr1 112956415 113047055 +132530 AL390242.1 chr1 112978610 112999636 +132534 LRIG2-DT chr1 113011687 113073113 +132539 LRIG2 chr1 113073198 113132260 +132608 MAGI3 chr1 113390515 113685923 +132808 PHTF1 chr1 113696831 113759489 +133068 RSBN1 chr1 113761832 113812476 +133171 AL137856.1 chr1 113812379 113870159 +133190 PTPN22 chr1 113813811 113871753 +133506 AP4B1-AS1 chr1 113856635 113901237 +133513 BCL2L15 chr1 113876816 113887581 +133560 AP4B1 chr1 113894194 113905201 +133707 DCLRE1B chr1 113905213 113914086 +133756 HIPK1-AS1 chr1 113924000 113929495 +133779 HIPK1 chr1 113929324 113977869 +134101 OLFML3 chr1 113979391 114035572 +134143 AL591742.2 chr1 114032393 114034511 +134146 SYT6 chr1 114089291 114153919 +134314 AL121999.1 chr1 114206427 114262278 +134318 TRIM33 chr1 114392790 114511203 +134455 BCAS2 chr1 114567557 114581629 +134482 DENND2C chr1 114582848 114670422 +134642 AMPD1 chr1 114673090 114695618 +134778 NRAS chr1 114704469 114716771 +134798 CSDE1 chr1 114716913 114758676 +135217 SIKE1 chr1 114769479 114780685 +135279 SYCP1 chr1 114854863 114995370 +135645 TSHB chr1 115029824 115034309 +135665 TSPAN2 chr1 115048011 115089503 +135728 LINC01765 chr1 115099672 115102658 +135732 AL049825.1 chr1 115270767 115283763 +135738 NGF-AS1 chr1 115283034 115368072 +135742 NGF chr1 115285918 115338236 +135754 AL512638.3 chr1 115356664 115364897 +135759 VANGL1 chr1 115641970 115698224 +135850 CASQ2 chr1 115700007 115768781 +135882 NHLH2 chr1 115836377 115843917 +135908 LINC01649 chr1 115904855 115931616 +135942 SLC22A15 chr1 115976513 116070054 +135993 AL365318.1 chr1 116013813 116017705 +135998 MAB21L3 chr1 116111755 116135240 +136023 LINC01779 chr1 116164284 116166241 +136027 AL355538.1 chr1 116289237 116297621 +136032 ATP1A1 chr1 116372668 116410261 +136244 ATP1A1-AS1 chr1 116390575 116418635 +136261 LINC01762 chr1 116423724 116478842 +136294 AL136376.1 chr1 116429049 116433368 +136298 AL390066.1 chr1 116493016 116499212 +136302 AL390066.2 chr1 116493350 116502634 +136306 CD58 chr1 116514534 116571039 +136376 IGSF3 chr1 116574399 116667755 +136467 C1orf137 chr1 116694112 116706603 +136473 CD2 chr1 116754430 116769229 +136498 AL157904.1 chr1 116909149 116909531 +136501 PTGFRN chr1 116909916 116990353 +136531 CD101 chr1 117001750 117036476 +136587 AL445231.1 chr1 117025482 117059490 +136596 TTF2 chr1 117060326 117107453 +136687 TRIM45 chr1 117111060 117122587 +136761 VTCN1 chr1 117143587 117210960 +136850 LINC01525 chr1 117272182 117321336 +136863 AL358072.1 chr1 117364899 117365473 +136866 MAN1A2 chr1 117367449 117528872 +136945 AL157902.1 chr1 117596832 117605770 +136957 TENT5C chr1 117606048 117628389 +136967 GDAP2 chr1 117863485 117929621 +137060 WDR3 chr1 117929720 117966543 +137158 SPAG17 chr1 117953590 118185228 +137355 AL391557.1 chr1 118185349 118207051 +137360 TBX15 chr1 118883046 118989556 +137414 AL139420.1 chr1 119000344 119001392 +137418 AL139420.2 chr1 119000618 119001405 +137422 WARS2 chr1 119031216 119140671 +137472 WARS2-IT1 chr1 119047405 119064785 +137476 WARS2-AS1 chr1 119140391 119275973 +137523 AL359915.1 chr1 119230313 119327915 +137540 LINC01780 chr1 119327399 119356182 +137550 HAO2 chr1 119368779 119394130 +137634 HAO2-IT1 chr1 119368946 119370331 +137638 HSD3B2 chr1 119414931 119423035 +137689 HSD3B1 chr1 119507198 119515054 +137730 LINC00622 chr1 119597702 119599271 +137733 ZNF697 chr1 119619377 119648266 +137745 PHGDH chr1 119648411 119744226 +138334 HMGCS2 chr1 119747996 119768905 +138392 REG4 chr1 119794017 119811580 +138453 ADAM30 chr1 119893533 119896515 +138461 NOTCH2 chr1 119911553 120100779 +138690 AC245008.1 chr1 120076616 120077091 +138693 SEC22B chr1 120150898 120176520 +138716 AC253572.1 chr1 120723946 120793874 +138732 NBPF26 chr1 120723949 120842110 +139202 AC253572.2 chr1 120849674 120850985 +139205 PPIAL4A chr1 120889746 120890405 +139213 LINC00623 chr1 120913184 121009291 +139237 FCGR1B chr1 121087345 121097161 +139341 AC244453.3 chr1 121087528 121116676 +139345 AC244453.2 chr1 121090289 121097655 +139349 AC244453.1 chr1 121118126 121146826 +139355 FAM72B chr1 121167646 121185539 +139428 SRGAP2C chr1 121184811 121392874 +139482 SRGAP2-AS1 chr1 121360156 121398806 +139492 LINC02798 chr1 121396754 121463508 +139517 AL592494.1 chr1 121494329 121511588 +139528 AL592494.2 chr1 121518366 121518829 +139531 LINC01691 chr1 121573946 121580524 +139535 LINC02799 chr1 143499187 143500512 +139540 AC239800.2 chr1 143736066 143739506 +139544 LINC02591 chr1 143790010 143797108 +139548 HIST2H3PS2 chr1 143894544 143905966 +139572 AC246680.1 chr1 143905487 143934776 +139578 FAM72C chr1 143955364 143971965 +139603 IGKV1OR1-1 chr1 144085628 144086098 +139607 LINC02802 chr1 144227029 144250326 +139622 PPIAL4E chr1 144372875 144373659 +139630 AC246785.3 chr1 144418113 144419192 +139634 NBPF15 chr1 144421386 144461674 +139813 PPIAL4F chr1 144592868 144593652 +139821 LINC01632 chr1 144627192 144642372 +139832 FP700111.1 chr1 144641371 144919902 +139838 SRGAP2B chr1 144887265 145095528 +139930 FAM72D chr1 145095974 145112696 +139944 PPIAL4D chr1 145241630 145242124 +139951 AC245014.3 chr1 145281116 145281462 +139954 AC245014.1 chr1 145286610 145287755 +139958 NBPF20 chr1 145289900 145405778 +140652 AC239860.4 chr1 145475606 145480999 +140656 GPR89A chr1 145607988 145670650 +140886 PDZK1 chr1 145670852 145708148 +140984 CD160 chr1 145719471 145739288 +141046 RNF115 chr1 145738868 145824095 +141077 POLR3C chr1 145824088 145844402 +141170 NUDT17 chr1 145845630 145848954 +141215 PIAS3 chr1 145848522 145859836 +141341 ANKRD35 chr1 145866560 145885866 +141404 ITGA10 chr1 145891208 145910111 +141535 AC243547.1 chr1 145892847 145893483 +141539 PEX11B chr1 145911350 145918717 +141573 RBM8A chr1 145917714 145927678 +141670 LIX1L-AS1 chr1 145926590 145959179 +141749 LIX1L chr1 145933423 145958017 +141767 ANKRD34A chr1 145959441 145964575 +141797 AC243547.2 chr1 145961388 145964422 +141801 POLR3GL chr1 145964690 145978848 +141852 TXNIP chr1 145992435 145996579 +141900 HJV chr1 146017468 146036746 +141978 AC239799.2 chr1 146050441 146052244 +141981 LINC01719 chr1 146052566 146061948 +142021 NBPF10 chr1 146064711 146229000 +142439 NOTCH2NLA chr1 146146203 146229026 +142476 AC239799.1 chr1 146235806 146237807 +142479 PPIAL4H chr1 146344131 146344790 +142487 AC245407.2 chr1 146387202 146388092 +142491 NBPF12 chr1 146938744 146996202 +142920 AC244394.2 chr1 147001931 147003618 +142929 PRKAB2 chr1 147155106 147172550 +142962 AC242426.2 chr1 147172755 147295734 +143009 FMO5 chr1 147175351 147243050 +143154 CHD1L chr1 147242654 147295765 +144582 LINC00624 chr1 147258885 147517875 +144595 BCL9 chr1 147541501 147626216 +144631 ACP6 chr1 147629652 147670524 +144772 AC241644.1 chr1 147697794 147699335 +144776 GJA5 chr1 147756199 147773362 +144802 AC241644.3 chr1 147757185 147758434 +144809 AC241644.2 chr1 147777590 147788953 +144813 GJA8 chr1 147907956 147909257 +144820 GPR89B chr1 147928393 147993592 +144969 AC239803.1 chr1 148011799 148012228 +144972 LINC02804 chr1 148013203 148025934 +144996 NBPF11 chr1 148102046 148152322 +145239 LINC02805 chr1 148156139 148186980 +145312 AC239809.3 chr1 148159213 148255012 +145484 LINC01731 chr1 148271884 148280749 +145489 LINC01138 chr1 148290889 148519604 +145576 LINC02806 chr1 148295180 148297556 +145580 AC245100.1 chr1 148295895 148344638 +145600 AC245100.6 chr1 148358245 148358686 +145603 PPIAL4G chr1 148479824 148483679 +145611 NBPF14 chr1 148531385 148679742 +146199 NOTCH2NLB chr1 148607040 148679779 +146215 NUDT4B chr1 148748894 148750099 +146223 PDE4DIP chr1 148808181 149048286 +147274 AC239802.1 chr1 149006309 149009527 +147279 AC239802.2 chr1 149018671 149026269 +147284 AC239804.1 chr1 149048576 149051273 +147288 NBPF9 chr1 149054027 149103561 +147690 AC245297.3 chr1 149175748 149259987 +147730 AC245297.2 chr1 149264252 149264816 +147733 NOTCH2NLC chr1 149390614 149468030 +147781 NBPF19 chr1 149475338 149556361 +148147 PPIAL4C chr1 149583865 149584464 +148155 AC242842.1 chr1 149607765 149612402 +148161 FCGR1A chr1 149782671 149792518 +148196 HIST2H2BF chr1 149782689 149812373 +148222 AC243772.2 chr1 149785659 149793020 +148226 HIST2H3D chr1 149813271 149813681 +148233 HIST2H4A chr1 149832659 149839767 +148268 HIST2H3C chr1 149839538 149841193 +148276 HIST2H2AA3 chr1 149842188 149842736 +148284 HIST2H2AA4 chr1 149851061 149851624 +148292 HIST2H3A chr1 149852619 149854274 +148300 HIST2H4B chr1 149854045 149861210 +148326 AC239868.1 chr1 149861271 149862504 +148329 HIST2H2BE chr1 149884459 149886652 +148337 HIST2H2AC chr1 149886975 149887364 +148344 HIST2H2AB chr1 149887484 149888013 +148352 BOLA1 chr1 149887890 149900798 +148385 SV2A chr1 149903318 149917844 +148446 SF3B4 chr1 149923317 149927803 +148473 MTMR11 chr1 149928651 149936879 +148622 OTUD7B chr1 149937812 150010726 +148682 AC244033.2 chr1 150045660 150067701 +148702 VPS45 chr1 150067279 150145329 +149080 PLEKHO1 chr1 150149183 150164720 +149141 AC242988.2 chr1 150173049 150181429 +149146 ANP32E chr1 150218417 150236156 +149291 AC242988.1 chr1 150255095 150257286 +149295 CA14 chr1 150257251 150265078 +149398 APH1A chr1 150265399 150269580 +149485 C1orf54 chr1 150268200 150280916 +149539 CIART chr1 150282543 150287093 +149628 MRPS21 chr1 150293720 150308979 +149649 PRPF3 chr1 150321479 150353233 +149724 RPRD2 chr1 150363091 150476566 +149800 TARS2 chr1 150487364 150507609 +150052 ECM1 chr1 150508062 150513789 +150149 FALEC chr1 150515757 150518032 +150153 AL356356.1 chr1 150548562 150557724 +150161 ADAMTSL4 chr1 150549369 150560937 +150334 ADAMTSL4-AS1 chr1 150560202 150574552 +150344 MCL1 chr1 150574551 150579738 +150380 ENSA chr1 150600851 150629612 +150552 GOLPH3L chr1 150646230 150697154 +150586 HORMAD1 chr1 150698060 150720895 +150745 CTSS chr1 150730188 150765792 +150823 CTSK chr1 150796208 150808260 +150862 ARNT chr1 150809713 150876708 +151147 CTXND2 chr1 150887136 150913292 +151157 SETDB1 chr1 150926263 150964744 +151449 CERS2 chr1 150960583 150975004 +151667 AL590133.2 chr1 150965245 150966256 +151674 AL590133.1 chr1 150973123 150975534 +151679 ANXA9 chr1 150982249 150995634 +151719 MINDY1 chr1 150996086 151008375 +151865 PRUNE1 chr1 151008420 151035713 +152018 BNIPL chr1 151036321 151047720 +152145 C1orf56 chr1 151047751 151051986 +152162 CDC42SE1 chr1 151050971 151070325 +152238 MLLT11 chr1 151057758 151068497 +152248 GABPB2 chr1 151070578 151125542 +152317 AL592424.1 chr1 151130075 151131610 +152320 SEMA6C chr1 151131685 151146664 +152575 TNFAIP8L2 chr1 151156649 151159749 +152585 SCNM1 chr1 151156664 151170297 +152661 LYSMD1 chr1 151159748 151165948 +152684 TMOD4 chr1 151169986 151176284 +152768 VPS72 chr1 151169987 151195321 +152844 PIP5K1A chr1 151197949 151249536 +153095 PSMD4 chr1 151254703 151267479 +153225 ZNF687-AS1 chr1 151279678 151281950 +153238 ZNF687 chr1 151281618 151292176 +153343 PI4KB chr1 151291797 151327715 +153559 AL391069.3 chr1 151327949 151328429 +153562 RFX5 chr1 151340640 151347357 +153904 AL391069.1 chr1 151340648 151341966 +153908 AL391069.2 chr1 151346967 151348027 +153912 SELENBP1 chr1 151364304 151372707 +154246 PSMB4 chr1 151399560 151401937 +154293 POGZ chr1 151402724 151459494 +154659 CGN chr1 151510510 151538692 +154756 TUFT1 chr1 151540305 151583583 +154882 AL365436.2 chr1 151540516 151561855 +154886 SNX27 chr1 151612006 151699091 +155169 AL391335.1 chr1 151612038 151613363 +155173 CELF3 chr1 151700058 151716803 +155296 AL589765.1 chr1 151701026 151708386 +155300 RIIAD1 chr1 151710433 151729805 +155357 AL589765.7 chr1 151755541 151759911 +155361 MRPL9 chr1 151759647 151763496 +155487 OAZ3 chr1 151762899 151771334 +155630 AL589765.4 chr1 151763384 151769501 +155635 AL589765.2 chr1 151765709 151766389 +155639 AL589765.5 chr1 151766486 151767000 +155642 TDRKH chr1 151770107 151791416 +155978 TDRKH-AS1 chr1 151790804 151794402 +155988 AL589765.6 chr1 151798054 151798602 +155991 LINGO4 chr1 151800264 151806154 +156001 RORC chr1 151806071 151831845 +156143 C2CD4D chr1 151837819 151840557 +156153 C2CD4D-AS1 chr1 151841877 151850385 +156158 THEM5 chr1 151847101 151853712 +156183 THEM4 chr1 151870866 151909637 +156239 AL450992.2 chr1 151885251 151899333 +156244 AL450992.3 chr1 151944890 151953985 +156248 S100A10 chr1 151982915 151993859 +156280 AL450992.1 chr1 151994531 152042774 +156295 S100A11 chr1 152032506 152047907 +156311 TCHHL1 chr1 152084141 152089064 +156323 TCHH chr1 152106317 152115454 +156343 AL589986.1 chr1 152122534 152125065 +156347 RPTN chr1 152153595 152159228 +156359 FLG-AS1 chr1 152168125 152445456 +156481 AL589986.2 chr1 152205858 152207057 +156485 HRNR chr1 152212076 152224193 +156497 FLG chr1 152302175 152325203 +156509 FLG2 chr1 152348735 152360006 +156521 CRNN chr1 152409243 152414263 +156533 LCE5A chr1 152510803 152512177 +156543 CRCT1 chr1 152514482 152516008 +156553 LCE3E chr1 152565654 152566780 +156563 LCE3D chr1 152579381 152580516 +156573 LCE3C chr1 152600662 152601086 +156581 LCE3B chr1 152613811 152614098 +156588 LCE3A chr1 152622834 152623103 +156595 LCE2D chr1 152663380 152664659 +156605 LCE2C chr1 152675295 152676574 +156615 LCE2B chr1 152686123 152687397 +156625 LCE2A chr1 152698345 152699442 +156635 LCE4A chr1 152708160 152709491 +156652 C1orf68 chr1 152719522 152720470 +156659 KPRP chr1 152759561 152762052 +156667 LCE1F chr1 152776372 152776728 +156674 LCE1E chr1 152786214 152788426 +156701 LCE1D chr1 152796721 152798181 +156711 LCE1C chr1 152804835 152806628 +156727 LCE1B chr1 152811971 152813108 +156735 LCE1A chr1 152827473 152828097 +156742 LCE6A chr1 152842856 152843983 +156752 AL162596.1 chr1 152859996 152860985 +156762 SMCP chr1 152878322 152885047 +156772 IVL chr1 152908546 152911886 +156782 LINC01527 chr1 152930040 152949210 +156786 SPRR5 chr1 152947154 152949258 +156796 SPRR4 chr1 152970648 152972574 +156806 SPRR1A chr1 152985231 152985500 +156813 SPRR3 chr1 153001747 153003856 +156846 SPRR1B chr1 153031203 153032900 +156856 SPRR2D chr1 153039732 153041931 +156895 SPRR2A chr1 153056120 153057512 +156905 SPRR2B chr1 153070224 153070840 +156913 SPRR2E chr1 153093135 153106184 +156932 SPRR2F chr1 153112121 153113516 +156942 SPRR2G chr1 153149582 153150890 +156952 AL161636.1 chr1 153174518 153191676 +156957 LELP1 chr1 153203430 153205120 +156967 PRR9 chr1 153217584 153219310 +156977 LOR chr1 153259687 153262124 +156987 PGLYRP3 chr1 153297862 153310718 +157007 PGLYRP4 chr1 153330120 153348841 +157058 S100A9 chr1 153357854 153361023 +157070 S100A12 chr1 153373711 153375621 +157082 S100A8 chr1 153390032 153391073 +157108 S100A7A chr1 153416520 153423222 +157140 S100A7L2 chr1 153437058 153439949 +157152 S100A7 chr1 153457744 153460651 +157175 BX470102.1 chr1 153533603 153535115 +157179 S100A6 chr1 153534599 153536244 +157227 S100A5 chr1 153537147 153541765 +157252 S100A4 chr1 153543613 153550136 +157306 S100A3 chr1 153547329 153549258 +157329 S100A2 chr1 153561108 153567890 +157404 BX470102.2 chr1 153586813 153606283 +157408 S100A16 chr1 153606886 153613145 +157457 S100A14 chr1 153614255 153616986 +157520 S100A13 chr1 153618787 153631360 +157578 S100A1 chr1 153627926 153632039 +157626 AL162258.2 chr1 153631438 153634397 +157636 CHTOP chr1 153633982 153646306 +157725 SNAPIN chr1 153658703 153661852 +157750 ILF2 chr1 153661788 153671028 +157855 NPR1 chr1 153678688 153693992 +157915 INTS3 chr1 153728050 153774808 +158261 AL513523.4 chr1 153746851 153751227 +158265 AL513523.3 chr1 153750983 153752176 +158269 SLC27A3 chr1 153774354 153780157 +158402 GATAD2B chr1 153789030 153923360 +158549 AL358472.5 chr1 153923337 153935240 +158558 DENND4B chr1 153929501 153946718 +158714 CRTC2 chr1 153947669 153958615 +158852 SLC39A1 chr1 153959099 153968184 +158983 AL358472.4 chr1 153964361 153965070 +158986 AL358472.3 chr1 153966516 153966930 +158989 CREB3L4 chr1 153967534 153974361 +159162 JTB chr1 153974269 153977674 +159227 AL358472.2 chr1 153977743 153979160 +159230 RAB13 chr1 153981605 153986358 +159292 RPS27 chr1 153990762 153992155 +159333 NUP210L chr1 153992685 154155116 +159537 TPM3 chr1 154155304 154194648 +159948 C1orf189 chr1 154199085 154206333 +159962 C1orf43 chr1 154206696 154220637 +160129 UBAP2L chr1 154220179 154271510 +160610 HAX1 chr1 154272511 154275875 +160746 AQP10 chr1 154321090 154325325 +160784 ATP8B2 chr1 154325553 154351304 +160961 IL6R-AS1 chr1 154402328 154406564 +160965 IL6R chr1 154405193 154469450 +161083 SHE chr1 154469772 154502412 +161117 AL162591.2 chr1 154480012 154481501 +161121 TDRD10 chr1 154502219 154548147 +161205 UBE2Q1 chr1 154548577 154559028 +161269 UBE2Q1-AS1 chr1 154553609 154555017 +161273 AL592078.2 chr1 154564855 154567748 +161283 CHRNB2 chr1 154567778 154580013 +161353 AL592078.1 chr1 154579065 154579663 +161357 ADAR chr1 154582057 154628013 +161784 AL606500.1 chr1 154671593 154678345 +161788 KCNN3 chr1 154697455 154870281 +161879 PMVK chr1 154924740 154936719 +161895 AL451085.1 chr1 154937370 154938059 +161898 PBXIP1 chr1 154944076 154956123 +162007 PYGO2 chr1 154957026 154963853 +162034 AL451085.2 chr1 154961825 154962623 +162037 SHC1 chr1 154962298 154974395 +162263 CKS1B chr1 154974653 154979251 +162310 FLAD1 chr1 154983338 154993111 +162442 LENEP chr1 154993586 154994315 +162459 ZBTB7B chr1 155002630 155018522 +162520 DCST2 chr1 155018520 155033781 +162622 DCST1 chr1 155033824 155050930 +162775 DCST1-AS1 chr1 155045191 155046118 +162779 ADAM15 chr1 155050566 155062775 +163511 EFNA4 chr1 155063737 155069553 +163551 EFNA3 chr1 155078837 155087538 +163576 EFNA1 chr1 155127876 155134899 +163621 SLC50A1 chr1 155135344 155138857 +163799 DPM3 chr1 155139891 155140595 +163825 KRTCAP2 chr1 155169408 155173475 +163889 TRIM46 chr1 155173787 155184971 +164115 MUC1 chr1 155185824 155192916 +164620 AC234582.1 chr1 155195004 155205495 +164649 THBS3 chr1 155195588 155209051 +164921 MTX1 chr1 155208699 155213824 +165024 AC234582.2 chr1 155211151 155213819 +165028 GBA chr1 155234452 155244699 +165193 FAM189B chr1 155247205 155255483 +165346 SCAMP3 chr1 155255979 155262430 +165432 CLK2 chr1 155262868 155278491 +165554 HCN3 chr1 155277463 155289848 +165594 PKLR chr1 155289293 155301438 +165662 FDPS chr1 155308748 155320666 +165934 RUSC1-AS1 chr1 155316863 155324176 +165953 RUSC1 chr1 155320894 155331114 +166217 ASH1L chr1 155335268 155562807 +166382 ASH1L-IT1 chr1 155396010 155396978 +166386 ASH1L-AS1 chr1 155562042 155563944 +166393 AL353807.2 chr1 155609776 155610380 +166397 MSTO1 chr1 155610205 155614967 +166645 AL353807.5 chr1 155626757 155637604 +166650 YY1AP1 chr1 155659443 155689000 +167132 DAP3 chr1 155687960 155739010 +167505 AL162734.1 chr1 155710098 155710563 +167509 GON4L chr1 155749662 155859400 +168024 SYT11 chr1 155859567 155885199 +168038 RIT1 chr1 155897808 155911404 +168160 KHDC4 chr1 155913045 155934413 +168290 RXFP4 chr1 155941710 155942949 +168297 ARHGEF2 chr1 155946851 156007070 +168712 AL355388.2 chr1 155978799 155982986 +168716 AL355388.1 chr1 155991390 156001787 +168720 AL355388.3 chr1 156001953 156033342 +168733 SSR2 chr1 156009048 156020951 +168919 UBQLN4 chr1 156035299 156053798 +168956 LAMTOR2 chr1 156054752 156058510 +169005 RAB25 chr1 156061160 156070504 +169037 MEX3A chr1 156072013 156082465 +169051 LMNA chr1 156082573 156140089 +169383 SEMA4A chr1 156147366 156177752 +169661 SLC25A44 chr1 156193932 156212796 +169698 PMF1 chr1 156212993 156240042 +169782 BGLAP chr1 156242184 156243317 +169799 PAQR6 chr1 156243320 156248117 +170051 SMG5 chr1 156249224 156282825 +170114 TMEM79 chr1 156282935 156293185 +170179 GLMP chr1 156290089 156295689 +170343 VHLL chr1 156298624 156299299 +170351 CCT3 chr1 156308968 156367873 +170642 TSACC chr1 156337314 156346995 +170747 RHBG chr1 156369211 156385219 +170895 AL139130.1 chr1 156388226 156395609 +170899 C1orf61 chr1 156404250 156456763 +171070 MEF2D chr1 156463727 156500779 +171213 AL365181.1 chr1 156509854 156511681 +171216 IQGAP3 chr1 156525405 156572604 +171385 TTC24 chr1 156579727 156586770 +171433 NAXE chr1 156591762 156594299 +171491 GPATCH4 chr1 156594487 156601496 +171651 AL365181.4 chr1 156614742 156615288 +171654 HAPLN2 chr1 156619331 156625725 +171699 AL365181.2 chr1 156637783 156641004 +171702 BCAN chr1 156641390 156659532 +171833 AL365181.3 chr1 156641666 156644887 +171836 AL590666.2 chr1 156646507 156661424 +171840 NES chr1 156668763 156677407 +171854 AL590666.3 chr1 156687695 156691997 +171858 AL590666.4 chr1 156689676 156704757 +171862 CRABP2 chr1 156699606 156705816 +171915 AL590666.1 chr1 156712212 156713174 +171919 ISG20L2 chr1 156721891 156728799 +171957 RRNAD1 chr1 156728442 156736960 +172071 MRPL24 chr1 156737303 156741590 +172145 HDGF chr1 156742109 156766925 +172254 PRCC chr1 156750610 156800815 +172315 AL590666.5 chr1 156768105 156769233 +172319 SH2D2A chr1 156806243 156816862 +172402 NTRK1 chr1 156815640 156881850 +172627 INSRR chr1 156840063 156859117 +172677 PEAR1 chr1 156893698 156916434 +172842 LRRC71 chr1 156920632 156933094 +172904 ARHGEF11 chr1 156934840 157045370 +173115 ETV3L chr1 157092043 157112412 +173182 ETV3 chr1 157121191 157138474 +173215 AL138900.1 chr1 157232231 157237136 +173219 LINC02772 chr1 157273760 157283968 +173233 FCRL5 chr1 157513377 157552515 +173351 FCRL4 chr1 157573747 157598085 +173397 FCRL3 chr1 157674321 157700769 +173649 AL356276.1 chr1 157691762 157696459 +173653 FCRL2 chr1 157745733 157777132 +173726 FCRL1 chr1 157794403 157820120 +173841 CD5L chr1 157830911 157898256 +173864 KIRREL1 chr1 157993273 158100262 +173989 KIRREL1-IT1 chr1 158025550 158031166 +173993 AL138899.3 chr1 158127287 158128301 +174001 LINC01704 chr1 158131983 158149810 +174047 CD1D chr1 158179947 158184896 +174067 AL138899.1 chr1 158197922 158203877 +174071 CD1A chr1 158254424 158258269 +174089 CD1C chr1 158289923 158294774 +174118 CD1B chr1 158327951 158331531 +174149 CD1E chr1 158353696 158357553 +174349 OR10T2 chr1 158398522 158399466 +174356 OR10K2 chr1 158418210 158426237 +174372 OR10K1 chr1 158461574 158470857 +174419 OR10R2 chr1 158472220 158480936 +174441 AL365440.2 chr1 158474454 158494886 +174450 OR6Y1 chr1 158544550 158554405 +174475 OR6P1 chr1 158560606 158570580 +174493 OR10X1 chr1 158578919 158579899 +174500 OR10Z1 chr1 158605268 158612514 +174516 SPTA1 chr1 158610704 158686715 +174660 OR6K2 chr1 158699678 158700652 +174667 OR6K3 chr1 158716327 158720720 +174683 OR6N1 chr1 158747814 158772195 +174703 OR6K6 chr1 158754720 158755891 +174718 OR6N2 chr1 158774222 158781204 +174734 MNDA chr1 158831351 158849506 +174766 PYHIN1 chr1 158930796 158977059 +174887 IFI16 chr1 158999968 159055155 +175131 AIM2 chr1 159062484 159147096 +175172 CADM3 chr1 159171609 159203313 +175238 CADM3-AS1 chr1 159194325 159207973 +175247 ACKR1 chr1 159203307 159206500 +175279 FCER1A chr1 159289714 159308224 +175312 AL513323.1 chr1 159346166 159469068 +175318 OR10J1 chr1 159437845 159443078 +175342 LINC02819 chr1 159466321 159483376 +175347 OR10J5 chr1 159535078 159536007 +175354 APCS chr1 159587826 159588865 +175364 CRP chr1 159712289 159714589 +175430 DUSP23 chr1 159780932 159782543 +175462 FCRL6 chr1 159800511 159816257 +175585 SLAMF8 chr1 159826811 159837492 +175624 AL590560.2 chr1 159834474 159873053 +175680 SNHG28 chr1 159834495 159855237 +175698 VSIG8 chr1 159854316 159862657 +175718 AL590560.3 chr1 159854870 159867685 +175724 CFAP45 chr1 159872364 159900165 +175836 AL590560.5 chr1 159900475 159903431 +175840 TAGLN2 chr1 159918107 159925732 +175904 IGSF9 chr1 159927039 159945613 +176074 SLAMF9 chr1 159951492 159954237 +176107 LINC01133 chr1 159958035 159984750 +176126 KCNJ10 chr1 159998651 160070160 +176210 PIGM chr1 160024953 160031990 +176218 AL121987.1 chr1 160062461 160080769 +176229 KCNJ9 chr1 160081538 160090563 +176241 IGSF8 chr1 160091340 160098943 +176315 ATP1A2 chr1 160115759 160143591 +176490 ATP1A4 chr1 160151570 160186977 +176637 CASQ1 chr1 160190575 160201886 +176689 AL121987.2 chr1 160202199 160208869 +176696 PEA15 chr1 160205337 160215376 +176745 DCAF8 chr1 160215715 160262531 +177006 AL139011.1 chr1 160261741 160263328 +177016 PEX19 chr1 160276812 160286348 +177153 COPA chr1 160288594 160343273 +178021 NCSTN chr1 160343316 160358952 +178252 NHLH1 chr1 160367071 160372846 +178262 VANGL2 chr1 160400564 160428670 +178288 SLAMF6 chr1 160485030 160523262 +178350 AL138930.1 chr1 160537073 160571458 +178354 CD84 chr1 160541095 160579516 +178463 SLAMF1 chr1 160608106 160647295 +178518 AL121985.1 chr1 160670778 160699761 +178577 CD48 chr1 160678746 160711831 +178611 SLAMF7 chr1 160739057 160754821 +178754 LY9 chr1 160796074 160828261 +178891 CD244 chr1 160830160 160862887 +178987 ITLN1 chr1 160876540 160885180 +179016 AL354714.3 chr1 160931739 160934380 +179020 AL354714.1 chr1 160932465 160949922 +179028 ITLN2 chr1 160945025 160954809 +179058 F11R chr1 160995211 161021343 +179150 TSTD1 chr1 161037631 161038977 +179216 USF1 chr1 161039251 161045977 +179402 ARHGAP30 chr1 161046946 161069970 +179550 NECTIN4 chr1 161070998 161089558 +179578 AL591806.1 chr1 161084465 161087571 +179583 KLHDC9 chr1 161098361 161100346 +179636 PFDN2 chr1 161100556 161118055 +179653 NIT1 chr1 161118086 161125445 +179791 DEDD chr1 161120974 161132688 +179927 UFC1 chr1 161152776 161158856 +179971 AL590714.1 chr1 161153760 161159349 +179975 USP21 chr1 161159450 161165723 +180147 PPOX chr1 161166056 161178013 +180580 B4GALT3 chr1 161171310 161177968 +180694 ADAMTS4 chr1 161184302 161199054 +180730 NDUFS2 chr1 161197104 161214395 +180883 FCER1G chr1 161215234 161220699 +180919 APOA2 chr1 161222292 161223631 +181028 TOMM40L chr1 161225939 161230746 +181140 NR1I3 chr1 161229666 161238302 +181742 PCP4L1 chr1 161258745 161285450 +181754 MPZ chr1 161304735 161309972 +181857 SDHC chr1 161314257 161375340 +181972 CFAP126 chr1 161364731 161367874 +181988 AL592295.4 chr1 161399409 161422424 +181992 AL592295.5 chr1 161399998 161401868 +181995 AL592295.3 chr1 161403409 161470523 +182002 AL831711.1 chr1 161433444 161440996 +182006 FCGR2A chr1 161505430 161524013 +182130 HSPA6 chr1 161524540 161526894 +182138 FCGR3A chr1 161541759 161550737 +182232 AL590385.1 chr1 161556290 161557078 +182236 FCGR3B chr1 161623196 161631963 +182343 FCGR2B chr1 161663147 161678654 +182415 AL451067.1 chr1 161671978 161674824 +182423 FCRLA chr1 161706972 161714352 +182586 FCRLB chr1 161721563 161728143 +182675 DUSP12 chr1 161749758 161757238 +182737 AL359541.1 chr1 161765325 161766227 +182741 ATF6 chr1 161766320 161964070 +182785 OLFML2B chr1 161983192 162023854 +182851 AL590408.1 chr1 162039016 162039567 +182855 NOS1AP chr1 162069691 162370475 +182954 AL450163.1 chr1 162146709 162175243 +182964 AL512785.1 chr1 162316852 162317794 +182968 SPATA46 chr1 162373203 162376854 +182989 C1orf226 chr1 162378841 162386812 +183010 SH2D1B chr1 162395268 162412138 +183027 UHMK1 chr1 162497251 162529631 +183096 AL596325.1 chr1 162560227 162561308 +183099 UAP1 chr1 162561506 162599842 +183211 AL596325.2 chr1 162593103 162593754 +183215 DDR2 chr1 162631373 162787405 +183396 HSD17B7 chr1 162790702 162812817 +183509 CCDC190 chr1 162824458 162868815 +183555 RGS4 chr1 163068775 163076802 +183675 RGS5 chr1 163111121 163321791 +183796 AL499616.1 chr1 163161675 163213023 +183802 AL592435.1 chr1 163244505 163321894 +183846 AL592435.2 chr1 163259850 163260659 +183850 NUF2 chr1 163266576 163355764 +184059 PBX1 chr1 164555584 164899296 +184315 AL391001.1 chr1 164680085 164680799 +184318 AL357568.1 chr1 164769116 164774641 +184324 AL357568.2 chr1 164828436 164829952 +184327 LMX1A chr1 165201867 165356715 +184403 AL390730.1 chr1 165210627 165213090 +184408 AL390730.2 chr1 165215951 165219104 +184418 RXRG chr1 165400922 165445355 +184480 LRRC52-AS1 chr1 165476838 165582155 +184544 LRRC52 chr1 165544007 165563961 +184554 AL356441.1 chr1 165598356 165624084 +184572 MGST3 chr1 165631213 165661796 +184710 ALDH9A1 chr1 165662216 165698863 +184756 AL451074.5 chr1 165706556 165707284 +184759 TMCO1 chr1 165724293 165827755 +184922 TMCO1-AS1 chr1 165768929 165775176 +184926 UCK2 chr1 165827614 165911618 +185020 AL358115.1 chr1 165889725 165900995 +185028 FAM78B chr1 166057426 166166969 +185078 AL626787.1 chr1 166081183 166087483 +185083 AL596087.3 chr1 166147782 166165095 +185087 AL596087.2 chr1 166165911 166339090 +185096 AL583804.1 chr1 166387727 166452632 +185101 LINC01675 chr1 166474879 166490307 +185111 POGK chr1 166839447 166856344 +185157 TADA1 chr1 166856510 166876264 +185184 ILDR2 chr1 166895711 166975540 +185339 MAEL chr1 166975582 167022214 +185464 AL158837.1 chr1 167052551 167058542 +185468 GPA33 chr1 167052836 167166479 +185522 DUSP27 chr1 167094075 167129165 +185574 LINC01363 chr1 167175363 167195792 +185595 AL451050.2 chr1 167219831 167220512 +185598 POU2F1 chr1 167220876 167427345 +185968 AL136984.1 chr1 167379108 167381000 +185971 CD247 chr1 167430640 167518610 +186044 AL359962.3 chr1 167455195 167458646 +186048 AL359962.1 chr1 167457383 167458661 +186052 AL359962.2 chr1 167457742 167459891 +186056 CREG1 chr1 167529117 167553805 +186085 AL031733.2 chr1 167627385 167630674 +186089 RCSD1 chr1 167630093 167708696 +186153 MPZL1 chr1 167721192 167791919 +186247 ADCY10 chr1 167809386 167914215 +186497 Z99943.1 chr1 167820406 167821224 +186501 MPC2 chr1 167916675 167937072 +186547 DCAF6 chr1 167935783 168075843 +186803 GPR161 chr1 168079543 168137667 +186938 TIPRL chr1 168178962 168202109 +186973 SFT2D2 chr1 168225938 168253021 +187039 TBX19 chr1 168280877 168314426 +187092 AL023755.1 chr1 168400829 168495685 +187141 AL022100.2 chr1 168401483 168407274 +187146 XCL2 chr1 168540768 168543997 +187158 XCL1 chr1 168576605 168582069 +187170 DPT chr1 168695468 168729206 +187184 AL031275.1 chr1 168763365 168774490 +187188 LINC00626 chr1 168784012 168792886 +187215 AL135926.2 chr1 168898633 168902836 +187219 LINC00970 chr1 168903905 169087005 +187226 AL031726.2 chr1 169059576 169062441 +187230 AL031726.1 chr1 169104124 169104907 +187234 ATP1B1 chr1 169105697 169132722 +187282 NME7 chr1 169132531 169367948 +187462 Z99758.1 chr1 169310665 169322479 +187466 BLZF1 chr1 169367970 169396540 +187540 CCDC181 chr1 169394870 169460669 +187627 SLC19A2 chr1 169463909 169485944 +187680 Z99572.1 chr1 169486076 169500182 +187683 F5 chr1 169511953 169586588 +187797 SELP chr1 169588849 169630193 +187996 C1orf112 chr1 169662007 169854080 +188311 SELL chr1 169690665 169711702 +188389 SELE chr1 169722640 169764705 +188545 AL021940.1 chr1 169762929 169764648 +188549 METTL18 chr1 169792529 169794963 +188575 SCYL3 chr1 169849631 169894267 +188710 KIFAP3 chr1 169921326 170085208 +188901 AL356475.1 chr1 170024077 170024683 +188905 METTL11B chr1 170146001 170167790 +188925 LINC01681 chr1 170173865 170304358 +188997 LINC01142 chr1 170271395 170284277 +189007 GORAB-AS1 chr1 170460453 170532647 +189028 GORAB chr1 170532129 170553446 +189085 AL162399.1 chr1 170587249 170588236 +189089 AL023495.1 chr1 170598854 170647339 +189094 PRRX1 chr1 170662728 170739421 +189153 Z97200.1 chr1 170667381 170669425 +189156 BX284613.2 chr1 170748573 171251857 +189183 MROH9 chr1 170935471 171064765 +189283 FMO3 chr1 171090901 171117819 +189349 FMO2 chr1 171185249 171212686 +189415 AL021026.1 chr1 171199244 171227788 +189427 FMO1 chr1 171248471 171285978 +189552 FMO4 chr1 171314183 171342084 +189598 PRRC2C chr1 171485551 171593511 +190005 MYOCOS chr1 171600621 171638799 +190056 MYOC chr1 171635417 171652688 +190081 VAMP4 chr1 171700160 171742074 +190156 EEF1AKNMT chr1 171781660 171814023 +190236 DNM3 chr1 171841498 172418466 +190493 DNM3-IT1 chr1 171864187 171864687 +190497 DNM3OS chr1 172138397 172144840 +190525 AL137157.1 chr1 172210711 172213499 +190529 PIGC chr1 172370189 172444086 +190570 C1orf105 chr1 172420685 172468831 +190638 SUCO chr1 172532349 172611833 +190913 FASLG chr1 172659103 172666876 +190938 AL031599.1 chr1 172775905 173064015 +190945 Z97198.1 chr1 172906900 172907684 +190949 TNFSF18 chr1 173039960 173050963 +190961 AL022310.1 chr1 173174300 173175503 +190965 TNFSF4 chr1 173183731 173207331 +190991 AL645568.1 chr1 173417793 173489407 +191025 PRDX6 chr1 173477330 173488815 +191049 SLC9C2 chr1 173500460 173603072 +191153 AL139142.1 chr1 173555251 173612772 +191158 ANKRD45 chr1 173608336 173669851 +191179 TEX50 chr1 173635338 173637130 +191189 KLHL20 chr1 173714941 173786692 +191235 CENPL chr1 173799550 173824720 +191317 DARS2 chr1 173824653 173858808 +191704 GAS5 chr1 173858559 173868882 +191974 GAS5-AS1 chr1 173862473 173863941 +191978 ZBTB37 chr1 173868082 173903549 +192033 SERPINC1 chr1 173903804 173917378 +192078 RC3H1 chr1 173931214 174022297 +192219 RC3H1-IT1 chr1 174009267 174016206 +192223 LINC02776 chr1 174022509 174022985 +192227 RABGAP1L-DT chr1 174110268 174160165 +192258 RABGAP1L chr1 174159410 174995308 +192679 GPR52 chr1 174447964 174449545 +192687 RABGAP1L-IT1 chr1 174896958 174897996 +192691 Z99127.1 chr1 174934947 174954261 +192703 Z99127.4 chr1 174998353 174999623 +192706 CACYBP chr1 174999163 175012027 +192792 MRPS14 chr1 175010789 175023425 +192819 TNN chr1 175067833 175148075 +192938 KIAA0040 chr1 175156986 175192999 +192997 AL008626.1 chr1 175203228 175204849 +193001 Z94057.1 chr1 175307218 175335459 +193008 TNR chr1 175315194 175743616 +193122 TNR-IT1 chr1 175538775 175556818 +193126 LINC01657 chr1 175877343 175880468 +193131 LINC02803 chr1 175904762 175921057 +193136 COP1 chr1 175944831 176207286 +193443 AL590723.1 chr1 176017277 176018760 +193447 AL591043.2 chr1 176207648 176447919 +193466 PAPPA2 chr1 176463171 176845601 +193544 AL031290.1 chr1 176829128 176831841 +193548 ASTN1 chr1 176857302 177164973 +193725 BRINP2 chr1 177170958 177282422 +193756 LINC01645 chr1 177351562 177437880 +193772 AL136114.1 chr1 177392667 177920152 +193838 LINC01741 chr1 177700524 177712275 +193852 SEC16B chr1 177923956 177984303 +194042 RASAL2-AS1 chr1 178090677 178093984 +194055 RASAL2 chr1 178094141 178484147 +194165 CLEC20A chr1 178479247 178499634 +194213 AL513013.1 chr1 178511563 178513051 +194217 TEX35 chr1 178513109 178548602 +194365 C1orf220 chr1 178542752 178548889 +194374 AL137796.1 chr1 178651706 178652282 +194377 AL449106.1 chr1 178724306 178726285 +194380 RALGPS2 chr1 178725147 178921841 +194544 ANGPTL1 chr1 178849535 178871077 +194584 FAM20B chr1 179025804 179076567 +194615 TOR3A chr1 179082070 179098023 +194690 ABL2 chr1 179099330 179229684 +194957 SOAT1 chr1 179293714 179358680 +195082 AXDND1 chr1 179365720 179554735 +195382 AL160286.3 chr1 179543201 179548922 +195386 NPHS2 chr1 179550539 179575952 +195427 AL160286.2 chr1 179590372 179591305 +195430 TDRD5 chr1 179591613 179691272 +195571 AL359853.2 chr1 179730191 179742697 +195581 FAM163A chr1 179743163 179816198 +195597 AL359853.1 chr1 179816184 179818191 +195604 LINC02818 chr1 179829609 179836124 +195608 TOR1AIP2 chr1 179839967 179877803 +195670 AL353708.3 chr1 179881607 179882595 +195673 TOR1AIP1 chr1 179882042 179925000 +195874 AL353708.2 chr1 179926641 179941796 +195879 AL353708.1 chr1 179953184 179954440 +195882 CEP350 chr1 179954773 180114875 +196082 AL390718.1 chr1 180117140 180123890 +196087 QSOX1 chr1 180154869 180204030 +196176 LHX4 chr1 180230264 180278984 +196208 ACBD6 chr1 180269653 180502954 +196326 OVAAL chr1 180547436 180566520 +196348 XPR1 chr1 180632022 180890279 +196428 LINC02816 chr1 180906651 180909166 +196439 KIAA1614 chr1 180912897 180951614 +196505 AL162431.1 chr1 180944042 180976482 +196509 KIAA1614-AS1 chr1 180949699 180954887 +196513 STX6 chr1 180972712 181023121 +196559 MR1 chr1 181033425 181061938 +196674 IER5 chr1 181088700 181092900 +196682 LINC01732 chr1 181174484 181182208 +196691 AL358393.1 chr1 181190471 181191149 +196695 LINC01699 chr1 181236388 181238604 +196700 CACNA1E chr1 181317690 181808084 +197537 AL161734.2 chr1 181808927 181998985 +197544 AL161734.1 chr1 181812705 181813261 +197547 ZNF648 chr1 182054570 182061712 +197557 AL355482.1 chr1 182062677 182069253 +197562 AL355482.2 chr1 182086551 182090112 +197567 LINC01344 chr1 182096338 182314061 +197611 AL390856.1 chr1 182127297 182128682 +197619 GLUL chr1 182381704 182392206 +197759 TEDDM1 chr1 182398117 182400667 +197767 LINC00272 chr1 182407621 182414815 +197777 RGSL1 chr1 182409192 182560599 +198146 RNASEL chr1 182573634 182589256 +198183 RGS16 chr1 182598623 182604389 +198199 LINC01686 chr1 182615254 182616629 +198202 RGS8 chr1 182641816 182684576 +198301 LINC01688 chr1 182712862 182714544 +198305 NPL chr1 182789293 182830384 +198518 AL355999.1 chr1 182837185 182839561 +198522 DHX9 chr1 182839347 182887982 +198627 SHCBP1L chr1 182899865 182953525 +198685 LAMC1 chr1 183023420 183145592 +198780 LAMC1-AS1 chr1 183138402 183141282 +198785 LAMC2 chr1 183186238 183245127 +198893 NMNAT2 chr1 183248237 183418380 +198959 AL354953.1 chr1 183252263 183258968 +198963 AL449223.1 chr1 183372870 183374556 +198967 SMG7-AS1 chr1 183460874 183472265 +198989 SMG7 chr1 183472216 183598246 +199375 NCF2 chr1 183555563 183590876 +199546 AL137800.1 chr1 183613537 183619335 +199551 ARPC5 chr1 183620846 183635783 +199597 RGL1 chr1 183636085 183928531 +199682 APOBEC4 chr1 183646275 183653316 +199695 AL590422.1 chr1 183754418 183754937 +199700 COLGALT2 chr1 183929854 184037729 +199794 TSEN15 chr1 184051651 184123978 +200046 AL158011.1 chr1 184080657 184149652 +200050 AL445228.1 chr1 184329071 184332826 +200054 AL445228.2 chr1 184385753 184386704 +200057 C1orf21 chr1 184387029 184629019 +200109 AL078645.1 chr1 184408337 184412360 +200113 AL713852.1 chr1 184607599 184672166 +200137 AL713852.2 chr1 184664282 184668535 +200141 EDEM3 chr1 184690237 184754907 +200273 NIBAN1 chr1 184790724 184974508 +200335 LINC01633 chr1 184999710 185008789 +200340 RNF2 chr1 185045526 185102603 +200394 TRMT1L chr1 185118101 185157072 +200451 SWT1 chr1 185157080 185291781 +200551 IVNS1ABP chr1 185296388 185317273 +200655 AL078644.2 chr1 185317779 185318530 +200658 LINC01350 chr1 185558371 185628944 +200778 AL133383.1 chr1 185646463 185657168 +200790 HMCN1 chr1 185734391 186190949 +201046 AL133553.1 chr1 186176814 186177302 +201050 AL133553.2 chr1 186224472 186228191 +201054 PRG4 chr1 186296279 186314562 +201195 TPR chr1 186311652 186375693 +201398 ODR4 chr1 186375838 186421378 +201502 OCLM chr1 186401046 186401180 +201509 AL096803.2 chr1 186423481 186626619 +201552 PDC chr1 186443566 186461114 +201577 AL096803.4 chr1 186521773 186522304 +201580 PTGS2 chr1 186671791 186680423 +201648 PACERR chr1 186680622 186681446 +201651 PLA2G4A chr1 186828949 186988981 +201701 ERVMER61-1 chr1 187070700 187686628 +201794 AL136372.2 chr1 188013642 188144768 +201800 AL596211.1 chr1 188218400 188220676 +201803 AL929288.1 chr1 188508538 188536465 +201809 AL691515.1 chr1 188705623 188732208 +201814 AL691515.2 chr1 188869474 188888540 +201829 LINC01035 chr1 188905688 189037564 +201837 LINC01701 chr1 189775465 189814918 +201843 AL591504.1 chr1 189868001 189868528 +201847 AL591504.2 chr1 189868381 189876160 +201851 BRINP3 chr1 190097658 190478404 +201897 AL354771.1 chr1 190264898 190362270 +201904 LINC01351 chr1 190478551 190480735 +201911 AL391645.1 chr1 190480379 190494297 +201915 LINC01720 chr1 190624890 190801658 +201922 AL138927.1 chr1 190878145 191151410 +201930 AL713866.1 chr1 191151510 191154634 +201933 LINC01680 chr1 191221159 191228467 +201937 LINC02770 chr1 191823432 192011260 +201951 AL359081.1 chr1 191858707 191890229 +201958 RGS18 chr1 192158462 192185815 +201991 AL390957.1 chr1 192167786 192957713 +202094 RGS21 chr1 192316992 192367285 +202110 AL136987.1 chr1 192517190 192538102 +202119 RGS1 chr1 192575763 192580024 +202162 RGS13 chr1 192636138 192660306 +202209 AL136454.1 chr1 192716132 192716653 +202221 RGS2 chr1 192809039 192812275 +202250 UCHL5 chr1 193012250 193060080 +202513 RO60 chr1 193059422 193091777 +202715 GLRX2 chr1 193090866 193106114 +202762 CDC73 chr1 193121958 193254815 +203053 B3GALT2 chr1 193178730 193186613 +203063 LINC01031 chr1 193304745 193365953 +203088 AL138778.1 chr1 193457422 193465198 +203098 AL136456.1 chr1 193473224 194198708 +203116 AL357793.1 chr1 193678894 193727035 +203121 AL357793.2 chr1 193684246 193688429 +203126 AL513348.1 chr1 194350943 194352426 +203130 AL353072.2 chr1 194785517 194931310 +203140 AL353709.1 chr1 195747024 195763501 +203179 LINC01724 chr1 196044883 196065235 +203185 KCNT2 chr1 196225779 196609225 +203547 CFH chr1 196651878 196747504 +203669 CFHR3 chr1 196774795 196795406 +203754 CFHR1 chr1 196819757 196832189 +203797 CFHR4 chr1 196888014 196918713 +203887 CFHR2 chr1 196943738 196959622 +203995 CFHR5 chr1 196977556 197009674 +204021 F13B chr1 197038741 197067267 +204068 ASPM chr1 197084127 197146694 +204240 ZBTB41 chr1 197153680 197200542 +204278 CRB1 chr1 197268204 197478455 +204480 AL136322.1 chr1 197437976 197447469 +204486 DENND1B chr1 197504748 197775696 +204705 AL365258.1 chr1 197757319 197761965 +204709 C1orf53 chr1 197902630 197907367 +204734 LHX9 chr1 197911902 197935478 +204834 NEK7 chr1 198156994 198322420 +204940 AL450352.1 chr1 198450666 198519877 +204944 ATP6V1G3 chr1 198523222 198540945 +204997 AL157402.1 chr1 198597724 198598868 +205001 PTPRC chr1 198638457 198757476 +205384 AL157402.2 chr1 198657553 198667061 +205389 MIR181A1HG chr1 198777861 198937471 +205411 AC096631.1 chr1 198973379 198985506 +205430 LINC01222 chr1 199006040 199021037 +205435 LINC01221 chr1 199016133 199076735 +205440 AC105941.1 chr1 199040501 199080975 +205444 LINC02789 chr1 199148598 199393307 +205450 NR5A2 chr1 200027614 200177420 +205539 LINC00862 chr1 200253419 200400705 +205583 AC097065.2 chr1 200315435 200315967 +205586 AC104461.1 chr1 200333193 200478669 +205633 ZNF281 chr1 200404940 200410056 +205663 AL359834.1 chr1 200478020 200483604 +205667 KIF14 chr1 200551497 200620751 +205795 DDX59 chr1 200623896 200669907 +205900 DDX59-AS1 chr1 200669507 200694250 +205905 CAMSAP2 chr1 200739558 200860704 +206050 GPR25 chr1 200872981 200874178 +206058 INAVA chr1 200891048 200915742 +206147 KIF21B chr1 200969390 201023700 +206450 AL358473.1 chr1 201023949 201028792 +206457 AL358473.2 chr1 201031136 201043073 +206467 CACNA1S chr1 201039512 201112451 +206652 ASCL5 chr1 201113953 201127184 +206668 TMEM9 chr1 201134772 201171574 +206820 IGFN1 chr1 201190825 201228952 +207031 AC103925.1 chr1 201222113 201223123 +207035 PKP1 chr1 201283452 201332993 +207145 TNNT2 chr1 201359008 201377764 +207928 LAD1 chr1 201380833 201399915 +208012 AC119427.1 chr1 201399633 201401190 +208016 TNNI1 chr1 201403768 201429866 +208170 PHLDA3 chr1 201464278 201469237 +208198 AC096677.2 chr1 201464383 201465146 +208202 CSRP1 chr1 201483530 201509456 +208387 AC096677.1 chr1 201507241 201534784 +208391 NAV1 chr1 201622885 201826969 +208670 AC092800.1 chr1 201673105 201674144 +208674 IPO9-AS1 chr1 201688259 201829559 +208687 AL645504.1 chr1 201723294 201737506 +208691 IPO9 chr1 201829149 201884291 +208769 SHISA4 chr1 201888680 201892306 +208794 AL513217.1 chr1 201893842 201899978 +208803 LMOD1 chr1 201896456 201946588 +208828 TIMM17A chr1 201955503 201970664 +208862 RNPEP chr1 201982372 202006147 +209022 ELF3-AS1 chr1 201995696 202010463 +209029 ELF3 chr1 202007945 202017183 +209137 AL691482.3 chr1 202011370 202015657 +209141 GPR37L1 chr1 202122917 202133592 +209151 ARL8A chr1 202133404 202144743 +209197 PTPN7 chr1 202147013 202161588 +209490 LGR6 chr1 202193901 202319781 +209689 UBE2T chr1 202331657 202341980 +209748 PPP1R12B chr1 202348699 202592706 +210078 SYT2 chr1 202590596 202710454 +210125 AC104463.2 chr1 202604268 202605293 +210129 AC104463.1 chr1 202632428 202632911 +210133 KDM5B chr1 202724495 202809470 +211040 AC098934.4 chr1 202810238 202810829 +211043 PCAT6 chr1 202810954 202812156 +211056 RABIF chr1 202878282 202889149 +211066 KLHL12 chr1 202891116 202928636 +211128 ADIPOR1 chr1 202940826 202958572 +211205 CYB5R1 chr1 202961873 202967275 +211269 TMEM183A chr1 203007374 203024848 +211310 PPFIA4 chr1 203026498 203078740 +211681 MYOG chr1 203083129 203086012 +211693 ADORA1 chr1 203090654 203167405 +211773 AC105940.2 chr1 203115468 203128367 +211781 AC105940.1 chr1 203144694 203152579 +211787 MYBPH chr1 203167811 203175826 +211846 CHI3L1 chr1 203178931 203186704 +211893 CHIT1 chr1 203212827 203273641 +212038 LINC01353 chr1 203273221 203288804 +212061 LINC01136 chr1 203298758 203305309 +212074 BTG2 chr1 203305491 203309602 +212095 FMOD chr1 203340628 203351758 +212125 PRELP chr1 203475806 203491352 +212137 OPTC chr1 203494153 203508949 +212170 ATP2B4 chr1 203626561 203744081 +212346 LAX1 chr1 203765177 203776372 +212383 ZC3H11A chr1 203795654 203854999 +212763 ZBED6 chr1 203795714 203854999 +212842 SNRPE chr1 203861599 203871152 +212889 AC096645.1 chr1 203996532 204008357 +212894 LINC00303 chr1 204032447 204041265 +212917 AL592146.2 chr1 204064533 204073965 +212921 SOX13 chr1 204073115 204127743 +213052 AL592146.1 chr1 204131062 204131966 +213056 ETNK2 chr1 204131062 204152044 +213182 ERLNC1 chr1 204141404 204143327 +213196 REN chr1 204154819 204190324 +213251 KISS1 chr1 204190341 204196491 +213273 GOLT1A chr1 204198163 204213988 +213292 PLEKHA6 chr1 204218853 204377665 +213488 AL592114.3 chr1 204276901 204280363 +213499 LINC00628 chr1 204368431 204369719 +213502 AL606489.1 chr1 204377850 204435846 +213507 PPP1R15B chr1 204403381 204411817 +213517 PIK3C2B chr1 204422628 204494724 +213700 MDM4 chr1 204516379 204558120 +213967 AL512306.3 chr1 204603035 204616565 +213972 LRRN2 chr1 204617170 204685738 +214004 AL512306.2 chr1 204626775 204629712 +214008 AL161793.1 chr1 204663872 204664613 +214012 AC096675.1 chr1 204822664 204829274 +214017 NFASC chr1 204828651 205022822 +214787 CNTN2 chr1 205042937 205078289 +215457 TMEM81 chr1 205083129 205084460 +215465 RBBP5 chr1 205086142 205122015 +215536 DSTYK chr1 205142505 205211702 +215614 TMCC2 chr1 205227946 205285632 +215708 AC093422.2 chr1 205233821 205236867 +215712 NUAK2 chr1 205302063 205321760 +215750 KLHDC8A chr1 205336065 205357090 +215892 LEMD1-AS1 chr1 205373252 205387440 +215898 LEMD1 chr1 205381378 205455954 +215993 BLACAT1 chr1 205434885 205457091 +216020 LEMD1-DT chr1 205455929 205469024 +216025 CDK18 chr1 205504595 205532793 +216363 MFSD4A chr1 205568885 205602918 +216507 ELK4 chr1 205597556 205631962 +216572 SLC45A3 chr1 205657851 205680509 +216592 NUCKS1 chr1 205712822 205750182 +216615 RAB29 chr1 205767986 205775482 +216717 AC119673.1 chr1 205775559 205783623 +216722 SLC41A1 chr1 205789094 205813748 +216768 AC119673.2 chr1 205813322 205896082 +216892 PM20D1 chr1 205828025 205850132 +216945 SLC26A9 chr1 205913048 205943460 +217114 AL713965.1 chr1 205935128 205935768 +217118 RAB7B chr1 205976740 206003461 +217192 CTSE chr1 206009264 206023895 +217244 RHEX chr1 206053173 206102449 +217312 AVPR1B chr1 206106936 206117699 +217325 AC244035.1 chr1 206117783 206126805 +217330 AC244035.4 chr1 206147164 206166149 +217334 AC244035.2 chr1 206175060 206177246 +217338 FAM72A chr1 206186179 206204414 +217417 SRGAP2 chr1 206203345 206464443 +217683 IKBKE chr1 206470476 206496889 +217864 C1orf147 chr1 206491116 206497728 +217868 AC244034.2 chr1 206503948 206504456 +217871 RASSF5 chr1 206507531 206589448 +217967 EIF2D chr1 206571292 206612465 +218119 AL591846.2 chr1 206634196 206635714 +218130 DYRK3 chr1 206635536 206684419 +218199 MAPKAPK2 chr1 206684944 206734283 +218256 IL10 chr1 206767602 206774541 +218341 IL19 chr1 206770764 206842981 +218441 IL20 chr1 206865354 206869223 +218487 IL24 chr1 206897443 206904139 +218589 FCMR chr1 206903317 206923247 +218711 PIGR chr1 206928522 206946466 +218745 FCAMR chr1 206957965 206970625 +218833 C1orf116 chr1 207018522 207032756 +218858 PFKFB2 chr1 207034366 207081024 +219033 YOD1 chr1 207043849 207052980 +219056 C4BPB chr1 207088860 207099993 +219156 C4BPA chr1 207104233 207144972 +219214 AL445493.3 chr1 207127010 207127486 +219217 AL445493.2 chr1 207179296 207184062 +219223 AL596218.1 chr1 207240122 207309292 +219234 CD55 chr1 207321376 207386804 +219506 AL391597.1 chr1 207401691 207416236 +219511 CR2 chr1 207454230 207489895 +219660 CR1 chr1 207496147 207641765 +220225 AL137789.1 chr1 207551925 207606555 +220245 CR1L chr1 207645113 207738416 +220319 AL137789.2 chr1 207709024 207711508 +220324 CD46 chr1 207752057 207795513 +220669 MIR29B2CHG chr1 207801518 207879115 +220710 CD34 chr1 207880972 207911402 +220775 AL356275.1 chr1 207909992 207917088 +220786 LINC02767 chr1 207959292 207969329 +220793 PLXNA2 chr1 208022242 208244384 +220880 AL590138.1 chr1 208106102 208107655 +220884 AL606753.2 chr1 208266059 208270667 +220888 LINC01735 chr1 208606564 208614295 +220893 LINC02769 chr1 208626741 208628085 +220897 LINC01717 chr1 208728665 208736286 +220925 LINC01774 chr1 208972454 208975307 +220929 AC092810.4 chr1 209107503 209114419 +220934 AC092810.3 chr1 209147220 209266758 +221007 LINC01696 chr1 209325392 209328535 +221019 LINC01698 chr1 209367662 209380518 +221037 MIR205HG chr1 209428817 209432838 +221109 AL023754.1 chr1 209528455 209567673 +221125 AL023754.2 chr1 209531236 209536351 +221129 CAMK1G chr1 209583714 209613939 +221250 LAMB3 chr1 209614870 209652425 +221428 HSD11B1-AS1 chr1 209661364 209724125 +221437 G0S2 chr1 209675412 209676390 +221447 HSD11B1 chr1 209686178 209734949 +221516 TRAF3IP3 chr1 209756032 209782320 +221798 C1orf74 chr1 209779208 209784559 +221808 IRF6 chr1 209785617 209806175 +221892 UTP25 chr1 209827972 209857565 +221931 SYT14 chr1 209900923 210171389 +222135 AL022397.1 chr1 209987333 209997092 +222139 SERTAD4-AS1 chr1 210231456 210234047 +222149 SERTAD4 chr1 210232796 210246631 +222177 HHAT chr1 210328252 210676296 +222387 AL034351.4 chr1 210362861 210366948 +222391 AL034351.3 chr1 210386657 210394112 +222397 KCNH1 chr1 210676823 211134165 +222721 AC092017.4 chr1 211108445 211207138 +222738 KCNH1-IT1 chr1 211132588 211133374 +222742 RCOR3 chr1 211258377 211316385 +222986 TRAF5 chr1 211326615 211374946 +223090 AL590101.1 chr1 211376834 211382717 +223094 LINC00467 chr1 211382736 211435570 +223290 RD3 chr1 211476522 211492917 +223305 AC105275.1 chr1 211492255 211492917 +223309 SLC30A1 chr1 211571568 211579161 +223319 AC105275.2 chr1 211583015 211583725 +223322 AL356310.1 chr1 211635865 211644114 +223327 LINC01693 chr1 211639440 211654627 +223374 NEK2 chr1 211658657 211675630 +223446 AC096637.2 chr1 211675749 211690103 +223466 AC096637.1 chr1 211715928 211725402 +223470 LPGAT1 chr1 211743457 211830763 +223520 LPGAT1-AS1 chr1 211829636 211853703 +223548 INTS7 chr1 211940399 212035557 +223829 DTL chr1 212035553 212107400 +223923 AL606468.1 chr1 212168207 212190259 +223929 LINC02608 chr1 212225278 212238977 +223970 PPP2R5A chr1 212285410 212361853 +224049 AL360091.2 chr1 212297448 212299579 +224053 AL360091.3 chr1 212299495 212331713 +224057 AL360091.1 chr1 212357418 212358353 +224061 PACC1 chr1 212363931 212414901 +224123 AC092803.3 chr1 212430269 212432775 +224127 NENF chr1 212432920 212446379 +224153 LINC02771 chr1 212466699 212472905 +224162 AC092803.2 chr1 212504178 212534060 +224169 LINC01740 chr1 212545694 212556065 +224174 AC092803.1 chr1 212557833 212559731 +224177 AC092803.4 chr1 212559363 212561399 +224181 ATF3 chr1 212565334 212620777 +224299 AL590648.2 chr1 212624284 212626771 +224303 FAM71A chr1 212624474 212626775 +224311 LINC02773 chr1 212653305 212665638 +224320 BATF3 chr1 212686417 212699840 +224338 NSL1 chr1 212726153 212791782 +224414 TATDN3 chr1 212791828 212816830 +224686 SPATA45 chr1 212830141 212847649 +224698 FLVCR1-DT chr1 212852105 212858126 +224714 FLVCR1 chr1 212858275 212899363 +224777 AC104333.4 chr1 212916787 212917577 +224782 VASH2 chr1 212950520 212992037 +224928 ANGEL2 chr1 212992182 213015867 +225015 RPS6KC1 chr1 213051233 213274774 +225240 AL592402.1 chr1 213492288 213579267 +225245 AC096639.1 chr1 213731416 213794587 +225249 PROX1-AS1 chr1 213817751 213988508 +225564 LINC00538 chr1 213924749 213926654 +225567 PROX1 chr1 213983181 214041510 +225645 AC011700.1 chr1 213983793 213986419 +225648 AL606537.1 chr1 214028891 214030901 +225651 LINC02775 chr1 214051194 214187773 +225658 SMYD2 chr1 214281102 214337131 +225735 AL929236.1 chr1 214344172 214357615 +225740 PTPN14 chr1 214348700 214552449 +225836 CENPF chr1 214603195 214664571 +225912 AC099563.2 chr1 214946909 214988040 +225916 KCNK2 chr1 215005775 215237093 +226068 AL450990.1 chr1 215393646 215394418 +226072 KCTD3 chr1 215567304 215621807 +226155 USH2A chr1 215622891 216423448 +226360 AL358452.1 chr1 215886582 215901464 +226364 AC093581.1 chr1 216072465 216086917 +226380 AC138024.1 chr1 216194051 216204366 +226385 ESRRG chr1 216503246 217137755 +226772 GPATCH2 chr1 217426992 217631090 +226829 SPATA17 chr1 217631324 217871696 +226892 SPATA17-AS1 chr1 217781198 217785120 +226897 LINC00210 chr1 217892900 217920804 +226907 AL355526.1 chr1 218031835 218033660 +226911 LINC01653 chr1 218043505 218059140 +226917 AL355526.2 chr1 218046943 218049221 +226923 RRP15 chr1 218285293 218337983 +226942 TGFB2-AS1 chr1 218344196 218345678 +226947 TGFB2 chr1 218345336 218444619 +226998 TGFB2-OT1 chr1 218442626 218443996 +227001 C1orf143 chr1 218459265 218525978 +227017 LINC01710 chr1 218912757 218918714 +227027 LYPLAL1-DT chr1 218983023 219173961 +227094 LYPLAL1 chr1 219173869 219212865 +227177 AL360093.1 chr1 219222248 219225497 +227181 AC096642.1 chr1 219270774 219273387 +227184 AC096642.2 chr1 219294982 219297668 +227188 LYPLAL1-AS1 chr1 219409039 219459369 +227227 AL356364.1 chr1 219557192 219557701 +227231 ZC3H11B chr1 219608010 219613145 +227254 SLC30A10 chr1 219685427 219958647 +227294 EPRS chr1 219968600 220046530 +227451 BPNT1 chr1 220057482 220090462 +227641 IARS2 chr1 220094132 220148041 +227708 RAB3GAP2 chr1 220148293 220272453 +227848 AL451081.1 chr1 220359731 220360183 +227852 AC096644.3 chr1 220401122 220404033 +227855 LINC02779 chr1 220485104 220487558 +227860 MARK1 chr1 220528183 220664461 +228023 C1orf115 chr1 220690363 220699153 +228033 MARC2 chr1 220748225 220784815 +228099 MARC1 chr1 220786913 220819659 +228171 RNU6ATAC35P chr1 220825620 220826063 +228174 AL445423.1 chr1 220828676 220829211 +228177 LINC01352 chr1 220829255 220832429 +228183 HLX-AS1 chr1 220832763 220880140 +228188 HLX chr1 220879431 220885059 +228215 LINC02817 chr1 221330080 221336489 +228277 AL360013.2 chr1 221508559 221510979 +228281 AL360013.3 chr1 221549362 221554314 +228285 AL360013.4 chr1 221555550 221563653 +228290 DUSP10 chr1 221701424 221742089 +228337 LINC01655 chr1 221819842 221840717 +228348 LINC02257 chr1 221880981 221978523 +228360 LINC02474 chr1 221966341 221984964 +228369 LINC01705 chr1 222010825 222064773 +228382 AL356108.1 chr1 222088806 222389103 +228396 AL513314.1 chr1 222452738 222454705 +228401 AL513314.2 chr1 222477252 222504622 +228427 HHIPL2 chr1 222522258 222548104 +228466 TAF1A chr1 222557902 222589933 +228590 TAF1A-AS1 chr1 222589825 222593843 +228610 MIA3 chr1 222618097 222668007 +228793 AL592148.3 chr1 222658867 222661512 +228796 AIDA chr1 222668013 222713210 +228878 BROX chr1 222712553 222735196 +229041 FAM177B chr1 222737207 222750805 +229118 AL392172.2 chr1 222743356 222773149 +229125 AL392172.1 chr1 222815022 222837384 +229203 DISP1 chr1 222872271 223005995 +229233 AL929091.1 chr1 223091872 223103335 +229247 TLR5 chr1 223109404 223143248 +229321 AL359979.2 chr1 223144049 223144954 +229325 AL359979.1 chr1 223181144 223188154 +229330 SUSD4 chr1 223220819 223364178 +229471 CCDC185 chr1 223393415 223395465 +229479 CAPN8 chr1 223538007 223665734 +229658 CAPN2 chr1 223701593 223776018 +229819 TP53BP2 chr1 223779893 223845954 +229996 AC138393.3 chr1 223994262 223995196 +230000 FBXO28 chr1 224114111 224162047 +230049 DEGS1 chr1 224175756 224193441 +230090 AC092809.2 chr1 224208741 224213625 +230100 AC092809.4 chr1 224219613 224228043 +230105 NVL chr1 224227334 224330189 +230580 CNIH4 chr1 224356858 224379459 +230655 WDR26 chr1 224385143 224437033 +230821 CNIH3 chr1 224434660 224740554 +230912 AC096537.1 chr1 224608130 224616220 +230925 AL596330.2 chr1 224703272 224712849 +230930 AL596330.1 chr1 224717504 224730662 +230935 LINC02813 chr1 224766324 224779335 +230953 AL391811.1 chr1 224802959 224881355 +230959 DNAH14 chr1 224896262 225399292 +231750 LBR chr1 225401502 225428925 +231885 LINC02765 chr1 225447233 225465400 +231916 AC092811.1 chr1 225465021 225473837 +231920 ENAH chr1 225486835 225653142 +232076 AC099066.2 chr1 225700264 225752258 +232099 AC099066.1 chr1 225710968 225736274 +232104 SRP9 chr1 225777813 225790468 +232205 EPHX1 chr1 225810092 225845563 +232300 AL591895.1 chr1 225840883 225846522 +232304 TMEM63A chr1 225845536 225882380 +232415 LEFTY1 chr1 225886282 225911382 +232432 PYCR2 chr1 225919877 225924340 +232530 AL117348.1 chr1 225936411 225937557 +232534 LEFTY2 chr1 225936598 225941383 +232566 SDE2 chr1 225982702 225999343 +232586 AL512343.2 chr1 226045561 226061898 +232594 H3F3A chr1 226061851 226072007 +232704 LINC01703 chr1 226083590 226090465 +232721 ACBD3 chr1 226144679 226186741 +232746 ACBD3-AS1 chr1 226148003 226155071 +232750 MIXL1 chr1 226223618 226227054 +232772 LIN9 chr1 226231149 226309869 +232916 PARP1 chr1 226360691 226408093 +233032 AL359704.3 chr1 226538305 226542729 +233037 STUM chr1 226548764 226609230 +233067 ITPKB chr1 226631690 226739323 +233117 ITPKB-IT1 chr1 226656640 226675067 +233124 ITPKB-AS1 chr1 226668897 226676345 +233128 AL359732.1 chr1 226827711 226833906 +233132 PSEN2 chr1 226870184 226896105 +233327 COQ8A chr1 226897536 226987545 +233484 CDC42BPA chr1 226989865 227318474 +234041 AL353689.2 chr1 226992140 226993206 +234046 AL353689.3 chr1 227123895 227132394 +234051 AL451047.1 chr1 227178333 227183444 +234056 AL627308.3 chr1 227280449 227281967 +234060 LINC01641 chr1 227393554 227431035 +234074 AL451054.4 chr1 227518738 227520619 +234079 ZNF678 chr1 227563543 227677443 +234135 SNAP47 chr1 227728539 227781231 +234254 JMJD4 chr1 227730425 227735411 +234331 SNAP47-AS1 chr1 227743831 227747191 +234335 AL731702.1 chr1 227786753 227792179 +234354 PRSS38 chr1 227815693 227846470 +234370 WNT9A chr1 227918656 227947932 +234384 WNT3A chr1 228006998 228061271 +234398 LINC02809 chr1 228073909 228076550 +234403 ARF1 chr1 228082660 228099212 +234509 C1orf35 chr1 228100726 228105411 +234572 MRPL55 chr1 228106679 228109312 +234954 AL136379.1 chr1 228119149 228121312 +234958 GUK1 chr1 228139962 228148984 +235366 GJC2 chr1 228149930 228159826 +235376 IBA57-DT chr1 228164086 228165512 +235383 IBA57 chr1 228165804 228182257 +235403 OBSCN-AS1 chr1 228203503 228213664 +235433 OBSCN chr1 228208063 228378876 +237283 AL353593.1 chr1 228238241 228276066 +237300 AL353593.2 chr1 228295549 228303002 +237304 AL353593.3 chr1 228329467 228331191 +237308 AL670729.3 chr1 228357012 228368554 +237319 AL670729.2 chr1 228384114 228385016 +237323 TRIM11 chr1 228393673 228406835 +237393 AL670729.1 chr1 228394290 228396967 +237398 AL139288.1 chr1 228407365 228410870 +237407 TRIM17 chr1 228407935 228416861 +237518 HIST3H3 chr1 228424845 228425325 +237525 HIST3H2A chr1 228456979 228457873 +237533 HIST3H2BB chr1 228458107 228460470 +237541 RNF187 chr1 228487382 228496188 +237569 RHOU chr1 228735479 228746664 +237581 LINC02815 chr1 229022773 229038274 +237587 LINC02814 chr1 229087114 229205428 +237607 AL162595.2 chr1 229223457 229242902 +237616 TMEM78 chr1 229249636 229251810 +237619 AL162595.1 chr1 229256892 229271242 +237643 RAB4A chr1 229271062 229305894 +237697 SPHAR chr1 229305135 229305326 +237704 AL117350.1 chr1 229319403 229323087 +237708 CCSAP chr1 229321011 229343294 +237749 ACTA1 chr1 229431245 229434098 +237786 NUP133 chr1 229440259 229508341 +237859 AL160004.1 chr1 229440284 229441020 +237863 AL121990.1 chr1 229508369 229514272 +237868 ABCB10 chr1 229516582 229558707 +237908 TAF5L chr1 229593111 229626047 +237964 URB2 chr1 229626247 229660200 +237999 LINC01682 chr1 229812917 229892046 +238033 LINC01736 chr1 230002372 230007195 +238048 GALNT2 chr1 230057990 230282122 +238107 AL136988.2 chr1 230258694 230272100 +238113 AL136988.1 chr1 230280312 230281893 +238117 PGBD5 chr1 230314490 230426332 +238161 AL133516.1 chr1 230426491 230436822 +238165 LINC01737 chr1 230592660 230595583 +238169 COG2 chr1 230642481 230693982 +238363 AL158214.2 chr1 230692533 230696888 +238367 AGT chr1 230702523 230714122 +238383 AL512328.1 chr1 230710698 230795492 +238394 CAPN9 chr1 230747384 230802003 +238530 AL118511.2 chr1 230823641 230824707 +238534 C1orf198 chr1 230837119 230869589 +238608 AL118511.1 chr1 230868259 230879141 +238628 AL118511.4 chr1 230878662 230890169 +238633 AL118511.3 chr1 230889949 230895788 +238637 TTC13 chr1 230906243 230978875 +238822 ARV1 chr1 230978981 231000733 +238919 FAM89A chr1 231018958 231040254 +238936 TRIM67 chr1 231162112 231221556 +239014 AL109810.2 chr1 231184098 231187627 +239030 C1orf131 chr1 231223763 231241187 +239118 GNPAT chr1 231241207 231277973 +239249 EXOC8 chr1 231332753 231337852 +239257 SPRTN chr1 231337104 231355023 +239319 EGLN1 chr1 231363751 231422287 +239386 AL445524.1 chr1 231520729 231528618 +239438 TSNAX chr1 231528541 231566524 +239485 LINC00582 chr1 231591292 231612090 +239489 DISC1 chr1 231626815 232041272 +239977 AL136171.2 chr1 231767464 231847706 +240005 DISC1-IT1 chr1 231925834 231945233 +240011 AL353052.1 chr1 232160091 232185643 +240016 AL353052.2 chr1 232174932 232180113 +240020 SIPA1L2 chr1 232397965 232561558 +240159 LINC01745 chr1 232718071 232722250 +240164 LINC01744 chr1 232727251 232751299 +240178 MAP10 chr1 232804892 232808407 +240186 AL122003.2 chr1 232843386 232897660 +240192 NTPCR chr1 232950605 232983882 +240250 PCNX2 chr1 232983435 233295725 +240607 MAP3K21 chr1 233327724 233385148 +240663 AL360006.1 chr1 233527544 233543633 +240669 KCNK1 chr1 233614106 233672514 +240708 AL357972.1 chr1 233724454 233730746 +240713 AL663058.2 chr1 233844621 233865370 +240717 AL713868.1 chr1 233904104 233905931 +240721 SLC35F3 chr1 233904676 234324511 +240762 AL122008.3 chr1 234212606 234215088 +240766 AL122008.1 chr1 234261706 234274465 +240770 AL122008.4 chr1 234268583 234272500 +240774 AL355472.2 chr1 234357006 234365828 +240778 AL355472.3 chr1 234372186 234372811 +240781 COA6-AS1 chr1 234372807 234373593 +240785 COA6 chr1 234373456 234385068 +240828 TARBP1 chr1 234391313 234479179 +240938 LINC01354 chr1 234527887 234531803 +240960 AL161640.2 chr1 234535963 234539054 +240965 AL161640.3 chr1 234550542 234554838 +240975 AL161640.1 chr1 234565298 234570088 +240979 IRF2BP2 chr1 234604269 234609525 +241001 AL160408.2 chr1 234607008 234609483 +241005 LINC00184 chr1 234629311 234634780 +241009 AL160408.5 chr1 234644666 234647571 +241013 AL160408.1 chr1 234646289 234683176 +241034 AL160408.4 chr1 234660271 234667104 +241039 AL160408.3 chr1 234669523 234696153 +241043 AL160408.6 chr1 234709383 234720220 +241049 LINC01132 chr1 234724042 234736720 +241063 AL360294.1 chr1 234757619 234760056 +241068 AL391832.4 chr1 234811052 234932653 +241072 AL391832.1 chr1 234957231 234959989 +241076 AL391832.2 chr1 234957342 234970062 +241146 AL391832.3 chr1 234979647 234980804 +241150 LINC01348 chr1 235065479 235074220 +241155 AL732292.2 chr1 235104180 235104609 +241158 TOMM20 chr1 235109341 235128837 +241184 RBM34 chr1 235131183 235161283 +241295 ARID4B chr1 235131634 235328219 +241647 GGPS1 chr1 235327350 235344532 +241726 TBCE chr1 235328570 235448952 +242462 AL357556.4 chr1 235366353 235367366 +242466 TBCE chr1 235367360 235452443 +243855 B3GALNT2 chr1 235447190 235504452 +243941 GNG4 chr1 235547685 235650754 +244001 LYST chr1 235661041 235883640 +244319 LYST-AS1 chr1 235839483 235840182 +244323 AL139161.1 chr1 235942553 235943805 +244327 LINC02768 chr1 235957879 235971825 +244331 NID1 chr1 235975830 236065109 +244416 AL122018.2 chr1 236123667 236130415 +244421 GPR137B chr1 236142505 236221865 +244478 ERO1B chr1 236215101 236281958 +244544 EDARADD chr1 236348257 236502915 +244636 LGALS8 chr1 236518000 236552981 +245079 LGALS8-AS1 chr1 236523052 236524508 +245084 AL359921.2 chr1 236536162 236536704 +245087 AL359921.1 chr1 236540094 236550280 +245091 HEATR1 chr1 236549005 236604516 +245299 ACTN2 chr1 236664141 236764631 +245702 MTR chr1 236795292 236921278 +246063 MT1HL1 chr1 237004103 237004441 +246071 AL359259.1 chr1 237013373 237014200 +246075 RYR2 chr1 237042184 237833988 +246748 AL359924.1 chr1 237862175 237928321 +246762 ZP4 chr1 237877864 237890922 +246823 MTRNR2L11 chr1 237943724 237945275 +246831 AL356010.2 chr1 238238943 238404906 +246841 LINC01139 chr1 238476542 238486060 +246865 AL359551.1 chr1 238485445 238538305 +246871 AL583825.1 chr1 238842767 238848115 +246875 AC093426.2 chr1 239205138 239212284 +246879 AC093426.1 chr1 239247808 239250818 +246882 CHRM3 chr1 239386565 239915452 +246943 CHRM3-AS2 chr1 239703381 239770130 +246988 CHRM3-AS1 chr1 239898016 239899872 +246992 AL356361.2 chr1 239915439 239916955 +246996 AL356361.3 chr1 240007524 240008381 +246999 FMN2 chr1 240014348 240475187 +247120 AL359918.2 chr1 240177839 240179644 +247128 AL590490.1 chr1 240400671 240401123 +247132 GREM2 chr1 240489573 240612155 +247142 AL358176.1 chr1 240530452 240530862 +247146 AL358176.4 chr1 240588522 240590748 +247150 AL365184.2 chr1 240739419 240739853 +247153 AL365184.1 chr1 240763334 240776824 +247204 RGS7 chr1 240775515 241357230 +247387 AL359764.1 chr1 241357343 241364054 +247398 AL359764.2 chr1 241413716 241468661 +247495 AL359764.3 chr1 241453751 241484995 +247501 FH chr1 241497603 241519761 +247534 KMO chr1 241532134 241595642 +247695 OPN3 chr1 241590102 241677376 +247759 CHML chr1 241628853 241640254 +247795 AL133390.1 chr1 241640555 241641835 +247798 WDR64 chr1 241652278 241802133 +248019 EXO1 chr1 241847967 241895148 +248209 BECN2 chr1 241957767 241959062 +248216 MAP1LC3C chr1 241995490 241999098 +248230 PLD5 chr1 242082986 242524696 +248389 AL591686.2 chr1 242147230 242209129 +248409 AL591686.1 chr1 242203555 242210827 +248414 AL606534.3 chr1 243005845 243007468 +248419 CEP170 chr1 243124428 243255348 +248771 AL606534.1 chr1 243135898 243140588 +248775 AL606534.2 chr1 243164638 243169445 +248783 SDCCAG8 chr1 243256034 243500091 +248901 AKT3 chr1 243488233 243851079 +249196 AL591721.1 chr1 243545532 243548329 +249201 AL662889.1 chr1 243702857 243740821 +249206 AKT3-IT1 chr1 243793205 243794400 +249210 LINC02774 chr1 243917402 244047317 +249231 ZBTB18 chr1 244048939 244057476 +249250 AL590483.1 chr1 244068820 244093026 +249257 AL590483.4 chr1 244087306 244090295 +249261 AL590483.2 chr1 244107365 244109011 +249265 AL358177.1 chr1 244184953 244187559 +249269 C1orf100 chr1 244352635 244389663 +249308 AL645465.1 chr1 244375100 244409592 +249314 ADSS chr1 244408494 244451909 +249357 CATSPERE chr1 244454377 244641177 +249586 DESI2 chr1 244653103 244709033 +249629 AL451007.3 chr1 244729898 244730962 +249637 AL451007.2 chr1 244731024 244731586 +249640 BX323046.2 chr1 244834374 244835011 +249643 COX20 chr1 244835616 244845057 +249685 HNRNPU chr1 244840638 244864560 +250248 BX323046.1 chr1 244864738 244865272 +250251 AL356512.1 chr1 244969350 244971088 +250254 EFCAB2 chr1 244969705 245127164 +250427 KIF26B chr1 245154985 245709432 +250501 KIF26B-AS1 chr1 245206444 245234501 +250508 AC104462.2 chr1 245614773 245615145 +250512 AC104462.1 chr1 245673732 245676478 +250516 SMYD3 chr1 245749342 246507312 +250715 AC118555.1 chr1 246025897 246035603 +250720 AC092801.1 chr1 246108626 246113866 +250732 SMYD3-IT1 chr1 246321663 246322438 +250736 LINC01743 chr1 246516039 246524287 +250741 TFB2M chr1 246540561 246566261 +250763 CNST chr1 246566444 246668595 +250836 AL591623.1 chr1 246605873 246608102 +250840 AL591848.3 chr1 246682108 246685075 +250843 AL591848.2 chr1 246690047 246691821 +250847 SCCPDH chr1 246724409 246768137 +250877 AL591848.4 chr1 246772301 246775772 +250880 LINC01341 chr1 246775880 246792385 +250934 AHCTF1 chr1 246839098 246931967 +251218 ZNF695 chr1 246945547 247008093 +251303 ZNF670 chr1 247034637 247078811 +251317 ZNF669 chr1 247099962 247104372 +251377 AL627095.2 chr1 247105405 247108929 +251383 C1orf229 chr1 247110160 247112417 +251386 ZNF124 chr1 247121975 247172016 +251448 AL390728.6 chr1 247187281 247188526 +251451 AL390728.5 chr1 247210691 247241823 +251457 ZNF496 chr1 247297412 247331846 +251515 AC104335.1 chr1 247337886 247348076 +251520 AC104335.2 chr1 247390243 247393839 +251524 NLRP3 chr1 247416156 247449108 +251717 OR2B11 chr1 247449118 247458105 +251751 GCSAML chr1 247507058 247577690 +251923 OR2C3 chr1 247524677 247536440 +251951 GCSAML-AS1 chr1 247524679 247532613 +251964 AL606804.1 chr1 247565639 247640854 +251973 OR2G2 chr1 247588360 247589313 +251980 OR2G3 chr1 247605586 247606515 +251987 AL390860.1 chr1 247639630 247761255 +252024 OR13G1 chr1 247670812 247679739 +252041 OR6F1 chr1 247711436 247716646 +252080 OR14A2 chr1 247722957 247724043 +252096 OR14K1 chr1 247738615 247739559 +252103 OR1C1 chr1 247754846 247760556 +252120 OR14A16 chr1 247814660 247824119 +252138 OR11L1 chr1 247840928 247841896 +252145 TRIM58 chr1 247857187 247880138 +252163 OR2W3 chr1 247895587 247896531 +252170 OR2T8 chr1 247920252 247921956 +252186 OR2AJ1 chr1 247924889 247935339 +252196 OR2L8 chr1 247948858 247949796 +252203 OR2AK2 chr1 247965233 247966386 +252217 OR2L5 chr1 248013660 248024276 +252227 OR2L2 chr1 248030070 248042305 +252255 OR2L3 chr1 248046836 248063407 +252285 OR2L13 chr1 248095184 248101103 +252317 OR2M5 chr1 248145148 248146086 +252324 OR2M2 chr1 248174821 248181067 +252351 OR2M3 chr1 248197265 248212925 +252368 OR2M4 chr1 248231417 248244679 +252384 OR2T33 chr1 248269917 248277976 +252401 OR2T12 chr1 248290139 248303424 +252420 OR2M7 chr1 248323630 248324568 +252427 OR14C36 chr1 248348775 248349713 +252434 OR2T4 chr1 248361581 248362627 +252447 OR2T6 chr1 248375746 248391811 +252465 OR2T1 chr1 248403048 248408020 +252481 OR2T2 chr1 248445512 248455725 +252513 OR2T3 chr1 248473351 248474307 +252520 AC138089.1 chr1 248484245 248485484 +252524 OR2T5 chr1 248488589 248491113 +252531 OR2G6 chr1 248508073 248527337 +252557 AC098483.1 chr1 248548756 248565299 +252567 OR2T29 chr1 248556912 248562772 +252584 OR2T34 chr1 248573801 248574757 +252591 OR2T10 chr1 248590487 248597700 +252608 OR2T11 chr1 248623557 248635091 +252625 OR2T35 chr1 248636356 248645278 +252641 OR2T27 chr1 248649838 248655528 +252668 OR14I1 chr1 248681322 248682328 +252676 LYPD8 chr1 248739415 248755759 +252696 SH3BP5L chr1 248810446 248825915 +252732 ZNF672 chr1 248838210 248849517 +252795 ZNF692 chr1 248850006 248859144 +253141 AL672291.1 chr1 248859164 248864796 +253146 PGBD2 chr1 248906196 248919946 +253173 FAM110C chr2 38814 46870 +253189 AC079779.1 chr2 197569 209892 +253203 SH3YL1 chr2 217730 266398 +253589 ACP1 chr2 264140 278283 +253747 ALKAL2 chr2 279558 288851 +253852 AC079779.2 chr2 286419 301515 +253861 AC079779.3 chr2 290941 314373 +254042 AC079779.4 chr2 307683 309424 +254046 LINC01865 chr2 317912 342118 +254055 AC105393.2 chr2 388412 416885 +254059 AC105393.1 chr2 421057 424059 +254069 LINC01874 chr2 490944 503905 +254077 AC093326.2 chr2 495731 496633 +254081 LINC01875 chr2 545805 546667 +254085 AC093326.1 chr2 558153 578145 +254113 TMEM18 chr2 663877 677406 +254198 AC092159.2 chr2 677186 697382 +254210 AC092159.3 chr2 692083 693235 +254214 AC092159.1 chr2 724194 731224 +254224 AC116609.3 chr2 739588 740164 +254227 AC116609.2 chr2 741977 749856 +254231 AC116609.1 chr2 742488 747767 +254235 LINC01115 chr2 779840 868608 +254278 LINC01939 chr2 899462 905539 +254288 AC113607.1 chr2 910926 921124 +254292 SNTG2-AS1 chr2 949627 950274 +254296 SNTG2 chr2 950849 1367613 +254448 AC114808.1 chr2 1059133 1068341 +254452 AC114808.2 chr2 1158310 1160424 +254457 AC108462.1 chr2 1341044 1346568 +254461 AC105450.1 chr2 1366234 1580747 +254470 TPO chr2 1374066 1543711 +254789 AC141930.1 chr2 1546665 1620113 +254794 AC141930.2 chr2 1552445 1554701 +254799 AC144450.1 chr2 1620510 1625419 +254803 PXDN chr2 1631887 1744852 +254985 MYT1L chr2 1789113 2331664 +256699 AC093390.2 chr2 1795525 1811526 +256710 AC093390.1 chr2 1824412 1828667 +256714 MYT1L-AS1 chr2 2319232 2327110 +256721 AC018685.2 chr2 2638178 2696285 +256729 AC018685.3 chr2 2697490 2701812 +256733 AC011995.2 chr2 2707368 2840512 +256768 AC018685.1 chr2 2729908 2730957 +256772 AC011995.1 chr2 2870558 2871231 +256776 LINC01250 chr2 2895048 3126026 +256791 AC019118.2 chr2 3131581 3145780 +256798 AC019118.1 chr2 3156756 3157797 +256803 EIPR1 chr2 3188925 3377882 +256983 EIPR1-IT1 chr2 3298341 3301465 +256987 TRAPPC12 chr2 3379675 3485094 +257231 TRAPPC12-AS1 chr2 3481242 3482409 +257235 AC114810.1 chr2 3496956 3497428 +257238 ADI1 chr2 3497366 3519531 +257272 AC231981.1 chr2 3519275 3523197 +257276 AC108488.1 chr2 3531813 3536873 +257296 RNASEH1 chr2 3541430 3558333 +257357 RNASEH1-AS1 chr2 3558474 3564842 +257369 AC108488.3 chr2 3568505 3575100 +257376 RPS7 chr2 3575260 3580920 +257524 COLEC11 chr2 3594832 3644644 +257716 AC010907.2 chr2 3603397 3604242 +257720 ALLC chr2 3658200 3702671 +257763 AC010907.1 chr2 3702585 3704153 +257767 DCDC2C chr2 3703575 3848008 +257807 LINC01304 chr2 3957652 3974124 +257902 AC012445.1 chr2 4136644 4140731 +257907 LINC01249 chr2 4628216 4656498 +257928 AC107057.1 chr2 5549780 5556031 +257932 LINC01248 chr2 5602505 5691488 +257936 AC108025.1 chr2 5618327 5691118 +257949 SOX11 chr2 5692384 5701385 +257957 AC010729.2 chr2 5696220 5719670 +257967 AC010729.1 chr2 5726253 5730355 +257975 LINC01810 chr2 5810641 5812670 +257984 SILC1 chr2 5932543 6003510 +258140 AC017053.1 chr2 6258348 6341788 +258166 LINC01247 chr2 6366010 6375422 +258171 LINC01824 chr2 6495651 6511839 +258191 MIR7515HG chr2 6615389 6651104 +258695 AC097517.1 chr2 6649706 6650897 +258699 LINC00487 chr2 6728177 6770311 +258716 NRIR chr2 6819463 6840464 +258731 CMPK2 chr2 6840570 6866635 +258794 RSAD2 chr2 6865806 6898239 +258831 AC017076.1 chr2 6905724 6906301 +258834 RNF144A-AS1 chr2 6911754 6918734 +258972 RNF144A chr2 6917412 7068286 +259050 AC068481.1 chr2 7045329 7077916 +259074 AC010904.2 chr2 7260871 7261504 +259077 AC013460.1 chr2 7383227 7450544 +259192 AC092580.4 chr2 7671330 7675736 +259196 AC092580.2 chr2 7671604 7672246 +259200 LINC01871 chr2 7725801 7730705 +259204 AC007463.1 chr2 7886767 7899725 +259228 LINC00298 chr2 7922425 8278186 +259251 AC007463.2 chr2 7937282 7953402 +259255 LINC00299 chr2 7988683 8488090 +259369 U91324.1 chr2 8139335 8144950 +259387 LINC01814 chr2 8461703 8592903 +259459 AC092617.1 chr2 8488420 8505027 +259465 AC011747.1 chr2 8600892 8622942 +259470 ID2-AS1 chr2 8666636 8681864 +259521 ID2 chr2 8678845 8684461 +259560 KIDINS220 chr2 8721081 8837630 +260016 MBOAT2 chr2 8852690 9003709 +260137 AC093904.2 chr2 9103440 9105114 +260145 AC093904.4 chr2 9106593 9109865 +260148 AC093904.3 chr2 9110457 9116947 +260157 AC093904.1 chr2 9143166 9146106 +260162 ASAP2 chr2 9206765 9405683 +260320 ITGB1BP1 chr2 9403475 9423547 +260575 CPSF3 chr2 9423651 9473101 +260681 IAH1 chr2 9473658 9496543 +260846 ADAM17 chr2 9488486 9556732 +261193 AC080162.1 chr2 9501466 9512413 +261202 AC073195.1 chr2 9555899 9556775 +261205 YWHAQ chr2 9583967 9630997 +261258 AC082651.1 chr2 9638745 9712920 +261288 AC082651.4 chr2 9671875 9708413 +261302 AC082651.3 chr2 9757496 9770341 +261306 TAF1B chr2 9843443 9934416 +261452 AC010969.2 chr2 9936360 9939590 +261455 AC010969.3 chr2 9939088 9950817 +261460 GRHL1 chr2 9951693 10002277 +261641 AC010969.1 chr2 10001757 10006030 +261649 AC104794.4 chr2 10021578 10022825 +261652 AC104794.3 chr2 10039092 10040663 +261655 KLF11 chr2 10042849 10054836 +261722 AC104794.5 chr2 10054421 10054866 +261725 CYS1 chr2 10056780 10080944 +261741 AC104794.2 chr2 10083781 10086101 +261746 RRM2 chr2 10120698 10211725 +261968 AC007240.3 chr2 10287800 10302485 +261974 HPCAL1 chr2 10302889 10427617 +262095 ODC1 chr2 10439968 10448327 +262171 ODC1-DT chr2 10448689 10457693 +262194 NOL10 chr2 10570754 10689987 +262358 AC007314.1 chr2 10589166 10604830 +262364 RN7SL832P chr2 10690344 10692099 +262367 AC092687.2 chr2 10717773 10720952 +262374 ATP6V1C2 chr2 10721100 10785110 +262503 AC092687.3 chr2 10767875 10770058 +262508 PDIA6 chr2 10783391 10837977 +262725 LINC01954 chr2 10844477 10885118 +262736 AC092687.1 chr2 10847577 10854955 +262741 KCNF1 chr2 10911934 10914225 +262749 AC062028.1 chr2 11105317 11132821 +262787 C2orf50 chr2 11133053 11146790 +262812 SLC66A3 chr2 11155198 11178870 +262928 ROCK2 chr2 11179759 11348330 +263202 AC099344.1 chr2 11357515 11365636 +263206 AC099344.2 chr2 11388023 11390367 +263211 LINC00570 chr2 11391810 11403080 +263245 AC099344.3 chr2 11405508 11427186 +263265 E2F6 chr2 11444375 11466177 +263456 GREB1 chr2 11482341 11642788 +263740 NTSR2 chr2 11658178 11670195 +263754 AC106875.2 chr2 11673964 11676925 +263758 LPIN1 chr2 11677595 11827409 +264110 AC106875.1 chr2 11681460 11683328 +264117 AC012456.1 chr2 11721619 11724222 +264121 AC012456.2 chr2 11740997 11745301 +264126 MIR3681HG chr2 11833926 12702913 +264208 AC096559.1 chr2 12598987 12605145 +264214 AC009486.2 chr2 12702764 12716557 +264218 AC009486.1 chr2 12715415 12716227 +264221 TRIB2 chr2 12716889 12742734 +264258 AC064875.1 chr2 12780593 13007029 +264343 AC093912.1 chr2 13000953 13331683 +264350 AC073062.1 chr2 13537673 13609168 +264354 LINC00276 chr2 13710531 14400963 +264366 AC016730.1 chr2 13723048 13758152 +264371 AC011897.1 chr2 14616428 14630192 +264379 LRATD1 chr2 14632700 14650814 +264410 AC068286.2 chr2 14705668 14992066 +264416 AC068286.1 chr2 14886647 14907664 +264421 NBAS chr2 15166914 15561334 +264673 AC008278.2 chr2 15564170 15573868 +264679 DDX1 chr2 15591178 15631111 +264913 AC008278.1 chr2 15668684 15680484 +264918 LINC01804 chr2 15690782 15744339 +264936 AC113608.2 chr2 15801747 15810877 +264940 MYCNOS chr2 15918350 15942249 +264961 MYCNUT chr2 15920399 15936017 +264966 MYCN chr2 15940550 15947007 +264987 AC010145.1 chr2 15997049 16062885 +264992 GACAT3 chr2 16013928 16087201 +265033 AC130710.1 chr2 16085222 16105841 +265043 AC010745.1 chr2 16202430 16204226 +265048 AC010745.2 chr2 16224047 16333978 +265082 AC010745.3 chr2 16227027 16228194 +265086 AC010745.5 chr2 16294445 16302290 +265094 AC010745.4 chr2 16316324 16319566 +265098 AC010880.1 chr2 16354256 16432702 +265108 AC104623.1 chr2 16523176 16555564 +265131 FAM49A chr2 16549459 16666331 +265224 AC008164.1 chr2 16728124 16769567 +265235 LINC01866 chr2 16970034 16974497 +265240 RAD51AP2 chr2 17510584 17518439 +265252 VSNL1 chr2 17539126 17657018 +265316 SMC6 chr2 17663812 17800242 +265617 GEN1 chr2 17753858 17788946 +265730 MSGN1 chr2 17816460 17817798 +265738 KCNS3 chr2 17877847 18361616 +265780 AC079148.3 chr2 18403967 18504484 +265785 AC079148.2 chr2 18505729 18514332 +265789 AC079148.1 chr2 18547386 18548204 +265792 RDH14 chr2 18554723 18560679 +265805 NT5C1B chr2 18562872 18589572 +265914 AC106053.1 chr2 18784807 18787752 +265918 AC130814.1 chr2 18939697 18946650 +265923 LINC01376 chr2 18986451 19348067 +265956 OSR1 chr2 19351485 19358623 +265974 AC010096.1 chr2 19458220 19468961 +265982 LINC01808 chr2 19468997 19520095 +266042 AC019055.1 chr2 19711715 19717576 +266046 LINC00954 chr2 19868860 19885047 +266102 TTC32 chr2 19896631 19901983 +266133 AC013400.1 chr2 19902025 19902569 +266136 WDR35 chr2 19910260 19990131 +266383 AC079145.1 chr2 19990209 20004795 +266392 MATN3 chr2 19992052 20012668 +266436 LAPTM4A chr2 20032650 20051628 +266460 LAPTM4A-DT chr2 20052134 20054496 +266464 AC098828.2 chr2 20063856 20106829 +266468 SDC1 chr2 20200797 20225433 +266538 PUM2 chr2 20248691 20352234 +266841 RHOB chr2 20447074 20449440 +266849 AC023137.1 chr2 20451042 20452947 +266853 AC012065.1 chr2 20499571 20501311 +266857 HS1BP3 chr2 20560448 20651130 +266970 AC012065.3 chr2 20586248 20586686 +266973 HS1BP3-IT1 chr2 20590775 20592548 +266977 GDF7 chr2 20667144 20679243 +266987 AC012065.4 chr2 20678254 20678932 +266990 LDAH chr2 20684014 20823130 +267188 LINC02850 chr2 20859771 20861661 +267192 AC115619.1 chr2 20999313 21000917 +267195 APOB chr2 21001429 21044073 +267298 AC010872.2 chr2 21094101 21096543 +267302 TDRD15 chr2 21123917 21143272 +267322 AC018742.1 chr2 21221169 21970959 +267337 AC011752.1 chr2 21317660 21561313 +267370 AC009411.2 chr2 21607465 21637197 +267379 AC009411.1 chr2 21638068 21649572 +267405 LINC01822 chr2 21687430 21710656 +267427 AC096570.1 chr2 21932662 22536322 +267466 AC096570.2 chr2 22377594 22482004 +267472 LINC01884 chr2 22508129 22548800 +267520 AC018467.1 chr2 23018125 23199056 +267544 AC012506.1 chr2 23330664 23332044 +267550 AC012506.3 chr2 23347654 23351864 +267554 AC012506.2 chr2 23357516 23360376 +267558 AC012506.4 chr2 23375229 23381299 +267571 KLHL29 chr2 23385179 23708611 +267636 AC011239.1 chr2 23507043 23524344 +267640 AC009242.1 chr2 23667208 23685453 +267656 ATAD2B chr2 23748664 23927123 +267813 UBXN2A chr2 23927285 24004909 +267866 MFSD2B chr2 24010081 24063321 +267995 WDCP chr2 24029347 24049575 +268027 FKBP1B chr2 24049701 24063681 +268102 SF3B6 chr2 24067586 24076373 +268119 FAM228B chr2 24076526 24169640 +268250 TP53I3 chr2 24077433 24085861 +268312 PFN4 chr2 24114809 24123464 +268342 AC008073.2 chr2 24165884 24175005 +268351 FAM228A chr2 24175053 24200849 +268410 AC008073.1 chr2 24199839 24201698 +268414 ITSN2 chr2 24202864 24360714 +268843 AC009228.1 chr2 24210650 24222201 +268857 AC093798.1 chr2 24402995 24413292 +268863 NCOA1 chr2 24491914 24770702 +269182 PTRHD1 chr2 24789734 24793382 +269208 CENPO chr2 24793136 24822376 +269303 ADCY3 chr2 24819169 24919839 +269535 AC012073.1 chr2 24825610 24826717 +269538 DNAJC27 chr2 24943636 24972094 +269620 DNAJC27-AS1 chr2 24971390 25039716 +269667 AC013267.2 chr2 25000147 25010274 +269671 EFR3B chr2 25042076 25159135 +269901 POMC chr2 25160853 25168903 +269961 LINC01381 chr2 25204313 25209202 +269965 DNMT3A chr2 25227855 25342590 +270272 AC012074.1 chr2 25369136 25375845 +270278 DTNB chr2 25377198 25673647 +270837 AC104699.1 chr2 25421117 25427643 +270842 ASXL2 chr2 25733753 25878487 +270969 KIF3C chr2 25926598 25982749 +271074 RAB10 chr2 26034084 26137454 +271112 GAREM2 chr2 26173088 26189663 +271150 HADHA chr2 26190635 26244672 +271549 HADHB chr2 26243170 26290465 +271757 AC010896.1 chr2 26298570 26306340 +271764 ADGRF3 chr2 26308173 26346817 +271977 SELENOI chr2 26308547 26395891 +272062 DRC1 chr2 26401920 26456711 +272186 OTOF chr2 26457203 26558698 +272649 FAM166C chr2 26562585 26579532 +272692 CIB4 chr2 26581205 26641366 +272724 AC015977.2 chr2 26671254 26674464 +272729 KCNK3 chr2 26692690 26733420 +272750 SLC35F6 chr2 26764284 26781231 +272802 CENPA chr2 26764289 26801067 +272864 DPYSL5 chr2 26847747 26950351 +272997 AC013472.2 chr2 26950308 27009807 +273001 MAPRE3 chr2 26970637 27027219 +273114 AC013472.1 chr2 26984776 27014612 +273135 TMEM214 chr2 27032910 27041694 +273368 AGBL5 chr2 27042364 27070622 +273530 AGBL5-AS1 chr2 27049683 27050264 +273534 AC013472.3 chr2 27053618 27054276 +273537 AGBL5-IT1 chr2 27061038 27061815 +273541 AC013403.2 chr2 27062428 27062907 +273544 OST4 chr2 27070472 27071654 +273576 EMILIN1 chr2 27078615 27086403 +273611 KHK chr2 27086747 27100762 +273695 CGREF1 chr2 27098889 27119128 +273830 ABHD1 chr2 27123789 27130812 +273937 PREB chr2 27130756 27134666 +274053 PRR30 chr2 27136848 27139410 +274078 TCF23 chr2 27149004 27156974 +274093 SLC5A6 chr2 27199587 27212958 +274332 ATRAID chr2 27212027 27217178 +274429 CAD chr2 27217369 27243943 +274684 SLC30A3 chr2 27253684 27275817 +274803 DNAJC5G chr2 27275433 27281499 +274889 TRIM54 chr2 27282392 27307439 +274945 UCN chr2 27307400 27308445 +274955 MPV17 chr2 27309492 27325680 +275246 GTF3C2 chr2 27325849 27357034 +275461 GTF3C2-AS1 chr2 27335520 27342599 +275525 AC074117.1 chr2 27356246 27367622 +275536 EIF2B4 chr2 27364352 27370486 +275798 SNX17 chr2 27370496 27377535 +275991 ZNF513 chr2 27377235 27380790 +276029 PPM1G chr2 27381195 27409591 +276067 NRBP1 chr2 27427790 27442259 +276243 KRTCAP3 chr2 27442366 27446481 +276335 IFT172 chr2 27444377 27489789 +276703 FNDC4 chr2 27491883 27495200 +276735 GCKR chr2 27496839 27523684 +276850 C2orf16 chr2 27537386 27582721 +276873 ZNF512 chr2 27582969 27623217 +277049 CCDC121 chr2 27625639 27629012 +277075 GPN1 chr2 27628247 27651511 +277372 SUPT7L chr2 27650809 27663840 +277452 SLC4A1AP chr2 27663471 27694976 +277588 LINC01460 chr2 27705786 27715732 +277592 MRPL33 chr2 27771717 27988087 +277646 RBKS chr2 27781379 27890681 +277713 BABAM2 chr2 27889941 28338901 +277922 AC093690.1 chr2 28307063 28310560 +277934 AC104695.2 chr2 28384409 28394672 +277942 FOSL2 chr2 28392448 28417317 +277984 AC104695.4 chr2 28396815 28397110 +277987 AC104695.3 chr2 28425945 28426719 +277990 AC104695.1 chr2 28448167 28450184 +277994 PLB1 chr2 28457145 28644142 +278535 AC074011.1 chr2 28633282 28664540 +278539 AC092164.1 chr2 28707511 28751722 +278599 PPP1CB chr2 28751640 28802940 +278725 SPDYA chr2 28782517 28850611 +278804 AC097724.1 chr2 28810281 28810706 +278807 TRMT61B chr2 28849821 28870309 +278862 WDR43 chr2 28894667 28948219 +278958 TOGARAM2 chr2 28956611 29061373 +279063 PCARE chr2 29060976 29074523 +279077 AC105398.1 chr2 29088649 29097586 +279086 CLIP4 chr2 29097705 29189643 +279342 ALK chr2 29192774 29921586 +279552 AC074096.1 chr2 29319554 29352214 +279559 AC016907.2 chr2 29841187 30143804 +279575 AC106870.2 chr2 29890371 29892354 +279579 AC106870.1 chr2 29899597 29907199 +279583 YPEL5 chr2 30146941 30160533 +279670 LBH chr2 30231534 30323730 +279749 AC109642.1 chr2 30343222 30348298 +279753 LINC01936 chr2 30346623 30361010 +279772 LCLAT1 chr2 30447226 30644225 +279933 CAPN13 chr2 30722771 30820542 +280083 AC009301.1 chr2 30887626 30897387 +280090 GALNT14 chr2 30910467 31155202 +280336 AC009305.1 chr2 30986939 30991426 +280340 CAPN14 chr2 31173056 31233858 +280439 EHD3 chr2 31234152 31269451 +280457 XDH chr2 31334321 31414742 +280546 SRD5A2 chr2 31522480 31580938 +280562 AL133247.1 chr2 31526942 31563464 +280567 LINC01946 chr2 31793823 31803980 +280574 AL121652.1 chr2 31852976 31853423 +280577 MEMO1 chr2 31865060 32011230 +280710 DPY30 chr2 31867809 32039805 +280782 AL121655.1 chr2 32013061 32013368 +280785 SPAST chr2 32063547 32157637 +281419 AL121658.1 chr2 32165046 32165757 +281422 SLC30A6 chr2 32165841 32224379 +281678 NLRC4 chr2 32224453 32265732 +281797 YIPF4 chr2 32277904 32316594 +281838 AL133245.1 chr2 32321638 32323002 +281841 BIRC6 chr2 32357028 32618899 +282182 BIRC6-AS1 chr2 32377631 32379599 +282186 AL133243.2 chr2 32521927 32523547 +282189 AL133243.3 chr2 32526504 32529507 +282192 AL133243.1 chr2 32548675 32549040 +282195 TTC27 chr2 32628032 32821051 +282354 LINC00486 chr2 32825359 32926693 +282401 AL133244.2 chr2 32927085 32946149 +282446 LTBP1 chr2 32946953 33399509 +282862 AC019127.1 chr2 33274465 33281261 +282867 RASGRP3 chr2 33436324 33564750 +283114 AC020594.1 chr2 33555047 33563547 +283118 FAM98A chr2 33583660 33599382 +283189 AC017050.1 chr2 33599442 33657460 +283196 LINC01320 chr2 33706886 34738231 +283390 LINC01318 chr2 34067226 34069550 +283395 AC008170.1 chr2 34134371 34220575 +283402 AC073218.1 chr2 34692290 34703606 +283410 AC012593.1 chr2 34732287 34822726 +283421 AC079352.1 chr2 34799850 35284997 +283542 AC019064.1 chr2 34998273 35000160 +283547 CRIM1-DT chr2 36354749 36355114 +283550 CRIM1 chr2 36355778 36551135 +283631 AC007378.1 chr2 36513255 36513732 +283634 FEZ2 chr2 36531805 36646087 +283829 VIT chr2 36696690 36814792 +284064 STRN chr2 36837698 36966536 +284155 HEATR5B chr2 36968383 37084372 +284251 GPATCH11 chr2 37084451 37099244 +284299 EIF2AK2 chr2 37099210 37157065 +284490 SULT6B1 chr2 37167820 37196598 +284555 CEBPZOS chr2 37196488 37216193 +284645 CEBPZ chr2 37201612 37231596 +284696 AC007390.2 chr2 37208875 37212677 +284699 NDUFAF7 chr2 37231631 37253403 +284875 PRKD3 chr2 37250502 37324808 +285031 AC007391.1 chr2 37325340 37326797 +285035 AC007391.2 chr2 37339957 37343796 +285039 QPCT chr2 37342827 37373322 +285111 AC007391.3 chr2 37466781 37524807 +285116 AC006369.1 chr2 37562486 37646698 +285127 CDC42EP3 chr2 37641882 37738468 +285174 AC006369.2 chr2 37744333 37747046 +285178 LINC00211 chr2 37820498 37876274 +285215 RMDN2 chr2 37923187 38067142 +285438 RMDN2-AS1 chr2 37949911 38067041 +285499 CYP1B1 chr2 38066973 38109902 +285549 CYP1B1-AS1 chr2 38073447 38231651 +285734 AC009229.2 chr2 38132637 38138946 +285739 AC009229.3 chr2 38193348 38193629 +285742 AC009229.1 chr2 38203363 38239590 +285746 ATL2 chr2 38293954 38377285 +286071 LINC02613 chr2 38406527 38515934 +286136 AC016995.1 chr2 38408719 38412627 +286141 LINC01883 chr2 38431294 38433573 +286145 HNRNPLL chr2 38561969 38603586 +286409 AC011247.1 chr2 38601598 38602178 +286413 GALM chr2 38666081 38741237 +286481 AC074366.1 chr2 38668202 38671421 +286502 SRSF7 chr2 38743599 38751494 +286703 GEMIN6 chr2 38751534 38785002 +286745 DHX57 chr2 38797729 38875934 +286952 AC018693.1 chr2 38861720 38863133 +286956 MORN2 chr2 38875962 38929072 +287062 ARHGEF33 chr2 38889841 38975449 +287183 AC019171.1 chr2 38959287 38960342 +287186 SOS1 chr2 38981396 39124345 +287366 SOS1-IT1 chr2 38992279 38993857 +287376 CDKL4 chr2 39175646 39229588 +287441 MAP4K3 chr2 39249266 39437301 +287749 AC007684.2 chr2 39323328 39323804 +287752 MAP4K3-DT chr2 39436530 39665343 +287888 TMEM178A chr2 39664982 39717963 +287936 THUMPD2 chr2 39736060 39779267 +288052 SLC8A1-AS1 chr2 39786453 40255209 +288268 SLC8A1 chr2 40097270 40611053 +288491 AC007877.1 chr2 40534806 40545781 +288496 AC007317.1 chr2 40591285 40679604 +288502 AC007317.2 chr2 40620667 40639632 +288507 LINC01794 chr2 40746481 40767452 +288518 AC009413.2 chr2 41716133 41731611 +288523 LINC01913 chr2 41860155 41894050 +288577 LINC01914 chr2 41931599 41933909 +288587 C2orf91 chr2 41935368 41956806 +288618 AC013480.1 chr2 42015625 42025302 +288623 PKDCC chr2 42048021 42058517 +288690 AC083949.1 chr2 42143238 42170301 +288699 EML4 chr2 42169353 42332548 +288885 COX7A2L chr2 42333546 42425088 +288953 KCNG3 chr2 42442017 42493982 +288972 MTA3 chr2 42494569 42756947 +289320 OXER1 chr2 42762481 42764261 +289328 HAAO chr2 42767089 42792593 +289406 AC016735.1 chr2 43001355 43006060 +289411 LINC01819 chr2 43027823 43040662 +289466 LINC02590 chr2 43041193 43043782 +289470 LINC02580 chr2 43092530 43132482 +289489 AC010883.2 chr2 43128819 43131999 +289497 AC010883.3 chr2 43219849 43223227 +289501 ZFP36L2 chr2 43222402 43226606 +289511 LINC01126 chr2 43227210 43228855 +289514 AC010883.1 chr2 43229573 43233394 +289519 THADA chr2 43230836 43596046 +290107 PLEKHH2 chr2 43637260 43767987 +290276 C1GALT1C1L chr2 43675151 43676429 +290284 DYNC2LI1 chr2 43774039 43810010 +290474 ABCG5 chr2 43812472 43838865 +290537 ABCG8 chr2 43831942 43882988 +290594 LRPPRC chr2 43886224 43995989 +290797 AC019129.2 chr2 44167625 44168859 +290800 PPM1B chr2 44167969 44244384 +290919 SLC3A1 chr2 44275458 44321494 +291109 PREPL chr2 44316281 44361862 +291521 CAMKMT chr2 44361947 44772592 +291659 LINC01833 chr2 44921077 44939199 +291676 SIX3-AS1 chr2 44940154 44941873 +291683 SIX3 chr2 44941702 44946071 +291693 AC012354.1 chr2 44954664 44968762 +291699 SIX2 chr2 45005182 45009452 +291709 AC093702.1 chr2 45013214 45013668 +291713 LINC01121 chr2 45164816 45323397 +291748 AC093833.1 chr2 45168583 45169414 +291752 AC009236.2 chr2 45169616 45211673 +291758 AC009236.1 chr2 45173722 45175935 +291762 SRBD1 chr2 45388680 45612165 +291835 PRKCE chr2 45651345 46187990 +291964 U51244.1 chr2 45674701 45675476 +291968 AC017006.2 chr2 46078015 46078828 +291972 AC017006.1 chr2 46166789 46167978 +291976 EPAS1 chr2 46293667 46386697 +292067 LINC01820 chr2 46392291 46394228 +292083 LINC02583 chr2 46429190 46441833 +292101 TMEM247 chr2 46479565 46484425 +292111 ATP6V1E2 chr2 46490750 46542577 +292156 AC018682.2 chr2 46499731 46501278 +292160 RHOQ chr2 46541806 46584688 +292233 AC018682.1 chr2 46568256 46580238 +292237 PIGF chr2 46580937 46617055 +292313 CRIPT chr2 46616416 46630176 +292335 LINC01118 chr2 46698940 46822804 +292358 SOCS5 chr2 46698952 46780245 +292388 LINC01119 chr2 46816697 46859007 +292407 AC016722.1 chr2 46852020 46853496 +292411 AC016722.2 chr2 46899275 46908678 +292415 MCFD2 chr2 46901870 46941855 +292590 TTC7A chr2 46916157 47076137 +292941 AC093732.2 chr2 46956615 46956888 +292944 AC093732.1 chr2 47035279 47040524 +292948 STPG4 chr2 47045538 47155308 +293006 AC073283.1 chr2 47067822 47071204 +293010 CALM2 chr2 47160083 47176921 +293243 EPCAM-DT chr2 47192405 47345074 +293272 AC073283.2 chr2 47225781 47240886 +293288 EPCAM chr2 47345158 47387601 +293384 MSH2 chr2 47402969 47663146 +293695 KCNK12 chr2 47516581 47570939 +293708 AC138655.1 chr2 47527008 47535199 +293719 MSH6 chr2 47695530 47810101 +293967 FBXO11 chr2 47789316 47905793 +294176 AC079807.1 chr2 47905678 47907810 +294186 AC092650.1 chr2 47924181 48314224 +294249 FOXN2 chr2 48314637 48379295 +294299 AC093635.1 chr2 48440043 48440597 +294302 PPP1R21 chr2 48440598 48515391 +294578 STON1 chr2 48529383 48598513 +294634 STON1-GTF2A1L chr2 48529925 48776517 +294743 GTF2A1L chr2 48617798 48733148 +294848 LHCGR chr2 48686774 48755730 +294975 AC009975.1 chr2 48809340 49419013 +294982 FSHR chr2 48962157 49154537 +295080 AC009975.2 chr2 49202126 49451896 +295094 AC009971.1 chr2 49563388 49595126 +295099 NRXN1 chr2 49918503 51225575 +295939 AC068725.1 chr2 50324643 50345598 +295944 AC009234.1 chr2 50620963 50632993 +295950 AC007682.1 chr2 51011777 51016950 +295955 AC007402.1 chr2 51032601 52407917 +295968 AC007402.2 chr2 51441959 51455913 +295973 AC079304.1 chr2 51977787 52022435 +295978 LINC01867 chr2 52370602 52390056 +295983 AC139712.3 chr2 52494688 52500752 +295989 AC010967.1 chr2 52722671 52961452 +296009 AC010967.2 chr2 52864235 52866631 +296013 ASB3 chr2 53532672 53860160 +296219 CHAC2 chr2 53767804 53775196 +296231 ERLEC1 chr2 53787044 53818819 +296331 GPR75 chr2 53852912 53859967 +296341 PSME4 chr2 53864069 53970993 +296575 ACYP2 chr2 53970838 54305300 +296692 AC008280.3 chr2 54082554 54085066 +296696 TSPYL6 chr2 54253178 54256229 +296704 C2orf73 chr2 54330034 54383742 +296806 SPTBN1 chr2 54456317 54671446 +297078 AC092839.1 chr2 54516048 54540697 +297084 AC092839.2 chr2 54545368 54546677 +297088 AC093110.1 chr2 54661011 54680045 +297097 EML6 chr2 54723499 54972025 +297233 AC104781.1 chr2 54747103 54750473 +297238 AC104781.2 chr2 54768492 54801540 +297245 RTN4 chr2 54972187 55112621 +297491 CLHC1 chr2 55172547 55232563 +297655 AC012358.1 chr2 55214387 55216126 +297659 RPS27A chr2 55231903 55235853 +297760 MTIF2 chr2 55236595 55269347 +297951 AC012358.3 chr2 55282350 55346049 +298063 CCDC88A chr2 55287842 55419895 +299876 CFAP36 chr2 55519604 55545879 +300002 PPP4R3B chr2 55547292 55618880 +300126 AC015982.2 chr2 55617909 55618373 +300129 PNPT1 chr2 55634061 55693863 +300366 EFEMP1 chr2 55865967 55924139 +300565 AC011306.1 chr2 55952158 56181652 +300574 MIR217HG chr2 55963191 56047326 +300579 LINC01813 chr2 56077417 56090382 +300583 AC007743.1 chr2 56173534 56185870 +300607 CCDC85A chr2 56183990 56386172 +300625 AC132153.1 chr2 57289648 57380132 +300641 VRK2 chr2 57907629 58159920 +300908 AC068193.1 chr2 58040211 58046700 +300913 FANCL chr2 58159243 58241372 +301128 AC007250.1 chr2 58241349 58241686 +301131 LINC01795 chr2 58275532 58296817 +301146 LINC01122 chr2 58427799 59063766 +301328 LINC01793 chr2 59217708 59279400 +301333 AC007100.1 chr2 59218680 60100200 +301346 AC007179.2 chr2 59238703 59733396 +301455 AC007179.1 chr2 59434552 59442261 +301466 AC007100.2 chr2 59778685 59791656 +301470 AC007132.1 chr2 60057601 60071127 +301476 AC007381.1 chr2 60336446 60439828 +301502 AC007381.2 chr2 60383141 60385794 +301506 BCL11A chr2 60450520 60554467 +301759 AC009970.1 chr2 60495686 60499964 +301764 PAPOLG chr2 60756253 60802086 +301960 LINC01185 chr2 60823069 60881317 +301970 REL chr2 60881521 60931610 +302032 AC010733.2 chr2 60925909 60931610 +302035 PUS10 chr2 60940222 61018259 +302168 PEX13 chr2 61017225 61051990 +302214 KIAA1841 chr2 61065871 61138034 +302520 AC016747.1 chr2 61141592 61144969 +302534 C2orf74 chr2 61145068 61164829 +302612 AC016747.2 chr2 61151433 61162105 +302622 USP34 chr2 61187463 61471087 +303043 AC016747.3 chr2 61199979 61200769 +303046 AC016727.1 chr2 61471188 61484130 +303069 XPO1 chr2 61477849 61538626 +303446 AC016727.3 chr2 61527340 61529160 +303450 FAM161A chr2 61824848 61854143 +303544 CCT4 chr2 61868085 61888671 +303617 AC107081.2 chr2 61868432 61886082 +303621 AC107081.4 chr2 61878940 61881353 +303625 COMMD1 chr2 61888724 62147247 +303691 AC018462.1 chr2 62069447 62146881 +303708 B3GNT2 chr2 62196115 62224731 +303727 AC093159.1 chr2 62463127 62464070 +303731 TMEM17 chr2 62500218 62511894 +303753 AC092155.1 chr2 62533681 62662829 +304008 EHBP1 chr2 62673851 63046487 +304358 AC092567.2 chr2 62817764 62819706 +304362 AC092567.1 chr2 62826064 62858438 +304366 AC007098.1 chr2 62957326 63048640 +304394 OTX1 chr2 63050057 63057836 +304450 AC009501.3 chr2 63106879 63197037 +304455 WDPCP chr2 63119559 63827843 +304754 MDH1 chr2 63588609 63607197 +304946 UGP2 chr2 63840940 63891562 +305391 VPS54 chr2 63892146 64019428 +305562 AC012368.2 chr2 64086353 64088246 +305566 PELI1 chr2 64092652 64144420 +305600 AC012368.1 chr2 64143239 64252859 +305659 LINC00309 chr2 64185078 64205485 +305673 AC114752.1 chr2 64330481 64332801 +305682 AC114752.2 chr2 64338067 64341647 +305686 LGALSL-DT chr2 64395220 64453967 +305700 LGALSL chr2 64453969 64461381 +305768 LINC01805 chr2 64486353 64500904 +305773 AC008074.2 chr2 64522187 64524093 +305776 AFTPH chr2 64524305 64593005 +305907 LINC02579 chr2 64606975 64616556 +305918 SERTAD2 chr2 64631621 64751005 +305933 AC007365.1 chr2 64644612 64646698 +305937 AC007880.1 chr2 64836985 64848264 +305941 LINC01800 chr2 64846130 64863626 +305948 LINC02245 chr2 64901840 65056168 +305969 SLC1A4 chr2 64988477 65023865 +306031 LINC02576 chr2 65030727 65053017 +306040 CEP68 chr2 65056366 65087004 +306098 RAB1A chr2 65070696 65130331 +306182 ACTR2 chr2 65227753 65271253 +306279 SPRED2 chr2 65310851 65432637 +306372 AC012370.1 chr2 65373700 65380685 +306378 AC007389.1 chr2 65436711 66200373 +306439 AC012370.2 chr2 65439838 65456571 +306493 AC007389.3 chr2 65589566 65640177 +306499 AC007389.5 chr2 65623272 65628424 +306504 AC118345.1 chr2 66235377 66236213 +306508 AC092669.1 chr2 66327349 66328984 +306516 LINC01873 chr2 66383306 66392450 +306521 MEIS1-AS3 chr2 66426735 66433470 +306527 MEIS1 chr2 66433452 66573869 +306742 MEIS1-AS2 chr2 66439088 66444221 +306752 LINC01798 chr2 66574030 66731223 +306785 LINC01797 chr2 66696190 66703252 +306803 LINC01799 chr2 66904436 66971462 +306828 LINC01628 chr2 66921510 66922482 +306833 AC007403.1 chr2 67040546 67041966 +306837 LINC01828 chr2 67086446 67311439 +306912 LINC01829 chr2 67123357 67397980 +306949 AC023115.1 chr2 67324627 67325304 +306953 ETAA1 chr2 67397322 67412089 +307020 LINC02831 chr2 67562067 67620545 +307187 AC007422.1 chr2 67565604 67684077 +307191 AC010987.1 chr2 67677499 67680798 +307195 LINC01812 chr2 67796054 67825562 +307200 C1D chr2 68041130 68110948 +307277 WDR92 chr2 68122936 68157549 +307363 PNO1 chr2 68157888 68176238 +307401 PPP3R1 chr2 68178857 68256237 +307453 AC017083.2 chr2 68179833 68180532 +307456 AC017083.1 chr2 68252870 68253848 +307459 CNRIP1 chr2 68284171 68320051 +307497 AC015969.1 chr2 68361214 68365584 +307501 PLEK chr2 68365282 68397453 +307530 FBXO48 chr2 68459422 68467294 +307544 APLF chr2 68467572 68655862 +307650 PROKR1 chr2 68643589 68658247 +307662 ARHGAP25 chr2 68679601 68826833 +307910 LINC01890 chr2 68822855 68837235 +307933 LINC01888 chr2 68832014 68837726 +307943 BMP10 chr2 68860909 68871397 +307953 GKN2 chr2 68945232 68952893 +307986 GKN1 chr2 68974573 68980974 +308008 ANTXR1 chr2 69013178 69249327 +308150 AC114802.1 chr2 69030042 69033637 +308154 GFPT1 chr2 69319769 69387254 +308257 NFU1 chr2 69395750 69437628 +308418 AAK1 chr2 69457997 69674349 +308606 ANXA4 chr2 69644425 69827112 +308761 AC092431.1 chr2 69700192 69713847 +308765 GMCL1 chr2 69829660 69881384 +308814 SNRNP27 chr2 69893956 69905575 +308879 MXD1 chr2 69897688 69942945 +308952 ASPRV1 chr2 69960089 69962265 +308960 PCBP1-AS1 chr2 69962263 70103220 +310539 PCBP1 chr2 70087477 70089203 +310547 AC016700.3 chr2 70089721 70096100 +310552 LINC01816 chr2 70124036 70125317 +310556 C2orf42 chr2 70149880 70248615 +310684 TIA1 chr2 70209444 70248660 +310972 PCYOX1 chr2 70257386 70281185 +311046 SNRPG chr2 70281362 70293740 +311140 FAM136A chr2 70295975 70302090 +311192 AC022201.2 chr2 70301451 70302072 +311196 AC022201.1 chr2 70402934 70422678 +311202 TGFA chr2 70447284 70554193 +311321 TGFA-IT1 chr2 70467385 70468495 +311325 ADD2 chr2 70607618 70768225 +311637 AC005234.2 chr2 70629657 70648761 +311642 AC005234.1 chr2 70687142 70691824 +311646 FIGLA chr2 70777310 70790643 +311662 CLEC4F chr2 70808643 70820599 +311701 CD207 chr2 70830211 70835816 +311719 LINC01143 chr2 70887871 70889959 +311725 VAX2 chr2 70900576 70965373 +311799 ATP6V1B1 chr2 70935900 70965431 +311914 ANKRD53 chr2 70978380 70985499 +311997 TEX261 chr2 70985942 70994873 +312049 AC007040.1 chr2 70994510 71002754 +312053 AC007881.2 chr2 71002531 71064743 +312059 NAGK chr2 71064344 71079808 +312392 AC007881.3 chr2 71067519 71068125 +312395 MCEE chr2 71109684 71130239 +312436 AC007881.4 chr2 71112877 71117406 +312440 MPHOSPH10 chr2 71130632 71150101 +312493 PAIP2B chr2 71182738 71227103 +312507 ZNF638 chr2 71276561 71435069 +312874 AC007878.1 chr2 71373938 71376320 +312878 DYSF chr2 71453722 71686768 +314224 CYP26B1 chr2 72129238 72148038 +314288 EXOC6B chr2 72175984 72826041 +314486 SPR chr2 72887382 72892158 +314502 EMX1 chr2 72916260 72936071 +314543 AC012366.1 chr2 72932974 72934355 +314547 SFXN5 chr2 72942036 73075619 +314808 RAB11FIP5 chr2 73073382 73156721 +314856 AC010913.1 chr2 73113018 73115907 +314862 NOTO chr2 73202574 73212513 +314874 SMYD5 chr2 73214222 73227221 +314983 PRADC1 chr2 73228010 73233239 +315007 CCT7 chr2 73233420 73253021 +315207 FBXO41 chr2 73254682 73284431 +315307 EGR4 chr2 73290929 73293701 +315326 AC069404.1 chr2 73305941 73307890 +315330 AC074008.2 chr2 73352610 73385677 +315336 ALMS1 chr2 73385758 73625166 +315645 ALMS1-IT1 chr2 73456764 73459482 +315649 AC074008.1 chr2 73469525 73471030 +315652 NAT8 chr2 73640723 73642422 +315662 TPRKB chr2 73729104 73737400 +315747 AC092653.1 chr2 73750256 73750786 +315750 DUSP11 chr2 73762184 73780157 +315821 C2orf78 chr2 73784189 73817147 +315833 AC073046.4 chr2 73823154 73824593 +315837 STAMBP chr2 73828916 73873659 +316024 AC073046.3 chr2 73834422 73856965 +316029 ACTG2 chr2 73892314 73919865 +316170 DGUOK chr2 73926826 73958961 +316255 DGUOK-AS1 chr2 73947322 73981441 +316268 AC073046.1 chr2 73985132 73986343 +316272 TET3 chr2 73986404 74108176 +316332 AC073263.1 chr2 74123965 74135640 +316341 BOLA3 chr2 74135400 74147912 +316378 BOLA3-AS1 chr2 74148007 74151952 +316396 MOB1A chr2 74152528 74178898 +316438 AC073263.2 chr2 74196698 74198560 +316441 MTHFD2 chr2 74198610 74217565 +316545 SLC4A5 chr2 74216242 74343414 +317057 DCTN1 chr2 74361154 74392087 +317776 DCTN1-AS1 chr2 74385474 74393882 +317813 C2orf81 chr2 74414176 74421591 +317869 AC005041.4 chr2 74415422 74416781 +317872 WDR54 chr2 74421678 74425755 +318001 RTKN chr2 74425835 74442422 +318126 INO80B chr2 74455087 74457944 +318216 WBP1 chr2 74458400 74460891 +318321 MOGS chr2 74461057 74465410 +318515 AC005041.5 chr2 74465339 74472961 +318519 MRPL53 chr2 74471982 74472687 +318546 CCDC142 chr2 74471986 74483408 +318646 TTC31 chr2 74483073 74494886 +318845 LBX2 chr2 74497517 74503316 +318882 AC005041.3 chr2 74501717 74502365 +318885 LBX2-AS1 chr2 74502595 74504678 +318891 PCGF1 chr2 74505043 74507695 +318950 TLX2 chr2 74513463 74517148 +318983 DQX1 chr2 74518131 74526281 +319093 AUP1 chr2 74526645 74529760 +319192 HTRA2 chr2 74529377 74533348 +319294 LOXL3 chr2 74532258 74555690 +319477 DOK1 chr2 74549026 74557554 +319571 M1AP chr2 74557883 74648338 +319698 SEMA4F chr2 74654228 74683853 +319902 AC007387.3 chr2 74750173 74778742 +319907 AC007387.2 chr2 74754773 74760227 +319912 AC019069.1 chr2 74832655 74833987 +319915 HK2 chr2 74833981 74893359 +320001 LINC01291 chr2 74918148 74938418 +320014 AC104135.1 chr2 74919555 74924846 +320018 LINC01293 chr2 74940258 74942670 +320022 POLE4 chr2 74958643 74970128 +320059 TACR1 chr2 75046463 75199520 +320091 AC007681.1 chr2 75154366 75189949 +320096 EVA1A chr2 75469302 75569722 +320196 AC007099.2 chr2 75474453 75482579 +320200 AC007099.1 chr2 75524068 75542706 +320205 MRPL19 chr2 75646783 75690851 +320291 GCFC2 chr2 75652000 75710985 +320515 AC005034.3 chr2 75660462 75662208 +320518 AC005034.5 chr2 75669989 75670454 +320521 AC005034.2 chr2 75697583 75697996 +320524 AC005034.6 chr2 75710782 75728123 +320528 AC005034.4 chr2 75719120 75720018 +320531 AC110614.1 chr2 75799974 76208703 +320538 AC073091.3 chr2 76185020 76399490 +320559 AC073091.4 chr2 76197855 76252927 +320565 AC068616.2 chr2 76633365 76673346 +320570 AC068616.3 chr2 76684975 76698996 +320574 AC068616.1 chr2 76691007 76692489 +320578 LRRTM4 chr2 76747719 77593319 +320646 AC079117.2 chr2 76893894 76897247 +320651 AC079117.1 chr2 76985965 77009791 +320657 AC013716.1 chr2 77210587 77327103 +320662 AC012494.1 chr2 77652025 78290469 +320674 AC084149.1 chr2 77672215 77673792 +320678 LINC01851 chr2 77915870 77918011 +320691 AC012494.2 chr2 78088729 78127806 +320758 AC092660.1 chr2 78597911 78599406 +320762 AC092604.1 chr2 78880713 78931146 +320769 REG3G chr2 79025686 79028505 +320826 REG1B chr2 79085023 79088019 +320867 REG1A chr2 79120362 79123409 +320897 REG3A chr2 79157003 79159753 +320953 AC011754.1 chr2 79158374 79185523 +320958 CTNNA2 chr2 79185231 80648861 +321331 AC011754.2 chr2 79269905 79292878 +321338 AC010975.1 chr2 79492704 79513900 +321356 AC016716.2 chr2 80028012 80030551 +321361 LRRTM1 chr2 80288351 80304752 +321427 AC008067.1 chr2 80572681 80618777 +321470 AC012355.1 chr2 80699388 80870190 +321477 LINC01815 chr2 81461358 81467468 +321504 AC079896.1 chr2 81983272 82005700 +321511 AC010105.1 chr2 82476825 82538711 +321521 AC098817.1 chr2 82831234 82866508 +321526 LINC01809 chr2 83522814 83523502 +321530 AC106874.1 chr2 84315108 84350774 +321535 SUCLG1 chr2 84423528 84460045 +321631 DNAH6 chr2 84516455 84819589 +321987 TRABD2A chr2 84821650 84907008 +322068 TMSB10 chr2 84905656 84906671 +322080 AC022210.2 chr2 84926019 84966685 +322093 KCMF1 chr2 84971093 85059472 +322144 LINC01964 chr2 85061213 85067347 +322151 TCF7L1 chr2 85133392 85310387 +322202 TCF7L1-IT1 chr2 85186409 85187253 +322206 TGOLN2 chr2 85318020 85328296 +322287 RETSAT chr2 85341955 85354531 +322383 ELMOD3 chr2 85354394 85391752 +322812 AC062037.2 chr2 85387074 85387146 +322815 CAPG chr2 85394753 85418432 +323028 AC062037.3 chr2 85418504 85426724 +323069 SH2D6 chr2 85418931 85437029 +323284 PARTICL chr2 85537462 85538666 +323287 MAT2A chr2 85539168 85545281 +323350 GGCX chr2 85544720 85561547 +323481 VAMP8 chr2 85561562 85582031 +323517 VAMP5 chr2 85584431 85593406 +323532 RNF181 chr2 85595725 85597708 +323599 TMEM150A chr2 85598547 85603196 +323746 USP39 chr2 85602856 85649283 +324046 C2orf68 chr2 85605254 85612066 +324092 SFTPB chr2 85657314 85668741 +324244 GNLY chr2 85685175 85698854 +324351 ATOH8 chr2 85751344 85791383 +324379 AC105053.1 chr2 85815130 85825391 +324384 ST3GAL5 chr2 85837120 85905199 +325426 ST3GAL5-AS1 chr2 85889151 85891136 +325433 AC012511.1 chr2 85904279 85904727 +325436 AC012511.2 chr2 85934535 85937548 +325440 POLR1A chr2 86020216 86106155 +325648 PTCD3 chr2 86106223 86142157 +325863 IMMT chr2 86143932 86195770 +326131 AC009309.1 chr2 86195590 86196049 +326134 MRPL35 chr2 86199355 86213790 +326190 REEP1 chr2 86213993 86338083 +326373 KDM3A chr2 86440647 86492716 +326660 CHMP3 chr2 86503430 86563479 +326740 AC015971.1 chr2 86562070 86618766 +326759 RNF103 chr2 86603398 86623866 +326797 RMND5A chr2 86720291 86778041 +326835 CD8A chr2 86784610 86808396 +326905 CD8B chr2 86815339 86861924 +327004 RGPD1 chr2 86907953 87013976 +327245 PLGLB1 chr2 87002559 87021852 +327316 AC092651.3 chr2 87075653 87118267 +327322 LINC01955 chr2 87249095 87253750 +327326 AC068279.2 chr2 87311460 87348728 +327331 IGKV3OR2-268 chr2 87338511 87339035 +327338 LINC01943 chr2 87439523 87459044 +327348 CYTOR chr2 87454781 87636740 +327499 AC133644.2 chr2 87477495 87478034 +327502 PLGLB2 chr2 87748087 87759476 +327535 RGPD2 chr2 87755960 87825952 +327639 AC108479.3 chr2 88016780 88021451 +327650 KRCC1 chr2 88027205 88064252 +327673 SMYD1 chr2 88067825 88113384 +327738 FABP1 chr2 88122982 88128062 +327771 THNSL2 chr2 88170295 88186636 +327885 FOXI3 chr2 88446787 88452693 +327895 TEX37 chr2 88524649 88529585 +327909 AC104134.1 chr2 88538720 88575610 +327914 EIF2AK3 chr2 88556741 88627464 +328052 EIF2AK3-DT chr2 88627539 88631821 +328058 AC062029.1 chr2 88690177 88691464 +328062 RPIA chr2 88691673 88750929 +328086 IGKC chr2 88857161 88857683 +328092 IGKJ5 chr2 88860568 88860605 +328096 IGKJ4 chr2 88860886 88860922 +328100 IGKJ3 chr2 88861221 88861258 +328104 IGKJ2 chr2 88861525 88861563 +328108 IGKJ1 chr2 88861886 88861923 +328112 IGKV4-1 chr2 88885397 88886153 +328120 IGKV5-2 chr2 88897232 88897784 +328128 IGKV7-3 chr2 88915081 88915378 +328131 IGKV2-4 chr2 88931666 88932380 +328135 IGKV1-5 chr2 88947301 88947957 +328143 IGKV1-6 chr2 88966262 88966767 +328151 IGKV3-7 chr2 88978468 88979081 +328159 IGKV1-8 chr2 88992409 88992931 +328167 IGKV1-9 chr2 89009982 89010515 +328175 IGKV2-10 chr2 89019992 89020686 +328179 IGKV3-11 chr2 89027171 89027731 +328187 IGKV1-12 chr2 89040224 89040745 +328195 IGKV1-13 chr2 89045995 89046466 +328199 IGKV2-14 chr2 89078010 89078784 +328203 IGKV3-15 chr2 89085177 89085787 +328211 IGKV1-16 chr2 89099859 89100361 +328219 IGKV1-17 chr2 89117342 89117844 +328227 IGKV2-18 chr2 89128724 89129483 +328231 IGKV2-19 chr2 89134975 89135257 +328234 IGKV3-20 chr2 89142574 89143160 +328242 IGKV6-21 chr2 89159751 89160366 +328250 IGKV1-22 chr2 89170775 89171212 +328254 IGKV2-23 chr2 89172022 89172553 +328258 IGKV2-24 chr2 89176328 89177160 +328266 IGKV3-25 chr2 89192500 89192752 +328269 IGKV2-26 chr2 89196096 89196829 +328273 IGKV1-27 chr2 89213423 89213928 +328281 IGKV2-28 chr2 89221698 89222461 +328289 IGKV2-29 chr2 89234174 89234912 +328293 IGKV2-30 chr2 89244781 89245596 +328301 IGKV3-31 chr2 89252211 89252736 +328305 IGKV1-32 chr2 89253571 89254015 +328309 IGKV1-33 chr2 89266494 89268506 +328322 IGKV3-34 chr2 89275298 89275787 +328326 IGKV1-35 chr2 89286689 89286973 +328329 IGKV2-36 chr2 89295233 89295455 +328332 IGKV1-37 chr2 89297264 89297785 +328340 IGKV2-38 chr2 89309898 89310144 +328343 IGKV1-39 chr2 89319625 89320146 +328351 IGKV2-40 chr2 89330110 89330429 +328358 IGKV2D-40 chr2 89851791 89852497 +328368 IGKV1D-39 chr2 89862482 89862981 +328376 IGKV2D-38 chr2 89872463 89872702 +328379 IGKV1D-37 chr2 89884740 89885216 +328386 IGKV2D-36 chr2 89887022 89887247 +328389 IGKV1D-35 chr2 89895502 89895772 +328392 IGKV3D-34 chr2 89906757 89907246 +328396 IGKV1D-33 chr2 89913982 89916052 +328409 IGKV1D-32 chr2 89928422 89928867 +328413 IGKV3D-31 chr2 89929701 89930202 +328417 IGKV2D-30 chr2 89936859 89937679 +328425 IGKV2D-29 chr2 89947512 89948279 +328437 IGKV2D-28 chr2 89959979 89960754 +328448 IGKV1D-27 chr2 89968867 89969335 +328452 IGKV2D-26 chr2 89985922 89986702 +328460 IGKV3D-25 chr2 89989987 89990221 +328463 IGKV2D-24 chr2 90004797 90005629 +328471 IGKV2D-23 chr2 90009402 90009927 +328475 IGKV1D-22 chr2 90010741 90011184 +328479 IGKV6D-21 chr2 90021567 90022185 +328487 IGKV3D-20 chr2 90038848 90039479 +328495 IGKV2D-19 chr2 90046796 90047057 +328498 IGKV2D-18 chr2 90052581 90053372 +328502 IGKV6D-41 chr2 90069662 90070238 +328510 IGKV1D-17 chr2 90082635 90083291 +328518 IGKV1D-16 chr2 90100236 90100738 +328526 IGKV3D-15 chr2 90114838 90115402 +328534 IGKV2D-14 chr2 90121786 90122564 +328538 IGKV1D-13 chr2 90154073 90154574 +328546 IGKV1D-12 chr2 90159840 90160335 +328554 IGKV3D-11 chr2 90172802 90173414 +328562 IGKV2D-10 chr2 90179889 90180587 +328566 IGKV1D-42 chr2 90190193 90190681 +328574 IGKV1D-43 chr2 90209873 90210529 +328582 IGKV1D-8 chr2 90220727 90221384 +328590 IGKV3D-7 chr2 90234812 90235370 +328598 IGKV1OR2-118 chr2 90315366 90315836 +328602 AC233263.6 chr2 90365737 90367699 +328605 AC233266.2 chr2 91580336 91580863 +328608 AC027612.5 chr2 91759462 91767701 +328613 IGKV1OR2-1 chr2 91817771 91818248 +328617 AL845331.2 chr2 94588522 94604573 +328636 TEKT4 chr2 94871430 94876823 +328661 AC103563.7 chr2 95025193 95026709 +328666 MAL chr2 95025677 95053992 +328711 AC103563.2 chr2 95051395 95053176 +328715 AC103563.9 chr2 95067074 95076900 +328719 MRPS5 chr2 95085369 95149434 +328807 ZNF514 chr2 95145000 95165413 +328851 ZNF2 chr2 95165432 95184317 +328919 AC092835.1 chr2 95207535 95259774 +328952 PROM2 chr2 95274449 95291308 +329216 KCNIP3 chr2 95297327 95386077 +329302 FAHD2A chr2 95402708 95416616 +329374 TRIM43B chr2 95476967 95484731 +329410 AC009237.14 chr2 95525109 95526702 +329413 AC009237.15 chr2 95537969 95538469 +329416 TRIM43 chr2 95592001 95599778 +329436 AC008268.1 chr2 95660588 95668727 +329454 LINC00342 chr2 95807052 95835003 +329510 ANKRD36C chr2 95836919 95991831 +329952 GPAT2 chr2 96021946 96039451 +330202 ADRA2B chr2 96112876 96116571 +330210 ASTL chr2 96123850 96138436 +330237 DUSP2 chr2 96143169 96145440 +330254 AC012307.1 chr2 96145602 96147012 +330258 STARD7 chr2 96184859 96208825 +330310 STARD7-AS1 chr2 96208403 96243353 +330333 TMEM127 chr2 96248516 96265994 +330371 CIAO1 chr2 96266159 96274173 +330405 SNRNP200 chr2 96274338 96321271 +330627 AC021188.1 chr2 96307263 96321731 +330631 ITPRIPL1 chr2 96325331 96330517 +330673 NCAPH chr2 96335766 96377091 +330865 NEURL3 chr2 96497646 96508109 +330912 AC013270.1 chr2 96527940 96532306 +330917 ARID5A chr2 96536743 96552634 +330989 KANSL3 chr2 96593170 96642787 +331528 FER1L5 chr2 96642737 96704887 +332124 LMAN2L chr2 96705929 96740064 +332279 CNNM4 chr2 96760902 96811874 +332315 CNNM3-DT chr2 96812239 96813657 +332319 CNNM3 chr2 96816245 96835382 +332373 ANKRD23 chr2 96824526 96857934 +332467 ANKRD39 chr2 96836611 96858016 +332504 SEMA4C chr2 96859718 96870757 +332591 FAM178B chr2 96875882 96986580 +332669 AC092636.1 chr2 96912549 96917272 +332676 IGKV2OR2-1 chr2 97046588 97046891 +332679 IGKV2OR2-2 chr2 97050729 97051028 +332682 IGKV1OR2-3 chr2 97060128 97060415 +332685 FAHD2B chr2 97083583 97094882 +332747 ANKRD36 chr2 97113218 97264434 +333299 AC159540.2 chr2 97281356 97291849 +333336 AC159540.1 chr2 97301729 97304151 +333340 IGKV1OR2-9 chr2 97322137 97322423 +333343 IGKV2OR2-10 chr2 97331533 97331843 +333346 IGKV2OR2-7D chr2 97335671 97335974 +333349 IGKV3OR2-5 chr2 97348899 97349179 +333352 IGKV1OR2-6 chr2 97355059 97355335 +333355 IGKV2OR2-7 chr2 97372532 97372835 +333358 IGKV2OR2-8 chr2 97376674 97376973 +333361 IGKV1OR2-11 chr2 97386082 97386368 +333364 AC092683.1 chr2 97416165 97433527 +333472 AC092683.2 chr2 97421075 97434847 +333483 ANKRD36B chr2 97492663 97589965 +333873 AC017099.2 chr2 97618638 97638417 +333881 COX5B chr2 97646062 97648383 +333910 ACTR1B chr2 97655939 97664044 +333949 C2orf92 chr2 97664217 97703064 +334492 ZAP70 chr2 97713560 97739862 +334584 TMEM131 chr2 97756333 97995948 +334740 VWA3B chr2 98087116 98313299 +335232 AC092675.1 chr2 98331389 98356005 +335247 CNGA3 chr2 98346155 98398601 +335331 AC092675.2 chr2 98346995 98351140 +335335 INPP4A chr2 98444854 98594390 +335659 COA5 chr2 98599314 98608515 +335693 UNC50 chr2 98608579 98618515 +335762 MGAT4A chr2 98619106 98731132 +335934 LINC02611 chr2 98761098 98775361 +335985 KIAA1211L chr2 98793846 98936259 +336076 TSGA10 chr2 98997261 99154964 +336368 C2orf15 chr2 99141485 99151487 +336413 AC079447.1 chr2 99141485 99322741 +336452 LIPT1 chr2 99154955 99163157 +336519 MITD1 chr2 99161427 99181058 +336621 MRPL30 chr2 99181152 99199561 +336682 LYG2 chr2 99242246 99255282 +336779 LYG1 chr2 99284238 99304742 +336820 TXNDC9 chr2 99318982 99340702 +336913 EIF5B chr2 99337371 99401326 +337033 REV1 chr2 99400475 99490035 +337269 AC018690.1 chr2 99405218 99405843 +337272 AFF3 chr2 99545419 100192428 +337788 AC092667.1 chr2 100104919 100107504 +337791 LINC01104 chr2 100208254 100251484 +337800 LONRF2 chr2 100273291 100322733 +337859 CHST10 chr2 100391860 100417668 +337995 NMS chr2 100470482 100483280 +338021 PDCL3 chr2 100562993 100576739 +338061 LINC01849 chr2 100603752 100611542 +338079 AC092845.1 chr2 100642444 100652567 +338084 LINC01868 chr2 100669892 100676038 +338088 AC092168.1 chr2 100722221 100722882 +338092 AC092168.3 chr2 100739958 100747391 +338096 NPAS2 chr2 100820139 100996829 +338246 AC092168.2 chr2 100822661 100847220 +338251 AC016738.2 chr2 100970767 100977766 +338272 AC016738.1 chr2 100993676 101002244 +338276 RPL31 chr2 101002229 101024032 +338409 TBC1D8 chr2 101007617 101252866 +338533 TBC1D8-AS1 chr2 101151660 101155412 +338537 CNOT11 chr2 101252886 101270316 +338570 RNF149 chr2 101271219 101308701 +338623 CREG2 chr2 101345550 101387503 +338645 RFX8 chr2 101397359 101475112 +338793 LINC01870 chr2 101479390 101486822 +338798 AC093894.1 chr2 101535601 101539077 +338802 AC093894.2 chr2 101551592 101567901 +338808 MAP4K4 chr2 101696850 101894689 +339658 LINC01127 chr2 101962056 101987167 +339678 IL1R2 chr2 101991960 102028544 +339776 AC007271.1 chr2 102037963 102058190 +339784 IL1R1 chr2 102064544 102179874 +340058 IL1R1-AS1 chr2 102172621 102182108 +340063 IL1RL2 chr2 102187006 102240002 +340141 IL1RL1 chr2 102311502 102352037 +340280 IL18R1 chr2 102311529 102398775 +340379 IL18RAP chr2 102418689 102452565 +340446 AC007278.2 chr2 102433957 102435340 +340450 AC007278.1 chr2 102438713 102440475 +340455 SLC9A4 chr2 102473226 102533972 +340488 SLC9A2 chr2 102619553 102711355 +340528 MFSD9 chr2 102714630 102736888 +340635 TMEM182 chr2 102736905 103019900 +340765 LINC01796 chr2 102873183 102895780 +340788 LINC01935 chr2 102967408 102984429 +340794 AC108051.1 chr2 102987323 102988565 +340799 AC073987.1 chr2 103109759 103176260 +340805 AC011593.1 chr2 103362082 103403712 +340810 AC013727.1 chr2 103855829 103869651 +340822 AC013727.2 chr2 103856970 103880209 +340832 LINC01965 chr2 103874310 104077778 +340859 AC096554.1 chr2 104125268 104147229 +340866 AC068535.1 chr2 104406471 104416720 +340884 LINC01831 chr2 104412146 104414195 +340895 AC068535.2 chr2 104423039 104429454 +340901 LINC01102 chr2 104430130 104532747 +341080 LINC01103 chr2 104488458 104510509 +341088 AC013402.2 chr2 104580821 104581890 +341092 AC013402.3 chr2 104583138 104621767 +341100 PANTR1 chr2 104656135 104853183 +341148 AC013402.1 chr2 104659337 104666858 +341165 AC068057.1 chr2 104702650 104705813 +341181 LINC01114 chr2 104746638 104757719 +341195 AC018730.1 chr2 104853285 104927722 +341221 POU3F3 chr2 104854115 104858574 +341229 LINC01159 chr2 104865407 104872595 +341248 AC010884.2 chr2 104928803 104936467 +341252 AC010884.1 chr2 104936241 105038496 +341257 MRPS9 chr2 105038069 105099960 +341305 AC104655.1 chr2 105092368 105103036 +341330 LINC01918 chr2 105144113 105145424 +341341 GPR45 chr2 105241743 105243467 +341349 AC012360.2 chr2 105249404 105249794 +341352 TGFBRAP1 chr2 105264391 105329735 +341438 AC012360.1 chr2 105324210 105330529 +341444 AC012360.3 chr2 105334027 105337475 +341447 C2orf49 chr2 105337532 105349211 +341476 FHL2 chr2 105357712 105438513 +341673 AC108058.1 chr2 105363038 105378839 +341683 AC018802.1 chr2 105600703 105610487 +341687 AC018802.2 chr2 105601146 105636637 +341691 NCK2 chr2 105744912 105894274 +341764 AC010978.1 chr2 105846534 105857177 +341788 AC009505.1 chr2 105874509 105962386 +341804 ECRG4 chr2 106063246 106078155 +341857 UXS1 chr2 106093303 106194339 +342064 AC018878.1 chr2 106179542 106183797 +342068 RGPD3 chr2 106391290 106468376 +342171 CD8B2 chr2 106487364 106544297 +342206 AC108868.2 chr2 106521563 106544297 +342213 AC108868.1 chr2 106521903 106538079 +342218 ST6GAL2 chr2 106801600 106887108 +342286 ST6GAL2-IT1 chr2 106822923 106825031 +342290 AC016994.1 chr2 106834464 106841207 +342294 AC005040.2 chr2 106933739 106996534 +342307 LINC01789 chr2 107254691 107365873 +342320 AC096669.1 chr2 107362282 107407329 +342333 LINC01885 chr2 107382715 107748270 +342349 LINC01886 chr2 107529292 107556499 +342379 AC064869.1 chr2 107698737 107746941 +342385 GACAT1 chr2 107754112 107822129 +342397 RGPD4-AS1 chr2 107823063 107826891 +342419 RGPD4 chr2 107826937 107890841 +342471 SLC5A7 chr2 107986523 108013994 +342518 LINC01593 chr2 108049200 108052755 +342523 LINC01594 chr2 108167125 108217886 +342542 SULT1C3 chr2 108247195 108265351 +342561 SULT1C2 chr2 108288639 108309915 +342697 SULT1C4 chr2 108377911 108388989 +342735 GCC2 chr2 108448561 108509415 +342936 GCC2-AS1 chr2 108507515 108534196 +342944 LIMS1 chr2 108534355 108687246 +343174 LIMS1-AS1 chr2 108676795 108678601 +343179 RANBP2 chr2 108719482 108785809 +343272 CCDC138 chr2 108786757 108885477 +343423 EDAR chr2 108894471 108989372 +343509 SH3RF3-AS1 chr2 109127327 109128930 +343512 SH3RF3 chr2 109129205 109504634 +343538 SEPTIN10 chr2 109542799 109614143 +343770 AC011753.2 chr2 109594693 109605698 +343774 SOWAHC chr2 109614364 109618990 +343782 AC074387.1 chr2 109758799 109760364 +343786 RGPD5 chr2 109792758 109857705 +344012 LIMS3 chr2 109898428 109924868 +344089 LINC01123 chr2 109987063 109996140 +344098 MALL chr2 110083870 110116566 +344136 NPHP1 chr2 110122311 110205066 +344435 MTLN chr2 110211529 110245420 +344479 LINC01106 chr2 110375138 110384442 +344494 LIMS4 chr2 110446640 110473075 +344561 AC112229.2 chr2 110449242 110451064 +344566 RGPD6 chr2 110513812 110577185 +344741 AC226101.1 chr2 110610916 110612404 +344745 BUB1 chr2 110637528 110678063 +345052 AC114776.1 chr2 110709575 110716595 +345056 ACOXL chr2 110732573 111118222 +345255 MIR4435-2HG chr2 111036776 111523376 +345626 ACOXL-AS1 chr2 111098345 111116407 +345638 BCL2L11 chr2 111119378 111168445 +345960 AC108463.2 chr2 111195963 111206494 +345964 AC108463.3 chr2 111210995 111212476 +345967 AC068491.2 chr2 111265283 111279880 +345971 AC068491.3 chr2 111266868 111267473 +345974 AC017002.6 chr2 111429324 111699033 +345990 AC017002.5 chr2 111468810 111637967 +345994 AC017002.3 chr2 111491273 111570974 +346002 AC017002.1 chr2 111491943 111494811 +346006 AC017002.2 chr2 111607841 111612518 +346010 ANAPC1 chr2 111611639 111884690 +346273 MERTK chr2 111898607 112029561 +346546 AC093675.1 chr2 112039378 112055337 +346550 TMEM87B chr2 112055269 112119318 +346703 AC093675.2 chr2 112061084 112063709 +346707 FBLN7 chr2 112138385 112188218 +346813 ZC3H8 chr2 112211529 112255136 +346911 AC092645.2 chr2 112239621 112244375 +346915 ZC3H6 chr2 112275597 112340063 +346982 RGPD8 chr2 112368369 112434488 +347178 TTL chr2 112482156 112541739 +347208 POLR1B chr2 112541915 112577150 +347510 CHCHD5 chr2 112584240 112589275 +347558 AC012442.2 chr2 112589040 112614431 +347562 AC012442.1 chr2 112590796 112591939 +347566 AC079922.2 chr2 112641832 112645720 +347590 SLC20A1 chr2 112645939 112663825 +347685 NT5DC4 chr2 112721486 112742879 +347750 CKAP2L chr2 112736349 112764664 +347818 IL1A chr2 112773915 112784590 +347838 AC079753.2 chr2 112817076 112824457 +347842 IL1B chr2 112829751 112836816 +347919 IL37 chr2 112912971 112918882 +347984 IL36G chr2 112973203 112985658 +348024 IL36A chr2 113005459 113008044 +348038 IL36B chr2 113022089 113052867 +348071 IL36RN chr2 113058638 113065382 +348120 IL1F10 chr2 113067970 113075843 +348152 IL1RN chr2 113107214 113134016 +348254 PSD4 chr2 113157325 113209396 +348423 AC016683.1 chr2 113171535 113175360 +348430 PAX8-AS1 chr2 113211421 113276581 +348590 PAX8 chr2 113215997 113278921 +348798 AC016745.1 chr2 113325372 113425548 +348807 IGKV1OR2-108 chr2 113406396 113406872 +348814 AC016745.2 chr2 113432600 113436042 +348817 CBWD2 chr2 113437691 113496204 +349027 FOXD4L1 chr2 113498665 113501155 +349035 LINC01961 chr2 113512222 113515488 +349049 PGM5P4-AS1 chr2 113526836 113542694 +349074 FAM138B chr2 113577382 113578852 +349082 AL078621.4 chr2 113582354 113583152 +349086 RABL2A chr2 113627229 113643396 +349328 AC017074.2 chr2 113669166 113673191 +349334 AC017074.1 chr2 113677702 113704078 +349339 SLC35F5 chr2 113705011 113756693 +349527 AC104653.2 chr2 113829390 113831119 +349531 AC104653.1 chr2 113831049 113843356 +349539 AC110769.2 chr2 113888203 113889750 +349542 ACTR3 chr2 113890063 113962596 +349657 LINC01191 chr2 113970719 114007304 +349678 AC110769.1 chr2 113979909 113983258 +349682 AC010982.2 chr2 114114679 114117390 +349686 AC010982.1 chr2 114122274 114123293 +349690 DPP10 chr2 114442299 115845752 +350019 DPP10-AS3 chr2 114828432 114833548 +350023 DPP10-AS2 chr2 114833830 114835588 +350027 AC093610.1 chr2 115079354 115099092 +350034 DPP10-AS1 chr2 115126622 115161384 +350066 AC016721.1 chr2 115835129 115940291 +350071 AC064856.1 chr2 117536387 117539464 +350075 AC009312.1 chr2 117754139 117804174 +350085 DDX18 chr2 117814691 117832377 +350154 AC009404.1 chr2 117833937 117841658 +350173 CCDC93 chr2 117915478 118014133 +350335 AC009303.2 chr2 117995397 118055033 +350375 AC009303.3 chr2 117998745 117999480 +350378 INSIG2 chr2 118088452 118110997 +350456 THORLNC chr2 118132128 118222250 +350489 LINC01956 chr2 118766965 118835110 +350499 EN1 chr2 118842171 118847678 +350512 MARCO chr2 118942166 118994660 +350566 AC013457.1 chr2 118949306 118952983 +350570 C1QL2 chr2 119156243 119158751 +350580 STEAP3 chr2 119223831 119265652 +350647 STEAP3-AS1 chr2 119244422 119270714 +350656 C2orf76 chr2 119302225 119366834 +350742 DBI chr2 119366921 119372560 +350881 TMEM37 chr2 119429901 119438504 +350910 SCTR chr2 119439843 119525301 +350994 AC013275.1 chr2 119476428 119487346 +351005 CFAP221 chr2 119544432 119662251 +351329 TMEM177 chr2 119679167 119686507 +351378 PTPN4 chr2 119759922 119984899 +351585 EPB41L5 chr2 120013077 120179119 +351851 AC012363.1 chr2 120174885 120216544 +351856 TMEM185B chr2 120217479 120223400 +351864 RALB chr2 120240064 120294710 +351962 AC012363.2 chr2 120319007 120326298 +351967 INHBB chr2 120346136 120351803 +351977 AC073257.2 chr2 120542905 120545249 +351987 AC073257.1 chr2 120552481 120558119 +352003 AC018866.1 chr2 120686635 120710517 +352010 GLI2 chr2 120735623 120992653 +352260 AC017033.1 chr2 120866378 120867403 +352264 AC067960.1 chr2 121081437 121088726 +352268 AC079988.1 chr2 121178327 121182580 +352272 TFCP2L1 chr2 121216587 121285202 +352313 CLASP1 chr2 121337776 121649587 +352952 AC012447.1 chr2 121530422 121532705 +352956 NIFK-AS1 chr2 121649320 121728563 +353015 NIFK chr2 121726945 121736911 +353086 TSN chr2 121737103 121767853 +353225 LINC01823 chr2 121779133 121809962 +353329 AC011246.1 chr2 121902501 122887691 +353346 AC073632.1 chr2 122503366 122505118 +353350 AC062020.1 chr2 123065321 123067722 +353354 LINC01826 chr2 123066151 123073481 +353359 AC073409.2 chr2 123421486 123438693 +353363 AC073409.1 chr2 123443266 123444445 +353367 AC079154.1 chr2 124011984 124025173 +353376 CNTNAP5 chr2 124025287 124915287 +353436 AC019159.2 chr2 124695242 124696530 +353440 AC097499.2 chr2 125665331 125717150 +353446 LINC01889 chr2 125710969 125765842 +353450 LINC01941 chr2 126109761 126118023 +353460 AC142116.2 chr2 126154583 126203372 +353464 AC023347.1 chr2 126308494 126343992 +353473 GYPC chr2 126656133 126696667 +353519 TEX51 chr2 126898864 126902097 +353662 AC012508.2 chr2 127024252 127025723 +353665 AC012508.3 chr2 127024866 127033948 +353671 AC012508.1 chr2 127025211 127029686 +353674 BIN1 chr2 127048027 127107288 +354097 AC110926.2 chr2 127141976 127143793 +354101 CYP27C1 chr2 127183832 127220313 +354167 ERCC3 chr2 127257290 127294176 +354574 AC068282.1 chr2 127294212 127375075 +354585 MAP3K2 chr2 127298730 127388465 +354673 MAP3K2-DT chr2 127388184 127400580 +354685 AC068282.2 chr2 127406731 127408221 +354689 PROC chr2 127418427 127429246 +354816 IWS1 chr2 127436207 127526886 +354916 AC010976.1 chr2 127455394 127514623 +355086 MYO7B chr2 127535802 127637729 +355403 AC010976.2 chr2 127625997 127626848 +355406 LIMS2 chr2 127638381 127681786 +355707 GPR17 chr2 127645864 127652639 +355757 WDR33 chr2 127701027 127811187 +355873 SFT2D3 chr2 127701497 127705242 +355881 POLR2D chr2 127843553 127858155 +355922 AMMECR1L chr2 127861630 127885922 +355965 AC012306.2 chr2 127886556 127887185 +355968 AC012306.3 chr2 127888829 127892732 +355972 SAP130 chr2 127941217 128028120 +356187 UGGT1 chr2 128091200 128195677 +356456 HS6ST1 chr2 128236716 128318868 +356476 AC012451.1 chr2 128580491 128581576 +356480 AC068483.1 chr2 129063846 129071725 +356484 LINC01854 chr2 129242173 129273848 +356491 LINC02572 chr2 129825126 129877664 +356517 AC079776.5 chr2 129877896 129884441 +356524 LINC01856 chr2 129923177 129946703 +356530 RAB6C chr2 129979666 129982738 +356538 POTEF chr2 130073535 130129222 +356596 AC018865.1 chr2 130107684 130109741 +356600 CCDC74B chr2 130139287 130145134 +356736 SMPD4 chr2 130151392 130182750 +357163 MZT2B chr2 130181737 130190729 +357233 TUBA3E chr2 130191745 130198439 +357249 CCDC115 chr2 130337933 130342699 +357317 IMP4 chr2 130342225 130347810 +357507 PTPN18 chr2 130356045 130375405 +357668 POTEI chr2 130459455 130509707 +357779 AC013269.2 chr2 130515997 130526691 +357783 CFC1B chr2 130521197 130528604 +357829 AC013269.1 chr2 130530275 130537182 +357833 AC140481.2 chr2 130583549 130590463 +357837 CFC1 chr2 130592168 130599575 +357883 POTEJ chr2 130611481 130658091 +357919 GPR148 chr2 130729070 130730336 +357927 AC140481.1 chr2 130742959 130755879 +357937 AMER3 chr2 130755435 130768134 +357970 AC133785.1 chr2 130830978 130836994 +357980 ARHGEF4 chr2 130836916 131047263 +358259 SMIM39 chr2 131035092 131035262 +358266 FAM168B chr2 131047876 131093460 +358305 PLEKHB2 chr2 131104847 131353709 +358493 POTEE chr2 131218067 131265278 +358653 RAB6D chr2 131361111 131364142 +358661 AC073869.5 chr2 131363364 131364881 +358666 LINC01120 chr2 131402778 131410050 +358721 AC073869.3 chr2 131461821 131463615 +358725 MZT2A chr2 131464900 131492743 +358765 TUBA3D chr2 131476119 131482934 +358785 CCDC74A chr2 131527675 131533666 +358882 AC093838.1 chr2 131555007 131568599 +358887 LINC01087 chr2 131637025 131649615 +358891 C2orf27A chr2 131647990 131767404 +358935 AC103564.1 chr2 131829801 131832031 +358940 AJ239322.2 chr2 131958277 131965535 +358944 AJ239322.1 chr2 131964731 131979873 +358949 LINC01945 chr2 131983937 131994161 +358953 AC093787.2 chr2 132010195 132017000 +358957 ANKRD30BL chr2 132147591 132257969 +359016 AC097532.1 chr2 132285795 132294377 +359021 AC097532.2 chr2 132345616 132347297 +359024 AC097532.3 chr2 132347473 132365130 +359031 GPR39 chr2 132416805 132646582 +359051 LYPD1 chr2 132643286 132671579 +359085 AC010974.1 chr2 132660526 132666990 +359089 NCKAP5 chr2 132671788 133568463 +359310 AC010974.2 chr2 132685224 132816896 +359316 NCKAP5-AS1 chr2 132915557 132931494 +359320 NCKAP5-AS2 chr2 133264968 133285445 +359344 NCKAP5-IT1 chr2 133431666 133433897 +359348 AC011243.1 chr2 133554315 133558227 +359353 AC092623.1 chr2 134028608 134032597 +359357 MGAT5 chr2 134119983 134454621 +359444 TMEM163 chr2 134455759 134719000 +359473 AC110620.2 chr2 134718188 134725474 +359477 CCNT2-AS1 chr2 134735464 134918710 +359499 ACMSD chr2 134838616 134902034 +359563 CCNT2 chr2 134918235 134959342 +359727 MAP3K19 chr2 134964485 135047468 +360008 RAB3GAP1 chr2 135052265 135176394 +360215 ZRANB3 chr2 135136916 135531218 +360481 R3HDM1 chr2 135531455 135725270 +360893 UBXN4 chr2 135741734 135785056 +360989 LCT chr2 135787850 135837184 +361046 AC011893.1 chr2 135820191 135823087 +361050 MCM6 chr2 135839626 135876443 +361100 DARS chr2 135905881 135986100 +361241 DARS-AS1 chr2 135985176 136022593 +361390 AC068492.1 chr2 136077892 136078513 +361394 CXCR4 chr2 136114349 136118165 +361414 THSD7B chr2 136765545 137677718 +361614 HNMT chr2 137964020 138016364 +361702 LINC01832 chr2 138101878 138107178 +361707 AC114763.1 chr2 138418284 138501698 +361719 AC114763.2 chr2 138470656 138473932 +361724 SPOPL chr2 138501770 138573547 +361797 AC092620.1 chr2 138569090 138574458 +361804 AC092620.2 chr2 138599663 138602426 +361807 LINC02631 chr2 138601599 138617469 +361830 NXPH2 chr2 138669157 138780390 +361840 AC023468.1 chr2 138917204 138975006 +361845 AC013265.1 chr2 139323921 139364583 +361852 AC062021.1 chr2 139366165 139379147 +361858 AC016710.1 chr2 139469775 139477747 +361862 AC078851.1 chr2 139824896 139825877 +361866 LINC01853 chr2 140103583 140131780 +361872 LRP1B chr2 140231423 142131701 +362146 AC078882.1 chr2 142131178 142137830 +362150 KYNU chr2 142877657 143055833 +362337 ARHGAP15 chr2 143091362 143768352 +362450 AC013437.1 chr2 143162078 143172172 +362456 AC079793.1 chr2 143295421 143598002 +362486 AC092652.3 chr2 143601517 143608759 +362491 AC092652.1 chr2 143629133 143656179 +362502 AC092652.2 chr2 143674315 143741294 +362512 AC079584.2 chr2 143765940 143776119 +362517 AC079584.1 chr2 143799467 143819599 +362522 AC016910.1 chr2 143937073 143964156 +362527 GTDC1 chr2 143938068 144332568 +362891 ZEB2 chr2 144364364 144521057 +363560 AC009951.5 chr2 144444848 144450450 +363567 ZEB2-AS1 chr2 144517978 144521477 +363635 AC009951.6 chr2 144523552 144524651 +363639 LINC01412 chr2 144523912 144579434 +363644 TEX41 chr2 144666312 145262988 +364784 AC023128.1 chr2 144688413 144690185 +364788 LINC01966 chr2 144877734 144882033 +364793 AC096666.1 chr2 145294277 145331847 +364800 AC092484.1 chr2 145569294 145588024 +364806 AC079163.2 chr2 145572662 145765726 +364810 AC079163.1 chr2 145600907 145603423 +364815 AC079248.1 chr2 145872209 145931146 +364833 LINC01911 chr2 146837727 146878220 +364926 AC062032.1 chr2 146879909 146898218 +364933 AC018678.1 chr2 147150707 147152047 +364937 ACVR2A chr2 147844517 147930826 +365036 AC009480.1 chr2 147899401 147902956 +365041 ORC4 chr2 147930397 148021604 +365292 MBD5 chr2 148021011 148516971 +365616 EPC2 chr2 148644440 148787569 +365697 AC105402.3 chr2 148866470 148888823 +365713 KIF5C chr2 148875227 149026759 +365818 AC105402.4 chr2 148909406 148927254 +365822 LYPD6B chr2 149038107 149215262 +365967 AC009230.1 chr2 149170561 149184570 +365973 LYPD6 chr2 149329985 149474138 +366072 MMADHC chr2 149569637 149587778 +366139 AC007364.1 chr2 149587196 150047447 +366162 LINC01931 chr2 149745648 149859191 +366179 AC016682.1 chr2 150150633 150166266 +366183 LINC01818 chr2 150169474 150356460 +366199 LINC01817 chr2 150234892 150257007 +366204 RND3 chr2 150468195 150539011 +366291 LINC01920 chr2 150552532 150572221 +366299 AC104777.2 chr2 150566134 150568080 +366304 AC104777.1 chr2 150595102 150620067 +366308 LINC02612 chr2 150612381 150635818 +366404 AC023469.2 chr2 150982506 151003474 +366410 AC023469.1 chr2 151001220 151048774 +366417 AC018731.1 chr2 151114811 151186209 +366427 RBM43 chr2 151247940 151261863 +366450 NMI chr2 151270470 151289894 +366490 TNFAIP6 chr2 151357592 151380046 +366512 RIF1 chr2 151409883 151508013 +366984 NEB chr2 151485336 151734487 +369767 ARL5A chr2 151788984 151828492 +369854 AC097448.1 chr2 151796688 151798688 +369858 CACNB4 chr2 151832768 152099475 +371491 AC079790.1 chr2 152098328 152109202 +371495 STAM2 chr2 152116801 152175763 +371571 AC079790.2 chr2 152176020 152225211 +371578 FMNL2 chr2 152335174 152649826 +371676 AC012066.2 chr2 152450162 152452891 +371680 AC012443.2 chr2 152635268 152641275 +371684 PRPF40A chr2 152651593 152717997 +371920 ARL6IP6 chr2 152717893 152761253 +371969 AC011901.1 chr2 153168399 153201762 +371980 LINC01850 chr2 153337705 153357422 +371986 AC012501.2 chr2 153421616 153593288 +371997 RPRM chr2 153477338 153478762 +372005 GALNT13 chr2 153871922 154453979 +372139 AC009227.1 chr2 154435853 154457438 +372146 AC009227.2 chr2 154459857 154460820 +372150 AC061961.1 chr2 154688296 154697817 +372162 KCNJ3 chr2 154697855 154858354 +372200 AC092625.1 chr2 154964308 154969101 +372206 AC073225.1 chr2 155525424 155664668 +372426 LINC01876 chr2 156011530 156254950 +372505 AC074099.1 chr2 156305108 156320255 +372510 NR4A2 chr2 156324437 156342348 +372677 GPD2 chr2 156435290 156613735 +372966 LINC01958 chr2 156655224 156695659 +372973 AC096589.2 chr2 156788731 156865701 +372977 AC096589.1 chr2 156803339 156891160 +372981 AC108057.1 chr2 157033837 157049716 +372988 GALNT5 chr2 157257705 157318491 +373020 ERMN chr2 157318625 157327713 +373126 CYTIP chr2 157414619 157488961 +373239 ACVR1C chr2 157526767 157628864 +373326 AC019186.1 chr2 157725708 157736005 +373330 ACVR1 chr2 157736444 157875862 +373594 UPP2 chr2 157876702 158136154 +373647 AC013731.1 chr2 157877683 157878565 +373650 AC091488.1 chr2 157917712 157918371 +373653 UPP2-IT1 chr2 158127957 158133988 +373657 CCDC148-AS1 chr2 158166650 158236169 +373664 CCDC148 chr2 158171073 158456753 +373852 PKP4 chr2 158456964 158682879 +374215 PKP4-AS1 chr2 158658337 158735002 +374227 AC005042.2 chr2 158685903 158753775 +374232 DAPL1 chr2 158795317 158862781 +374287 AC064843.1 chr2 158847619 158870393 +374291 TANC1 chr2 158968640 159232659 +374369 WDSUB1 chr2 159235793 159286799 +374495 BAZ2B chr2 159318979 159616569 +374803 AC008277.1 chr2 159386367 159404636 +374825 AC009506.1 chr2 159615296 159617082 +374829 AC009961.1 chr2 159670708 159712435 +374842 MARCH7 chr2 159712457 159771027 +374976 CD302 chr2 159768628 159798255 +375032 AC009961.4 chr2 159797288 159798043 +375035 LY75 chr2 159803355 159904756 +375131 PLA2R1 chr2 159932006 160062615 +375261 ITGB6 chr2 160099667 160200313 +375473 AC092153.1 chr2 160141981 160271888 +375488 LINC02478 chr2 160257718 160271880 +375502 RBMS1 chr2 160272151 160493807 +375739 AC009313.1 chr2 161096231 161160224 +375744 TANK chr2 161136908 161236230 +376029 AC009299.3 chr2 161222785 161308389 +376088 LINC01806 chr2 161244730 161249050 +376100 PSMD14 chr2 161308425 161411717 +376158 TBR1 chr2 161416297 161425870 +376215 AC009487.1 chr2 161422659 161423577 +376222 AC009487.3 chr2 161424015 161428774 +376226 SLC4A10 chr2 161424332 161985282 +376618 AC062022.2 chr2 161577192 161625752 +376625 DPP4 chr2 161992245 162074215 +376858 AC008063.1 chr2 162073256 162077911 +376867 AC008063.2 chr2 162092232 162095032 +376877 GCG chr2 162142882 162152404 +376923 AC007750.1 chr2 162159762 162173223 +376934 FAP chr2 162170684 162245151 +377220 IFIH1 chr2 162267074 162318684 +377325 GCA chr2 162318840 162371595 +377450 KCNH7 chr2 162371407 162838767 +377563 AC011900.1 chr2 162768936 162797972 +377570 FIGN chr2 163593396 163736012 +377596 AC016766.1 chr2 163743913 164352223 +377609 GRB14 chr2 164492417 164621482 +377707 COBLL1 chr2 164653624 164843679 +378089 AC019197.1 chr2 164840661 165208261 +378183 SLC38A11 chr2 164896186 164955525 +378328 SCN3A chr2 165087522 165204067 +378848 SCN2A chr2 165194993 165392310 +379636 AC011303.1 chr2 165433438 165436614 +379641 CSRNP3 chr2 165469647 165689407 +379743 GALNT3 chr2 165747588 165794659 +379862 AC009495.3 chr2 165794851 165810010 +379867 AC009495.1 chr2 165794857 165846091 +379871 AC009495.2 chr2 165833048 165839098 +379876 TTC21B chr2 165857475 165953816 +380060 TTC21B-AS1 chr2 165933857 165949891 +380075 SCN1A-AS1 chr2 165957188 166390771 +380309 SCN1A chr2 165984641 166149214 +381176 SCN9A chr2 166195185 166376001 +381658 SCN7A chr2 166403573 166611482 +381991 XIRP2 chr2 166888487 167259753 +382207 XIRP2-AS1 chr2 167123904 167140955 +382211 AC073050.1 chr2 167293171 167558333 +382216 AC016723.1 chr2 167814757 167941180 +382243 B3GALT1 chr2 167868948 167874041 +382251 STK39 chr2 167954020 168247595 +382307 CERS6 chr2 168455862 168775137 +382360 CERS6-AS1 chr2 168771951 168786961 +382420 NOSTRIN chr2 168786539 168865514 +382720 SPC25 chr2 168834132 168913371 +382766 G6PC2 chr2 168901291 168910000 +382821 ABCB11 chr2 168915498 169031324 +382970 DHRS9 chr2 169064789 169096167 +383097 AC007556.1 chr2 169100743 169101210 +383101 LRP2 chr2 169127109 169362534 +383445 BBS5 chr2 169479480 169506655 +383530 KLHL41 chr2 169509702 169526258 +383558 FASTKD1 chr2 169528508 169573875 +383683 PPIG chr2 169584344 169641406 +383911 CCDC173 chr2 169645425 169694405 +383955 PHOSPHO2 chr2 169694454 169701708 +384050 KLHL23 chr2 169694488 169776989 +384126 SSB chr2 169791933 169812064 +384257 METTL5 chr2 169810081 169824931 +384436 UBR3 chr2 169827458 170084131 +384776 MYO3B chr2 170178145 170655171 +385179 MYO3B-AS1 chr2 170332085 170408564 +385592 AC007277.1 chr2 170640374 170695374 +385604 AC007405.1 chr2 170700368 170813670 +385709 LINC01124 chr2 170712451 170714567 +385712 SP5 chr2 170715337 170718078 +385725 AC007405.3 chr2 170766878 170778729 +385786 ERICH2 chr2 170783786 170798971 +385802 GAD1 chr2 170813213 170861151 +386081 AC007405.2 chr2 170814686 170818037 +386096 AC007405.4 chr2 170820066 170821295 +386100 AC010092.1 chr2 170890393 170914873 +386106 GORASP2 chr2 170928464 170967130 +386233 TLK1 chr2 170990823 171231314 +386563 METTL8 chr2 171317405 171434802 +386801 DCAF17 chr2 171434217 171485052 +386971 CYBRD1 chr2 171522247 171558129 +387031 DYNC1I2 chr2 171687409 171748420 +387574 SLC25A12 chr2 171783405 171999859 +387726 HAT1 chr2 171922448 171983686 +387822 METAP1D chr2 171999943 172082430 +387877 DLX1 chr2 172084740 172089677 +387927 DLX2 chr2 172099438 172102900 +387948 DLX2-DT chr2 172103006 172109982 +387955 AC104088.1 chr2 172137345 172370401 +387979 AC104088.3 chr2 172234230 172237223 +387983 AC104088.2 chr2 172323260 172330582 +387988 ITGA6 chr2 172427354 172506459 +388319 AC078883.2 chr2 172427774 172428603 +388323 ITGA6-AS1 chr2 172464262 172466022 +388330 AC078883.1 chr2 172480840 172556596 +388350 PDK1 chr2 172555373 172608669 +388516 RAPGEF4-AS1 chr2 172677141 172736206 +388529 RAPGEF4 chr2 172735274 173052893 +388956 MAP3K20 chr2 173075435 173268015 +389143 MAP3K20-AS1 chr2 173166446 173282036 +389162 CDCA7 chr2 173354820 173368997 +389299 AC106900.1 chr2 173811076 173811392 +389302 SP3 chr2 173880850 173965702 +389429 AC016737.1 chr2 173968351 173969418 +389432 AC016737.2 chr2 174011856 174012975 +389436 LINC01960 chr2 174025280 174027163 +389439 OLA1 chr2 174072447 174248599 +389577 LINC01305 chr2 174326027 174330643 +389585 SP9 chr2 174334954 174338500 +389595 CIR1 chr2 174348022 174395712 +389647 SCRN3 chr2 174395730 174429575 +389805 GPR155 chr2 174431571 174487094 +389966 AC010894.2 chr2 174487380 174488386 +389979 AC010894.3 chr2 174547141 174776720 +389996 WIPF1 chr2 174559572 174682916 +390192 AC010894.4 chr2 174575227 174587726 +390196 CHRNA1 chr2 174747592 174787935 +390378 CHN1 chr2 174799313 175005381 +391075 ATF2 chr2 175072250 175168382 +391623 AC096649.1 chr2 175167904 175168522 +391627 ATP5MC3 chr2 175176258 175184607 +391680 AC093459.1 chr2 175257250 175463180 +391695 AC016751.2 chr2 175897336 175904232 +391699 AC016751.1 chr2 175904371 175905502 +391703 LNPK chr2 175923882 176002839 +391856 EVX2 chr2 176077472 176083913 +391868 HOXD13 chr2 176092721 176095944 +391878 HOXD12 chr2 176099730 176101193 +391896 HOXD11 chr2 176104216 176109754 +391909 HOXD10 chr2 176108790 176119942 +391926 HOXD-AS2 chr2 176121611 176137098 +391940 HOXD9 chr2 176122719 176124937 +391950 HOXD8 chr2 176129694 176132695 +391993 HOXD3 chr2 176136612 176173102 +392026 HOXD4 chr2 176151550 176153226 +392036 HAGLR chr2 176164051 176188958 +392117 AC009336.1 chr2 176164164 176165716 +392120 HAGLROS chr2 176177717 176179008 +392124 HOXD1 chr2 176188668 176190907 +392134 MTX2 chr2 176269395 176338025 +392247 LINC01117 chr2 176495255 176819180 +392265 AC017048.1 chr2 176506245 176507702 +392269 AC017048.2 chr2 176524879 176531683 +392275 AC017048.3 chr2 176611437 176612249 +392278 LINC01116 chr2 176629572 176637931 +392295 AC092162.2 chr2 176723614 176819310 +392330 AC073636.1 chr2 176830839 176849428 +392398 AC074286.1 chr2 176989418 177164656 +392453 AC079305.3 chr2 177111036 177212662 +392464 HNRNPA3 chr2 177212563 177223958 +392562 NFE2L2 chr2 177227595 177392697 +392727 AC079305.1 chr2 177264359 177265515 +392731 AC019080.1 chr2 177283508 177392691 +392778 AC019080.4 chr2 177300600 177302006 +392782 AC019080.5 chr2 177306373 177310572 +392786 AC019080.6 chr2 177317715 177318471 +392789 AGPS chr2 177392757 177559299 +392935 TTC30B chr2 177548998 177552796 +392943 AC073834.1 chr2 177603089 177618572 +392948 TTC30A chr2 177612999 177618742 +392956 PDE11A chr2 177623244 178072777 +393183 AC012499.1 chr2 177653419 177723289 +393197 AC011998.3 chr2 177953111 178011989 +393201 RBM45 chr2 178112424 178139011 +393291 OSBPL6 chr2 178194481 178402893 +393657 CHROMR chr2 178413635 178440243 +393735 PRKRA chr2 178431414 178451512 +393872 PJVK chr2 178451346 178461409 +394078 FKBP7 chr2 178463664 178478600 +394163 PLEKHA3 chr2 178480457 178516463 +394220 TTN-AS1 chr2 178521183 178779963 +394695 TTN chr2 178525989 178830802 +398764 AC009948.3 chr2 178541125 178541799 +398767 AC009948.2 chr2 178548884 178550681 +398770 AC010680.3 chr2 178577103 178577622 +398773 AC010680.2 chr2 178578790 178580906 +398776 AC010680.4 chr2 178616581 178617123 +398779 AC010680.5 chr2 178644717 178645179 +398782 AC010680.1 chr2 178723457 178727046 +398785 AC092640.1 chr2 178828349 179007807 +398814 CCDC141 chr2 178829757 179050086 +398960 SESTD1 chr2 179101678 179264832 +399113 AC093911.1 chr2 179273831 179285707 +399117 ZNF385B chr2 179441982 179861612 +399287 CWC22 chr2 179944876 180007297 +399376 AC009478.1 chr2 180571712 180692454 +399382 SCHLAP1 chr2 180692104 180916939 +399389 UBE2E3 chr2 180967248 181076585 +399560 AC104076.1 chr2 180979427 180980090 +399564 AC068196.1 chr2 181076051 181105968 +399572 LINC01934 chr2 181086076 181409321 +399674 AC020595.1 chr2 181422154 181425749 +399678 ITGA4 chr2 181457202 181538940 +399833 CERKL chr2 181536672 181680665 +400100 NEUROD1 chr2 181673088 181680876 +400113 AC013733.2 chr2 181683113 181685707 +400117 AC013733.1 chr2 181690380 181693415 +400121 AC009962.1 chr2 181887851 181891663 +400124 ITPRID2 chr2 181891730 181930738 +400437 PPP1R1C chr2 181954241 182131398 +400541 PDE1A chr2 182140036 182523192 +400735 AC012500.1 chr2 182278684 182282752 +400739 DNAJC10 chr2 182716041 182794464 +401069 FRZB chr2 182833275 182866637 +401087 NCKAP1 chr2 182909115 183038858 +401250 DUSP19 chr2 183078559 183100008 +401280 AC064871.2 chr2 183083405 183108519 +401288 NUP35 chr2 183117513 183161680 +401422 AC021851.1 chr2 183178806 183215414 +401431 AC021851.2 chr2 183253652 183495501 +401437 AC093639.3 chr2 183897950 183902147 +401442 AC093639.1 chr2 183904529 183949112 +401447 AC093639.2 chr2 183997372 184002264 +401451 AC096555.1 chr2 184049467 184187573 +401459 AC020584.1 chr2 184204372 184382869 +401467 AC096667.1 chr2 184593577 184599008 +401472 ZNF804A chr2 184598529 184939492 +401495 AC009315.1 chr2 185425063 185505608 +401505 FSIP2-AS1 chr2 185652374 185800151 +401517 FSIP2-AS2 chr2 185719874 185740479 +401531 FSIP2 chr2 185738804 185833290 +401649 AC097500.1 chr2 185950469 185953171 +401653 LINC01473 chr2 186032884 186422432 +401822 AC017071.1 chr2 186354570 186356773 +401825 ZC3H15 chr2 186486253 186509361 +401920 ITGAV chr2 186590056 186680901 +402139 AC017101.1 chr2 186641339 186695287 +402144 FAM171B chr2 186694060 186765959 +402183 ZSWIM2 chr2 186827475 186849208 +402218 AC007319.1 chr2 187003220 187556288 +402237 CALCRL chr2 187341964 187448460 +402390 TFPI chr2 187464230 187565760 +402562 LINC01090 chr2 187712816 188384313 +402577 GULP1 chr2 188291669 188595931 +402868 AC092598.1 chr2 188598791 188839445 +402878 DIRC1 chr2 188733738 188790104 +402891 COL3A1 chr2 188974320 189012746 +403107 COL5A2 chr2 189031898 189225312 +403354 AC133106.1 chr2 189095063 189096158 +403358 WDR75 chr2 189441446 189475552 +403528 AC013439.2 chr2 189537384 189540417 +403532 SLC40A1 chr2 189560579 189583758 +403612 ASNSD1 chr2 189661385 189670831 +403671 ASDURF chr2 189661452 189666437 +403720 ANKAR chr2 189674290 189761193 +403933 OSGEPL1 chr2 189746660 189763227 +404048 OSGEPL1-AS1 chr2 189762704 189765556 +404059 AC013468.1 chr2 189763859 189764456 +404062 ORMDL1 chr2 189770267 189784364 +404134 PMS1 chr2 189784085 189877629 +404551 C2orf88 chr2 189879609 190203484 +404621 MSTN chr2 190055700 190062729 +404633 HIBCH chr2 190189735 190344193 +404815 INPP1 chr2 190343570 190371665 +404972 MFSD6 chr2 190408355 190509205 +405083 AC093388.1 chr2 190454092 190454521 +405086 NEMP2 chr2 190504338 190534722 +405174 AC108047.1 chr2 190534855 190569776 +405179 AC006460.2 chr2 190607660 190649840 +405208 NAB1 chr2 190646746 190692766 +405333 AC006460.1 chr2 190676944 190708716 +405346 AC005540.1 chr2 190880797 190882059 +405350 GLS chr2 190880827 190965552 +405556 STAT1 chr2 190964358 191020960 +405938 AC067945.2 chr2 191017954 191019079 +405942 AC067945.3 chr2 191021526 191032314 +405950 STAT4 chr2 191029576 191151596 +406158 AC067945.4 chr2 191045458 191065345 +406162 AC092614.1 chr2 191229165 191246172 +406168 MYO1B chr2 191245185 191425389 +406544 NABP1 chr2 191678068 191696664 +406679 AC098872.1 chr2 191792797 191820257 +406698 CAVIN2 chr2 191834310 191847088 +406708 AC098617.1 chr2 191846539 192044525 +406796 TMEFF2 chr2 191949043 192194933 +406863 AC062039.1 chr2 192629919 192645706 +406867 AC013401.1 chr2 192644102 192645387 +406874 PCGEM1 chr2 192749845 192776899 +406884 AC096647.1 chr2 193170704 193172765 +406888 AC074290.2 chr2 193867722 193868982 +406892 AC068135.2 chr2 193898367 193899394 +406895 LINC01821 chr2 194344190 194576578 +406992 AC073973.1 chr2 194587925 194612145 +406997 LINC01790 chr2 194730595 194761435 +407003 AC010983.1 chr2 195003711 195026370 +407007 AC104823.1 chr2 195448532 195481827 +407019 AC064834.1 chr2 195451778 195515699 +407024 LINC01825 chr2 195532945 195540287 +407037 LINC01827 chr2 195569628 195572970 +407041 SLC39A10 chr2 195575977 195737702 +407169 DNAH7 chr2 195737703 196068837 +407398 STK17B chr2 196133583 196176503 +407468 AC114760.2 chr2 196151263 196154881 +407472 HECW2 chr2 196189099 196593684 +407897 HECW2-AS1 chr2 196260024 196264204 +407908 AC068544.2 chr2 196638422 196639497 +407912 CCDC150 chr2 196639554 196763490 +408188 GTF3C3 chr2 196763035 196799725 +408372 C2orf66 chr2 196804415 196810276 +408395 PGAP1 chr2 196833004 196927796 +408667 ANKRD44 chr2 196967017 197311173 +409019 AC013264.1 chr2 197197991 197199273 +409023 ANKRD44-IT1 chr2 197250858 197302519 +409031 AC010746.2 chr2 197311393 197312740 +409035 SF3B1 chr2 197388515 197435091 +409314 COQ10B chr2 197453423 197475308 +409361 HSPD1 chr2 197486584 197516737 +409527 HSPE1 chr2 197500140 197503449 +409576 MOB4 chr2 197515571 197553699 +409722 RFTN2 chr2 197568224 197676045 +409775 AC020550.2 chr2 197640441 197641574 +409779 AC011997.1 chr2 197693106 197774823 +409785 MARS2 chr2 197705369 197708395 +409793 BOLL chr2 197726879 197786762 +409958 PLCL1 chr2 197804593 198572581 +410032 AC011997.2 chr2 197817423 197836326 +410037 AC020719.1 chr2 198187802 198191521 +410044 LINC01923 chr2 198299276 198375490 +410062 AC019330.1 chr2 198493242 198772356 +410072 AC020718.1 chr2 198882573 199071791 +410077 SATB2 chr2 199269500 199471266 +410261 AC016746.1 chr2 199325310 199329362 +410266 SATB2-AS1 chr2 199457700 199476935 +410289 LINC01877 chr2 199608068 199750341 +410356 FTCDNL1 chr2 199760544 199851173 +410418 AC097717.1 chr2 199867396 199911159 +410639 C2orf69 chr2 199911293 199955935 +410652 TYW5 chr2 199928913 199955736 +410725 MAIP1 chr2 199955317 200008540 +410775 AC004464.1 chr2 200086870 200100025 +410779 SPATS2L chr2 200305881 200482264 +411265 AC012459.1 chr2 200390666 200478018 +411289 KCTD18 chr2 200488958 200519784 +411346 SGO2 chr2 200510008 200584096 +411410 AOX1 chr2 200586014 200677064 +411587 LINC01792 chr2 200711535 200735186 +411609 AC007163.1 chr2 200780495 200812170 +411615 BZW1 chr2 200810594 200827338 +411812 CLK1 chr2 200853009 200864744 +412023 PPIL3 chr2 200870907 200889303 +412199 NIF3L1 chr2 200889327 200903938 +412350 ORC2 chr2 200908977 200963680 +412439 AC005037.1 chr2 200963263 201009102 +412446 FAM126B chr2 200973718 201071671 +412584 NDUFB3 chr2 201071433 201085750 +412631 AC007272.1 chr2 201101382 201103136 +412635 CFLAR chr2 201116154 201176687 +412979 CFLAR-AS1 chr2 201140278 201157823 +413110 AC007283.1 chr2 201166965 201167546 +413114 CASP10 chr2 201182881 201229406 +413312 CASP8 chr2 201233443 201287711 +413602 FLACC1 chr2 201288271 201357398 +413803 TRAK2 chr2 201377207 201451500 +413876 STRADB chr2 201387858 201480846 +413998 C2CD6 chr2 201487421 201619178 +414136 TMEM237 chr2 201620184 201643570 +414343 AC007279.2 chr2 201643398 201645990 +414347 MPP4 chr2 201644870 201698694 +414775 ALS2 chr2 201700267 201780956 +415009 CDK15 chr2 201790461 201895550 +415235 AC069148.1 chr2 202032770 202033537 +415238 FZD7 chr2 202034587 202038445 +415246 KIAA2012 chr2 202073255 202205188 +415352 KIAA2012-AS1 chr2 202075410 202117062 +415361 AC079354.3 chr2 202137570 202149627 +415366 AC079354.2 chr2 202178660 202179391 +415370 SUMO1 chr2 202206180 202238608 +415516 NOP58 chr2 202265736 202303661 +415625 AC064836.4 chr2 202302122 202303614 +415629 AC064836.2 chr2 202336739 202337200 +415632 AC064836.3 chr2 202374932 202375604 +415635 BMPR2 chr2 202376327 202567751 +415728 FAM117B chr2 202634969 202769757 +415754 ICA1L chr2 202773150 202871985 +416094 WDR12 chr2 202874782 203014798 +416155 CARF chr2 202912214 202988263 +416578 NBEAL1 chr2 203014879 203226378 +416787 CYP20A1 chr2 203238940 203305611 +417000 ABI2 chr2 203328239 203447728 +417375 AC080075.1 chr2 203328459 203329226 +417379 RAPH1 chr2 203394345 203535335 +417725 CD28 chr2 203706475 203738912 +417762 CTLA4 chr2 203867771 203873965 +417813 ICOS chr2 203936748 203961577 +417842 AC009965.1 chr2 204090457 204109849 +417849 AC009498.1 chr2 204219984 204234985 +417859 AC016903.1 chr2 204470076 204473837 +417863 AC016903.2 chr2 204473834 204507672 +417871 PARD3B chr2 204545475 205620162 +418274 AC007736.1 chr2 204668863 204678698 +418278 NRP2 chr2 205681990 205798133 +418542 AC007362.1 chr2 205756469 205764006 +418601 AC007679.1 chr2 205989585 206000858 +418606 INO80D chr2 205993721 206086303 +418664 AC007383.2 chr2 206084605 206086564 +418671 NDUFS1 chr2 206114817 206159509 +418993 AC007383.3 chr2 206115547 206122323 +418997 EEF1B2 chr2 206159585 206162928 +419138 GPR1 chr2 206175316 206218047 +419241 GPR1-AS chr2 206203543 206265326 +419258 ZDBF2 chr2 206274663 206314427 +419426 ADAM23 chr2 206443532 206621127 +419549 AC010731.2 chr2 206606497 206609812 +419554 AC010731.3 chr2 206640073 206641282 +419558 FAM237A chr2 206642412 206649011 +419573 DYTN chr2 206651621 206718396 +419620 MDH1B chr2 206737763 206765328 +419758 FASTKD2 chr2 206765357 206796189 +419869 AC008269.1 chr2 206798325 206926876 +419896 AC008269.2 chr2 206821190 206822294 +419899 CPO chr2 206939518 206969474 +419923 KLF7 chr2 207074137 207167267 +420033 KLF7-IT1 chr2 207120884 207122044 +420037 MYOSLID chr2 207166120 207248668 +420057 AC007879.1 chr2 207173634 207222790 +420064 AC007879.3 chr2 207186717 207236066 +420074 AC007879.5 chr2 207217532 207219145 +420078 AC007879.2 chr2 207226949 207228308 +420082 AC007879.4 chr2 207235299 207237875 +420086 AC009226.1 chr2 207239864 207529795 +420103 LINC01802 chr2 207260445 207270690 +420108 CREB1 chr2 207529737 207605988 +420309 METTL21A chr2 207580631 207625928 +420449 LINC01857 chr2 207662375 207667024 +420453 CCNYL1 chr2 207711540 207761839 +420593 AC096772.1 chr2 207753872 207754435 +420596 FZD5 chr2 207762598 207769906 +420606 PLEKHM3 chr2 207821288 208025527 +420669 AC083900.1 chr2 207868582 207869915 +420673 CRYGD chr2 208121607 208124524 +420685 CRYGC chr2 208128137 208129828 +420697 CRYGB chr2 208142573 208146158 +420709 CRYGA chr2 208160740 208163589 +420721 C2orf80 chr2 208165343 208190030 +420833 IDH1 chr2 208236227 208266074 +420961 IDH1-AS1 chr2 208255247 208256181 +420968 PIKFYVE chr2 208266255 208358746 +421262 PTH2R chr2 208359714 208854503 +421348 AC019185.2 chr2 208469850 208540413 +421353 AC109824.1 chr2 208885755 208888143 +421357 AC016743.1 chr2 209353977 209387322 +421362 MAP2 chr2 209424058 209734118 +421600 UNC80 chr2 209771993 209999300 +421963 RPE chr2 210002565 210022260 +422230 KANSL1L chr2 210021421 210171409 +422404 AC007038.2 chr2 210028417 210029156 +422407 AC007038.1 chr2 210030572 210064356 +422417 AC006994.2 chr2 210171518 210233976 +422430 ACADL chr2 210187126 210225447 +422481 MYL1 chr2 210290150 210315174 +422534 LANCL1-AS1 chr2 210324759 210469246 +422552 LANCL1 chr2 210431249 210477652 +422717 CPS1 chr2 210477682 210679107 +423127 CPS1-IT1 chr2 210617571 210619876 +423130 ERBB4 chr2 211375717 212538841 +423392 AC093865.1 chr2 212581357 213021545 +423399 LINC01878 chr2 212795300 212819264 +423423 AC108066.1 chr2 212911003 212919809 +423428 AC108066.2 chr2 212932894 212937520 +423433 IKZF2 chr2 212999691 213152427 +423683 AC079610.1 chr2 213152970 213153659 +423686 LINC01953 chr2 213155806 213167712 +423690 AC079610.2 chr2 213266995 213276152 +423694 SPAG16-DT chr2 213276552 213284205 +423699 SPAG16 chr2 213284379 214410501 +423957 AC068051.1 chr2 214241676 214684246 +423974 VWC2L chr2 214411054 214578976 +424002 VWC2L-IT1 chr2 214510196 214536890 +424008 BARD1 chr2 214725646 214809683 +424245 SNHG31 chr2 214810181 214963575 +424268 ABCA12 chr2 214931542 215138626 +424486 AC072062.1 chr2 215004782 215085488 +424556 AC092844.1 chr2 215178791 215310947 +424563 AC073284.1 chr2 215274992 215277947 +424568 ATIC chr2 215311956 215349773 +424778 FN1 chr2 215360440 215436073 +425891 AC012462.3 chr2 215436253 215436992 +425895 AC012462.1 chr2 215453688 215486639 +425931 AC012462.2 chr2 215476667 215480248 +425935 AC012668.2 chr2 215530447 215545526 +425942 AC012668.3 chr2 215533133 215713895 +425971 AC012668.1 chr2 215579407 215582635 +425975 LINC00607 chr2 215611563 215848954 +426074 LINC01614 chr2 215718043 215719424 +426078 AC122136.1 chr2 215869923 215870518 +426082 AC093382.1 chr2 215939308 215941719 +426086 MREG chr2 215942584 216034096 +426156 PECR chr2 215996329 216082955 +426233 TMEM169 chr2 216081866 216102783 +426300 XRCC5 chr2 216107464 216206303 +426467 LINC01963 chr2 216217045 216220192 +426470 MARCH4 chr2 216257865 216372483 +426484 AC012513.1 chr2 216259595 216266130 +426488 AC069155.1 chr2 216303325 216321737 +426493 AC098820.2 chr2 216385288 216412696 +426500 SMARCAL1 chr2 216412414 216483053 +426697 AC098820.1 chr2 216479030 216498761 +426711 AC098820.3 chr2 216483032 216487196 +426715 RPL37A chr2 216498825 216579180 +426842 LINC01280 chr2 216590426 216606938 +426848 AC073321.1 chr2 216594359 216611206 +426859 IGFBP2 chr2 216632828 216664436 +426907 IGFBP5 chr2 216672105 216695549 +426931 AC007563.2 chr2 216694464 216994079 +426941 AC007563.1 chr2 216799608 216805335 +426945 AC007563.4 chr2 216821077 216831910 +426950 AC007557.2 chr2 216854389 216855132 +426954 TNP1 chr2 216859458 216860064 +426964 LINC01921 chr2 216859948 216871643 +426969 AC007557.4 chr2 216866332 216867813 +426973 AC007557.1 chr2 216868012 216869156 +426977 AC007557.3 chr2 216870441 216873932 +426981 AC007749.1 chr2 216995906 216996490 +426984 AC007749.2 chr2 217061067 217064818 +426989 DIRC3-AS1 chr2 217261699 217336120 +427033 DIRC3 chr2 217284019 217756593 +427100 TNS1 chr2 217799588 218033982 +427833 AC010136.1 chr2 217978707 217993747 +427843 RUFY4 chr2 218034960 218090581 +427969 CXCR2 chr2 218125289 218137251 +428039 CXCR1 chr2 218162841 218166962 +428049 ARPC2 chr2 218217141 218254356 +428236 AC021016.2 chr2 218255319 218257366 +428239 GPBAR1 chr2 218259496 218263861 +428276 AAMP chr2 218264123 218270257 +428418 PNKD chr2 218270392 218346793 +428512 TMBIM1 chr2 218274197 218292586 +428855 CATIP-AS2 chr2 218326889 218357966 +428861 CATIP chr2 218356857 218368099 +428903 CATIP-AS1 chr2 218366665 218367835 +428911 SLC11A1 chr2 218382029 218396894 +429131 CTDSP1 chr2 218398256 218405941 +429276 AC021016.3 chr2 218398743 218399219 +429279 VIL1 chr2 218419121 218453295 +429409 USP37 chr2 218450251 218568351 +429692 CNOT9 chr2 218568580 218597080 +429823 PLCD4 chr2 218607855 218637184 +430066 AC012510.1 chr2 218633256 218634014 +430069 ZNF142 chr2 218637916 218659655 +430197 BCS1L chr2 218658764 218663443 +430470 RNF25 chr2 218663892 218672002 +430542 STK36 chr2 218672069 218702716 +430836 TTLL4 chr2 218710835 218755416 +431159 CYP27A1 chr2 218781749 218815293 +431223 AC009974.2 chr2 218799729 218802554 +431227 AC009974.1 chr2 218818690 218819144 +431230 PRKAG3 chr2 218822383 218832086 +431376 WNT6 chr2 218859805 218874233 +431393 WNT10A chr2 218880852 218899581 +431418 LINC01494 chr2 218900811 218930636 +431425 AC097468.2 chr2 218944629 218961903 +431429 CDK5R2 chr2 218959666 218962155 +431437 LINC00608 chr2 218975393 218989940 +431465 FEV chr2 218981087 218985657 +431480 CRYBA2 chr2 218990189 218993422 +431530 AC097468.1 chr2 219002215 219015721 +431535 CFAP65 chr2 219002846 219041527 +431852 IHH chr2 219054424 219060921 +431864 AC097468.4 chr2 219065308 219070022 +431869 AC097468.3 chr2 219069354 219069809 +431872 NHEJ1 chr2 219075317 219160865 +431995 SLC23A3 chr2 219161465 219170095 +432144 CNPPD1 chr2 219171897 219178106 +432227 RETREG2 chr2 219176225 219185475 +432365 ZFAND2B chr2 219195237 219209651 +432657 AC068946.3 chr2 219198640 219200034 +432661 ABCB6 chr2 219209772 219218994 +432845 ATG9A chr2 219219380 219229717 +433227 ANKZF1 chr2 219229783 219236679 +433479 GLB1L chr2 219236598 219245478 +433675 STK16 chr2 219245455 219250337 +433814 TUBA4A chr2 219249710 219278170 +433901 TUBA4B chr2 219253243 219272197 +433925 DNAJB2 chr2 219279267 219286900 +434109 PTPRN chr2 219289623 219309648 +434417 AC114803.1 chr2 219299002 219304130 +434422 RESP18 chr2 219327407 219333177 +434464 DNPEP chr2 219373527 219400022 +434858 AC053503.2 chr2 219388496 219403633 +434862 DES chr2 219418377 219426734 +434903 AC053503.4 chr2 219425071 219426184 +434907 SPEG chr2 219434843 219493629 +435252 AC053503.1 chr2 219482073 219516877 +435256 SPEGNB chr2 219496125 219498287 +435286 AC053503.5 chr2 219497611 219498246 +435289 GMPPA chr2 219498867 219506989 +435571 ASIC4 chr2 219514170 219538772 +435639 CHPF chr2 219538948 219543809 +435675 TMEM198 chr2 219543663 219550595 +435726 AC009955.3 chr2 219547211 219547658 +435729 OBSL1 chr2 219550728 219571859 +435967 AC009955.4 chr2 219559083 219559626 +435970 INHA chr2 219569162 219575711 +435983 STK11IP chr2 219597857 219616451 +436149 AC009955.1 chr2 219625059 219626693 +436153 SLC4A3 chr2 219627394 219641980 +436461 AC009955.2 chr2 219645090 219645631 +436464 LINC02832 chr2 219685381 219737937 +436476 LINC01803 chr2 219903900 219904923 +436481 AC008281.1 chr2 219904983 219912834 +436485 AC019211.1 chr2 220105656 220450778 +436491 AC093083.1 chr2 220127546 220212491 +436496 AC067956.1 chr2 220450679 220741493 +436521 AC093843.1 chr2 220776818 220855873 +436537 AC093843.2 chr2 220811618 220853456 +436541 AC011233.2 chr2 221306290 221308329 +436545 EPHA4 chr2 221418027 221574202 +436745 AC079834.2 chr2 221572506 221574454 +436748 AC068489.1 chr2 221609324 221650218 +436760 PAX3 chr2 222199888 222298996 +436966 CCDC140 chr2 222298147 222305217 +436982 AC010980.1 chr2 222317242 222318653 +436985 SGPP2 chr2 222424543 222562621 +437001 FARSB chr2 222566899 222656092 +437044 MOGAT1 chr2 222671658 222709930 +437062 ACSL3 chr2 222860942 222944639 +437203 AC013476.1 chr2 222917387 222919363 +437207 KCNE4 chr2 223051814 223198399 +437222 AC013448.1 chr2 223498773 223504611 +437227 AC013448.2 chr2 223505476 223510933 +437231 SCG2 chr2 223596940 223602361 +437257 AP1S3 chr2 223751686 223838027 +437368 WDFY1 chr2 223855716 223945357 +437429 MRPL44 chr2 223957463 223967714 +437443 AC073641.1 chr2 223965701 223967706 +437447 SERPINE2 chr2 223975045 224039318 +437585 FAM124B chr2 224378698 224402107 +437615 AC073052.2 chr2 224464682 224474500 +437623 CUL3 chr2 224470150 224585397 +437863 CCDC195 chr2 224703764 224716365 +437874 DOCK10 chr2 224765090 225042445 +438441 NYAP2 chr2 225399710 225654018 +438478 AC016717.2 chr2 225698514 225703654 +438481 AC062015.1 chr2 226180044 226185371 +438485 IRS1 chr2 226731317 226799759 +438498 AC010735.2 chr2 226800146 226813741 +438509 AC010735.1 chr2 226804036 226805061 +438512 RHBDD1 chr2 226835581 226999215 +438648 COL4A4 chr2 227002711 227164453 +438783 COL4A3 chr2 227164565 227314792 +438949 AC097662.1 chr2 227221052 227325711 +439133 MFF chr2 227325151 227357836 +439476 TM4SF20 chr2 227362038 227381995 +439497 SCYGR1 chr2 227387683 227387949 +439504 AGFG1 chr2 227472152 227561214 +439693 SCYGR2 chr2 227598893 227599255 +439700 C2orf83 chr2 227610090 227648606 +439741 SCYGR3 chr2 227614538 227614840 +439748 AC064853.1 chr2 227616998 227617790 +439752 SCYGR4 chr2 227616998 227618655 +439760 SCYGR5 chr2 227666804 227667061 +439767 SLC19A3 chr2 227683763 227718028 +439951 SCYGR6 chr2 227724440 227724757 +439958 SCYGR7 chr2 227728335 227728625 +439965 SCYGR8 chr2 227745845 227746681 +439973 CCL20 chr2 227805739 227817564 +440014 DAW1 chr2 227871054 227924344 +440117 SPHKAP chr2 227979955 228181687 +440179 AC009410.1 chr2 228378500 228379773 +440184 LINC01807 chr2 228475224 228841689 +440206 AC012070.1 chr2 228683537 228684580 +440210 PID1 chr2 228850526 229271285 +440272 DNER chr2 229357629 229714555 +440308 AC008273.1 chr2 229407358 229408328 +440312 TRIP12 chr2 229763838 229923239 +440693 FBXO36 chr2 229922302 230013119 +440738 FBXO36-IT1 chr2 229942728 229945137 +440742 SLC16A14 chr2 230034982 230068993 +440800 AC009950.1 chr2 230121370 230174223 +440850 SP110 chr2 230167293 230225729 +441105 SP140 chr2 230203110 230313215 +441392 SP140L chr2 230327184 230403732 +441596 SP100 chr2 230415942 230545606 +442007 AC010149.1 chr2 230520594 230580006 +442023 LINC01907 chr2 230690065 230700529 +442034 CAB39 chr2 230712842 230821075 +442137 ITM2C chr2 230864639 230879248 +442259 GCSIR chr2 230886474 230904693 +442285 GPR55 chr2 230907318 230961066 +442342 AC012507.1 chr2 230908852 230910102 +442346 AC012507.3 chr2 230924567 230929919 +442351 SPATA3-AS1 chr2 230984368 230996032 +442408 SPATA3 chr2 230990324 231025055 +442551 C2orf72 chr2 231037523 231049719 +442570 AC009407.1 chr2 231052040 231052637 +442573 PSMD1 chr2 231056864 231172827 +442886 HTR2B chr2 231108230 231125042 +442900 ARMC9 chr2 231198546 231374837 +443168 AC017104.1 chr2 231388976 231394991 +443178 B3GNT7 chr2 231395710 231401164 +443191 AC017104.3 chr2 231452195 231453153 +443196 NCL chr2 231453531 231483641 +443309 LINC00471 chr2 231508422 231514366 +443318 AC017104.6 chr2 231518582 231521067 +443322 NMUR1 chr2 231523187 231530445 +443334 AC104634.2 chr2 231588959 231592776 +443338 TEX44 chr2 231592864 231594276 +443346 PTMA chr2 231706895 231713541 +443476 PDE6D chr2 231732433 231786272 +443525 COPS7B chr2 231781671 231809254 +443841 AC073476.3 chr2 231809846 231812352 +443844 NPPC chr2 231921809 231926396 +443865 DIS3L2 chr2 231961245 232344350 +444238 AC019130.1 chr2 231978488 232015720 +444242 ALPP chr2 232378724 232382889 +444278 AC068134.1 chr2 232379635 232381674 +444286 ALPG chr2 232406844 232410714 +444314 AC068134.2 chr2 232420661 232421461 +444318 ALPI chr2 232456125 232460753 +444371 ECEL1 chr2 232479827 232487834 +444484 PRSS56 chr2 232520463 232525716 +444550 CHRND chr2 232525993 232536667 +444695 CHRNG chr2 232539692 232548115 +444757 TIGD1 chr2 232547970 232550557 +444765 EIF4E2 chr2 232550674 232583644 +444934 AC073254.1 chr2 232580948 232611971 +444994 EFHD1 chr2 232606057 232682780 +445079 GIGYF2 chr2 232697299 232860575 +445910 AC064852.1 chr2 232760146 232767949 +445915 KCNJ13 chr2 232765802 232776565 +445963 SNORC chr2 232857270 232878708 +446024 NGEF chr2 232878701 233013256 +446154 AC106876.1 chr2 233012614 233015885 +446162 NEU2 chr2 233032672 233035057 +446171 INPP5D chr2 233059967 233207903 +446388 ATG16L1 chr2 233210051 233295674 +446755 SAG chr2 233307816 233347055 +446932 AC013726.1 chr2 233351132 233353416 +446935 DGKD chr2 233354507 233472104 +447198 USP40 chr2 233475520 233566782 +447535 UGT1A8 chr2 233617645 233773310 +447551 UGT1A10 chr2 233636454 233773305 +447582 UGT1A9 chr2 233671898 233773300 +447598 UGT1A7 chr2 233681938 233773299 +447622 UGT1A6 chr2 233691607 233773300 +447711 AC114812.2 chr2 233693434 233708699 +447715 UGT1A5 chr2 233712992 233773299 +447730 UGT1A4 chr2 233718778 233773299 +447762 UGT1A3 chr2 233729108 233773299 +447778 UGT1A1 chr2 233760248 233773299 +447808 MROH2A chr2 233775679 233833423 +448029 HJURP chr2 233833416 233854566 +448151 TRPM8 chr2 233917373 234019522 +448415 AC005538.1 chr2 233946146 233955435 +448419 AC005538.3 chr2 233977872 233980018 +448423 SPP2 chr2 234050679 234077134 +448485 AC006037.1 chr2 234109081 234109481 +448489 AC122134.1 chr2 234222838 234224514 +448494 AC097713.3 chr2 234351247 234356038 +448498 AC097713.1 chr2 234438328 234462127 +448503 LINC01891 chr2 234444590 234454595 +448508 ARL4C chr2 234493041 234497081 +448525 LINC01173 chr2 234682668 234717764 +448530 AC010148.1 chr2 234803808 234913384 +448567 SH3BP4 chr2 234952017 235055714 +448676 AC114814.1 chr2 235084822 235088586 +448681 AC114814.3 chr2 235177896 235178905 +448685 AGAP1 chr2 235494043 236131800 +449017 AGAP1-IT1 chr2 235505751 235507566 +449021 AC064874.1 chr2 235773855 235783387 +449030 GBX2 chr2 236165236 236168386 +449054 AC019068.1 chr2 236167447 236294927 +449063 ASB18 chr2 236194872 236264409 +449116 IQCA1 chr2 236324147 236507535 +449340 AC093915.1 chr2 236367560 236369102 +449343 IQCA1-AS1 chr2 236391074 236392388 +449347 ACKR3 chr2 236567787 236582354 +449364 AC084030.1 chr2 236733289 236754363 +449378 AC012063.1 chr2 236910797 237085838 +449416 AC105760.1 chr2 237048599 237056167 +449425 COPS8 chr2 237085882 237100474 +449530 AC107079.1 chr2 237122910 237124097 +449534 AC112715.1 chr2 237257091 237257676 +449538 COL6A3 chr2 237324003 237414375 +450080 AC112721.1 chr2 237421420 237425276 +450085 AC112721.2 chr2 237428920 237434822 +450090 MLPH chr2 237485428 237555322 +450423 PRLH chr2 237566574 237567175 +450432 RAB17 chr2 237574322 237601614 +450545 AC104667.2 chr2 237591020 237595981 +450554 AC104667.1 chr2 237612977 237626525 +450558 LRRFIP1 chr2 237627587 237813682 +450760 AC012076.1 chr2 237728569 237731131 +450764 RBM44 chr2 237798389 237842808 +450891 RAMP1 chr2 237858893 237912106 +450938 UBE2F chr2 237966827 238042782 +451400 SCLY chr2 238060924 238099413 +451669 ESPNL chr2 238100340 238133287 +451751 KLHL30 chr2 238138668 238152947 +451773 ERFE chr2 238158970 238168900 +451832 ILKAP chr2 238170402 238203708 +451987 LINC02610 chr2 238224552 238231699 +452018 AC012485.1 chr2 238231684 238255633 +452030 HES6 chr2 238238267 238240662 +452130 PER2 chr2 238244044 238290102 +452208 AC012485.3 chr2 238289127 238300185 +452214 AC012485.2 chr2 238295392 238300620 +452220 TRAF3IP1 chr2 238320441 238400897 +452321 ASB1 chr2 238426742 238452250 +452387 AC016999.1 chr2 238427077 238427729 +452391 LINC01107 chr2 238510690 238555054 +452396 LINC01937 chr2 238554541 238740849 +452404 AC113618.2 chr2 238711224 238722543 +452411 AC145625.2 chr2 238771768 238784764 +452415 AC145625.1 chr2 238788648 238789716 +452419 TWIST2 chr2 238848032 238910534 +452438 LINC01940 chr2 238919302 238926269 +452450 HDAC4 chr2 239048168 239401654 +452712 AC017028.1 chr2 239114858 239118842 +452716 AC017028.2 chr2 239194118 239197654 +452720 HDAC4-AS1 chr2 239401436 239402364 +452733 AC023787.2 chr2 239439643 239531363 +452737 AC023787.3 chr2 239493587 239496697 +452741 AC023787.1 chr2 239538379 239544876 +452748 AC079612.1 chr2 239578301 239586094 +452752 AC079612.2 chr2 239625698 239630839 +452756 AC093802.2 chr2 239734956 239735538 +452759 AC093802.1 chr2 239762860 239824764 +452771 NDUFA10 chr2 239892450 240025345 +452985 OR6B2 chr2 240028965 240030456 +452993 OR6B3 chr2 240045077 240047027 +453009 COPS9 chr2 240126563 240136807 +453049 OTOS chr2 240139026 240144562 +453078 AC124861.3 chr2 240184716 240187878 +453082 AC124861.2 chr2 240189710 240194408 +453087 AC124861.1 chr2 240227560 240256035 +453092 GPC1 chr2 240435663 240468076 +453206 AC110619.1 chr2 240449315 240456714 +453219 ANKMY1 chr2 240479422 240569209 +453610 AC124862.1 chr2 240558089 240558925 +453613 DUSP28 chr2 240560054 240564014 +453649 RNPEPL1 chr2 240565804 240581372 +453737 CAPN10-DT chr2 240582700 240586699 +453740 CAPN10 chr2 240586734 240617705 +454010 GPR35 chr2 240605430 240631259 +454069 AQP12B chr2 240676418 240682906 +454139 AC011298.1 chr2 240686334 240690414 +454144 AQP12A chr2 240691851 240698483 +454182 KIF1A chr2 240713761 240821036 +455797 AGXT chr2 240868824 240880502 +455840 MAB21L4 chr2 240886048 240896889 +455900 CROCC2 chr2 240906330 240993311 +455976 AC104809.2 chr2 240954617 240967451 +455996 AC104809.1 chr2 240981515 240986072 +456000 SNED1 chr2 240998618 241095568 +456296 AC093585.1 chr2 241010045 241010744 +456300 AC005237.1 chr2 241015599 241064116 +456305 MTERF4 chr2 241072169 241102332 +456501 PASK chr2 241106099 241150264 +456785 PPP1R7 chr2 241149576 241183652 +457084 ANO7 chr2 241188509 241225377 +457228 HDLBP chr2 241227264 241317061 +457923 SEPTIN2 chr2 241315100 241354027 +458529 AC104841.1 chr2 241326334 241327039 +458533 AC005104.1 chr2 241351340 241353104 +458537 FARP2 chr2 241356285 241494841 +458808 AC005104.3 chr2 241360891 241372749 +458813 STK25 chr2 241492670 241509730 +459233 BOK-AS1 chr2 241544403 241558977 +459237 BOK chr2 241551424 241574131 +459256 AC133528.1 chr2 241581922 241582726 +459259 THAP4 chr2 241584405 241637158 +459328 ATG4B chr2 241637213 241673857 +459653 DTYMK chr2 241675747 241686944 +459726 ING5 chr2 241687085 241729478 +459851 AC114730.3 chr2 241724615 241725693 +459855 D2HGDH chr2 241734602 241768816 +460018 AC114730.1 chr2 241734715 241735498 +460022 AC114730.2 chr2 241754793 241755740 +460026 GAL3ST2 chr2 241776822 241804287 +460040 AC131097.1 chr2 241800916 241801907 +460044 AC131097.2 chr2 241808312 241812016 +460056 NEU4 chr2 241808825 241817413 +460222 AC131097.3 chr2 241844380 241845036 +460226 PDCD1 chr2 241849884 241858894 +460265 RTP5 chr2 241869600 241873823 +460286 LINC01237 chr2 241881363 242078722 +460309 FAM240C chr2 241893985 241902551 +460343 LINC01238 chr2 241970683 241977276 +460361 AC093642.1 chr2 242025183 242026176 +460365 AC093642.7 chr2 242037716 242041501 +460370 LINC01880 chr2 242047695 242084233 +460385 LINC01238 chr2 242087351 242088457 +460388 LINC01986 chr3 11745 24849 +460415 AC066595.1 chr3 53348 54346 +460419 CHL1-AS2 chr3 109707 197341 +460444 AC066595.2 chr3 123563 133500 +460448 CHL1 chr3 196763 409417 +460778 CHL1-AS1 chr3 363370 385795 +460786 AC087428.1 chr3 524012 551657 +460790 LINC01266 chr3 536062 846561 +460853 AC090044.1 chr3 857124 858091 +460857 AC087430.1 chr3 1008135 1012934 +460861 CNTN6 chr3 1092658 1404217 +461048 AC018814.1 chr3 1962381 1987470 +461052 CNTN4 chr3 2098813 3057959 +461403 CNTN4-AS2 chr3 2110409 2144241 +461408 AC087427.1 chr3 2135757 2141988 +461412 CNTN4-AS1 chr3 3039033 3069242 +461423 IL5RA chr3 3066326 3126613 +461671 TRNT1 chr3 3126933 3150879 +461959 CRBN chr3 3144628 3179727 +462131 AC024060.2 chr3 3152942 3153435 +462134 AC034195.1 chr3 3250687 3627296 +462153 SUMF1 chr3 3700814 4467273 +462280 LRRN1 chr3 3799431 3849834 +462297 AC023480.1 chr3 3918709 4046722 +462313 AC023483.1 chr3 4269153 4311495 +462318 SETMAR chr3 4303304 4317567 +462390 ITPR1-DT chr3 4490891 4493163 +462394 ITPR1 chr3 4493345 4847840 +464432 EGOT chr3 4749192 4751590 +464436 AC018816.1 chr3 4814294 4887293 +464468 BHLHE40-AS1 chr3 4896809 4980414 +464494 BHLHE40 chr3 4979437 4985323 +464518 ARL8B chr3 5122245 5180912 +464617 AC026202.2 chr3 5156905 5187329 +464623 AC026202.3 chr3 5187172 5188298 +464626 EDEM1 chr3 5187646 5219958 +464729 AC026202.1 chr3 5255535 5256761 +464733 AC087857.1 chr3 5962842 6124120 +464738 AC026167.1 chr3 6148484 6365885 +464743 AC069277.1 chr3 6490460 6736750 +464972 GRM7-AS3 chr3 6631008 6805479 +465016 GRM7 chr3 6770001 7741533 +465280 GRM7-AS2 chr3 6892632 6894022 +465284 AC066585.1 chr3 7241916 7250209 +465288 GRM7-AS1 chr3 7519741 7560333 +465296 AC077690.1 chr3 7606890 7790482 +465306 LMCD1-AS1 chr3 7951263 8611924 +465361 AC018832.1 chr3 8079322 8125538 +465380 AC023481.1 chr3 8359344 8366427 +465392 LMCD1 chr3 8501807 8574668 +465487 AC034187.1 chr3 8573726 8593124 +465491 SSUH2 chr3 8619400 8745040 +465816 CAV3 chr3 8733800 8841808 +465841 OXTR chr3 8750408 8769628 +465874 RAD18 chr3 8775402 8963773 +466014 SRGAP3 chr3 8980591 9363053 +466229 SRGAP3-AS1 chr3 9014123 9015979 +466233 AC037193.1 chr3 9100803 9104078 +466237 SRGAP3-AS2 chr3 9192493 9194453 +466257 SRGAP3-AS3 chr3 9216895 9219508 +466264 SRGAP3-AS4 chr3 9249742 9257507 +466269 AC026191.1 chr3 9292588 9363303 +466288 THUMPD3-AS1 chr3 9349689 9398579 +466430 THUMPD3 chr3 9362971 9386791 +466560 SETD5 chr3 9397615 9479240 +467276 LHFPL4 chr3 9498361 9553822 +467296 MTMR14 chr3 9649433 9702393 +467611 AC022382.2 chr3 9693182 9721399 +467616 CPNE9 chr3 9703826 9729908 +467775 BRPF1 chr3 9731729 9748015 +468017 OGG1 chr3 9749944 9788219 +468241 CAMK1 chr3 9757347 9769992 +468335 TADA3 chr3 9779860 9793011 +468422 ARPC4 chr3 9792495 9807726 +468534 TTLL3 chr3 9808086 9855138 +468977 AC022382.1 chr3 9812762 9813097 +468980 RPUSD3 chr3 9837849 9844602 +469154 CIDEC chr3 9866711 9880254 +469269 JAGN1 chr3 9890574 9894349 +469288 IL17RE chr3 9902612 9916402 +469523 IL17RC chr3 9917074 9933630 +470163 CRELD1 chr3 9933822 9945413 +470322 AC018809.1 chr3 9935706 9936258 +470325 PRRT3 chr3 9945542 9952408 +470365 PRRT3-AS1 chr3 9947404 9954787 +470371 AC018809.2 chr3 9958717 9962539 +470374 EMC3 chr3 9962537 10011116 +470440 AC022007.1 chr3 10004048 10011209 +470468 FANCD2 chr3 10026414 10101930 +470880 FANCD2OS chr3 10081317 10108255 +470922 BRK1 chr3 10115675 10127190 +470934 VHL chr3 10141008 10152220 +470959 AC034193.1 chr3 10149986 10153326 +470963 IRAK2 chr3 10164919 10243745 +470995 TATDN2 chr3 10248023 10281218 +471055 LINC00852 chr3 10284419 10285746 +471060 GHRL chr3 10285666 10292947 +471231 GHRLOS chr3 10285754 10294903 +471251 SEC13 chr3 10293131 10321112 +471462 ATP2B2 chr3 10324023 10708007 +472011 ATP2B2-IT1 chr3 10566255 10570375 +472015 ATP2B2-IT2 chr3 10626015 10629307 +472020 LINC00606 chr3 10759350 10764209 +472033 AC018495.1 chr3 10767464 10771718 +472037 SLC6A11 chr3 10816201 10940714 +472087 AC027128.1 chr3 10914196 10977981 +472093 SLC6A1 chr3 10992186 11039247 +473255 SLC6A1-AS1 chr3 11006098 11019224 +473260 AC066580.1 chr3 11060973 11091548 +473268 HRH1 chr3 11137093 11263557 +473305 AC083855.2 chr3 11193439 11225877 +473315 ATG7 chr3 11272309 11557665 +473645 VGLL4 chr3 11556069 11771350 +473867 AC022001.2 chr3 11607184 11610748 +473871 AC022001.3 chr3 11611602 11612197 +473874 TAMM41 chr3 11790442 11846919 +474028 SYN2 chr3 12004388 12192032 +474127 TIMP4 chr3 12153068 12158912 +474143 PPARG chr3 12287368 12434356 +474580 TSEN2 chr3 12484432 12539623 +474778 MKRN2OS chr3 12514934 12561059 +474813 MKRN2 chr3 12557087 12583713 +474875 RAF1 chr3 12583601 12664226 +475071 TMEM40 chr3 12733528 12769457 +475214 CAND2 chr3 12796472 12871916 +475356 AC034198.2 chr3 12832219 12832728 +475359 RPL32 chr3 12834485 12841582 +475447 LINC02022 chr3 12877522 12885211 +475452 IQSEC1 chr3 12897043 13283281 +475675 NUP210 chr3 13316235 13420322 +475791 HDAC11-AS1 chr3 13476982 13480053 +475795 HDAC11 chr3 13479724 13506424 +476126 FBLN2 chr3 13549125 13638422 +476277 LINC00620 chr3 13650696 13746638 +476296 WNT7A chr3 13816258 13880071 +476317 AC090004.2 chr3 14038647 14047181 +476321 CHCHD4 chr3 14112077 14124870 +476352 TMEM43 chr3 14124940 14143679 +476401 AC093495.1 chr3 14144637 14165978 +476476 XPC chr3 14145147 14178783 +476582 LSM3 chr3 14178817 14201122 +476596 AC093496.1 chr3 14272373 14303845 +476600 LINC01267 chr3 14348451 14352568 +476605 SLC6A6 chr3 14402576 14489349 +476832 GRIP2 chr3 14489107 14556075 +477041 AC090952.2 chr3 14602035 14641443 +477046 AC090952.1 chr3 14648194 14649432 +477050 CCDC174 chr3 14651746 14672659 +477150 C3orf20 chr3 14675141 14773036 +477274 AC090957.1 chr3 14764952 14767440 +477278 AC087591.1 chr3 14791534 14793504 +477282 LINC02011 chr3 14799331 14811414 +477287 FGD5 chr3 14810853 14934571 +477434 FGD5-AS1 chr3 14920347 14948424 +477466 NR2C2 chr3 14947584 15053600 +477718 MRPS25 chr3 15042460 15065317 +477788 RBSN chr3 15070073 15099163 +477935 CAPN7 chr3 15206152 15252916 +478054 SH3BP5-AS1 chr3 15254184 15264515 +478080 SH3BP5 chr3 15254353 15341368 +478216 METTL6 chr3 15381275 15440566 +478334 EAF1 chr3 15427598 15450635 +478370 EAF1-AS1 chr3 15436171 15455940 +478423 COLQ chr3 15450133 15521751 +478611 AC027129.1 chr3 15501439 15504060 +478615 HACL1 chr3 15560699 15601852 +478930 BTD chr3 15601341 15722311 +479235 ANKRD28 chr3 15667236 15859771 +479576 AC090945.1 chr3 15860158 15875979 +479581 AC090946.1 chr3 15970003 15971253 +479585 GALNT15 chr3 16174680 16231992 +479676 AC090953.2 chr3 16252123 16253130 +479680 DPH3 chr3 16257061 16264969 +479709 OXNAD1 chr3 16265160 16350299 +479880 RFTN1 chr3 16313574 16514026 +480030 AC090948.1 chr3 16314439 16314987 +480033 AC090948.2 chr3 16339308 16339871 +480036 AC090948.3 chr3 16345126 16346440 +480040 AC090948.4 chr3 16361348 16370398 +480045 AC010727.1 chr3 16444540 16447914 +480049 LINC00690 chr3 16524771 16541903 +480121 AC010139.1 chr3 16524800 16531807 +480130 DAZL chr3 16586792 16670306 +480202 AC091493.1 chr3 16687986 16697479 +480207 PLCL2 chr3 16802651 17090604 +480259 PLCL2-AS1 chr3 17042742 17044192 +480263 AC090644.1 chr3 17141015 17205165 +480270 TBC1D5 chr3 17157162 18444817 +480745 AC104451.2 chr3 17742952 17745665 +480749 AC132807.1 chr3 17990023 17995544 +480753 AC132807.2 chr3 18013226 18041603 +480764 SATB1 chr3 18345377 18445588 +480972 AC144521.1 chr3 18408680 18409635 +480975 SATB1-AS1 chr3 18445024 18920401 +481407 KCNH8 chr3 19148510 19535642 +481487 AC061958.1 chr3 19389185 19702795 +481502 EFHB chr3 19879472 19947025 +481623 RAB5A chr3 19947097 19985175 +481710 PP2D1 chr3 19979961 20012267 +481738 KAT2B chr3 20040446 20154404 +481799 SGO1 chr3 20160593 20186206 +482053 SGO1-AS1 chr3 20174244 21145967 +482102 AC116096.1 chr3 20388249 20390562 +482105 AC099753.1 chr3 21006730 21226305 +482110 ZNF385D chr3 21412218 22373321 +482216 ZNF385D-AS1 chr3 21542789 21579959 +482224 ZNF385D-AS2 chr3 21942566 21979828 +482235 UBE2E2-AS1 chr3 23194929 23202703 +482248 UBE2E2 chr3 23203020 23591794 +482331 UBE2E1-AS1 chr3 23804024 23806905 +482335 UBE2E1 chr3 23805955 23891640 +482443 NKIRAS1 chr3 23891660 23946591 +482571 RPL15 chr3 23916545 23924374 +482752 NR1D2 chr3 23945286 23980617 +482814 LINC00691 chr3 24096269 24103238 +482823 THRB chr3 24117153 24495756 +483211 THRB-IT1 chr3 24455136 24459434 +483215 THRB-AS1 chr3 24494087 24681711 +483260 AC012087.2 chr3 24496272 24499580 +483264 AC092422.1 chr3 24687919 25174305 +483272 RARB chr3 25174332 25597932 +483384 TOP2B chr3 25597905 25664907 +483636 NGLY1 chr3 25718944 25790039 +483855 OXSM chr3 25782917 25794534 +483925 LINC00692 chr3 25858525 25873748 +483950 AC099754.1 chr3 26614261 26622943 +483956 LRRC3B chr3 26622806 26717537 +484020 NEK10 chr3 27110085 27369460 +484353 AC099535.2 chr3 27369568 27387960 +484357 SLC4A7 chr3 27372721 27484420 +485125 LINC02084 chr3 27712910 27714005 +485128 EOMES chr3 27715949 27722711 +485180 LINC01980 chr3 27797552 27931579 +485443 LINC01981 chr3 27830886 27834136 +485458 LINC01967 chr3 27916774 28059268 +485480 CMC1 chr3 28241584 28325142 +485554 AZI2 chr3 28315003 28349050 +485709 ZCWPW2 chr3 28348721 28538122 +485795 RBMS3 chr3 28574791 30010391 +486144 RBMS3-AS3 chr3 29054570 29290726 +486164 RBMS3-AS2 chr3 29526251 29642809 +486192 RBMS3-AS1 chr3 29926811 29934156 +486197 AC025614.2 chr3 30292548 30305037 +486203 LINC01985 chr3 30518833 30527193 +486212 AC116035.1 chr3 30521664 30526254 +486234 TGFBR2 chr3 30606502 30694142 +486296 AC096921.2 chr3 30697661 30699576 +486299 GADL1 chr3 30726200 30894765 +486368 STT3B chr3 31532638 31637616 +486452 OSBPL10 chr3 31657890 32077580 +486610 OSBPL10-AS1 chr3 31704058 31721652 +486645 ZNF860 chr3 31981750 31991723 +486659 GPD1L chr3 32105689 32168713 +486743 AC097639.1 chr3 32236688 32238578 +486746 CMTM8 chr3 32238679 32370321 +486771 CMTM7 chr3 32391698 32483067 +486838 CMTM6 chr3 32481312 32502852 +486859 DYNC1LI1 chr3 32525974 32570858 +486968 CNOT10 chr3 32685145 32773875 +487254 CNOT10-AS1 chr3 32730635 32737454 +487258 TRIM71 chr3 32817997 32897824 +487272 CCR4 chr3 32951644 32956349 +487282 GLB1 chr3 32996609 33097202 +487527 TMPPE chr3 33090421 33097146 +487546 CRTAP chr3 33113979 33147773 +487589 AC112211.1 chr3 33144104 33147721 +487593 SUSD5 chr3 33150043 33218810 +487618 FBXL2 chr3 33277025 33403662 +487978 UBP1 chr3 33388336 33441371 +488172 CLASP2 chr3 33496245 33718356 +488938 AC112220.2 chr3 33793644 33798539 +488942 PDCD6IP chr3 33798571 33869707 +489178 LINC01811 chr3 33956972 34677247 +489387 AC123023.2 chr3 34152979 34157297 +489391 AC123023.1 chr3 34203244 34268811 +489395 AC018359.1 chr3 34524818 34543880 +489400 AC007483.1 chr3 34692820 34694174 +489404 ARPP21 chr3 35638945 35794496 +489921 ARPP21-AS1 chr3 35650197 35651961 +489925 STAC chr3 36380344 36548007 +490031 DCLK3 chr3 36712422 36764349 +490066 LINC02033 chr3 36819276 36822498 +490073 TRANK1 chr3 36826820 36945098 +490307 AC011816.2 chr3 36973117 36973672 +490310 EPM2AIP1 chr3 36985043 36993131 +490334 MLH1 chr3 36993332 37050918 +490847 LRRFIP2 chr3 37052626 37183689 +491186 AC126118.1 chr3 37182107 37182734 +491189 AC097359.3 chr3 37216779 37217988 +491192 AC097359.2 chr3 37241789 37244177 +491195 GOLGA4 chr3 37243177 37366751 +491466 C3orf35 chr3 37381062 37440186 +491544 ITGA9 chr3 37452115 37823507 +491655 ITGA9-AS1 chr3 37693655 37861802 +491853 CTDSPL chr3 37861880 37984469 +491956 VILL chr3 37988059 38007188 +492148 PLCD1 chr3 38007496 38029762 +492258 DLEC1 chr3 38039205 38124025 +492462 ACAA1 chr3 38103129 38137242 +492782 MYD88 chr3 38138478 38143022 +492973 OXSR1 chr3 38165089 38255484 +493092 SLC22A13 chr3 38265812 38278757 +493144 SLC22A14 chr3 38282294 38318575 +493210 XYLB chr3 38346760 38421348 +493401 ACVR2B-AS1 chr3 38451027 38454820 +493405 ACVR2B chr3 38453890 38493142 +493455 EXOG chr3 38496127 38542161 +493722 SCN5A chr3 38548057 38649673 +494287 SCN10A chr3 38696802 38816286 +494585 AC116038.1 chr3 38823902 38825302 +494590 SCN11A chr3 38845767 39051941 +494836 WDR48 chr3 39052013 39096671 +495036 GORASP1 chr3 39096659 39108363 +495287 TTC21A chr3 39107704 39138903 +495573 CSRNP1 chr3 39141855 39154562 +495604 AC092053.3 chr3 39148281 39172952 +495610 AC092053.2 chr3 39152906 39154723 +495613 AC092053.4 chr3 39177761 39179586 +495617 XIRP1 chr3 39183210 39192596 +495647 AC092053.6 chr3 39213069 39216585 +495651 AC092053.5 chr3 39258194 39263352 +495657 CX3CR1 chr3 39263494 39281735 +495708 AC104850.2 chr3 39292556 39384300 +495714 CCR8 chr3 39329709 39333680 +495735 SLC25A38 chr3 39383370 39397351 +495875 RPSA chr3 39406716 39412542 +495959 AC099332.2 chr3 39420644 39424870 +495963 AC099332.1 chr3 39425342 39448037 +495968 MOBP chr3 39467198 39529479 +496143 AC092058.1 chr3 39494837 39502567 +496148 MYRIP chr3 39808914 40260321 +496440 EIF1B-AS1 chr3 40061110 40309698 +496496 EIF1B chr3 40309707 40312424 +496520 ENTPD3-AS1 chr3 40313802 40453329 +496551 ENTPD3 chr3 40387184 40428744 +496673 RPL14 chr3 40457292 40468587 +496762 ZNF619 chr3 40477113 40491053 +496898 ZNF620 chr3 40477131 40518736 +496970 ZNF621 chr3 40524878 40574685 +497060 AC122683.1 chr3 40603125 40605427 +497064 AC099560.1 chr3 40719859 40862626 +497074 AC099541.2 chr3 40869548 40875980 +497080 AC099541.1 chr3 40970541 40971578 +497084 AC009743.1 chr3 41162287 41168547 +497090 CTNNB1 chr3 41194741 41260096 +498729 ULK4 chr3 41246599 41962130 +498929 TRAK1 chr3 42013802 42225890 +499271 CCK chr3 42257825 42266185 +499312 AC018358.1 chr3 42264989 42266390 +499315 LYZL4 chr3 42397083 42410610 +499352 VIPR1 chr3 42489299 42537573 +499624 VIPR1-AS1 chr3 42506465 42533258 +499843 SEC22C chr3 42547969 42601080 +500063 SS18L2 chr3 42581840 42595114 +500091 NKTR chr3 42600655 42648735 +500322 AC006059.1 chr3 42601963 42654388 +500342 ZBTB47 chr3 42653697 42667580 +500379 AC006059.5 chr3 42665873 42683793 +500384 KLHL40 chr3 42685537 42692544 +500402 HHATL chr3 42692663 42702824 +500566 HHATL-AS1 chr3 42702541 42706776 +500577 CCDC13 chr3 42705756 42773253 +500647 AC006059.4 chr3 42719401 42723136 +500652 CCDC13-AS1 chr3 42732575 42746768 +500666 LINC02158 chr3 42770612 42773635 +500670 HIGD1A chr3 42784298 42804531 +500727 AC099329.1 chr3 42785087 42852428 +500739 ACKR2 chr3 42804752 42887974 +500821 AC099329.2 chr3 42809414 42908105 +500838 KRBOX1 chr3 42809483 42942792 +500890 CYP8B1 chr3 42856005 42875898 +500907 ZNF662 chr3 42906142 42919334 +500955 KRBOX1-AS1 chr3 42934252 42936785 +500959 GASK1A chr3 42979267 43060211 +501010 POMGNT2 chr3 43079232 43106079 +501031 AC092042.1 chr3 43087479 43088068 +501035 AC092042.4 chr3 43088236 43090443 +501039 SNRK chr3 43286512 43424764 +501125 SNRK-AS1 chr3 43346923 43352152 +501134 ANO10 chr3 43354859 43691594 +501400 ABHD5 chr3 43690108 43734371 +501648 AC006055.1 chr3 43778961 43779982 +501653 AC006058.2 chr3 43996896 43997443 +501656 AC006058.3 chr3 43998081 43999149 +501659 AC006058.1 chr3 44117299 44122365 +501662 TOPAZ1 chr3 44241886 44332098 +501708 AC104187.1 chr3 44337941 44338552 +501711 TCAIM chr3 44338119 44409451 +501903 LINC01988 chr3 44424134 44429529 +501919 ZNF445 chr3 44431705 44477670 +501992 ZNF852 chr3 44494847 44510636 +502021 ZKSCAN7 chr3 44555193 44594173 +502138 ZKSCAN7-AS1 chr3 44557357 44685653 +502143 ZNF660 chr3 44578223 44599694 +502178 ZNF197 chr3 44584888 44648471 +502273 ZNF197-AS1 chr3 44617128 44624797 +502277 ZNF35 chr3 44648732 44660791 +502344 AC124045.1 chr3 44667412 44669364 +502347 ZNF502 chr3 44712643 44723831 +502392 ZNF501 chr3 44729596 44737083 +502422 KIAA1143 chr3 44737661 44761619 +502439 KIF15 chr3 44761721 44873376 +502749 TMEM42 chr3 44861904 44865670 +502764 TGM4 chr3 44874608 44914990 +502829 AC098649.1 chr3 44899178 44900925 +502833 ZDHHC3 chr3 44915257 44976185 +502966 EXOSC7 chr3 44975241 45036066 +503047 CLEC3B chr3 45001548 45036071 +503074 CDCP1 chr3 45082277 45146422 +503115 TMEM158 chr3 45224466 45226287 +503123 LARS2 chr3 45388561 45554726 +503509 LARS2-AS1 chr3 45483974 45509545 +503515 LIMD1 chr3 45555394 45686341 +503569 LIMD1-AS1 chr3 45676369 45689200 +503582 SACM1L chr3 45689056 45745409 +503939 SLC6A20 chr3 45755449 45796536 +504049 LZTFL1 chr3 45823316 45916042 +504277 AC099782.2 chr3 45842265 45866571 +504283 CCR9 chr3 45886504 45903175 +504333 FYCO1 chr3 45917899 45995824 +504455 CXCR6 chr3 45940933 45948351 +504490 XCR1 chr3 46017024 46027742 +504509 CCR3 chr3 46163604 46266706 +504574 CCR1 chr3 46201711 46208313 +504584 CCR2 chr3 46353734 46360928 +504626 CCR5AS chr3 46364955 46407059 +504632 CCR5 chr3 46370854 46376206 +504649 CCRL2 chr3 46407166 46412997 +504699 LINC02009 chr3 46416524 46423591 +504711 LTF chr3 46435645 46485234 +504905 RTP3 chr3 46497976 46500950 +504915 LRRC2 chr3 46515385 46580099 +504968 LRRC2-AS1 chr3 46557398 46559694 +504975 TDGF1 chr3 46574534 46582457 +505022 FAM240A chr3 46612435 46626543 +505045 AC104304.3 chr3 46647171 46661507 +505052 ALS2CL chr3 46668995 46693704 +505351 TMIE chr3 46694528 46710886 +505385 PRSS45P chr3 46742092 46750891 +505414 MYL3 chr3 46835111 46882172 +505543 PTH1R chr3 46877721 46903799 +505769 CCDC12 chr3 46921726 46982010 +505877 NBEAL2 chr3 46979683 47009704 +506310 SETD2 chr3 47016429 47163967 +506534 KIF9-AS1 chr3 47164186 47246601 +506547 KIF9 chr3 47228026 47283451 +506853 KLHL18 chr3 47282917 47346816 +506937 AC099778.1 chr3 47379089 47380999 +506940 PTPN23 chr3 47381011 47413435 +507076 SCAP chr3 47413681 47477126 +507420 ELP6 chr3 47495640 47513712 +507600 CSPG5 chr3 47562238 47580792 +507660 SMARCC1 chr3 47585269 47782106 +507795 AC112512.1 chr3 47601715 47604677 +507799 DHX30 chr3 47802909 47850195 +508158 MAP4 chr3 47850690 48089272 +508449 CDC25A chr3 48157146 48188417 +508558 CAMP chr3 48223347 48225491 +508585 ZNF589 chr3 48241100 48299253 +508677 NME6 chr3 48290722 48301685 +508962 SPINK8 chr3 48306842 48328341 +508977 FBXW12 chr3 48372219 48401259 +509095 PLXNB1 chr3 48403854 48430086 +509461 CCDC51 chr3 48432164 48440456 +509530 TMA7 chr3 48440257 48444208 +509551 AC134772.1 chr3 48440352 48446656 +509559 ATRIP chr3 48446710 48467645 +509815 TREX1 chr3 48465811 48467645 +509874 SHISA5 chr3 48467798 48504826 +510099 PFKFB4 chr3 48517684 48562015 +510366 UCN2 chr3 48561718 48563781 +510376 COL7A1 chr3 48564073 48595267 +510764 UQCRC1 chr3 48599002 48610976 +510879 TMEM89 chr3 48620759 48621769 +510889 SLC26A6 chr3 48625723 48635493 +511368 CELSR3 chr3 48636463 48662886 +511462 LINC02585 chr3 48663776 48669174 +511467 AC141002.1 chr3 48672455 48672733 +511470 NCKIPSD chr3 48673844 48686364 +511615 IP6K2 chr3 48688003 48740353 +511915 PRKAR2A chr3 48744597 48847874 +512041 PRKAR2A-AS1 chr3 48847572 48851981 +512064 SLC25A20 chr3 48856926 48898904 +512135 ARIH2OS chr3 48917782 48919385 +512145 ARIH2 chr3 48918821 48986382 +512445 AC137630.2 chr3 48979918 48983985 +512452 AC137630.1 chr3 48985049 48989988 +512456 AC137630.4 chr3 48985485 48985963 +512459 P4HTM chr3 48989889 49007153 +512572 WDR6 chr3 49007062 49015953 +512795 DALRD3 chr3 49015488 49022293 +512999 NDUFAF3 chr3 49020459 49023495 +513069 IMPDH2 chr3 49024325 49029408 +513188 AC137630.3 chr3 49029316 49029706 +513191 QRICH1 chr3 49029707 49094363 +513331 QARS chr3 49095932 49105130 +514216 USP19 chr3 49108046 49120938 +514553 LAMB2 chr3 49121114 49133118 +514771 CCDC71 chr3 49162535 49166331 +514781 KLHDC8B chr3 49171598 49176486 +514815 C3orf84 chr3 49177634 49191858 +514846 CCDC36 chr3 49198428 49258106 +514932 AC121247.1 chr3 49260085 49261316 +514937 C3orf62 chr3 49268596 49277232 +514972 USP4 chr3 49277144 49340712 +515201 RHOA chr3 49359145 49412998 +515270 RHOA-IT1 chr3 49365145 49367006 +515274 TCTA chr3 49412206 49416475 +515303 AMT chr3 49416775 49422753 +515960 NICN1 chr3 49422946 49429326 +516052 DAG1 chr3 49468703 49535618 +516244 BSN-DT chr3 49549306 49554366 +516256 BSN chr3 49554477 49671549 +516289 BSN-AS1 chr3 49640483 49641769 +516293 APEH chr3 49674014 49683971 +516585 MST1 chr3 49683947 49689501 +516755 RNF123 chr3 49689538 49721529 +517151 AMIGO3 chr3 49716829 49719684 +517159 GMPPB chr3 49716844 49723951 +517237 IP6K1 chr3 49724294 49786542 +517332 CDHR4 chr3 49790732 49799873 +517435 INKA1 chr3 49803261 49805030 +517453 UBA7 chr3 49805209 49813953 +517548 TRAIP chr3 49828601 49856574 +517699 CAMKV chr3 49857988 49869935 +517998 MST1R chr3 49887002 49903873 +518271 AC105935.2 chr3 49899302 49903757 +518275 AC105935.1 chr3 49903845 49916937 +518285 MON1A chr3 49907160 49930173 +518391 RBM6 chr3 49940007 50100045 +518819 RBM5 chr3 50088919 50119021 +519100 RBM5-AS1 chr3 50099603 50100988 +519103 SEMA3F-AS1 chr3 50116022 50156085 +519112 SEMA3F chr3 50155045 50189075 +519308 GNAT1 chr3 50191610 50197696 +519375 SLC38A3 chr3 50205246 50221486 +519502 GNAI2 chr3 50226292 50259362 +519693 U73169.1 chr3 50239618 50239984 +519696 U73166.1 chr3 50260303 50263358 +519706 SEMA3B-AS1 chr3 50266641 50267371 +519710 SEMA3B chr3 50267558 50277546 +520009 LSMEM2 chr3 50279087 50288114 +520023 IFRD2 chr3 50287732 50292918 +520187 HYAL3 chr3 50292831 50299405 +520269 NAA80 chr3 50296402 50299421 +520330 HYAL1 chr3 50299890 50312381 +520436 HYAL2 chr3 50317790 50322782 +520530 TUSC2 chr3 50320027 50328251 +520587 RASSF1 chr3 50329782 50340980 +520707 RASSF1-AS1 chr3 50337511 50338300 +520710 ZMYND10-AS1 chr3 50341106 50345697 +520714 ZMYND10 chr3 50341110 50345732 +520844 NPRL2 chr3 50347330 50350826 +521123 CYB561D2 chr3 50350695 50358460 +521180 TMEM115 chr3 50354750 50359521 +521190 CACNA2D2 chr3 50362799 50504244 +521688 CYB561D2 chr3 50365334 50368197 +521711 C3orf18 chr3 50558025 50571027 +521824 HEMK1 chr3 50569152 50596168 +521964 AC096920.1 chr3 50599879 50601148 +521970 CISH chr3 50606490 50611831 +521998 MAPKAPK3 chr3 50611520 50649291 +522132 LINC02019 chr3 50669989 50672048 +522138 DOCK3 chr3 50674927 51384198 +522250 MANF chr3 51385291 51389397 +522300 RBM15B chr3 51391285 51397908 +522308 DCAF1 chr3 51395867 51500002 +522458 RAD54L2 chr3 51541144 51668667 +522593 TEX264 chr3 51662693 51704323 +522772 AC099050.1 chr3 51668592 51671176 +522776 GRM2 chr3 51707068 51718613 +522854 IQCF6 chr3 51778561 51779241 +522890 IQCF3 chr3 51826883 51830856 +522967 IQCF2 chr3 51861615 51863424 +522983 IQCF5-AS1 chr3 51873596 51875767 +522988 IQCF5 chr3 51873721 51875601 +522998 IQCF1 chr3 51894876 51903353 +523027 AC115284.4 chr3 51927071 51932483 +523035 RRP9 chr3 51933429 51941904 +523071 PARP3 chr3 51942345 51948867 +523214 GPR62 chr3 51955381 51957499 +523222 PCBP4 chr3 51957454 51974016 +523598 ABHD14B chr3 51968510 51983409 +523690 ABHD14A chr3 51971426 51981199 +523762 ACY1 chr3 51983340 51989197 +524248 RPL29 chr3 51993522 51995895 +524367 AC115284.3 chr3 52046763 52048657 +524372 DUSP7 chr3 52048919 52056571 +524391 POC1A chr3 52075226 52154690 +524471 AC097637.3 chr3 52183722 52186834 +524475 ALAS1 chr3 52198086 52214327 +524604 TLR9 chr3 52221080 52226163 +524614 TWF2 chr3 52228612 52239158 +524664 AC006252.1 chr3 52239258 52241097 +524671 PPM1M chr3 52245759 52250599 +524793 WDR82 chr3 52254434 52288020 +524855 GLYCTK chr3 52287089 52295257 +524966 GLYCTK-AS1 chr3 52288580 52299067 +524979 DNAH1 chr3 52316319 52400491 +525327 BAP1 chr3 52401008 52410008 +525493 PHF7 chr3 52410660 52423641 +525652 SEMA3G chr3 52433035 52445103 +525724 TNNC1 chr3 52451100 52454041 +525756 NISCH chr3 52455118 52493068 +525980 STAB1 chr3 52495338 52524495 +526211 NT5DC2 chr3 52524385 52535054 +526431 SMIM4 chr3 52534013 52579237 +526466 PBRM1 chr3 52545352 52685917 +527230 GNL3 chr3 52681156 52694497 +527390 GLT8D1 chr3 52694488 52706032 +527599 SPCS1 chr3 52704955 52711148 +527647 NEK4 chr3 52708444 52770946 +527812 ITIH1 chr3 52777595 52792068 +528022 ITIH3 chr3 52794768 52809009 +528196 ITIH4 chr3 52812962 52830688 +528462 ITIH4-AS1 chr3 52823935 52825314 +528467 MUSTN1 chr3 52833114 52835019 +528490 STIMATE chr3 52836219 52897548 +528548 SFMBT1 chr3 52903572 53046750 +528652 RFT1 chr3 53088483 53130453 +528740 PRKCD chr3 53156009 53192717 +529058 AC097015.1 chr3 53196820 53197359 +529062 TKT chr3 53224712 53256052 +529321 DCP1A chr3 53283429 53347586 +529424 CACNA1D chr3 53328963 53813733 +530538 AC012467.1 chr3 53797764 53798019 +530541 CHDH chr3 53812335 53846419 +530583 IL17RB chr3 53846568 53865794 +530645 AC012467.2 chr3 53858994 53861576 +530648 ACTR8 chr3 53867066 53882152 +530750 SELENOK chr3 53884417 53891962 +530806 AC115282.2 chr3 54033988 54058864 +530813 AC115282.1 chr3 54057690 54125377 +530818 CACNA2D3 chr3 54122547 55074557 +531419 ESRG chr3 54632122 54639857 +531425 CACNA2D3-AS1 chr3 54874605 54901255 +531434 LRTM1 chr3 54918231 54967088 +531457 AC092059.1 chr3 55166910 55175732 +531462 LINC02017 chr3 55178172 55189214 +531467 LINC02030 chr3 55226862 55300738 +531491 AC121764.2 chr3 55335462 55350915 +531495 AC121764.3 chr3 55360443 55361829 +531499 WNT5A chr3 55465715 55490539 +531566 WNT5A-AS1 chr3 55487699 55488308 +531570 AC121764.1 chr3 55493830 55505261 +531576 ERC2 chr3 55508311 56468467 +531765 AC025572.1 chr3 55610603 55613104 +531770 ERC2-IT1 chr3 55657206 55659382 +531773 CCDC66 chr3 56557161 56621837 +532096 TASOR chr3 56620133 56683237 +532294 ARHGEF3 chr3 56727418 57079329 +532579 ARHGEF3-AS1 chr3 56940040 56960854 +532588 SPATA12 chr3 57060664 57075432 +532598 AC097358.2 chr3 57078943 57080101 +532601 IL17RD chr3 57089982 57170306 +532765 HESX1 chr3 57197838 57227606 +532818 APPL1 chr3 57227726 57278105 +532995 ASB14 chr3 57268342 57292685 +533056 AC093928.1 chr3 57293083 57300187 +533060 DNAH12 chr3 57293699 57544344 +533475 AC092418.2 chr3 57555581 57556054 +533478 PDE12 chr3 57556274 57566848 +533499 ARF4 chr3 57571363 57598220 +533596 ARF4-AS1 chr3 57597531 57600927 +533610 DENND6A chr3 57625454 57693077 +533695 DENND6A-AS1 chr3 57628810 57654918 +533699 DENND6A-DT chr3 57693205 57696596 +533703 SLMAP chr3 57755450 57930003 +534539 FLNB chr3 58008400 58172251 +535089 FLNB-AS1 chr3 58162547 58170636 +535096 AC137936.1 chr3 58174478 58178374 +535101 DNASE1L3 chr3 58192257 58214697 +535207 ABHD6 chr3 58237532 58295693 +535305 RPP14 chr3 58306247 58324695 +535372 HTD2 chr3 58306262 58318574 +535464 AC098479.1 chr3 58329965 58330118 +535467 PXK chr3 58332880 58426127 +535898 PDHB chr3 58427630 58433857 +536056 AC135507.1 chr3 58428255 58428815 +536059 AC116036.2 chr3 58490830 58491291 +536062 KCTD6 chr3 58492096 58502360 +536116 ACOX2 chr3 58505136 58537283 +536273 FAM107A chr3 58564117 58627610 +536374 AC119424.1 chr3 58572744 58574319 +536379 FAM3D-AS1 chr3 58607080 58644491 +536390 FAM3D chr3 58633946 58666834 +536488 C3orf67 chr3 58717365 59050084 +536728 C3orf67-AS1 chr3 58824437 59019093 +536755 AC126121.3 chr3 59050164 59754808 +536803 AC138057.1 chr3 59380024 59388704 +536808 AC126121.2 chr3 59464330 59510678 +536812 FHIT chr3 59747277 61251459 +536926 AC093418.1 chr3 59809269 59811310 +536930 PTPRG chr3 61561569 62297609 +537095 PTPRG-AS1 chr3 62221249 62369406 +537240 C3orf14 chr3 62318973 62336213 +537331 FEZF2 chr3 62369681 62374324 +537377 CADPS chr3 62398346 62875416 +537783 LINC00698 chr3 62950430 63125062 +537819 SYNPR chr3 63228315 63616924 +537987 SYNPR-AS1 chr3 63423596 63550051 +537994 SNTN chr3 63652675 63679020 +538034 C3orf49 chr3 63819299 63848636 +538109 THOC7 chr3 63833870 63863868 +538197 THOC7-AS1 chr3 63860645 63861819 +538201 AC104162.2 chr3 63863155 63905838 +538227 ATXN7 chr3 63898399 64003453 +538363 SCAANT1 chr3 63911518 63911772 +538366 PSMD6-AS2 chr3 64004022 64012148 +538371 AC012557.1 chr3 64008082 64008692 +538374 PSMD6 chr3 64010549 64024010 +538523 PSMD6-AS1 chr3 64011964 64016246 +538527 AC012557.2 chr3 64019508 64019925 +538530 AC092040.1 chr3 64067964 64103131 +538535 LINC00994 chr3 64078361 64087363 +538541 PRICKLE2 chr3 64092236 64445476 +538638 PRICKLE2-AS1 chr3 64099273 64101122 +538645 PRICKLE2-AS2 chr3 64103470 64106056 +538651 PRICKLE2-AS3 chr3 64187544 64200965 +538657 PRICKLE2-DT chr3 64445231 64456070 +538668 ADAMTS9 chr3 64515654 64688000 +538982 ADAMTS9-AS1 chr3 64561322 64592757 +539061 ADAMTS9-AS2 chr3 64684909 65053439 +539095 LINC02040 chr3 65174916 65193509 +539112 MAGI1 chr3 65353525 66038834 +539619 AC121493.1 chr3 65359268 65359717 +539622 MAGI1-IT1 chr3 65872815 65954558 +539627 MAGI1-AS1 chr3 65893816 65925297 +539632 SLC25A26 chr3 66133610 66388116 +539765 LRIG1 chr3 66378797 66501263 +539905 AC098969.2 chr3 66780076 66824439 +539910 AC098969.1 chr3 66794041 66796921 +539914 AC020655.1 chr3 66997168 66998020 +539917 KBTBD8 chr3 66998307 67011210 +539958 AC114401.1 chr3 67296300 67306359 +539965 SUCLG2 chr3 67360460 67654614 +540058 SUCLG2-AS1 chr3 67654669 67947713 +540133 TAFA1 chr3 68004247 68545621 +540175 AC104167.1 chr3 68500613 68505873 +540179 TAFA4 chr3 68731766 68953297 +540225 EOGT chr3 68975217 69013684 +540452 AC109587.1 chr3 69013941 69056622 +540504 TMF1 chr3 69019827 69052339 +540666 UBA3 chr3 69054730 69080408 +540899 ARL6IP5 chr3 69084937 69106092 +540949 LMOD3 chr3 69106872 69123032 +540987 FRMD4B chr3 69168782 69542583 +541225 AC099328.2 chr3 69564106 69571172 +541230 AC104445.1 chr3 69591341 69593121 +541234 MITF chr3 69739435 69968337 +541553 SAMMSON chr3 69999550 70518064 +541727 MDFIC2 chr3 70194479 70312638 +541740 AC104633.1 chr3 70605420 70617605 +541745 AC104633.2 chr3 70617766 70620325 +541749 FOXP1 chr3 70952817 71583993 +543415 FOXP1-AS1 chr3 71289769 71305853 +543422 AC097634.2 chr3 71567863 71571112 +543426 FOXP1-IT1 chr3 71570255 71574457 +543430 AC097634.3 chr3 71581721 71628558 +543435 AC097634.1 chr3 71584943 71587409 +543438 EIF4E3 chr3 71675414 71754773 +543598 GPR27 chr3 71753855 71756496 +543606 PROK2 chr3 71771655 71785206 +543631 AC096970.1 chr3 71785428 71786425 +543635 LINC00877 chr3 71943592 72279503 +543770 AC105265.3 chr3 72061061 72069933 +543781 AC105265.4 chr3 72080564 72084641 +543785 LINC00870 chr3 72151236 72207776 +543810 AC112219.2 chr3 72178279 72178810 +543813 AC112219.1 chr3 72202944 72209914 +543818 AC134508.2 chr3 72301616 72319429 +543823 AC134508.1 chr3 72321051 72324027 +543826 RYBP chr3 72371825 72446621 +543838 AC104435.2 chr3 72504806 72550552 +543843 AC097369.2 chr3 72738918 72740525 +543847 SHQ1 chr3 72749277 72861914 +543966 GXYLT2 chr3 72888046 72998138 +544005 PPP4R2 chr3 72996803 73069198 +544103 EBLN2 chr3 73061659 73063337 +544111 PDZRN3 chr3 73382431 73624941 +544275 PDZRN3-AS1 chr3 73621713 73626796 +544293 LINC02005 chr3 73805754 73902960 +544313 LINC02047 chr3 73999805 74005609 +544317 CNTN3 chr3 74262568 74521140 +544371 AC117481.1 chr3 75214510 75240770 +544376 LINC02018 chr3 75435232 75538029 +544648 FRG2C chr3 75664330 75667220 +544675 LINC00960 chr3 75672300 75742048 +544721 ZNF717 chr3 75678660 75785583 +544808 ROBO2 chr3 75906695 77649964 +545207 AC133040.1 chr3 77567508 77571881 +545211 LINC02077 chr3 78038705 78046794 +545216 AC117462.1 chr3 78087404 78092270 +545221 AC108752.1 chr3 78266940 78294731 +545235 ROBO1 chr3 78597239 79767998 +545687 AC117461.1 chr3 79411714 79470827 +545711 AC108690.1 chr3 80602716 80677898 +545717 AC068756.1 chr3 80761042 80788963 +545722 LINC02050 chr3 80764862 80789388 +545747 LINC02027 chr3 80993854 81105182 +545768 AC099542.2 chr3 81208193 81208914 +545772 AC099542.1 chr3 81246579 81297345 +545784 AC107302.2 chr3 81359739 81368191 +545789 GBE1 chr3 81489703 81761645 +545879 AC017015.2 chr3 81762706 81764756 +545884 AC129807.1 chr3 81840514 81953534 +545940 LINC02008 chr3 81986138 82463675 +545991 AC023503.1 chr3 83384445 83437728 +545996 AC092825.1 chr3 83924157 83937031 +546000 AC117464.1 chr3 83953639 84051419 +546015 LINC00971 chr3 84638405 84881924 +546078 LINC02025 chr3 84881984 84893379 +546088 AC132660.2 chr3 84940619 84947061 +546092 CADM2 chr3 84958981 86074429 +546173 CADM2-AS2 chr3 85799987 85828050 +546179 CADM2-AS1 chr3 85992183 86028007 +546183 AC108733.1 chr3 86258936 86267424 +546194 LINC02070 chr3 86481943 86496996 +546198 VGLL3 chr3 86876388 86991149 +546247 AC107204.1 chr3 87089129 87158363 +546265 CHMP2B chr3 87227271 87255556 +546333 POU1F1 chr3 87259404 87276584 +546392 AC108749.1 chr3 87641412 87793629 +546407 HTR1F chr3 87990696 87993835 +546415 CGGBP1 chr3 88051944 88149885 +546472 ZNF654 chr3 88059255 88144664 +546518 C3orf38 chr3 88149959 88168729 +546547 CSNKA2IP chr3 88338416 88467594 +546576 EPHA3 chr3 89107621 89482134 +546674 AC109129.1 chr3 89283016 89314604 +546679 PROS1 chr3 93873033 93980003 +546977 ARL13B chr3 93980139 94055678 +547141 STX19 chr3 94014365 94028597 +547151 DHFR2 chr3 94047836 94063389 +547203 NSUN3 chr3 94062980 94131832 +547259 LINC00879 chr3 94937980 95168351 +547531 AC106719.1 chr3 95916726 95919552 +547535 MTRNR2L12 chr3 96617188 96618236 +547543 AC109782.1 chr3 96810838 96814407 +547553 EPHA6 chr3 96814581 97752460 +547783 AC110491.1 chr3 97759523 97761532 +547786 ARL6 chr3 97764521 97801229 +547935 AC110491.3 chr3 97800733 97821884 +547940 CRYBG3 chr3 97822011 97944984 +548009 AC110491.2 chr3 97836986 97874691 +548017 RIOX2 chr3 97941818 97972457 +548148 AC026100.1 chr3 97973012 97975056 +548153 GABRR3 chr3 97986673 98035304 +548209 OR5AC2 chr3 98087173 98088102 +548216 AC117460.1 chr3 98099908 98148134 +548220 OR5H1 chr3 98130721 98138548 +548236 OR5H14 chr3 98147479 98156614 +548253 OR5H15 chr3 98166696 98169774 +548269 AC117473.1 chr3 98233651 98457898 +548275 OR5H6 chr3 98263252 98265356 +548298 OR5H2 chr3 98282888 98283832 +548311 OR5K4 chr3 98353854 98354819 +548318 OR5K3 chr3 98390666 98391631 +548325 OR5K1 chr3 98463201 98472924 +548342 OR5K2 chr3 98497604 98498663 +548350 CLDND1 chr3 98497912 98523066 +548739 AC021660.2 chr3 98522570 98525334 +548743 GPR15 chr3 98531978 98534681 +548751 AC021660.4 chr3 98573061 98578231 +548755 CPOX chr3 98579446 98593648 +548795 ST3GAL6-AS1 chr3 98706236 98732757 +548876 ST3GAL6 chr3 98732236 98821201 +549285 DCBLD2 chr3 98795941 98901695 +549406 AC091212.1 chr3 98902424 99018562 +549412 LINC00973 chr3 98981058 98983096 +549416 AC078828.1 chr3 99500347 99505508 +549420 AC107029.1 chr3 99507187 99529985 +549428 AC107029.2 chr3 99598064 99637308 +549444 COL8A1 chr3 99638475 99799226 +549528 AC069222.1 chr3 99802699 99806058 +549531 CMSS1 chr3 99817837 100181732 +549661 FILIP1L chr3 99830141 100114513 +549761 AC129803.1 chr3 100132903 100260264 +549767 TBC1D23 chr3 100260992 100325251 +549950 NIT2 chr3 100334739 100361635 +550043 TOMM70 chr3 100363431 100401089 +550079 LNP1 chr3 100401532 100456319 +550119 TMEM45A chr3 100492619 100577444 +550186 ADGRG7 chr3 100609601 100695479 +550263 TFG chr3 100709331 100748964 +550431 ABI3BP chr3 100749156 100993515 +551260 IMPG2 chr3 101222546 101320575 +551304 SENP7 chr3 101324205 101513241 +551587 TRMT10C chr3 101561868 101566446 +551604 PCNP chr3 101574180 101594465 +551685 ZBTB11 chr3 101648889 101677132 +551725 ZBTB11-AS1 chr3 101676475 101679217 +551728 RPL24 chr3 101681091 101686718 +551788 AC084198.2 chr3 101686827 101700926 +551793 CEP97 chr3 101724593 101770562 +551898 NXPE3 chr3 101779202 101828231 +552006 AC020651.1 chr3 101823793 101824998 +552010 NFKBIZ chr3 101827991 101861022 +552175 AC020651.2 chr3 101878333 101925726 +552181 LINC02085 chr3 101940859 101997926 +552187 AC106712.1 chr3 101960358 101997926 +552196 ZPLD1 chr3 102099244 102479841 +552298 AC063938.1 chr3 102621061 102673986 +552317 ALCAM chr3 105366909 105576900 +552484 CBLB chr3 105655461 105869552 +552960 AC131237.1 chr3 106160417 106224375 +552966 AC079382.2 chr3 106367979 106427977 +552976 LINC00882 chr3 106449775 107240671 +553470 AC117435.1 chr3 107046026 107053166 +553474 DUBR chr3 107220744 107348464 +553616 AC063944.1 chr3 107272611 107421338 +553660 AC063944.3 chr3 107329430 107329962 +553663 CCDC54 chr3 107377439 107378635 +553671 LINC01990 chr3 107430892 107463912 +553700 BBX chr3 107522936 107811339 +554132 LINC00636 chr3 107834586 107928907 +554145 LINC00635 chr3 107840228 107882250 +555740 AC012020.1 chr3 108032456 108039916 +555749 CD47 chr3 108043091 108091862 +555848 LINC01215 chr3 108125821 108138610 +555853 IFT57 chr3 108160812 108222435 +555918 HHLA2 chr3 108296490 108378285 +556134 MYH15 chr3 108380368 108529322 +556247 CIP2A chr3 108549864 108589644 +556481 DZIP3 chr3 108589705 108694840 +556754 RETNLB chr3 108743424 108757384 +556772 TRAT1 chr3 108822770 108855005 +556818 GUCA1C chr3 108907792 108953879 +556855 MORC1 chr3 108958248 109118134 +556976 MORC1-AS1 chr3 109101456 109110342 +556981 C3orf85 chr3 109118252 109151401 +557030 AC063923.2 chr3 109176438 109177365 +557033 LINC00488 chr3 109178143 109216965 +557043 DPPA2 chr3 109293788 109316517 +557067 DPPA4 chr3 109326141 109337572 +557136 LINC01205 chr3 109409990 109723273 +557179 AC078980.1 chr3 109648107 109810861 +557184 AC117430.1 chr3 110527482 110529582 +557190 NECTIN3-AS1 chr3 110888384 111071553 +557222 NECTIN3 chr3 111070071 111275563 +557336 CD96 chr3 111292719 111665750 +557494 AC092916.1 chr3 111466313 111497095 +557498 ZBED2 chr3 111592900 111595346 +557508 PLCXD2 chr3 111674676 111846447 +557557 PLCXD2-AS1 chr3 111676736 111677433 +557561 PHLDB2 chr3 111732497 111976517 +557939 AC117509.1 chr3 111835723 111860730 +557943 ABHD10 chr3 111979010 111993368 +558003 TAGLN3 chr3 111998739 112013887 +558089 TMPRSS7 chr3 112034843 112081269 +558255 C3orf52 chr3 112086335 112131004 +558328 GCSAM chr3 112120839 112133270 +558444 TBILA chr3 112133423 112135359 +558447 SLC9C1 chr3 112140898 112294227 +558637 AC112487.1 chr3 112302478 112332791 +558650 CD200 chr3 112332347 112362812 +558753 AC092894.1 chr3 112396647 112409134 +558757 BTLA chr3 112463966 112499472 +558792 ATG3 chr3 112532510 112562046 +558918 SLC35A5 chr3 112561709 112585579 +559014 CCDC80 chr3 112596794 112649530 +559094 LINC02042 chr3 112736447 112749319 +559101 CD200R1L-AS1 chr3 112802478 112812819 +559109 CD200R1L chr3 112815709 112846856 +559192 CD200R1 chr3 112921205 112975103 +559270 AC074044.1 chr3 112990447 112991153 +559273 GTPBP8 chr3 112990984 113015060 +559409 NEPRO chr3 113002444 113019861 +559719 AC078785.1 chr3 113019468 113184377 +559754 AC078785.2 chr3 113050912 113063443 +559759 LINC02044 chr3 113142350 113167819 +559765 BOC chr3 113211003 113287459 +560032 AC026329.1 chr3 113259786 113266824 +560036 CFAP44 chr3 113286930 113441610 +560288 CFAP44-AS1 chr3 113403988 113433992 +560307 SPICE1 chr3 113442718 113515187 +560416 SIDT1 chr3 113532296 113629578 +560582 SIDT1-AS1 chr3 113588748 113590189 +560586 USF3 chr3 113648385 113696646 +560644 NAA50 chr3 113716458 113746300 +560778 AC108693.2 chr3 113746872 113747408 +560782 ATP6V1A chr3 113747033 113812056 +560895 GRAMD1C chr3 113828182 113947174 +561129 AC128687.2 chr3 113947005 113947570 +561132 ZDHHC23 chr3 113947901 113965401 +561228 CCDC191 chr3 113964137 114056594 +561370 AC128687.3 chr3 113986835 113992113 +561374 AC092896.2 chr3 113998782 114016261 +561380 QTRT2 chr3 114005833 114088422 +561536 DRD3 chr3 114128652 114199407 +561619 AC093010.2 chr3 114214313 114236204 +561627 ZNF80 chr3 114234631 114237578 +561653 TIGIT chr3 114276913 114310288 +561725 AC093010.3 chr3 114314501 114329714 +561728 ZBTB20 chr3 114314501 115147271 +561969 ZBTB20-AS1 chr3 114351771 114388978 +562049 ZBTB20-AS5 chr3 114445521 114529452 +562064 ZBTB20-AS2 chr3 114684580 114687609 +562068 ZBTB20-AS3 chr3 114873114 114876514 +562073 ZBTB20-AS4 chr3 115100423 115103061 +562077 AC026341.1 chr3 115147605 115564389 +562148 AC026341.2 chr3 115413476 115486449 +562153 AC026341.3 chr3 115418862 115438550 +562157 GAP43 chr3 115623324 115721490 +562182 AC092468.1 chr3 115658533 115661279 +562186 LSAMP chr3 115802363 117139389 +562272 LSAMP-AS1 chr3 116360024 116370090 +562278 LINC00903 chr3 116552473 116568264 +562282 TUSC7 chr3 116709235 116723581 +562326 LINC00901 chr3 116921431 116932238 +562330 AC092691.1 chr3 117672154 117997592 +562338 LINC02024 chr3 117678693 117691005 +562380 AC092691.3 chr3 117719859 117794384 +562398 AC068633.1 chr3 118004819 118810836 +562426 AC068633.2 chr3 118488876 118491760 +562430 IGSF11 chr3 118900557 119146068 +562589 IGSF11-AS1 chr3 118943073 118948241 +562599 TEX55 chr3 119146151 119160042 +562647 UPK1B chr3 119173517 119205143 +562739 B4GALT4 chr3 119211732 119240946 +562971 B4GALT4-AS1 chr3 119226486 119290666 +562981 ARHGAP31 chr3 119294383 119420714 +563026 ARHGAP31-AS1 chr3 119314293 119322760 +563030 TMEM39A chr3 119428949 119468830 +563169 POGLUT1 chr3 119468963 119494708 +563315 AC073352.1 chr3 119497678 119498181 +563318 TIMMDC1 chr3 119498547 119525090 +563431 CD80 chr3 119524293 119559614 +563483 AC073352.2 chr3 119579212 119579650 +563486 ADPRH chr3 119579268 119589945 +563557 PLA1A chr3 119597875 119629811 +563684 POPDC2 chr3 119636457 119665324 +563766 COX17 chr3 119654513 119677454 +563840 AC023494.1 chr3 119666282 119670688 +563844 MAATS1 chr3 119703022 119767102 +564096 AC069444.1 chr3 119744139 119750350 +564101 NR1I2 chr3 119780484 119818485 +564220 GSK3B chr3 119821323 120094417 +564313 AC092910.3 chr3 120094895 120136783 +564328 GPR156 chr3 120164645 120285094 +564417 LRRC58 chr3 120324509 120349354 +564431 AC063952.4 chr3 120365993 120368326 +564436 FSTL1 chr3 120392293 120450993 +564535 AC126182.3 chr3 120448974 120509675 +564540 NDUFB4 chr3 120596328 120602507 +564593 HGD chr3 120628172 120682269 +564713 RABL3 chr3 120686681 120742993 +564854 GTF2E1 chr3 120742637 120783069 +564900 AC072026.2 chr3 120811530 120908093 +564926 LINC02049 chr3 120833440 120836360 +564930 AC072026.3 chr3 120833936 120871794 +564937 STXBP5L chr3 120908072 121424761 +565306 AC079841.2 chr3 121394772 121431198 +565310 POLQ chr3 121431427 121546641 +565454 ARGFX chr3 121567949 121590622 +565482 FBXO40 chr3 121593379 121630295 +565496 HCLS1 chr3 121631399 121660927 +565657 GOLGB1 chr3 121663199 121749767 +565927 IQCB1 chr3 121769761 121835079 +566077 EAF2 chr3 121835183 121886526 +566148 SLC15A2 chr3 121894401 121944188 +566281 ILDR1 chr3 121987323 122022247 +566367 CD86 chr3 122055362 122121139 +566488 CASR chr3 122183683 122291629 +566568 CSTA chr3 122325248 122341969 +566589 CCDC58 chr3 122359591 122383231 +566658 FAM162A chr3 122384176 122412334 +566704 WDR5B chr3 122411846 122416062 +566712 AC083798.2 chr3 122416207 122443180 +566734 KPNA1 chr3 122421902 122514945 +566938 AC096861.2 chr3 122515006 122518172 +566942 PARP9 chr3 122527924 122564577 +567088 DTX3L chr3 122564338 122575203 +567116 PARP15 chr3 122577628 122639047 +567228 PARP14 chr3 122680839 122730840 +567365 HSPBAP1 chr3 122739999 122793831 +567413 SLC49A4 chr3 122795069 122881139 +567458 LINC02035 chr3 122886941 122892416 +567461 SEMA5B chr3 122909082 123028605 +567914 PDIA5 chr3 123067025 123225227 +568044 SEC22A chr3 123201927 123274136 +568180 AC112503.2 chr3 123277353 123277904 +568183 ADCY5 chr3 123282296 123449758 +568407 AC112503.1 chr3 123283593 123283983 +568410 HACD2 chr3 123490820 123585053 +568459 MYLK-AS1 chr3 123585300 123644568 +568496 MYLK chr3 123610049 123884331 +569081 MYLK-AS2 chr3 123689644 123692407 +569089 AC020634.2 chr3 123715851 123716399 +569092 CCDC14 chr3 123897305 123961408 +569412 ROPN1 chr3 123968521 123992178 +569548 KALRN chr3 124080023 124726325 +570147 AC022336.2 chr3 124723788 124726325 +570150 UMPS chr3 124730433 124749273 +570285 ITGB5 chr3 124761948 124901418 +570435 ITGB5-AS1 chr3 124781155 124787757 +570439 MUC13 chr3 124905442 124953819 +570498 HEG1 chr3 124965710 125055997 +570592 AC117488.1 chr3 125061448 125063710 +570596 SLC12A8 chr3 125082636 125212864 +570796 ZNF148 chr3 125225561 125375354 +570951 SNX4 chr3 125446650 125520202 +571045 OSBPL11 chr3 125528858 125595497 +571077 AC092902.4 chr3 125766516 125852936 +571085 AC092902.2 chr3 125774714 125797953 +571089 AC092902.6 chr3 125799887 125800616 +571093 LINC02614 chr3 125827238 125916384 +571195 AC092903.2 chr3 125907765 125916360 +571207 ALG1L chr3 125929275 125937039 +571241 ROPN1B chr3 125969160 125983454 +571359 SLC41A3 chr3 126006355 126101561 +571674 AC117422.1 chr3 126056923 126058228 +571678 AC079848.1 chr3 126083659 126095349 +571692 ALDH1L1 chr3 126103562 126197994 +572128 ALDH1L1-AS1 chr3 126103640 126108069 +572134 ALDH1L1-AS2 chr3 126180012 126210169 +572149 AC079848.2 chr3 126213204 126247714 +572184 AC016924.1 chr3 126266747 126291525 +572209 AC063919.1 chr3 126288123 126301213 +572218 AC063919.2 chr3 126312385 126323406 +572223 KLF15 chr3 126342635 126357408 +572238 CCDC37-DT chr3 126393032 126394851 +572265 CFAP100 chr3 126394909 126436556 +572377 ZXDC chr3 126437601 126475891 +572443 UROC1 chr3 126481166 126517773 +572536 CHST13 chr3 126524155 126543291 +572560 C3orf22 chr3 126526999 126558965 +572591 AC024558.2 chr3 126571779 126608555 +572605 TXNRD3 chr3 126607059 126655124 +572754 CHCHD6 chr3 126704240 126960420 +572852 PLXNA1 chr3 126988594 127037392 +572937 AC112482.2 chr3 127165506 127218473 +572941 C3orf56 chr3 127193131 127198185 +572951 AC133681.1 chr3 127274581 127278304 +572956 PRR20G chr3 127283784 127288046 +572968 LINC02016 chr3 127322307 127390670 +572988 LINC01471 chr3 127480690 127537817 +573274 AC016968.1 chr3 127489553 127490787 +573280 LINC02034 chr3 127537937 127540485 +573286 AC084035.1 chr3 127571232 127571838 +573289 TPRA1 chr3 127571232 127598267 +573544 MCM2 chr3 127598410 127622436 +573711 AC023593.1 chr3 127620106 127629049 +573716 PODXL2 chr3 127629185 127672802 +573738 ABTB1 chr3 127672935 127680926 +573937 MGLL chr3 127689062 128052190 +574143 AC117480.1 chr3 127837436 127845499 +574147 KBTBD12 chr3 127915232 127987671 +574222 SEC61A1 chr3 128051641 128071683 +574330 RUVBL1 chr3 128064778 128153914 +574432 RUVBL1-AS1 chr3 128075810 128079056 +574436 EEFSEC chr3 128153481 128408646 +574478 AL449214.1 chr3 128181402 128194452 +574482 DNAJB8 chr3 128462439 128467248 +574503 DNAJB8-AS1 chr3 128463594 128472317 +574508 GATA2 chr3 128479427 128493185 +574583 GATA2-AS1 chr3 128489212 128502970 +574597 AC080005.1 chr3 128563316 128564431 +574601 LINC01565 chr3 128572000 128576086 +574608 RPN1 chr3 128619969 128681075 +574691 RAB7A chr3 128726122 128814796 +574789 AC112484.3 chr3 128859716 128860526 +574792 AC112484.1 chr3 128860620 128871540 +574802 AC112484.5 chr3 128872349 128876218 +574806 ACAD9 chr3 128879596 128916067 +575080 KIAA1257 chr3 128909866 129002690 +575221 EFCC1 chr3 129001629 129040742 +575249 GP9 chr3 129060767 129062406 +575261 RAB43 chr3 129087569 129122801 +575358 AC108673.2 chr3 129123439 129124003 +575361 ISY1 chr3 129127415 129161293 +575493 AC108673.3 chr3 129163606 129163940 +575496 CNBP chr3 129169484 129183922 +575621 COPG1 chr3 129249606 129277773 +575768 AC137695.3 chr3 129277753 129278782 +575771 HMCES chr3 129278828 129306186 +575898 H1FX chr3 129314771 129316286 +575906 H1FX-AS1 chr3 129315392 129326225 +575926 EFCAB12 chr3 129401321 129428651 +575999 MBD4 chr3 129430944 129440179 +576130 IFT122 chr3 129440036 129520507 +576936 RHO chr3 129528639 129535344 +576952 H1FOO chr3 129543214 129551467 +576981 PLXND1 chr3 129555175 129606818 +577182 TMCC1 chr3 129647792 129893606 +577322 AC083799.1 chr3 129847048 129847957 +577325 TMCC1-AS1 chr3 129893811 129918575 +577348 AC083906.3 chr3 129954105 129969294 +577354 TRH chr3 129974688 129977935 +577377 ALG1L2 chr3 130081831 130113227 +577412 LINC02014 chr3 130089433 130094304 +577418 LINC02021 chr3 130111669 130201336 +577451 AC130888.1 chr3 130181346 130188814 +577456 COL6A5 chr3 130345516 130484844 +577688 COL6A6 chr3 130560334 130678155 +577846 PIK3R4 chr3 130678934 130746829 +577948 AC097105.1 chr3 130821184 130823914 +577952 ATP2C1 chr3 130850595 131016712 +578870 AC055733.2 chr3 130899414 130929976 +578874 ASTE1 chr3 131013875 131027649 +578977 NEK11 chr3 131026850 131350465 +579350 AC116424.1 chr3 131053317 131072339 +579363 AC010210.1 chr3 131325092 131381656 +579396 NUDT16 chr3 131381671 131388830 +579429 AC107027.3 chr3 131455126 131458598 +579432 MRPL3 chr3 131462212 131502983 +579571 AC107027.1 chr3 131502573 131520880 +579619 CPNE4 chr3 131533555 132285410 +579924 ACPP chr3 132317369 132368298 +580044 DNAJC13 chr3 132417502 132539032 +580350 ACAD11 chr3 132558138 132660082 +580541 ACKR4 chr3 132597270 132618967 +580560 UBA5 chr3 132654446 132678097 +580779 NPHP3 chr3 132680609 132722414 +580996 NPHP3-AS1 chr3 132721750 132874223 +581015 AC079942.1 chr3 133015004 133037052 +581019 TMEM108 chr3 133038391 133397792 +581148 TMEM108-AS1 chr3 133245603 133257207 +581158 BFSP2 chr3 133400056 133475222 +581197 BFSP2-AS1 chr3 133429269 133455776 +581204 AC022296.4 chr3 133543064 133543466 +581207 CDV3 chr3 133573730 133590261 +581329 TOPBP1 chr3 133598175 133662380 +581493 TF chr3 133746040 133796641 +581647 SRPRB chr3 133784023 133825772 +581703 AC080128.2 chr3 133799440 133806139 +581707 RAB6B chr3 133824235 133895882 +581827 SLCO2A1 chr3 133928145 134052184 +581957 LINC02000 chr3 134055256 134057648 +581961 RYK chr3 134065303 134250744 +582115 LINC02004 chr3 134313576 134321171 +582119 AC010207.1 chr3 134347288 134349233 +582122 AMOTL2 chr3 134355874 134375479 +582285 ANAPC13 chr3 134477706 134486716 +582336 CEP63 chr3 134485721 134575017 +582670 EPHB1 chr3 134597801 135260467 +582858 KY chr3 134599923 134651636 +582958 AC016931.1 chr3 134774543 134796493 +582962 AC092969.1 chr3 135138469 135439888 +583015 PPP2R3A chr3 135965728 136147894 +583135 AC072039.2 chr3 136087475 136087913 +583138 MSL2 chr3 136148917 136197241 +583178 PCCB chr3 136250340 136337896 +583640 STAG1 chr3 136336236 136752403 +584102 AC117382.2 chr3 136752630 136755780 +584105 AC096992.3 chr3 136778181 136806308 +584111 SLC35G2 chr3 136818647 136855888 +584133 NCK1-DT chr3 136835345 136862618 +584171 AC096992.2 chr3 136837338 136839021 +584174 NCK1 chr3 136862208 136951606 +584281 IL20RB chr3 136946230 137011085 +584356 IL20RB-AS1 chr3 136959125 136982196 +584360 SOX14 chr3 137764315 137766334 +584368 LINC01210 chr3 137771660 137780882 +584480 AC007159.1 chr3 137791973 137796678 +584483 CLDN18 chr3 137998735 138033655 +584527 AC016252.1 chr3 138004649 138005122 +584530 DZIP1L chr3 138061990 138115818 +584645 A4GNT chr3 138123713 138132390 +584657 DBR1 chr3 138160988 138174921 +584702 ARMC8 chr3 138187248 138298384 +585267 NME9 chr3 138261437 138329886 +585453 MRAS chr3 138347648 138405534 +585579 ESYT3 chr3 138434586 138481686 +585728 CEP70 chr3 138494344 138594538 +586030 FAIM chr3 138608606 138633376 +586135 PIK3CB chr3 138652699 138834938 +586465 LINC01391 chr3 138935189 138944020 +586477 FOXL2 chr3 138944224 138947137 +586485 FOXL2NB chr3 138947217 138953990 +586511 PRR23A chr3 139003962 139006268 +586518 MRPS22 chr3 139005806 139357223 +586698 PRR23B chr3 139019031 139020926 +586706 PRR23C chr3 139042102 139044892 +586714 BPESC1 chr3 139104185 139125171 +586719 PISRT1 chr3 139232992 139233522 +586722 AC024933.2 chr3 139316157 139340870 +586726 AC024933.1 chr3 139349024 139349371 +586729 COPB2 chr3 139355600 139389680 +586942 AC046134.2 chr3 139389761 139782699 +587030 RBP2 chr3 139452884 139480747 +587064 AC097103.1 chr3 139466430 139466795 +587068 RBP1 chr3 139517434 139539829 +587155 NMNAT3 chr3 139560180 139678017 +587416 AC110716.2 chr3 139678620 139682564 +587419 AC110716.1 chr3 139688403 139689342 +587423 AC016933.1 chr3 139837220 139859894 +587428 CLSTN2 chr3 139935185 140577397 +587480 AC010181.1 chr3 140449435 140460351 +587499 AC010181.2 chr3 140461000 140462825 +587503 CLSTN2-AS1 chr3 140505611 140508789 +587507 TRIM42 chr3 140678064 140701150 +587523 AC121333.1 chr3 140865075 140867783 +587526 SLC25A36 chr3 140941830 140980978 +587733 AC108727.1 chr3 140972744 140973255 +587737 SPSB4 chr3 141051347 141148611 +587765 AC108727.2 chr3 141115124 141124182 +587770 PXYLP1 chr3 141228726 141367753 +588016 AC022215.2 chr3 141251004 141284306 +588020 AC117383.1 chr3 141267353 141367137 +588025 ZBTB38 chr3 141324213 141449792 +588210 RASA2 chr3 141487027 141615356 +588361 RASA2-IT1 chr3 141525133 141526121 +588365 RNF7 chr3 141738249 141747560 +588429 GRK7 chr3 141778148 141818490 +588443 AC112504.3 chr3 141851549 141861168 +588448 ATP1B3 chr3 141876124 141926549 +588573 ATP1B3-AS1 chr3 141918252 141919021 +588577 TFDP2 chr3 141944428 142149544 +588948 GK5 chr3 142157527 142225592 +589146 XRN1 chr3 142306607 142448062 +589510 ATR chr3 142449007 142578733 +590036 AC109992.2 chr3 142465315 142472337 +590040 PLS1 chr3 142596393 142713664 +590255 PLS1-AS1 chr3 142654784 142656745 +590259 AC072028.1 chr3 142687982 142723881 +590263 TRPC1 chr3 142724034 142807888 +590367 PCOLCE2 chr3 142815922 142889206 +590491 AC021074.3 chr3 142912116 142942537 +590595 PAQR9 chr3 142949164 142963674 +590621 PAQR9-AS1 chr3 142960650 143001559 +590681 U2SURP chr3 142964497 143060725 +591058 AC026304.1 chr3 143000907 143001467 +591061 AC018450.2 chr3 143111802 143112359 +591065 CHST2 chr3 143119771 143124014 +591075 AC018450.1 chr3 143123362 143131893 +591082 SLC9A9 chr3 143265222 143848485 +591152 AC131210.1 chr3 143313067 143314429 +591156 SLC9A9-AS1 chr3 143342246 143347071 +591162 SLC9A9-AS2 chr3 143381338 143382161 +591166 DIPK2A chr3 143971798 144048719 +591220 AC055758.2 chr3 145939912 145961536 +591229 AC055758.1 chr3 145961755 145963623 +591233 AC107021.2 chr3 146059585 146061679 +591236 AC107021.1 chr3 146064042 146105204 +591248 LNCSRLR chr3 146066344 146069185 +591252 PLOD2 chr3 146069440 146163653 +591459 PLSCR4 chr3 146192335 146251179 +591648 PLSCR2 chr3 146391421 146495991 +591766 PLSCR1 chr3 146515180 146544856 +592044 PLSCR5 chr3 146576555 146606216 +592108 PLSCR5-AS1 chr3 146589602 146590325 +592112 AC092957.1 chr3 146909685 147370656 +592128 LINC02010 chr3 146921795 146927429 +592139 ZIC4 chr3 147386046 147406860 +592292 ZIC4-AS1 chr3 147386967 147387453 +592296 ZIC1 chr3 147393422 147510293 +592327 AC092925.1 chr3 147844123 147846657 +592332 AC092958.1 chr3 147939905 148007127 +592363 AC092958.4 chr3 148028046 148079637 +592370 LINC02032 chr3 148076432 148089134 +592394 AC092958.3 chr3 148090341 148096921 +592399 AC092958.2 chr3 148093175 148127233 +592405 AC025566.1 chr3 148160911 148226606 +592414 LINC02045 chr3 148192872 148280098 +592427 LINC02046 chr3 148279682 148401084 +592505 AC069410.1 chr3 148368384 148591927 +592513 AGTR1 chr3 148697784 148743008 +592597 CPB1 chr3 148791102 148860187 +592716 AC092979.1 chr3 148850933 148960112 +592723 CPA3 chr3 148865296 148897203 +592757 AC092979.2 chr3 148922703 148956088 +592763 GYG1 chr3 148991341 149027668 +592916 HLTF chr3 149030127 149086554 +593181 HLTF-AS1 chr3 149086332 149102823 +593186 HPS3 chr3 149129638 149173732 +593304 CP chr3 149162410 149221829 +593510 AC093001.2 chr3 149224138 149226334 +593516 AC093001.1 chr3 149284782 149333653 +593520 TM4SF18 chr3 149318498 149334414 +593576 TM4SF1 chr3 149369022 149377692 +593625 TM4SF1-AS1 chr3 149377778 149386583 +593636 AC108751.4 chr3 149384179 149385800 +593640 TM4SF4 chr3 149474697 149503394 +593667 WWTR1 chr3 149517235 149736714 +593805 WWTR1-IT1 chr3 149648997 149650184 +593809 WWTR1-AS1 chr3 149656999 149661364 +593823 COMMD2 chr3 149738472 149752495 +593887 ANKUB1 chr3 149761100 149968385 +593959 RNF13 chr3 149812708 149962139 +594232 PFN2 chr3 149964904 150050788 +594423 AC117395.1 chr3 149976755 149979355 +594431 AC117386.2 chr3 150039214 150213726 +594444 LINC01998 chr3 150077494 150080117 +594448 AC117386.1 chr3 150202174 150225190 +594456 LINC01213 chr3 150238519 150244232 +594477 LINC01214 chr3 150265407 150296605 +594487 AC018545.1 chr3 150339478 150343210 +594491 TSC22D2 chr3 150408335 150466431 +594540 SERP1 chr3 150541998 150603228 +594597 EIF2A chr3 150546678 150586016 +594882 SELENOT chr3 150602875 150630445 +594996 ERICH6 chr3 150659885 150703971 +595096 ERICH6-AS1 chr3 150703564 150723005 +595118 AC011317.1 chr3 150734469 150738977 +595134 SIAH2 chr3 150741125 150763477 +595156 SIAH2-AS1 chr3 150761937 150873554 +595164 CLRN1-AS1 chr3 150852484 151080726 +595178 MINDY4B chr3 150870376 150905439 +595210 AC020636.1 chr3 150890636 151038818 +595215 CLRN1 chr3 150926163 150972999 +595293 MED12L chr3 151085697 151437072 +595559 GPR171 chr3 151197832 151203216 +595584 P2RY14 chr3 151212117 151278542 +595618 AC078816.1 chr3 151293317 151295494 +595622 GPR87 chr3 151294086 151316820 +595636 P2RY13 chr3 151326312 151329549 +595646 P2RY12 chr3 151337380 151384812 +595661 IGSF10 chr3 151425384 151458709 +595694 LINC02066 chr3 151637174 151657966 +595699 AADACL2 chr3 151733916 151761339 +595728 AADACL2-AS1 chr3 151751443 151928175 +595740 AADAC chr3 151814073 151828488 +595769 SUCNR1 chr3 151873643 151884619 +595781 AC108718.1 chr3 152118173 152151724 +595785 MBNL1 chr3 152243828 152465780 +596175 MBNL1-AS1 chr3 152245262 152269557 +596188 AC026347.1 chr3 152457759 152496813 +596192 AC092924.1 chr3 152648146 152650447 +596196 AC092924.2 chr3 152650519 152679450 +596202 P2RY1 chr3 152835131 152841439 +596210 AC117394.2 chr3 153156511 153161775 +596214 RAP2B chr3 153162226 153170627 +596222 AC078788.1 chr3 153357107 153374186 +596226 AC078788.2 chr3 153376831 153377562 +596230 LINC02006 chr3 153384934 153980186 +596247 C3orf79 chr3 153431856 153502697 +596262 AC068985.1 chr3 153881526 153940836 +596270 ARHGEF26-AS1 chr3 154024401 154121347 +596340 ARHGEF26 chr3 154121003 154257827 +596467 DHX36 chr3 154272546 154324487 +596732 GPR149 chr3 154334943 154430190 +596746 AC092994.1 chr3 154511535 154539309 +596750 AC073359.2 chr3 154827016 154861017 +596754 AC073359.1 chr3 154969283 154970223 +596758 MME chr3 155024124 155183729 +597180 MME-AS1 chr3 155158370 155183285 +597184 LINC01487 chr3 155240919 155258766 +597211 STRIT1 chr3 155290227 155293683 +597223 AC104831.1 chr3 155291188 155294176 +597228 PLCH1 chr3 155375580 155745067 +597488 PLCH1-AS1 chr3 155449184 155457753 +597492 PLCH1-AS2 chr3 155485803 155487121 +597496 AC104472.1 chr3 155742142 155743726 +597499 C3orf33 chr3 155762617 155806278 +597577 SLC33A1 chr3 155821024 155854456 +597716 AC104472.4 chr3 155854752 155863191 +597721 GMPS chr3 155870650 155944020 +597798 AC104472.5 chr3 155886615 155890729 +597802 KCNAB1 chr3 156037701 156539138 +598107 AC091607.2 chr3 156143570 156540627 +598111 KCNAB1-AS2 chr3 156215560 156227883 +598117 KCNAB1-AS1 chr3 156441157 156446905 +598122 AC084036.1 chr3 156523740 156524247 +598125 SSR3 chr3 156540140 156555184 +598219 TIPARP-AS1 chr3 156671862 156674446 +598232 TIPARP chr3 156673235 156706770 +598342 LINC00886 chr3 156747343 156817062 +598362 LEKR1 chr3 156825481 157046129 +598512 LINC00880 chr3 157081667 157128595 +598522 LINC02029 chr3 157081738 157088547 +598579 LINC00881 chr3 157089634 157135557 +598624 CCNL1 chr3 157146508 157160760 +598927 AC104411.1 chr3 157163452 157169133 +598931 AC092944.1 chr3 157174201 157381265 +598965 AC092944.3 chr3 157234580 157235149 +598969 VEPH1 chr3 157259742 157533619 +599210 PTX3 chr3 157436850 157443633 +599222 SLC66A1L chr3 157543246 157677749 +599320 AC084212.1 chr3 157579694 157587495 +599324 AC079943.2 chr3 157814822 158088997 +599349 AC079943.1 chr3 157976561 157978136 +599353 SHOX2 chr3 158095954 158106503 +599433 RSRC1 chr3 158105855 158545730 +599695 AC106707.1 chr3 158545189 158571066 +599720 MLF1 chr3 158571163 158607252 +600135 GFM1 chr3 158644278 158692575 +600334 LXN chr3 158645822 158672648 +600363 AC080013.4 chr3 158693120 158693768 +600366 AC080013.6 chr3 158695367 158695581 +600369 RARRES1 chr3 158696892 158732489 +600411 MFSD1 chr3 158732198 158829719 +600856 AC080013.1 chr3 158732263 158784070 +600891 AC080013.3 chr3 158782547 158783124 +600894 AC080013.5 chr3 158801257 158801935 +600897 IQCJ-SCHIP1 chr3 158962235 159897366 +601110 IQCJ chr3 158962928 159266307 +601156 AC092943.2 chr3 159711852 159731646 +601162 IQCJ-SCHIP1-AS1 chr3 159765387 159768612 +601169 SCHIP1 chr3 159839861 159897360 +601241 IL12A-AS1 chr3 159902045 160225299 +601330 IL12A chr3 159988835 159996019 +601399 LINC01100 chr3 160016024 160031423 +601406 C3orf80 chr3 160225496 160228213 +601421 IFT80 chr3 160256986 160399880 +601806 SMC4 chr3 160399274 160434954 +602234 TRIM59 chr3 160432445 160485773 +602309 KPNA4 chr3 160495007 160565571 +602363 ARL14 chr3 160677160 160678448 +602371 AC069224.1 chr3 160753428 160755142 +602374 PPM1L chr3 160755602 161078902 +602434 B3GALNT1 chr3 161083883 161105411 +603244 NMD3 chr3 161104696 161253532 +603452 SPTSSB chr3 161344792 161372880 +603493 LINC02067 chr3 161426427 161448242 +603499 AC112491.1 chr3 161429112 161429613 +603503 OTOL1 chr3 161496808 161503942 +603516 AC112770.1 chr3 161600438 161735399 +603520 AC131211.1 chr3 161816909 161821908 +603524 AC128685.1 chr3 163026396 163232149 +603531 LINC01192 chr3 163109152 163361563 +604031 AC079910.1 chr3 163455568 163479500 +604039 LINC01323 chr3 164670878 164686076 +604045 LINC01324 chr3 164714095 164831480 +604054 SI chr3 164978898 165078496 +604172 LINC02023 chr3 165150006 165158062 +604176 SLITRK3 chr3 165186720 165197109 +604202 LINC01322 chr3 165206929 165846519 +604438 BCHE chr3 165772904 165837462 +604500 LINC01326 chr3 166569693 166570763 +604504 AC069439.2 chr3 166835021 166844956 +604508 ZBBX chr3 167240287 167381346 +604820 LINC01327 chr3 167392796 167408519 +604826 SERPINI2 chr3 167441789 167479004 +604972 WDR49 chr3 167478684 167653983 +605174 PDCD10 chr3 167683298 167734939 +605464 SERPINI1 chr3 167735243 167825568 +605554 AC079822.1 chr3 167794947 167811081 +605558 AC026353.1 chr3 167866500 167950292 +605585 GOLIM4 chr3 168008689 168095924 +605662 AC069243.1 chr3 168094049 168095087 +605665 AC124893.1 chr3 168288553 168291228 +605669 LINC02082 chr3 168902194 168924590 +605681 AC092954.1 chr3 168927475 168927919 +605684 AC092954.2 chr3 168928169 168928598 +605687 LINC01997 chr3 169003022 169038416 +605697 MECOM chr3 169083499 169663775 +606147 AC074033.1 chr3 169447867 169477052 +606154 AC007849.1 chr3 169613510 169623951 +606159 TERC chr3 169764520 169765060 +606162 ACTRT3 chr3 169766921 169769561 +606172 AC078802.1 chr3 169769649 169772043 +606176 MYNN chr3 169772831 169789716 +606274 AC078795.1 chr3 169777192 169780334 +606277 LRRC34 chr3 169793428 169812986 +606417 AC078795.3 chr3 169793495 169793966 +606420 AC078795.2 chr3 169794962 169796213 +606423 LRRIQ4 chr3 169821922 169837775 +606438 LRRC31 chr3 169839172 169869935 +606514 SAMD7 chr3 169911572 169939175 +606584 AC008040.1 chr3 169939353 169966734 +606598 SEC62 chr3 169966635 169998373 +606714 SEC62-AS1 chr3 169978536 169985715 +606718 GPR160 chr3 170037995 170085392 +606790 PHC3 chr3 170086732 170181749 +607042 PRKCI chr3 170222424 170305977 +607110 AC073288.1 chr3 170345678 170353961 +607114 SKIL chr3 170357678 170396835 +607221 AC073288.2 chr3 170410512 170418615 +607227 CLDN11 chr3 170418865 170454733 +607267 SLC7A14-AS1 chr3 170448639 170860993 +607292 SLC7A14 chr3 170459548 170586075 +607317 AC026316.3 chr3 170656562 170662123 +607321 AC026316.5 chr3 170691997 170736061 +607332 AC026316.2 chr3 170740351 170741365 +607336 RPL22L1 chr3 170864875 170870208 +607403 EIF5A2 chr3 170888418 170908644 +607462 AC061708.1 chr3 170908857 171054973 +607467 SLC2A2 chr3 170996347 171026743 +607559 TNIK chr3 171058414 171460408 +608163 AC092919.1 chr3 171459248 171469702 +608175 PLD1 chr3 171600404 171810950 +608415 TMEM212-AS1 chr3 171815586 171900749 +608421 TMEM212 chr3 171843349 171938715 +608482 TMEM212-IT1 chr3 171894436 171895240 +608486 AC055714.1 chr3 171941607 171996871 +608496 FNDC3B chr3 172039578 172401669 +608743 GHSR chr3 172443291 172448456 +608760 TNFSF10 chr3 172505508 172523475 +608810 LINC02068 chr3 172560888 172595607 +608823 NCEH1 chr3 172630249 172711218 +608910 AC108667.2 chr3 172711151 172725038 +608914 ECT2 chr3 172750682 172821474 +609310 SPATA16 chr3 172889357 173141235 +609357 AC068759.1 chr3 173153737 173336965 +609370 NLGN1 chr3 173396284 174286644 +609467 NLGN1-AS1 chr3 173910498 173920796 +609477 NAALADL2 chr3 174438573 175810548 +609596 NAALADL2-AS3 chr3 175079307 175115242 +609606 NAALADL2-AS2 chr3 175234861 175271096 +609611 AC008180.2 chr3 175473919 175477602 +609615 NAALADL2-AS1 chr3 175773145 175776333 +609620 AC104640.1 chr3 175938929 175941037 +609623 LINC01208 chr3 176415439 176867838 +609659 LINC01209 chr3 176814155 176817001 +609666 TBL1XR1 chr3 177019340 177228000 +610090 TBL1XR1-AS1 chr3 177037405 177047923 +610099 LINC00501 chr3 177294442 177323418 +610103 AC117465.1 chr3 177337628 177349166 +610108 LINC00578 chr3 177441910 177767379 +610167 AC026355.3 chr3 177621382 177628287 +610172 AC026355.2 chr3 177683627 177691250 +610178 LINC02015 chr3 177816865 177899224 +610197 AC007953.1 chr3 177930758 177940299 +610206 AC007953.2 chr3 177952327 177959817 +610214 AC110992.1 chr3 178028130 178172449 +610220 AC117453.1 chr3 178164008 178385479 +610274 KCNMB2 chr3 178272932 178844429 +610396 LINC01014 chr3 178419201 178457309 +610408 KCNMB2-AS1 chr3 178526505 178937352 +610448 ZMAT3 chr3 178960121 179072215 +610521 AC076966.2 chr3 179101366 179147973 +610526 PIK3CA chr3 179148114 179240093 +610644 KCNMB3 chr3 179236691 179267002 +610732 ZNF639 chr3 179323031 179338583 +610867 AC007823.1 chr3 179340322 179341887 +610870 MFN1 chr3 179347709 179394936 +611056 GNB4 chr3 179396088 179451476 +611139 AC007620.2 chr3 179396961 179399191 +611149 AC007620.3 chr3 179405448 179405944 +611152 ACTL6A chr3 179562886 179588407 +611324 AC090425.3 chr3 179583262 179583762 +611327 AC090425.2 chr3 179584271 179584410 +611330 MRPL47 chr3 179588285 179604649 +611386 NDUFB5 chr3 179604690 179627647 +611549 USP13 chr3 179653040 179789401 +611692 PEX5L chr3 179794958 180037053 +612080 AC007687.1 chr3 179804063 179804366 +612083 PEX5L-AS1 chr3 179875376 179881609 +612087 PEX5L-AS2 chr3 179898199 179921895 +612092 AC092939.1 chr3 179971494 180017083 +612097 LINC02053 chr3 180413008 180476778 +612120 AC125618.1 chr3 180566718 180601935 +612125 TTC14 chr3 180602163 180617828 +612316 CCDC39 chr3 180602858 180684942 +612522 CCDC39-AS1 chr3 180680084 180700449 +612526 AC108734.4 chr3 180707589 180871005 +612548 FXR1 chr3 180868141 180982753 +612932 DNAJC19 chr3 180983709 180989774 +613058 SOX2-OT chr3 180989762 181836880 +613593 AC068308.1 chr3 181372732 181442597 +613662 AC125613.1 chr3 181534177 181700611 +613681 SOX2 chr3 181711925 181714436 +613689 LINC01206 chr3 181952343 182035644 +614516 AC012081.2 chr3 182049058 182052270 +614521 AC012081.1 chr3 182121884 182142137 +614525 AC109131.1 chr3 182149430 182158313 +614529 AC084211.1 chr3 182365147 182368256 +614533 LINC01994 chr3 182446970 182486364 +614539 LINC01995 chr3 182498187 182536772 +614552 AC021055.1 chr3 182588093 182617810 +614557 LINC02031 chr3 182644214 182655880 +614564 AC083801.2 chr3 182739669 182740848 +614567 AC069431.1 chr3 182783236 182793394 +614571 ATP11B chr3 182793503 182921629 +614802 AC092953.2 chr3 182921240 182921938 +614805 DCUN1D1 chr3 182938074 182985953 +614936 MCCC1 chr3 183015218 183116075 +615333 MCCC1-AS1 chr3 183016255 183017808 +615337 LAMP3 chr3 183122215 183163839 +615395 MCF2L2 chr3 183178043 183428778 +615703 B3GNT5 chr3 183253253 183298504 +615774 KLHL6 chr3 183487551 183555706 +615823 KLHL6-AS1 chr3 183548735 183552326 +615827 KLHL24 chr3 183635610 183684519 +615973 YEATS2 chr3 183697797 183812624 +616071 YEATS2-AS1 chr3 183806457 183810783 +616086 MAP6D1 chr3 183815876 183825594 +616121 PARL chr3 183829271 183884933 +616354 ABCC5 chr3 183919934 184017939 +616682 ABCC5-AS1 chr3 184006338 184011419 +616687 HTR3D chr3 184031544 184039369 +616758 HTR3C chr3 184053047 184060673 +616782 HTR3E-AS1 chr3 184095118 184105178 +616787 HTR3E chr3 184097064 184106995 +616903 AC131235.3 chr3 184132942 184133561 +616906 AC131235.2 chr3 184134019 184135238 +616915 EIF2B5 chr3 184135038 184146127 +617652 DVL3 chr3 184155377 184173614 +617819 AP2M1 chr3 184174689 184184091 +618092 ABCF3 chr3 184186023 184194012 +618312 VWA5B2 chr3 184230429 184242329 +618423 ALG3 chr3 184242301 184249548 +618589 EEF1AKMT4 chr3 184249650 184259585 +618601 CAMK2N2 chr3 184259213 184261553 +618611 ECE2 chr3 184276011 184293031 +618829 PSMD2 chr3 184299198 184309050 +619083 EIF4G1 chr3 184314495 184335358 +620364 FAM131A chr3 184335926 184348421 +620512 CLCN2 chr3 184346185 184361650 +621115 POLR2H chr3 184361718 184368596 +621244 THPO chr3 184371935 184381968 +621361 CHRD chr3 184380073 184390736 +621720 LINC02054 chr3 184399790 184457891 +621742 LINC01839 chr3 184505113 184508399 +621746 LINC01840 chr3 184546714 184556918 +621750 EPHB3 chr3 184561785 184582408 +621794 MAGEF1 chr3 184710364 184712064 +621802 AC107294.2 chr3 184712245 184780720 +621842 LINC02069 chr3 184725013 184773178 +621857 AC107294.3 chr3 184741937 184742462 +621860 AC107294.1 chr3 184742818 184743284 +621863 VPS8 chr3 184812143 185052614 +622503 C3orf70 chr3 185076838 185153060 +622513 EHHADH-AS1 chr3 185162871 185191955 +622527 EHHADH chr3 185190624 185281990 +622589 MAP3K13 chr3 185282941 185489094 +622857 TMEM41A chr3 185476496 185499057 +622916 AC099661.1 chr3 185499140 185501109 +622920 LIPH chr3 185506262 185552588 +622998 SENP2 chr3 185582496 185633551 +623187 IGF2BP2 chr3 185643739 185825056 +623368 IGF2BP2-AS1 chr3 185712528 185729787 +623393 TRA2B chr3 185914558 185938103 +623555 ETV5 chr3 186046314 186110318 +623729 ETV5-AS1 chr3 186079170 186080947 +623733 DGKG chr3 186105668 186362234 +623958 LINC02020 chr3 186439239 186457299 +624076 LINC02052 chr3 186454969 186493661 +624190 LINC02051 chr3 186476727 186478370 +624194 CRYGS chr3 186538441 186546702 +624222 TBCCD1 chr3 186546067 186570543 +624305 DNAJB11 chr3 186567403 186585800 +624369 AC068631.1 chr3 186579476 186772986 +624645 AHSG chr3 186613060 186621318 +624689 FETUB chr3 186635969 186653141 +624812 HRG chr3 186660216 186678240 +624842 KNG1 chr3 186717348 186744410 +624923 AC112907.3 chr3 186781780 186784179 +624926 EIF4A2 chr3 186783205 186789897 +625198 RFC4 chr3 186789880 186807058 +625395 AC112907.1 chr3 186807692 186818121 +625399 LINC02043 chr3 186810880 186825521 +625405 ADIPOQ chr3 186842704 186858463 +625430 ADIPOQ-AS1 chr3 186851886 186856123 +625435 ST6GAL1 chr3 186930502 187078553 +625661 RPL39L chr3 187120948 187180908 +625695 AC007920.1 chr3 187197090 187207629 +625702 RTP1 chr3 187197486 187201462 +625712 MASP1 chr3 187217285 187292022 +625912 AC007920.2 chr3 187291272 187297933 +625916 RTP4 chr3 187368385 187372076 +625926 LINC02041 chr3 187448845 187449450 +625930 SST chr3 187668912 187670394 +625940 RTP2 chr3 187698259 187702557 +625950 AC072022.1 chr3 187702313 187733849 +625959 BCL6 chr3 187721377 187745725 +626113 AC072022.2 chr3 187743686 187746028 +626123 AC108681.1 chr3 187796187 187805258 +626131 AC068295.1 chr3 187932764 187946221 +626135 LINC01991 chr3 187958775 187976407 +626142 AC092941.1 chr3 187997422 188003990 +626146 AC092941.2 chr3 188001700 188003406 +626150 AC022498.1 chr3 188107072 188147310 +626163 LPP-AS2 chr3 188151206 188154057 +626166 LPP chr3 188153284 188890671 +626395 LPP-AS1 chr3 188562238 188568666 +626399 TPRG1-AS1 chr3 188941715 188947639 +626403 TPRG1 chr3 188947214 189325304 +626530 TPRG1-AS2 chr3 189238686 189240594 +626535 TP63 chr3 189631389 189897276 +626866 P3H2 chr3 189956728 190122437 +626984 P3H2-AS1 chr3 190120964 190145107 +626991 CLDN1 chr3 190305707 190322446 +627008 CLDN16 chr3 190322541 190412143 +627038 TMEM207 chr3 190428655 190449876 +627054 IL1RAP chr3 190514051 190659750 +627386 AC108747.1 chr3 190659216 190659750 +627389 LINC02013 chr3 190680421 190699314 +627404 GMNC chr3 190852737 190892429 +627443 OSTN chr3 191199241 191265615 +627466 OSTN-AS1 chr3 191213291 191234605 +627478 UTS2B chr3 191267168 191330536 +627592 CCDC50 chr3 191329085 191398659 +627652 AC073365.1 chr3 191425493 191591097 +627858 PYDC2 chr3 191461163 191461456 +627865 AC026320.1 chr3 192029880 192036557 +627877 AC026320.3 chr3 192078950 192119864 +627883 FGF12 chr3 192139395 192767764 +627983 FGF12-AS1 chr3 192238037 192283097 +627994 FGF12-AS2 chr3 192515022 192516573 +627998 FGF12-AS3 chr3 192516831 192521398 +628002 MB21D2 chr3 192796815 192917856 +628012 AC092966.1 chr3 193144464 193176864 +628017 PLAAT1 chr3 193241128 193277738 +628052 ATP13A5 chr3 193274789 193378820 +628165 ATP13A5-AS1 chr3 193307244 193314362 +628169 ATP13A4 chr3 193398967 193593111 +628507 ATP13A4-AS1 chr3 193553213 193555088 +628515 OPA1 chr3 193593144 193697811 +629972 OPA1-AS1 chr3 193618609 193627337 +629980 AC069421.2 chr3 193770543 193772424 +629984 AC069421.3 chr3 193771874 193782758 +629990 LINC02038 chr3 193842560 193844024 +629998 LINC02026 chr3 193957372 194003760 +630012 AC024559.1 chr3 193980614 194006098 +630017 LINC02028 chr3 194005259 194071025 +630314 AC024559.2 chr3 194070103 194086826 +630330 AC080129.1 chr3 194091561 194109174 +630334 AC080129.2 chr3 194130616 194131201 +630338 HES1 chr3 194136148 194138732 +630355 LINC02036 chr3 194202392 194250203 +630406 LINC02037 chr3 194247638 194260720 +630422 LINC02048 chr3 194276682 194287368 +630431 LINC00887 chr3 194296191 194322871 +630477 AC117469.1 chr3 194300329 194302048 +630481 CPN2 chr3 194339768 194351328 +630499 LRRC15 chr3 194355247 194369743 +630520 GP5 chr3 194394821 194398354 +630528 ATP13A3 chr3 194402672 194498364 +631000 LINC00884 chr3 194487140 194521156 +631042 AC108676.1 chr3 194496317 194501503 +631046 TMEM44-AS1 chr3 194584004 194590260 +631063 TMEM44 chr3 194587673 194633689 +631289 AC046143.1 chr3 194632923 194645401 +631293 AC046143.2 chr3 194637505 194637664 +631296 LSG1 chr3 194640791 194672463 +631383 FAM43A chr3 194685883 194689037 +631391 AC106706.1 chr3 194702667 194727675 +631429 AC106706.2 chr3 194708010 194709395 +631433 LINC01968 chr3 194708093 194826008 +631598 LINC01972 chr3 194765238 194768712 +631603 AC090505.2 chr3 194827890 194832592 +631608 XXYLT1 chr3 195068284 195271159 +631706 XXYLT1-AS1 chr3 195094588 195096057 +631712 XXYLT1-AS2 chr3 195147871 195152790 +631719 AC090018.2 chr3 195260632 195263628 +631723 ACAP2 chr3 195274745 195443044 +631984 ACAP2-IT1 chr3 195280723 195282741 +631988 PPP1R2 chr3 195514428 195543386 +632064 AC069213.1 chr3 195544048 195550581 +632074 APOD chr3 195568705 195584033 +632142 AC233280.1 chr3 195655565 195657927 +632147 MUC20 chr3 195720884 195741123 +632221 MUC4 chr3 195746765 195811973 +633133 LINC01983 chr3 195836193 195860404 +633143 TNK2 chr3 195863364 195911945 +633682 AC124944.3 chr3 195900986 195903417 +633686 TNK2-AS1 chr3 195908076 195913986 +633699 AC024937.3 chr3 195996262 196027694 +633708 TFRC chr3 196027183 196082096 +633907 LINC00885 chr3 196142525 196160893 +633937 ZDHHC19 chr3 196197452 196211437 +634025 SLC51A chr3 196211487 196243178 +634131 PCYT1A chr3 196214222 196287957 +634345 AC069257.1 chr3 196250542 196251654 +634352 TCTEX1D2 chr3 196291219 196318299 +634406 TM4SF19-AS1 chr3 196318330 196325570 +634416 TM4SF19 chr3 196319342 196338503 +634469 UBXN7 chr3 196347662 196432430 +634568 UBXN7-AS1 chr3 196431385 196432530 +634572 RNF168 chr3 196468783 196503768 +634605 AC117490.2 chr3 196474801 196475394 +634608 SMCO1 chr3 196506879 196515346 +634631 WDR53 chr3 196554177 196568674 +634681 FBXO45 chr3 196568611 196589059 +634704 AC092933.2 chr3 196598549 196609410 +634709 LINC01063 chr3 196631498 196632587 +634713 NRROS chr3 196639694 196662004 +634728 PIGX chr3 196639775 196736007 +634875 CEP19 chr3 196706277 196712250 +634896 PAK2 chr3 196739857 196832647 +634950 SENP5 chr3 196867856 196934714 +635050 AC016949.1 chr3 196912646 196914579 +635054 NCBP2 chr3 196935402 196942594 +635170 NCBP2-AS1 chr3 196939877 196942534 +635175 NCBP2AS2 chr3 196942674 196943543 +635183 PIGZ chr3 196946356 196969060 +635214 AC011322.1 chr3 196973709 196979197 +635220 MELTF chr3 196988621 197029817 +635302 MELTF-AS1 chr3 196999460 197004744 +635320 DLG1 chr3 197042560 197299330 +638326 DLG1-AS1 chr3 197298252 197303755 +638344 AL121981.1 chr3 197333944 197340706 +638350 AC128709.2 chr3 197445061 197458323 +638355 AC128709.1 chr3 197450327 197456654 +638360 AC128709.3 chr3 197458405 197467105 +638364 LINC02012 chr3 197505262 197506986 +638367 BDH1 chr3 197509783 197573323 +638574 AC024560.3 chr3 197645669 197646017 +638577 AC024560.4 chr3 197649303 197651482 +638581 AC024560.1 chr3 197660565 197665757 +638585 AC024560.5 chr3 197665316 197674863 +638589 RUBCN chr3 197668867 197749727 +638806 FYTTD1 chr3 197737179 197787596 +638962 AC055764.2 chr3 197789700 197790369 +638965 LRCH3 chr3 197791226 197888436 +639340 AC055764.1 chr3 197830685 197831296 +639344 IQCG chr3 197889077 197960142 +639485 RPL35A chr3 197950190 197956610 +639584 LMLN chr3 197960200 198043720 +639791 AC135893.1 chr3 198027956 198035970 +639796 LMLN-AS1 chr3 198038321 198039234 +639801 ZNF595 chr4 53286 88208 +639852 ZNF718 chr4 124501 202303 +639894 AC253576.2 chr4 149738 150317 +639897 ZNF732 chr4 270675 305474 +639920 AC079140.6 chr4 307335 337433 +639924 ZNF141 chr4 337814 384868 +639977 AC092574.2 chr4 386174 454070 +639981 AC092574.1 chr4 416118 416537 +639984 ZNF721 chr4 425815 499156 +640052 PIGG chr4 499210 540200 +640341 TMEM271 chr4 573880 576300 +640349 AC116565.1 chr4 577168 618076 +640368 PDE6B chr4 625584 670782 +640592 AC107464.1 chr4 652850 656213 +640606 AC107464.3 chr4 661209 661945 +640609 ATP5ME chr4 672436 674330 +640638 MYL5 chr4 673580 682033 +640774 SLC49A3 chr4 681829 689441 +640932 PCGF3 chr4 705748 770640 +641131 AC107464.2 chr4 722275 724034 +641135 AC139887.4 chr4 757022 757740 +641138 AC139887.2 chr4 760202 781859 +641160 AC139887.1 chr4 764487 765074 +641164 CPLX1 chr4 784957 826129 +641205 AC139887.3 chr4 836512 837224 +641208 AC139887.5 chr4 843963 846294 +641212 GAK chr4 849276 932373 +641536 TMEM175 chr4 932387 958656 +641879 DGKQ chr4 958887 986895 +642014 SLC26A1 chr4 979073 993440 +642066 IDUA chr4 986997 1004564 +642218 FGFRL1 chr4 1009936 1026898 +642318 AC019103.1 chr4 1027678 1028972 +642322 RNF212 chr4 1056250 1113564 +642514 AC092535.4 chr4 1113639 1132977 +642522 AC092535.2 chr4 1151372 1153701 +642526 SPON2 chr4 1166932 1208962 +642701 AC092535.5 chr4 1167778 1168174 +642704 CTBP1-AS chr4 1210120 1218591 +642712 CTBP1 chr4 1211448 1249953 +642906 CTBP1-DT chr4 1249300 1288291 +642927 MAEA chr4 1289887 1340147 +643195 UVSSA chr4 1347208 1388049 +643352 AC078852.2 chr4 1356581 1358075 +643356 AC078852.1 chr4 1358479 1359461 +643360 CRIPAK chr4 1391552 1395992 +643368 NKX1-1 chr4 1402932 1406331 +643377 AC147067.2 chr4 1550284 1550572 +643380 AC147067.1 chr4 1574062 1580253 +643384 FAM53A chr4 1617915 1684302 +643466 SLBP chr4 1692731 1712344 +643575 AC016773.1 chr4 1712821 1715945 +643581 TACC3 chr4 1712891 1745176 +643909 TMEM129 chr4 1715952 1721358 +643973 FGFR3 chr4 1793293 1808872 +644272 LETM1 chr4 1811479 1856156 +644333 NSD2 chr4 1871393 1982207 +644909 NELFA chr4 1982717 2041903 +645134 C4orf48 chr4 2041993 2043970 +645161 NAT8L chr4 2059512 2069089 +645183 POLN chr4 2071918 2242121 +645402 HAUS3 chr4 2078998 2242276 +645570 AL136360.2 chr4 2139673 2141058 +645574 MXD4 chr4 2247432 2262109 +645631 ZFYVE28 chr4 2269582 2418663 +645817 AL158068.2 chr4 2295584 2319089 +645822 CFAP99 chr4 2418974 2462942 +645920 RNF4 chr4 2462220 2625320 +646190 AL645924.1 chr4 2463797 2464124 +646194 FAM193A chr4 2536631 2732565 +646585 TNIP2 chr4 2741648 2756342 +646651 SH3BP2 chr4 2793071 2841098 +647018 ADD1 chr4 2843857 2930076 +647509 AL121750.1 chr4 2859983 2862673 +647513 MFSD10 chr4 2930561 2934834 +647737 NOP14-AS1 chr4 2934882 2961738 +647804 NOP14 chr4 2937933 2963406 +647972 GRK4 chr4 2963571 3040760 +648145 HTT chr4 3041422 3243960 +648423 HTT-AS chr4 3049094 3074538 +648440 MSANTD1 chr4 3244369 3271738 +648499 RGS12 chr4 3293028 3439913 +648811 HGFAC chr4 3441887 3449495 +648895 AL590235.2 chr4 3450638 3453108 +648899 DOK7 chr4 3463306 3501473 +648986 LRPAP1 chr4 3503612 3532446 +649065 AL590235.1 chr4 3544555 3548796 +649076 LINC00955 chr4 3576869 3590711 +649086 AL121796.1 chr4 3633029 3633975 +649090 LINC02171 chr4 3673593 3677855 +649095 LINC02600 chr4 3758748 3763390 +649099 ADRA2C chr4 3766348 3768526 +649116 OTOP1 chr4 4188803 4226889 +649134 TMEM128 chr4 4235542 4248223 +649165 LYAR chr4 4267701 4290154 +649230 ZBTB49 chr4 4290251 4321786 +649311 AC105415.1 chr4 4321962 4334182 +649316 NSG1 chr4 4348140 4419058 +649480 STX18 chr4 4415742 4542346 +649594 STX18-IT1 chr4 4476121 4481700 +649600 STX18-AS1 chr4 4542131 4787359 +649691 LINC01396 chr4 4844188 4850827 +649705 MSX1 chr4 4859665 4863936 +649718 CYTL1 chr4 5014586 5019458 +649748 STK32B chr4 5051480 5500994 +649890 LINC01587 chr4 5524569 5527801 +649907 EVC2 chr4 5542772 5709548 +650108 EVC chr4 5711201 5814305 +650196 CRMP1 chr4 5748084 5893086 +650328 C4orf50 chr4 5897373 6200555 +650442 JAKMIP1 chr4 6026199 6200591 +650698 AC092442.1 chr4 6064977 6070162 +650707 AC113615.2 chr4 6178186 6184925 +650712 AC113615.1 chr4 6202328 6206649 +650716 WFS1 chr4 6269849 6303265 +650783 AC116317.1 chr4 6292369 6308636 +650796 PPP2R2C chr4 6320578 6563600 +650950 MAN2B2 chr4 6575189 6623362 +651082 MRFAP1 chr4 6640091 6642745 +651127 LINC02482 chr4 6648695 6673965 +651154 AC093323.1 chr4 6663396 6676755 +651184 LINC002481 chr4 6687448 6690519 +651189 S100P chr4 6693878 6697170 +651202 MRFAP1L1 chr4 6707701 6709865 +651214 BLOC1S4 chr4 6716174 6717664 +651222 AC106045.1 chr4 6763508 6767660 +651226 KIAA0232 chr4 6781375 6884170 +651291 TBC1D14 chr4 6909242 7033118 +651481 AC097382.3 chr4 6985926 6987036 +651484 AC097382.1 chr4 6995341 6998958 +651488 AC097382.2 chr4 7030554 7046231 +651494 CCDC96 chr4 7040849 7043001 +651502 TADA2B chr4 7041899 7057952 +651542 GRPEL1 chr4 7058895 7068064 +651569 LINC02447 chr4 7093776 7103394 +651582 SORCS2 chr4 7192538 7742836 +651717 PSAPL1 chr4 7430285 7434930 +651725 AFAP1-AS1 chr4 7754090 7778928 +651729 AFAP1 chr4 7758714 7939926 +651920 AC112254.1 chr4 7798527 7808051 +651924 AC097381.1 chr4 7939001 7940296 +651929 ABLIM2 chr4 7965310 8158832 +652345 AC097381.3 chr4 8022665 8023126 +652348 AC097381.2 chr4 8066528 8067724 +652352 SH3TC1 chr4 8182072 8241803 +652638 HTRA3 chr4 8269754 8307098 +652681 LINC02517 chr4 8320105 8327165 +652732 AC104825.1 chr4 8355090 8358338 +652735 ACOX3 chr4 8366282 8440723 +652900 TRMT44 chr4 8436140 8493531 +652981 AC105345.2 chr4 8453410 8454942 +652985 AC105345.1 chr4 8482270 8516759 +652998 GPR78 chr4 8558725 8619761 +653068 CPZ chr4 8592660 8619759 +653193 AC209005.1 chr4 8745391 8747727 +653198 HMX1 chr4 8846076 8871839 +653217 AC116612.1 chr4 8858715 8860827 +653221 AC108519.1 chr4 9034519 9381269 +653253 AC073648.7 chr4 9076949 9092530 +653257 FAM90A26 chr4 9170409 9176730 +653277 USP17L10 chr4 9210657 9212608 +653294 USP17L11 chr4 9215405 9217356 +653311 USP17L12 chr4 9220152 9221744 +653318 USP17L13 chr4 9224896 9226847 +653335 USP17L15 chr4 9234385 9236334 +653348 USP17L17 chr4 9243879 9245830 +653365 USP17L18 chr4 9248630 9250581 +653382 USP17L19 chr4 9253378 9255329 +653399 USP17L20 chr4 9258124 9260075 +653416 USP17L21 chr4 9262872 9264823 +653433 USP17L22 chr4 9267619 9269570 +653450 USP17L23 chr4 9272364 9272914 +653455 USP17L24 chr4 9325165 9327116 +653472 USP17L25 chr4 9329911 9331862 +653489 USP17L26 chr4 9334658 9336609 +653506 USP17L5 chr4 9339403 9340995 +653513 USP17L27 chr4 9344148 9345740 +653520 USP17L28 chr4 9348893 9350485 +653527 USP17L29 chr4 9353638 9355230 +653534 USP17L30 chr4 9363129 9364721 +653541 DEFB131A chr4 9444534 9450514 +653550 AC105916.1 chr4 9567474 9691786 +653557 SLC2A9 chr4 9771153 10054936 +653710 DRD5 chr4 9781634 9784009 +653718 AC108199.1 chr4 9922814 9924146 +653722 AC005674.1 chr4 10006482 10009725 +653726 AC005674.2 chr4 10068089 10073019 +653730 WDR1 chr4 10074339 10116949 +653956 ZNF518B chr4 10439880 10457426 +653985 AC005599.1 chr4 10456745 10531022 +653990 CLNK chr4 10486395 10684768 +654120 AC084048.1 chr4 10685003 10697661 +654125 LINC02498 chr4 10737558 10749586 +654130 HS3ST1 chr4 11393150 11429564 +654154 AC006230.1 chr4 11426874 11467802 +654169 AC025539.1 chr4 11469250 11478196 +654173 AC005699.1 chr4 11625714 11823906 +654426 LINC02360 chr4 11740948 11769468 +654432 AC108037.1 chr4 11914667 11919688 +654436 LINC02270 chr4 12223445 12251286 +654463 AC007370.2 chr4 12859101 12864961 +654467 AC007370.1 chr4 12947574 12948670 +654471 RAB28 chr4 13361354 13484365 +654604 AC006445.3 chr4 13491185 13516498 +654610 LINC01097 chr4 13526319 13534335 +654625 NKX3-2 chr4 13540830 13544508 +654635 LINC01096 chr4 13546075 13547801 +654642 BOD1L1 chr4 13568738 13627725 +654750 LINC01182 chr4 13654374 14003756 +654774 AC007126.1 chr4 13777377 13782157 +654777 AC073848.1 chr4 14134936 14143592 +654782 AC092546.1 chr4 14164455 14242813 +654790 AC006296.3 chr4 14359400 14453625 +654795 AC006296.2 chr4 14383123 14409078 +654803 AC006296.1 chr4 14390439 14393992 +654807 LINC00504 chr4 14470465 14888169 +654835 CPEB2-DT chr4 14909961 15002045 +654851 CPEB2 chr4 15002674 15070153 +655021 AC098829.1 chr4 15004942 15427914 +655035 C1QTNF7 chr4 15339818 15446166 +655095 AC099550.1 chr4 15358141 15420032 +655101 CC2D2A chr4 15469865 15601557 +655732 AC116651.1 chr4 15563698 15564253 +655735 FBXL5 chr4 15604381 15681679 +655923 FAM200B chr4 15681662 15705565 +656035 BST1 chr4 15703065 15738313 +656131 CD38 chr4 15778275 15853232 +656192 FGFBP1 chr4 15935577 15938740 +656204 FGFBP2 chr4 15960245 15969309 +656217 PROM1 chr4 15963076 16084378 +656688 AC108063.2 chr4 16114233 16117479 +656692 TAPT1 chr4 16160505 16227410 +656852 AC108063.1 chr4 16178939 16183120 +656856 TAPT1-AS1 chr4 16226685 16320140 +656870 AC006427.2 chr4 16322954 16326967 +656874 AC097515.1 chr4 16400430 16512187 +656884 LDB2 chr4 16501541 16898678 +657085 AC104656.1 chr4 16598718 16604593 +657090 AC106894.1 chr4 16973275 17073903 +657095 LINC02493 chr4 17171757 17186079 +657108 QDPR chr4 17460261 17512206 +657235 CLRN2 chr4 17515165 17527104 +657247 LAP3 chr4 17577192 17607972 +657401 AC006160.1 chr4 17586267 17614585 +657411 MED28 chr4 17614641 17634105 +657446 FAM184B chr4 17629306 17781621 +657488 DCAF16 chr4 17800655 17810758 +657506 NCAPG chr4 17810979 17844865 +657622 LCORL chr4 17841199 18021876 +657745 AC093898.1 chr4 18418662 18888662 +657756 AC093871.1 chr4 18488062 18489508 +657760 LINC02438 chr4 19172335 19456994 +657769 AC024230.1 chr4 19455418 19938448 +657786 AC110767.1 chr4 19747179 19754591 +657790 SLIT2 chr4 20251905 20620561 +658263 SLIT2-IT1 chr4 20392154 20394856 +658269 PACRGL chr4 20696282 20752907 +658774 KCNIP4 chr4 20728606 21948772 +658951 AC097505.1 chr4 20766808 20767372 +658954 AC110296.1 chr4 21304468 21350673 +658964 AC096576.6 chr4 21520854 21523709 +658969 AC096576.3 chr4 21582096 21613728 +658975 AC096576.2 chr4 21697450 21719026 +658979 KCNIP4-IT1 chr4 21843341 21853188 +658982 AC096719.1 chr4 21949015 22330330 +658996 ADGRA3 chr4 22345071 22516066 +659175 AC097512.1 chr4 22989147 23193740 +659384 AC092440.1 chr4 23234625 23285573 +659388 AC093607.1 chr4 23560923 23768652 +659395 ERVH-1 chr4 23723262 23733579 +659401 PPARGC1A chr4 23755041 23904089 +659625 AC092834.1 chr4 23779590 23782560 +659630 DHX15 chr4 24517441 24584554 +659698 LINC02473 chr4 24659856 24671568 +659706 SOD3 chr4 24789912 24800842 +659728 CCDC149 chr4 24806117 24980204 +659856 LGI2 chr4 24998847 25030946 +659893 SEPSECS chr4 25120014 25160449 +660004 SEPSECS-AS1 chr4 25160641 25201440 +660011 PI4K2B chr4 25160663 25279204 +660062 AC104662.1 chr4 25220403 25220913 +660065 ZCCHC4 chr4 25312774 25370383 +660186 ANAPC4 chr4 25377213 25418498 +660395 AC105290.1 chr4 25529177 25619468 +660405 SLC34A2 chr4 25648011 25678748 +660562 SEL1L3 chr4 25747433 25863760 +660794 AC092436.3 chr4 25770266 25773577 +660798 SMIM20 chr4 25861830 25929874 +660838 AC133961.1 chr4 25864881 25869550 +660842 LINC02357 chr4 26070754 26104258 +660847 RBPJ chr4 26163455 26435131 +661311 CCKAR chr4 26481396 26490484 +661327 TBC1D19 chr4 26576437 26756223 +661534 STIM2 chr4 26857601 27025381 +661784 STIM2-AS1 chr4 26859806 26860632 +661800 AC024132.2 chr4 27133996 27140051 +661805 AC024132.1 chr4 27207505 27218404 +661809 LINC02261 chr4 27217479 27282225 +661817 AC024132.3 chr4 27262506 27267254 +661821 AC007106.2 chr4 27917753 27943065 +661826 AC007106.1 chr4 27964517 27985063 +661834 AC093791.2 chr4 28225969 28288297 +661838 AC093791.1 chr4 28343862 28402936 +661859 AC097480.1 chr4 28435449 28600275 +661865 AC097480.2 chr4 28580991 28600845 +661872 LINC02364 chr4 28996498 29017256 +661940 AC068944.1 chr4 29046591 29048765 +661944 AC109349.1 chr4 29118304 29211696 +661954 LINC02472 chr4 29214253 29291869 +661972 AC098595.1 chr4 30718805 30721970 +661976 PCDH7 chr4 30720415 31146805 +662034 AC097716.1 chr4 30776257 30793970 +662039 LINC02497 chr4 31171013 31211678 +662052 AC104071.1 chr4 31350284 31351725 +662056 LINC02501 chr4 31506422 31558831 +662070 LINC02506 chr4 31997376 32228543 +662112 AC097654.1 chr4 32005076 32022483 +662118 LINC02353 chr4 32351038 32353220 +662122 AC116611.1 chr4 32583855 32745525 +662132 AC093606.1 chr4 33150326 33208430 +662137 AC097535.1 chr4 33433510 33437877 +662141 AC079772.1 chr4 33467398 33693993 +662152 AC016687.3 chr4 33775498 34039914 +662168 AC016687.2 chr4 33850591 33982349 +662224 LINC02484 chr4 34120090 34335351 +662245 AC110790.1 chr4 34140598 34180729 +662249 AC093689.1 chr4 34657606 34669432 +662261 ARAP2 chr4 35948221 36244514 +662440 AC104078.1 chr4 36244116 36274220 +662454 DTHD1 chr4 36281622 36345756 +662556 AC104078.2 chr4 36311190 36392410 +662561 LINC02505 chr4 36496128 36641939 +662591 AC093746.1 chr4 36902242 36913339 +662595 LINC02616 chr4 37001772 37023499 +662612 AL136537.1 chr4 37073681 37133849 +662687 NWD2 chr4 37244743 37449463 +662707 C4orf19 chr4 37453925 37623495 +662745 AC022463.1 chr4 37454698 37476401 +662751 AC027607.1 chr4 37588087 37588875 +662755 RELL1 chr4 37590800 37686376 +662807 PGM2 chr4 37826660 37862937 +662946 TBC1D1 chr4 37891084 38139175 +663222 PTTG2 chr4 37960398 37961128 +663230 AC098680.2 chr4 38276178 38279880 +663234 AC098680.1 chr4 38286994 38287491 +663238 LINC02513 chr4 38366914 38385759 +663242 LINC01258 chr4 38420662 38523180 +663262 LINC01259 chr4 38509767 38518056 +663267 LINC02278 chr4 38564003 38572022 +663277 KLF3-AS1 chr4 38602438 38664914 +663406 AC021860.1 chr4 38618265 38619437 +663410 KLF3 chr4 38664197 38701517 +663444 TLR10 chr4 38772238 38782990 +663521 TLR1 chr4 38790677 38856817 +663600 TLR6 chr4 38823715 38856817 +663641 FAM114A1 chr4 38867677 38945739 +663731 TMEM156 chr4 38966744 39032922 +663770 KLHL5 chr4 39045039 39126857 +663928 AC079921.1 chr4 39066974 39182258 +663943 AC079921.2 chr4 39133913 39135608 +663947 WDR19 chr4 39182504 39285810 +664289 RFC1 chr4 39287456 39366375 +664521 KLB chr4 39406930 39451533 +664537 RPL9 chr4 39452521 39458949 +664718 LIAS chr4 39459004 39485109 +665094 UGDH chr4 39498755 39528311 +665290 UGDH-AS1 chr4 39528019 39594707 +665297 AC021148.2 chr4 39539395 39546073 +665301 SMIM14 chr4 39546336 39638902 +665368 AC108471.3 chr4 39614465 39618488 +665372 AC108471.2 chr4 39639107 39666879 +665409 UBE2K chr4 39698109 39782792 +665501 PDS5A chr4 39822863 39977956 +665666 N4BP2 chr4 40056850 40158252 +665793 AC095057.3 chr4 40166675 40167831 +665796 AC095057.4 chr4 40187170 40190464 +665801 RHOH chr4 40191053 40246967 +666009 AC095057.2 chr4 40265472 40266457 +666013 LINC02265 chr4 40316485 40330419 +666018 CHRNA9 chr4 40335333 40355217 +666041 RBM47 chr4 40423267 40630875 +666222 AC098869.2 chr4 40426119 40427585 +666226 AC131953.2 chr4 40743627 40750865 +666230 NSUN7 chr4 40749925 40811184 +666314 APBB2 chr4 40810027 41216714 +666770 AC131953.1 chr4 40812779 40826151 +666774 UCHL1-AS1 chr4 41220074 41256727 +666782 UCHL1 chr4 41256413 41268455 +666968 LIMCH1 chr4 41359607 41700044 +667749 AC108050.1 chr4 41608312 41612411 +667753 AC105389.2 chr4 41688858 41692797 +667758 PHOX2B chr4 41744082 41748970 +667774 AC105389.3 chr4 41748293 41824119 +667781 AC105389.1 chr4 41750345 41757341 +667786 LINC00682 chr4 41872747 41882955 +667802 AC108210.1 chr4 41883060 41935075 +667813 TMEM33 chr4 41935129 41960803 +667945 DCAF4L1 chr4 41981756 41986465 +667953 AC106052.1 chr4 41988741 41989237 +667956 SLC30A9 chr4 41990502 42090461 +668059 BEND4 chr4 42110853 42152878 +668111 AC111006.1 chr4 42151028 42268110 +668120 AC024022.1 chr4 42281830 42391651 +668135 SHISA3 chr4 42397488 42402487 +668145 ATP8A1 chr4 42408373 42657105 +668396 AC096734.2 chr4 42657496 42657928 +668399 AC096734.1 chr4 42706107 42707335 +668403 GRXCR1 chr4 42893267 43030658 +668416 AC111198.1 chr4 43133867 43234956 +668423 AC097451.1 chr4 43340875 43345600 +668433 LINC02383 chr4 43457527 43492543 +668438 AC080132.1 chr4 43763134 43972184 +668464 AC114757.1 chr4 43972921 44025516 +668501 LINC02475 chr4 44016700 44022063 +668514 KCTD8 chr4 44173903 44448809 +668533 YIPF7 chr4 44622065 44678556 +668586 GUF1 chr4 44678420 44700928 +668670 GNPDA2 chr4 44682200 44726588 +668762 AC096586.2 chr4 44693946 44694386 +668765 AC096586.1 chr4 44704405 44704965 +668768 AC108467.1 chr4 45009540 45051652 +668776 GABRG1 chr4 46035769 46124054 +668800 AC104072.1 chr4 46243548 46244215 +668803 GABRA2 chr4 46248427 46475230 +669107 AC095060.1 chr4 46390255 46510194 +669118 COX7B2 chr4 46734827 46909245 +669165 GABRA4 chr4 46918900 46993581 +669253 GABRB1 chr4 46993723 47426447 +669312 AC107398.3 chr4 47431960 47438959 +669315 COMMD8 chr4 47450787 47463702 +669334 AC107398.4 chr4 47463590 47470477 +669346 AC107398.5 chr4 47481001 47485210 +669351 ATP10D chr4 47485275 47593486 +669481 AC107398.2 chr4 47556731 47560259 +669486 CORIN chr4 47593999 47838106 +669787 AC107068.2 chr4 47831330 47897965 +669804 AC107068.1 chr4 47840122 47844339 +669807 NFXL1 chr4 47847233 47914667 +670056 NIPAL1 chr4 47914142 48040173 +670113 CNGA1 chr4 47935977 48016672 +670282 TXK chr4 48066393 48134250 +670378 TEC chr4 48135783 48269838 +670485 SLAIN2 chr4 48341529 48426201 +670556 SLC10A4 chr4 48483343 48489526 +670571 ZAR1 chr4 48490252 48494389 +670585 FRYL chr4 48497361 48780322 +671219 OCIAD1 chr4 48805212 48861817 +671669 OCIAD1-AS1 chr4 48852008 48860203 +671673 OCIAD2 chr4 48885019 48906937 +671785 CWH43 chr4 48986275 49062081 +671900 DCUN1D4 chr4 51843000 51916837 +672224 AC027271.1 chr4 51918772 51919381 +672227 LRRC66 chr4 51993702 52017620 +672241 SGCB chr4 52020706 52038482 +672283 LINC02480 chr4 52044805 52046954 +672288 SPATA18 chr4 52051304 52097299 +672435 AC097522.2 chr4 52252820 52551574 +672440 USP46 chr4 52590960 52659301 +672586 USP46-AS1 chr4 52659406 52661668 +672590 AC104066.3 chr4 52680609 52692999 +672595 LINC01618 chr4 52712394 52866821 +672624 DANCR chr4 52712404 52720351 +672646 AC104066.4 chr4 52712713 52722377 +672650 ERVMER34-1 chr4 52722618 52751586 +672679 RASL11B chr4 52862317 52866835 +672700 SCFD2 chr4 52872982 53366066 +672766 AC023154.1 chr4 52945649 52958087 +672778 FIP1L1 chr4 53377641 53460862 +673029 LNX1 chr4 53459301 53701405 +673144 LNX1-AS1 chr4 53496400 53549578 +673161 LNX1-AS2 chr4 53592956 53604047 +673168 AC124017.1 chr4 53659208 53737156 +673178 AC105384.1 chr4 53899871 53916835 +673183 AC110792.3 chr4 53997415 53997712 +673186 CHIC2 chr4 54009789 54064605 +673237 AC110792.2 chr4 54059597 54061210 +673240 AC110792.4 chr4 54065239 54078454 +673244 GSX2 chr4 54099523 54102498 +673266 PDGFRA chr4 54229280 54298245 +673442 LINC02283 chr4 54332892 54355954 +673446 AC098587.1 chr4 54376002 54376752 +673450 AC098868.1 chr4 54440502 54446723 +673456 LINC02260 chr4 54603211 54607131 +673460 KIT chr4 54657918 54740715 +673563 AC097494.1 chr4 54836041 54845470 +673574 LINC02358 chr4 54845568 54859241 +673578 AC111194.1 chr4 54943626 54957832 +673583 AC111194.2 chr4 55053060 55092534 +673589 KDR chr4 55078481 55125595 +673704 AC021220.2 chr4 55157877 55161880 +673708 SRD5A3 chr4 55346242 55373100 +673738 SRD5A3-AS1 chr4 55363971 55395847 +673904 AC069200.1 chr4 55387949 55388271 +673907 TMEM165 chr4 55395957 55453397 +674003 CLOCK chr4 55427903 55546909 +674222 AC024243.1 chr4 55547112 55547889 +674225 PDCL2 chr4 55556519 55592245 +674243 NMU chr4 55595229 55636698 +674353 EXOC1L chr4 55819819 55837487 +674376 EXOC1 chr4 55853648 55905086 +674536 AC110611.1 chr4 55889743 55903177 +674540 AC110611.2 chr4 55938153 55947996 +674545 CEP135 chr4 55948871 56033361 +674649 KIAA1211 chr4 56049073 56328625 +674805 AC022267.1 chr4 56291601 56299873 +674809 AASDH chr4 56338287 56387508 +675038 AC068620.1 chr4 56387625 56388153 +675041 PPAT chr4 56393362 56435615 +675113 AC068620.2 chr4 56396312 56396871 +675116 PAICS chr4 56435741 56464579 +675247 SRP72 chr4 56467617 56503681 +675392 ARL9 chr4 56505209 56525481 +675428 THEGL chr4 56530606 56603507 +675458 HOPX chr4 56647988 56681899 +675607 SPINK2 chr4 56809860 56821742 +675681 REST chr4 56907876 56966678 +675806 AC069307.1 chr4 56960927 56961373 +675809 NOA1 chr4 56963350 56977606 +675829 POLR2B chr4 56977722 57031158 +676159 IGFBP7 chr4 57030773 57110385 +676194 IGFBP7-AS1 chr4 57109762 57207459 +676212 AC111197.1 chr4 57110547 57111400 +676215 AC105390.1 chr4 57154577 57156452 +676220 LINC02380 chr4 57424495 57478341 +676260 AC013724.1 chr4 57490808 57495844 +676277 AC107396.1 chr4 57595940 57605872 +676281 AC093725.2 chr4 57605694 57658800 +676290 AC093725.1 chr4 57720035 57724655 +676294 AC104790.1 chr4 57841721 57855271 +676299 LINC02494 chr4 58524515 58536328 +676304 AC019133.1 chr4 58562160 58565212 +676309 AC017091.1 chr4 58780626 58984194 +676342 LINC02619 chr4 58939288 58988182 +676378 LINC02429 chr4 58984215 59046959 +676398 AC097501.1 chr4 59047020 59075256 +676403 AC108517.2 chr4 59150924 59180414 +676408 AC108517.1 chr4 59152834 59176146 +676412 AC096588.1 chr4 59551142 59630324 +676420 AC093857.1 chr4 59767816 59792114 +676426 AC092596.1 chr4 59903404 59920670 +676431 LINC02496 chr4 60750575 60796103 +676441 LINC02271 chr4 61143656 61153962 +676450 ADGRL3 chr4 61201258 62078335 +677244 AC020741.1 chr4 61420246 61428221 +677249 ADGRL3-AS1 chr4 62071752 62165554 +677282 AC097491.1 chr4 63128311 63143881 +677287 AC093730.1 chr4 63465511 63529761 +677296 TECRL chr4 64275257 64409468 +677388 AC104689.2 chr4 64836361 64883916 +677395 LINC02232 chr4 64914281 65024485 +677449 LINC02835 chr4 65225867 65241814 +677454 EPHA5 chr4 65319563 65670495 +677691 EPHA5-AS1 chr4 65669961 65698029 +677703 AC104137.1 chr4 65702202 65705553 +677707 AC097110.1 chr4 65858761 65860204 +677711 AC116049.2 chr4 65998846 66150012 +677717 AC096721.1 chr4 66003281 66016792 +677721 AC110809.1 chr4 66169778 66329377 +677726 AC104806.2 chr4 67417305 67468251 +677748 CENPC chr4 67468762 67545503 +677907 STAP1 chr4 67558727 67607337 +677956 UBA6 chr4 67612652 67701155 +678107 UBA6-AS1 chr4 67701209 68080952 +678202 GNRHR chr4 67739328 67754360 +678224 TMPRSS11D chr4 67820876 67884002 +678296 TMPRSS11A chr4 67909385 67964140 +678366 TMPRSS11F chr4 68053198 68129869 +678392 TMPRSS11B chr4 68226653 68245694 +678428 YTHDC1 chr4 68310387 68350089 +678574 TMPRSS11E chr4 68447463 68497604 +678615 UGT2B17 chr4 68537184 68568527 +678633 UGT2B15 chr4 68646597 68670652 +678651 UGT2B10 chr4 68815994 68832023 +678686 AC021146.12 chr4 68901008 68906983 +678690 UGT2A3 chr4 68928463 68951804 +678727 UGT2B7 chr4 69051363 69112987 +678795 AC111000.4 chr4 69182100 69216766 +678807 UGT2B11 chr4 69199951 69214748 +678828 UGT2B28 chr4 69280475 69295050 +678859 UGT2B4 chr4 69480165 69526014 +678928 UGT2A1 chr4 69588417 69653249 +679015 UGT2A2 chr4 69589309 69639642 +679048 SULT1B1 chr4 69721167 69787961 +679098 SULT1E1 chr4 69841212 69860145 +679126 CSN1S1 chr4 69931068 69946574 +679286 CSN2 chr4 69955256 69961007 +679306 STATH chr4 69995931 70002570 +679374 HTN3 chr4 70028413 70036538 +679455 HTN1 chr4 70050438 70058848 +679514 PRR27 chr4 70133616 70176799 +679591 ODAM chr4 70196496 70204576 +679678 FDCSP chr4 70226124 70235252 +679693 CSN3 chr4 70242588 70251428 +679709 CABS1 chr4 70334981 70337116 +679719 SMR3A chr4 70360760 70367158 +679731 SMR3B chr4 70370093 70390244 +679770 OPRPN chr4 70397931 70410195 +679790 MUC7 chr4 70430492 70482997 +679850 AMTN chr4 70518569 70532743 +679897 AMBN chr4 70592256 70607288 +679993 ENAM chr4 70628744 70646824 +680024 AC009570.2 chr4 70637745 70686816 +680034 JCHAIN chr4 70655541 70681817 +680115 UTP3 chr4 70688532 70690551 +680123 AC009570.1 chr4 70703747 70704491 +680126 RUFY3 chr4 70704204 70808619 +680365 GRSF1 chr4 70815783 70839897 +680520 MOB1B chr4 70902326 71022449 +680583 DCK chr4 70992538 71030914 +680672 SLC4A4 chr4 71062667 71572087 +681010 GC chr4 71741696 71804041 +681168 AC068721.1 chr4 71821305 71823980 +681174 NPFFR2 chr4 72031804 72148067 +681230 ADAMTS3 chr4 72280969 72569221 +681343 AC095056.1 chr4 72323028 72330751 +681347 COX18 chr4 73052362 73069755 +681417 ANKRD17 chr4 73073376 73258798 +681814 AC053527.2 chr4 73259209 73317953 +681821 ALB chr4 73397114 73421482 +682155 AFP chr4 73431138 73456174 +682246 AFM chr4 73481745 73504001 +682285 LINC02499 chr4 73508803 73534128 +682297 RASSF6 chr4 73571550 73620631 +682405 UMLILO chr4 73710302 73714527 +682410 CXCL8 chr4 73740541 73743716 +682438 CXCL6 chr4 73836640 73849064 +682467 PF4V1 chr4 73853296 73854483 +682479 CXCL1 chr4 73869393 73871308 +682497 PF4 chr4 73980811 73982027 +682509 PPBP chr4 73986439 73988190 +682521 CXCL5 chr4 73995642 73998677 +682535 AC097709.1 chr4 73997933 74007682 +682540 CXCL3 chr4 74036589 74038807 +682565 AC093677.3 chr4 74076533 74078973 +682569 CXCL2 chr4 74097040 74099196 +682590 MTHFD2L chr4 74114174 74303099 +682772 AC093677.2 chr4 74156511 74158373 +682775 EPGN chr4 74308470 74316789 +682894 EREG chr4 74365145 74388749 +682917 AC021180.1 chr4 74418917 74440457 +682921 AREG chr4 74445136 74455005 +682957 AC239584.1 chr4 74552584 74589481 +682965 BTC chr4 74744759 74794523 +682994 AC098825.1 chr4 74881174 74882934 +682998 PARM1 chr4 74933095 75050115 +683023 AC110760.2 chr4 74955974 74970362 +683033 AC110760.1 chr4 74993877 75034824 +683039 LINC02562 chr4 75081702 75084717 +683051 AC025244.1 chr4 75269068 75361182 +683055 AC025244.2 chr4 75341279 75359024 +683061 LINC02483 chr4 75354076 75362566 +683067 AC096759.1 chr4 75361207 75434449 +683071 AC096759.2 chr4 75401195 75423023 +683081 RCHY1 chr4 75479037 75514764 +683293 THAP6 chr4 75513946 75550473 +683452 ODAPH chr4 75556048 75565885 +683501 CDKL2 chr4 75576496 75630716 +683582 G3BP2 chr4 75642782 75724525 +683829 USO1 chr4 75724593 75814286 +683947 AC110615.1 chr4 75822966 75838389 +683957 PPEF2 chr4 75859864 75902571 +684099 NAAA chr4 75913660 75941013 +684224 SDAD1 chr4 75940950 75990962 +684438 AC112719.2 chr4 75980790 76005942 +684443 CXCL9 chr4 76001275 76007509 +684457 ART3 chr4 76011184 76112802 +684657 CXCL10 chr4 76021118 76023497 +684671 CXCL11 chr4 76033682 76041415 +684700 NUP54 chr4 76114659 76148444 +684917 AC110795.1 chr4 76148561 76200666 +684922 SCARB2 chr4 76158737 76234536 +685357 FAM47E chr4 76214040 76283783 +685454 AC034139.1 chr4 76240740 76312098 +685461 STBD1 chr4 76306026 76311599 +685471 CCDC158 chr4 76312997 76421868 +685574 SHROOM3 chr4 76435229 76783253 +685679 AC107072.2 chr4 76708853 76802426 +685699 AC107072.1 chr4 76758554 76801964 +685703 SOWAHB chr4 76894152 76898144 +685711 SEPTIN11 chr4 76949703 77040384 +685918 CCNI chr4 77047155 77075989 +685999 CCNG2 chr4 77157207 77433388 +686107 AC092674.1 chr4 77394491 77494286 +686112 CXCL13 chr4 77511753 77611834 +686132 CNOT6L chr4 77713387 77819615 +686308 MRPL1 chr4 77862830 77952785 +686367 FRAS1 chr4 78057323 78544269 +686715 ANXA3 chr4 78551747 78610451 +686881 LINC01094 chr4 78638780 78683185 +686973 AC112253.1 chr4 78669690 78691671 +686977 AC098818.2 chr4 78773654 78775973 +686980 BMP2K chr4 78776342 78916372 +687157 PAQR3 chr4 78887127 78939438 +687317 LINC01088 chr4 78939485 79309673 +687390 NAA11 chr4 79225694 79326061 +687412 GK2 chr4 79406361 79408228 +687420 LINC00989 chr4 79491802 79623479 +687470 AC092542.1 chr4 79596542 79597173 +687474 LINC02469 chr4 79663761 79696837 +687480 PCAT4 chr4 79827471 79877770 +687488 ANTXR2 chr4 79901146 80125454 +687694 AC021127.1 chr4 80182637 80197410 +687703 PRDM8 chr4 80183879 80204329 +687818 FGF5 chr4 80266599 80336680 +687859 CFAP299 chr4 80335720 80963756 +687952 BMP3 chr4 81030708 81057632 +687964 PRKG2 chr4 81087370 81215117 +688166 AC139722.1 chr4 81164922 81193395 +688186 RASGEF1B chr4 81426393 82044244 +688423 AC124016.2 chr4 82344876 82346842 +688427 HNRNPD chr4 82352498 82374503 +688597 AC124016.1 chr4 82374301 82384027 +688603 HNRNPDL chr4 82422564 82430408 +688814 ENOPH1 chr4 82430590 82461177 +688879 TMEM150C chr4 82483170 82562357 +688956 LINC00575 chr4 82610974 82621610 +688972 AC067942.4 chr4 82612184 82615575 +688977 SCD5 chr4 82629539 82798796 +689006 SEC31A chr4 82818509 82901166 +690063 THAP9-AS1 chr4 82893009 82900960 +690118 THAP9 chr4 82900684 82919969 +690203 LIN54 chr4 82909973 83012926 +690453 COPS4 chr4 83034447 83075818 +690607 AC073840.1 chr4 83075957 83085600 +690611 PLAC8 chr4 83090048 83137075 +690693 AC114781.2 chr4 83233512 83247213 +690698 COQ2 chr4 83261536 83284914 +690795 HPSE chr4 83292461 83335153 +690994 HELQ chr4 83407343 83455855 +691125 MRPS18C chr4 83455932 83469735 +691212 ABRAXAS1 chr4 83459517 83523348 +691356 GPAT3 chr4 83535914 83605875 +691467 AC021192.1 chr4 83668510 83731755 +691473 AC079160.1 chr4 83796436 84299189 +691508 AC104063.1 chr4 84371393 84380189 +691513 NKX6-1 chr4 84491987 84498450 +691536 CDS1 chr4 84583127 84651334 +691581 WDFY3 chr4 84669610 84966391 +691822 WDFY3-AS1 chr4 84796614 84810403 +691827 WDFY3-AS2 chr4 84965534 85011277 +691970 AC108021.1 chr4 84970180 84970730 +691973 ARHGAP24 chr4 85475150 86002668 +692117 MAPK10 chr4 85990007 86594625 +696729 AC104827.1 chr4 86117912 86219926 +696739 PTPN13 chr4 86594315 86815171 +697274 SLC10A6 chr4 86823468 86849384 +697297 C4orf36 chr4 86876205 86892422 +697370 AC093827.4 chr4 86924630 86936202 +697387 AFF1 chr4 86935002 87141054 +697625 KLHL8 chr4 87160103 87240314 +697759 AC108516.1 chr4 87261931 87266822 +697763 HSD17B13 chr4 87303789 87322886 +697800 HSD17B11 chr4 87336515 87391188 +697863 NUDT9 chr4 87422573 87459455 +697964 AC112250.2 chr4 87460807 87462280 +697968 SPARCL1 chr4 87473335 87531061 +698143 AC093895.1 chr4 87568035 87733956 +698160 DSPP chr4 87608529 87616873 +698176 DMP1 chr4 87650280 87664361 +698209 IBSP chr4 87799554 87812435 +698229 MEPE chr4 87821411 87846817 +698348 AC131944.1 chr4 87974385 88008477 +698353 SPP1 chr4 87975650 87983426 +698480 PKD2 chr4 88007635 88077777 +698588 ABCG2 chr4 88090150 88231628 +698724 PPM1K chr4 88257620 88284769 +698827 PPM1K-DT chr4 88284507 88331421 +698855 AC107067.2 chr4 88352222 88358423 +698859 AC107067.1 chr4 88358945 88361304 +698864 HERC6 chr4 88378739 88443111 +699051 HERC5 chr4 88457119 88506163 +699173 PYURF chr4 88520998 88523776 +699183 PIGY chr4 88521573 88521789 +699190 PIGY-DT chr4 88523826 88524983 +699197 HERC3 chr4 88592434 88708541 +699394 NAP1L5 chr4 88695913 88697829 +699402 FAM13A-AS1 chr4 88709298 88730103 +699428 FAM13A chr4 88725955 89111398 +699850 TIGD2 chr4 89111500 89114899 +699867 AC104785.1 chr4 89119284 89119871 +699870 GPRIN3 chr4 89236383 89307800 +699887 AC093866.1 chr4 89410960 89726752 +699933 SNCA chr4 89724099 89838315 +700124 AC097478.1 chr4 89743792 89744305 +700127 AC097478.3 chr4 89747802 89755853 +700133 AC097478.2 chr4 89748283 89749154 +700136 SNCA-AS1 chr4 89836408 89841978 +700145 MMRN1 chr4 89879532 89954629 +700214 AC105445.1 chr4 89995223 89999409 +700220 CCSER1 chr4 90127535 91601913 +700408 AC004054.1 chr4 91108023 91112790 +700412 AC074124.1 chr4 91319034 91325306 +700417 AC093810.1 chr4 91887886 91904335 +700423 AC097520.2 chr4 92183235 92265316 +700428 LNCPRESS2 chr4 92268767 92277075 +700432 AC112695.1 chr4 92297251 92304178 +700437 GRID2 chr4 92303966 93810157 +700599 AC095059.1 chr4 92833685 92838842 +700603 AC110800.1 chr4 93318623 93319786 +700607 ATOH1 chr4 93828753 93830966 +700615 AC096746.1 chr4 94117792 94207556 +700626 SMARCAD1 chr4 94207611 94291292 +700926 HPGDS chr4 94298535 94342876 +700953 AC109925.2 chr4 94315486 94343041 +700957 PDLIM5 chr4 94451857 94668227 +701382 AC108067.1 chr4 94675245 94702570 +701386 BMPR1B-DT chr4 94743668 94757681 +701391 BMPR1B chr4 94757955 95158448 +701607 UNC5C chr4 95162504 95549206 +701753 AC106881.1 chr4 95549129 95552457 +701756 PDHA2 chr4 95840093 95841464 +701764 LINC02267 chr4 96310701 96818864 +701773 AC096585.1 chr4 96841995 96857900 +701779 AC108515.1 chr4 97120701 97135059 +701783 STPG2 chr4 97184093 98143476 +701830 AC034154.1 chr4 97334635 97633823 +701841 STPG2-AS1 chr4 97366681 97491899 +701861 AC019077.1 chr4 98251688 98261630 +701865 RAP1GDS1 chr4 98261384 98443861 +702224 TSPAN5 chr4 98470367 98658611 +702362 AC108159.1 chr4 98496364 98509935 +702368 AC114811.2 chr4 98658904 98664550 +702371 EIF4E chr4 98871684 98930637 +702505 AC019131.1 chr4 98928897 98994994 +702512 AC019131.3 chr4 98961083 98964790 +702517 METAP1 chr4 98995659 99062809 +702678 AC019131.2 chr4 99067256 99068125 +702681 ADH5 chr4 99070978 99088801 +702828 AP002026.1 chr4 99088805 99301356 +702891 ADH4 chr4 99123657 99157792 +703089 ADH6 chr4 99202638 99219537 +703202 ADH1A chr4 99276369 99291003 +703237 ADH1B chr4 99304971 99352760 +703344 ADH1C chr4 99336497 99352746 +703403 ADH7 chr4 99412261 99435737 +703514 C4orf17 chr4 99511012 99542303 +703589 TRMT10A chr4 99546709 99564039 +703690 MTTP chr4 99563761 99623999 +703916 AC083902.1 chr4 99594799 99625913 +703922 C4orf54 chr4 99636529 99654648 +703931 DAPP1 chr4 99816827 99870190 +703990 LAMTOR3 chr4 99878336 99894428 +704036 DNAJB14 chr4 99896248 99946618 +704180 H2AFZ chr4 99948086 99950355 +704233 AC097460.1 chr4 99950006 100195099 +704258 DDIT4L chr4 100185870 100190782 +704286 AP001961.1 chr4 100190033 100215505 +704293 EMCN chr4 100395341 100880126 +704429 AC097459.1 chr4 100421655 100474461 +704433 LINC01216 chr4 100660279 100675113 +704439 LINC01217 chr4 100778582 100791426 +704447 LINC01218 chr4 100812255 100814280 +704451 PPP3CA chr4 101023409 101348278 +704648 AP001816.1 chr4 101347780 101348883 +704655 BANK1 chr4 101411286 102074812 +704870 AC084277.1 chr4 101640946 101649974 +704875 AP002075.1 chr4 101976894 102036903 +704880 SLC39A8 chr4 102251041 102431258 +704976 AC098487.1 chr4 102418602 102450010 +704994 AF213884.3 chr4 102500841 102501319 +704997 NFKB1 chr4 102501331 102617302 +705387 MANBA chr4 102630770 102760994 +705853 UBE2D3 chr4 102794383 102868896 +706393 AC018797.3 chr4 102814252 102819881 +706397 UBE2D3-AS1 chr4 102828055 102844075 +706401 CISD2 chr4 102868974 102892807 +706463 SLC9B1 chr4 102885048 103019719 +706658 SLC9B2 chr4 103019868 103085829 +706835 BDH2 chr4 103077592 103099870 +706966 CENPE chr4 103105349 103198445 +707311 LINC02428 chr4 103255822 103454667 +707361 AC105460.2 chr4 103548745 103624534 +707374 AC105460.1 chr4 103550586 103559277 +707409 TACR3 chr4 103586031 103719985 +707425 AC004047.1 chr4 103871890 103878436 +707429 LINC02503 chr4 103961616 104037543 +707435 AC004052.1 chr4 104230380 104411035 +707452 CXXC4 chr4 104468308 104494901 +707471 CXXC4-AS1 chr4 104490849 104734546 +707496 AC004063.1 chr4 104556960 104568877 +707502 AC004053.1 chr4 104653874 104966793 +707510 AC096577.1 chr4 104900125 105120000 +707535 AC004069.1 chr4 105137280 105140619 +707539 TET2 chr4 105145875 105279816 +707684 TET2-AS1 chr4 105171354 105178063 +707691 PPA2 chr4 105369077 105474067 +708018 AC004066.2 chr4 105540190 105552355 +708024 ARHGEF38 chr4 105552620 105708093 +708104 ARHGEF38-IT1 chr4 105561591 105570238 +708109 INTS12 chr4 105682627 105895986 +708259 GSTCD chr4 105708778 105847728 +708439 AC008243.1 chr4 105746245 105827172 +708457 NPNT chr4 105894775 106004027 +708739 AC109361.2 chr4 105927060 105932722 +708746 AC109361.1 chr4 106003317 106022478 +708752 TBCK chr4 106041599 106321495 +709245 AIMP1 chr4 106315544 106349456 +709520 GIMD1 chr4 106357485 106368825 +709540 LINC02173 chr4 106433489 106453449 +709555 AC092445.1 chr4 106525401 106938640 +709568 DKK2 chr4 106921802 107283806 +709618 AC104663.1 chr4 107258700 107301870 +709622 PAPSS1 chr4 107590276 107720234 +709687 SGMS2 chr4 107824563 107915047 +709779 AC096564.1 chr4 107863473 107989679 +709821 CYP2U1 chr4 107931549 107953461 +709859 AC096564.2 chr4 107936031 107941255 +709865 HADH chr4 107989714 108035175 +710195 LEF1 chr4 108047545 108168956 +710469 LEF1-AS1 chr4 108167525 108258037 +710503 RPL34-AS1 chr4 108538190 108620460 +710523 RPL34 chr4 108620566 108630412 +710611 OSTC chr4 108650585 108667820 +710657 AC107071.1 chr4 108669949 108678874 +710662 ETNPPL chr4 108742048 108763054 +710846 COL25A1 chr4 108808725 109302752 +711404 ZCCHC23 chr4 109303035 109316135 +711409 SEC24B-AS1 chr4 109347475 109433817 +711467 SEC24B chr4 109433772 109540896 +711627 MCUB chr4 109560209 109688719 +711669 CASP6 chr4 109688622 109703583 +711746 AC004067.1 chr4 109692004 109692703 +711749 PLA2G12A chr4 109709989 109730070 +711790 CFI chr4 109740694 109802179 +711938 AC126283.1 chr4 109815047 109815410 +711941 GAR1 chr4 109815510 109824740 +711991 RRH chr4 109827972 109849123 +712029 LRIT3 chr4 109848107 109872315 +712056 EGF chr4 109912883 110013766 +712296 ELOVL6 chr4 110045846 110199199 +712377 ENPEP chr4 110365733 110565285 +712454 AC098798.1 chr4 110512488 110519505 +712460 PANCR chr4 110595513 110615458 +712469 PITX2 chr4 110617423 110642123 +712622 LINC01438 chr4 110794403 110797344 +712626 AC083795.2 chr4 111632172 111648962 +712648 AC139718.2 chr4 111802801 111839886 +712653 AC139718.1 chr4 111804418 111809694 +712657 AC004704.1 chr4 111826881 112072698 +712662 FAM241A chr4 112145454 112195256 +712672 AC109347.1 chr4 112229561 112231596 +712675 AP1AR chr4 112231740 112273110 +712748 AC109347.2 chr4 112272968 112273316 +712751 TIFA chr4 112274537 112285904 +712770 ALPK1 chr4 112285509 112442621 +713076 NEUROG2 chr4 112513516 112516180 +713086 AC023886.1 chr4 112515385 112546881 +713095 ZGRF1 chr4 112539333 112636995 +713426 LARP7 chr4 112637107 112657592 +713698 MIR302CHG chr4 112646476 112650051 +713710 AC106864.1 chr4 112693047 112706810 +713714 ANK2 chr4 112818032 113384221 +720733 AC017007.5 chr4 112880298 112882330 +720737 AC093879.1 chr4 112973272 113071962 +720750 AC093879.2 chr4 113031287 113034551 +720755 CAMK2D chr4 113451032 113761927 +721215 ARSJ chr4 113900284 113979727 +721247 AC104779.1 chr4 113943256 113944320 +721251 UGT8 chr4 114598770 114678225 +721293 NDST4 chr4 114827763 115113876 +721400 MTRNR2L13 chr4 116298876 116300320 +721408 AC106892.1 chr4 116489364 116515619 +721424 AC093765.5 chr4 116714844 116719669 +721429 AC093765.4 chr4 116720123 116739945 +721433 AC093765.3 chr4 116751473 116952699 +721444 AC093765.2 chr4 116754453 116921792 +721457 TRAM1L1 chr4 117083554 117085576 +721465 LINC02262 chr4 117314597 117360655 +721493 LINC02263 chr4 117360596 117412712 +721605 LINC01378 chr4 117406166 117691188 +721686 AC092661.1 chr4 117648832 117657312 +721691 LINC02264 chr4 117834145 117869960 +721714 NDST3 chr4 118033618 118258634 +721751 SNHG8 chr4 118278709 118285316 +721786 PRSS12 chr4 118280038 118353003 +721831 METTL14-DT chr4 118664087 118685343 +721919 METTL14 chr4 118685392 118715433 +722018 SEC24D chr4 118722823 118838683 +722308 SYNPO2 chr4 118850688 119061247 +722397 MYOZ2 chr4 119135784 119187789 +722415 USP53 chr4 119212587 119295517 +722568 C4orf3 chr4 119296419 119304445 +722590 FABP2 chr4 119317250 119322138 +722604 AC093752.3 chr4 119409333 119410233 +722607 AC093752.2 chr4 119456350 119457277 +722611 PDE5A chr4 119494397 119628804 +722813 AC080089.2 chr4 119686538 119693563 +722817 LINC01365 chr4 119799089 119804554 +722835 LINC02502 chr4 119939540 119964293 +722839 AC097173.2 chr4 120035033 120040615 +722843 MAD2L1 chr4 120055623 120066858 +722889 AC073475.1 chr4 120066958 120564789 +722916 AC025741.1 chr4 120639090 120650796 +722923 PRDM5 chr4 120684919 120922870 +723108 NDNF chr4 121035613 121073021 +723148 AC105254.1 chr4 121071429 121080476 +723153 TNIP3 chr4 121131408 121227466 +723274 QRFPR chr4 121328642 121381059 +723330 ANXA5 chr4 121667946 121696995 +723502 TMEM155 chr4 121758930 121765427 +723578 AC079341.1 chr4 121764585 121766814 +723581 EXOSC9 chr4 121801317 121817021 +723778 CCNA2 chr4 121816444 121823933 +723821 BBS7 chr4 121824329 121870487 +723930 AC079341.2 chr4 121870583 121872848 +723933 TRPC3 chr4 121874481 121952060 +724050 KIAA1109 chr4 122152333 122362758 +724738 ADAD1 chr4 122378966 122429802 +724864 IL2 chr4 122451470 122456725 +724882 IL21 chr4 122610108 122621066 +724915 IL21-AS1 chr4 122618983 122689156 +724950 AC053545.1 chr4 122700445 122708788 +724954 BBS12 chr4 122732702 122744942 +724984 FGF2 chr4 122826708 122898236 +725026 AC021205.3 chr4 122879778 122885805 +725034 NUDT6 chr4 122888697 122922968 +725123 SPATA5 chr4 122923078 123319433 +725177 AC026402.2 chr4 123349250 123351221 +725181 SPRY1 chr4 123396795 123403760 +725257 AC093821.1 chr4 123490242 123522106 +725270 LINC02435 chr4 123505279 123527525 +725275 LINC01091 chr4 123539026 123962698 +725491 AC096732.1 chr4 123744923 123745673 +725496 AC108075.1 chr4 124025295 124028268 +725500 AC121154.1 chr4 124149377 124252044 +725507 AC133530.1 chr4 124324973 124339047 +725511 LINC02516 chr4 124499940 124558445 +725544 ANKRD50 chr4 124664048 124712732 +725573 FAT4 chr4 125316399 125492932 +725650 AC104664.1 chr4 125676718 126017357 +725658 LINC02379 chr4 126064128 126073370 +725683 AC097528.1 chr4 126431694 126735523 +725698 AC096773.1 chr4 127043430 127077762 +725703 AC093772.1 chr4 127094410 127470569 +725732 AC093772.2 chr4 127228519 127352379 +725736 AC097462.3 chr4 127532828 127623803 +725750 INTU chr4 127623271 127726737 +725903 SLC25A31 chr4 127730400 127774292 +725921 HSPA4L chr4 127781821 127840733 +726086 AC093591.2 chr4 127840198 127844040 +726089 PLK4 chr4 127880893 127899224 +726312 MFSD8 chr4 127917732 127966034 +727531 ABHD18 chr4 127965306 128039927 +727719 LARP1B chr4 128061286 128222931 +728025 PGRMC2 chr4 128269237 128288829 +728112 LINC02615 chr4 128292751 128519398 +728156 AC110609.1 chr4 128552590 128553416 +728160 AC078850.1 chr4 128567972 128570531 +728164 AC078850.2 chr4 128582999 128601407 +728171 JADRR chr4 128768228 128769948 +728174 JADE1 chr4 128809700 128875224 +728447 SCLT1 chr4 128864921 129093600 +728680 C4orf33 chr4 129093317 129116640 +728757 AC082650.1 chr4 129299175 129305022 +728761 AC082650.2 chr4 129362911 129377504 +728765 LINC02466 chr4 129612330 129771527 +728840 LINC02465 chr4 129771596 129975329 +729149 LINC02479 chr4 130376229 130432227 +729157 AC093831.1 chr4 130881027 130885641 +729161 LINC02377 chr4 131379717 131591825 +729191 SNHG27 chr4 131727587 131791492 +729259 AC096711.2 chr4 131930031 131975952 +729264 AC093916.1 chr4 131978485 132345621 +729279 AC096711.1 chr4 132027175 132028434 +729283 AC114741.1 chr4 132435802 132447235 +729288 LINC01256 chr4 132591064 132678503 +729301 AC115622.1 chr4 132836772 132981677 +729306 AC110751.1 chr4 132985510 132988677 +729311 AC105383.1 chr4 133075311 133149147 +729436 PCDH10 chr4 133149294 133208606 +729463 AC108052.1 chr4 133261022 133263115 +729467 AC079380.1 chr4 133871246 134010690 +729473 AC015631.1 chr4 134026665 134327977 +729600 AC096763.1 chr4 134057468 134085506 +729605 PABPC4L chr4 134196333 134201789 +729615 LINC02462 chr4 134383467 134545648 +729639 AC093722.1 chr4 134759399 134817289 +729646 AC104619.2 chr4 134932889 134934131 +729650 AC107463.1 chr4 135067233 135097658 +729663 LINC02485 chr4 135112905 135123779 +729672 AC105362.1 chr4 135792384 135805904 +729677 LINC00613 chr4 135866983 135913680 +729690 AC073429.2 chr4 136097797 136099240 +729693 AC018680.1 chr4 136118675 136395471 +729703 AC073429.1 chr4 136125909 136138874 +729708 LINC02511 chr4 136795919 137212799 +729743 LINC02510 chr4 137193756 137198367 +729747 PCDH18 chr4 137518918 137532494 +729838 LINC02172 chr4 137545731 137603430 +729842 AC116563.1 chr4 137645265 137655174 +729848 AC131956.2 chr4 137690477 137734977 +729859 AC131956.3 chr4 137751029 137755300 +729865 AC131956.1 chr4 137807706 137816402 +729869 AC097511.1 chr4 137943022 138051288 +729880 LINC00616 chr4 137978547 138131182 +730217 SLC7A11-AS1 chr4 138057464 138178177 +730242 SLC7A11 chr4 138164097 138242349 +730289 AC093903.1 chr4 138277115 138281784 +730293 LINC00498 chr4 138298856 138312658 +730297 LINC00499 chr4 138309613 138663403 +730427 LINC00500 chr4 138425523 138436869 +730431 AC098859.2 chr4 138664725 138665569 +730435 AC093766.1 chr4 138773537 138803567 +730506 AC109927.1 chr4 138819954 139012646 +730518 AC109927.2 chr4 138923930 138924232 +730521 NOCT chr4 139015781 139045939 +730547 ELF2 chr4 139028112 139177218 +730717 MGARP chr4 139266165 139280225 +730731 NDUFC1 chr4 139266880 139302551 +730865 NAA15 chr4 139301505 139420033 +730994 AC097376.3 chr4 139411927 139454034 +731013 RAB33B chr4 139453232 139476609 +731037 SETD7 chr4 139495941 139606699 +731138 AC112236.2 chr4 139556799 139557643 +731141 AC112236.3 chr4 139568573 139580143 +731146 AC112236.1 chr4 139618136 139623232 +731150 MGST2 chr4 139665768 139740745 +731231 MAML3 chr4 139716753 140154184 +731270 AC108053.1 chr4 139763080 139770391 +731274 AC131182.1 chr4 140128015 140134565 +731279 SCOC chr4 140257286 140385726 +731429 SCOC-AS1 chr4 140283724 140373403 +731457 CLGN chr4 140388453 140427661 +731549 MGAT4D chr4 140442262 140498377 +731680 ELMOD2 chr4 140524168 140553770 +731763 UCP1 chr4 140559431 140568961 +731781 AC108019.2 chr4 140577845 140579657 +731785 TBC1D9 chr4 140620782 140756385 +731839 AC096733.1 chr4 140712168 140716081 +731843 AC096733.2 chr4 140756528 140757921 +731846 RNF150 chr4 140859807 141212877 +731949 ZNF330 chr4 141220887 141234697 +732082 AC107220.1 chr4 141240739 141278789 +732087 LINC02432 chr4 141302910 141357096 +732125 AC097504.2 chr4 141430831 141431284 +732128 LINC02276 chr4 141569931 141576077 +732132 IL15 chr4 141636583 141733987 +732260 INPP4B chr4 142023160 142847432 +732824 AC139720.2 chr4 142514446 142518983 +732828 AC139720.1 chr4 142566019 142660950 +732833 AC104596.1 chr4 142933195 143184861 +732844 USP38 chr4 143184917 143223874 +732918 AC097658.2 chr4 143286293 143329858 +732922 GAB1 chr4 143336762 143474568 +733076 AC097658.3 chr4 143351515 143355794 +733080 SMARCA5-AS1 chr4 143513472 143514635 +733084 SMARCA5 chr4 143513702 143557486 +733144 AC107223.1 chr4 143559457 144343750 +733311 FREM3 chr4 143577302 143700675 +733336 GYPE chr4 143870864 143905563 +733376 GYPB chr4 143996104 144019345 +733553 AC093890.2 chr4 144010237 144012598 +733557 GYPA chr4 144109303 144140751 +733836 AC098588.3 chr4 144111039 144870953 +733860 AC106871.1 chr4 144505900 144509001 +733863 HHIP-AS1 chr4 144642922 144661357 +733879 HHIP chr4 144646156 144745271 +733954 ANAPC10 chr4 144831908 145098541 +734147 AC109811.1 chr4 144851572 144874787 +734162 ABCE1 chr4 145098288 145129524 +734312 OTUD4 chr4 145110838 145180589 +734524 LINC02266 chr4 145335263 145343559 +734564 AC093796.1 chr4 145444899 145469638 +734569 SMAD1 chr4 145481194 145559176 +734697 SMAD1-AS2 chr4 145497073 145502971 +734701 SMAD1-AS1 chr4 145514615 145517118 +734705 MMAA chr4 145599042 145660033 +734848 AC093864.1 chr4 145642336 145650624 +734852 C4orf51 chr4 145680115 145771032 +734876 ZNF827 chr4 145757627 145938823 +735282 AC104791.1 chr4 145833118 145839580 +735287 AC108206.1 chr4 146052604 146056762 +735290 LINC01095 chr4 146077717 146121913 +735336 LSM6 chr4 146175703 146200000 +735415 REELD1 chr4 146214515 146230878 +735460 AC097372.1 chr4 146241806 146243669 +735464 SLC10A7 chr4 146253975 146521964 +735604 POU4F2 chr4 146638893 146642474 +735614 TTC29 chr4 146706638 146945882 +735809 AC092435.2 chr4 146934001 146945471 +735814 AC092435.1 chr4 146957438 146975457 +735823 AC092435.3 chr4 147005492 147009145 +735826 AC097450.1 chr4 147060613 147159068 +735841 EDNRA chr4 147480917 147544954 +735981 LINC02507 chr4 147567606 147594589 +736008 AC093835.1 chr4 147609552 147617245 +736012 TMEM184C chr4 147617386 147672044 +736076 PRMT9 chr4 147637785 147684163 +736143 ARHGAP10 chr4 147732063 148072776 +736266 NR3C2 chr4 148078762 148444698 +736409 AC069272.1 chr4 148146471 148208880 +736414 AC002460.2 chr4 148445703 149024624 +736423 AC108935.1 chr4 148693032 148694323 +736427 AC002460.1 chr4 148940941 148942415 +736438 AC108156.1 chr4 149027445 149062522 +736444 LINC02430 chr4 149147793 149154175 +736455 LINC02355 chr4 149154279 149278123 +736474 IQCM chr4 149351903 149896233 +736600 AC108168.1 chr4 149377257 149380107 +736604 AC093893.1 chr4 149666057 149711149 +736609 AC105343.1 chr4 149956208 149958572 +736613 AC105343.2 chr4 150047004 150051290 +736617 DCLK2 chr4 150078445 150257438 +736826 LRBA chr4 150264435 151015727 +737735 AC110813.1 chr4 150579089 150581545 +737739 MAB21L2 chr4 150582151 150584693 +737747 RPS3A chr4 151099624 151104642 +737940 SH3D19 chr4 151102751 151325632 +738301 AC095055.1 chr4 151139991 151141103 +738304 PRSS48 chr4 151277171 151291453 +738331 AC104819.3 chr4 151333775 151353224 +738335 FAM160A1-DT chr4 151407551 151408835 +738339 FAM160A1 chr4 151409176 151670503 +738458 GATB chr4 151670504 151761007 +738661 AC092611.1 chr4 151674483 151677893 +738666 AC107074.1 chr4 151798917 151833097 +738701 AC112242.2 chr4 151883711 151886239 +738705 AC112242.1 chr4 151887543 151891263 +738710 AC097375.2 chr4 151904932 151928710 +738719 AC097375.1 chr4 151919468 151943933 +738725 AC097375.4 chr4 151949338 151991925 +738729 AC097375.3 chr4 151955991 151969381 +738745 AC097375.5 chr4 151988526 152045275 +738764 LINC02273 chr4 152090459 152104720 +738780 AC079340.3 chr4 152113857 152116497 +738784 AC079340.1 chr4 152146385 152178573 +738791 AC079340.2 chr4 152206987 152225870 +738802 AC080078.1 chr4 152308283 152309983 +738806 AC080078.2 chr4 152317902 152318364 +738809 FBXW7 chr4 152320544 152536092 +739033 FBXW7-AS1 chr4 152337655 152338098 +739037 AC023424.3 chr4 152448275 152513788 +739044 MIR4453HG chr4 152536264 152539263 +739047 TMEM154 chr4 152618628 152680012 +739096 AC106882.1 chr4 152666368 152670107 +739100 TIGD4 chr4 152769354 152779730 +739110 ARFIP1 chr4 152779937 152918463 +739244 AC093599.2 chr4 152934516 152936761 +739248 FHDC1 chr4 152936352 152979696 +739305 AC093599.1 chr4 153034211 153091563 +739316 TRIM2 chr4 153152342 153339317 +739464 MND1 chr4 153344649 153415118 +739564 TMEM131L chr4 153466346 153636711 +739809 AC106865.2 chr4 153633692 153655689 +739813 TLR2 chr4 153684070 153705702 +739884 RNF175 chr4 153710125 153760235 +739991 AC020703.1 chr4 153720327 153727722 +739998 SFRP2 chr4 153780591 153789083 +740010 AC079298.3 chr4 153948718 154300500 +740031 DCHS2 chr4 154231742 154491799 +740144 AC079298.1 chr4 154235980 154237598 +740147 AC079298.2 chr4 154261735 154262193 +740150 PLRG1 chr4 154535005 154550400 +740331 FGB chr4 154562956 154571086 +740405 FGA chr4 154583128 154590745 +740455 FGG chr4 154604134 154612967 +740616 LRAT chr4 154626945 154753120 +740672 AC009567.1 chr4 154754756 154781873 +740678 RBM46 chr4 154781213 154828813 +740735 AC097467.3 chr4 155173716 155381694 +740966 AC104407.1 chr4 155206529 155209027 +740975 NPY2R chr4 155208636 155217078 +740994 AC097467.1 chr4 155286162 155287136 +740998 MAP9 chr4 155342658 155376970 +741186 AC097526.1 chr4 155442650 155448610 +741194 AC107208.1 chr4 155496110 155520353 +741207 GUCY1A1 chr4 155666711 155732349 +741480 AC104083.1 chr4 155734448 155737062 +741483 GUCY1B1 chr4 155758992 155807774 +741754 ASIC5 chr4 155829729 155866277 +741780 TDO2 chr4 155854738 155920406 +741878 CTSO chr4 155924118 155953866 +741900 AC096736.3 chr4 156585979 156590039 +741904 LINC02272 chr4 156634494 156642454 +741912 AC096736.2 chr4 156642580 156643569 +741916 AC096736.1 chr4 156686664 156692636 +741920 PDGFC chr4 156760454 156971799 +742015 AC092608.1 chr4 156841359 156842236 +742019 GLRB chr4 157076125 157172090 +742148 GRIA2 chr4 157204182 157366075 +742458 AC093817.2 chr4 157568731 157824256 +742463 LINC02433 chr4 157572490 157576154 +742475 AC093817.1 chr4 157637687 157667044 +742479 AC017037.5 chr4 157879902 157962924 +742484 AC084740.1 chr4 157929071 158094763 +742491 GASK1B chr4 158124474 158173318 +742588 FAM198B-AS1 chr4 158170752 158202877 +742615 AC098679.6 chr4 158178168 158182806 +742621 AC098679.1 chr4 158199105 158200442 +742625 TMEM144 chr4 158201604 158255416 +742858 AC098679.5 chr4 158262995 158270211 +742862 RXFP1 chr4 158315311 158653372 +743232 AC121161.2 chr4 158490766 158509908 +743237 C4orf46 chr4 158666675 158672255 +743259 ETFDH chr4 158672125 158709623 +743361 PPID chr4 158709127 158723396 +743411 FNIP2 chr4 158769026 158908050 +743510 C4orf45 chr4 158893134 159038760 +743535 RAPGEF2 chr4 159103013 159360174 +743821 AC074344.2 chr4 159398533 159401246 +743825 LINC02233 chr4 159665833 159777828 +743830 LINC02477 chr4 160539254 160586817 +743837 AC104793.1 chr4 161378953 161388417 +743841 FSTL5 chr4 161383897 162164004 +743960 AC023136.1 chr4 162022733 162047567 +743968 AC021134.1 chr4 162705359 162907428 +743988 AC021134.2 chr4 162806370 162844690 +743994 AC022272.1 chr4 163108785 163119965 +744002 NAF1 chr4 163110073 163166890 +744072 NPY1R chr4 163323962 163344832 +744142 NPY5R chr4 163343892 163351934 +744176 TKTL2 chr4 163471095 163473754 +744184 TMA16 chr4 163494442 163520539 +744291 MARCH1 chr4 163524298 164384050 +744437 AC093788.1 chr4 163529771 163530697 +744440 SMIM31 chr4 164754064 164803795 +744465 APELA chr4 164877178 164898965 +744507 AC106872.12 chr4 164920894 164931047 +744511 TRIM61 chr4 164954446 164977668 +744538 FAM218A chr4 164956948 164959122 +744548 AC106872.9 chr4 165007086 165007959 +744552 TRIM60 chr4 165016458 165041749 +744604 TRIM75P chr4 165053864 165060554 +744614 TMEM192 chr4 165070608 165208549 +744666 KLHL2 chr4 165207561 165323156 +744910 GK3P chr4 165277812 165279679 +744918 MSMO1 chr4 165327667 165343164 +744986 CPE chr4 165361194 165498547 +745052 AC080079.2 chr4 165647636 165757667 +745061 LINC01179 chr4 165684639 165762778 +745069 TLL1 chr4 165873237 166104457 +745264 AC097487.1 chr4 166388701 166526119 +745270 SPOCK3 chr4 166733384 167234796 +745831 AC079349.1 chr4 167306910 167308789 +745836 AC116634.1 chr4 167946674 168113331 +745842 ANXA10 chr4 168092537 168187736 +745884 AC068989.1 chr4 168170097 168194861 +745888 DDX60 chr4 168216294 168318804 +746018 DDX60L chr4 168356735 168537786 +746388 PALLD chr4 168497052 168928457 +746699 AC079858.1 chr4 168647896 168648587 +746704 AC080188.1 chr4 168828919 168832937 +746708 CBR4 chr4 168863770 169010275 +746796 AC021151.1 chr4 169010430 169010939 +746800 SH3RF1 chr4 169094259 169270956 +746873 AC096741.1 chr4 169201794 169220349 +746880 NEK1 chr4 169392857 169612629 +747309 AC084724.1 chr4 169572328 169576451 +747313 CLCN3 chr4 169612633 169723673 +747534 HPF1 chr4 169729470 169757944 +747563 AC079768.3 chr4 169849053 169867346 +747567 AC079768.4 chr4 169912705 169919663 +747571 LINC02275 chr4 169917761 169975904 +747592 AC079768.2 chr4 169921417 169923442 +747596 AC084866.2 chr4 169945981 169963337 +747604 AC084866.1 chr4 169981744 169994488 +747609 MFAP3L chr4 169986597 170033031 +747706 AADAT chr4 170060222 170091699 +747890 LINC01612 chr4 170226535 170283723 +747919 LINC02512 chr4 170343089 170372311 +747924 LINC02382 chr4 170742469 170743718 +747928 AC034159.2 chr4 170979831 170994656 +747932 LINC02431 chr4 171040564 171059163 +747981 LINC02504 chr4 171289475 171298267 +747985 AC074254.2 chr4 171494684 171525072 +747990 LINC02174 chr4 171536034 171638763 +748003 AC074254.1 chr4 171553000 171564267 +748008 GALNTL6 chr4 171812254 173041559 +748111 AC105285.1 chr4 173094868 173169652 +748158 GALNT7 chr4 173168811 173323967 +748252 AC097534.1 chr4 173322206 173329694 +748257 HMGB2 chr4 173331376 173334432 +748316 AC097534.2 chr4 173349543 173370721 +748339 SAP30 chr4 173369969 173377532 +748357 SCRG1 chr4 173384701 173406380 +748392 AC093849.4 chr4 173397770 173409559 +748397 AC093849.3 chr4 173445033 173446596 +748401 AC093849.1 chr4 173467833 173470041 +748404 AC093849.2 chr4 173509633 173511764 +748408 HAND2 chr4 173524969 173530229 +748443 HAND2-AS1 chr4 173527270 173659696 +748678 LINC02269 chr4 173699082 174001488 +748801 AC106895.1 chr4 173877471 173913252 +748811 AC106895.2 chr4 173924207 173991024 +748836 LINC02268 chr4 174091766 174220398 +748870 AC012055.1 chr4 174135055 174154637 +748874 AC012055.2 chr4 174164441 174168913 +748879 FBXO8 chr4 174236658 174284264 +748964 CEP44 chr4 174283730 174333380 +749161 AC116616.1 chr4 174354854 174376445 +749166 HPGD chr4 174490175 174523154 +749361 AC096751.2 chr4 174522617 174541047 +749371 GLRA3 chr4 174636920 174829247 +749426 ADAM29 chr4 174829668 174978180 +749561 AC105914.2 chr4 174977571 174979381 +749566 AC022325.2 chr4 175038080 175236669 +749570 AC095050.1 chr4 175346358 175403110 +749575 AC131094.1 chr4 175457726 175473197 +749585 GPM6A chr4 175632934 176002664 +749841 AC097537.1 chr4 175790307 175812189 +749851 WDR17 chr4 176065834 176182818 +750111 SPATA4 chr4 176184579 176195585 +750153 ASB5 chr4 176213673 176277571 +750228 AC019163.1 chr4 176308268 176320458 +750233 SPCS3 chr4 176319966 176332245 +750262 AC093801.1 chr4 176669621 176706145 +750270 VEGFC chr4 176683538 176792922 +750295 AC097518.2 chr4 176844493 177301253 +750314 AC092673.1 chr4 176866614 176875457 +750319 LINC02509 chr4 176875688 176908031 +750335 AC097518.1 chr4 177242539 177248773 +750341 NEIL3 chr4 177309874 177362936 +750380 AC027627.1 chr4 177343004 177357032 +750384 AGA chr4 177430774 177442437 +750445 AC078881.1 chr4 177442519 177681381 +750466 AC103879.1 chr4 177686673 177691068 +750470 LINC01098 chr4 177728757 178028971 +750485 LINC01099 chr4 177729638 177907936 +750498 AC020551.1 chr4 179389134 179465305 +750503 AC108169.1 chr4 179923773 180059792 +750512 AC096747.1 chr4 180095527 180117163 +750517 AC104803.1 chr4 180731164 180759038 +750523 LINC00290 chr4 181064089 181159149 +750528 LINC02500 chr4 181260442 181265145 +750535 AC093840.2 chr4 181590255 181591969 +750539 AC084741.1 chr4 181686182 181700142 +750543 TEMN3-AS1 chr4 181820019 181829973 +750548 TENM3-AS1 chr4 181874438 182145249 +750594 TENM3 chr4 182143987 182803024 +750696 AC108142.1 chr4 182144852 182190382 +750700 AC079226.2 chr4 182697902 182708042 +750704 AC079226.1 chr4 182772565 182773931 +750708 AC114798.1 chr4 182828100 182830597 +750712 AC079766.1 chr4 182881777 182882203 +750715 DCTD chr4 182890060 182917936 +750954 AC019193.4 chr4 183017426 183036100 +750959 AC019193.3 chr4 183075480 183076033 +750962 AC019193.2 chr4 183094423 183095056 +750965 WWC2-AS2 chr4 183097017 183099199 +750968 WWC2 chr4 183099257 183320777 +751294 WWC2-AS1 chr4 183233628 183240634 +751298 CLDN22 chr4 183318194 183320774 +751306 CLDN24 chr4 183321764 183322426 +751313 CDKN2AIP chr4 183444635 183449064 +751352 AC107214.1 chr4 183494884 183504494 +751361 ING2 chr4 183505058 183512429 +751378 AC107214.2 chr4 183516894 183517527 +751381 RWDD4 chr4 183639635 183659203 +751505 TRAPPC11 chr4 183659267 183713594 +751757 AC108477.2 chr4 183725830 183732570 +751761 AC108477.1 chr4 183762115 183765721 +751765 STOX2 chr4 183797692 184023526 +751810 AC074194.1 chr4 183987669 183996680 +751817 ENPP6 chr4 184088706 184221230 +751861 AC107222.2 chr4 184100482 184106038 +751867 LINC02363 chr4 184334292 184353977 +751883 LINC02362 chr4 184365180 184382416 +751972 IRF2 chr4 184387729 184474550 +752090 AC099343.2 chr4 184471924 184472609 +752093 AC099343.3 chr4 184474802 184477304 +752096 AC099343.4 chr4 184484141 184490293 +752101 LINC02427 chr4 184503271 184537626 +752110 LINC02365 chr4 184584093 184625030 +752121 CASP3 chr4 184627696 184649509 +752232 PRIMPOL chr4 184649667 184694963 +752448 CENPU chr4 184694085 184734130 +752540 ACSL1 chr4 184755595 184826818 +752980 AC084871.1 chr4 184813619 184821300 +752985 AC084871.3 chr4 184826607 184850920 +753000 MIR3945HG chr4 184844554 184855751 +753019 LINC01093 chr4 184892858 184899553 +753117 LINC02437 chr4 184988997 185005186 +753121 HELT chr4 185018841 185020804 +753164 LINC02436 chr4 185051081 185115500 +753580 AC093824.2 chr4 185118984 185127478 +753584 SLC25A4 chr4 185143266 185150382 +753611 CFAP97 chr4 185159665 185209504 +753670 SNX25 chr4 185204237 185370185 +753892 LRP2BP chr4 185363879 185395899 +753969 AC112722.1 chr4 185370725 185390928 +753974 ANKRD37 chr4 185396021 185400628 +754017 UFSP2 chr4 185399537 185425979 +754178 C4orf47 chr4 185426249 185449826 +754241 CCDC110 chr4 185445182 185471752 +754400 AC106897.1 chr4 185471461 185507055 +754419 PDLIM3 chr4 185500660 185535612 +754585 SORBS2 chr4 185585444 185956652 +755645 AC093797.1 chr4 185587909 185594003 +755651 AC108472.1 chr4 185665885 185675417 +755655 AC096659.1 chr4 185918140 185919460 +755659 TLR3 chr4 186069152 186088069 +755705 FAM149A chr4 186104419 186172667 +756020 CYP4V2 chr4 186191567 186213463 +756067 KLKB1 chr4 186208979 186258471 +756222 F11 chr4 186265945 186288806 +756336 F11-AS1 chr4 186286094 186500997 +756361 AC109517.1 chr4 186326302 186336662 +756365 MTNR1A chr4 186533655 186555567 +756375 FAT1 chr4 186587794 186726722 +756565 AC107050.1 chr4 186701579 186704086 +756569 AC108865.1 chr4 186890969 186892366 +756573 AC108865.2 chr4 186892552 186892983 +756576 AC110772.1 chr4 186979490 187027451 +756582 AC110772.2 chr4 187005944 187060930 +756608 AC108046.1 chr4 187198218 187201894 +756612 LINC02374 chr4 187201986 187209346 +756620 AC097652.1 chr4 187304083 187309682 +756626 LINC02514 chr4 187370648 187371921 +756631 LINC02515 chr4 187408232 187415748 +756636 AC093763.1 chr4 187516153 187517208 +756640 LINC02492 chr4 187532873 187672755 +756776 AC097521.1 chr4 187613708 187712329 +756833 AC108073.3 chr4 187942164 187963345 +756838 ZFP42 chr4 187995771 188005046 +756870 TRIML2 chr4 188091273 188109603 +756944 TRIML1 chr4 188139441 188147743 +756971 AC138781.1 chr4 188140822 188143379 +756975 LINC02434 chr4 188159705 188161157 +757014 LINC01060 chr4 188400736 188681051 +757134 AC093909.2 chr4 188757678 188779343 +757139 LINC02508 chr4 188776657 188785511 +757144 AC093909.4 chr4 188777672 188818522 +757154 AC122138.1 chr4 188990715 189002075 +757158 AC107391.1 chr4 189193100 189204877 +757162 AC105924.1 chr4 189288677 189291336 +757166 LINC01262 chr4 189659605 189661486 +757171 AF250324.1 chr4 189703881 189704490 +757174 FRG1-DT chr4 189764391 189940733 +757208 LINC01596 chr4 189881515 189884868 +757212 FRG1 chr4 189940870 189963202 +757310 FRG2 chr4 190024351 190027257 +757337 DBET chr4 190064502 190067864 +757340 DUX4 chr4 190173774 190185942 +757384 PLEKHG4B chr5 92151 189972 +757501 LRRC14B chr5 191495 196334 +757511 AC021087.4 chr5 195778 196341 +757514 CCDC127 chr5 196868 218153 +757533 SDHA chr5 218241 257082 +757785 AC021087.1 chr5 269858 271516 +757789 PDCD6 chr5 271621 314974 +757937 AHRR chr5 321759 435110 +758033 EXOC3-AS1 chr5 441498 443160 +758038 EXOC3 chr5 443175 471937 +758183 AC010442.1 chr5 466124 473098 +758196 SLC9A3 chr5 470456 524449 +758316 SLC9A3-AS1 chr5 473236 480884 +758374 AC106772.2 chr5 524109 527448 +758382 AC106772.1 chr5 602620 612210 +758387 CEP72 chr5 612340 667168 +758431 TPPP chr5 659862 693352 +758445 AC026740.1 chr5 675826 676616 +758448 ZDHHC11B chr5 710355 784729 +758533 AC026740.3 chr5 716808 766919 +758569 ZDHHC11 chr5 795606 850986 +758709 BRD9 chr5 850291 892801 +759066 TRIP13 chr5 892884 919357 +759141 AC122719.3 chr5 904319 912587 +759146 AC122719.1 chr5 946315 956520 +759150 AC122719.2 chr5 979365 981300 +759154 AC116351.1 chr5 987180 997308 +759158 AC116351.2 chr5 1005039 1006623 +759161 NKD2 chr5 1008802 1038943 +759227 SLC12A7 chr5 1050384 1112063 +759368 AC114291.1 chr5 1173141 1178605 +759382 SLC6A19 chr5 1201595 1225111 +759439 SLC6A18 chr5 1225381 1246189 +759473 AC114291.2 chr5 1252006 1255976 +759478 TERT chr5 1253147 1295047 +759640 CLPTM1L chr5 1317752 1345099 +759840 AC026748.3 chr5 1345197 1350786 +759844 LINC01511 chr5 1353896 1380107 +759867 SLC6A3 chr5 1392794 1445440 +759910 LPCAT1 chr5 1456480 1523962 +760006 AC091849.2 chr5 1544107 1551710 +760012 AC026412.3 chr5 1594626 1611467 +760017 AC112176.1 chr5 1725149 1728172 +760020 MRPL36 chr5 1798385 1801366 +760064 NDUFS6 chr5 1801400 1816605 +760092 AC025183.3 chr5 1850950 1851497 +760096 LINC02116 chr5 1855970 1856568 +760100 IRX4 chr5 1877413 1887236 +760221 AC025183.1 chr5 1883966 1884649 +760225 AC025183.2 chr5 1887332 1900493 +760231 AC126768.3 chr5 1931058 1933985 +760235 AC124852.1 chr5 1931064 2119926 +760305 AC126768.1 chr5 1963346 1967251 +760310 AC126768.2 chr5 1968094 1969013 +760314 LSINCT5 chr5 2712591 2715237 +760317 AC091891.1 chr5 2736662 2737759 +760321 IRX2 chr5 2745845 2751677 +760350 C5orf38 chr5 2752131 2755397 +760413 AC094105.1 chr5 2831021 2835139 +760417 AC094105.2 chr5 2921496 2967955 +760435 AC091832.1 chr5 3177835 3181487 +760443 LINC01019 chr5 3357264 3536094 +760456 LINC02162 chr5 3452816 3461660 +760461 LINC01017 chr5 3496229 3504004 +760466 IRX1 chr5 3595832 3601403 +760480 AC016595.1 chr5 3596211 3600188 +760484 AC025773.1 chr5 4012708 4013649 +760488 AC025187.1 chr5 4033713 4041764 +760493 LINC02063 chr5 4135638 4147429 +760502 AC106799.3 chr5 4436850 4440259 +760506 AC106799.2 chr5 4451930 4866311 +760534 AC106799.1 chr5 4512262 4516776 +760538 AC010634.1 chr5 4640731 4648254 +760542 LINC02114 chr5 4773481 4774865 +760546 AC026719.1 chr5 4775476 4805769 +760550 AC026415.1 chr5 4866521 4874759 +760555 AC010451.3 chr5 4967764 4970425 +760560 AC010451.1 chr5 4974690 5034267 +760570 LINC01020 chr5 4987789 5070314 +760650 AC010451.2 chr5 5046796 5049497 +760657 LINC02121 chr5 5069192 5078311 +760661 AC022424.1 chr5 5132101 5140119 +760681 ADAMTS16 chr5 5140330 5320304 +760784 AC022424.2 chr5 5142138 5176214 +760788 AC091978.1 chr5 5390096 5422116 +760793 ICE1 chr5 5420664 5490220 +760866 AC026736.1 chr5 5688805 5694742 +760871 AC010266.2 chr5 6019029 6022283 +760874 AC010266.1 chr5 6030035 6030841 +760878 LINC02145 chr5 6310441 6339884 +760885 MED10 chr5 6371874 6378571 +760905 AC093307.1 chr5 6378674 6411690 +760911 UBE2QL1 chr5 6448859 6496723 +760921 LINC01018 chr5 6582136 6600288 +761021 NSUN2 chr5 6599239 6633291 +761192 SRD5A1 chr5 6633427 6674386 +761242 LINC02102 chr5 6686325 6707711 +761258 TENT4A chr5 6713432 6757044 +761346 LINC02236 chr5 6765891 6833120 +761372 AC122710.2 chr5 6779458 6779998 +761375 LINC02196 chr5 6839460 7219291 +761397 AC122710.1 chr5 6868554 6888087 +761407 AC025756.1 chr5 7065091 7069351 +761411 AC091889.1 chr5 7226156 7229357 +761415 AC091951.4 chr5 7272792 7276923 +761420 AC027343.3 chr5 7344579 7345921 +761424 LINC02123 chr5 7346986 7348671 +761431 AC027343.1 chr5 7362979 7364531 +761436 AC027343.2 chr5 7367929 7373074 +761441 LINC02142 chr5 7373115 7391907 +761454 ADCY2 chr5 7396138 7830081 +761563 AC093305.1 chr5 7707802 7749766 +761568 C5orf49 chr5 7830378 7851151 +761591 MTRR chr5 7851186 7906025 +761903 FASTKD3 chr5 7859159 7869037 +761989 AC025174.1 chr5 7924292 7925398 +761994 AC116361.1 chr5 8012377 8014804 +761998 AC091912.3 chr5 8207019 8366437 +762002 LINC02226 chr5 8333481 8457558 +762010 AC091965.1 chr5 8387638 8457564 +762021 AC091965.4 chr5 8444949 8445535 +762024 MIR4458HG chr5 8450701 8486930 +762063 AC091953.1 chr5 8525144 8561682 +762084 AC091932.1 chr5 8785042 8785468 +762087 LINC02199 chr5 8839700 8898052 +762108 AC021088.1 chr5 9001774 9045940 +762116 SEMA5A chr5 9035033 9546075 +762254 AC091906.1 chr5 9363275 9422481 +762260 SEMA5A-AS1 chr5 9511333 9518086 +762265 AC027335.1 chr5 9519853 9523178 +762269 SNHG18 chr5 9546200 9550609 +762280 AC026787.1 chr5 9621377 9658458 +762285 TAS2R1 chr5 9628997 9712378 +762309 LINC02112 chr5 9641305 9903852 +762349 AC091838.1 chr5 9789295 9812664 +762353 LINC02221 chr5 9854371 9899970 +762375 AC034229.1 chr5 10137138 10138365 +762379 AC034229.2 chr5 10195121 10197628 +762382 AC034229.3 chr5 10195187 10197622 +762385 AC034229.4 chr5 10203600 10204040 +762388 ATPSCKMT chr5 10225507 10249897 +762474 AC012640.1 chr5 10248325 10249915 +762478 CCT5 chr5 10249929 10266389 +762680 AC012640.4 chr5 10264597 10267146 +762683 AC012640.3 chr5 10269489 10269918 +762686 CMBL chr5 10275875 10307902 +762729 AC012640.2 chr5 10352701 10353601 +762732 MARCH6 chr5 10353695 10440388 +763022 ROPN1L-AS1 chr5 10441290 10441792 +763026 ROPN1L chr5 10441524 10472029 +763076 LINC01513 chr5 10479371 10482309 +763080 AC092336.1 chr5 10493291 10494094 +763084 LINC02212 chr5 10493291 10502728 +763095 LINC02213 chr5 10504996 10522084 +763104 ANKRD33B chr5 10564070 10657816 +763133 ANKRD33B-AS1 chr5 10627260 10628225 +763137 DAP chr5 10679230 10761272 +763178 AC012629.2 chr5 10761065 10770294 +763186 AC012629.1 chr5 10775058 10777062 +763190 CTNND2 chr5 10971836 11904446 +763549 AC106771.1 chr5 12553890 12574637 +763554 LINC01194 chr5 12574830 12804363 +763575 LINC02220 chr5 12914068 13032886 +763580 AC016553.1 chr5 13144000 13190677 +763589 DNAH5 chr5 13690331 13944543 +763776 AC016576.1 chr5 13860303 13901036 +763785 TRIO chr5 14143342 14532128 +764387 AC016549.1 chr5 14356886 14359285 +764391 OTULINL chr5 14581792 14616180 +764421 AC010491.1 chr5 14661808 14664604 +764431 OTULIN chr5 14664664 14699850 +764490 ANKH chr5 14704800 14871778 +764560 AC010491.2 chr5 14728587 14734258 +764567 AC016575.1 chr5 14872332 14872713 +764570 AC016575.2 chr5 14970909 14992961 +764575 LINC02149 chr5 15112120 15266541 +764589 AC114964.2 chr5 15425758 15496353 +764593 FBXL7 chr5 15500180 15939795 +764628 AC010638.1 chr5 15602189 15619109 +764642 MARCH11 chr5 16067139 16180762 +764667 AC016650.1 chr5 16129178 16141602 +764671 AC092335.1 chr5 16180238 16185585 +764675 LINC02150 chr5 16373361 16440081 +764685 AC020980.1 chr5 16428536 16432436 +764690 ZNF622 chr5 16451519 16465800 +764708 RETREG1 chr5 16473038 16617058 +764776 AC024588.1 chr5 16615926 16681905 +764786 AC022113.1 chr5 16617225 16621276 +764792 MYO10 chr5 16661907 16936288 +765173 BASP1 chr5 17065598 17276843 +765203 BASP1-AS1 chr5 17089296 17217047 +765235 AC026790.1 chr5 17107360 17107789 +765238 AC026785.2 chr5 17353910 17354899 +765242 AC026785.3 chr5 17367588 17375653 +765250 LINC02111 chr5 17378906 17387310 +765255 LINC02217 chr5 17403889 17443619 +765316 LINC02218 chr5 17444010 17486829 +765333 AC106774.4 chr5 17491325 17491769 +765341 TAF11L2 chr5 17498231 17498827 +765348 TAF11L3 chr5 17518367 17518963 +765355 TAF11L4 chr5 17521801 17522397 +765362 TAF11L5 chr5 17525235 17525831 +765369 TAF11L6 chr5 17528669 17529265 +765376 TAF11L7 chr5 17585162 17585758 +765383 TAF11L8 chr5 17590364 17590960 +765390 TAF11L9 chr5 17593798 17594394 +765397 TAF11L10 chr5 17597232 17597828 +765404 TAF11L11 chr5 17604177 17605377 +765412 TAF11L12 chr5 17610496 17611583 +765420 TAF11L13 chr5 17632088 17632684 +765427 TAF11L14 chr5 17634460 17635053 +765434 H3.Y chr5 17654870 17655847 +765442 LINC02223 chr5 17684584 17955857 +765559 LINC02100 chr5 18704433 18746173 +765563 AC106744.1 chr5 18965861 19142346 +765567 AC106744.2 chr5 19035197 19038799 +765575 CDH18 chr5 19471296 20575873 +765798 CDH18-AS1 chr5 20305565 20347972 +765809 LINC02146 chr5 20606710 20616441 +765830 LINC02241 chr5 20611806 20937800 +766446 AC140168.1 chr5 20967211 21032845 +766461 AC093274.1 chr5 21323873 21341375 +766470 AC091946.2 chr5 21569755 21570045 +766473 AC091946.1 chr5 21616262 21779522 +766479 CDH12 chr5 21750673 22853344 +766613 AC139497.1 chr5 22139247 22141468 +766618 AC138854.1 chr5 22212476 22213761 +766622 AC091938.1 chr5 22754227 22766824 +766647 AC010445.1 chr5 23013048 23014527 +766651 PRDM9 chr5 23443586 23528597 +766715 C5orf17 chr5 23951348 24178263 +766727 AC114930.1 chr5 24135160 24271863 +766741 AC010387.1 chr5 24352309 24353443 +766745 AC010387.2 chr5 24478516 24480057 +766749 CDH10 chr5 24487100 24644978 +766816 AC091885.2 chr5 24554018 24613222 +766821 AC091893.2 chr5 24729379 24738195 +766825 AC106821.2 chr5 24772144 24850971 +766830 LINC02239 chr5 24835280 24840583 +766835 AC106821.1 chr5 24881943 24885461 +766839 LINC02228 chr5 25087450 25190956 +766872 LINC02211 chr5 25187800 25324386 +766901 AC099499.2 chr5 25188059 25188778 +766904 AC099499.1 chr5 25218973 25298612 +766911 AC106754.1 chr5 25319834 25321346 +766914 AC022140.1 chr5 25404733 25445925 +766927 AC113370.1 chr5 25963839 25990687 +766934 AC025475.1 chr5 26382519 26399819 +766941 AC025475.2 chr5 26473505 26484711 +766947 AC113347.4 chr5 26711551 26749997 +766952 CDH9 chr5 26880597 27121150 +767015 PURPL chr5 27217714 27496994 +767224 AC113355.1 chr5 27406530 27436421 +767231 LINC02103 chr5 28285964 28287807 +767242 AC008825.1 chr5 28548135 28809291 +767264 AC109472.1 chr5 28614613 28654531 +767269 LINC02109 chr5 28809331 29217115 +767357 AC112172.2 chr5 29239922 29265940 +767362 LINC02064 chr5 29304305 29396095 +767540 AC099517.1 chr5 30545177 30693984 +767545 AC026433.1 chr5 30733557 30743704 +767549 AC113386.1 chr5 31093977 31267610 +767556 CDH6 chr5 31193686 31329146 +767625 DROSHA chr5 31400497 31532196 +768027 C5orf22 chr5 31532287 31555053 +768154 PDZD2 chr5 31639131 32110932 +768273 AC022447.2 chr5 31657218 31665067 +768278 AC022447.5 chr5 31738269 31738660 +768281 AC022447.3 chr5 31741833 31742327 +768284 AC022447.1 chr5 31743988 31744451 +768287 AC022447.7 chr5 31747644 31748078 +768290 AC022447.6 chr5 31754219 31754656 +768293 AC025178.1 chr5 32103445 32121941 +768300 GOLPH3 chr5 32124716 32174319 +768331 AC025181.2 chr5 32174471 32175272 +768334 MTMR12 chr5 32226994 32312987 +768479 ZFR chr5 32354350 32444740 +768570 SUB1 chr5 32531633 32604079 +768707 LINC02061 chr5 32646564 32651976 +768711 AC008766.1 chr5 32653321 32656022 +768715 NPR3 chr5 32689070 32791724 +768829 AC010343.3 chr5 32888236 33298066 +768850 LINC02120 chr5 32947443 32962467 +768864 AC034223.1 chr5 33008934 33026025 +768874 AC034223.2 chr5 33011322 33017607 +768879 LINC02160 chr5 33229516 33284642 +768896 AC034231.1 chr5 33424025 33440619 +768900 TARS chr5 33440696 33469539 +769252 AC034232.2 chr5 33519616 33522230 +769256 ADAMTS12 chr5 33523535 33892019 +769397 RXFP3 chr5 33936386 33938918 +769405 SLC45A2 chr5 33944623 33984693 +769471 AMACR chr5 33986165 34008104 +769596 C1QTNF3 chr5 34019448 34043832 +769647 AC139792.1 chr5 34158121 34158767 +769650 AC138409.3 chr5 34245273 34288755 +769655 AC025754.2 chr5 34651457 34651888 +769658 RAI14 chr5 34656328 34832612 +770174 AC025754.1 chr5 34656412 34657250 +770178 AC026801.2 chr5 34837549 34839278 +770182 TTC23L chr5 34838833 34899456 +770323 RAD1 chr5 34905260 34918989 +770428 BRIX1 chr5 34915677 34925996 +770480 DNAJC21 chr5 34929559 34958964 +770701 AGXT2 chr5 34998101 35048135 +770812 PRLR chr5 35048756 35230487 +771172 SPEF2 chr5 35617844 35814611 +771630 AC137810.1 chr5 35678484 35827018 +771636 IL7R chr5 35852695 35879603 +771743 CAPSL chr5 35904288 35938779 +771810 AC112204.2 chr5 35938822 35939993 +771814 UGT3A1 chr5 35951006 36001028 +771923 UGT3A2 chr5 36035021 36071358 +771995 LMBRD2 chr5 36098407 36151887 +772046 SKP2 chr5 36151989 36184319 +772224 NADK2 chr5 36192589 36242279 +772440 NADK2-AS1 chr5 36221055 36221902 +772444 RANBP3L chr5 36248434 36302114 +772553 AC114277.1 chr5 36343672 36347157 +772557 SLC1A3 chr5 36606355 36688334 +772712 AC008957.2 chr5 36636019 36649347 +772717 AC008957.1 chr5 36666214 36725195 +772733 AC026741.1 chr5 36861736 36867238 +772737 NIPBL-DT chr5 36864425 36876700 +772746 NIPBL chr5 36876769 37066413 +773077 CPLANE1 chr5 37106228 37249428 +773588 AC025449.2 chr5 37249026 37252617 +773598 NUP155 chr5 37288137 37371106 +773860 WDR70 chr5 37379285 37753435 +773968 GDNF-AS1 chr5 37811589 37953827 +774002 GDNF chr5 37812677 37840041 +774085 LINC02117 chr5 37899363 37920869 +774091 AC008869.1 chr5 37939365 37947955 +774095 LINC02110 chr5 37948491 37951055 +774099 AC034226.1 chr5 37953402 37966964 +774103 LINC02119 chr5 38025568 38184717 +774141 EGFLAM chr5 38258409 38465480 +774398 EGFLAM-AS4 chr5 38282264 38290986 +774404 EGFLAM-AS3 chr5 38345347 38346551 +774408 EGFLAM-AS2 chr5 38399814 38403471 +774428 EGFLAM-AS1 chr5 38425036 38427376 +774432 AC010457.1 chr5 38460925 38468339 +774439 LIFR chr5 38474668 38608354 +774596 LIFR-AS1 chr5 38556765 38671216 +774671 AC010425.1 chr5 38682070 38685126 +774675 OSMR-AS1 chr5 38682581 38845829 +774711 AC091435.2 chr5 38783580 38792754 +774715 OSMR chr5 38845858 38945596 +774807 RICTOR chr5 38937920 39074399 +775113 AC008964.1 chr5 39092658 39103677 +775119 FYB1 chr5 39105252 39274528 +775372 C9 chr5 39284140 39424868 +775419 DAB2 chr5 39371675 39462300 +775639 LINC02104 chr5 39520398 39524726 +775648 LINC00603 chr5 39892138 40053324 +775658 LINC00604 chr5 40240167 40267657 +775666 AC108105.1 chr5 40306824 40312905 +775671 AC093277.1 chr5 40415137 40431491 +775675 AC114977.1 chr5 40463562 40504563 +775683 AC114977.2 chr5 40474908 40490430 +775688 TTC33 chr5 40512333 40755963 +775753 PTGER4 chr5 40679915 40693735 +775778 PRKAA1 chr5 40759379 40798374 +775873 RPL37 chr5 40825262 40835222 +775923 CARD6 chr5 40841308 40860175 +775946 C7 chr5 40909497 40984643 +776011 MROH2B chr5 40998017 41071342 +776260 C6 chr5 41142234 41261438 +776384 PLCXD3 chr5 41306952 41510628 +776409 OXCT1 chr5 41730065 41870425 +776533 AC034222.2 chr5 41868975 41880210 +776538 OXCT1-AS1 chr5 41869927 41872241 +776549 C5orf51 chr5 41904188 41921636 +776594 FBXO4 chr5 41925254 41941743 +776678 AC108099.1 chr5 42188266 42191523 +776681 GHR chr5 42423439 42721878 +776948 CCDC152 chr5 42756818 42802439 +776991 SELENOP chr5 42799880 42887392 +777149 AC008945.1 chr5 42806394 42806997 +777152 AC008945.2 chr5 42813647 42924535 +777169 AC008875.3 chr5 42983636 42993276 +777180 AC008875.2 chr5 42995134 42997480 +777184 AC008875.1 chr5 43006733 43007543 +777187 AC025171.1 chr5 43013060 43067452 +777205 AC025171.3 chr5 43018429 43024678 +777232 AC025171.5 chr5 43033716 43034635 +777235 ANXA2R chr5 43039081 43043170 +777252 AC025171.2 chr5 43041575 43054603 +777285 AC025171.4 chr5 43061395 43062441 +777288 ZNF131 chr5 43065176 43192021 +777527 NIM1K chr5 43192071 43280850 +777567 HMGCS1 chr5 43287470 43313512 +777640 AC114947.2 chr5 43287601 43290839 +777646 CCL28 chr5 43376645 43412391 +777685 TMEM267 chr5 43444252 43483893 +777751 AC114956.3 chr5 43483913 43509356 +777762 C5orf34 chr5 43486709 43515148 +777824 AC114956.2 chr5 43511058 43521811 +777829 AC114956.1 chr5 43515274 43525310 +777834 PAIP1 chr5 43526267 43557758 +778021 NNT-AS1 chr5 43571594 43603230 +778050 NNT chr5 43602692 43707405 +778898 AC104119.1 chr5 43874367 43886628 +778902 FGF10 chr5 44303544 44389706 +778921 FGF10-AS1 chr5 44388732 44413989 +778926 LINC02224 chr5 44495099 44658569 +778940 AC093292.1 chr5 44698431 44700808 +778944 MRPS30-DT chr5 44742420 44808777 +778988 AC093297.1 chr5 44752949 44765744 +778993 MRPS30 chr5 44808947 44820428 +779021 AC093297.2 chr5 44826076 44828592 +779024 AC114954.1 chr5 45035199 45098647 +779028 AC116350.1 chr5 45226286 45228428 +779033 HCN1 chr5 45254948 45696498 +779078 AC122694.1 chr5 45890216 45895970 +779082 EMB chr5 50396192 50443248 +779168 AC112187.3 chr5 50662859 50663266 +779171 PARP8 chr5 50665899 50846519 +779733 AC022441.1 chr5 50858760 50860020 +779737 AC022441.2 chr5 50929484 50934521 +779742 AC008808.2 chr5 50965687 50967008 +779746 LINC02106 chr5 50969217 50970167 +779754 AC008808.1 chr5 50969660 50970187 +779758 AC010478.1 chr5 51372736 51383332 +779767 ISL1 chr5 51383448 51394730 +779807 AC022433.1 chr5 51438792 51665048 +779813 AC091860.2 chr5 51451158 51462089 +779818 LINC02118 chr5 52008031 52080987 +779829 AC022126.1 chr5 52673186 52872925 +779845 PELO chr5 52787916 52804044 +779860 ITGA1 chr5 52787916 52959209 +780035 AC025180.1 chr5 52930606 52990278 +780053 ITGA2 chr5 52989340 53094779 +780436 AC008966.3 chr5 53024924 53035884 +780441 AC008966.2 chr5 53089016 53089468 +780444 MOCS2 chr5 53095679 53110063 +780596 AC008966.1 chr5 53109816 53127673 +780630 AC027329.1 chr5 53297872 53326565 +780637 FST chr5 53480626 53487134 +780698 NDUFS4 chr5 53560633 53683338 +780779 LINC02105 chr5 53776048 53819722 +780821 AC025175.1 chr5 53880293 53881051 +780824 ARL15 chr5 53883942 54310582 +780902 AC025175.2 chr5 53897464 53899370 +780906 LINC01033 chr5 54313564 54415238 +781028 HSPB3 chr5 54455699 54456377 +781036 SNX18 chr5 54517759 54546586 +781063 AC016583.2 chr5 54663327 54737057 +781071 AC112198.3 chr5 54956235 54957846 +781075 ESM1 chr5 54977867 55022671 +781107 AC034238.1 chr5 55021299 55042844 +781203 GZMK chr5 55024256 55034570 +781222 AC034238.3 chr5 55054428 55055140 +781226 AC034238.2 chr5 55063179 55066230 +781230 GZMA chr5 55102646 55110252 +781246 CDC20B chr5 55112995 55173175 +781378 GPX8 chr5 55160167 55167297 +781432 MCIDAS chr5 55219580 55227315 +781478 CCNO chr5 55231152 55233608 +781501 AC026704.1 chr5 55233934 55295201 +781508 DHX29 chr5 55256055 55307694 +781673 MTREX chr5 55307989 55425579 +781839 PLPP1 chr5 55424854 55534969 +781899 SLC38A9 chr5 55625845 55773194 +782335 DDX4 chr5 55738017 55817157 +782728 IL31RA chr5 55851357 55922854 +783075 IL6ST chr5 55935095 55995022 +783421 AC008914.1 chr5 55936143 55941727 +783426 AC008892.1 chr5 55978248 56111329 +783440 AC016596.1 chr5 55995167 56003649 +783444 ANKRD55 chr5 56099680 56233330 +783542 AC034245.1 chr5 56313905 56321397 +783546 LINC01948 chr5 56451627 56481946 +783568 AC008391.1 chr5 56488486 56491499 +783572 C5orf67 chr5 56511567 56606232 +783605 AC022431.1 chr5 56536583 56537826 +783609 AC008940.1 chr5 56770799 56772303 +783613 MAP3K1 chr5 56815549 56896152 +783663 AC008937.2 chr5 56842016 56862164 +783669 AC008937.1 chr5 56900041 56910714 +783673 SETD9 chr5 56909260 56925532 +783762 MIER3 chr5 56919602 56971675 +783969 AC008937.3 chr5 56927874 56929573 +783972 AC016644.1 chr5 56941307 56947152 +783976 GPBP1 chr5 57173948 57264679 +784138 AC025470.2 chr5 57395060 57534504 +784149 ACTBL2 chr5 57480018 57482811 +784157 AC008780.1 chr5 57574027 57619816 +784219 AC008780.2 chr5 57650678 57679842 +784224 AC106822.1 chr5 57751192 57751717 +784227 LINC02225 chr5 57890327 57899162 +784232 LINC02101 chr5 58107631 58122375 +784254 AC008786.1 chr5 58114598 58145996 +784258 PLK2 chr5 58453982 58460139 +784384 GAPT chr5 58491435 58497090 +784432 LINC02108 chr5 58541567 58558243 +784438 RAB3C chr5 58582221 58859394 +784467 AC016642.1 chr5 58741581 58817099 +784476 AC008852.1 chr5 58846885 58863414 +784481 PDE4D chr5 58969038 60522120 +785021 AC092343.1 chr5 59039761 59063503 +785025 AC034234.1 chr5 60021249 60033020 +785034 PART1 chr5 60487713 60548813 +785061 DEPDC1B chr5 60596912 60700190 +785160 AC109133.1 chr5 60699729 60702010 +785164 ELOVL7 chr5 60751791 60844274 +785312 AC104113.1 chr5 60866457 60866935 +785315 ERCC8 chr5 60873831 60945073 +785550 AC022445.1 chr5 60917490 60919573 +785555 NDUFAF2 chr5 60945205 61153026 +785595 SMIM15 chr5 61157704 61162468 +785620 SMIM15-AS1 chr5 61162070 61232040 +785626 LINC02057 chr5 61201304 61304811 +785644 ZSWIM6 chr5 61332258 61546172 +785678 C5orf64 chr5 61610424 61793401 +785833 AC026746.1 chr5 61658474 61698432 +785853 C5orf64-AS1 chr5 61732774 61735715 +785864 AC008877.1 chr5 61878109 61927134 +785873 KIF2A chr5 62306162 62537249 +786117 DIMT1 chr5 62347284 62403939 +786251 IPO11 chr5 62403972 62628582 +786540 LRRC70 chr5 62578819 62581446 +786565 AC008558.1 chr5 63569419 63571617 +786569 AC122707.1 chr5 63957893 63981043 +786573 HTR1A chr5 63960356 63962507 +786588 RNF180 chr5 64165843 64372869 +786633 RGS7BP chr5 64506015 64612319 +786660 SHISAL2B chr5 64690442 64718190 +786706 SREK1IP1 chr5 64718148 64768691 +786742 CWC27 chr5 64768930 65018750 +786821 AC092354.2 chr5 65020038 65020551 +786824 AC092354.1 chr5 65020614 65020989 +786827 ADAMTS6 chr5 65148738 65481920 +787002 AC025176.1 chr5 65486444 65487048 +787006 CENPK chr5 65517766 65563168 +787279 PPWD1 chr5 65563236 65587549 +787505 TRIM23 chr5 65589690 65625975 +787638 SHLD3 chr5 65624765 65630891 +787655 TRAPPC13 chr5 65625004 65666233 +787849 SGTB chr5 65665928 65723035 +787894 NLN chr5 65722205 65871725 +788037 AC010359.2 chr5 65924629 65925135 +788040 ERBIN chr5 65926475 66082549 +788503 AC010359.3 chr5 65965373 65969143 +788507 AC025442.2 chr5 66085405 66093937 +788511 SREK1 chr5 66139971 66183615 +788723 AC025442.1 chr5 66144156 66144795 +788727 LINC02065 chr5 66205120 66209893 +788732 AC092353.1 chr5 66298394 66393521 +788797 AC092353.2 chr5 66350148 66440356 +788802 LINC02229 chr5 66507380 66511644 +788807 MAST4 chr5 66596361 67169595 +789263 MAST4-IT1 chr5 66662331 66662988 +789266 MAST4-AS1 chr5 67001383 67003953 +789270 CD180 chr5 67179613 67196799 +789285 AC010420.1 chr5 67268022 67270182 +789290 AC008459.1 chr5 67356663 67366303 +789294 AC112206.2 chr5 67379378 67806600 +789386 AC079467.1 chr5 67463809 67475592 +789398 LINC02242 chr5 67632266 67646789 +789403 AC106798.1 chr5 67699429 67902600 +789414 AC024581.1 chr5 67800740 67890096 +789419 LINC02219 chr5 68189876 68198407 +789424 PIK3R1 chr5 68215756 68301821 +789679 AC024579.1 chr5 68374765 68375292 +789683 AC010280.2 chr5 68430427 68434481 +789688 AC010280.1 chr5 68508223 68565515 +789701 AC010280.3 chr5 68523878 68530007 +789705 AC093523.1 chr5 68792609 69007185 +789723 AC093248.1 chr5 68963246 68967845 +789727 LINC02198 chr5 68970692 69030165 +789735 AC010273.3 chr5 69038518 69043821 +789739 SLC30A5 chr5 69093949 69131069 +789882 AC010273.2 chr5 69113112 69136394 +789890 CCNB1 chr5 69167135 69178245 +789993 CENPH chr5 69189574 69210357 +790083 MRPS36 chr5 69217760 69230158 +790131 CDK7 chr5 69234795 69277430 +790410 CCDC125 chr5 69280175 69332809 +790538 AK6 chr5 69350984 69370013 +790605 TAF9 chr5 69364743 69370013 +790682 RAD17 chr5 69369293 69414801 +791214 MARVELD2 chr5 69415065 69444330 +791348 AC145146.1 chr5 69477472 69502466 +791355 OCLN chr5 69492292 69558104 +791432 GTF2H2C chr5 69560208 69594723 +791710 SERF1B chr5 70025247 70043113 +791779 SMN2 chr5 70049612 70078522 +792013 AC140134.2 chr5 70055820 70057416 +792016 AC146944.4 chr5 70449636 70450353 +792019 SERF1A chr5 70900665 70918530 +792109 SMN1 chr5 70925030 70953942 +792282 AC139834.1 chr5 70931244 70932840 +792285 NAIP chr5 70968483 71025114 +792508 GTF2H2 chr5 71032670 71067689 +792736 LINC02197 chr5 71337182 71446772 +792751 AC145141.2 chr5 71372676 71374898 +792756 AC145141.1 chr5 71445616 71446569 +792760 BDP1 chr5 71455651 71567820 +792991 MCCC2 chr5 71587288 71658706 +793171 CARTPT chr5 71719275 71721048 +793186 AC025774.1 chr5 72087782 72108000 +793198 MAP1B chr5 72107234 72209565 +793275 MRPS27 chr5 72219409 72320646 +793471 PTCD2 chr5 72320367 72368395 +793707 AC093278.2 chr5 72439903 72442387 +793710 ZNF366 chr5 72439903 72507410 +793750 LINC02056 chr5 72574120 72660669 +793762 AC063979.2 chr5 72687112 72771733 +793793 AC035140.1 chr5 72794405 72816565 +793797 TNPO1 chr5 72816312 72916733 +794051 AC008972.1 chr5 72953635 72954274 +794054 AC008972.2 chr5 72955206 72955699 +794057 FCHO2 chr5 72956041 73090522 +794226 TMEM171 chr5 73120569 73131809 +794253 AC116345.3 chr5 73132008 73150592 +794257 TMEM174 chr5 73173193 73175143 +794270 AC116345.4 chr5 73195314 73201973 +794275 AC116345.1 chr5 73213930 73295258 +794319 LINC02230 chr5 73337906 73338533 +794323 FOXD1 chr5 73444827 73448777 +794334 FOXD1-AS1 chr5 73446357 73446984 +794338 LINC01385 chr5 73451498 73453395 +794342 LINC01386 chr5 73454187 73472896 +794349 AC099522.2 chr5 73497550 73498293 +794352 BTF3 chr5 73498408 73505635 +794430 ANKRA2 chr5 73552190 73565667 +794491 UTP15 chr5 73565443 73583380 +794635 ARHGEF28 chr5 73626158 73941993 +795151 AC091868.2 chr5 73778039 73786491 +795156 AC093283.1 chr5 73952940 73954014 +795159 LINC02122 chr5 74084068 74103216 +795163 LINC01331 chr5 74111690 74536976 +795175 LINC01335 chr5 74258689 74321255 +795192 LINC01333 chr5 74321293 74341236 +795265 LINC01332 chr5 74327995 74334766 +795269 ENC1 chr5 74627406 74641424 +795352 HEXB chr5 74640023 74722647 +795508 GFM2 chr5 74721206 74767147 +795743 NSA2 chr5 74766991 74780113 +795795 FAM169A chr5 74777574 74866966 +795955 AC010501.2 chr5 74865893 74867854 +795958 AC116337.4 chr5 74899115 74903650 +795962 AC116337.3 chr5 74917726 75023928 +795969 GCNT4 chr5 75025346 75052770 +795990 ANKRD31 chr5 75068275 75236878 +796118 AC008897.2 chr5 75320155 75336914 +796123 HMGCR chr5 75336329 75362101 +796317 CERT1 chr5 75356345 75512138 +797147 AC008897.3 chr5 75363760 75364242 +797150 POLK chr5 75511756 75601144 +797521 AC010245.1 chr5 75598482 75599380 +797525 AC010245.2 chr5 75608817 75609983 +797528 ANKDD1B chr5 75611182 75681773 +797771 POC5 chr5 75674124 75717448 +797965 AC026774.1 chr5 76081946 76084186 +797969 SV2C chr5 76083383 76353939 +798035 AC113404.1 chr5 76285542 76311462 +798040 IQGAP2 chr5 76403285 76708132 +798538 AC026725.1 chr5 76606608 76608970 +798542 F2RL2 chr5 76615482 76623413 +798561 AC025188.1 chr5 76691439 76716215 +798567 F2R chr5 76716126 76735770 +798586 F2RL1 chr5 76818933 76835315 +798603 S100Z chr5 76850001 76921650 +798643 CRHBP chr5 76953045 76981158 +798691 AGGF1 chr5 77029251 77065234 +798754 ZBED3 chr5 77072072 77087285 +798776 AC008581.1 chr5 77073881 77074520 +798780 ZBED3-AS1 chr5 77086688 77166909 +799019 PDE8B chr5 77210449 77429807 +799321 WDR41 chr5 77425970 77620611 +799708 OTP chr5 77628712 77639688 +799723 TBCA chr5 77691166 77868780 +799828 AC108482.1 chr5 77942757 77946438 +799832 AC108482.2 chr5 77958243 77959092 +799836 AP3B1 chr5 78000525 78294755 +799993 SCAMP1-AS1 chr5 78342365 78360507 +800004 SCAMP1 chr5 78360611 78480739 +800112 LHFPL2 chr5 78485215 78770021 +800164 ARSB chr5 78777209 78986087 +800237 DMGDH chr5 78997564 79236038 +800401 BHMT2 chr5 79069767 79090069 +800485 BHMT chr5 79111809 79132288 +800537 JMY chr5 79236131 79327211 +800568 HOMER1 chr5 79372636 79514134 +800645 TENT2 chr5 79612120 79686648 +800885 CMYA5 chr5 79689836 79800240 +800933 AC008496.2 chr5 79774348 79816190 +800940 AC008496.3 chr5 79840797 79845239 +800952 LINC01455 chr5 79936579 79967626 +800957 MTX3 chr5 79976731 79991265 +801040 THBS4 chr5 79991311 80083287 +801166 AC012636.1 chr5 80052374 80083654 +801190 SERINC5 chr5 80111651 80256048 +801326 AC010260.1 chr5 80128361 80143883 +801331 SPZ1 chr5 80319625 80321842 +801346 ZFYVE16 chr5 80408013 80483379 +801563 AC008771.1 chr5 80411231 80488095 +801576 FAM151B chr5 80487969 80542563 +801630 ANKRD34B chr5 80556755 80570280 +801661 LINC01337 chr5 80608623 80622524 +801665 DHFR chr5 80626226 80654983 +801746 AC008434.1 chr5 80630313 80631590 +801750 MSH3 chr5 80654652 80876815 +801986 RASGRF2-AS1 chr5 80947694 80960907 +802001 RASGRF2 chr5 80960363 81230162 +802165 AC026427.1 chr5 81113385 81114852 +802169 CKMT2-AS1 chr5 81201341 81301565 +802220 CKMT2 chr5 81233320 81266398 +802361 ZCCHC9 chr5 81301587 81313297 +802453 ACOT12 chr5 81329996 81394179 +802515 AC010623.1 chr5 81408517 81411867 +802519 SSBP2 chr5 81413021 81751797 +802905 AC026726.2 chr5 81817531 81842360 +802912 AC026726.1 chr5 81851601 81852201 +802915 ATG10 chr5 81972023 82276857 +803040 ATG10-IT1 chr5 81991995 81992481 +803043 ATG10-AS1 chr5 82073055 82073702 +803046 RPS23 chr5 82273320 82278396 +803149 ATP6AP1L chr5 82279462 82386977 +803198 AC026782.1 chr5 82545862 82546310 +803201 AC026782.2 chr5 82586776 82587411 +803204 AC008885.2 chr5 82765404 82766333 +803207 LINC01338 chr5 82848260 82859958 +803217 AC108174.1 chr5 82919376 82921119 +803221 AC027338.2 chr5 82940458 82940983 +803224 AC027338.1 chr5 83012285 83013109 +803227 AC104118.1 chr5 83049376 83050964 +803230 TMEM167A chr5 83052846 83077863 +803265 XRCC4 chr5 83077498 83353787 +803366 VCAN chr5 83471618 83582303 +803592 VCAN-AS1 chr5 83531352 83581320 +803600 HAPLN1 chr5 83637805 83720855 +803678 EDIL3 chr5 83940554 84384880 +803742 AC113383.1 chr5 84382424 84490765 +803789 AC114928.1 chr5 85112342 85112756 +803792 AC117522.2 chr5 85212958 85213614 +803795 AC010486.1 chr5 85420028 85420451 +803798 AC010486.2 chr5 85429702 85430184 +803801 AC010486.3 chr5 85446974 85447758 +803804 AC010595.1 chr5 85663232 85664684 +803807 AC026414.1 chr5 85848502 85849199 +803810 AC016550.1 chr5 86335024 86335808 +803813 AC016550.2 chr5 86353803 86368854 +803822 AC016550.3 chr5 86380660 86381426 +803825 COX7C chr5 86617928 86620962 +803874 LINC02059 chr5 86746818 86749777 +803889 AC008539.1 chr5 86797685 86800280 +803893 AC109492.1 chr5 86967321 87137712 +803901 LINC01949 chr5 87048858 87240145 +803919 RASA1 chr5 87267883 87391931 +804210 CCNH chr5 87318416 87412930 +804377 AC018754.1 chr5 87412342 87499340 +804384 LINC02488 chr5 87662040 87705337 +804392 LINC02144 chr5 87665345 87733269 +804400 AC020930.1 chr5 87767608 87774070 +804407 AC114971.1 chr5 87863703 88144455 +804420 TMEM161B chr5 88189633 88269476 +804687 TMEM161B-AS1 chr5 88268891 88439337 +805040 LINC02060 chr5 88408982 88439090 +805051 AC091826.2 chr5 88433892 88498697 +805055 LINC00461 chr5 88507546 88691057 +805233 MEF2C-AS2 chr5 88676033 88779088 +805250 AC008525.1 chr5 88691757 88695041 +805268 AC008525.2 chr5 88692651 88692859 +805272 MEF2C chr5 88717117 88904257 +806035 MEF2C-AS1 chr5 88883328 89466398 +806113 AC074131.1 chr5 89466537 89470039 +806117 LINC02161 chr5 89581209 89677701 +806121 AC113167.1 chr5 89900664 89990883 +806156 LINC01339 chr5 90153052 90290078 +806216 AC099554.1 chr5 90353037 90356609 +806220 AC093510.2 chr5 90388468 90389363 +806223 CETN3 chr5 90392261 90409786 +806307 AC093510.1 chr5 90410000 90410669 +806313 MBLAC2 chr5 90458209 90474771 +806330 POLR3G chr5 90471748 90514557 +806457 LYSMD3 chr5 90515611 90529584 +806506 ADGRV1 chr5 90529344 91164437 +807357 LUCAT1 chr5 91054834 91314547 +807692 AC074132.1 chr5 91132303 91142470 +807697 AC093281.1 chr5 91223419 91223967 +807700 AC093281.2 chr5 91226475 91227071 +807703 AC123595.1 chr5 91280097 91281142 +807706 AC123595.2 chr5 91280272 91281643 +807709 AC008799.2 chr5 91355380 91356026 +807712 ARRDC3 chr5 91368631 91383317 +807759 ARRDC3-AS1 chr5 91380349 91612566 +807790 AC093298.2 chr5 91642643 91799234 +807801 AC114316.1 chr5 92082597 92479426 +807847 AC124854.1 chr5 92410256 92660863 +807860 AC026780.1 chr5 92654848 92679141 +807867 AC026780.2 chr5 92675956 92688254 +807871 AC008517.1 chr5 92823935 92844992 +807881 LINC02058 chr5 92907180 92939591 +807887 AC012625.1 chr5 93019663 93068669 +807892 AC026408.1 chr5 93088856 93091768 +807897 NR2F1-AS1 chr5 93360779 93585649 +808418 NR2F1 chr5 93583222 93594611 +808463 FAM172A chr5 93617725 94111699 +808609 AC106818.2 chr5 93621683 93675081 +808617 POU5F2 chr5 93733220 93741600 +808625 AC108102.1 chr5 93741640 93743500 +808629 AC099501.1 chr5 93790505 93801320 +808633 AC114980.1 chr5 93860669 93863825 +808636 AC117528.1 chr5 94111720 94176029 +808642 KIAA0825 chr5 94152966 94618597 +808713 AC025766.1 chr5 94611906 94618122 +808718 SLF1 chr5 94618669 94739436 +808832 MCTP1 chr5 94703741 95284575 +809249 AC008534.1 chr5 94788789 94793599 +809255 MCTP1-AS1 chr5 94979151 94980893 +809259 FAM81B chr5 95391366 95450454 +809380 TTC37 chr5 95461755 95555007 +809710 ARSK chr5 95555101 95605102 +809798 GPR150 chr5 95620087 95622142 +809806 RFESD chr5 95646754 95684773 +809889 SPATA9 chr5 95652181 95698711 +809979 AC008840.1 chr5 95701249 95732295 +809990 RHOBTB3 chr5 95713522 95824383 +810140 GLRX chr5 95751319 95822726 +810202 AC008592.4 chr5 95835943 95852721 +810206 LINC01554 chr5 95838245 95860133 +810223 AC008592.5 chr5 95849309 95849855 +810226 AC008592.1 chr5 95861786 95874519 +810234 ELL2 chr5 95885098 95961851 +810313 AC104123.1 chr5 95962001 96631085 +810326 AC008592.2 chr5 95964999 95986311 +810332 MIR583HG chr5 96050115 96215519 +810337 AC099509.1 chr5 96213346 96215075 +810341 AC099509.2 chr5 96247776 96278751 +810345 PCSK1 chr5 96390333 96434143 +810434 CAST chr5 96525267 96779595 +811843 AC020900.1 chr5 96741079 96742698 +811847 ERAP1 chr5 96760810 96808100 +811991 AC008906.1 chr5 96784777 96785999 +811998 AC008906.2 chr5 96803688 96806105 +812008 AC009126.1 chr5 96814028 96935809 +812073 ERAP2 chr5 96875939 96919716 +812289 LNPEP chr5 96935394 97037513 +812383 LIX1-AS1 chr5 97089075 97437217 +812392 LIX1 chr5 97091867 97142753 +812421 RIOK2 chr5 97160867 97183247 +812503 AC008883.3 chr5 97183827 97216074 +812507 AC008883.1 chr5 97188090 97201880 +812511 AC008883.2 chr5 97223371 97227957 +812515 LINC01340 chr5 97504663 97690180 +812550 AC122697.1 chr5 97799404 97882687 +812556 LINC02234 chr5 97840912 97923497 +812572 LINC01846 chr5 98085866 98161352 +812585 RGMB chr5 98768650 98798643 +812632 RGMB-AS1 chr5 98769618 98773469 +812662 AC008522.1 chr5 98792861 98795766 +812667 CHD1 chr5 98853985 98928957 +812892 LINC02062 chr5 98929171 98995013 +812903 LINC02113 chr5 99549432 99577957 +812907 AC113385.1 chr5 100399047 100526912 +812983 AC021086.1 chr5 100428124 100535262 +813000 FAM174A chr5 100535374 100586741 +813019 AC027315.1 chr5 100654112 100657970 +813024 ST8SIA4 chr5 100806933 100903282 +813065 AC008948.1 chr5 102141893 102146874 +813070 SLCO4C1 chr5 102233986 102296284 +813102 SLCO6A1 chr5 102371774 102499016 +813253 AC094108.1 chr5 102500541 102505670 +813260 LINC00492 chr5 102581368 102617589 +813264 LINC00491 chr5 102604220 102671765 +813303 AC099487.1 chr5 102605635 102606197 +813307 AC099487.2 chr5 102664610 102726598 +813314 PAM chr5 102753981 103031105 +813804 GIN1 chr5 103086000 103120138 +813883 PPIP5K2 chr5 103120149 103212799 +814375 AC011362.1 chr5 103246048 103253519 +814379 C5orf30 chr5 103258763 103278660 +814413 AC010406.1 chr5 103408941 103412511 +814417 LINC02115 chr5 103528434 103541985 +814424 NUDT12 chr5 103548855 103562790 +814469 AC008505.1 chr5 103880129 103891404 +814498 LINC02163 chr5 104079847 104406121 +814527 AC099520.1 chr5 104383298 105392970 +814636 AC099520.2 chr5 104773641 104799772 +814640 AC091987.1 chr5 104917492 105246364 +814650 LINC01950 chr5 106815197 107011052 +814669 EFNA5 chr5 107376889 107670937 +814720 AC024587.2 chr5 107699392 107716841 +814737 FBXL17 chr5 107859035 108382098 +814837 AC008462.1 chr5 108382156 108418016 +814842 LINC01023 chr5 108727825 108728260 +814845 FER chr5 108747841 109196841 +815026 AC008871.1 chr5 108818041 108830790 +815030 AC116428.1 chr5 109165289 109187152 +815035 AC008467.1 chr5 109237120 109326369 +815045 PJA2 chr5 109334713 109409974 +815102 AC091917.3 chr5 109467353 109467952 +815105 AC091917.2 chr5 109470843 109471586 +815108 AC091917.1 chr5 109497877 109499108 +815112 AC012603.1 chr5 109687802 109688329 +815115 MAN2A1 chr5 109689366 109869625 +815184 LINC01848 chr5 109883182 109884751 +815189 TMEM232 chr5 110289233 110738956 +815354 SLC25A46 chr5 110738136 110765161 +815469 AC010395.1 chr5 110970951 111008899 +815477 TSLP chr5 111070062 111078026 +815515 AC008572.1 chr5 111076921 111092115 +815521 WDR36 chr5 111091716 111130502 +815700 CAMK4 chr5 111223653 111494886 +815872 AC010468.2 chr5 111265809 111270089 +815876 AC010275.1 chr5 111277517 111302567 +815881 STARD4 chr5 111496033 111512590 +816015 STARD4-AS1 chr5 111510396 111739726 +816037 NREP chr5 111662621 111997464 +816313 NREP-AS1 chr5 111912508 112017309 +816326 EPB41L4A chr5 112142441 112419313 +816495 EPB41L4A-AS1 chr5 112160526 112164818 +816514 AC010261.1 chr5 112173570 112175548 +816518 AC010261.2 chr5 112192020 112210139 +816531 AC104126.1 chr5 112228283 112257309 +816537 EPB41L4A-DT chr5 112419583 112420978 +816542 LINC02200 chr5 112628436 112642483 +816571 APC chr5 112707498 112846239 +816803 SRP19 chr5 112861188 112898371 +816933 REEP5 chr5 112876385 112922289 +817011 DCP2 chr5 112976702 113022195 +817119 MCC chr5 113022099 113488823 +817309 AC079465.1 chr5 113323028 113437174 +817319 TSSK1B chr5 113432553 113434989 +817327 YTHDC2 chr5 113513694 113595285 +817492 AC093240.1 chr5 113738106 113776837 +817498 KCNN2 chr5 114055545 114496500 +817644 AC010230.1 chr5 114475339 114668410 +817658 LINC01957 chr5 114576041 114579970 +817662 AC094104.2 chr5 115031273 115031894 +817665 AC094104.1 chr5 115087892 115088475 +817668 TRIM36 chr5 115124762 115180546 +817787 TRIM36-IT1 chr5 115148764 115149644 +817790 AC008494.2 chr5 115188563 115188932 +817793 PGGT1B chr5 115204012 115262877 +817850 AC008494.3 chr5 115262505 115263448 +817853 CCDC112 chr5 115267190 115296693 +817967 FEM1C chr5 115520908 115544775 +817979 TICAM2 chr5 115578650 115602479 +817992 AC010226.1 chr5 115602057 115623897 +818007 TMED7 chr5 115613210 115632992 +818032 AC008549.2 chr5 115691462 115692167 +818035 AC008549.1 chr5 115738978 115756543 +818047 CDO1 chr5 115804733 115816659 +818077 ATG12 chr5 115828200 115841837 +818186 AP3S1 chr5 115841592 115914081 +818270 LINCADL chr5 115956571 115958599 +818274 LVRN chr5 115962454 116027619 +818539 ARL14EPL chr5 116032324 116060118 +818565 AC034236.3 chr5 116078110 116078570 +818568 AC034236.2 chr5 116083807 116085416 +818571 COMMD10 chr5 116085016 116412762 +818672 AC018752.1 chr5 116302354 116304134 +818676 SEMA6A chr5 116443616 116574934 +818907 SEMA6A-AS1 chr5 116447547 116508276 +818928 SEMA6A-AS2 chr5 116574482 116611200 +818947 LINC02214 chr5 116742991 116762209 +818953 AC010267.1 chr5 116819220 116830370 +818962 AC093534.2 chr5 117031200 117038569 +818966 AC093295.1 chr5 117313085 117330149 +818970 LINC00992 chr5 117415509 117546298 +818980 LINC02147 chr5 117730515 118266267 +819008 LINC02208 chr5 118000253 118562199 +819114 LINC02148 chr5 118282575 118284782 +819118 LINC02216 chr5 118575575 118581324 +819125 AC114311.1 chr5 118581242 118628178 +819129 LINC02215 chr5 118596188 118628092 +819136 AC093206.1 chr5 118760474 118785459 +819140 DTWD2 chr5 118836074 118988547 +819203 AC008629.1 chr5 119006347 119070902 +819218 DMXL1 chr5 119037772 119249138 +819498 TNFAIP8 chr5 119268692 119399688 +819567 HSD17B4 chr5 119452473 119637199 +820648 FAM170A chr5 119629559 119635822 +820742 AC008574.1 chr5 120245448 120333502 +820746 AC113418.1 chr5 120345907 120410969 +820756 PRR16 chr5 120464300 120687332 +820806 AC114284.1 chr5 120781218 120790778 +820810 AC008568.1 chr5 121164687 121359869 +820862 FTMT chr5 121851882 121852833 +820870 SRFBP1 chr5 121961975 122075570 +820896 LOX chr5 122063195 122078360 +820967 AC010255.1 chr5 122114598 122154856 +820975 ZNF474 chr5 122129546 122153569 +821001 AC010255.3 chr5 122129622 122183949 +821043 AC010255.2 chr5 122154496 122156015 +821047 AC113349.2 chr5 122311297 122311673 +821050 SNCAIP chr5 122311354 122464219 +821480 AC113349.1 chr5 122321291 122323358 +821484 AC119150.1 chr5 122369762 122383568 +821490 AC022101.1 chr5 122436497 122479087 +821514 LINC02201 chr5 122628952 122730685 +821568 SNX2 chr5 122775079 122834543 +821729 AC008669.1 chr5 122832356 122834533 +821732 SNX24 chr5 122843439 123029354 +821880 PPIC chr5 123023250 123036725 +821899 AC106786.2 chr5 123036271 123054667 +821903 AC106786.1 chr5 123087248 123090299 +821910 PRDM6 chr5 123089241 123194266 +821947 CEP120 chr5 123344885 123423592 +822253 CSNK1G3 chr5 123512099 123617045 +822476 LINC01170 chr5 124059794 124438625 +822512 AC016556.1 chr5 124395603 124400655 +822516 AC025465.2 chr5 124452277 124460552 +822525 AC025465.4 chr5 124459912 124460549 +822528 AC025465.3 chr5 124469591 124469901 +822531 AC025465.1 chr5 124492775 124536348 +822536 ZNF608 chr5 124636913 124748807 +822669 AC112196.1 chr5 124707827 124710737 +822674 AC113398.2 chr5 124734618 124735175 +822677 LINC02240 chr5 124808981 125602227 +822732 AC109464.1 chr5 124829472 124830290 +822735 AC109464.2 chr5 124868972 124869914 +822738 AC109458.2 chr5 124993408 124996096 +822742 AC116362.1 chr5 125333369 126368755 +822771 AC109471.1 chr5 125376828 125377439 +822774 AC116362.2 chr5 125493261 125602229 +822780 LINC02039 chr5 126179565 126193858 +822791 GRAMD2B chr5 126360132 126496494 +823158 AC093535.1 chr5 126372477 126509021 +823175 ALDH7A1 chr5 126531200 126595362 +824018 PHAX chr5 126600925 126627252 +824048 TEX43 chr5 126631705 126636284 +824063 LMNB1-DT chr5 126751963 126776486 +824069 LMNB1 chr5 126776623 126837020 +824181 MARCH3 chr5 126867714 127030558 +824217 C5orf63 chr5 127042558 127073492 +824320 AC011416.3 chr5 127215159 127229828 +824339 AC011416.4 chr5 127231977 127290731 +824366 MEGF10 chr5 127290796 127465737 +824577 AC010424.2 chr5 127478295 127478737 +824580 PRRC1 chr5 127517609 127555089 +824659 AC010424.3 chr5 127588746 127590710 +824663 CTXN3 chr5 127649044 127658630 +824696 AC022118.1 chr5 127651693 127664029 +824702 CCDC192 chr5 127703389 127941634 +824727 AC068658.1 chr5 127838486 127857804 +824731 LINC01184 chr5 127939152 128083172 +824870 SLC12A2 chr5 128083766 128189677 +825122 FBN2 chr5 128257909 128659185 +825535 SLC27A6 chr5 128538013 129033642 +825632 AC008588.1 chr5 128663978 128742829 +825636 ISOC1 chr5 129094749 129114028 +825661 AC008679.1 chr5 129150677 129173257 +825665 ADAMTS19-AS1 chr5 129424782 129461076 +825674 ADAMTS19 chr5 129460281 129738683 +825758 AC008591.1 chr5 129500361 129905917 +825785 MINAR2 chr5 129748094 129766732 +825797 CHSY3 chr5 129904465 130186634 +825813 AC006525.1 chr5 130655383 130944178 +825821 HINT1 chr5 131159027 131171735 +825925 LYRM7 chr5 131170944 131205428 +825968 CDC42SE2 chr5 131245493 131398447 +826068 RAPGEF6 chr5 131423921 131635236 +826617 FNIP1 chr5 131641714 131797063 +826812 MEIKIN chr5 131806990 131945698 +826895 AC034228.3 chr5 131944408 131968220 +826900 ACSL6 chr5 131949973 132012243 +827967 AC034228.1 chr5 132003592 132007022 +827971 AC034228.2 chr5 132011448 132013199 +827976 IL3 chr5 132060655 132063204 +827992 CSF2 chr5 132073789 132076170 +828006 AC063976.1 chr5 132179234 132181128 +828010 P4HA2-AS1 chr5 132184876 132192808 +828015 P4HA2 chr5 132191838 132295315 +828383 PDLIM4 chr5 132257696 132273454 +828449 SLC22A4 chr5 132294394 132344190 +828484 MIR3936HG chr5 132311285 132370170 +828523 SLC22A5 chr5 132369752 132395614 +828649 C5orf56 chr5 132410636 132488702 +828684 AC116366.2 chr5 132419416 132426714 +828691 AC116366.1 chr5 132468890 132473043 +828695 IRF1 chr5 132481609 132490777 +828843 IL5 chr5 132541445 132556838 +828869 RAD50 chr5 132556019 132646349 +829317 TH2LCRR chr5 132630589 132664272 +829334 IL13 chr5 132656263 132661110 +829386 IL4 chr5 132673986 132682678 +829428 AC004039.1 chr5 132688681 132723725 +829443 KIF3A chr5 132692628 132737638 +829644 CCNI2 chr5 132747445 132754403 +829685 SEPTIN8 chr5 132750819 132807241 +829968 SOWAHA chr5 132813302 132816786 +829976 AC004775.1 chr5 132817248 132818000 +829979 SHROOM1 chr5 132822141 132830898 +830076 GDF9 chr5 132861181 132866884 +830147 UQCRQ chr5 132866630 132868847 +830188 LEAP2 chr5 132873444 132875046 +830207 AFF4 chr5 132875395 132963634 +830348 AC010240.3 chr5 132963770 132964164 +830351 ZCCHC10 chr5 132996985 133026604 +830462 AC113410.5 chr5 133025847 133050178 +830466 AC113410.4 chr5 133051065 133051893 +830469 HSPA4 chr5 133052013 133106449 +830612 AC113410.2 chr5 133111055 133114475 +830616 AC010307.2 chr5 133160438 133224413 +830626 FSTL4 chr5 133196455 133612541 +830732 AC010307.3 chr5 133243764 133248781 +830739 AC010307.4 chr5 133256492 133275977 +830747 AC010608.1 chr5 133387773 133388549 +830751 WSPAR chr5 133913677 133917269 +830756 C5orf15 chr5 133955510 133968674 +830775 VDAC1 chr5 133971871 134004975 +830876 AC008608.2 chr5 134005147 134005562 +830879 TCF7 chr5 134114681 134151865 +831222 SKP1 chr5 134148935 134177038 +831391 PPP2CA chr5 134194332 134226073 +831441 AC104109.2 chr5 134226410 134227827 +831444 CDKL3 chr5 134286350 134371047 +831642 UBE2B chr5 134371469 134392108 +831719 AC109454.2 chr5 134399495 134401921 +831723 CDKN2AIPNL chr5 134402065 134411881 +831744 AC109454.3 chr5 134429051 134460615 +831753 AC005355.1 chr5 134436711 134492519 +831757 LINC01843 chr5 134506552 134509229 +831761 JADE2 chr5 134524312 134583230 +831927 SAR1B chr5 134601149 134649271 +832091 SEC24A chr5 134648785 134727909 +832187 CAMLG chr5 134738548 134752157 +832212 DDX46 chr5 134758771 134855133 +832456 C5orf24 chr5 134845680 134859735 +832511 TXNDC15 chr5 134873803 134901525 +832602 PCBD2 chr5 134904906 135007959 +832654 CATSPER3 chr5 134967907 135011696 +832680 PITX1 chr5 135027734 135034813 +832730 C5orf66 chr5 135033280 135358219 +832761 AC008406.3 chr5 135034521 135035894 +832764 C5orf66-AS1 chr5 135038831 135040047 +832771 AC008406.2 chr5 135120526 135139681 +832776 AC008406.1 chr5 135124380 135131249 +832780 C5orf66-AS2 chr5 135236234 135248179 +832789 H2AFY chr5 135333900 135399914 +832989 AC026691.1 chr5 135399280 135401296 +832992 DCANP1 chr5 135444214 135447348 +833000 TIFAB chr5 135444226 135452351 +833010 AC022092.1 chr5 135450613 135458697 +833014 NEUROG1 chr5 135534282 135535964 +833022 AC034206.1 chr5 135559577 135634874 +833032 CXCL14 chr5 135570679 135579279 +833059 SLC25A48 chr5 135579202 135889770 +833221 SLC25A48-AS1 chr5 135648584 135653935 +833226 AC114296.1 chr5 135812667 135827546 +833255 IL9 chr5 135892246 135895841 +833271 AC002428.2 chr5 135897637 135900250 +833275 AC002428.1 chr5 135900353 135918161 +833282 LECT2 chr5 135922279 135954983 +833336 TGFBI chr5 136028988 136063818 +833545 SMAD5-AS1 chr5 136129507 136134890 +833549 SMAD5 chr5 136132845 136188747 +833676 SMIM32 chr5 136191468 136193162 +833684 TRPC7 chr5 136213320 136365545 +833855 TRPC7-AS1 chr5 136214048 136222159 +833859 TRPC7-AS2 chr5 136303757 136316100 +833864 AC063980.1 chr5 136376348 136397042 +833868 AC112178.1 chr5 136466645 136521432 +833905 AC109439.2 chr5 136734830 136763409 +833923 SPOCK1 chr5 136975298 137598379 +834032 KLHL3 chr5 137617500 137736089 +834230 HNRNPA0 chr5 137745651 137754363 +834238 AC106791.2 chr5 137761546 137761936 +834241 AC106791.1 chr5 137809780 137889394 +834266 MYOT chr5 137867791 137887851 +834366 PKD2L2 chr5 137887968 137942747 +834544 FAM13B chr5 137937960 138051961 +834764 AC113382.1 chr5 138032774 138037266 +834768 AC113382.2 chr5 138039199 138039979 +834772 WNT8A chr5 138083990 138092365 +834841 NME5 chr5 138115175 138139443 +834876 BRD8 chr5 138139766 138178986 +835445 KIF20A chr5 138178719 138187723 +835584 CDC23 chr5 138187650 138213343 +835695 GFRA3 chr5 138252380 138274621 +835736 CDC25C chr5 138285265 138338355 +835974 FAM53C chr5 138331935 138349729 +836062 AC104116.1 chr5 138347027 138349641 +836066 KDM3B chr5 138352685 138437028 +836267 REEP2 chr5 138439057 138446969 +836406 EGR1 chr5 138465479 138469303 +836416 ETF1 chr5 138506095 138543236 +836557 HSPA9 chr5 138553756 138575416 +836769 CTNNA1 chr5 138610967 138935034 +837372 AC034243.1 chr5 138744434 138753309 +837376 LRRTM2 chr5 138868921 138875368 +837407 SIL1 chr5 138946724 139293557 +837595 AC011405.1 chr5 139012647 139051203 +837612 MATR3 chr5 139273752 139331671 +837908 SNHG4 chr5 139274102 139284899 +837965 MATR3 chr5 139293674 139331677 +838354 PAIP2 chr5 139341587 139369720 +838428 AC135457.1 chr5 139364677 139369717 +838432 SLC23A1 chr5 139367196 139384553 +838533 MZB1 chr5 139387467 139390081 +838607 PROB1 chr5 139390592 139395104 +838615 SPATA24 chr5 139396563 139404088 +838708 DNAJC18 chr5 139408588 139444491 +838850 ECSCR chr5 139448560 139462743 +838876 SMIM33 chr5 139470778 139474772 +838886 TMEM173 chr5 139475533 139482935 +839109 AC010378.2 chr5 139503242 139511374 +839113 UBE2D2 chr5 139526431 139628434 +839239 AC113361.1 chr5 139644460 139645002 +839242 CXXC5 chr5 139647299 139683882 +839363 CXXC5-AS1 chr5 139648999 139649728 +839367 AC008667.1 chr5 139684645 139745010 +839375 PSD2-AS1 chr5 139740951 139747406 +839392 AC008667.3 chr5 139772528 139775406 +839396 AC008667.4 chr5 139775305 139775472 +839399 PSD2 chr5 139795808 139844466 +839446 NRG2 chr5 139846779 140043299 +839628 AC008667.2 chr5 139848290 139856389 +839633 MALINC1 chr5 140071312 140109274 +839712 PURA chr5 140107777 140125619 +839743 IGIP chr5 140125937 140129392 +839751 AC011379.2 chr5 140157319 140173051 +839762 CYSTM1 chr5 140175156 140282052 +839799 AC011379.1 chr5 140200163 140203187 +839802 PFDN1 chr5 140245035 140303113 +839856 HBEGF chr5 140332843 140346603 +839880 AC008438.2 chr5 140348484 140357794 +839884 SLC4A9 chr5 140360194 140375141 +840088 AC008438.1 chr5 140370891 140401460 +840096 ANKHD1 chr5 140401814 140539856 +840582 SRA1 chr5 140537340 140558252 +840626 EIF4EBP3 chr5 140547662 140549576 +840638 APBB3 chr5 140558268 140564781 +840968 SLC35A4 chr5 140564828 140569100 +841011 CD14 chr5 140631728 140633701 +841059 NDUFA2 chr5 140638740 140647785 +841088 TMCO6 chr5 140639427 140645408 +841263 IK chr5 140647058 140662480 +841437 WDR55 chr5 140664676 140674124 +841507 DND1 chr5 140670794 140673576 +841521 HARS chr5 140673904 140691537 +841892 HARS2 chr5 140691430 140699305 +842353 ZMAT2 chr5 140698680 140706686 +842399 AC005609.5 chr5 140785698 140828549 +842415 PCDHA1 chr5 140786136 141012347 +842447 PCDHA2 chr5 140794852 141012347 +842477 PCDHA3 chr5 140801028 141012347 +842498 PCDHA4 chr5 140806929 141012347 +842548 PCDHA5 chr5 140821604 141012347 +842584 PCDHA6 chr5 140827958 141012347 +842618 PCDHA7 chr5 140834248 141012347 +842639 PCDHA8 chr5 140841187 141012347 +842660 PCDHA9 chr5 140847463 141012344 +842681 AC005609.2 chr5 140849105 140849696 +842684 PCDHA10 chr5 140855883 141012347 +842735 AC005609.4 chr5 140867513 140867959 +842738 PCDHA11 chr5 140868183 141012344 +842772 PCDHA12 chr5 140875302 141012347 +842808 AC005609.3 chr5 140875346 140875922 +842811 AC005609.1 chr5 140878073 140882642 +842815 PCDHA13 chr5 140882124 141012347 +842850 PCDHAC1 chr5 140926369 141012344 +842870 AC010223.1 chr5 140966212 140966490 +842873 PCDHAC2 chr5 140966470 141012347 +842904 AC244517.5 chr5 141046260 141096402 +842927 PCDHB1 chr5 141051135 141059344 +842935 AC244517.9 chr5 141078076 141084481 +842940 PCDHB2 chr5 141094606 141098703 +842980 AC244517.2 chr5 141100242 141174391 +842999 PCDHB3 chr5 141100473 141103827 +843012 AC244517.1 chr5 141118680 141120765 +843015 PCDHB4 chr5 141121818 141125623 +843026 PCDHB5 chr5 141135206 141138615 +843041 AC244517.11 chr5 141136683 141245380 +843061 PCDHB6 chr5 141150022 141153287 +843078 AC244517.12 chr5 141168231 141168893 +843081 PCDHB7 chr5 141172644 141176383 +843089 PCDHB8 chr5 141177790 141180539 +843097 PCDHB16 chr5 141181399 141186399 +843112 AC244517.4 chr5 141183401 141201396 +843119 PCDHB9 chr5 141187127 141191541 +843137 AC244517.7 chr5 141191599 141194088 +843141 PCDHB10 chr5 141192353 141195647 +843149 PCDHB11 chr5 141199610 141203779 +843166 PCDHB12 chr5 141208697 141212571 +843192 PCDHB13 chr5 141213919 141218979 +843200 PCDHB14 chr5 141222932 141227759 +843217 PCDHB15 chr5 141245395 141249365 +843232 TAF7 chr5 141260225 141320784 +843251 SLC25A2 chr5 141302635 141304049 +843259 AC005618.4 chr5 141320980 141325985 +843264 AC005618.1 chr5 141326210 141329357 +843270 PCDHGA1 chr5 141330571 141512981 +843290 PCDHGA2 chr5 141338760 141512975 +843311 PCDHGA3 chr5 141343829 141512979 +843346 PCDHGB1 chr5 141350102 141512979 +843366 AC005618.3 chr5 141350109 141350662 +843369 PCDHGA4 chr5 141355021 141512975 +843390 PCDHGB2 chr5 141360042 141512979 +843410 PCDHGA5 chr5 141364232 141512979 +843430 PCDHGB3 chr5 141370242 141512975 +843450 PCDHGA6 chr5 141373914 141512979 +843471 PCDHGA7 chr5 141382739 141512975 +843492 PCDHGB4 chr5 141387698 141512979 +843512 PCDHGA8 chr5 141390157 141512979 +843532 PCDHGB5 chr5 141397987 141512979 +843552 PCDHGA9 chr5 141402932 141512979 +843572 PCDHGB6 chr5 141408021 141512979 +843592 PCDHGA10 chr5 141412987 141512979 +843612 PCDHGB7 chr5 141417645 141512979 +843633 PCDHGA11 chr5 141421047 141512975 +843666 AC005618.2 chr5 141427295 141427752 +843669 PCDHGA12 chr5 141430507 141512975 +843690 AC008781.3 chr5 141468465 141471528 +843694 PCDHGC3 chr5 141475947 141512977 +843762 PCDHGC4 chr5 141484997 141512979 +843802 PCDHGC5 chr5 141489121 141512979 +843823 DIAPH1 chr5 141515016 141619055 +844311 AC008781.2 chr5 141558311 141565263 +844316 AC008781.1 chr5 141618414 141626481 +844321 HDAC3 chr5 141620876 141636849 +844474 RELL2 chr5 141636950 141641064 +844570 FCHSD1 chr5 141639302 141651418 +844765 ARAP3 chr5 141653401 141682230 +845071 AC005753.2 chr5 141718711 141775187 +845075 AC005753.3 chr5 141822076 141825488 +845082 AC005753.1 chr5 141825708 141826325 +845085 PCDH1 chr5 141853111 141879246 +845157 AC005740.5 chr5 141882815 141907939 +845166 DELE1 chr5 141923855 141942047 +845274 PCDH12 chr5 141943585 141969741 +845299 AC005740.4 chr5 141952419 141953375 +845302 RNF14 chr5 141958328 141990292 +845528 AC005740.3 chr5 141970637 141982687 +845533 GNPDA1 chr5 141991749 142013041 +845713 NDFIP1 chr5 142108779 142154440 +845745 SPRY4 chr5 142310427 142326455 +845783 SPRY4-AS1 chr5 142325293 142672001 +845815 FGF1 chr5 142592178 142698070 +845996 AC005592.1 chr5 142703782 142705421 +845999 LINC01844 chr5 142716229 142761035 +846142 AC005592.2 chr5 142732704 142737461 +846146 ARHGAP26 chr5 142770377 143229011 +846508 ARHGAP26-AS1 chr5 142859604 142868922 +846528 ARHGAP26-IT1 chr5 143192500 143194166 +846532 NR3C1 chr5 143277931 143435512 +846789 AC016598.1 chr5 143489855 143531350 +846793 AC016598.2 chr5 143531331 143598434 +846821 AC008696.2 chr5 143605628 143828772 +846828 HMHB1 chr5 143812161 143820719 +846844 YIPF5 chr5 144158162 144170714 +846925 KCTD16 chr5 144170873 144485686 +846950 AC008652.1 chr5 144369334 144385310 +846957 AC109441.1 chr5 144439204 144468471 +846964 AC132803.1 chr5 144856890 145228982 +846973 AC137770.1 chr5 145337932 145381670 +846977 AC008700.1 chr5 145429811 145451108 +846994 PRELID2 chr5 145471799 145835369 +847089 GRXCR2 chr5 145858521 145937126 +847114 SH3RF2 chr5 145936578 146081791 +847185 PLAC8L1 chr5 146084313 146105577 +847212 AC091887.1 chr5 146099406 146120412 +847217 LARS chr5 146113034 146182650 +847489 RBM27 chr5 146203605 146289223 +847540 AC011396.2 chr5 146307098 146376963 +847549 POU4F3 chr5 146338839 146341728 +847559 AC011396.3 chr5 146375591 146376219 +847563 AC011396.1 chr5 146400981 146407359 +847567 TCERG1 chr5 146447311 146511961 +847792 GPR151 chr5 146513103 146516190 +847800 AC008728.1 chr5 146563226 146617004 +847806 PPP2R2B chr5 146581146 147084784 +848155 PPP2R2B-IT1 chr5 146914207 146919506 +848161 AC010251.1 chr5 147093259 147097240 +848166 STK32A-AS1 chr5 147180204 147234859 +848171 STK32A chr5 147234963 147387855 +848318 DPYSL3 chr5 147390808 147510068 +848440 AC011373.1 chr5 147401760 147401996 +848443 JAKMIP2-AS1 chr5 147559994 147662009 +848464 JAKMIP2 chr5 147585438 147782775 +848665 AC011370.1 chr5 147725551 147728464 +848669 SPINK1 chr5 147824568 147831786 +848697 SCGB3A2 chr5 147870682 147882191 +848728 C5orf46 chr5 147880726 147906538 +848755 AC011352.1 chr5 147886086 147886878 +848758 AC011352.3 chr5 147887112 147887704 +848761 SPINK5 chr5 148025683 148137289 +849107 AC011346.1 chr5 148088125 148383907 +849180 SPINK14 chr5 148169733 148175398 +849203 SPINK6 chr5 148202794 148215137 +849243 MARCOL chr5 148221650 148243580 +849271 SPINK13 chr5 148268180 148286255 +849321 SPINK7 chr5 148312419 148315922 +849357 SPINK9 chr5 148321203 148339852 +849386 FBXO38 chr5 148383935 148442836 +849653 AC114939.1 chr5 148430159 148430807 +849657 HTR4 chr5 148451032 148677235 +849871 AC008627.1 chr5 148644687 148646390 +849874 ADRB2 chr5 148825245 148828687 +849882 SH3TC2 chr5 148923639 149063163 +850203 AC116312.1 chr5 148970340 148970653 +850206 SH3TC2-DT chr5 149063254 149129578 +850234 ABLIM3 chr5 149141483 149260542 +850586 AC012613.1 chr5 149163955 149276776 +850594 AC012613.2 chr5 149216523 149276805 +850598 AFAP1L1 chr5 149271859 149343637 +850716 AC131025.3 chr5 149324220 149345333 +850720 GRPEL2 chr5 149345430 149354583 +850761 GRPEL2-AS1 chr5 149348116 149357642 +850765 PCYOX1L chr5 149358037 149369653 +850854 IL17B chr5 149371324 149404202 +850874 AC131025.1 chr5 149372174 149375116 +850878 CARMN chr5 149406689 149432835 +850980 AC131025.2 chr5 149425771 149428289 +850984 CSNK1A1 chr5 149492982 149551471 +851337 ARHGEF37 chr5 149551947 149634968 +851382 AC022100.1 chr5 149694237 149696308 +851386 PPARGC1B chr5 149730298 149855022 +851524 PDE6A chr5 149857953 149944793 +851691 SLC26A2 chr5 149960737 149993455 +851718 TIGD6 chr5 149993118 150000654 +851740 HMGXB3 chr5 150000046 150053142 +851904 CSF1R chr5 150053291 150113372 +852061 PDGFRB chr5 150113839 150155872 +852211 CDX1 chr5 150166778 150184558 +852235 SLC6A7 chr5 150190062 150222788 +852309 CAMK2A chr5 150219491 150290291 +852778 ARSI chr5 150296343 150339307 +852804 TCOF1 chr5 150357629 150400308 +853502 CD74 chr5 150400041 150412929 +853661 AC011388.1 chr5 150427904 150429906 +853665 RPS14 chr5 150442635 150449739 +853761 NDST1-AS1 chr5 150475531 150485968 +853766 NDST1 chr5 150485818 150558211 +853869 SYNPO chr5 150601080 150659207 +853915 AC011383.1 chr5 150608428 150615354 +853920 AC008453.2 chr5 150621007 150626779 +853925 MYOZ3 chr5 150660874 150679365 +854003 AC008453.1 chr5 150670658 150672390 +854007 RBM22 chr5 150690792 150701077 +854112 DCTN4 chr5 150708440 150759109 +854350 SMIM3 chr5 150777946 150796734 +854371 IRGM chr5 150846523 150900736 +854394 ZNF300 chr5 150894392 150904983 +854478 GPX3 chr5 151020438 151028992 +854602 TNIP1 chr5 151029945 151093577 +855152 ANXA6 chr5 151100706 151157785 +855490 AC008641.1 chr5 151158106 151158462 +855494 CCDC69 chr5 151181052 151224093 +855578 GM2A chr5 151212150 151270440 +855610 SLC36A3 chr5 151276762 151303766 +855673 SLC36A2 chr5 151314972 151347590 +855783 SLC36A1 chr5 151437046 151492379 +855981 FAT2 chr5 151504093 151568944 +856058 AC011337.1 chr5 151509453 151512769 +856061 AC011374.3 chr5 151595264 151602709 +856065 AC011374.1 chr5 151652275 151655449 +856069 SPARC chr5 151661096 151686975 +856166 CLMAT3 chr5 151676945 151725473 +856180 AC011374.2 chr5 151724831 151725356 +856183 ATOX1 chr5 151742316 151772532 +856261 AC091982.1 chr5 151753992 151767247 +856266 AC091982.3 chr5 151770242 151771508 +856270 G3BP1 chr5 151771045 151812785 +856496 GLRA1 chr5 151822513 151924842 +856573 LINC01933 chr5 151949571 152270449 +856603 AC008571.2 chr5 152374998 152726160 +856614 NMUR2 chr5 152391532 152433368 +856633 LINC01470 chr5 152618965 153223543 +856685 GRIA1 chr5 153489615 153813869 +856943 LINC01861 chr5 153887428 153898987 +856949 AC091962.1 chr5 153901459 153903223 +856952 FAM114A2 chr5 153990148 154038936 +857192 MFAP3 chr5 154038906 154220478 +857271 GALNT10 chr5 154190730 154420984 +857413 SAP30L-AS1 chr5 154325568 154445850 +857442 AC008625.1 chr5 154346042 154347834 +857446 SAP30L chr5 154445997 154461053 +857507 HAND1 chr5 154474972 154478227 +857517 AC026688.2 chr5 154483917 154486150 +857524 LARP1 chr5 154712843 154817605 +857750 FAXDC2 chr5 154818492 154859252 +857940 CNOT8 chr5 154857553 154876793 +858266 GEMIN5 chr5 154887411 154938211 +858335 MRPL22 chr5 154941073 154969411 +858429 KIF4B chr5 155013755 155018141 +858437 AC010476.2 chr5 155087430 155199252 +858451 SGCD chr5 155870344 156767788 +858537 AC011351.1 chr5 156019228 156039977 +858541 AC025434.1 chr5 156704058 156739812 +858546 PPP1R2B chr5 156850295 156852528 +858554 TIMD4 chr5 156919292 156963226 +858613 HAVCR1 chr5 157029413 157059119 +858715 HAVCR2 chr5 157085832 157142869 +858776 AC011377.1 chr5 157104788 157114900 +858780 MED7 chr5 157137424 157159019 +858808 ITK chr5 157142933 157255191 +858924 FAM71B chr5 157161846 157166264 +858934 AC010609.1 chr5 157199242 157224380 +858938 AC009185.1 chr5 157260122 157266625 +858943 CYFIP2 chr5 157266079 157395595 +859487 FNDC9 chr5 157341598 157345677 +859504 AC016571.1 chr5 157363382 157365501 +859508 AC008676.1 chr5 157375741 157384950 +859516 ADAM19 chr5 157395534 157575775 +859698 NIPAL4 chr5 157460019 157474717 +859758 AC106801.1 chr5 157565964 157569098 +859762 SOX30 chr5 157625679 157671480 +859808 C5orf52 chr5 157671533 157680158 +859820 THG1L chr5 157731420 157741449 +859864 LSM11 chr5 157743712 157760709 +859878 CLINT1 chr5 157785743 157859175 +860035 AC025437.5 chr5 158173601 158176422 +860039 AC025437.4 chr5 158175396 158200016 +860043 AC025437.3 chr5 158225352 158234376 +860050 AC025437.2 chr5 158256137 158258436 +860054 AC025437.1 chr5 158275711 158278813 +860058 LINC02227 chr5 158320683 158409773 +860067 AC091979.1 chr5 158424585 158452758 +860071 AC091979.2 chr5 158464465 158464678 +860074 AC091939.1 chr5 158485190 158588546 +860100 EBF1 chr5 158695916 159099916 +860310 AC136424.2 chr5 158983006 158984789 +860315 AC136424.1 chr5 158985806 158987199 +860320 LINC02202 chr5 159100483 159117478 +860332 RNF145 chr5 159157409 159210053 +860545 AC134043.2 chr5 159209921 159248796 +860550 LINC01932 chr5 159227715 159245127 +860555 UBLCP1 chr5 159263290 159286036 +860592 AC008691.1 chr5 159310745 159805536 +860650 IL12B chr5 159314783 159330887 +860671 LINC01845 chr5 159448556 159466291 +860684 AC008703.1 chr5 159484130 159511687 +860689 LINC01847 chr5 159698586 159937766 +860716 ADRA1B chr5 159865080 159973012 +860738 TTC1 chr5 160009113 160065543 +860806 PWWP2A chr5 160061801 160119450 +860875 FABP6 chr5 160187367 160238735 +860927 AC008609.1 chr5 160195744 160204826 +860934 CCNJL chr5 160249106 160345396 +861106 C1QTNF2 chr5 160347754 160370641 +861129 ZBED8 chr5 160393148 160400054 +861150 SLU7 chr5 160401641 160421711 +861245 PTTG1 chr5 160421855 160428739 +861320 MIR3142HG chr5 160438594 160487426 +861327 ATP10B chr5 160563120 160852214 +861504 AC008456.1 chr5 160613873 160639183 +861508 AC011363.1 chr5 160685351 160692889 +861514 LINC02159 chr5 160931778 160938626 +861523 GABRB2 chr5 161288429 161549044 +861695 GABRA6 chr5 161547063 161702593 +861794 AC091944.1 chr5 161687347 161689408 +861798 GABRA1 chr5 161847063 161899981 +862177 LINC01202 chr5 161907111 162001536 +862182 GABRG2 chr5 162000057 162162977 +862712 AC113414.1 chr5 162424042 163437326 +862791 CCNG1 chr5 163437569 163446151 +862921 NUDCD2 chr5 163446526 163460102 +862956 HMMR chr5 163460203 163491941 +863152 HMMR-AS1 chr5 163483065 163494058 +863161 MAT2B chr5 163503114 163519354 +863255 AC010291.1 chr5 163597352 163612516 +863260 AC008662.1 chr5 164119098 164234097 +863267 AC008662.2 chr5 164209631 164211892 +863271 AC109466.1 chr5 164296696 165171643 +863415 LINC02143 chr5 164448161 164467879 +863421 AC091973.1 chr5 165129307 165153014 +863427 LINC01938 chr5 165220577 165241756 +863470 AC008415.1 chr5 165349030 165778689 +863474 AC114321.1 chr5 166128498 166155439 +863479 LINC01947 chr5 166905222 166926370 +863484 AC091819.2 chr5 167116318 167119585 +863488 AC091819.1 chr5 167164934 167168401 +863492 TENM2 chr5 167284799 168264157 +863696 AC091820.2 chr5 167287320 167294273 +863700 AC091820.1 chr5 167296234 167303372 +863705 AC008601.1 chr5 167306273 167309870 +863710 AC008708.2 chr5 167653228 167660481 +863714 AC008708.1 chr5 167721363 167729124 +863718 AC008464.1 chr5 167937717 167953469 +863724 AC008705.2 chr5 167965187 167967086 +863728 AC011369.1 chr5 168085329 168187719 +863736 AC026689.1 chr5 168229583 168269415 +863745 WWC1 chr5 168291651 168472303 +864013 RARS chr5 168486451 168519301 +864149 FBLL1 chr5 168529305 168530634 +864157 PANK3 chr5 168548495 168579368 +864193 AC011365.2 chr5 168654513 168667761 +864198 SLIT3 chr5 168661733 169301129 +864465 AC011365.1 chr5 168706567 168720884 +864480 AC011389.2 chr5 168993000 168995677 +864485 AC011389.1 chr5 169013227 169037998 +864533 SPDL1 chr5 169583636 169604778 +864738 DOCK2 chr5 169637268 170083382 +865138 AC008680.1 chr5 169772966 169779365 +865142 INSYN2B chr5 169861303 169980495 +865159 FOXI1 chr5 170105897 170109734 +865178 LINC01187 chr5 170191579 170199141 +865188 C5orf58 chr5 170232447 170252575 +865244 LCP2 chr5 170246233 170297818 +865417 LINC01366 chr5 170307722 170335508 +865453 AC034199.1 chr5 170308701 170312716 +865457 KCNIP1 chr5 170353487 170736632 +865643 KCNMB1 chr5 170374671 170389634 +865668 AC027306.1 chr5 170389493 170422844 +865673 AC008619.1 chr5 170483806 170486407 +865677 AC027312.1 chr5 170639158 170681437 +865692 AC008514.1 chr5 170747047 170788650 +865704 GABRP chr5 170763350 170814047 +865875 RANBP17 chr5 170861870 171300015 +866407 AC091980.2 chr5 171305980 171309777 +866411 TLX3 chr5 171309248 171312139 +866423 NPM1 chr5 171387116 171411137 +866575 FGF18 chr5 171419647 171457626 +866591 AC022440.1 chr5 171724575 171737519 +866598 AC011410.1 chr5 171773652 171774739 +866602 SMIM23 chr5 171782432 171796126 +866654 FBXW11 chr5 171861549 172006873 +866850 STK10 chr5 172042079 172188224 +866963 EFCAB9 chr5 172194172 172203454 +866977 UBTD2 chr5 172209646 172283764 +866989 SH3PXD2B chr5 172325000 172454525 +867097 AC011407.1 chr5 172479274 172536444 +867101 LINC01944 chr5 172543403 172559202 +867110 NEURL1B chr5 172641263 172691540 +867152 AC027309.1 chr5 172690454 172697720 +867156 AC022217.2 chr5 172755457 172762587 +867166 AC022217.3 chr5 172762980 172782334 +867177 DUSP1 chr5 172768096 172771195 +867191 AC110011.1 chr5 172816592 172819958 +867202 ERGIC1 chr5 172834251 172952683 +867345 AC008429.1 chr5 172954786 172959392 +867366 AC008429.3 chr5 172954907 172957162 +867371 RPL26L1 chr5 172958729 172969771 +867440 ATP6V0E1 chr5 172983771 173035445 +867487 CREBRF chr5 173056352 173139284 +867557 AC008378.1 chr5 173144162 173145039 +867561 BNIP1 chr5 173144442 173164387 +867636 NKX2-5 chr5 173232109 173235311 +867671 STC2 chr5 173314713 173329503 +867710 AC016573.1 chr5 173383941 173451591 +867751 AC008632.1 chr5 173463484 173484584 +867763 AC008663.1 chr5 173562478 173573199 +867768 AC008663.3 chr5 173574938 173576275 +867772 AC008663.2 chr5 173578275 173585068 +867790 BOD1 chr5 173607145 173616659 +867849 LINC01863 chr5 173642519 173658194 +867853 LINC01942 chr5 173689459 173705849 +867858 LINC01484 chr5 173707614 173746279 +867896 AC008674.1 chr5 173757562 173773164 +867900 LINC01485 chr5 173778527 173809039 +867935 CPEB4 chr5 173888349 173961980 +868141 C5orf47 chr5 173973779 174006140 +868162 NSG2 chr5 174045706 174243501 +868261 AC113423.1 chr5 174056060 174056585 +868265 AC113423.2 chr5 174081506 174086618 +868282 AC011333.1 chr5 174173101 174181814 +868286 AC025752.1 chr5 174329612 174330503 +868290 LINC01411 chr5 174336295 174532457 +868327 AC108112.1 chr5 174618164 174625775 +868333 MSX2 chr5 174724582 174730896 +868352 AC113346.2 chr5 174751304 174850725 +868358 AC113346.1 chr5 174820027 174826324 +868362 LINC01951 chr5 174919082 174995513 +868367 AC008413.2 chr5 174986295 174987050 +868371 DRD1 chr5 175440036 175444182 +868381 AC091393.2 chr5 175471414 175475378 +868385 SFXN1 chr5 175477062 175529742 +868522 HRH2 chr5 175658030 175710756 +868560 CPLX2 chr5 175796310 175884021 +868674 AC138965.2 chr5 175906939 175958538 +868678 THOC3 chr5 175917873 176034680 +868812 AC138965.1 chr5 175972606 175987666 +868826 AC139491.3 chr5 176036593 176042888 +868834 AC139491.1 chr5 176049678 176062021 +868839 FAM153B chr5 176060689 176116015 +869121 AC139491.4 chr5 176124210 176131461 +869125 AC139491.8 chr5 176158610 176168367 +869135 AC139493.2 chr5 176173345 176199295 +869173 SIMC1 chr5 176238367 176345991 +869318 KIAA1191 chr5 176346062 176361807 +869489 AC138956.1 chr5 176347941 176353584 +869494 AC138956.2 chr5 176354206 176356168 +869498 ARL10 chr5 176365487 176401865 +869529 NOP16 chr5 176383938 176388975 +869647 HIGD2A chr5 176388751 176389761 +869657 CLTB chr5 176392455 176416569 +869743 FAF2 chr5 176447628 176510074 +869799 RNF44 chr5 176526712 176538025 +869895 CDHR2 chr5 176542511 176595974 +870133 GPRIN1 chr5 176595802 176610156 +870143 SNCB chr5 176620082 176630556 +870235 EIF4E1B chr5 176630618 176646644 +870355 TSPAN17 chr5 176647387 176659054 +870525 AC113391.1 chr5 176707356 176726243 +870529 AC113391.2 chr5 176726942 176739458 +870535 LINC01574 chr5 176743205 176743871 +870539 UNC5A chr5 176810519 176880898 +870633 HK3 chr5 176880869 176899346 +870720 UIMC1 chr5 176905005 177022633 +870953 ZNF346 chr5 177022696 177081189 +871097 ZNF346-IT1 chr5 177051714 177052963 +871101 FGFR4 chr5 177086905 177098144 +871359 NSD1 chr5 177133025 177300215 +871663 AC146507.3 chr5 177260340 177263909 +871667 RAB24 chr5 177301198 177303744 +871770 MXD3 chr5 177301461 177312757 +871885 PRELID1 chr5 177303799 177306949 +871964 LMAN2 chr5 177331567 177351668 +872065 RGS14 chr5 177357924 177372596 +872183 SLC34A1 chr5 177379235 177398848 +872265 PFN3 chr5 177400109 177400661 +872273 F12 chr5 177402140 177409576 +872331 GRK6 chr5 177403204 177442901 +872599 PRR7-AS1 chr5 177438503 177447699 +872615 PRR7 chr5 177446445 177456286 +872660 DBN1 chr5 177456608 177474401 +872855 PDLIM7 chr5 177483394 177497606 +873122 AC145098.1 chr5 177494995 177503647 +873126 DOK3 chr5 177501907 177511274 +873274 DDX41 chr5 177511577 177516961 +873594 FAM193B chr5 177519789 177554563 +873799 AC139795.3 chr5 177554824 177555364 +873802 TMED9 chr5 177592203 177597242 +873839 B4GALT7 chr5 177600132 177610330 +873913 AC139795.2 chr5 177611240 177619754 +873926 AC138819.1 chr5 177682294 177713969 +873931 FAM153A chr5 177707981 177783398 +874361 AC140125.2 chr5 177782197 177794396 +874366 AC140125.1 chr5 177801204 177803344 +874370 AC140125.3 chr5 177856262 177871227 +874384 AC106795.3 chr5 177939622 177983054 +874388 AC106795.2 chr5 177950335 177963960 +874408 AC106795.5 chr5 177967004 177967457 +874411 PROP1 chr5 177992235 177996242 +874423 FAM153CP chr5 178006348 178086529 +875018 N4BP3 chr5 178113532 178126081 +875034 RMND5B chr5 178130996 178150568 +875211 NHP2 chr5 178149460 178153967 +875266 GMCL2 chr5 178184503 178187432 +875274 HNRNPAB chr5 178204533 178211163 +875413 PHYKPL chr5 178208471 178232802 +875649 COL23A1 chr5 178237618 178590393 +875777 AC136601.1 chr5 178350867 178352250 +875781 AC008659.1 chr5 178438681 178443094 +875785 CLK4 chr5 178602664 178630615 +876007 AC113348.3 chr5 178690804 178693681 +876012 AC113348.1 chr5 178694605 178697695 +876026 ZNF354A chr5 178711512 178730659 +876068 ZNF354B chr5 178859953 178888122 +876103 ZFP2 chr5 178895898 178933212 +876173 AC104117.5 chr5 178938677 178939223 +876176 ZNF454 chr5 178941191 178966433 +876212 AC104117.3 chr5 178969390 178990116 +876216 GRM6 chr5 178977587 178996206 +876307 ZNF879 chr5 179023804 179035064 +876358 ZNF354C chr5 179060373 179083977 +876374 ADAMTS2 chr5 179110853 179345461 +876505 AC109479.3 chr5 179377505 179378865 +876509 AC109479.1 chr5 179377531 179378761 +876513 AC136628.1 chr5 179455415 179456095 +876517 AC136628.4 chr5 179503322 179515579 +876521 RUFY1 chr5 179550554 179610012 +876765 AC136604.2 chr5 179595904 179603741 +876776 HNRNPH1 chr5 179614178 179634784 +877373 C5orf60 chr5 179641544 179645046 +877413 AC136604.3 chr5 179657762 179665136 +877430 CBY3 chr5 179678560 179681034 +877440 CANX chr5 179678628 179731641 +877741 MAML1 chr5 179732822 179777283 +877764 LTC4S chr5 179793980 179796647 +877836 MGAT4B chr5 179797597 179806952 +878149 SQSTM1 chr5 179806398 179838078 +878308 MRNIP chr5 179835133 179862173 +878629 AC008393.1 chr5 179859013 179861283 +878633 TBC1D9B chr5 179862066 179907859 +878851 RNF130 chr5 179911651 180072113 +878954 AC010285.1 chr5 179963615 179964419 +878958 AC010285.3 chr5 179974584 179980186 +878963 RASGEF1C chr5 180100795 180209211 +879132 MAPK9 chr5 180233143 180292099 +879390 AC008610.1 chr5 180293245 180295253 +879394 GFPT2 chr5 180300698 180353336 +879484 AC034213.1 chr5 180416949 180443240 +879494 CNOT6 chr5 180494379 180578358 +879614 SCGB3A1 chr5 180590105 180591499 +879629 FLT4 chr5 180601506 180649624 +879964 LINC02222 chr5 180684766 180686546 +879968 OR2Y1 chr5 180739042 180740099 +879976 MGAT1 chr5 180784782 180815652 +880133 HEIH chr5 180826871 180831605 +880140 LINC00847 chr5 180830326 180839742 +880222 AC022413.2 chr5 180833928 180835726 +880229 ZFP62 chr5 180847611 180861285 +880284 BTNL8 chr5 180899077 180950906 +880466 BTNL3 chr5 180988846 181006727 +880488 BTNL9 chr5 181040225 181061521 +880602 OR2V1 chr5 181123122 181131169 +880651 OR2V2 chr5 181147586 181159285 +880678 LINC01962 chr5 181178821 181191852 +880689 AC008443.5 chr5 181191875 181194429 +880700 TRIM7 chr5 181193924 181205293 +880788 AC008443.6 chr5 181195496 181203103 +880808 AC008443.4 chr5 181205361 181206120 +880812 AC008443.9 chr5 181207480 181217864 +880816 TRIM41 chr5 181222499 181235808 +880915 AC008443.2 chr5 181224646 181230685 +880919 RACK1 chr5 181236897 181248096 +881345 AC008443.1 chr5 181246507 181272167 +881363 TRIM52 chr5 181254417 181261139 +881387 TRIM52-AS1 chr5 181261169 181272307 +881405 AC008443.8 chr5 181276848 181277555 +881408 AC008443.3 chr5 181281375 181283652 +881412 AC138035.1 chr5 181306502 181324685 +881434 AC138035.2 chr5 181329241 181342213 +881439 OR4F3 chr5 181367268 181368262 +881447 AL035696.3 chr6 181466 205519 +881467 AL035696.4 chr6 184339 186899 +881471 AL035696.1 chr6 203313 206392 +881478 AL365272.1 chr6 285443 292013 +881483 DUSP22 chr6 291630 351355 +881679 IRF4 chr6 391752 411443 +881741 AL512308.1 chr6 453391 477829 +881745 EXOC2 chr6 485154 693139 +881826 AL031770.1 chr6 524171 525581 +881830 HUS1B chr6 655939 656963 +881838 AL357054.2 chr6 692530 796781 +881856 AL357054.4 chr6 708592 711405 +881859 AL357054.5 chr6 729128 760936 +881863 AL357054.3 chr6 761675 780648 +881868 AL392183.1 chr6 774747 780214 +881872 AL356130.1 chr6 905445 909006 +881876 LINC01622 chr6 958323 1101400 +881911 AL033381.2 chr6 1026494 1027225 +881914 AL033381.1 chr6 1079929 1104946 +881919 AL033381.3 chr6 1111367 1114329 +881923 FOXQ1 chr6 1312098 1314758 +881931 LINC01394 chr6 1321698 1324022 +881935 AL034346.1 chr6 1383790 1385066 +881938 FOXF2 chr6 1389576 1395603 +881948 AL512329.2 chr6 1528364 1528911 +881951 FOXCUT chr6 1601654 1607354 +881958 FOXC1 chr6 1609915 1613897 +881966 GMDS chr6 1623806 2245605 +882058 AL035693.1 chr6 2227803 2230261 +882062 GMDS-DT chr6 2245718 2525976 +882252 AL031768.2 chr6 2353427 2386110 +882257 AL031768.1 chr6 2437549 2438249 +882260 AL359852.2 chr6 2503797 2528665 +882267 LINC02521 chr6 2617144 2640001 +882279 LINC01600 chr6 2621913 2634619 +882296 MYLK4 chr6 2663629 2750922 +882357 WRNIP1 chr6 2765393 2786952 +882451 SERPINB1 chr6 2832332 2841959 +882493 SERPINB9P1 chr6 2851230 2881407 +882532 SERPINB9 chr6 2887270 2903309 +882552 AL133351.2 chr6 2916894 2917733 +882556 SERPINB6 chr6 2948159 2972165 +882941 LINC01011 chr6 2987967 2991173 +882955 NQO2 chr6 2987987 3028869 +883113 AL133351.1 chr6 2989335 2999604 +883130 AL031963.2 chr6 3055849 3057357 +883134 RIPK1 chr6 3063991 3115187 +883195 AL031963.3 chr6 3068045 3068894 +883198 BPHL chr6 3118374 3153578 +883370 AL031963.1 chr6 3138394 3153062 +883374 TUBB2A chr6 3153666 3157544 +883393 LINC02525 chr6 3182626 3195784 +883405 TUBB2B chr6 3224277 3231730 +883424 PSMG4 chr6 3231403 3303373 +883523 SLC22A23 chr6 3268962 3457022 +883730 AL445309.1 chr6 3311662 3313650 +883733 AL033523.1 chr6 3585101 3720081 +883911 PXDC1 chr6 3722614 3752026 +883950 AL391422.4 chr6 3751111 3753871 +883953 AL391422.3 chr6 3831933 3855737 +883960 AL391422.2 chr6 3831936 3894292 +883973 FAM50B chr6 3849373 3851320 +883990 AL590004.3 chr6 3904920 3911979 +883993 AL138831.2 chr6 4018713 4019202 +883996 AL138831.1 chr6 4018843 4021215 +884000 PRPF4B chr6 4021267 4064983 +884157 FAM217A chr6 4049434 4087344 +884243 C6orf201 chr6 4079206 4130951 +884305 ECI2 chr6 4115689 4135597 +884515 AL136309.4 chr6 4135423 4146053 +884519 AL136309.2 chr6 4136072 4157385 +884525 AL136309.3 chr6 4185479 4188950 +884530 AL162718.1 chr6 4304942 4583871 +884537 AL159166.1 chr6 4341756 4347162 +884557 AL162718.3 chr6 4381211 4383597 +884561 AL162718.2 chr6 4449392 4468181 +884566 LINC02533 chr6 4491807 4495769 +884570 AL034376.2 chr6 4599287 4602420 +884574 AL034376.1 chr6 4610612 4611919 +884578 CDYL chr6 4706159 4955551 +884690 AL356747.1 chr6 4714098 4724885 +884695 AL022725.1 chr6 4774526 4775408 +884699 RPP40 chr6 4994717 5004063 +884806 AL359643.3 chr6 5003774 5080946 +884882 AL359643.2 chr6 5031756 5054423 +884886 PPP1R3G chr6 5084581 5089487 +884894 LYRM4 chr6 5102593 5260939 +884970 FARS2 chr6 5261044 5829192 +885050 AL021328.1 chr6 5451683 5458075 +885058 AL022097.1 chr6 5664985 5695272 +885064 AL136307.1 chr6 5851506 5870220 +885069 NRN1 chr6 5997999 6007605 +885111 F13A1 chr6 6144085 6321013 +885195 LY86-AS1 chr6 6346465 6622771 +885265 AL162719.1 chr6 6450356 6507443 +885271 LY86 chr6 6588108 6654983 +885304 AL031123.2 chr6 6680309 6683633 +885307 AL031123.1 chr6 6692741 6739030 +885334 AL031123.4 chr6 6710891 6713970 +885338 AL031123.5 chr6 6725036 6733191 +885342 AL136361.1 chr6 6758276 6759291 +885346 AL158817.1 chr6 6901022 6918715 +885350 AL139390.1 chr6 6993191 6995727 +885355 RREB1 chr6 7107597 7251980 +885565 AL355336.1 chr6 7183083 7185287 +885569 AL139095.5 chr6 7258910 7261993 +885573 SSR1 chr6 7268306 7347446 +885756 AL139095.4 chr6 7276031 7298872 +885761 CAGE1 chr6 7326656 7389742 +885999 RIOK1 chr6 7389793 7418037 +886081 AL031058.1 chr6 7540451 7541338 +886084 DSP chr6 7541617 7586714 +886196 SNRNP48 chr6 7590198 7611967 +886247 BMP6 chr6 7726099 7881728 +886267 TXNDC5 chr6 7881517 7910788 +886331 BLOC1S5 chr6 8013567 8064396 +886402 EEF1E1 chr6 8073360 8102559 +886467 AL355499.1 chr6 8102711 8343139 +886523 AL359378.1 chr6 8341937 8389183 +886545 SLC35B3 chr6 8411463 8435611 +886683 HULC chr6 8435568 9294133 +887438 AL137220.1 chr6 9124221 9161777 +887443 TFAP2A chr6 10393186 10419659 +887659 TFAP2A-AS2 chr6 10404502 10407928 +887662 TFAP2A-AS1 chr6 10409340 10416446 +887670 AL138885.2 chr6 10423140 10426176 +887675 AL138885.3 chr6 10426623 10429110 +887680 LINC00518 chr6 10429255 10435015 +887711 MIR5689HG chr6 10434316 10456781 +887720 LINC02522 chr6 10474500 10478502 +887724 GCNT2 chr6 10492223 10629368 +887842 AL139039.3 chr6 10511036 10514546 +887846 AL358777.1 chr6 10659498 10692860 +887854 C6orf52 chr6 10671418 10694797 +887932 PAK1IP1 chr6 10694972 10709782 +887958 TMEM14C chr6 10722915 10731129 +888009 AL024498.1 chr6 10743324 10747663 +888019 TMEM14B chr6 10747759 10852753 +888266 MAK chr6 10762723 10838555 +888432 GCM2 chr6 10873223 10881941 +888448 AL357497.1 chr6 10881780 10884349 +888453 SYCP2L chr6 10886831 10979320 +888677 ELOVL2 chr6 10980759 11044305 +888699 ELOVL2-AS1 chr6 11043482 11079154 +888742 SMIM13 chr6 11093834 11138733 +888763 ERVFRD-1 chr6 11102489 11111725 +888780 AL139807.1 chr6 11173452 11259099 +888787 NEDD9 chr6 11183298 11382348 +888946 AL022098.1 chr6 11291299 11296224 +888950 AL445430.2 chr6 11414636 11515710 +888962 AL445430.1 chr6 11417207 11481324 +888986 TMEM170B chr6 11537749 11583524 +888998 AL357518.1 chr6 11607552 11607981 +889001 ADTRP chr6 11712054 11807046 +889118 AL022724.3 chr6 11722547 11731923 +889128 AL022724.2 chr6 11810602 11811248 +889132 AL157373.1 chr6 11990338 12001286 +889137 AL157373.2 chr6 12007670 12008856 +889145 HIVEP1 chr6 12008762 12164999 +889283 EDN1 chr6 12290361 12297194 +889299 LINC02530 chr6 12582915 12585404 +889303 PHACTR1 chr6 12716805 13290484 +889441 AL008729.1 chr6 13264861 13295586 +889461 TBC1D7 chr6 13266542 13328583 +889765 AL008729.2 chr6 13290018 13290490 +889768 GFOD1 chr6 13357830 13487662 +889811 GFOD1-AS1 chr6 13486294 13486852 +889815 SIRT5 chr6 13574529 13615158 +889954 AL441883.1 chr6 13614111 13615155 +889957 NOL7 chr6 13615335 13632739 +890000 RANBP9 chr6 13621498 13711835 +890038 Z93020.1 chr6 13671720 13678908 +890042 MCUR1 chr6 13786557 13814568 +890108 AL023583.1 chr6 13825432 13826574 +890111 RNF182 chr6 13924446 13980310 +890190 AL022396.1 chr6 14004920 14006901 +890194 CD83 chr6 14117256 14136918 +890225 AL133259.1 chr6 14152196 14211186 +890229 AL353152.2 chr6 14210293 14214374 +890233 AL353152.1 chr6 14229775 14231570 +890237 LINC01108 chr6 14280127 14285454 +890245 AL080313.2 chr6 14391094 14393929 +890252 AL080313.1 chr6 14394326 14404289 +890257 AL009177.1 chr6 14431683 14502701 +890262 AL109914.1 chr6 14597514 14599690 +890266 AL138720.1 chr6 14661829 15090170 +890300 AL136162.1 chr6 15243923 15245000 +890303 JARID2 chr6 15246069 15522042 +890393 JARID2-AS1 chr6 15247815 15248634 +890397 DTNBP1 chr6 15522801 15663058 +890634 AL021978.1 chr6 15555780 15559980 +890638 LINC02543 chr6 15994944 15999797 +890642 MYLIP chr6 16129086 16148248 +890679 GMPR chr6 16238587 16295549 +890715 AL009031.1 chr6 16259101 16264553 +890722 ATXN1 chr6 16299112 16761491 +890823 AL137003.1 chr6 16761138 16762652 +890831 AL137003.2 chr6 16764346 16766883 +890834 AL133405.2 chr6 16901104 16952699 +890839 AL133405.1 chr6 17015817 17034396 +890844 AL138740.1 chr6 17092714 17108156 +890849 STMND1 chr6 17102258 17131372 +890880 AL136305.1 chr6 17224243 17281424 +890884 RBM24 chr6 17281361 17293871 +890958 CAP2 chr6 17393505 17557790 +891198 AL138824.1 chr6 17586899 17600191 +891207 FAM8A1 chr6 17600302 17611715 +891223 NUP153 chr6 17615035 17706834 +891370 AL138724.1 chr6 17706257 17707344 +891373 KIF13A chr6 17759183 17987635 +891906 NHLRC1 chr6 18120440 18122677 +891914 TPMT chr6 18128311 18155077 +891938 KDM1B chr6 18155329 18223854 +892097 DEK chr6 18223860 18264548 +892344 RNF144B chr6 18387350 18468874 +892370 MIR548A1HG chr6 18522735 18674001 +892388 AL357052.1 chr6 19290319 19321021 +892392 AL022068.1 chr6 19323428 19839080 +892582 ID4 chr6 19837370 19842197 +892594 AL022726.1 chr6 19892397 19894214 +892598 MBOAT1 chr6 20099684 20212469 +892630 AL158198.1 chr6 20212087 20317739 +892635 AL158198.2 chr6 20265720 20307200 +892639 AL132775.1 chr6 20321461 20333193 +892643 AL132775.2 chr6 20329922 20334411 +892651 E2F3 chr6 20401879 20493714 +892705 E2F3-IT1 chr6 20437821 20440178 +892709 CDKAL1 chr6 20534457 21232404 +892801 AL513188.1 chr6 20756103 20800694 +892808 AL451080.1 chr6 21233168 21271132 +892812 AL031767.1 chr6 21354411 21355296 +892816 AL031767.2 chr6 21369690 21383200 +892820 LINC00581 chr6 21485896 21521414 +892832 AL512380.1 chr6 21521678 21523783 +892838 AL512380.2 chr6 21528739 21595593 +892843 SOX4 chr6 21593751 21598619 +892851 CASC15 chr6 21664185 22654455 +893665 NBAT1 chr6 22133205 22147193 +893670 PRL chr6 22287244 22302826 +893746 HDGFL1 chr6 22569566 22571666 +893754 AL033539.1 chr6 22589137 22593833 +893759 AL033539.2 chr6 22663507 22675493 +893763 AL035401.1 chr6 22744395 23031780 +893768 AL139231.1 chr6 23337711 23404132 +893778 NRSN1 chr6 24126186 24154900 +893837 DCDC2 chr6 24171755 24358059 +893883 KAAG1 chr6 24356903 24358285 +893891 MRS2 chr6 24402908 24426194 +894020 GPLD1 chr6 24424565 24495205 +894113 ALDH5A1 chr6 24494867 24537207 +894262 KIAA0319 chr6 24544104 24646191 +894535 TDP2 chr6 24649979 24666930 +894584 ACOT13 chr6 24667035 24705065 +894613 AL031775.1 chr6 24700907 24701793 +894616 C6orf62 chr6 24704861 24719998 +894647 AL031775.2 chr6 24706747 24707151 +894650 LINC02828 chr6 24721658 24751960 +894666 GMNN chr6 24774931 24786099 +894766 ARMH2 chr6 24797335 24798917 +894776 RIPOR2 chr6 24804282 25042170 +895277 AL160400.1 chr6 25012985 25015696 +895283 AL133268.3 chr6 25041839 25056664 +895288 AL133268.2 chr6 25053627 25057073 +895294 AL133268.4 chr6 25061796 25134971 +895302 CARMIL1 chr6 25279078 25620530 +895467 AL022170.1 chr6 25632673 25640931 +895472 SCGN chr6 25652201 25701783 +895547 HIST1H2AA chr6 25726132 25726527 +895554 HIST1H2BA chr6 25726777 25727292 +895562 SLC17A4 chr6 25754699 25781199 +895642 SLC17A1 chr6 25782902 25832052 +895756 SLC17A3 chr6 25833066 25882286 +895918 SLC17A2 chr6 25912754 25930726 +896002 TRIM38 chr6 25962802 25991231 +896024 U91328.2 chr6 25983812 25999167 +896028 U91328.1 chr6 25992641 26001775 +896067 U91328.3 chr6 26013241 26013757 +896070 HIST1H1A chr6 26017085 26017732 +896077 HIST1H3A chr6 26020490 26020900 +896084 HIST1H4A chr6 26021679 26021990 +896091 HIST1H4B chr6 26026815 26027252 +896098 HIST1H3B chr6 26031594 26032099 +896106 HIST1H2AB chr6 26033176 26033568 +896113 HIST1H2BB chr6 26043277 26043657 +896120 HIST1H3C chr6 26045411 26045869 +896127 HIST1H1C chr6 26055787 26056428 +896134 HFE chr6 26087281 26098343 +896327 HIST1H4C chr6 26103876 26104310 +896335 HIST1H1T chr6 26107419 26108136 +896343 HIST1H2BC chr6 26114873 26123926 +896360 HIST1H2AC chr6 26124145 26139116 +896388 HIST1H1E chr6 26156354 26157107 +896396 HIST1H2BD chr6 26158146 26171349 +896413 AL353759.1 chr6 26160765 26172802 +896418 HIST1H2BE chr6 26172059 26184655 +896439 HIST1H4D chr6 26188765 26189076 +896446 HIST1H3D chr6 26196840 26197250 +896453 HIST1H2AD chr6 26198851 26199243 +896460 HIST1H2BF chr6 26199520 26200715 +896468 HIST1H4E chr6 26204552 26206038 +896476 HIST1H2BG chr6 26215159 26216692 +896484 HIST1H2AE chr6 26216975 26217483 +896491 HIST1H3E chr6 26224199 26227473 +896507 HIST1H1D chr6 26234268 26234933 +896514 HIST1H4F chr6 26240426 26240737 +896521 HIST1H4G chr6 26246681 26246977 +896528 HIST1H3F chr6 26250195 26250605 +896535 HIST1H2BH chr6 26251651 26253710 +896542 HIST1H3G chr6 26269405 26271815 +896550 HIST1H2BI chr6 26272976 26273356 +896557 HIST1H4H chr6 26277609 26285638 +896594 AL021917.1 chr6 26324705 26331900 +896599 BTN3A2 chr6 26365159 26378320 +896855 BTN2A2 chr6 26383096 26394874 +897067 BTN3A1 chr6 26402237 26415208 +897221 BTN3A3 chr6 26440472 26453415 +897387 BTN2A1 chr6 26457904 26476621 +897513 BTN1A1 chr6 26501221 26510422 +897554 HCG11 chr6 26521709 26527404 +897557 HMGN4 chr6 26538366 26546933 +897570 AL121936.1 chr6 26569324 26574698 +897574 ABT1 chr6 26596953 26600739 +897586 AL513548.3 chr6 26602733 26606661 +897592 ZNF322 chr6 26634383 26659752 +897675 AL513548.4 chr6 26677003 26683211 +897679 AL513548.1 chr6 26686241 26687964 +897682 LINC00240 chr6 26956932 27059749 +897753 AL133255.1 chr6 27001208 27001648 +897756 AL590062.1 chr6 27018935 27020280 +897759 AL021807.1 chr6 27122657 27123221 +897762 HIST1H2BJ chr6 27125897 27132750 +897784 HIST1H2AG chr6 27133042 27135291 +897792 HIST1H4I chr6 27138588 27139881 +897800 HIST1H2BK chr6 27146418 27146798 +897807 HIST1H2AH chr6 27147129 27147515 +897814 PRSS16 chr6 27247701 27256624 +898007 POM121L2 chr6 27285903 27312170 +898021 ZNF391 chr6 27374615 27403904 +898051 AL031118.1 chr6 27404010 27406964 +898054 ZNF184 chr6 27450743 27473118 +898089 AL021918.4 chr6 27454568 27457575 +898093 AL021918.5 chr6 27473194 27494436 +898098 AL021918.3 chr6 27491422 27519435 +898104 AL009179.3 chr6 27679971 27680555 +898107 AL009179.1 chr6 27694035 27713352 +898130 AL009179.2 chr6 27759870 27763184 +898135 HIST1H2BL chr6 27807444 27807931 +898143 HIST1H2AI chr6 27808199 27808701 +898151 HIST1H3H chr6 27810064 27811300 +898159 HIST1H2AJ chr6 27814354 27814740 +898166 HIST1H2BM chr6 27815044 27815424 +898173 HIST1H4J chr6 27824108 27824480 +898181 HIST1H4K chr6 27831216 27831527 +898188 HIST1H2BN chr6 27837760 27865798 +898226 HIST1H2AK chr6 27837947 27838339 +898233 HIST1H2AL chr6 27865355 27865747 +898240 HIST1H1B chr6 27866849 27867529 +898247 HIST1H3I chr6 27871905 27872315 +898254 HIST1H4L chr6 27873199 27873510 +898261 HIST1H3J chr6 27890382 27893106 +898271 HIST1H2AM chr6 27892757 27893149 +898278 HIST1H2BO chr6 27893463 27893843 +898285 OR2B2 chr6 27911185 27912396 +898293 OR2B6 chr6 27957241 27958182 +898300 ZSCAN16-AS1 chr6 28015122 28137293 +898318 AL121944.1 chr6 28078792 28081130 +898322 ZNF165 chr6 28080568 28089563 +898335 ZSCAN16 chr6 28124609 28130082 +898349 AL358933.1 chr6 28136849 28139678 +898352 ZKSCAN8 chr6 28141883 28159460 +898425 ZSCAN9 chr6 28224886 28233482 +898529 ZKSCAN4 chr6 28241697 28252269 +898545 NKAPL chr6 28259297 28260958 +898553 ZSCAN26 chr6 28267010 28278224 +898637 PGBD1 chr6 28281572 28302549 +898657 ZSCAN31 chr6 28324693 28356271 +898866 ZKSCAN3 chr6 28349947 28369172 +898918 ZSCAN12 chr6 28378955 28399734 +898951 ZSCAN23 chr6 28431930 28443502 +898982 Z98745.2 chr6 28476996 28489455 +898986 Z98745.1 chr6 28489896 28491661 +898990 GPX6 chr6 28503296 28528215 +899045 GPX5 chr6 28525925 28534952 +899086 ZBED9 chr6 28570535 28616212 +899129 AL049543.1 chr6 28587378 28591747 +899133 AL121932.2 chr6 28634861 28649538 +899143 LINC00533 chr6 28648286 28649066 +899147 AL662890.1 chr6 28837869 28839006 +899151 LINC01623 chr6 28859625 28864630 +899161 HCG14 chr6 28896530 28897322 +899165 TRIM27 chr6 28903002 28923988 +899240 LINC01556 chr6 28943877 28944537 +899244 HCG15 chr6 28986203 28987484 +899249 AL662791.1 chr6 28986800 28988536 +899253 ZNF311 chr6 28994785 29005316 +899280 AL662791.2 chr6 29036021 29076524 +899295 OR2W1 chr6 29044213 29045240 +899303 OR2B3 chr6 29086208 29087313 +899311 OR2J1 chr6 29099657 29102701 +899328 OR2J3 chr6 29108059 29114770 +899364 AL645937.2 chr6 29124210 29128908 +899368 AL645937.4 chr6 29162475 29166201 +899371 OR2J2 chr6 29170907 29175811 +899388 OR14J1 chr6 29301701 29313017 +899405 OR5V1 chr6 29353749 29431967 +899435 OR12D3 chr6 29373423 29375291 +899443 OR12D2 chr6 29395631 29398008 +899460 OR11A1 chr6 29425504 29457071 +899501 OR10C1 chr6 29439306 29440977 +899515 OR2H1 chr6 29457181 29464328 +899571 MAS1L chr6 29486697 29487956 +899579 LINC02829 chr6 29497475 29510558 +899589 LINC01015 chr6 29528721 29533665 +899612 OR2I1P chr6 29550407 29557721 +899628 UBD chr6 29555515 29559732 +899638 GABBR1 chr6 29555629 29633976 +900078 OR2H2 chr6 29585121 29590500 +900095 MOG chr6 29657002 29672372 +900382 ZFP57 chr6 29672392 29681110 +900425 HLA-F chr6 29722775 29738528 +900568 HLA-F-AS1 chr6 29726601 29749049 +900586 AL645939.4 chr6 29751965 29752207 +900589 AL645939.5 chr6 29752573 29763295 +900593 HLA-G chr6 29826967 29831125 +900710 AL645929.2 chr6 29871895 29873783 +900713 HLA-A chr6 29941260 29945884 +900840 HCG9 chr6 29975112 29978410 +900848 ZNRD1 chr6 30058899 30064909 +900915 PPP1R11 chr6 30066709 30070333 +900986 RNF39 chr6 30070266 30075887 +901015 TRIM31 chr6 30102897 30113090 +901065 TRIM31-AS1 chr6 30105240 30114724 +901071 TRIM40 chr6 30136124 30148735 +901122 TRIM10 chr6 30151943 30161211 +901163 TRIM15 chr6 30163206 30172693 +901226 TRIM26 chr6 30184455 30213427 +901340 HCG17 chr6 30234039 30326134 +901350 HCG18 chr6 30286690 30327382 +901514 TRIM39 chr6 30326479 30343729 +901692 RPP21 chr6 30345131 30346884 +901775 AL662873.1 chr6 30451139 30456212 +901779 HLA-E chr6 30489509 30494194 +901808 LINC02569 chr6 30516266 30519217 +901812 GNL1 chr6 30541377 30557174 +901866 PRR3 chr6 30556886 30563723 +901908 ABCF1 chr6 30571393 30597179 +902106 PPP1R10 chr6 30600413 30618612 +902174 MRPS18B chr6 30617840 30626395 +902213 ATAT1 chr6 30626842 30646823 +902421 C6orf136 chr6 30647039 30653210 +902587 DHX16 chr6 30653119 30673006 +902681 PPP1R18 chr6 30676389 30687895 +902737 NRM chr6 30688047 30691420 +902807 MDC1 chr6 30699807 30717447 +902913 MDC1-AS1 chr6 30703067 30713184 +902918 TUBB chr6 30720352 30725426 +902971 AL662797.1 chr6 30723105 30723877 +902974 FLOT1 chr6 30727709 30742732 +903133 IER3-AS1 chr6 30742929 30743592 +903137 IER3 chr6 30743199 30744548 +903154 HCG20 chr6 30743790 30792250 +903174 LINC00243 chr6 30798654 30830659 +903181 LINC02570 chr6 30839526 30848159 +903186 DDR1-DT chr6 30866982 30875918 +903190 DDR1 chr6 30876421 30900156 +904183 GTF2H4 chr6 30908207 30914106 +904274 VARS2 chr6 30914205 30926459 +904628 SFTA2 chr6 30931353 30955636 +904660 MUCL3 chr6 30934523 30954221 +904701 HCG21 chr6 30945979 30954862 +904706 MUC21 chr6 30983718 30989903 +904729 MUC22 chr6 31010474 31035402 +904743 HCG22 chr6 31053450 31059890 +904770 C6orf15 chr6 31111223 31112575 +904780 PSORS1C1 chr6 31114750 31140092 +904841 CDSN chr6 31115087 31120446 +904851 PSORS1C2 chr6 31137534 31139066 +904861 CCHCR1 chr6 31142439 31158238 +905375 TCF19 chr6 31158547 31167159 +905415 POU5F1 chr6 31164337 31180731 +905522 PSORS1C3 chr6 31173735 31177899 +905527 AL662844.4 chr6 31195200 31198037 +905530 HCG27 chr6 31197760 31203968 +905546 AL662844.3 chr6 31200165 31201918 +905550 HLA-C chr6 31268749 31272130 +905666 HLA-B chr6 31269491 31357188 +905746 LINC02571 chr6 31293908 31301642 +905752 AL671883.3 chr6 31367057 31376088 +905756 AL645933.2 chr6 31394289 31395495 +905759 MICA chr6 31399784 31415315 +905807 HCP5 chr6 31400700 31478903 +905831 LINC01149 chr6 31441667 31446973 +905835 AL645933.3 chr6 31479973 31494935 +905842 MICB chr6 31494881 31511124 +905898 MCCD1 chr6 31528962 31530232 +905908 DDX39B chr6 31530219 31542448 +906189 DDX39B-AS1 chr6 31542304 31543138 +906196 ATP6V1G2 chr6 31544462 31548427 +906246 NFKBIL1 chr6 31546870 31558829 +906303 LTA chr6 31572054 31574324 +906338 TNF chr6 31575565 31578336 +906352 LTB chr6 31580525 31582522 +906384 LST1 chr6 31586124 31588909 +906598 NCR3 chr6 31588895 31593006 +906663 AIF1 chr6 31615217 31617021 +906716 PRRC2A chr6 31620715 31637771 +906901 BAG6 chr6 31639028 31652705 +907482 APOM chr6 31652416 31658210 +907532 C6orf47 chr6 31658298 31660778 +907540 C6orf47-AS1 chr6 31658329 31660721 +907544 GPANK1 chr6 31661228 31666283 +907635 CSNK2B chr6 31665236 31670343 +907731 LY6G5B chr6 31670167 31673776 +907755 LY6G5C chr6 31676684 31684040 +907803 ABHD16A chr6 31686955 31703356 +908109 LY6G6F chr6 31706885 31710595 +908127 LY6G6E chr6 31711771 31714065 +908167 LY6G6D chr6 31715356 31717804 +908189 MPIG6B chr6 31718594 31726714 +908328 LY6G6C chr6 31718648 31721746 +908353 DDAH2 chr6 31727038 31730617 +908476 CLIC1 chr6 31730581 31739763 +908572 MSH5 chr6 31739677 31762678 +909075 SAPCD1 chr6 31762996 31764851 +909107 SAPCD1-AS1 chr6 31764310 31765588 +909111 VWA7 chr6 31765590 31777328 +909179 VARS chr6 31777518 31795752 +909332 LSM2 chr6 31797396 31806966 +909378 HSPA1L chr6 31809619 31815283 +909388 HSPA1A chr6 31815543 31817946 +909405 HSPA1B chr6 31827738 31830254 +909413 SNHG32 chr6 31834608 31839766 +909463 NEU1 chr6 31857659 31862822 +909507 SLC44A4 chr6 31863192 31879046 +909747 EHMT2-AS1 chr6 31877808 31884204 +909757 EHMT2 chr6 31879759 31897687 +910079 C2 chr6 31897785 31945672 +910457 ZBTB12 chr6 31899613 31902086 +910467 C2-AS1 chr6 31934474 31941724 +910472 CFB chr6 31945650 31952084 +910621 NELFE chr6 31952087 31959038 +910860 SKIV2L chr6 31959117 31969751 +911116 DXO chr6 31969810 31972290 +911254 STK19 chr6 31971091 31982821 +911408 C4A chr6 31982057 32002681 +911660 C4A-AS1 chr6 31999976 32003521 +911664 C4B chr6 32014795 32035418 +912019 C4B-AS1 chr6 32032713 32036258 +912023 CYP21A2 chr6 32038327 32041644 +912188 TNXB chr6 32041153 32115334 +912641 AL662884.5 chr6 32108406 32112849 +912645 ATF6B chr6 32115264 32128253 +912799 FKBPL chr6 32128707 32130288 +912809 PRRT1 chr6 32148359 32153083 +912851 AL662884.3 chr6 32152802 32154365 +912871 PPT2 chr6 32153441 32163678 +913055 EGFL8 chr6 32164595 32168281 +913136 AGPAT1 chr6 32168212 32178096 +913263 RNF5 chr6 32178405 32180793 +913285 AGER chr6 32180968 32184322 +913544 AL662884.1 chr6 32184733 32185882 +913548 PBX2 chr6 32184733 32190202 +913590 GPSM3 chr6 32190766 32195523 +913665 NOTCH4 chr6 32194843 32224067 +913763 TSBP1-AS1 chr6 32254640 32407763 +913827 TSBP1 chr6 32288526 32371912 +914332 BTNL2 chr6 32393963 32407128 +914404 HLA-DRA chr6 32439878 32445046 +914435 HLA-DRB5 chr6 32517353 32530287 +914453 HLA-DRB1 chr6 32578769 32589848 +914471 HLA-DQA1 chr6 32628179 32647062 +914558 HLA-DQB1 chr6 32659467 32668383 +914657 HLA-DQB1-AS1 chr6 32659880 32660729 +914661 AL662789.1 chr6 32718005 32719170 +914675 HLA-DQA2 chr6 32741391 32747198 +914691 HLA-DQB2 chr6 32756098 32763532 +914750 HLA-DOB chr6 32812763 32820466 +914817 TAP2 chr6 32821833 32838770 +914915 PSMB8 chr6 32840717 32844679 +914985 PSMB8-AS1 chr6 32844078 32846500 +915009 PSMB9 chr6 32844136 32859851 +915066 TAP1 chr6 32845209 32853978 +915142 HLA-DMB chr6 32934629 32941028 +915190 HLA-DMA chr6 32948613 32969094 +915269 BRD2 chr6 32968594 32981505 +915562 AL645941.1 chr6 32970232 32970886 +915566 AL645941.3 chr6 32972065 32972853 +915570 HLA-DOA chr6 33004182 33009591 +915609 HLA-DPA1 chr6 33064569 33080775 +915663 HLA-DPB1 chr6 33075990 33089696 +915721 HCG24 chr6 33144783 33147767 +915725 COL11A2 chr6 33162681 33192499 +916197 RXRB chr6 33193588 33200688 +916278 SLC39A7 chr6 33200445 33204439 +916337 HSD17B8 chr6 33204655 33206831 +916369 RING1 chr6 33208500 33212722 +916395 AL645940.1 chr6 33246075 33246856 +916399 HCG25 chr6 33249534 33255167 +916438 VPS52 chr6 33250272 33272047 +916596 RPS18 chr6 33272075 33276511 +916664 B3GALT4 chr6 33277123 33284832 +916675 WDR46 chr6 33279108 33289247 +916774 PFDN6 chr6 33289302 33298401 +916854 RGL2 chr6 33291654 33298942 +916998 TAPBP chr6 33299694 33314387 +917117 ZBTB22 chr6 33314406 33317942 +917143 DAXX chr6 33318558 33323016 +917263 SMIM40 chr6 33323625 33329269 +917275 KIFC1 chr6 33391823 33409896 +917334 PHF1 chr6 33410399 33416453 +917542 CUTA chr6 33416442 33418317 +917749 SYNGAP1 chr6 33419661 33453689 +918229 SYNGAP1-AS1 chr6 33437363 33454453 +918236 ZBTB9 chr6 33453970 33457544 +918267 BAK1 chr6 33572547 33580293 +918323 LINC00336 chr6 33586106 33593338 +918327 ITPR3 chr6 33620365 33696574 +918572 UQCC2 chr6 33694293 33711727 +918612 IP6K3 chr6 33721662 33746905 +918660 LEMD2 chr6 33771202 33789130 +918830 MLN chr6 33794673 33804003 +918876 AL138889.3 chr6 33800142 33802960 +918880 LINC01016 chr6 33867506 33896914 +918920 AL138889.1 chr6 33891327 33927631 +918982 GRM4 chr6 34018645 34155622 +919230 HMGA1 chr6 34236873 34246231 +919316 SMIM29 chr6 34246381 34249108 +919425 AL354740.1 chr6 34248535 34286768 +919443 NUDT3 chr6 34279679 34392669 +919459 RPS10-NUDT3 chr6 34284887 34426071 +919529 RPS10 chr6 34417454 34426069 +919646 PACSIN1 chr6 34466061 34535229 +919761 SPDEF chr6 34537802 34556333 +919794 ILRUN chr6 34587288 34696859 +919838 AL451165.2 chr6 34696317 34697470 +919848 SNRPC chr6 34757505 34773857 +919903 UHRF1BP1 chr6 34792015 34883138 +920000 TAF11 chr6 34877462 34888071 +920046 ANKS1A chr6 34889255 35091406 +920185 AL591002.1 chr6 35041116 35058015 +920189 TCP11 chr6 35118071 35148610 +920696 SCUBE3 chr6 35213956 35253079 +920746 Z97832.2 chr6 35220370 35224630 +920749 ZNF76 chr6 35258909 35295985 +920904 DEF6 chr6 35297818 35321771 +920942 PPARD chr6 35342558 35428191 +921044 FANCE chr6 35452356 35467103 +921096 RPL10A chr6 35468401 35470785 +921139 TEAD3 chr6 35473597 35497079 +921229 TULP1 chr6 35497874 35512896 +921366 AL033519.4 chr6 35539838 35546573 +921379 FKBP5 chr6 35573585 35728583 +921482 AL033519.5 chr6 35650997 35652856 +921486 AL157823.2 chr6 35733867 35736947 +921492 ARMC12 chr6 35737032 35749079 +921555 CLPSL2 chr6 35776594 35779552 +921587 CLPSL1 chr6 35781019 35793675 +921606 CLPS chr6 35794982 35797344 +921637 LHFPL5 chr6 35797206 35845397 +921713 SRPK1 chr6 35832966 35921342 +921925 SLC26A8 chr6 35943516 36024868 +922131 MAPK14 chr6 36027677 36111236 +922345 MAPK13 chr6 36127809 36144524 +922434 Z84485.1 chr6 36146698 36197205 +922448 BRPF3 chr6 36196744 36232790 +922668 PNPLA1 chr6 36243203 36312229 +922770 BNIP5 chr6 36315761 36336888 +922800 ETV7 chr6 36354091 36387800 +922957 Z84484.1 chr6 36386831 36393462 +922965 PXT1 chr6 36390551 36442854 +922992 KCTD20 chr6 36442767 36491143 +923127 STK38 chr6 36493892 36547479 +923161 SRSF3 chr6 36594353 36605600 +923244 PANDAR chr6 36673621 36675126 +923247 CDKN1A chr6 36676460 36687339 +923317 DINOL chr6 36677609 36678559 +923320 RAB44 chr6 36697826 36733184 +923354 CPNE5 chr6 36740775 36839444 +923513 Z85996.2 chr6 36768485 36774651 +923517 Z85996.3 chr6 36841430 36844402 +923522 PPIL1 chr6 36854827 36874803 +923540 C6orf89 chr6 36871870 36928964 +923634 AL122034.1 chr6 36940071 36944675 +923638 PI16 chr6 36948263 36964837 +923706 MTCH1 chr6 36968141 36986298 +923818 FGD2 chr6 37005646 37029069 +923963 PIM1 chr6 37170152 37175428 +923989 TMEM217 chr6 37212178 37258155 +924120 AL353579.1 chr6 37212181 37257637 +924150 TBC1D22B chr6 37257772 37332970 +924182 AL096712.2 chr6 37301210 37305176 +924189 RNF8 chr6 37353979 37394734 +924302 CMTR1 chr6 37433219 37482827 +924419 CCDC167 chr6 37482938 37499893 +924433 LINC02520 chr6 37507348 37535616 +924439 AL353597.1 chr6 37545145 37550860 +924451 MDGA1 chr6 37630679 37699306 +924628 AL121574.1 chr6 37815777 37819218 +924633 ZFAND3 chr6 37819727 38154624 +924704 BTBD9 chr6 38168451 38640148 +924884 BTBD9-AS1 chr6 38481692 38482531 +924888 GLO1 chr6 38675925 38703145 +924910 AL391415.1 chr6 38714051 38715217 +924914 DNAH8 chr6 38715311 39030792 +925483 AL034345.2 chr6 38923029 38953099 +925497 GLP1R chr6 39048781 39091303 +925529 SAYSD1 chr6 39104063 39115186 +925551 KCNK5 chr6 39188971 39229475 +925567 KCNK17 chr6 39299001 39314461 +925604 KCNK16 chr6 39314698 39322968 +925682 KIF6 chr6 39329990 39725408 +925893 DAAM2 chr6 39792298 39904877 +926181 AL590999.1 chr6 39881804 39900071 +926204 MOCS1 chr6 39899578 39934551 +926358 AL139275.2 chr6 40271566 40276237 +926363 TDRG1 chr6 40334775 40387590 +926419 LINC00951 chr6 40344344 40346151 +926423 AL139275.1 chr6 40358744 40369474 +926427 LRFN2 chr6 40391591 40587364 +926439 AL359475.1 chr6 40501631 40502393 +926443 AL033380.1 chr6 40505507 40523963 +926456 AL583854.1 chr6 40713411 40715363 +926461 UNC5CL chr6 41026895 41039221 +926512 OARD1 chr6 41033627 41097787 +926727 TSPO2 chr6 41042467 41044337 +926765 APOBEC2 chr6 41053304 41064511 +926777 NFYA chr6 41072945 41099976 +926826 AL031778.1 chr6 41080624 41101056 +926830 TREML1 chr6 41149342 41154337 +926883 TREM2 chr6 41158506 41163186 +926927 TREML2 chr6 41189749 41201149 +926943 TREML4 chr6 41228339 41238882 +926993 TREM1 chr6 41267926 41286682 +927050 NCR2 chr6 41335608 41350889 +927100 FOXP4-AS1 chr6 41494853 41548621 +927116 LINC01276 chr6 41499033 41519852 +927136 FOXP4 chr6 41546426 41602384 +927346 MDFI chr6 41636882 41654246 +927451 TFEB chr6 41683978 41736259 +927715 AL035588.1 chr6 41720396 41734032 +927719 PGC chr6 41736711 41754109 +927782 AL365205.4 chr6 41764292 41764460 +927785 FRS3 chr6 41770176 41786542 +927849 PRICKLE4 chr6 41780762 41787372 +927944 TOMM6 chr6 41787662 41789898 +927967 USP49 chr6 41789896 41895361 +928053 AL365205.3 chr6 41791410 41791477 +928056 AL160163.1 chr6 41868622 41869731 +928060 MED20 chr6 41905354 41921139 +928128 BYSL chr6 41921499 41933046 +928187 CCND3 chr6 41934933 42050357 +928384 AL513008.1 chr6 42030053 42031382 +928388 TAF8 chr6 42050513 42087461 +928559 AL512274.1 chr6 42092233 42094259 +928562 C6orf132 chr6 42101119 42142620 +928589 GUCA1A chr6 42155406 42180049 +928637 AL096814.2 chr6 42155406 42180056 +928702 AL096814.1 chr6 42155426 42163439 +928721 GUCA1B chr6 42183284 42194956 +928735 MRPS10 chr6 42206807 42217861 +928755 TRERF1 chr6 42224931 42452051 +928951 UBR2 chr6 42564062 42693504 +929179 PRPH2 chr6 42696598 42722597 +929191 TBCC chr6 42744498 42746103 +929199 BICRAL chr6 42746958 42868560 +929295 RPL7L1 chr6 42879616 42889925 +929389 C6orf226 chr6 42890265 42890821 +929397 AL035587.3 chr6 42893761 42903072 +929404 PTCRA chr6 42915989 42925835 +929457 AL035587.2 chr6 42928287 42929457 +929461 CNPY3 chr6 42929192 42939294 +929496 AL035587.1 chr6 42940364 42948360 +929505 GNMT chr6 42960754 42963880 +929523 PEX6 chr6 42963865 42979181 +929597 PPP2R5D chr6 42984553 43012342 +929830 MEA1 chr6 43011143 43016868 +929907 KLHDC3 chr6 43014103 43021298 +929989 RRP36 chr6 43021623 43034156 +930024 AL136304.1 chr6 43033897 43034405 +930027 CUL7 chr6 43037617 43053945 +930150 KLC4 chr6 43040777 43075095 +930492 MRPL2 chr6 43054029 43059438 +930578 AL355385.1 chr6 43074331 43074739 +930581 PTK7 chr6 43076307 43161719 +931034 SRF chr6 43171269 43181506 +931054 CUL9 chr6 43182184 43224587 +931366 AL133375.1 chr6 43213801 43223860 +931370 DNPH1 chr6 43225629 43229484 +931409 TTBK1 chr6 43243481 43288258 +931476 SLC22A7 chr6 43295694 43305538 +931606 CRIP3 chr6 43299710 43308797 +931680 ZNF318 chr6 43307134 43369647 +931743 AL359813.1 chr6 43370026 43425283 +931751 AL359813.2 chr6 43403815 43408341 +931755 ABCC10 chr6 43427366 43450427 +931913 DLK2 chr6 43450352 43456632 +931974 TJAP1 chr6 43477523 43506556 +932257 LRRC73 chr6 43506969 43510686 +932275 POLR1C chr6 43509702 43562419 +932568 YIPF3 chr6 43511832 43516985 +932781 AL355802.3 chr6 43519180 43519724 +932784 XPO5 chr6 43522334 43576038 +932966 POLH chr6 43576150 43615660 +933031 POLH-AS1 chr6 43588230 43591362 +933035 GTPBP2 chr6 43605316 43629264 +933169 MAD2L1BP chr6 43629540 43640952 +933197 RSPH9 chr6 43645036 43672600 +933230 MRPS18A chr6 43671303 43687791 +933276 AL136131.2 chr6 43722786 43737834 +933281 VEGFA chr6 43770184 43786487 +933783 AL136131.3 chr6 43770429 43770616 +933786 AL157371.2 chr6 43803193 43842625 +933791 LINC02537 chr6 43844878 43852317 +933803 AL157371.1 chr6 43851757 43852333 +933807 AL109615.3 chr6 43995723 44074652 +933827 C6orf223 chr6 44000580 44007612 +933869 AL109615.2 chr6 44058792 44089288 +933880 AL109615.4 chr6 44090787 44095585 +933883 MRPL14 chr6 44113451 44127452 +933895 TMEM63B chr6 44126914 44155519 +934159 CAPN11 chr6 44158811 44184401 +934261 MYMX chr6 44216926 44218234 +934280 SLC29A1 chr6 44219505 44234151 +934759 HSP90AB1 chr6 44246166 44253888 +934873 SLC35B2 chr6 44254096 44257890 +934948 NFKBIE chr6 44258166 44265788 +935003 TMEM151B chr6 44270450 44307506 +935025 TCTE1 chr6 44278734 44297698 +935050 AARS2 chr6 44298731 44313347 +935103 SPATS1 chr6 44342660 44377167 +935180 CDC5L chr6 44387706 44450425 +935218 AL136140.1 chr6 44513262 44527448 +935230 AL133334.1 chr6 44727921 44830188 +935235 SUPT3H chr6 44809317 45377953 +935356 RUNX2 chr6 45328157 45664349 +935559 AL096865.1 chr6 45421079 45422005 +935562 RUNX2-AS1 chr6 45573346 45576770 +935566 CLIC5 chr6 45880827 46080348 +935731 AL035701.1 chr6 46096004 46129857 +935745 ENPP4 chr6 46129989 46146688 +935759 ENPP5 chr6 46159185 46170980 +935791 RCAN2 chr6 46220736 46491972 +935850 AL035670.1 chr6 46492052 46606162 +935869 CYP39A1 chr6 46549580 46652830 +935938 SLC25A27 chr6 46652915 46678190 +936039 AL591242.1 chr6 46670444 46688165 +936049 TDRD6 chr6 46687875 46704319 +936087 PLA2G7 chr6 46704201 46735693 +936146 ANKRD66 chr6 46746917 46759506 +936169 AL161618.1 chr6 46758296 46761158 +936173 MEP1A chr6 46793389 46839782 +936237 ADGRF5 chr6 46852522 46954943 +936341 AL096772.1 chr6 46903471 46909078 +936347 ADGRF1 chr6 46997708 47042350 +936521 TNFRSF21 chr6 47231532 47309905 +936539 AL451166.1 chr6 47374561 47397398 +936544 AL355353.1 chr6 47477243 47477572 +936547 CD2AP chr6 47477789 47627263 +936603 ADGRF2 chr6 47656436 47697797 +936687 ADGRF4 chr6 47685864 47722021 +936764 AL356421.2 chr6 47729827 47740741 +936768 OPN5 chr6 47781982 47832780 +936852 PTCHD4 chr6 47878028 48068689 +936873 AL353138.1 chr6 48069213 48111078 +936878 AL391538.1 chr6 48754649 48795513 +936883 MMUT chr6 49430360 49463253 +936915 CENPQ chr6 49463370 49493107 +936939 GLYATL3 chr6 49499923 49528078 +936972 C6orf141 chr6 49550646 49561907 +937023 RHAG chr6 49605158 49636884 +937181 CRISP2 chr6 49692358 49713590 +937257 AL121974.1 chr6 49714325 49820503 +937403 CRISP3 chr6 49727384 49744437 +937482 PGK2 chr6 49785660 49787285 +937490 AL359458.1 chr6 49823712 49824782 +937495 CRISP1 chr6 49834257 49877096 +937574 DEFB133 chr6 49946021 49950265 +937590 DEFB114 chr6 49960249 49964164 +937600 DEFB113 chr6 49968677 49969625 +937609 DEFB110 chr6 50009138 50021994 +937627 DEFB112 chr6 50042144 50049874 +937645 AL138826.1 chr6 50093389 50181007 +937664 AL132799.1 chr6 50411844 50415875 +937668 AL360175.1 chr6 50514035 50521104 +937672 AL135908.1 chr6 50587607 50637205 +937684 TFAP2D chr6 50713828 50772988 +937713 TFAP2B chr6 50818723 50847619 +937747 AL355997.1 chr6 51599723 51623428 +937761 PKHD1 chr6 51615299 52087613 +938028 LINCMD1 chr6 52146814 52151119 +938033 IL17A chr6 52186375 52190638 +938045 IL17F chr6 52236681 52244537 +938060 MCM3 chr6 52264014 52284881 +938240 PAQR8 chr6 52361421 52407777 +938268 EFHC1 chr6 52362123 52529886 +938939 TRAM2 chr6 52497408 52577060 +938967 TRAM2-AS1 chr6 52576787 52643058 +939043 TMEM14A chr6 52671113 52686588 +939059 GSTA2 chr6 52750087 52763475 +939079 GSTA1 chr6 52791371 52803860 +939110 GSTA5 chr6 52831655 52846095 +939153 GSTA3 chr6 52896639 52909698 +939201 GSTA4 chr6 52977948 52995304 +939275 ICK chr6 53001279 53061802 +939344 FBXO9 chr6 53051991 53100873 +939532 AL512347.1 chr6 53125644 53126146 +939535 GCM1 chr6 53126961 53148841 +939553 ELOVL5 chr6 53267398 53349179 +939650 AL034374.1 chr6 53350158 53350705 +939653 GCLC chr6 53497341 53616970 +939896 AL033397.2 chr6 53503109 53507660 +939905 AL033397.1 chr6 53561289 53617171 +939939 LINC01564 chr6 53616471 53631400 +939954 KLHL31 chr6 53647916 53665756 +939974 AL590652.1 chr6 53739266 53794904 +940007 LRRC1 chr6 53794497 53924125 +940086 AL033384.2 chr6 53918974 53920788 +940090 MLIP chr6 53929982 54266280 +940328 AL033384.1 chr6 53930022 53997667 +940338 MLIP-AS1 chr6 53978549 54079726 +940401 MLIP-IT1 chr6 53998890 54007152 +940407 AL359380.1 chr6 54190206 54190709 +940411 TINAG chr6 54307859 54390142 +940475 AL589946.1 chr6 54365335 54369971 +940480 AL512363.1 chr6 54840118 54840855 +940484 FAM83B chr6 54846771 54945099 +940500 AL049555.1 chr6 54943167 54945099 +940503 HCRTR2 chr6 55106460 55282620 +940544 GFRAL chr6 55327469 55402493 +940568 HMGCLL1 chr6 55434369 55579214 +940737 BMP5 chr6 55753653 55875590 +940757 COL21A1 chr6 56056590 56394094 +941057 AL031779.1 chr6 56331788 56332117 +941060 DST chr6 56457987 56954649 +942744 AL512422.1 chr6 56843928 56864078 +942754 BEND6 chr6 56955107 57027346 +942808 KIAA1586 chr6 57046532 57055239 +942838 ZNF451 chr6 57086844 57170305 +943100 ZNF451-AS1 chr6 57114894 57174236 +943201 BAG2 chr6 57172326 57189833 +943213 RAB23 chr6 57186992 57222307 +943252 PRIM2 chr6 57314805 57646850 +943396 FO680682.1 chr6 57493855 57497691 +943400 AL021368.3 chr6 57855891 57856468 +943403 AL021368.5 chr6 57880071 57884297 +943407 AL021368.1 chr6 57902609 57903148 +943410 AL021368.2 chr6 57908560 57913911 +943413 AL445250.1 chr6 57961438 58438364 +943521 AL590227.1 chr6 60723148 60723898 +943525 AL512427.2 chr6 60789805 60942327 +943531 KHDRBS2-OT chr6 61630233 61681049 +943539 KHDRBS2 chr6 61679961 62286225 +943563 AL355347.1 chr6 61870097 61893882 +943567 FKBP1C chr6 63211446 63213024 +943575 LGSN chr6 63275951 63319983 +943631 PTP4A1 chr6 63521746 63583436 +943732 AL135905.1 chr6 63571005 63572408 +943735 AL135905.2 chr6 63572472 63583587 +943770 PHF3 chr6 63635820 63779336 +944013 EYS chr6 63719980 65707226 +944313 SCAT8 chr6 63806836 63822642 +944317 AL357375.1 chr6 64377795 64412779 +944323 AL713998.1 chr6 67878316 67889339 +944375 AL713998.3 chr6 67884041 67986503 +944381 AL713998.4 chr6 67888977 67998751 +944387 AL646090.2 chr6 68040290 68093001 +944402 AL646090.1 chr6 68055351 68060502 +944406 AL593844.1 chr6 68223667 68242364 +944410 LINC02549 chr6 68226972 68329899 +944416 AL606923.2 chr6 68332019 68576191 +944430 AL391807.1 chr6 68627879 68635161 +944474 ADGRB3 chr6 68635282 69389506 +944667 LMBRD1 chr6 69672757 69867236 +945741 COL19A1 chr6 69866556 70212468 +945877 COL9A1 chr6 70215061 70303083 +946223 AL160262.1 chr6 70222758 70242156 +946227 AL080275.1 chr6 70345919 70351802 +946232 AL365226.2 chr6 70394881 70403117 +946245 AL365226.1 chr6 70412828 70413950 +946249 FAM135A chr6 70412941 70561174 +946670 SDHAF4 chr6 70566917 70589569 +946685 AL583856.2 chr6 70596438 70596980 +946688 SMAP1 chr6 70667776 70862011 +946815 B3GAT2 chr6 70856679 70957060 +946841 AL096709.1 chr6 71028582 71058476 +946845 AL589935.1 chr6 71221457 71328228 +946993 AL589935.3 chr6 71238743 71240947 +946997 OGFRL1 chr6 71288811 71309059 +947040 AL136164.1 chr6 71328942 71329806 +947044 LINC00472 chr6 71343427 71420745 +947115 LINC01626 chr6 71450834 71458874 +947128 AL035467.2 chr6 71532070 71534715 +947132 RIMS1 chr6 71886703 72403143 +947987 FO393414.3 chr6 72614386 72622073 +947996 KCNQ5 chr6 72621792 73198851 +948342 KCNQ5-IT1 chr6 72630495 72678558 +948348 KCNQ5-AS1 chr6 73130646 73143514 +948369 KHDC1L chr6 73223544 73225770 +948384 KHDC1 chr6 73241314 73310365 +948460 AC019205.1 chr6 73263212 73301789 +948484 DPPA5 chr6 73353063 73354276 +948496 KHDC3L chr6 73362658 73364171 +948508 OOEP chr6 73368555 73395133 +948539 OOEP-AS1 chr6 73369704 73387717 +948543 DDX43 chr6 73394828 73417566 +948594 CGAS chr6 73413515 73452297 +948630 MTO1 chr6 73461578 73509236 +948916 AL603910.1 chr6 73492025 73492742 +948920 EEF1A1 chr6 73515750 73523797 +949070 AL121972.1 chr6 73523618 73570596 +949080 SLC17A5 chr6 73593379 73653992 +949114 AL590428.1 chr6 73693903 73696131 +949118 CD109 chr6 73695785 73828316 +949361 AL357507.1 chr6 74069451 74690727 +949367 AL356277.3 chr6 74530248 74734319 +949388 AL356277.2 chr6 74642384 74652002 +949392 COL12A1 chr6 75084326 75206053 +950153 COX7A2 chr6 75237675 75250323 +950242 TMEM30A chr6 75252924 75284948 +950311 AL080250.1 chr6 75285014 75317525 +950337 FILIP1 chr6 75291859 75493800 +950391 AL445465.1 chr6 75357214 75399300 +950432 AL445465.2 chr6 75454944 75458900 +950438 SENP6 chr6 75601509 75718281 +950695 MYO6 chr6 75749192 75919537 +951820 IMPG1 chr6 75921114 76072678 +951925 LINC02540 chr6 76521640 76593821 +951934 AL591030.1 chr6 76561328 76562590 +951938 AL355612.1 chr6 76774972 77097788 +951951 HTR1B chr6 77461753 77463773 +951959 MEI4 chr6 77650274 77927028 +951988 AL121718.1 chr6 78604467 78606036 +951992 AL450327.1 chr6 78809715 78813303 +951996 IRAK1BP1 chr6 78867551 78946440 +952045 PHIP chr6 78934419 79078254 +952149 AL356776.2 chr6 79077841 79081371 +952155 HMGN3 chr6 79201245 79234738 +952209 HMGN3-AS1 chr6 79233718 79236797 +952213 LCAL1 chr6 79307669 79313384 +952225 AL391840.1 chr6 79420172 79529276 +952248 LCA5 chr6 79484991 79537458 +952312 AL391840.3 chr6 79537540 79539976 +952316 AL451064.1 chr6 79561132 79561602 +952319 SH3BGRL2 chr6 79631329 79703655 +952333 LINC01621 chr6 79803582 79833386 +952343 AL132875.3 chr6 79868402 79870483 +952348 AL132875.2 chr6 79871873 79874610 +952352 ELOVL4 chr6 79914814 79947553 +952370 AL133475.1 chr6 79947810 79980046 +952376 TTK chr6 80003887 80042527 +952598 AL591135.2 chr6 80046715 80084776 +952610 BCKDHB chr6 80106647 80346270 +952692 AL359715.3 chr6 80355424 80356859 +952695 AL359715.1 chr6 80441295 80466674 +952714 AL359715.2 chr6 80466958 80469080 +952720 TENT5A chr6 81491439 81752774 +952769 AL122017.1 chr6 81527102 81534915 +952777 AL359693.1 chr6 81551686 81554092 +952780 AL078599.2 chr6 81724722 81736353 +952786 LINC01526 chr6 81813286 81814157 +952790 LINC02542 chr6 81844602 82169391 +952831 AL360157.1 chr6 81969453 81969539 +952834 IBTK chr6 82169986 82247754 +953228 AL121977.2 chr6 82353861 82363657 +953232 TPBG chr6 82363206 82370828 +953262 UBE3D chr6 82892390 83065841 +953412 AL355613.1 chr6 82932601 82938677 +953416 DOP1A chr6 83067666 83171350 +953706 PGM3 chr6 83161150 83193936 +954151 RWDD2A chr6 83193357 83198935 +954163 ME1 chr6 83210402 83431051 +954197 PRSS35 chr6 83512534 83525704 +954207 SNAP91 chr6 83552880 83709691 +954949 AL136972.1 chr6 83728055 83736525 +954953 AL139232.1 chr6 83852312 83854167 +954956 RIPPLY2 chr6 83853266 83857515 +954982 CYB5R4 chr6 83859656 83967423 +955043 AL034347.1 chr6 83983728 84007323 +955049 LINC02857 chr6 84019204 84026100 +955055 MRAP2 chr6 84033772 84090881 +955069 CEP162 chr6 84124241 84227643 +955304 LINC01611 chr6 84421028 84556152 +955319 TBX18 chr6 84687351 84764598 +955401 TBX18-AS1 chr6 84687712 84709578 +955453 AL035694.1 chr6 84769010 84770219 +955457 LINC02535 chr6 85387219 85390186 +955461 NT5E chr6 85449584 85495791 +955541 SNX14 chr6 85505496 85594156 +956103 SYNCRIP chr6 85607785 85643792 +956202 SNHG5 chr6 85650491 85678932 +956656 AL450338.2 chr6 85949690 85998263 +956666 HTR1E chr6 86937528 87016679 +956676 CGA chr6 87085498 87095406 +956745 AL139274.2 chr6 87151159 87155285 +956748 ZNF292 chr6 87152833 87265943 +956850 GJB7 chr6 87282980 87329278 +956873 SMIM8 chr6 87322583 87399749 +956968 C6orf163 chr6 87344813 87365463 +957001 CFAP206 chr6 87407972 87464465 +957093 SLC35A1 chr6 87470623 87512336 +957178 RARS2 chr6 87513938 87589987 +957247 ORC3 chr6 87590067 87667453 +957396 AKIRIN2 chr6 87674860 87702233 +957415 AL136096.1 chr6 88047056 88047729 +957418 SPACA1 chr6 88047841 88066838 +957446 CNR1 chr6 88139864 88166359 +957508 AL139042.1 chr6 88177804 88442928 +957531 AL139090.1 chr6 88378280 88385447 +957535 RNGTT chr6 88609897 88963618 +957650 AL353135.1 chr6 89080164 89080667 +957653 PNRC1 chr6 89080751 89085160 +957681 SRSF12 chr6 89095959 89118071 +957728 AL353135.2 chr6 89130887 89145985 +957743 PM20D2 chr6 89146055 89165565 +957763 GABRR1 chr6 89177501 89231278 +957925 GABRR2 chr6 89254464 89315299 +957961 UBE2J1 chr6 89326625 89352722 +957983 RRAGD chr6 89364616 89412273 +958026 ANKRD6 chr6 89433152 89633834 +958384 AL159174.1 chr6 89560875 89567044 +958392 LYRM2 chr6 89568144 89638749 +958482 MDN1 chr6 89642498 89819794 +958962 AL096678.1 chr6 89673469 89675783 +958966 CASP8AP2 chr6 89829894 89874436 +959049 GJA10 chr6 89894469 89921760 +959067 BACH2 chr6 89926528 90296908 +959175 AL121787.1 chr6 89950116 89953186 +959183 AL158136.1 chr6 90073051 90079734 +959187 AL132996.1 chr6 90295507 90363912 +959233 MAP3K7 chr6 90513573 90587072 +959410 AL080284.1 chr6 91390313 91393000 +959415 CASC6 chr6 91557292 91690428 +959429 AL590814.1 chr6 92002610 92180156 +959436 AL133457.1 chr6 92387841 92388827 +959439 AL359987.1 chr6 92631066 92633268 +959443 LINC02531 chr6 92723003 92723829 +959447 AL138731.1 chr6 93070387 93103384 +959451 EPHA7 chr6 93240020 93419559 +959502 AL591519.1 chr6 93416951 93677954 +959509 AL356094.2 chr6 93720163 93745615 +959516 AL391336.1 chr6 93886900 93889410 +959520 AL157378.1 chr6 94163920 94194658 +959524 MANEA-DT chr6 95575183 95577450 +959527 MANEA chr6 95577535 95609452 +959558 AL034348.1 chr6 95917143 96015391 +959570 FUT9 chr6 96015974 96215612 +959586 UFL1-AS1 chr6 96199840 96521717 +959610 UFL1 chr6 96521595 96555276 +959657 FHL5 chr6 96562548 96616636 +959707 AL033379.1 chr6 96785137 96795821 +959712 GPR63 chr6 96794125 96837477 +959722 NDUFAF4 chr6 96889315 96897891 +959742 KLHL32 chr6 96924620 97140754 +959892 MMS22L chr6 97142161 97283217 +960118 AL589740.1 chr6 97283303 98400869 +960555 AL080316.1 chr6 97710953 97717197 +960560 AL590727.1 chr6 98210020 98214683 +960564 AL589826.2 chr6 98829967 98832508 +960569 POU3F2 chr6 98834574 98839458 +960577 FBXL4 chr6 98868535 98948006 +960626 FAXC chr6 99271168 99350062 +960664 COQ3 chr6 99369401 99394195 +960702 PNISR chr6 99398050 99425331 +960852 AL513550.1 chr6 99424922 99432323 +960856 USP45 chr6 99432379 99521728 +961150 TSTD3 chr6 99520693 99589899 +961196 CCNC chr6 99542387 99568825 +961594 PRDM13 chr6 99606730 99615578 +961621 MCHR2 chr6 99919910 99994247 +961656 MCHR2-AS1 chr6 99993934 100107613 +961699 SIM1 chr6 100385015 100464929 +961762 Z86062.2 chr6 100427118 100437484 +961766 ASCC3 chr6 100508194 100881372 +961964 AL133338.1 chr6 100881471 100882987 +961967 GRIK2 chr6 101181257 102070083 +962239 AP002528.1 chr6 101452917 101454245 +962243 AL357139.2 chr6 102350271 102369827 +962248 AL590608.1 chr6 103866023 103874687 +962252 AL357522.1 chr6 104487095 104528158 +962264 HACE1 chr6 104728094 104859919 +962568 AL357315.1 chr6 104831129 104845820 +962573 LIN28B-AS1 chr6 104864464 104941447 +962605 LIN28B chr6 104936616 105083332 +962649 BVES chr6 105096822 105137157 +962713 BVES-AS1 chr6 105136308 105169952 +962791 POPDC3 chr6 105157900 105180014 +962822 PREP chr6 105273220 105454062 +962904 AL133406.2 chr6 105279016 105281755 +962908 AL096794.1 chr6 105403207 105588802 +962924 LINC02836 chr6 105612667 105632296 +962938 AL591518.1 chr6 105679378 105893041 +962948 PRDM1 chr6 105993463 106109939 +963083 ATG5 chr6 106045423 106325791 +963270 AL022067.1 chr6 106100140 106100593 +963273 AL356859.1 chr6 106358566 106359717 +963277 CRYBG1 chr6 106360808 106571978 +963404 AL109920.1 chr6 106451496 106457248 +963408 RTN4IP1 chr6 106570771 106629498 +963454 QRSL1 chr6 106629578 106668417 +963506 LINC02526 chr6 106695535 106699994 +963511 LINC02532 chr6 106705334 106788148 +963781 CD24 chr6 106969831 106975627 +963849 MTRES1 chr6 107028199 107051586 +963894 BEND3 chr6 107065182 107115269 +963923 PDSS2 chr6 107152562 107459564 +963965 SOBP chr6 107490106 107661306 +964007 AL121957.1 chr6 107509803 107511721 +964015 SCML4 chr6 107702154 107824317 +964141 SEC63 chr6 107867756 107958208 +964254 AL024507.2 chr6 107957413 107959986 +964257 Z98200.1 chr6 108030249 108030718 +964260 OSTM1 chr6 108041409 108165854 +964315 OSTM1-AS1 chr6 108123457 108159392 +964325 NR2E1 chr6 108166058 108188809 +964387 SNX3 chr6 108211222 108261246 +964440 Z98742.4 chr6 108261288 108269200 +964445 Z98742.1 chr6 108275642 108276546 +964449 AFG1L chr6 108294991 108526796 +964551 AL139106.1 chr6 108441880 108558286 +964557 FOXO3 chr6 108559835 108684774 +964593 LINC00222 chr6 108751654 108769942 +964629 Z95118.2 chr6 108798929 108837113 +964636 ARMC2 chr6 108848416 108974476 +964745 ARMC2-AS1 chr6 108922976 108924103 +964749 SESN1 chr6 108986437 109094819 +964840 AL390208.1 chr6 108998482 108999125 +964843 CEP57L1 chr6 109095110 109163932 +965292 CD164 chr6 109366514 109382467 +965414 AL359711.2 chr6 109382795 109383666 +965417 PPIL6 chr6 109390215 109441171 +965549 SMPD2 chr6 109440724 109443919 +965588 MICAL1 chr6 109444062 109465968 +965822 ZBTB24 chr6 109462594 109483237 +965842 AL109947.1 chr6 109483638 109506800 +965852 AK9 chr6 109492856 109691217 +966164 FIG4 chr6 109691312 109825428 +966267 AL512303.1 chr6 109826522 109828785 +966271 GPR6 chr6 109978256 109980718 +966289 AL590009.1 chr6 110020011 110040241 +966295 WASF1 chr6 110099819 110180004 +966492 CDC40 chr6 110180141 110254275 +966628 METTL24 chr6 110245928 110358272 +966646 AL050350.1 chr6 110341973 110354563 +966653 DDO chr6 110391771 110415575 +966695 SLC22A16 chr6 110424687 110476641 +966798 AC002464.1 chr6 110477907 110479436 +966801 CDK19 chr6 110609978 110815958 +966941 AMD1 chr6 110874770 110898879 +967093 GTF3C6 chr6 110958706 110967890 +967118 RPF2 chr6 110982015 111028263 +967211 SLC16A10 chr6 111087503 111231194 +967276 AL360227.1 chr6 111227747 111259034 +967282 MFSD4B chr6 111259279 111445354 +967437 AL080317.1 chr6 111297126 111298510 +967440 REV3L chr6 111299028 111483715 +967927 AL080317.2 chr6 111309203 111313517 +967930 REV3L-IT1 chr6 111360641 111361607 +967934 TRAF3IP2-AS1 chr6 111483511 111598302 +967982 AL008730.1 chr6 111505307 111511071 +967987 TRAF3IP2 chr6 111555381 111606906 +968189 Z97989.1 chr6 111599875 111602295 +968192 FYN chr6 111660332 111873452 +968616 LINC02527 chr6 111900305 111909420 +968630 CCN6 chr6 112054072 112070969 +968776 TUBE1 chr6 112070663 112087529 +968913 FAM229B chr6 112087591 112102790 +968940 LAMA4 chr6 112107931 112254939 +969505 Z99289.1 chr6 112154765 112166476 +969543 Z99289.2 chr6 112217640 112219570 +969546 Z99289.3 chr6 112234165 112234758 +969549 AL365214.2 chr6 112236093 112307009 +969585 RFPL4B chr6 112347330 112351294 +969597 AL365214.4 chr6 112392363 112396364 +969601 AL357514.1 chr6 112476538 112481636 +969605 AL360015.1 chr6 112988311 113140870 +969617 AL589684.1 chr6 113357003 113367944 +969622 LINC02518 chr6 113428540 113433555 +969632 AL513123.1 chr6 113531118 113543793 +969637 LINC02541 chr6 113616927 113650090 +969664 FO393415.3 chr6 113791829 113837368 +969668 MARCKS chr6 113857345 113863475 +969678 LINC01268 chr6 113868013 113873351 +969688 FO393415.1 chr6 113904132 113921642 +969698 HDAC2 chr6 113933028 114011308 +969940 HDAC2-AS2 chr6 113969701 114471705 +970032 HS3ST5 chr6 114055586 114343045 +970060 AL138830.2 chr6 114477350 114488752 +970067 AL138830.1 chr6 114523443 114545335 +970077 AL590550.1 chr6 114822994 115002280 +970082 LINC02534 chr6 115633540 115643916 +970093 FRK chr6 115931149 116060891 +970115 AL357141.1 chr6 116033901 116046753 +970125 NT5DC1 chr6 116100851 116249497 +970193 COL10A1 chr6 116118909 116158747 +970241 AL050331.2 chr6 116244187 116244728 +970245 TSPYL4 chr6 116249964 116254075 +970253 DSE chr6 116254173 116444860 +970420 TSPYL1 chr6 116267760 116279903 +970439 Z84488.1 chr6 116460739 116463692 +970443 CALHM6 chr6 116461370 116463771 +970471 AL445224.1 chr6 116492297 116497099 +970476 TRAPPC3L chr6 116494989 116545684 +970514 CALHM5 chr6 116511639 116524788 +970524 CALHM4 chr6 116529013 116558868 +970578 RWDD1 chr6 116571409 116597675 +970667 RSPH4A chr6 116616479 116632985 +970714 ZUP1 chr6 116635618 116668794 +970766 KPNA5 chr6 116681187 116741867 +970850 FAM162B chr6 116752197 116765719 +970864 GPRC6A chr6 116792085 116829037 +970914 RFX6 chr6 116877212 116932161 +970981 Z98880.1 chr6 117262243 117264817 +970985 VGLL2 chr6 117265558 117273565 +971010 ROS1 chr6 117288300 117425855 +971204 AL132671.1 chr6 117451130 117453525 +971208 DCBLD1 chr6 117453817 117569858 +971347 GOPC chr6 117560269 117602542 +971413 NUS1 chr6 117675469 117710727 +971429 SLC35F1 chr6 117907264 118317676 +971470 CEP85L chr6 118460772 118710075 +971630 PLN chr6 118548296 118561716 +971640 Z99496.2 chr6 118565660 118576840 +971645 MCM9 chr6 118813442 118935162 +971766 ASF1A chr6 118894152 118909171 +971783 AL137009.1 chr6 118934770 119182745 +971790 FAM184A chr6 118959763 119149387 +972131 MAN1A1 chr6 119177205 119349761 +972163 AL078600.1 chr6 119349920 119391829 +972168 AL096854.1 chr6 120462511 120706789 +972172 AL357513.1 chr6 120840733 120845475 +972176 TBC1D32 chr6 121079494 121334745 +972454 GJA1 chr6 121435595 121449727 +972491 HSF2 chr6 122399551 122433119 +972563 SERINC1 chr6 122443351 122471807 +972589 PKIB chr6 122471917 122726373 +972734 AL512283.2 chr6 122562172 122621014 +972741 AL512283.1 chr6 122643388 122644771 +972744 AL512283.3 chr6 122711887 122718814 +972751 FABP7 chr6 122779716 122784074 +972776 SMPDL3A chr6 122789049 122809720 +972821 AL591428.1 chr6 122975198 122996061 +972827 CLVS2 chr6 122996235 123072925 +972860 TRDN chr6 123216339 123637093 +973074 TRDN-AS1 chr6 123389421 123510247 +973158 AL445259.1 chr6 123519697 123557670 +973173 AL133257.1 chr6 123589711 123685323 +973185 NKAIN2 chr6 123803865 124825640 +973260 AL354936.1 chr6 123823240 123829285 +973264 RNF217-AS1 chr6 124644434 124963165 +973371 RNF217 chr6 124962545 125092633 +973505 TPD52L1 chr6 125119049 125264407 +973713 HDDC2 chr6 125219962 125302078 +973810 AL121938.1 chr6 125268087 125274828 +973816 AL450332.1 chr6 125370034 125445193 +973849 AL365259.1 chr6 125577545 125749190 +973879 LINC02523 chr6 125674353 125720218 +973890 HEY2 chr6 125747664 125761269 +973921 NCOA7 chr6 125781161 125932034 +974118 NCOA7-AS1 chr6 125797856 125818858 +974123 HINT3 chr6 125956770 125980244 +974139 TRMT11 chr6 125986479 126203817 +974403 CENPW chr6 126340174 126348875 +974437 AL035603.1 chr6 126719560 126721778 +974441 RSPO3 chr6 127118671 127199481 +974479 RNF146 chr6 127266610 127288567 +974655 ECHDC1 chr6 127288712 127343609 +974959 KIAA0408 chr6 127438406 127459389 +975007 SOGA3 chr6 127472794 127519191 +975055 C6orf58 chr6 127519455 127591820 +975079 LINC02536 chr6 127664554 127681555 +975085 THEMIS chr6 127708072 127918631 +975182 PTPRK chr6 127968779 128520674 +975790 AL590006.1 chr6 128027886 128085248 +975797 AL034349.1 chr6 128500527 128501176 +975801 LAMA2 chr6 128883141 129516569 +976222 AL356124.1 chr6 129439485 129576047 +976331 AL356124.2 chr6 129479615 129481410 +976335 ARHGAP18 chr6 129576132 129710177 +976381 TMEM244 chr6 129831244 129861547 +976412 L3MBTL3 chr6 130013699 130141451 +976759 AL355581.1 chr6 130133410 130146179 +976789 SAMD3 chr6 130144315 130365425 +977036 TMEM200A chr6 130365734 130443063 +977075 AL583803.1 chr6 130697312 130697778 +977079 SMLR1 chr6 130827406 130837135 +977089 EPB41L2 chr6 130839347 131063322 +977793 AKAP7 chr6 131135467 131283535 +977895 ARG1 chr6 131470832 131584332 +978038 MED23 chr6 131573966 131628242 +978395 ENPP3 chr6 131628442 131747418 +978618 OR2A4 chr6 131699644 131701401 +978625 CTAGE9 chr6 131708441 131711017 +978632 ENPP1 chr6 131808016 131895155 +978829 AL117378.1 chr6 131901963 131920565 +978840 CCN2 chr6 131948176 131951372 +978856 AL133346.1 chr6 131950946 132077393 +978860 AL021408.1 chr6 132085084 132099279 +978867 LINC01013 chr6 132131888 132169374 +979039 MOXD1 chr6 132296055 132401475 +979111 STX7 chr6 132445867 132513198 +979174 TAAR9 chr6 132538290 132539336 +979181 TAAR8 chr6 132552693 132553721 +979188 TAAR6 chr6 132570322 132571359 +979195 TAAR5 chr6 132588673 132589686 +979202 AL513524.1 chr6 132599972 132602740 +979206 TAAR2 chr6 132617022 132624275 +979222 TAAR1 chr6 132644984 132646003 +979229 VNN1 chr6 132680849 132714055 +979249 VNN3 chr6 132722787 132734765 +979443 VNN2 chr6 132743870 132763459 +979680 AL032821.1 chr6 132752675 132753951 +979684 SLC18B1 chr6 132769370 132813339 +979868 RPS12 chr6 132814569 132817564 +979893 LINC00326 chr6 132954257 133107410 +979990 AL591115.1 chr6 133061240 133103128 +980004 EYA4 chr6 133240598 133532128 +980359 AL024497.1 chr6 133435077 133439464 +980363 AL024497.2 chr6 133452857 133456605 +980368 TARID chr6 133502252 133892802 +980432 AL450270.1 chr6 133540784 133541174 +980435 LINC01312 chr6 133821147 133872922 +980454 TCF21 chr6 133889138 133895553 +980475 TBPL1 chr6 133952170 133990432 +980574 SLC2A12 chr6 133987581 134052624 +980590 AL449363.2 chr6 134074123 134121433 +980595 SGK1 chr6 134169246 134318112 +980919 AL355881.1 chr6 134296301 134304297 +980924 LINC01010 chr6 134343307 134504581 +980984 Z84486.1 chr6 134345688 134349337 +980988 CT69 chr6 134428239 134520585 +981057 AL078590.2 chr6 134520163 134689399 +981140 AL078590.1 chr6 134606299 134609437 +981144 AL596188.1 chr6 134636489 134642495 +981149 AL121970.1 chr6 134706060 134707349 +981153 ALDH8A1 chr6 134917393 134950115 +981238 AL445190.1 chr6 134941392 134942450 +981242 HBS1L chr6 134960378 135103056 +981594 AL353596.1 chr6 135055033 135060550 +981598 MYB chr6 135181308 135219173 +982982 MYB-AS1 chr6 135195083 135195995 +982986 AL023693.1 chr6 135259996 135260933 +982990 AHI1 chr6 135283532 135497765 +983442 AL049552.1 chr6 135301568 135307158 +983447 AL049552.2 chr6 135323399 135327965 +983451 LINC00271 chr6 135497422 135813990 +983529 AL035604.1 chr6 135628787 135634681 +983540 AL133319.1 chr6 135807148 135808466 +983544 PDE7B chr6 135851701 136195574 +983615 AL360178.1 chr6 135854053 135880942 +983619 AL360178.2 chr6 135882780 135888133 +983623 AL138828.1 chr6 135991936 136225751 +983714 MTFR2 chr6 136231024 136250335 +983807 BCLAF1 chr6 136256627 136289851 +984263 AL023284.4 chr6 136335714 136336087 +984266 MAP7 chr6 136342281 136550819 +984624 AL024508.2 chr6 136550661 136552554 +984627 MAP3K5 chr6 136557046 136792477 +984697 AL024508.1 chr6 136629066 136648198 +984702 AL121933.2 chr6 136784045 136786280 +984706 PEX7 chr6 136822564 136913934 +984766 SLC35D3 chr6 136922301 136925660 +984776 AL135902.1 chr6 136982165 136993234 +984785 AL135902.2 chr6 136995170 136999504 +984789 IL20RA chr6 136999971 137045180 +984896 IL22RA2 chr6 137143820 137173648 +984948 IFNGR1 chr6 137197484 137219449 +985155 OLIG3 chr6 137492199 137494394 +985163 AL356234.2 chr6 137657998 137763984 +985208 AL356234.3 chr6 137693068 137700415 +985213 LINC02539 chr6 137730170 137792835 +985228 WAKMAR2 chr6 137823673 137868233 +985261 TNFAIP3 chr6 137867214 137883312 +985442 AL591468.2 chr6 137900585 137903576 +985446 AL591468.1 chr6 137943079 137945802 +985450 LINC02528 chr6 137945366 137972522 +985457 PERP chr6 138088505 138107419 +985469 ARFGEF3 chr6 138161939 138344663 +985543 PBOV1 chr6 138215986 138218491 +985551 SMIM28 chr6 138377905 138383075 +985561 HEBP2 chr6 138403531 138422197 +985610 NHSL1 chr6 138422043 138692571 +985700 AL590617.2 chr6 138692548 138697288 +985719 GVQW2 chr6 138725211 138773652 +985743 CCDC28A chr6 138773509 138793319 +985795 ECT2L chr6 138795926 138904070 +985959 REPS1 chr6 138903493 138988261 +986434 ABRACL chr6 139028745 139043302 +986455 HECA chr6 139135080 139180802 +986469 AL031772.1 chr6 139144204 139239653 +986541 TXLNB chr6 139240061 139291998 +986574 AL592429.2 chr6 139271362 139667284 +986613 CITED2 chr6 139371807 139374648 +986652 LINC01625 chr6 139435636 139474658 +986695 FILNC1 chr6 139677639 139860476 +986730 AL050338.1 chr6 139856104 139877391 +986734 AL050338.2 chr6 139938864 139991094 +986744 AL357146.1 chr6 139976352 140093721 +986821 AL035446.2 chr6 140575788 140898381 +986828 AL035446.1 chr6 140845958 140852924 +986832 AL355596.2 chr6 141403240 141404494 +986836 AL355596.1 chr6 141447011 141451006 +986839 NMBR chr6 142058330 142088799 +986855 NMBR-AS1 chr6 142088233 142089219 +986859 GJE1 chr6 142133090 142135151 +986871 VTA1 chr6 142147162 142224685 +986952 AL360007.1 chr6 142251847 142259632 +986956 ADGRG6 chr6 142301854 142446266 +987257 AL359313.1 chr6 142526455 142637889 +987270 AL355337.1 chr6 142671980 142681267 +987277 AL023584.1 chr6 142748443 142753759 +987281 HIVEP2 chr6 142751469 142956698 +987362 AL023584.2 chr6 142788123 142794086 +987366 AL355304.1 chr6 142946406 142957945 +987383 LINC01277 chr6 142966293 143059682 +987429 AL023581.2 chr6 143039425 143042324 +987433 AIG1 chr6 143060496 143341058 +987564 AL023581.1 chr6 143094034 143099645 +987568 ADAT2 chr6 143422832 143450695 +987606 PEX3 chr6 143450805 143490616 +987656 FUCA2 chr6 143494812 143511720 +987687 PHACTR2 chr6 143536845 143831185 +987891 PHACTR2-AS1 chr6 143554325 143562031 +987906 LTV1 chr6 143843338 143863812 +987934 ZC2HC1B chr6 143864436 143938343 +987966 PLAGL1 chr6 143940300 144064599 +988329 HYMAI chr6 144004916 144008262 +988332 SF3B5 chr6 144094884 144095573 +988340 STX11 chr6 144150517 144191939 +988350 UTRN chr6 144285701 144853034 +988674 AL024474.2 chr6 144311699 144333301 +988678 AL023283.1 chr6 145296545 145311092 +988682 EPM2A chr6 145382535 145736023 +988961 AL023806.1 chr6 145735570 145737218 +988964 AL023806.2 chr6 145736911 145737173 +988967 AL356599.1 chr6 145749917 145887430 +989040 AL023806.4 chr6 145784406 145786559 +989044 FBXO30 chr6 145793502 145814795 +989056 SHPRH chr6 145864245 145964423 +989517 GRM1 chr6 146027646 146437601 +989639 RAB32 chr6 146543833 146554953 +989651 AL359547.1 chr6 146594516 146598931 +989656 ADGB chr6 146598967 146815462 +989965 STXBP5-AS1 chr6 146824539 147204614 +990429 AL138916.1 chr6 146854983 146863460 +990447 AL138916.2 chr6 146948528 146951159 +990451 LUADT1 chr6 147158925 147180992 +990456 STXBP5 chr6 147204425 147390476 +990680 SAMD5 chr6 147508690 147737547 +990697 AL033504.1 chr6 147660703 147953937 +990714 AL365271.1 chr6 147741434 147743324 +990718 AL445123.2 chr6 148001716 148018985 +990722 AL445123.1 chr6 148017422 148020974 +990727 AL359382.1 chr6 148133809 148137404 +990731 AL359382.2 chr6 148155120 148157084 +990735 AL513164.1 chr6 148237585 148283408 +990741 SASH1 chr6 148272304 148552048 +990867 UST chr6 148747030 149076990 +990896 UST-AS1 chr6 148955628 148964684 +990901 AL357992.1 chr6 149027700 149032573 +990905 AL031056.1 chr6 149217926 149245554 +990922 TAB2 chr6 149218641 149411613 +991047 TAB2-AS1 chr6 149243299 149257551 +991056 AL031056.2 chr6 149246095 149255415 +991061 SUMO4 chr6 149400262 149401278 +991069 ZC3H12D chr6 149446795 149485014 +991114 PPIL4 chr6 149504495 149546043 +991157 AL078581.3 chr6 149561152 149563949 +991161 GINM1 chr6 149566294 149591748 +991215 AL078581.4 chr6 149576089 149590864 +991222 AL078581.2 chr6 149591755 149592663 +991226 KATNA1 chr6 149594873 149648972 +991350 LATS1 chr6 149658153 149718105 +991456 AL358852.1 chr6 149717621 149718888 +991459 NUP43 chr6 149724315 149749665 +991549 PCMT1 chr6 149749443 149811420 +991772 AL355312.2 chr6 149796151 149799150 +991779 LRP11 chr6 149818757 149864359 +991815 AL355312.4 chr6 149852462 149853192 +991819 AL355312.3 chr6 149863494 149919507 +991823 RAET1E chr6 149883375 149898102 +991902 RAET1E-AS1 chr6 149884431 149919508 +991911 RAET1G chr6 149916878 149923121 +991952 ULBP2 chr6 149942014 149949235 +991968 ULBP1 chr6 149963943 149973715 +991984 RAET1L chr6 150018334 150025532 +992013 AL355497.2 chr6 150040547 150042033 +992017 ULBP3 chr6 150061053 150069121 +992045 PPP1R14C chr6 150143044 150250392 +992059 IYD chr6 150368892 150405969 +992189 PLEKHG1 chr6 150599883 150843665 +992328 AL450344.3 chr6 150600834 150605850 +992332 AL450344.1 chr6 150624677 150626086 +992336 AL450344.2 chr6 150650772 150652025 +992340 MTHFD1L chr6 150865549 151101887 +992644 AL133260.2 chr6 151054897 151056057 +992648 AL138733.1 chr6 151088103 151228447 +992655 AL138733.2 chr6 151196681 151197638 +992659 AKAP12 chr6 151239967 151358559 +992713 ZBTB2 chr6 151364115 151391559 +992725 RMND1 chr6 151404762 151452158 +992926 ARMT1 chr6 151452258 151470101 +992973 CCDC170 chr6 151494017 151621193 +993009 ESR1 chr6 151656691 152129619 +993196 AL356311.1 chr6 151813276 151814179 +993200 AL078582.2 chr6 152091712 152094009 +993204 AL078582.1 chr6 152112759 152118397 +993208 SYNE1 chr6 152121684 152637801 +995467 SYNE1-AS1 chr6 152380546 152381564 +995471 AL049548.1 chr6 152402398 152404966 +995475 NANOGP11 chr6 152545930 152546984 +995479 MYCT1 chr6 152697895 152724567 +995507 VIP chr6 152750797 152759765 +995559 LINC02840 chr6 152754903 152875991 +995629 FBXO5 chr6 152970519 152983579 +995663 AL080276.2 chr6 152983331 152991322 +995680 MTRF1L chr6 152987362 153002709 +995790 RGS17 chr6 153004459 153131282 +995819 AL590867.1 chr6 153231320 153347488 +995824 AL358134.1 chr6 153304595 153427154 +995834 OPRM1 chr6 154010496 154246867 +996097 IPCEF1 chr6 154154496 154356792 +996289 CNKSR3 chr6 154387515 154510685 +996382 AL357075.3 chr6 154477982 154479593 +996386 AL357075.4 chr6 154510791 154522307 +996390 SCAF8 chr6 154733325 154834244 +996549 TIAM2 chr6 154832697 155257723 +996998 AL596202.1 chr6 155253139 155256724 +997002 TFB1M chr6 155256134 155314493 +997057 CLDN20 chr6 155264013 155276548 +997067 AL031773.1 chr6 155380511 155381183 +997071 NOX3 chr6 155395368 155455839 +997105 AL589693.1 chr6 155911195 156397589 +997111 AL512658.2 chr6 156350579 156390246 +997117 AL512658.1 chr6 156493226 156505011 +997132 AL355297.3 chr6 156774217 156774662 +997135 ARID1B chr6 156776020 157210779 +997754 AL355297.4 chr6 156776360 156778422 +997758 AL355297.2 chr6 156780327 156780455 +997761 AL049820.1 chr6 157107727 157119706 +997765 TMEM242 chr6 157289386 157323601 +997790 AL390955.2 chr6 157323964 157324477 +997793 AL117344.2 chr6 157377062 157380896 +997796 ZDHHC14 chr6 157381133 157678157 +997903 SNX9 chr6 157700387 157945077 +997975 AL391863.2 chr6 157829143 157830573 +997979 AL391863.1 chr6 157872571 157875210 +997988 AL035634.1 chr6 157885114 157892786 +997992 SYNJ2 chr6 157981863 158099176 +998249 AL139330.1 chr6 158000109 158000749 +998253 SYNJ2-IT1 chr6 158001107 158002383 +998258 SERAC1 chr6 158109519 158168280 +998806 GTF2H5 chr6 158168350 158199344 +998831 TULP4 chr6 158232236 158511828 +998929 AL360169.2 chr6 158282841 158428379 +998933 AL360169.3 chr6 158296671 158303372 +998937 AL360169.1 chr6 158397885 158398561 +998941 TMEM181 chr6 158536436 158635428 +998981 DYNLT1 chr6 158636474 158644743 +999004 SYTL3 chr6 158650014 158764876 +999170 EZR chr6 158765741 158819368 +999274 EZR-AS1 chr6 158817979 158822252 +999279 AL627422.2 chr6 158853588 158864502 +999285 C6orf99 chr6 158869848 158919105 +999354 RSPH3 chr6 158972871 159000187 +999417 AL035530.2 chr6 158988178 159088114 +999517 TAGAP chr6 159034468 159045152 +999610 AL356417.3 chr6 159051674 159121495 +999620 AL356417.1 chr6 159094093 159116254 +999642 AL356417.2 chr6 159165899 159170007 +999650 FNDC1 chr6 159169400 159272108 +999753 FNDC1-IT1 chr6 159240786 159243329 +999757 AL357832.1 chr6 159353922 159383339 +999772 LINC02529 chr6 159383422 159401147 +999804 AL078604.4 chr6 159468601 159662627 +999808 AL078604.2 chr6 159586955 159589169 +999812 SOD2 chr6 159669069 159745186 +999964 WTAP chr6 159725585 159756319 +1000089 SOD2-OT1 chr6 159760258 159762332 +1000093 ACAT2 chr6 159762045 159779112 +1000128 TCP1 chr6 159778498 159789703 +1000353 MRPL18 chr6 159789812 159798436 +1000382 PNLDC1 chr6 159800249 159820704 +1000566 AL035691.1 chr6 159899186 159902510 +1000570 MAS1 chr6 159906690 159916530 +1000578 IGF2R chr6 159969099 160113507 +1000729 AIRN chr6 160003291 160007664 +1000736 SLC22A1 chr6 160121815 160158718 +1000870 SLC22A2 chr6 160171061 160277638 +1000944 AL162582.1 chr6 160272617 160276130 +1000948 SLC22A3 chr6 160348378 160452577 +1000976 AL591069.1 chr6 160369200 160386934 +1000982 LPA chr6 160531483 160664259 +1001110 AL109933.1 chr6 160698288 160700632 +1001117 PLG chr6 160702238 160753315 +1001227 AL109933.5 chr6 160742509 160767490 +1001231 AL391361.2 chr6 160872888 160926204 +1001253 AL139393.2 chr6 160926269 160943110 +1001267 AL139393.1 chr6 160931080 160985624 +1001279 AL139393.3 chr6 160990318 160992342 +1001282 MAP3K4 chr6 160991727 161117385 +1001702 AGPAT4 chr6 161129967 161274061 +1001789 PRKN chr6 161347417 162727771 +1002034 AL132982.1 chr6 161353679 161355350 +1002038 AL138716.1 chr6 161435098 161446016 +1002042 PACRG chr6 162727132 163315492 +1002155 AL590286.2 chr6 162969050 162975007 +1002160 PACRG-AS2 chr6 163042557 163054161 +1002179 AL137182.1 chr6 163115691 163137775 +1002184 PACRG-AS3 chr6 163163830 163192038 +1002326 PACRG-AS1 chr6 163306907 163324530 +1002352 AL031121.2 chr6 163338363 163346744 +1002374 AL031121.3 chr6 163348019 163353220 +1002378 CAHM chr6 163413065 163413960 +1002381 QKI chr6 163414000 163578592 +1002634 AL445307.1 chr6 163586583 163588165 +1002638 AL078602.1 chr6 163671577 164231610 +1002710 AL137005.1 chr6 163705937 163714306 +1002715 AL136225.1 chr6 163956299 163960187 +1002719 Z97205.2 chr6 164084023 164085661 +1002722 Z97205.1 chr6 164108620 164109694 +1002726 AL358972.1 chr6 164346489 164348644 +1002730 AL450345.2 chr6 164791288 164827683 +1002762 AL450345.1 chr6 164827732 164832114 +1002776 AL133538.1 chr6 164928191 165077495 +1002782 C6orf118 chr6 165279664 165309605 +1002816 PDE10A chr6 165327287 165988078 +1003475 AL590302.2 chr6 165754189 165775780 +1003479 AL590302.1 chr6 165773056 165775221 +1003487 LINC00602 chr6 165987551 165989615 +1003490 AL627443.3 chr6 166098111 166099589 +1003494 AL627443.1 chr6 166099665 166113273 +1003499 TBXT chr6 166157656 166168700 +1003578 AL121956.1 chr6 166236969 166256947 +1003585 AL121956.4 chr6 166275462 166277077 +1003589 PRR18 chr6 166305300 166308448 +1003604 AL121956.6 chr6 166309572 166317470 +1003608 SFT2D1 chr6 166319728 166342576 +1003662 AL022069.3 chr6 166342632 166351466 +1003669 MPC1 chr6 166364919 166383013 +1003747 AL022069.1 chr6 166383189 166384824 +1003750 RPS6KA2 chr6 166409364 166906451 +1004092 RPS6KA2-IT1 chr6 166460663 166465383 +1004098 RAMACL chr6 166585604 166587594 +1004106 AL023775.2 chr6 166651524 166655610 +1004110 RPS6KA2-AS1 chr6 166903698 166904835 +1004114 RNASET2 chr6 166929504 166957191 +1004345 Z94721.1 chr6 166969626 166999065 +1004350 Z94721.3 chr6 166995735 166999511 +1004354 FGFR1OP chr6 166999317 167094789 +1004468 CCR6 chr6 167111807 167139696 +1004526 AL121935.1 chr6 167114957 167121527 +1004532 AL121935.2 chr6 167126223 167131572 +1004538 TCP10L2 chr6 167146414 167196913 +1004610 GPR31 chr6 167156271 167158329 +1004618 AL121935.3 chr6 167164565 167167233 +1004622 AL353747.4 chr6 167228300 167237511 +1004637 AL353747.3 chr6 167237508 167240480 +1004641 AL353747.2 chr6 167241891 167245916 +1004645 UNC93A chr6 167271169 167316014 +1004705 TTLL2 chr6 167325071 167359503 +1004754 TCP10 chr6 167357031 167384510 +1004888 AL356123.1 chr6 167644479 167658518 +1004893 LINC02538 chr6 167666840 167679270 +1004898 AL356123.2 chr6 167678232 167679523 +1004902 LINC02487 chr6 167679626 167696290 +1004922 LINC01558 chr6 167784537 167796872 +1004932 AL009178.2 chr6 167795530 167798248 +1004935 AL009178.3 chr6 167796647 167825145 +1004941 AFDN-DT chr6 167822103 167826812 +1004956 AFDN chr6 167826922 167972023 +1005608 HGC6.3 chr6 167975924 167979776 +1005615 KIF25-AS1 chr6 167992822 167997110 +1005630 KIF25 chr6 167996241 168045095 +1005781 FRMD1 chr6 168053166 168101511 +1006040 AL611929.1 chr6 168194358 168204501 +1006044 AL606970.5 chr6 168217032 168220262 +1006048 AL606970.4 chr6 168225279 168226517 +1006052 AL606970.2 chr6 168229732 168240715 +1006057 AL606970.3 chr6 168242938 168262581 +1006067 DACT2 chr6 168292830 168319777 +1006118 AL606970.1 chr6 168298069 168302114 +1006122 AL138918.1 chr6 168374697 168375355 +1006125 SMOC2 chr6 168441151 168673445 +1006228 AL136099.1 chr6 168716606 168723495 +1006233 AL513210.1 chr6 168920394 168964386 +1006247 AL109924.4 chr6 168999401 169000527 +1006251 AL109924.1 chr6 169034197 169035642 +1006255 AL109924.2 chr6 169067764 169069427 +1006269 AL136129.1 chr6 169097799 169102428 +1006273 LINC01615 chr6 169157162 169162992 +1006293 LINC02544 chr6 169175277 169182841 +1006298 BX322234.1 chr6 169213254 169245773 +1006311 THBS2 chr6 169215780 169254044 +1006482 BX322234.2 chr6 169286534 169289216 +1006490 LINC02519 chr6 169369998 169388385 +1006497 AL009176.1 chr6 169419004 169425156 +1006501 AL135910.1 chr6 169426420 169452475 +1006506 WDR27 chr6 169457212 169702067 +1006944 C6orf120 chr6 169702190 169704856 +1006952 PHF10 chr6 169703902 169725566 +1007074 AL354892.2 chr6 169725091 169725854 +1007079 AL354892.1 chr6 169725504 169738992 +1007083 TCTE3 chr6 169740109 169751587 +1007099 ERMARD chr6 169751622 169781600 +1007425 AL354892.3 chr6 169770413 169772042 +1007428 LINC00242 chr6 169788790 169799549 +1007435 LINC00574 chr6 169790057 169802873 +1007440 AL049612.1 chr6 169809318 169810102 +1007444 AL603783.1 chr6 170088022 170097234 +1007452 AL596442.4 chr6 170135374 170142926 +1007457 AL596442.3 chr6 170158728 170160471 +1007461 AL596442.1 chr6 170160606 170163142 +1007472 AL596442.2 chr6 170178681 170179660 +1007475 AL109910.1 chr6 170254334 170262569 +1007480 AL109910.2 chr6 170266669 170276762 +1007485 LINC01624 chr6 170272474 170279887 +1007495 DLL1 chr6 170282206 170306565 +1007532 FAM120B chr6 170290703 170407065 +1007640 AL078605.1 chr6 170297876 170298375 +1007643 AL008628.1 chr6 170414139 170419325 +1007646 PSMB1 chr6 170535120 170553307 +1007670 TBP chr6 170554302 170572870 +1007807 PDCD2 chr6 170575295 170584692 +1008000 AL031259.1 chr6 170612622 170638715 +1008005 AL672310.1 chr6 170615515 170738536 +1008020 AL731661.1 chr6 170695313 170696950 +1008025 AL731684.1 chr6 170736173 170737777 +1008030 AC215522.3 chr7 12704 27234 +1008037 AC215522.2 chr7 19018 35489 +1008052 AC093627.1 chr7 70972 95683 +1008057 AC093627.6 chr7 77038 81178 +1008061 AC093627.22 chr7 115186 132034 +1008066 AC093627.5 chr7 135853 149527 +1008119 AC093627.4 chr7 149549 155465 +1008141 AC093627.7 chr7 161765 164972 +1008144 AC093627.2 chr7 174920 176013 +1008149 AC093627.3 chr7 182935 194180 +1008154 FAM20C chr7 192571 260772 +1008198 AC187653.1 chr7 290170 294422 +1008216 AC188616.1 chr7 329776 333172 +1008221 AC226118.1 chr7 379359 382712 +1008226 AC188617.1 chr7 425373 439389 +1008236 AC188617.2 chr7 446281 448823 +1008240 AC147651.3 chr7 484107 496118 +1008245 PDGFA chr7 497258 520296 +1008316 AC147651.1 chr7 520391 525238 +1008332 PRKAR1B chr7 549197 727650 +1008548 AC147651.2 chr7 561958 565619 +1008552 AC147651.4 chr7 603185 608482 +1008556 DNAAF5 chr7 726699 786475 +1008660 SUN1 chr7 816615 896435 +1009214 GET4 chr7 876554 896436 +1009300 AC073957.3 chr7 879790 886547 +1009303 ADAP1 chr7 897900 955407 +1009598 COX19 chr7 898778 975549 +1009645 CYP2W1 chr7 983181 989640 +1009710 C7orf50 chr7 996986 1138260 +1009800 AC073957.1 chr7 1029025 1043891 +1009804 GPR146 chr7 1044546 1059261 +1009836 AC073957.2 chr7 1055360 1059261 +1009840 AC091729.1 chr7 1074450 1078036 +1009845 AC091729.2 chr7 1080863 1082178 +1009849 GPER1 chr7 1082208 1093815 +1009914 ZFAND2A chr7 1152071 1160759 +1009979 AC091729.3 chr7 1160374 1165607 +1010010 UNCX chr7 1232872 1237326 +1010022 AC073094.1 chr7 1267353 1269267 +1010026 MICALL2 chr7 1428465 1459470 +1010183 AC102953.1 chr7 1459937 1464008 +1010187 AC102953.2 chr7 1464497 1467522 +1010190 INTS1 chr7 1470277 1504389 +1010338 AC093734.1 chr7 1508655 1509427 +1010342 MAFK chr7 1530702 1543043 +1010376 TMEM184A chr7 1542235 1560821 +1010503 PSMG3 chr7 1567332 1571005 +1010535 PSMG3-AS1 chr7 1570073 1589626 +1010580 AC074389.2 chr7 1620654 1621405 +1010584 ELFN1 chr7 1688119 1747954 +1010605 AC074389.3 chr7 1691906 1692450 +1010609 AC074389.1 chr7 1692810 1694357 +1010618 ELFN1-AS1 chr7 1738630 1742291 +1010625 MAD1L1 chr7 1815793 2233243 +1010910 AC104129.1 chr7 1838586 1849931 +1010917 MRM2 chr7 2234222 2242205 +1010959 NUDT1 chr7 2242222 2251146 +1011054 SNX8 chr7 2251770 2354318 +1011159 EIF3B chr7 2354086 2380745 +1011319 CHST12 chr7 2403588 2448484 +1011348 GRIFIN chr7 2474844 2476894 +1011367 LFNG chr7 2512529 2529177 +1011503 BRAT1 chr7 2537810 2555694 +1011585 IQCE chr7 2558972 2614733 +1012071 TTYH3 chr7 2631986 2664802 +1012193 AMZ1 chr7 2679522 2775500 +1012248 GNA12 chr7 2728105 2844308 +1012312 CARD11 chr7 2906141 3043945 +1012399 AC004906.1 chr7 2944035 2947091 +1012403 AC024028.1 chr7 3083252 3118049 +1012410 AC073316.1 chr7 3140234 3174654 +1012431 AC073316.2 chr7 3196626 3198256 +1012436 AC073316.3 chr7 3264032 3302452 +1012440 SDK1 chr7 3301252 4269000 +1012775 AC011284.1 chr7 3642815 3643784 +1012779 AC017000.1 chr7 4130181 4134837 +1012784 AC072054.1 chr7 4642248 4642570 +1012787 FOXK1 chr7 4682295 4771442 +1012821 AC092428.1 chr7 4725440 4728721 +1012825 AP5Z1 chr7 4775615 4794397 +1013138 RADIL chr7 4797055 4883716 +1013243 PAPOLB chr7 4857738 4862030 +1013251 MMD2 chr7 4905989 4959213 +1013330 RBAK chr7 5045821 5069487 +1013367 RBAKDN chr7 5072125 5073223 +1013372 WIPI2 chr7 5190196 5233840 +1013577 SLC29A4 chr7 5274369 5306870 +1013689 TNRC18 chr7 5306790 5425414 +1013888 AC093620.1 chr7 5419827 5420767 +1013892 AC092171.1 chr7 5419846 5423122 +1013896 AC092171.4 chr7 5425770 5426401 +1013899 AC092171.3 chr7 5426277 5428927 +1013902 AC092171.5 chr7 5428731 5429672 +1013905 FBXL18 chr7 5431335 5513809 +1013977 AC092171.2 chr7 5475804 5479811 +1013981 ACTB chr7 5527148 5563784 +1014147 AC006483.2 chr7 5556731 5557245 +1014150 FSCN1 chr7 5592816 5606655 +1014204 RNF216 chr7 5620047 5781739 +1014369 RNF216-IT1 chr7 5662432 5680461 +1014374 OCM chr7 5879827 5886363 +1014403 CCZ1 chr7 5898725 5926550 +1014490 RSPH10B chr7 5925550 5970683 +1014702 PMS2 chr7 5970925 6009106 +1014954 AIMP2 chr7 6009255 6023834 +1015005 EIF2AK1 chr7 6022247 6059175 +1015112 ANKRD61 chr7 6031376 6036552 +1015123 AC004895.1 chr7 6080704 6093085 +1015141 USP42 chr7 6104884 6161564 +1015337 CYTH3 chr7 6161776 6272644 +1015441 FAM220A chr7 6329411 6348981 +1015469 AC009412.1 chr7 6329412 6348959 +1015487 RAC1 chr7 6374527 6403967 +1015545 DAGLB chr7 6409126 6484190 +1015709 KDELR2 chr7 6445953 6484190 +1015760 GRID2IP chr7 6497462 6551436 +1015903 ZDHHC4 chr7 6577434 6589374 +1016074 AC079742.1 chr7 6578565 6588974 +1016078 C7orf26 chr7 6590021 6608726 +1016146 ZNF853 chr7 6615610 6624290 +1016158 ZNF316 chr7 6637318 6658279 +1016200 AC073343.2 chr7 6663974 6708901 +1016216 ZNF12 chr7 6688433 6706947 +1016279 RSPH10B2 chr7 6754109 6799365 +1016501 CCZ1B chr7 6794134 6826770 +1016639 AC079804.3 chr7 6952625 7104482 +1016647 C1GALT1 chr7 7156934 7248651 +1016707 AC005532.1 chr7 7255154 7278071 +1016732 COL28A1 chr7 7356203 7535873 +1016893 AC004982.1 chr7 7550104 7552440 +1016897 AC004982.2 chr7 7552462 7566996 +1016909 MIOS chr7 7566875 7608932 +1017020 AC004948.1 chr7 7619872 7620543 +1017023 RPA3 chr7 7636518 7718607 +1017095 UMAD1 chr7 7640711 7968020 +1017196 AC006042.4 chr7 7949853 7950709 +1017200 AC006042.2 chr7 7958183 7969903 +1017204 GLCCI1 chr7 7968796 8094272 +1017304 ICA1 chr7 8113184 8262687 +1017707 AC006042.1 chr7 8114025 8116561 +1017712 AC007009.1 chr7 8262233 8262821 +1017716 AC007128.2 chr7 8303741 8341343 +1017724 NXPH1 chr7 8433609 8752961 +1017761 AC004852.2 chr7 9082557 9189857 +1017776 AC060834.2 chr7 9621764 9769513 +1017798 AC010991.1 chr7 9869774 9985895 +1017816 AC004936.1 chr7 9981516 10085494 +1017820 AC004879.1 chr7 10207670 10239863 +1017826 AC004949.1 chr7 10449820 10779944 +1017831 AC004415.1 chr7 10702676 10707406 +1017835 NDUFA4 chr7 10931943 10940153 +1017867 AC007029.1 chr7 10940423 10940735 +1017870 PHF14 chr7 10973336 11169630 +1018128 AC004160.1 chr7 11180902 11520175 +1018198 THSD7A chr7 11370365 11832198 +1018332 AC004160.2 chr7 11406955 11414078 +1018337 TMEM106B chr7 12211270 12243367 +1018433 VWDE chr7 12330885 12403941 +1018714 AC013470.2 chr7 12469621 12542222 +1018780 AC005281.1 chr7 12570125 12571392 +1018784 SCIN chr7 12570577 12660182 +1018952 AC011891.2 chr7 12654179 12654985 +1018956 ARL4A chr7 12686856 12690958 +1019020 AC011287.1 chr7 12726152 13751920 +1019089 AC011287.2 chr7 13339201 13365049 +1019096 AC005019.2 chr7 13854355 13862118 +1019104 ETV1 chr7 13891229 13991425 +1019515 DGKB chr7 14145049 14974777 +1019874 AC006150.1 chr7 14814131 14816565 +1019879 AC006458.1 chr7 15066207 15068651 +1019883 AGMO chr7 15200317 15562015 +1019936 MEOX2 chr7 15611212 15686683 +1019948 AC005550.2 chr7 15667947 15681980 +1019954 LINC02587 chr7 15688378 15696886 +1019962 AC005550.1 chr7 15689075 15690854 +1019966 AC006041.2 chr7 15736373 15796370 +1019970 AC006041.1 chr7 15841297 15842360 +1019974 CRPPA chr7 16087525 16421538 +1020026 CRPPA-AS1 chr7 16210484 16270604 +1020060 SOSTDC1 chr7 16461481 16530580 +1020085 AC005014.3 chr7 16471184 16471373 +1020088 LRRC72 chr7 16526825 16581568 +1020129 AC005014.2 chr7 16593626 16594224 +1020132 ANKMY2 chr7 16599779 16645817 +1020236 AC005014.4 chr7 16603816 16616295 +1020242 BZW2 chr7 16646131 16706523 +1020550 AC073333.1 chr7 16695871 16719898 +1020556 TSPAN13 chr7 16753755 16784536 +1020580 AGR2 chr7 16791811 16833433 +1020663 AGR3 chr7 16859412 16881987 +1020721 AHR chr7 16916359 17346152 +1020826 AC073332.1 chr7 16970320 17299368 +1020898 AC019117.2 chr7 17374867 17467256 +1020918 AC019117.1 chr7 17405479 17558909 +1021115 AC006482.1 chr7 17679549 17680659 +1021119 SNX13 chr7 17790761 17940501 +1021407 PRPS1L1 chr7 18026770 18027846 +1021420 HDAC9 chr7 18086949 19002416 +1021989 AC010082.1 chr7 18429062 18430738 +1021993 AC004994.1 chr7 18892096 18899433 +1021998 TWIST1 chr7 19020991 19117636 +1022028 AC003986.2 chr7 19112474 19114271 +1022032 AC003986.3 chr7 19119933 19121916 +1022036 AC003986.1 chr7 19144293 19146253 +1022040 FERD3L chr7 19144782 19145421 +1022048 AC007091.1 chr7 19353531 19578606 +1022060 TWISTNB chr7 19695461 19709037 +1022077 TMEM196 chr7 19719310 19773598 +1022146 AC004543.1 chr7 19813685 19818090 +1022152 AC005062.1 chr7 19918981 20140453 +1022203 AC007001.1 chr7 20096137 20130475 +1022210 MACC1 chr7 20134655 20217404 +1022268 MACC1-AS1 chr7 20141916 20153531 +1022274 AC005083.1 chr7 20217577 20221700 +1022289 AC099342.1 chr7 20296637 20314512 +1022333 AC004130.2 chr7 20328299 20331747 +1022343 ITGB8 chr7 20330702 20415754 +1022428 ABCB5 chr7 20615207 20777038 +1022592 SP8 chr7 20782283 20786886 +1022624 LINC01162 chr7 20835376 21023362 +1022642 AC080068.1 chr7 20959391 21028813 +1022650 SP4 chr7 21428043 21514822 +1022710 DNAH11 chr7 21543039 21901839 +1023264 CDCA7L chr7 21900899 21945903 +1023395 RAPGEF5 chr7 22118236 22357154 +1023681 STEAP1B chr7 22419444 22727613 +1023763 AC002480.1 chr7 22563337 22573996 +1023769 AC002480.2 chr7 22589698 22602536 +1023777 AC073072.1 chr7 22725395 22727620 +1023781 IL6 chr7 22725884 22732002 +1023885 TOMM7 chr7 22812628 22822852 +1023941 AC005682.2 chr7 22822954 22833430 +1023945 SNHG26 chr7 22854126 22872945 +1024017 FAM126A chr7 22889371 23014130 +1024137 KLHL7-DT chr7 23100214 23105703 +1024146 KLHL7 chr7 23105758 23177914 +1024300 NUP42 chr7 23181841 23201011 +1024428 AC005082.2 chr7 23200131 23206059 +1024432 AC005082.1 chr7 23205787 23208045 +1024435 GPNMB chr7 23235967 23275108 +1024581 MALSU1 chr7 23298739 23311729 +1024608 IGF2BP3 chr7 23310209 23470491 +1024786 TRA2A chr7 23504780 23532041 +1024924 CCDC126 chr7 23597382 23644708 +1024991 FAM221A chr7 23680130 23703249 +1025109 AC006026.3 chr7 23680195 23680786 +1025113 STK31 chr7 23710203 23832513 +1025398 AC003087.1 chr7 23891704 23897335 +1025402 AC004485.1 chr7 24196662 24255719 +1025406 NPY chr7 24284188 24291862 +1025444 AC003044.1 chr7 24318094 24445128 +1025448 MPP6 chr7 24573268 24694193 +1025613 GSDME chr7 24698355 24757940 +1025786 AC003093.1 chr7 24778444 24795496 +1025791 OSBPL3 chr7 24796540 24981634 +1026214 CYCS chr7 25120091 25125361 +1026261 C7orf31 chr7 25134692 25180356 +1026347 NPVF chr7 25224570 25228486 +1026359 AC004129.3 chr7 25254965 25257129 +1026363 AC003985.1 chr7 25321302 25326865 +1026376 AC005100.1 chr7 25358235 25432202 +1026390 AC005100.2 chr7 25431980 25500443 +1026395 AC091705.1 chr7 25547762 25551062 +1026399 AC005165.1 chr7 25593304 25751032 +1026529 AC005165.3 chr7 25750890 25756256 +1026533 AC018706.1 chr7 25831335 25831909 +1026537 AC010719.1 chr7 25948657 25949403 +1026540 NFE2L3 chr7 26152198 26187137 +1026563 HNRNPA2B1 chr7 26173057 26201529 +1026734 CBX3 chr7 26201162 26213607 +1026818 AC010677.2 chr7 26226413 26254709 +1026822 SNX10 chr7 26291895 26374329 +1026962 AC004540.2 chr7 26369310 26376701 +1026975 AC004540.1 chr7 26398593 26497595 +1027092 KIAA0087 chr7 26533121 26538788 +1027096 AC004947.1 chr7 26551686 26558880 +1027123 AC004947.3 chr7 26598600 26617295 +1027129 LINC02860 chr7 26637871 26647305 +1027139 SKAP2 chr7 26667068 26995239 +1027235 HOXA1 chr7 27093313 27095996 +1027256 HOTAIRM1 chr7 27095647 27100265 +1027276 HOXA2 chr7 27100354 27102686 +1027288 HOXA3 chr7 27106184 27152581 +1027354 HOXA-AS2 chr7 27107777 27134302 +1027401 HOXA4 chr7 27128507 27130780 +1027437 HOXA-AS3 chr7 27129977 27155928 +1027457 HOXA5 chr7 27141052 27143681 +1027470 HOXA6 chr7 27145396 27150603 +1027484 HOXA7 chr7 27153716 27157936 +1027506 AC004080.4 chr7 27158344 27158976 +1027509 HOXA9 chr7 27162438 27175180 +1027544 HOXA10-AS chr7 27168619 27171915 +1027555 HOXA10 chr7 27170592 27180261 +1027593 HOXA11 chr7 27181510 27185223 +1027612 HOXA11-AS chr7 27184507 27189298 +1027649 AC004080.2 chr7 27186573 27193448 +1027653 HOXA13 chr7 27193503 27200091 +1027666 HOTTIP chr7 27198575 27207259 +1027679 AC004080.17 chr7 27210801 27212965 +1027683 AC004080.1 chr7 27239243 27241228 +1027687 EVX1-AS chr7 27241429 27247229 +1027700 EVX1 chr7 27242700 27250493 +1027737 AC004009.1 chr7 27361591 27410358 +1027755 HIBADH chr7 27525442 27662883 +1027812 AC007130.1 chr7 27617474 27627496 +1027816 AC005091.1 chr7 27733064 27740395 +1027820 TAX1BP1 chr7 27739331 27844564 +1028115 JAZF1 chr7 27830573 28180795 +1028222 AC004549.1 chr7 27873785 27876546 +1028226 JAZF1-AS1 chr7 28180322 28243917 +1028246 CREB5 chr7 28299321 28825894 +1028440 TRIL chr7 28953358 28958330 +1028448 AC005013.1 chr7 28957667 28959345 +1028452 AC005162.3 chr7 28979967 29013367 +1028473 AC005162.2 chr7 28987028 28988899 +1028477 CPVL chr7 28995235 29195451 +1028689 AC005162.1 chr7 29080284 29082527 +1028694 AC005232.1 chr7 29122274 29128172 +1028713 AC004593.3 chr7 29122340 29514667 +1028763 CHN2 chr7 29146569 29514328 +1029037 AC004593.2 chr7 29191582 29194109 +1029040 AC004593.1 chr7 29199540 29208970 +1029045 AC007255.1 chr7 29514224 29563670 +1029053 PRR15 chr7 29563835 29567293 +1029070 WIPF3 chr7 29806486 29917066 +1029135 SCRN1 chr7 29920104 29990289 +1029289 AC007285.1 chr7 29988600 30027543 +1029299 FKBP14 chr7 30010587 30026684 +1029340 PLEKHA8 chr7 30027404 30130483 +1029587 AC007285.2 chr7 30069658 30075115 +1029592 AC007036.5 chr7 30129507 30134714 +1029597 MTURN chr7 30134986 30162762 +1029636 AC007036.2 chr7 30140870 30141417 +1029640 AC007036.3 chr7 30157531 30159534 +1029644 AC007036.1 chr7 30176387 30179014 +1029648 ZNRF2 chr7 30284597 30367689 +1029667 LINC01176 chr7 30390885 30412375 +1029679 NOD1 chr7 30424527 30478784 +1029804 AC006027.1 chr7 30424672 30425412 +1029807 GGCT chr7 30496621 30504841 +1029902 GARS-DT chr7 30516309 30595286 +1030130 AC005154.4 chr7 30525731 30533613 +1030135 AC005154.3 chr7 30550217 30551569 +1030139 GARS chr7 30594838 30634033 +1030253 CRHR2 chr7 30651942 30700129 +1030438 INMT chr7 30697985 30757602 +1030469 MINDY4 chr7 30771417 30892387 +1030521 AC004691.1 chr7 30796691 30803410 +1030525 AQP1 chr7 30911694 30925517 +1030622 GHRHR chr7 30938669 30993254 +1030796 ADCYAP1R1 chr7 31052461 31111479 +1031006 AC006398.1 chr7 31202831 31235648 +1031012 NEUROD6 chr7 31337465 31340726 +1031022 AC005090.1 chr7 31414158 31421303 +1031028 ITPRID1 chr7 31514071 31658720 +1031261 PPP1R17 chr7 31687215 31708455 +1031295 PDE1C chr7 31751179 32428131 +1031542 AC018637.1 chr7 32427901 32431804 +1031546 LSM5 chr7 32485338 32495283 +1031674 AVL9 chr7 32495426 32588726 +1031820 AC018645.3 chr7 32758882 32759353 +1031823 LINC00997 chr7 32760279 32762924 +1031826 AC018648.1 chr7 32845394 32846061 +1031829 KBTBD2 chr7 32868172 32894131 +1031892 FKBP9 chr7 32957404 33006930 +1032023 NT5C3A chr7 33014114 33062797 +1032221 RP9 chr7 33094797 33109404 +1032261 BBS9 chr7 33109557 33877180 +1033159 AC008080.1 chr7 33725981 33728456 +1033163 AC008080.2 chr7 33730292 33732064 +1033167 AC008080.4 chr7 33793167 33803190 +1033190 AC008080.3 chr7 33868501 33874231 +1033195 BMPER chr7 33904308 34156427 +1033888 AC007350.1 chr7 34124948 34128126 +1033892 AC009262.1 chr7 34209465 34299012 +1033902 NPSR1-AS1 chr7 34346512 34871582 +1033942 NPSR1 chr7 34658218 34878332 +1034122 DPY19L1 chr7 34928876 35038271 +1034276 AC005400.1 chr7 35036836 35125012 +1034281 TBX20 chr7 35202430 35254100 +1034310 AC009531.1 chr7 35258381 35259729 +1034314 AC007652.3 chr7 35313838 35377071 +1034319 AC007652.2 chr7 35372349 35379675 +1034323 AC007652.1 chr7 35496021 35510263 +1034327 AC018647.3 chr7 35614650 35622939 +1034332 HERPUD2 chr7 35632659 35695571 +1034423 AC018647.2 chr7 35695214 35699413 +1034426 AC018647.1 chr7 35715032 35734924 +1034484 SEPTIN7-AS1 chr7 35751856 35800676 +1034524 SEPTIN7 chr7 35800932 35907105 +1034818 AC083864.5 chr7 35976596 36028174 +1034823 AC083864.2 chr7 36001317 36055431 +1034839 AC083864.4 chr7 36064715 36066679 +1034844 AC083864.1 chr7 36079084 36085736 +1034848 AC083864.3 chr7 36095255 36100660 +1034862 EEPD1 chr7 36153254 36301538 +1034923 AC007327.2 chr7 36229280 36231107 +1034927 AC006960.3 chr7 36319775 36320479 +1034930 KIAA0895 chr7 36324221 36390125 +1035084 ANLN chr7 36389821 36453791 +1035314 AC006960.2 chr7 36463023 36504513 +1035320 AOAH chr7 36512941 36724549 +1035526 AOAH-IT1 chr7 36597834 36600120 +1035531 AC007349.4 chr7 36734004 36734535 +1035534 AC007349.1 chr7 36750687 36763081 +1035539 AC007349.3 chr7 36781008 36782789 +1035543 AC007349.2 chr7 36838972 36841373 +1035547 ELMO1 chr7 36854361 37449249 +1035871 ELMO1-AS1 chr7 36997796 37013630 +1035876 GPR141 chr7 37683796 37833788 +1035917 EPDR1 chr7 37683843 37951936 +1035962 NME8 chr7 37848597 37900397 +1036091 SFRP4 chr7 37905932 38025695 +1036127 STARD3NL chr7 38178222 38230671 +1036258 TRGC2 chr7 38239580 38249572 +1036270 TRGJ2 chr7 38253380 38253429 +1036274 TRGJP2 chr7 38256337 38256396 +1036278 TRGC1 chr7 38257879 38265678 +1036288 TRGJ1 chr7 38269491 38269540 +1036292 TRGJP chr7 38273587 38273647 +1036296 TRGJP1 chr7 38276259 38276318 +1036300 TRGV11 chr7 38291616 38292078 +1036305 TRGVB chr7 38295763 38296233 +1036308 TRGV10 chr7 38299811 38300322 +1036314 TRGV9 chr7 38317017 38318861 +1036322 TRGVA chr7 38322446 38322730 +1036325 AC006033.2 chr7 38326070 38329643 +1036329 TRGV8 chr7 38330343 38330935 +1036337 TRGV7 chr7 38335041 38335514 +1036341 TRGV6 chr7 38340700 38340998 +1036344 TRG-AS1 chr7 38341577 38378804 +1036365 TRGV5P chr7 38345030 38345499 +1036369 TRGV5 chr7 38349355 38350022 +1036377 TRGV4 chr7 38353715 38354517 +1036385 TRGV3 chr7 38358512 38359162 +1036393 TRGV2 chr7 38362864 38363518 +1036401 TRGV1 chr7 38367586 38368169 +1036409 AMPH chr7 38383704 38631420 +1036570 VPS41 chr7 38722974 38932394 +1036838 POU6F2 chr7 38977998 39493095 +1036984 POU6F2-AS2 chr7 38980370 39013551 +1036992 POU6F2-AS1 chr7 39404590 39406579 +1037008 AC011290.1 chr7 39545646 39566239 +1037013 YAE1 chr7 39566385 39610320 +1037056 AC004837.3 chr7 39609610 39610290 +1037060 AC004837.4 chr7 39621253 39623201 +1037064 RALA chr7 39623565 39708120 +1037109 AC004837.2 chr7 39700341 39703296 +1037113 LINC00265 chr7 39733430 39793092 +1037175 AC072061.1 chr7 39947522 39949755 +1037178 CDK13 chr7 39950121 40099580 +1037521 MPLKIP chr7 40126027 40134622 +1037531 SUGCT chr7 40134977 40860763 +1037698 AC004988.1 chr7 40538127 40546928 +1037702 AC005160.1 chr7 40775558 40785217 +1037708 LINC01450 chr7 40964667 40979939 +1037713 LINC01449 chr7 41089539 41133507 +1037736 INHBA chr7 41667168 41705834 +1037779 INHBA-AS1 chr7 41693884 41779388 +1037807 GLI3 chr7 41960949 42237870 +1037947 LINC01448 chr7 42661716 42706447 +1037952 AC010132.1 chr7 42829672 42844438 +1037956 AC010132.4 chr7 42901272 42902639 +1037959 C7orf25 chr7 42908726 42912305 +1038010 PSMA2 chr7 42916861 42932185 +1038100 MRPL32 chr7 42932376 42948958 +1038135 AC005537.1 chr7 42954135 43113931 +1038203 HECW1 chr7 43112629 43566001 +1038372 HECW1-IT1 chr7 43117896 43163187 +1038381 AC004692.2 chr7 43239066 43249268 +1038392 LUARIS chr7 43508728 43522542 +1038397 STK17A chr7 43582758 43650713 +1038448 COA1 chr7 43608456 43729717 +1038701 BLVRA chr7 43758680 43807342 +1038766 MRPS24 chr7 43866558 43869893 +1038802 URGCP chr7 43875894 43926411 +1038940 UBE2D4 chr7 43926436 43956136 +1039103 SPDYE1 chr7 43997897 44010122 +1039146 AC004951.1 chr7 44004046 44007866 +1039151 LINC00957 chr7 44039171 44042306 +1039158 DBNL chr7 44044640 44069456 +1039635 PGAM2 chr7 44062727 44065567 +1039647 AC017116.1 chr7 44064908 44066079 +1039654 POLM chr7 44072062 44082530 +1039899 AEBP1 chr7 44104345 44114562 +1040049 POLD2 chr7 44114681 44124358 +1040251 MYL7 chr7 44138864 44141332 +1040361 GCK chr7 44143213 44198170 +1040569 YKT6 chr7 44200968 44214294 +1040637 CAMK2B chr7 44217150 44334577 +1041325 NUDCD3 chr7 44379119 44490658 +1041386 NPC1L1 chr7 44512535 44541315 +1041535 DDX56 chr7 44565417 44575051 +1041773 TMED4 chr7 44577894 44582287 +1041824 AC004938.2 chr7 44582519 44583676 +1041827 OGDH chr7 44606572 44709066 +1042184 ZMIZ2 chr7 44748581 44769881 +1042510 AC013436.1 chr7 44785050 44787340 +1042514 PPIA chr7 44796680 44824564 +1042638 H2AFV chr7 44826791 44848083 +1042745 LINC01952 chr7 44848416 44849568 +1042752 PURB chr7 44876299 44885530 +1042760 AC004854.2 chr7 44884953 44886393 +1042763 AC004847.1 chr7 44958999 44960909 +1042766 MYO1G chr7 44962662 44979088 +1043007 SNHG15 chr7 44983023 44986961 +1043074 CCM2 chr7 44999475 45076469 +1043347 NACAD chr7 45080437 45088969 +1043372 TBRG4 chr7 45100100 45112047 +1043566 RAMP3 chr7 45157791 45186302 +1043602 AC073968.2 chr7 45268681 45384802 +1043606 AC073325.1 chr7 45460712 45542182 +1043611 ADCY1 chr7 45574140 45723116 +1043717 CCDC201 chr7 45859994 45873082 +1043729 IGFBP1 chr7 45888360 45893660 +1043767 IGFBP3 chr7 45912245 45921874 +1043886 AC073115.2 chr7 45940449 45986472 +1043902 AC073115.1 chr7 45990905 46000898 +1043906 AC023669.1 chr7 46261064 46294469 +1043912 AC023669.2 chr7 46302120 46343621 +1043916 AC004869.2 chr7 46476457 46477940 +1043920 AC004869.1 chr7 46477822 46481578 +1043925 AC011294.1 chr7 46673785 46759851 +1043940 AC004870.4 chr7 46890625 47049678 +1043948 AC004870.2 chr7 46969644 47027481 +1043966 AC004870.3 chr7 47000620 47079128 +1043977 AC087175.1 chr7 47252139 47254558 +1043981 TNS3 chr7 47275154 47582558 +1044269 LINC01447 chr7 47608465 47629893 +1044286 C7orf65 chr7 47655244 47661648 +1044291 PKD1L1 chr7 47740202 47948491 +1044450 LINC00525 chr7 47761476 47766772 +1044455 C7orf69 chr7 47795291 47819847 +1044465 HUS1 chr7 47963288 47979615 +1044591 SUN3 chr7 47987148 48029119 +1044783 C7orf57 chr7 48035511 48061304 +1044897 UPP1 chr7 48088628 48108736 +1045094 ABCA13 chr7 48171458 48647497 +1045529 AC091770.1 chr7 48660125 48669479 +1045534 LINC02838 chr7 48708327 48711582 +1045539 CDC14C chr7 48919765 48927454 +1045557 AC091730.1 chr7 49230137 49254816 +1045563 AC092448.1 chr7 49524208 49587165 +1045567 VWC2 chr7 49773638 49921950 +1045581 ZPBP chr7 49850421 50121329 +1045657 AC034148.1 chr7 50093279 50094123 +1045661 SPATA48 chr7 50096036 50159830 +1045685 AC020743.1 chr7 50141540 50142823 +1045690 AC020743.2 chr7 50202001 50262994 +1045699 AC020743.3 chr7 50274790 50275622 +1045704 IKZF1 chr7 50304068 50405101 +1045987 AC124014.1 chr7 50388489 50400097 +1045994 FIGNL1 chr7 50444128 50542535 +1046153 DDC chr7 50458436 50565405 +1046487 DDC-AS1 chr7 50531759 50543463 +1046494 GRB10 chr7 50590063 50793462 +1047114 AC005153.1 chr7 50641725 50643868 +1047118 AC004920.1 chr7 50839363 50841992 +1047122 AC004830.2 chr7 50866747 51022990 +1047132 COBL chr7 51016212 51316818 +1047362 AC005999.2 chr7 51471717 51729716 +1047371 AC005999.1 chr7 51614251 51630870 +1047375 AC006478.1 chr7 51773836 51781162 +1047380 AC006478.2 chr7 51849086 51864798 +1047386 AC079763.1 chr7 52165235 52192913 +1047392 AC006459.1 chr7 52493152 52503434 +1047397 POM121L12 chr7 53035633 53036925 +1047405 AC009468.2 chr7 53514992 53517116 +1047409 AC009468.1 chr7 53559214 53574555 +1047418 LINC01446 chr7 53655508 53811952 +1047588 LINC02854 chr7 53926676 53947804 +1047598 AC092848.2 chr7 54185071 54257577 +1047603 AC092848.1 chr7 54201224 54202421 +1047606 LINC01445 chr7 54330670 54455093 +1047670 VSTM2A chr7 54542325 54571080 +1047749 VSTM2A-OT1 chr7 54556970 54571726 +1047755 AC011228.1 chr7 54576052 54578794 +1047759 AC011228.2 chr7 54721724 54731047 +1047763 SEC61G chr7 54752250 54759974 +1047829 AC074351.1 chr7 54759348 54812727 +1047838 EGFR chr7 55019017 55211628 +1048187 EGFR-AS1 chr7 55179750 55188934 +1048191 ELDR chr7 55235965 55255635 +1048197 LANCL2 chr7 55365448 55433742 +1048257 VOPP1 chr7 55436056 55572988 +1048467 AC099681.1 chr7 55573171 55588336 +1048472 AC099681.3 chr7 55592074 55593193 +1048476 AC099681.2 chr7 55593777 55595006 +1048480 SEPTIN14 chr7 55793540 55862755 +1048512 ZNF713 chr7 55887456 55942530 +1048583 NIPSNAP2 chr7 55951793 56000181 +1048730 MRPS17 chr7 55951877 55956500 +1048751 PSPH chr7 56011051 56051604 +1048911 CCT6A chr7 56051685 56063989 +1049005 SUMF2 chr7 56064002 56080670 +1049397 PHKG1 chr7 56080283 56092996 +1049536 CHCHD2 chr7 56101573 56106476 +1049554 NUPR2 chr7 56114681 56116417 +1049564 AC006970.3 chr7 56214979 56220747 +1049569 AC092447.4 chr7 56477588 56484386 +1049592 AC092447.8 chr7 56493124 56497285 +1049595 AC092447.5 chr7 56528253 56538676 +1049619 AC095038.5 chr7 56615084 56617957 +1049623 AC095038.4 chr7 56659149 56675086 +1049628 AC118758.3 chr7 56809214 56848800 +1049653 ZNF479 chr7 57119614 57139864 +1049698 AC099654.15 chr7 57140112 57153836 +1049704 AC099654.1 chr7 57209865 57222897 +1049714 AC099654.16 chr7 57242681 57245931 +1049719 AC237221.1 chr7 57404172 57419535 +1049796 ZNF716 chr7 57450177 57473559 +1049810 AC069285.2 chr7 63044827 63054431 +1049814 AC006455.1 chr7 63326674 63354326 +1049819 AC006455.5 chr7 63348861 63351774 +1049835 AC006455.4 chr7 63354457 63359306 +1049840 AC073188.3 chr7 63380466 63385789 +1049844 AC073188.4 chr7 63388808 63393657 +1049849 AC073188.2 chr7 63393745 63422053 +1049855 AC073188.5 chr7 63394277 63395439 +1049859 AC073188.6 chr7 63396341 63399250 +1049865 AC092634.4 chr7 63888200 63900794 +1049905 LINC02848 chr7 63900313 63925202 +1049954 AC092634.8 chr7 63925832 63930920 +1049958 AC115220.1 chr7 63998874 64016130 +1049972 LINC01005 chr7 64024409 64030105 +1049989 AC115220.3 chr7 64035644 64037958 +1049993 ZNF727 chr7 64045434 64085339 +1050007 AC091685.1 chr7 64140495 64150058 +1050012 ZNF735 chr7 64207090 64220508 +1050026 ZNF679 chr7 64228474 64266931 +1050054 AC073270.1 chr7 64294516 64300818 +1050059 ZNF736 chr7 64307459 64356634 +1050118 AC073270.2 chr7 64369241 64375584 +1050122 ZNF680 chr7 64519878 64563075 +1050160 AC016769.5 chr7 64612535 64614834 +1050165 AC016769.6 chr7 64651655 64655836 +1050169 ZNF107 chr7 64666083 64711582 +1050254 ZNF138 chr7 64794388 64833681 +1050336 AC073349.4 chr7 64801958 64804117 +1050340 AC073349.5 chr7 64867427 64870076 +1050344 ZNF273 chr7 64870172 64930966 +1050399 AC073349.1 chr7 64888527 64890100 +1050404 AC073210.3 chr7 64947571 64950701 +1050415 ZNF117 chr7 64971772 65006684 +1050457 ERV3-1 chr7 64990356 65006743 +1050473 AC104073.4 chr7 65269374 65306238 +1050478 ZNF92 chr7 65373799 65401135 +1050526 AC114501.3 chr7 65463071 65463438 +1050530 AC093582.1 chr7 65840055 65842396 +1050533 VKORC1L1 chr7 65873074 65959563 +1050576 GUSB chr7 65960684 65982215 +1050738 ASL chr7 66075800 66094697 +1051122 CRCP chr7 66114604 66154568 +1051208 AC068533.3 chr7 66119603 66165011 +1051214 TPST1 chr7 66205317 66420543 +1051277 LINC00174 chr7 66376044 66493566 +1051412 AC008267.5 chr7 66493607 66495758 +1051431 KCTD7 chr7 66628767 66649067 +1051570 AC006001.2 chr7 66654538 66671523 +1051599 RABGEF1 chr7 66682164 66811464 +1051797 AC027644.3 chr7 66739829 66740385 +1051800 LINC02604 chr7 66902857 66906297 +1051803 TMEM248 chr7 66921225 66958551 +1051882 SBDS chr7 66987680 66995587 +1051939 TYW1 chr7 66995173 67239519 +1052077 SPDYE21P chr7 67278714 67286664 +1052114 AC006480.2 chr7 67333047 67334383 +1052117 AC005482.1 chr7 67691058 67697029 +1052121 AC092637.1 chr7 68020235 68036917 +1052138 AC006013.1 chr7 68091223 68119209 +1052142 AC093655.1 chr7 68149548 68319676 +1052161 AC104688.1 chr7 69026433 69046803 +1052167 AC069280.2 chr7 69145185 69174450 +1052175 AC092100.1 chr7 69186821 69430923 +1052195 AC069280.1 chr7 69187833 69189318 +1052200 CT66 chr7 69594793 69597493 +1052207 AUTS2 chr7 69598296 70793506 +1052699 GALNT17 chr7 71132144 71713600 +1052783 CALN1 chr7 71779491 72447151 +1052874 TYW1B chr7 72558744 72828200 +1052956 POM121 chr7 72879365 72951440 +1053121 AC211476.2 chr7 72924418 72925125 +1053124 AC211476.6 chr7 72954797 72957106 +1053128 TRIM74 chr7 72959485 72969466 +1053159 SPDYE8P chr7 73020338 73029766 +1053181 SPDYE17 chr7 73048481 73057911 +1053203 SPDYE9P chr7 73076165 73086038 +1053231 NSUN5 chr7 73302516 73308826 +1053352 TRIM50 chr7 73312536 73328082 +1053398 FKBP6 chr7 73328161 73358637 +1053551 FZD9 chr7 73433778 73436120 +1053559 BAZ1B chr7 73440406 73522293 +1053652 BCL7B chr7 73536356 73557690 +1053780 TBL2 chr7 73567537 73578791 +1054049 MLXIPL chr7 73593194 73624543 +1054313 AC005089.1 chr7 73609262 73611502 +1054316 VPS37D chr7 73667831 73672112 +1054339 DNAJC30 chr7 73680918 73683453 +1054347 BUD23 chr7 73683025 73705161 +1054641 STX1A chr7 73699206 73719672 +1054791 ABHD11 chr7 73736094 73738867 +1054934 CLDN3 chr7 73768997 73770270 +1054942 CLDN4 chr7 73799542 73832693 +1054976 METTL27 chr7 73834590 73842516 +1055014 TMEM270 chr7 73861159 73865890 +1055039 AC099398.1 chr7 73985992 73988767 +1055042 ELN chr7 74027789 74069907 +1056298 ELN-AS1 chr7 74059576 74062284 +1056302 LIMK1 chr7 74082933 74122525 +1056470 EIF4H chr7 74174245 74197101 +1056523 LAT2 chr7 74199652 74229834 +1056762 RFC2 chr7 74231499 74254458 +1057019 AC005081.1 chr7 74280747 74289286 +1057023 CLIP2 chr7 74289475 74405943 +1057169 GTF2IRD1 chr7 74453790 74602604 +1057449 AC211433.2 chr7 74606913 74607299 +1057452 GTF2I chr7 74650231 74760692 +1057948 AC211433.1 chr7 74688864 74729001 +1057978 NCF1 chr7 74773962 74789376 +1058088 GTF2IRD2 chr7 74796144 74851551 +1058238 CASTOR2 chr7 74964705 75031528 +1058269 RCC1L chr7 75027122 75074228 +1058379 GTF2IRD2B chr7 75092573 75149817 +1058606 AC211486.5 chr7 75225433 75234310 +1058611 AC211486.2 chr7 75232928 75233924 +1058615 AC211486.7 chr7 75281243 75287121 +1058632 AC211486.8 chr7 75309171 75315049 +1058649 AC211486.6 chr7 75337138 75343016 +1058666 TRIM73 chr7 75395063 75410996 +1058750 POM121C chr7 75416786 75486299 +1058862 SPDYE5 chr7 75493625 75504304 +1058923 HIP1 chr7 75533298 75738962 +1059149 CCL26 chr7 75769533 75789896 +1059174 CCL24 chr7 75811665 75823356 +1059199 RHBDD2 chr7 75842602 75888926 +1059272 POR chr7 75899200 75986855 +1059624 TMEM120A chr7 75986831 75994656 +1059831 STYXL1 chr7 75996338 76048004 +1060015 MDH2 chr7 76048051 76067508 +1060106 SRRM3 chr7 76201896 76287288 +1060161 HSPB1 chr7 76302673 76304295 +1060193 YWHAG chr7 76326799 76358991 +1060203 SSC4D chr7 76389334 76409697 +1060235 ZP3 chr7 76397518 76442071 +1060325 DTX2 chr7 76461676 76505995 +1060584 AC005522.1 chr7 76474587 76478856 +1060588 UPK3B chr7 76510428 76516521 +1060641 SPDYE16 chr7 76531319 76541459 +1060697 POMZP3 chr7 76609986 76627261 +1060775 AC006972.1 chr7 76818377 76903041 +1060785 AC007003.1 chr7 76902480 76919191 +1060799 AC114737.1 chr7 76972679 76976961 +1060803 CCDC146 chr7 77122434 77329533 +1060899 FGL2 chr7 77193369 77199848 +1060916 AC098851.1 chr7 77246340 77258123 +1060922 GSAP chr7 77310751 77416349 +1061122 AC004921.1 chr7 77416673 77425444 +1061129 AC004921.2 chr7 77487317 77498965 +1061133 PTPN12 chr7 77537295 77640069 +1061382 APTR chr7 77657659 77696267 +1061427 RSBN1L chr7 77696459 77783022 +1061503 TMEM60 chr7 77793728 77798434 +1061513 PHTF2 chr7 77798792 77957503 +1061825 AC004990.1 chr7 77990384 77995171 +1061836 MAGI2 chr7 78017055 79453667 +1062582 AC006043.1 chr7 78392626 78448999 +1062586 MAGI2-AS1 chr7 78939850 78940895 +1062590 MAGI2-AS2 chr7 79008988 79012277 +1062595 AC006355.2 chr7 79139829 79177210 +1062600 AC074024.1 chr7 79335780 79357594 +1062605 MAGI2-AS3 chr7 79452877 79471208 +1062823 AC073048.1 chr7 79657947 79675015 +1062828 GNAI1 chr7 79768028 80226181 +1063415 AC003988.1 chr7 80246409 80312456 +1063422 AC004862.1 chr7 80312574 80391474 +1063529 CD36 chr7 80369575 80679277 +1063971 GNAT3 chr7 80458635 80512064 +1063993 SEMA3C chr7 80742538 80922359 +1064145 AC005008.2 chr7 81175508 81199115 +1064156 HGF chr7 81699010 81770438 +1064365 CACNA2D1 chr7 81946444 82443777 +1064630 AC006145.1 chr7 82009177 82029955 +1064642 PCLO chr7 82754012 83162930 +1064827 AC079799.1 chr7 83355154 83362266 +1064831 SEMA3E chr7 83363238 83649139 +1064989 SEMA3A chr7 83955777 84492724 +1065116 AC003984.1 chr7 84532476 84584322 +1065125 AC074183.1 chr7 84939349 84940245 +1065129 SEMA3D chr7 84995553 85186855 +1065208 LINC00972 chr7 85421122 85489293 +1065217 GRM3 chr7 86643914 86864884 +1065271 AC005009.1 chr7 86775081 86776022 +1065275 AC005009.2 chr7 86782357 86803409 +1065285 KIAA1324L chr7 86876906 87059654 +1065570 AC004023.1 chr7 87109539 87111282 +1065573 AC005076.1 chr7 87151422 87152420 +1065583 DMTF1 chr7 87152361 87196337 +1066285 TMEM243 chr7 87196160 87220587 +1066347 TP53TG1 chr7 87322943 87345528 +1066388 CROT chr7 87345681 87399795 +1066537 ABCB4 chr7 87401697 87480435 +1066954 ABCB1 chr7 87503633 87713323 +1067194 RUNDC3B chr7 87627548 87832296 +1067314 SLC25A40 chr7 87833568 87876360 +1067416 DBF4 chr7 87876216 87909553 +1067551 ADAM22 chr7 87934143 88202889 +1067972 SRI chr7 88205118 88226993 +1068117 AC003991.2 chr7 88216660 88219226 +1068121 AC003991.1 chr7 88219359 88304367 +1068186 STEAP4 chr7 88270892 88306891 +1068228 AC002069.2 chr7 88420167 88756725 +1068242 ZNF804B chr7 88759700 89338528 +1068265 TEX47 chr7 88794106 88795737 +1068275 AC002383.1 chr7 89443946 89496918 +1068351 STEAP2-AS1 chr7 89882353 90211635 +1068359 AC004969.1 chr7 90119299 90122890 +1068363 STEAP1 chr7 90154456 90164829 +1068395 STEAP2 chr7 90167590 90238137 +1068535 CFAP69 chr7 90245174 90311063 +1068839 AC002064.2 chr7 90266034 90270216 +1068844 AC002064.1 chr7 90312496 90322592 +1068849 FAM237B chr7 90316503 90321308 +1068859 GTPBP10 chr7 90335223 90391455 +1069051 CLDN12 chr7 90383721 90513402 +1069164 CDK14 chr7 90466424 91210590 +1069414 AC002456.1 chr7 90590619 90597353 +1069430 AC002458.1 chr7 91030149 91033725 +1069434 FZD1 chr7 91264433 91271326 +1069442 AC079760.2 chr7 91311368 91515427 +1069492 AC079760.1 chr7 91380778 91556848 +1069496 AC000058.1 chr7 91638847 91643512 +1069500 MTERF1 chr7 91692008 91880702 +1069570 AC003086.1 chr7 91880791 91886490 +1069574 AKAP9 chr7 91940867 92110673 +1070066 CYP51A1 chr7 92112153 92134803 +1070135 CYP51A1-AS1 chr7 92134604 92180725 +1070147 LRRD1 chr7 92141643 92179531 +1070200 KRIT1 chr7 92198969 92246166 +1070625 AC000120.1 chr7 92200014 92206857 +1070629 ANKIB1 chr7 92245974 92401383 +1070739 GATAD1 chr7 92447482 92460075 +1070782 AC007566.1 chr7 92457564 92495601 +1070798 ERVW-1 chr7 92468380 92477986 +1070824 PEX1 chr7 92487020 92528520 +1071043 RBM48 chr7 92528773 92540481 +1071081 FAM133B chr7 92560758 92590393 +1071238 CDK6 chr7 92604921 92836594 +1071290 AC000065.2 chr7 92638198 92642316 +1071294 AC000065.1 chr7 92647906 92667083 +1071302 AC002454.1 chr7 92836483 92917187 +1071317 SAMD9 chr7 93099513 93118023 +1071345 SAMD9L chr7 93130056 93148385 +1071450 HEPACAM2 chr7 93188534 93226469 +1071554 VPS50 chr7 93232340 93361123 +1072005 CALCR chr7 93424487 93574730 +1072235 GNGT1 chr7 93591573 93911265 +1072289 TFPI2 chr7 93885396 93890753 +1072356 AC002076.1 chr7 93890913 93893601 +1072360 GNG11 chr7 93921735 93928610 +1072370 BET1 chr7 93962762 94004382 +1072462 AC006378.1 chr7 93969442 94011113 +1072473 AC003092.1 chr7 94022833 94066661 +1072485 AC003092.2 chr7 94071759 94077157 +1072490 AC002074.1 chr7 94278680 94395608 +1072504 AC002074.2 chr7 94311138 94347063 +1072510 COL1A2 chr7 94394561 94431232 +1072801 CASD1 chr7 94509219 94557019 +1072897 SGCE chr7 94524204 94656572 +1074865 PEG10 chr7 94656325 94669695 +1074942 PPP1R9A chr7 94907202 95296415 +1075197 AC002429.2 chr7 95035731 95214338 +1075219 PON1 chr7 95297676 95324532 +1075274 PON3 chr7 95359872 95396375 +1075426 PON2 chr7 95404862 95435329 +1075682 AC005021.1 chr7 95416108 95416462 +1075685 AC004012.1 chr7 95471835 95473998 +1075689 ASB4 chr7 95478444 95540233 +1075719 AC002451.1 chr7 95545191 95615132 +1075774 PDK4 chr7 95583499 95596516 +1075819 DYNC1I1 chr7 95772506 96110322 +1076141 SLC25A13 chr7 96120220 96322147 +1076263 SEM1 chr7 96481626 96709891 +1076500 DLX6-AS1 chr7 96955141 97014088 +1076541 DLX6 chr7 97005553 97011040 +1076566 DLX5 chr7 97020396 97024950 +1076591 SDHAF3 chr7 97116590 97181763 +1076618 TAC1 chr7 97732084 97740472 +1076680 ASNS chr7 97851677 97872542 +1076993 AC079781.5 chr7 97851688 97972985 +1077048 OCM2 chr7 97984684 97991169 +1077067 LMTK2 chr7 98106862 98209638 +1077106 BHLHA15 chr7 98211427 98212979 +1077123 TECPR1 chr7 98214624 98252232 +1077294 BRI3 chr7 98252379 98310441 +1077341 BAIAP2L1 chr7 98291650 98401090 +1077398 AC093799.1 chr7 98322853 98323430 +1077401 NPTX2 chr7 98617285 98629869 +1077421 TMEM130 chr7 98846488 98870771 +1077523 TRRAP chr7 98877933 99050831 +1078329 AC004893.3 chr7 98989867 98993778 +1078333 SMURF1 chr7 99027438 99144100 +1078434 KPNA7 chr7 99173574 99207506 +1078460 AC004834.1 chr7 99252452 99325826 +1078487 ARPC1A chr7 99325898 99366262 +1078551 ARPC1B chr7 99374249 99394816 +1078902 PDAP1 chr7 99392048 99408597 +1078954 BUD31 chr7 99408641 99419616 +1079037 PTCD1 chr7 99416739 99466163 +1079088 CPSF4 chr7 99438922 99457373 +1079250 ATP5MF chr7 99448475 99466331 +1079348 ZNF789 chr7 99472890 99503650 +1079464 ZNF394 chr7 99473877 99504857 +1079523 ZKSCAN5 chr7 99504651 99534700 +1079596 FAM200A chr7 99546300 99558536 +1079613 ZNF655 chr7 99558406 99576453 +1079882 TMEM225B chr7 99598267 99611045 +1079922 ZSCAN25 chr7 99616946 99632408 +1080029 CYP3A5 chr7 99648194 99679998 +1080248 CYP3A7 chr7 99684957 99735196 +1080328 CYP3A4 chr7 99756960 99784248 +1080487 AC069294.1 chr7 99766543 99766892 +1080490 CYP3A43 chr7 99828013 99866102 +1080801 OR2AE1 chr7 99875987 99877057 +1080809 TRIM4 chr7 99876958 99919600 +1080881 GJC3 chr7 99923266 99929620 +1080890 AC004522.3 chr7 99929392 99948620 +1080895 AZGP1 chr7 99966720 99976042 +1080938 AC004522.4 chr7 99974976 99979233 +1080942 AC004522.5 chr7 99997690 100011634 +1080948 ZKSCAN1 chr7 100015572 100041689 +1081028 ZSCAN21 chr7 100049774 100065040 +1081087 ZNF3 chr7 100064033 100082548 +1081250 COPS6 chr7 100088969 100092187 +1081358 MCM7 chr7 100092728 100101940 +1081564 AP4M1 chr7 100101549 100110345 +1081926 TAF6 chr7 100107070 100119841 +1082283 AC073842.2 chr7 100115214 100127139 +1082287 CNPY4 chr7 100119634 100125508 +1082338 MBLAC1 chr7 100126785 100128495 +1082355 AC073842.1 chr7 100130964 100140439 +1082359 LAMTOR4 chr7 100148907 100155944 +1082475 MAP11 chr7 100154420 100158723 +1082637 GAL3ST4 chr7 100159244 100168617 +1082713 GPC2 chr7 100169606 100177381 +1082771 STAG3 chr7 100177563 100221488 +1083313 CASTOR3 chr7 100200653 100272232 +1083397 PVRIG chr7 100218241 100221490 +1083418 SPDYE3 chr7 100307702 100322196 +1083452 PILRB chr7 100352176 100367733 +1083671 PILRA chr7 100367530 100400096 +1083759 AC005071.1 chr7 100388809 100398366 +1083764 ZCWPW1 chr7 100400826 100428992 +1083927 MEPCE chr7 100428790 100434118 +1083962 AC092849.2 chr7 100435257 100436510 +1083966 PPP1R35 chr7 100435282 100436497 +1083994 AC092849.1 chr7 100436204 100438504 +1083998 C7orf61 chr7 100456620 100464260 +1084015 TSC22D4 chr7 100463359 100479232 +1084072 AC092849.3 chr7 100482221 100483833 +1084076 NYAP1 chr7 100483927 100494802 +1084117 AC069281.1 chr7 100509416 100520205 +1084133 AGFG2 chr7 100539203 100568220 +1084216 SAP25 chr7 100572228 100573900 +1084269 LRCH4 chr7 100574011 100586129 +1084417 FBXO24 chr7 100583982 100601117 +1084563 PCOLCE-AS1 chr7 100589402 100604206 +1084580 PCOLCE chr7 100602363 100608175 +1084638 MOSPD3 chr7 100612102 100615384 +1084739 TFR2 chr7 100620416 100642779 +1084968 ACTL6B chr7 100643097 100656448 +1085039 GNB2 chr7 100673567 100679174 +1085270 GIGYF1 chr7 100679507 100694037 +1085403 POP7 chr7 100706121 100707486 +1085420 EPO chr7 100720468 100723700 +1085436 ZAN chr7 100733595 100797797 +1086176 EPHB4 chr7 100802565 100827523 +1086337 SLC12A9 chr7 100826820 100867010 +1086543 SLC12A9-AS1 chr7 100837314 100852616 +1086547 TRIP6 chr7 100867387 100873454 +1086656 SRRT chr7 100875103 100888664 +1086959 UFSP1 chr7 100888721 100889715 +1086973 ACHE chr7 100889994 100896974 +1087137 MUC3A chr7 100949534 100968347 +1087221 AC254629.1 chr7 100963828 100968124 +1087232 MUC12 chr7 100969623 101018949 +1087317 AC105446.1 chr7 101014320 101017608 +1087326 MUC17 chr7 101020072 101058859 +1087393 TRIM56 chr7 101085481 101097967 +1087426 SERPINE1 chr7 101127089 101139266 +1087450 AP1S1 chr7 101154456 101161596 +1087526 VGF chr7 101162509 101165569 +1087558 NAT16 chr7 101170496 101180293 +1087605 MOGAT3 chr7 101195007 101201038 +1087663 PLOD3 chr7 101205977 101218420 +1087834 ZNHIT1 chr7 101218165 101224190 +1087868 CLDN15 chr7 101232092 101238820 +1087963 FIS1 chr7 101239458 101252316 +1088059 LNCPRESS1 chr7 101299578 101301346 +1088063 AC006329.1 chr7 101308270 101314800 +1088071 IFT22 chr7 101310914 101321823 +1088189 COL26A1 chr7 101362875 101559024 +1088256 LINC01007 chr7 101562779 101569006 +1088267 MYL10 chr7 101613330 101629296 +1088308 CUX1 chr7 101815904 102283958 +1089110 AC005096.1 chr7 101822247 101824729 +1089114 AC005072.1 chr7 101960116 101961894 +1089117 AC005086.2 chr7 102153355 102154463 +1089121 SH2B2 chr7 102285091 102321711 +1089167 SPDYE6 chr7 102345746 102356444 +1089189 PRKRIP1 chr7 102363872 102426676 +1089287 AC073517.1 chr7 102426818 102434780 +1089292 ORAI2 chr7 102433106 102456825 +1089395 ALKBH4 chr7 102456238 102464863 +1089421 LRWD1 chr7 102464956 102473168 +1089553 POLR2J chr7 102473118 102478907 +1089578 RASA4B chr7 102482445 102517781 +1089747 UPK3BL2 chr7 102538417 102543849 +1089765 SPDYE2 chr7 102551232 102562308 +1089824 POLR2J3 chr7 102562133 102572583 +1089903 RASA4 chr7 102573807 102616757 +1090222 AC105052.4 chr7 102579104 102679295 +1090229 UPK3BL1 chr7 102637025 102642791 +1090247 SPDYE2B chr7 102650325 102661398 +1090306 POLR2J2 chr7 102665368 102671629 +1090330 AC105052.5 chr7 102699228 102748695 +1090335 FAM185A chr7 102748971 102809225 +1090447 FBXL13 chr7 102813230 103074843 +1090784 LRRC17 chr7 102913000 102945111 +1090828 NFE4 chr7 102973522 102988856 +1090841 AC073127.1 chr7 103030104 103031354 +1090845 ARMC10 chr7 103074881 103099759 +1091009 NAPEPLD chr7 103099776 103149560 +1091128 PMPCB chr7 103297435 103329511 +1091309 DNAJC2 chr7 103312289 103344830 +1091496 PSMC2 chr7 103344254 103369395 +1091592 SLC26A5 chr7 103352730 103446207 +1092161 AC005064.1 chr7 103445207 103514007 +1092171 RELN chr7 103471784 103989658 +1092596 ORC5 chr7 104126341 104208047 +1092730 LHFPL3 chr7 104328700 104907232 +1092755 LHFPL3-AS1 chr7 104738597 104804107 +1092797 LHFPL3-AS2 chr7 104894628 104926645 +1092809 AC007384.1 chr7 104940943 105000713 +1092828 LINC01004 chr7 104950315 105013044 +1092839 KMT2E-AS1 chr7 105013425 105014321 +1092843 KMT2E chr7 105014190 105115019 +1093250 AC005070.3 chr7 105102838 105105483 +1093253 SRPK2 chr7 105110704 105399308 +1093495 AC004884.2 chr7 105304277 105306642 +1093499 PUS7 chr7 105439661 105522271 +1093630 RINT1 chr7 105532169 105567677 +1093757 EFCAB10 chr7 105565120 105600875 +1093841 AC073073.2 chr7 105571083 105573660 +1093844 ATXN7L1 chr7 105605067 105876604 +1093997 CDHR3 chr7 105876796 106036432 +1094186 SYPL1 chr7 106090503 106112576 +1094268 NAMPT chr7 106248298 106286326 +1094381 AC007032.1 chr7 106285480 106286326 +1094384 AC004917.1 chr7 106372251 106770207 +1094408 AC005050.3 chr7 106425278 106511544 +1094412 AC005050.1 chr7 106569876 106598908 +1094426 AC005050.2 chr7 106624072 106628696 +1094433 CCDC71L chr7 106654360 106661158 +1094452 LINC02577 chr7 106774955 106838480 +1094491 PIK3CG chr7 106865278 106908980 +1094593 PRKAR2B chr7 107044705 107161811 +1094633 AC006387.1 chr7 107066591 107133733 +1094657 HBP1 chr7 107168961 107202522 +1094843 AC004492.1 chr7 107192559 107193300 +1094846 COG5 chr7 107201555 107564514 +1095041 GPR22 chr7 107470018 107475684 +1095060 DUS4L chr7 107563484 107578523 +1095195 AC004839.2 chr7 107579557 107580057 +1095198 BCAP29 chr7 107579977 107629170 +1095446 SLC26A4-AS1 chr7 107650260 107662204 +1095495 SLC26A4 chr7 107660828 107717809 +1095610 AC002467.1 chr7 107739999 107744581 +1095632 CBLL1 chr7 107743949 107761667 +1095730 SLC26A3 chr7 107765467 107803225 +1095843 DLD chr7 107891162 107931730 +1096092 LAMB1 chr7 107923799 108003187 +1096332 AC005046.1 chr7 107942116 107942740 +1096335 LAMB4 chr7 108023548 108130361 +1096591 NRCAM chr7 108147623 108456717 +1097147 PNPLA8 chr7 108470417 108569666 +1097339 THAP5 chr7 108554543 108569750 +1097391 DNAJB9 chr7 108569867 108574850 +1097409 AC005487.1 chr7 108598352 108639349 +1097434 C7orf66 chr7 108883975 108884587 +1097438 AC004014.1 chr7 108909453 108952666 +1097444 AC002386.1 chr7 109322320 109326315 +1097448 AC073071.1 chr7 109521981 109597166 +1097454 AC073114.1 chr7 110108031 110534757 +1097486 AC073326.2 chr7 110590082 110592204 +1097490 IMMP2L chr7 110663051 111562517 +1097610 AC073326.1 chr7 110724159 110725825 +1097614 LRRN3 chr7 111091006 111125454 +1097662 DOCK4 chr7 111726110 112206411 +1098398 AC003077.1 chr7 111757051 111762216 +1098407 DOCK4-AS1 chr7 111808516 111821773 +1098411 ZNF277 chr7 112206695 112343934 +1098543 AC004112.1 chr7 112328189 112409623 +1098553 IFRD1 chr7 112422968 112481017 +1098784 LSMEM1 chr7 112480853 112491062 +1098835 AC002463.1 chr7 112616440 112896625 +1099170 TMEM168 chr7 112762377 112790423 +1099255 BMT2 chr7 112819147 112939875 +1099292 AC018464.1 chr7 112953282 112995677 +1099522 GPR85 chr7 113078331 113087778 +1099585 AC073346.1 chr7 113100663 113146330 +1099594 SMIM30 chr7 113116718 113118560 +1099623 AC073348.2 chr7 113486407 113494870 +1099627 PPP1R3A chr7 113876777 114075920 +1099666 FOXP2 chr7 114086327 114693772 +1100412 AC073626.1 chr7 114414244 114419875 +1100416 AC003992.1 chr7 114560961 114561517 +1100419 MDFIC chr7 114922154 115019202 +1100518 LINC01393 chr7 115030564 115126314 +1100559 LINC01392 chr7 115061537 115231355 +1100567 AC092590.1 chr7 115647461 115676329 +1100571 AC093714.1 chr7 115679345 115682618 +1100575 AC093714.2 chr7 115789729 115791049 +1100580 TFEC chr7 115935148 116159896 +1100696 TES chr7 116210506 116258783 +1100788 AC073130.2 chr7 116237929 116327896 +1100798 AC002066.1 chr7 116238260 116499465 +1100814 AC073130.1 chr7 116275606 116286734 +1100831 CAV2 chr7 116287380 116508541 +1100962 CAV1 chr7 116525001 116561184 +1101050 AC006159.1 chr7 116542718 116551969 +1101054 AC006159.2 chr7 116563594 116571234 +1101058 LINC01510 chr7 116563594 116663829 +1101077 MET chr7 116672196 116798386 +1101228 CAPZA2 chr7 116811070 116922049 +1101400 ST7-AS1 chr7 116952446 116954334 +1101403 ST7 chr7 116953238 117230103 +1102018 ST7-OT4 chr7 116953899 117098806 +1102045 AC106873.1 chr7 116965846 116967472 +1102049 ST7-AS2 chr7 117072072 117146480 +1102087 AC002542.6 chr7 117091678 117097262 +1102091 WNT2 chr7 117275451 117323152 +1102151 AC002465.1 chr7 117300861 117322236 +1102155 AC002465.2 chr7 117332761 117350096 +1102159 ASZ1 chr7 117363222 117428123 +1102266 CFTR chr7 117465784 117715971 +1102655 CFTR-AS1 chr7 117560733 117564676 +1102659 AC000061.1 chr7 117604791 117647415 +1102664 CTTNBP2 chr7 117710651 117874139 +1102890 AC003084.1 chr7 117998858 118004045 +1102895 LSM8 chr7 118184144 118204035 +1102940 ANKRD7 chr7 118214669 118496171 +1103040 AC002529.1 chr7 118511942 118513830 +1103044 LINC02476 chr7 119495024 119907397 +1103061 AC004946.1 chr7 120141016 120227213 +1103066 AC004946.2 chr7 120166443 120186064 +1103072 KCND2 chr7 120273175 120750337 +1103105 AC004888.1 chr7 120746738 120752514 +1103110 TSPAN12 chr7 120787320 120858402 +1103224 ING3 chr7 120950763 120977216 +1103341 CPED1 chr7 120988697 121297442 +1103563 AC006364.1 chr7 121304657 121309842 +1103567 WNT16 chr7 121325367 121341104 +1103594 FAM3C chr7 121348878 121396364 +1103666 AC004875.1 chr7 121643334 121686363 +1103672 PTPRZ1 chr7 121873089 122062036 +1104571 AASS chr7 122073549 122144255 +1104814 AC015983.2 chr7 122144405 122219277 +1104857 FEZF1 chr7 122301303 122310691 +1104893 FEZF1-AS1 chr7 122303658 122310119 +1104913 CADPS2 chr7 122318411 122886759 +1105317 AC004594.1 chr7 122328469 122440388 +1105417 RNF133 chr7 122697735 122699117 +1105425 RNF148 chr7 122701668 122702922 +1105444 TAS2R16 chr7 122994704 122995700 +1105452 AC073311.1 chr7 123069249 123103589 +1105458 SLC13A1 chr7 123113531 123199972 +1105609 IQUB chr7 123452193 123535077 +1105744 AC073323.1 chr7 123456629 123459856 +1105749 NDUFA5 chr7 123536997 123557904 +1105865 ASB15 chr7 123567010 123639481 +1106037 AC006333.1 chr7 123584859 123624957 +1106061 LMOD2 chr7 123655866 123664290 +1106082 WASL chr7 123681943 123749003 +1106110 AC006333.2 chr7 123749068 123751166 +1106113 HYAL4 chr7 123828983 123877481 +1106181 SPAM1 chr7 123925237 123971414 +1106274 AC004690.2 chr7 123994622 124027659 +1106284 TMEM229A chr7 124030921 124033067 +1106292 AC006148.1 chr7 124032126 124489572 +1106371 AC006148.2 chr7 124274671 124288852 +1106376 AC004930.1 chr7 124337380 124349860 +1106381 SSU72P8 chr7 124476371 124476955 +1106388 GPR37 chr7 124743885 124765792 +1106398 C7orf77 chr7 124777292 124790810 +1106417 POT1 chr7 124822386 124929983 +1107321 POT1-AS1 chr7 124929873 125482966 +1107525 LINC02830 chr7 125151326 125153611 +1107529 AC019155.2 chr7 125229579 125264291 +1107536 AC003975.1 chr7 125917871 125933832 +1107543 AC000372.1 chr7 126378970 126424185 +1107552 GRM8 chr7 126438598 127253294 +1107742 AC002057.2 chr7 126495312 126531336 +1107747 AC002057.1 chr7 126533665 126537295 +1107752 AC000099.1 chr7 127215127 127229927 +1107763 ZNF800 chr7 127346790 127431924 +1107874 AC000123.1 chr7 127350128 127351523 +1107878 AC000124.1 chr7 127476883 127485804 +1107884 GCC1 chr7 127580628 127593611 +1107903 ARF5 chr7 127588386 127591700 +1107953 FSCN3 chr7 127591409 127602144 +1108001 PAX4 chr7 127610292 127618142 +1108148 AC073934.1 chr7 127644685 127652012 +1108153 SND1 chr7 127652194 128092609 +1108295 SND1-IT1 chr7 127997597 128000077 +1108298 LRRC4 chr7 128027071 128032107 +1108333 LEP chr7 128241278 128257629 +1108345 AC018635.2 chr7 128264526 128264889 +1108348 RBM28 chr7 128297685 128343908 +1108487 PRRT4 chr7 128350325 128361685 +1108577 IMPDH1 chr7 128392277 128410252 +1109027 HILPDA chr7 128455849 128458418 +1109052 METTL2B chr7 128476729 128506602 +1109155 AC090114.2 chr7 128524016 128531069 +1109158 AC018638.7 chr7 128667043 128668156 +1109161 FAM71F2 chr7 128672288 128687872 +1109246 AC018638.6 chr7 128690451 128691717 +1109249 FAM71F1 chr7 128709061 128731743 +1109373 CALU chr7 128739292 128773400 +1109484 OPN1SW chr7 128772491 128775790 +1109499 CCDC136 chr7 128790757 128822132 +1109738 FLNC chr7 128830377 128859274 +1109944 FLNC-AS1 chr7 128850162 128862626 +1109950 KCP chr7 128862451 128910719 +1110325 ATP6V1F chr7 128862856 128865847 +1110346 ATP6V1FNB chr7 128866330 128872047 +1110356 IRF5 chr7 128937457 128950038 +1110635 TNPO3 chr7 128954180 129055173 +1110889 AC011005.1 chr7 129126518 129130793 +1110898 TSPAN33 chr7 129144707 129169699 +1110931 SMO chr7 129188633 129213545 +1111020 AC011005.4 chr7 129209775 129213545 +1111024 AHCYL2 chr7 129225023 129430211 +1111268 AC009244.2 chr7 129366827 129374486 +1111274 STRIP2 chr7 129434432 129488399 +1111372 SMKR1 chr7 129502531 129512918 +1111385 AC078846.1 chr7 129604548 129611630 +1111388 NRF1 chr7 129611720 129757082 +1111549 AC084864.2 chr7 129763060 129769202 +1111554 AC084864.1 chr7 129783370 129785185 +1111559 UBE2H chr7 129830732 129952960 +1111692 AC073320.1 chr7 129953234 130026989 +1111702 ZC3HC1 chr7 130018286 130051451 +1111922 KLHDC10 chr7 130070534 130135705 +1111977 AC087071.1 chr7 130141707 130142618 +1111987 TMEM209 chr7 130164713 130207770 +1112119 AC087071.2 chr7 130173718 130205361 +1112126 SSMEM1 chr7 130206344 130216844 +1112148 CPA2 chr7 130266863 130289798 +1112211 CPA4 chr7 130293134 130324180 +1112359 CPA5 chr7 130344816 130368730 +1112581 CPA1 chr7 130380339 130388114 +1112694 CEP41 chr7 130393771 130442433 +1112948 AC007938.1 chr7 130481491 130484392 +1112951 MESTIT1 chr7 130486042 130491033 +1112958 MEST chr7 130486171 130506465 +1113301 AC007938.2 chr7 130495794 130498427 +1113304 COPG2 chr7 130506238 130668748 +1113419 AC007938.3 chr7 130507660 130508282 +1113422 AUXG01000058.1 chr7 130538954 130546900 +1113425 TSGA13 chr7 130668648 130687432 +1113498 AC234644.2 chr7 130668852 130669395 +1113501 KLF14 chr7 130731235 130734176 +1113509 AC016831.6 chr7 130790208 130791724 +1113512 AC016831.7 chr7 130791264 131110161 +1113572 LINC00513 chr7 130853720 130930682 +1113596 AC016831.1 chr7 130876809 130913310 +1113611 AC016831.5 chr7 130930209 130932206 +1113614 AC058791.1 chr7 130936464 130939661 +1113617 LINC-PINT chr7 130938963 131110176 +1113750 MKLN1 chr7 131110096 131496632 +1113964 MKLN1-AS chr7 131309469 131328312 +1114056 AC008264.2 chr7 131493964 131497694 +1114059 PODXL chr7 131500262 131558217 +1114142 AC009518.1 chr7 131897289 131948953 +1114157 PLXNA4 chr7 132123332 132648688 +1114327 AC018643.1 chr7 132264152 132271269 +1114332 AC011625.1 chr7 132352334 132367976 +1114337 AC009365.1 chr7 132648794 132728769 +1114349 AC009365.3 chr7 132758970 132760632 +1114357 CHCHD3 chr7 132784870 133082090 +1114452 AC009365.4 chr7 132830693 132849593 +1114458 EXOC4 chr7 133253073 134066589 +1114631 LRGUK chr7 134127299 134264591 +1114719 AC008154.2 chr7 134284500 134286055 +1114723 SLC35B4 chr7 134289332 134316930 +1114796 AC008154.1 chr7 134346071 134350791 +1114800 AC009275.1 chr7 134368737 134432534 +1114887 AKR1B1 chr7 134442356 134459284 +1115012 AKR1B10 chr7 134527567 134541412 +1115056 AKR1B15 chr7 134549110 134579875 +1115139 BPGM chr7 134646811 134679816 +1115184 AC009276.1 chr7 134684144 134687990 +1115189 CALD1 chr7 134744252 134970729 +1115593 AC083870.1 chr7 134816543 134998153 +1115597 AGBL3 chr7 134986508 135147963 +1115739 CYREN chr7 135092363 135170795 +1115847 TMEM140 chr7 135148072 135166215 +1115860 AC083862.2 chr7 135168403 135169547 +1115863 AC083862.3 chr7 135170816 135172414 +1115867 WDR91 chr7 135183839 135211534 +1115980 AC009542.1 chr7 135198401 135209837 +1115998 STRA8 chr7 135231979 135258492 +1116067 CNOT4 chr7 135361795 135510127 +1116301 NUP205 chr7 135557917 135648757 +1116511 STMP1 chr7 135662496 135693418 +1116543 SLC13A4 chr7 135681237 135729258 +1116627 AC091736.1 chr7 135704537 135704841 +1116630 FAM180A chr7 135728348 135748813 +1116672 AC015987.1 chr7 135774521 135932997 +1116677 MTPN chr7 135926760 135977359 +1116700 LUZP6 chr7 135927274 135927450 +1116706 AC024084.1 chr7 136025717 136084668 +1116717 AC078845.1 chr7 136092913 136437785 +1116769 AC009264.1 chr7 136685559 137182107 +1116813 CHRM2 chr7 136868669 137020255 +1116874 PTN chr7 137227341 137343774 +1116907 AC078842.2 chr7 137318592 137326953 +1116914 AC078842.1 chr7 137344930 137354483 +1116928 DGKI chr7 137381037 137847092 +1117336 CREB3L2 chr7 137874979 138002086 +1117475 CREB3L2-AS1 chr7 137953348 137957966 +1117481 AKR1D1 chr7 138002324 138118305 +1117570 AC083867.2 chr7 138163440 138164637 +1117574 TRIM24 chr7 138460259 138589996 +1117687 SVOPL chr7 138594285 138701352 +1117845 ATP6V0A4 chr7 138706294 138799560 +1118143 TMEM213 chr7 138797952 138838101 +1118189 KIAA1549 chr7 138831381 138981318 +1118280 ZC3HAV1L chr7 139025706 139036042 +1118296 ZC3HAV1 chr7 139043515 139109720 +1118397 TTC26 chr7 139133744 139191986 +1118678 UBN2 chr7 139230356 139308236 +1118759 FMC1 chr7 139339457 139346328 +1118782 LUC7L2 chr7 139340359 139423457 +1118954 AC083880.1 chr7 139359032 139359566 +1118957 KLRG2 chr7 139452690 139483673 +1118982 CLEC2L chr7 139523685 139544985 +1119011 HIPK2 chr7 139561570 139777998 +1119108 TBXAS1 chr7 139777051 140020325 +1119518 PARP12 chr7 140023744 140063721 +1119649 KDM7A chr7 140084746 140176983 +1119727 KDM7A-DT chr7 140177184 140179640 +1119730 SLC37A3 chr7 140293693 140404433 +1120090 RAB19 chr7 140404043 140426250 +1120126 MKRN1 chr7 140453033 140479536 +1120334 DENND2A chr7 140518420 140673993 +1120584 AC006452.1 chr7 140640909 140669476 +1120592 ADCK2 chr7 140672945 140696261 +1120672 NDUFB2 chr7 140690777 140722790 +1120843 NDUFB2-AS1 chr7 140695336 140697077 +1120847 BRAF chr7 140719327 140924928 +1121318 MRPS33 chr7 141002610 141015228 +1121386 TMEM178B chr7 141074064 141480380 +1121420 AC005692.3 chr7 141392155 141396517 +1121425 AC005692.1 chr7 141414383 141416390 +1121429 AC005692.2 chr7 141429711 141431268 +1121433 AC073878.1 chr7 141500079 141551304 +1121452 AC073878.2 chr7 141512698 141513183 +1121456 AGK chr7 141551278 141655244 +1122077 AC004918.1 chr7 141652381 141656810 +1122081 DENND11 chr7 141656728 141702166 +1122128 AC004918.4 chr7 141662922 141663846 +1122131 WEE2-AS1 chr7 141704003 141738346 +1122228 WEE2 chr7 141708353 141731271 +1122271 SSBP1 chr7 141738334 141787922 +1122463 TAS2R3 chr7 141764097 141765197 +1122471 TAS2R4 chr7 141778442 141780819 +1122479 TAS2R5 chr7 141790217 141791367 +1122487 PRSS37 chr7 141836286 141841487 +1122554 MGAM chr7 141907813 142106747 +1122946 OR9A4 chr7 141916399 141920625 +1122963 CLEC5A chr7 141927357 141947007 +1123049 TAS2R38 chr7 141972631 141973773 +1123057 MGAM2 chr7 142111749 142222324 +1123211 PRSS58 chr7 142252143 142258058 +1123244 AC245088.2 chr7 142285750 142288869 +1123248 TRBV1 chr7 142299177 142299460 +1123251 TRBV2 chr7 142300924 142301432 +1123259 TRBV3-1 chr7 142308542 142309048 +1123267 TRBV4-1 chr7 142313184 142313666 +1123275 TRBV5-1 chr7 142320677 142321544 +1123285 TRBV6-1 chr7 142328297 142328786 +1123293 TRBV7-1 chr7 142332182 142332701 +1123301 TRBV4-2 chr7 142345421 142345985 +1123309 TRBV6-2 chr7 142349152 142349664 +1123317 TRBV7-2 chr7 142352819 142353358 +1123325 TRBV8-1 chr7 142358639 142358917 +1123328 TRBV5-2 chr7 142372640 142372912 +1123331 TRBV6-4 chr7 142380806 142381261 +1123339 TRBV7-3 chr7 142384329 142384841 +1123347 TRBV8-2 chr7 142386378 142386647 +1123350 TRBV5-3 chr7 142389202 142389668 +1123357 TRBV9 chr7 142391891 142392412 +1123365 TRBV10-1 chr7 142399860 142400377 +1123373 TRBV11-1 chr7 142407672 142408136 +1123381 TRBV12-1 chr7 142415224 142415666 +1123385 TRBV10-2 chr7 142424965 142425465 +1123393 TRBV11-2 chr7 142433895 142434394 +1123397 TRBV12-2 chr7 142440883 142441325 +1123401 TRBV6-5 chr7 142450947 142451448 +1123409 TRBV7-4 chr7 142455174 142455635 +1123416 TRBV5-4 chr7 142462916 142463581 +1123424 TRBV6-6 chr7 142469537 142470013 +1123432 TRBV7-5 chr7 142474096 142474567 +1123436 TRBV5-5 chr7 142482548 142483019 +1123444 TRBV6-7 chr7 142487863 142488295 +1123451 TRBV7-6 chr7 142492132 142492673 +1123459 TRBV5-6 chr7 142500028 142500534 +1123467 TRBV6-8 chr7 142507382 142507810 +1123474 TRBV7-7 chr7 142511626 142512127 +1123481 TRBV5-7 chr7 142520090 142520556 +1123488 TRBV7-9 chr7 142529290 142529762 +1123495 TRBV13 chr7 142535809 142536292 +1123502 TRBV10-3 chr7 142544212 142544685 +1123510 TRBV11-3 chr7 142554836 142555318 +1123518 TRBV12-3 chr7 142560423 142560931 +1123526 TRBV12-4 chr7 142563740 142564245 +1123534 TRBV12-5 chr7 142580917 142581427 +1123542 TRBV14 chr7 142587868 142588359 +1123550 TRBV15 chr7 142592928 142593473 +1123558 TRBV16 chr7 142598016 142598469 +1123565 TRBV17 chr7 142601628 142602360 +1123572 TRBV18 chr7 142615716 142616415 +1123580 TRBV19 chr7 142618849 142619532 +1123588 TRBV20-1 chr7 142626649 142627399 +1123596 TRBV21-1 chr7 142636924 142637384 +1123600 TRBV22-1 chr7 142641746 142642196 +1123604 TRBV23-1 chr7 142645961 142646467 +1123611 TRBV24-1 chr7 142656701 142657213 +1123619 MTRNR2L6 chr7 142666272 142667718 +1123627 TRBV25-1 chr7 142670740 142671244 +1123635 TRBVA chr7 142681415 142681869 +1123639 TRBV26 chr7 142695699 142696183 +1123643 TRBVB chr7 142711384 142711924 +1123647 TRBV27 chr7 142715346 142715861 +1123655 TRBV28 chr7 142720660 142721160 +1123663 AC244472.1 chr7 142725729 142733437 +1123667 TRBV29-1 chr7 142740206 142740894 +1123675 PRSS1 chr7 142749468 142753076 +1123746 PRSS2 chr7 142760398 142774564 +1123820 TRBD1 chr7 142786213 142786224 +1123824 TRBJ1-1 chr7 142786880 142786927 +1123828 TRBJ1-2 chr7 142787017 142787064 +1123832 TRBJ1-3 chr7 142787630 142787679 +1123836 TRBJ1-4 chr7 142788225 142788275 +1123840 TRBJ1-5 chr7 142788498 142788547 +1123844 TRBJ1-6 chr7 142788988 142789040 +1123848 TRBC1 chr7 142791694 142793368 +1123860 TRBJ2-1 chr7 142796365 142796414 +1123864 TRBJ2-2 chr7 142796560 142796610 +1123868 TRBJ2-2P chr7 142796697 142796742 +1123872 TRBJ2-3 chr7 142796847 142796895 +1123876 TRBJ2-4 chr7 142796998 142797047 +1123880 TRBJ2-5 chr7 142797119 142797166 +1123884 TRBJ2-6 chr7 142797239 142797291 +1123888 TRBJ2-7 chr7 142797456 142797502 +1123892 TRBC2 chr7 142801041 142802748 +1123904 TRBV30 chr7 142812586 142813399 +1123912 EPHB6 chr7 142855061 142871094 +1124215 TRPV6 chr7 142871208 142885745 +1124344 AC245427.1 chr7 142875836 142892743 +1124348 AC245427.2 chr7 142899365 142900759 +1124352 TRPV5 chr7 142908101 142933746 +1124440 LLCFC1 chr7 142939343 142940865 +1124459 KEL chr7 142941114 142962363 +1124578 OR9A2 chr7 143026158 143027195 +1124586 OR6V1 chr7 143052320 143053347 +1124594 PIP chr7 143132077 143139739 +1124608 TAS2R39 chr7 143183419 143184435 +1124615 AC073342.2 chr7 143220468 143222267 +1124618 TAS2R40 chr7 143222037 143223079 +1124626 GSTK1 chr7 143244093 143270854 +1124754 AC073342.1 chr7 143255264 143287997 +1124764 TMEM139 chr7 143279957 143288048 +1124839 CASP2 chr7 143288215 143307696 +1124956 CLCN1 chr7 143316111 143352083 +1125063 FAM131B chr7 143353400 143362770 +1125209 AC093673.2 chr7 143363899 143364229 +1125212 AC093673.1 chr7 143379692 143380495 +1125216 ZYX chr7 143381295 143391111 +1125339 EPHA1 chr7 143390289 143408856 +1125419 EPHA1-AS1 chr7 143407813 143523449 +1125430 TAS2R60 chr7 143443453 143444409 +1125437 TAS2R41 chr7 143477873 143478796 +1125444 CTAGE15 chr7 143571801 143574387 +1125452 TCAF2 chr7 143620952 143730409 +1125583 TCAF2C chr7 143639230 143647646 +1125599 CTAGE6 chr7 143755089 143757696 +1125607 TCAF1 chr7 143851375 143902198 +1125695 OR2F2 chr7 143935166 143936279 +1125703 OR2F1 chr7 143954844 143997312 +1125731 OR6B1 chr7 144000320 144008793 +1125748 OR2A5 chr7 144048948 144058845 +1125768 OR2A25 chr7 144069811 144075870 +1125794 OR2A12 chr7 144086278 144098953 +1125811 OR2A2 chr7 144109514 144110564 +1125819 OR2A14 chr7 144123176 144131188 +1125836 CTAGE4 chr7 144183466 144186053 +1125844 ARHGEF35 chr7 144186083 144195655 +1125854 AC004889.1 chr7 144194858 144280547 +1125906 OR2A42 chr7 144228244 144239605 +1125924 OR2A7 chr7 144257663 144264792 +1125941 CTAGE8 chr7 144266701 144269288 +1125949 OR2A1-AS1 chr7 144300395 144356181 +1126000 OR2A1 chr7 144312464 144322668 +1126016 ARHGEF5 chr7 144355288 144380632 +1126125 NOBOX chr7 144397240 144410227 +1126210 TPK1 chr7 144451941 144836395 +1126417 AC006007.1 chr7 145675679 145681369 +1126425 CNTNAP2 chr7 146116002 148420998 +1126680 AC006004.1 chr7 147080934 147097609 +1126686 AC005518.1 chr7 147671711 147673143 +1126690 AC006974.1 chr7 148473599 148503458 +1126695 AC006974.2 chr7 148543677 148572177 +1126703 AC005229.5 chr7 148584818 148625479 +1126707 C7orf33 chr7 148590766 148615860 +1126719 AC005229.4 chr7 148696467 148698664 +1126722 CUL1 chr7 148697914 148801110 +1127517 EZH2 chr7 148807383 148884321 +1127870 AC073140.2 chr7 148940265 148941228 +1127873 AC073140.1 chr7 148941483 148941638 +1127876 GHET1 chr7 148987527 148989432 +1127879 PDIA4 chr7 149003062 149028662 +1127945 ZNF786 chr7 149069641 149090782 +1127970 ZNF425 chr7 149102784 149126324 +1128001 ZNF398 chr7 149126416 149183042 +1128078 ZNF282 chr7 149195546 149226238 +1128130 ZNF212 chr7 149239651 149255606 +1128188 ZNF783 chr7 149262171 149297302 +1128284 AC004941.1 chr7 149398204 149401456 +1128288 AC073314.1 chr7 149422675 149424890 +1128291 ZNF777 chr7 149431363 149461062 +1128309 ZNF746 chr7 149472696 149497817 +1128386 KRBA1 chr7 149714781 149734575 +1128564 ZNF467 chr7 149764182 149773588 +1128595 SSPO chr7 149776042 149833979 +1128897 ZNF862 chr7 149838375 149867479 +1128943 AC004877.1 chr7 149858400 149862492 +1128946 ATP6V0E2-AS1 chr7 149867697 149880610 +1128960 ATP6V0E2 chr7 149872968 149891204 +1129117 AC093458.1 chr7 149881359 149881580 +1129120 AC092681.3 chr7 149890739 149891416 +1129123 AC092681.2 chr7 150000752 150005124 +1129127 AC092666.1 chr7 150033653 150076655 +1129294 AC006008.1 chr7 150234194 150237608 +1129298 ACTR3C chr7 150243916 150323725 +1129376 ZBED6CL chr7 150322639 150332721 +1129392 LRRC61 chr7 150323263 150338156 +1129426 AC005586.2 chr7 150337483 150343346 +1129432 RARRES2 chr7 150338317 150341662 +1129498 AC005586.1 chr7 150363777 150372590 +1129503 REPIN1 chr7 150368189 150374044 +1129663 ZNF775 chr7 150368790 150398630 +1129693 AC073111.1 chr7 150379854 150383885 +1129697 AC073111.4 chr7 150400702 150412470 +1129741 LINC00996 chr7 150433654 150448140 +1129751 GIMAP8 chr7 150450630 150479393 +1129767 GIMAP7 chr7 150514872 150521073 +1129777 GIMAP4 chr7 150567369 150573953 +1129816 GIMAP6 chr7 150625375 150632648 +1129847 GIMAP2 chr7 150685697 150693641 +1129873 GIMAP1 chr7 150716606 150724284 +1129888 GIMAP5 chr7 150722253 150750033 +1129931 TMEM176B chr7 150791285 150801360 +1130044 TMEM176A chr7 150800403 150805118 +1130157 AOC1 chr7 150824627 150861504 +1130248 KCNH2 chr7 150944961 150978321 +1130357 NOS3 chr7 150991017 151014588 +1130573 ATG9B chr7 151012209 151024499 +1130743 ABCB8 chr7 151028422 151047782 +1131124 AC010973.1 chr7 151028781 151029754 +1131128 ASIC3 chr7 151048292 151052756 +1131295 CDK5 chr7 151053815 151057897 +1131367 SLC4A2 chr7 151057210 151076526 +1131655 AC010973.2 chr7 151074742 151076530 +1131659 FASTK chr7 151076593 151080866 +1131831 TMUB1 chr7 151081085 151083493 +1131911 AGAP3 chr7 151085831 151144436 +1132228 GBX1 chr7 151148589 151174745 +1132241 ASB10 chr7 151175698 151187832 +1132302 IQCA1L chr7 151190873 151205496 +1132378 AC021097.2 chr7 151207837 151210378 +1132388 ABCF2 chr7 151211484 151227205 +1132462 CHPF2 chr7 151232489 151238827 +1132509 SMARCD3 chr7 151238764 151277896 +1132718 AC021097.1 chr7 151240399 151240972 +1132721 AC005486.1 chr7 151249325 151254390 +1132725 NUB1 chr7 151341699 151378449 +1132938 WDR86 chr7 151375909 151410727 +1133030 WDR86-AS1 chr7 151409161 151413354 +1133050 AC005996.1 chr7 151427683 151439124 +1133054 CRYGN chr7 151428835 151440813 +1133110 RHEB chr7 151466012 151520120 +1133218 PRKAG2 chr7 151556124 151877125 +1133926 AC093583.1 chr7 151806490 151810820 +1133934 PRKAG2-AS1 chr7 151877042 151879223 +1133942 AC074257.1 chr7 151950386 151954985 +1133946 GALNTL5 chr7 151956379 152019929 +1134155 GALNT11 chr7 152025674 152122340 +1134334 AC006017.1 chr7 152120001 152121717 +1134338 KMT2C chr7 152134922 152436005 +1134895 LINC01003 chr7 152463786 152465549 +1134898 XRCC2 chr7 152644776 152676141 +1134914 ACTR3B chr7 152759749 152855378 +1135011 AC006348.1 chr7 152925233 152936981 +1135017 LINC01287 chr7 153355365 153413985 +1135199 AC073236.1 chr7 153395484 153396921 +1135203 AC005998.1 chr7 153715074 153748986 +1135207 DPP6 chr7 153887097 154894285 +1135513 AC006019.3 chr7 154026287 154038604 +1135518 AC006019.1 chr7 154055286 154063325 +1135575 AC006019.2 chr7 154092201 154096043 +1135579 AC024730.1 chr7 154544169 154547285 +1135583 AC073336.1 chr7 154838388 154865483 +1135587 PAXIP1-AS2 chr7 154928460 154952188 +1135636 PAXIP1 chr7 154943687 155003124 +1135837 AC093726.1 chr7 154951226 154952188 +1135840 AC093726.2 chr7 154956429 154957107 +1135843 PAXIP1-AS1 chr7 155003448 155005703 +1135846 HTR5A-AS1 chr7 155067034 155072450 +1135860 HTR5A chr7 155070324 155087392 +1135882 AC099552.1 chr7 155196563 155198455 +1135891 AC099552.3 chr7 155204147 155205189 +1135895 AC099552.5 chr7 155213920 155217134 +1135899 AC099552.2 chr7 155267137 155270912 +1135912 AC144652.1 chr7 155295918 155297541 +1135915 INSIG1 chr7 155297776 155310235 +1135988 BLACE chr7 155356985 155367934 +1135998 AC008060.1 chr7 155382076 155396356 +1136002 AC008060.4 chr7 155399922 155401782 +1136005 AC008060.5 chr7 155412596 155421884 +1136011 AC008060.3 chr7 155421206 155457099 +1136016 EN2 chr7 155458129 155464831 +1136026 CNPY1 chr7 155474206 155555450 +1136087 AC009403.2 chr7 155474256 155644406 +1136155 AC008060.2 chr7 155510283 155518623 +1136159 AC009403.3 chr7 155534964 155536825 +1136163 AC009403.1 chr7 155611231 155645205 +1136181 RBM33 chr7 155644451 155781485 +1136361 SHH chr7 155799980 155812463 +1136417 AC021218.1 chr7 155962632 155966343 +1136421 LINC01006 chr7 156388922 156640654 +1136523 LINC00244 chr7 156540491 156541103 +1136526 RNF32 chr7 156640281 156677130 +1136741 AC005534.1 chr7 156654185 156659582 +1136749 LMBR1 chr7 156668946 156893216 +1137119 AC006357.1 chr7 156944721 156945645 +1137123 NOM1 chr7 156949712 156973176 +1137176 MNX1 chr7 156994051 157010663 +1137244 MNX1-AS2 chr7 157006307 157007132 +1137248 MNX1-AS1 chr7 157010805 157016426 +1137252 AC006967.2 chr7 157057709 157058514 +1137256 AC006967.3 chr7 157109980 157111072 +1137259 UBE3C chr7 157138916 157269370 +1137395 AC004975.2 chr7 157281536 157282686 +1137399 DNAJB6 chr7 157335381 157417439 +1137652 AC006372.3 chr7 157466231 157499716 +1137658 AC006372.1 chr7 157501322 157503908 +1137678 AC006372.2 chr7 157513294 157518658 +1137687 PTPRN2 chr7 157539056 158587823 +1137926 AC005481.1 chr7 157614023 157618765 +1137930 AC006003.1 chr7 157739010 157740456 +1137934 AC011899.2 chr7 157854529 157863011 +1137945 AC011899.3 chr7 157868538 157869154 +1137948 AC011899.4 chr7 157987169 157989456 +1137952 AC011899.1 chr7 158027373 158031128 +1137956 AC078942.1 chr7 158537495 158539879 +1137960 LINC01022 chr7 158590629 158591120 +1137964 NCAPG2 chr7 158631169 158704804 +1138313 ESYT2 chr7 158730995 158830253 +1138536 WDR60 chr7 158856558 158956747 +1138678 AC004863.1 chr7 158957497 158958699 +1138682 LINC00689 chr7 159006522 159030195 +1138702 VIPR2 chr7 159028175 159144867 +1138801 AC007269.1 chr7 159107761 159109216 +1138804 AC144568.2 chr8 72601 79775 +1138811 OR4F21 chr8 166049 167043 +1138819 ZNF596 chr8 232137 264703 +1138990 AC004908.2 chr8 233119 233692 +1138993 AC004908.1 chr8 234347 234887 +1138996 AC004908.3 chr8 237045 237669 +1138999 AC136777.1 chr8 311133 331026 +1139004 FAM87A chr8 375931 384079 +1139031 FBXO25 chr8 406428 477967 +1139167 AC083964.1 chr8 450714 451343 +1139170 TDRP chr8 489792 545781 +1139227 ERICH1 chr8 614746 738106 +1139304 AC100797.1 chr8 725188 725877 +1139308 DLGAP2 chr8 737596 1708474 +1139483 AC100797.5 chr8 738548 740374 +1139486 AC026950.2 chr8 891251 893112 +1139490 AC129915.3 chr8 1018757 1019704 +1139493 AC110288.1 chr8 1246789 1248760 +1139498 AF067845.2 chr8 1296034 1302607 +1139503 AF067845.1 chr8 1368642 1369833 +1139506 AF067845.5 chr8 1373685 1381394 +1139510 AF067845.4 chr8 1377867 1380307 +1139515 DLGAP2-AS1 chr8 1565509 1622417 +1139525 CLN8 chr8 1755778 1801711 +1139647 AC100810.3 chr8 1758208 1760447 +1139650 AC100810.1 chr8 1761054 1764508 +1139666 AC100810.7 chr8 1810823 1817113 +1139671 ARHGEF10 chr8 1823926 1958641 +1140056 AC019257.9 chr8 1957921 1963131 +1140060 AC019257.1 chr8 1971153 1974637 +1140077 KBTBD11-OT1 chr8 1971397 1976478 +1140082 KBTBD11 chr8 1973677 2006936 +1140092 AC019257.2 chr8 1974818 1975314 +1140095 AC245164.1 chr8 2033508 2035587 +1140099 MYOM2 chr8 2045046 2165552 +1140310 AC245164.2 chr8 2130550 2134880 +1140314 AC245519.1 chr8 2493876 2512580 +1140319 AC245519.2 chr8 2495522 2499428 +1140324 AC245187.2 chr8 2517898 2556440 +1140333 AC245187.1 chr8 2518998 2522182 +1140338 AC245123.1 chr8 2562813 2623382 +1140357 AC246817.2 chr8 2648075 2728577 +1140442 AC246817.1 chr8 2726956 2926689 +1140467 AC115485.1 chr8 2873525 2877916 +1140471 CSMD1 chr8 2935353 4994972 +1141525 AC026991.1 chr8 3373353 3375226 +1141529 AC026991.2 chr8 3409133 3426587 +1141538 AC027251.1 chr8 4317388 4329027 +1141543 AC010941.1 chr8 4496392 4503392 +1141549 AC022068.1 chr8 4633065 4635654 +1141554 AC004944.1 chr8 5506068 5509126 +1141557 AC084768.1 chr8 5659679 5670140 +1141570 AC087369.2 chr8 5853138 5854977 +1141574 AC079054.1 chr8 6036433 6036974 +1141579 AC009435.1 chr8 6044353 6257537 +1141586 AC016065.1 chr8 6403551 6407142 +1141596 MCPH1 chr8 6406596 6648508 +1141689 ANGPT2 chr8 6499651 6563409 +1141778 AC018398.1 chr8 6572571 6576219 +1141783 AF287957.1 chr8 6615604 6617198 +1141786 MCPH1-AS1 chr8 6617310 6708224 +1141848 AGPAT5 chr8 6708642 6761503 +1141921 AF233439.3 chr8 6780874 6789021 +1141926 XKR5 chr8 6808517 6835524 +1141967 AF233439.1 chr8 6835535 6885276 +1141986 DEFB1 chr8 6870592 6877936 +1141996 DEFA6 chr8 6924697 6926076 +1142006 AF233439.2 chr8 6928608 6930473 +1142011 DEFA4 chr8 6935820 6938306 +1142023 DEFA1 chr8 6977649 6980080 +1142043 DEFA1B chr8 6996766 6999195 +1142055 DEFA3 chr8 7015869 7018297 +1142067 DEFA5 chr8 7055304 7056739 +1142077 FAM66B chr8 7298744 7355359 +1142142 USP17L1 chr8 7332387 7333979 +1142149 USP17L4 chr8 7337115 7338707 +1142156 ZNF705G chr8 7355517 7385558 +1142176 DEFB4B chr8 7414855 7416863 +1142186 DEFB103B chr8 7428888 7430348 +1142196 SPAG11B chr8 7442684 7463674 +1142296 DEFB104B chr8 7470308 7475082 +1142306 DEFB106B chr8 7482504 7486400 +1142316 DEFB105B chr8 7487679 7489593 +1142328 DEFB107B chr8 7495911 7509311 +1142338 PRR23D1 chr8 7539628 7542450 +1142352 AC134684.11 chr8 7556700 7559712 +1142365 AC134684.8 chr8 7571995 7575006 +1142378 AC134684.9 chr8 7579644 7582653 +1142391 AC084121.9 chr8 7715443 7718453 +1142404 AC084121.11 chr8 7723091 7726101 +1142417 AC084121.6 chr8 7730739 7733749 +1142430 AC084121.12 chr8 7738387 7741396 +1142443 AC084121.8 chr8 7746034 7749044 +1142456 AC084121.7 chr8 7753682 7756692 +1142469 AC084121.5 chr8 7761330 7764340 +1142482 AC084121.13 chr8 7768977 7771988 +1142495 PRR23D2 chr8 7778591 7781413 +1142509 DEFB107A chr8 7811720 7815716 +1142519 DEFB105A chr8 7821966 7823889 +1142531 DEFB106A chr8 7825139 7829053 +1142541 DEFB104A chr8 7836436 7841242 +1142551 SPAG11A chr8 7847876 7868867 +1142651 DEFB103A chr8 7881204 7882664 +1142661 DEFB4A chr8 7894629 7896711 +1142671 ZNF705B chr8 7926337 7952413 +1142691 FAM66E chr8 7955014 8008755 +1142709 USP17L8 chr8 7971661 7973253 +1142716 USP17L3 chr8 7976393 7977985 +1142723 FAM85B chr8 8167819 8226614 +1142730 AC068020.1 chr8 8188535 8189195 +1142733 PRAG1 chr8 8317736 8386439 +1142765 AC103957.1 chr8 8414204 8424648 +1142776 AC103957.2 chr8 8456909 8461337 +1142781 AC114550.2 chr8 8555738 8560965 +1142785 AC114550.3 chr8 8559894 8562124 +1142790 AC114550.1 chr8 8561386 8574038 +1142810 AC087269.3 chr8 8665497 8669404 +1142814 CLDN23 chr8 8701937 8704096 +1142822 AC087269.1 chr8 8723693 8782479 +1142832 MFHAS1 chr8 8783354 8893630 +1142858 ERI1 chr8 9002147 9116746 +1142969 PPP1R3B chr8 9136255 9151574 +1142988 AC022784.5 chr8 9141424 9145503 +1142999 AC022784.1 chr8 9151695 9425524 +1143345 AC022784.6 chr8 9158063 9158621 +1143348 AC022784.2 chr8 9180251 9182519 +1143352 AC022784.3 chr8 9255349 9260295 +1143356 AC021736.1 chr8 9351238 9358441 +1143361 AC021242.2 chr8 9367898 9436205 +1143396 AC021242.3 chr8 9555144 9556520 +1143399 TNKS chr8 9555912 9782346 +1143611 LINC00599 chr8 9899871 9906678 +1143666 AC034111.2 chr8 9984004 10055041 +1143671 AC034111.1 chr8 10050485 10054254 +1143674 MSRA chr8 10054292 10428891 +1143806 AC023385.1 chr8 10118005 10147423 +1143810 AC079200.1 chr8 10275499 10279737 +1143815 AC104964.3 chr8 10433672 10438312 +1143818 AC104964.1 chr8 10474565 10482388 +1143844 AC104964.2 chr8 10476591 10479446 +1143855 PRSS51 chr8 10482878 10547585 +1143931 AC104964.4 chr8 10486807 10489666 +1143934 PRSS55 chr8 10525532 10554166 +1143978 RP1L1 chr8 10606349 10712187 +1143996 C8orf74 chr8 10672628 10700590 +1144059 SOX7 chr8 10723768 10730511 +1144069 AC105001.1 chr8 10729314 10772910 +1144081 PINX1 chr8 10764961 10839884 +1144176 AC011008.1 chr8 10839964 10847594 +1144185 XKR6 chr8 10896045 11201833 +1144223 AF131215.3 chr8 11062647 11067089 +1144227 AF131215.6 chr8 11104691 11106704 +1144230 AF131215.5 chr8 11107788 11109726 +1144233 AF131215.4 chr8 11123381 11126064 +1144237 AF131215.2 chr8 11136898 11138607 +1144240 AF131215.7 chr8 11202965 11203671 +1144243 LINC00529 chr8 11247626 11267865 +1144247 AF131216.4 chr8 11283481 11285068 +1144252 MTMR9 chr8 11284816 11328146 +1144333 AF131216.1 chr8 11315859 11325429 +1144337 SLC35G5 chr8 11330888 11332208 +1144345 AF131216.3 chr8 11345748 11347502 +1144349 FAM167A-AS1 chr8 11368402 11438658 +1144375 FAM167A chr8 11421476 11475908 +1144436 AF131216.5 chr8 11479203 11481068 +1144441 BLK chr8 11486894 11564599 +1144547 AC022239.1 chr8 11552488 11564694 +1144565 LINC00208 chr8 11576257 11582817 +1144586 AC022239.2 chr8 11643404 11647945 +1144590 GATA4 chr8 11676959 11760002 +1144711 C8orf49 chr8 11761256 11763223 +1144716 NEIL2 chr8 11769639 11787345 +1144808 FDFT1 chr8 11795573 11839304 +1145197 AC069185.1 chr8 11797928 11802568 +1145204 CTSB chr8 11842524 11869448 +1145677 AC025857.2 chr8 11846154 11846391 +1145680 AC107918.5 chr8 11936033 11941273 +1145684 AC107918.6 chr8 11946461 11950753 +1145689 DEFB136 chr8 11973937 11974599 +1145698 DEFB135 chr8 11982321 11984590 +1145707 DEFB134 chr8 11993174 11996312 +1145726 DEFB130B chr8 12064389 12071747 +1145735 ZNF705D chr8 12104389 12115516 +1145768 FAM66D chr8 12115767 12177550 +1145839 USP17L7 chr8 12132417 12134438 +1145847 USP17L2 chr8 12137168 12139077 +1145855 FAM86B1 chr8 12182096 12194133 +1146116 AC145124.1 chr8 12194467 12196280 +1146120 DEFB130A chr8 12310962 12318316 +1146129 FAM66A chr8 12362019 12388296 +1146140 AC087203.3 chr8 12412827 12414373 +1146143 FAM86B2 chr8 12425614 12436343 +1146209 AC068587.4 chr8 12467693 12665588 +1146253 AC130352.1 chr8 12476462 12477122 +1146256 LONRF1 chr8 12721906 12756073 +1146403 AC123777.1 chr8 12765849 12811478 +1146414 LINC00681 chr8 12794243 12818291 +1146418 TRMT9B chr8 12945642 13031503 +1146501 DLC1 chr8 13083361 13604610 +1146740 AC106845.1 chr8 13147389 13207125 +1146748 AC019270.1 chr8 13338574 13342754 +1146752 C8orf48 chr8 13566869 13568288 +1146760 AC022832.2 chr8 13629644 13632574 +1146764 AC022690.2 chr8 13844101 13849109 +1146768 SGCZ chr8 14084845 15238431 +1146806 AC022039.1 chr8 14161084 14165359 +1146811 AC084838.1 chr8 14879057 14879819 +1146815 TUSC3 chr8 15417215 15766649 +1147008 AC018437.3 chr8 15896267 15967950 +1147015 AC018437.2 chr8 15973315 16000324 +1147020 MSR1 chr8 16107878 16567490 +1147219 AC011586.2 chr8 16598758 16915044 +1147238 AC011586.1 chr8 16604255 16664879 +1147243 FGF20 chr8 16992181 17002345 +1147262 MICU3 chr8 17027238 17122642 +1147354 AC079193.2 chr8 17131181 17149789 +1147359 ZDHHC2 chr8 17156482 17224799 +1147418 CNOT7 chr8 17224966 17246878 +1147553 VPS37A chr8 17246931 17302427 +1147725 MTMR7 chr8 17296794 17413528 +1147839 SLC7A2 chr8 17497088 17570573 +1148018 AP006248.4 chr8 17510613 17511300 +1148021 PDGFRL chr8 17576433 17644071 +1148063 AP006248.6 chr8 17604667 17610269 +1148067 MTUS1 chr8 17643795 17800917 +1148425 AC124069.1 chr8 17703988 17706187 +1148429 AC027117.2 chr8 17801345 17861069 +1148433 AC027117.1 chr8 17808361 17822183 +1148447 FGL1 chr8 17864380 17910365 +1148620 AC087273.1 chr8 17882043 17882661 +1148624 AC087273.2 chr8 17900484 17908011 +1148633 PCM1 chr8 17922840 18029944 +1149133 ASAH1 chr8 18055992 18084998 +1150553 AC124242.1 chr8 18084386 18097644 +1150592 AC124242.3 chr8 18104797 18127346 +1150597 NAT1 chr8 18170477 18223689 +1150684 AC025062.3 chr8 18386311 18388323 +1150692 NAT2 chr8 18391282 18401218 +1150711 PSD3 chr8 18527303 19084730 +1151039 AC100800.1 chr8 18720905 18734405 +1151044 AC009884.1 chr8 18989279 19000952 +1151049 AC100849.1 chr8 19084992 19259469 +1151068 AC100849.2 chr8 19091703 19145449 +1151091 AC068880.3 chr8 19246350 19249240 +1151095 AC068880.2 chr8 19254241 19257334 +1151101 SH2D4A chr8 19313693 19396218 +1151190 CSGALNACT1 chr8 19404161 19758029 +1151371 AC090541.1 chr8 19678572 19688934 +1151375 INTS10 chr8 19817391 19852083 +1151567 LPL chr8 19901717 19967259 +1151658 AC100802.1 chr8 20079114 20124857 +1151664 SLC18A1 chr8 20144855 20183206 +1151950 ATP6V1B2 chr8 20197381 20226819 +1152056 LZTS1 chr8 20246165 20303963 +1152101 LZTS1-AS1 chr8 20275773 20290458 +1152106 AC023403.1 chr8 20350210 20372769 +1152118 AC018541.1 chr8 20655184 20700152 +1152131 AC015468.3 chr8 20941428 20950175 +1152137 AC021613.1 chr8 20942863 21298168 +1152178 AC015468.1 chr8 20953127 20968904 +1152190 AC015468.2 chr8 20954012 20968904 +1152196 LINC02153 chr8 20972021 20995119 +1152237 AC103719.1 chr8 21023276 21030368 +1152248 AC021613.3 chr8 21167240 21170137 +1152254 AC021355.1 chr8 21297933 21309486 +1152265 GFRA2 chr8 21690398 21812357 +1152405 DOK2 chr8 21908873 21913690 +1152463 XPO7 chr8 21919662 22006585 +1152636 NPM2 chr8 22024125 22036897 +1152842 FGF17 chr8 22042398 22048809 +1152881 DMTN chr8 22048995 22082527 +1153425 FAM160B2 chr8 22089150 22104911 +1153558 NUDT18 chr8 22106874 22109419 +1153579 HR chr8 22114419 22133384 +1153701 REEP4 chr8 22138020 22141951 +1153788 LGI3 chr8 22146830 22157084 +1153870 SFTPC chr8 22156913 22164479 +1153988 BMP1 chr8 22165140 22212326 +1154463 AC105206.1 chr8 22169338 22171710 +1154473 AC105206.3 chr8 22188369 22192578 +1154478 PHYHIP chr8 22219703 22232101 +1154530 POLR3D chr8 22245133 22254601 +1154614 AC105206.2 chr8 22254576 22275162 +1154618 PIWIL2 chr8 22275316 22357568 +1154821 SLC39A14 chr8 22367249 22434129 +1154979 PPP3CC chr8 22440819 22541142 +1155146 AC087854.1 chr8 22481588 22553444 +1155162 SORBS3 chr8 22544986 22575788 +1155426 AC037459.4 chr8 22545560 22548837 +1155430 AC037459.3 chr8 22565997 22567171 +1155434 PDLIM2 chr8 22578279 22598025 +1155794 C8orf58 chr8 22599599 22604150 +1155888 CCAR2 chr8 22604632 22621514 +1156170 AC037459.2 chr8 22613908 22616657 +1156173 BIN3 chr8 22620418 22669148 +1156334 AC105046.1 chr8 22679013 22684009 +1156337 EGR3 chr8 22687659 22693480 +1156373 AC055854.1 chr8 22690150 22798616 +1156388 AC105046.2 chr8 22698384 22703776 +1156392 PEBP4 chr8 22713251 23000000 +1156425 AC037441.1 chr8 22877972 22888022 +1156440 AC037441.2 chr8 22895434 22897813 +1156444 AC107959.1 chr8 22984596 23019335 +1156455 RHOBTB2 chr8 22987417 23020199 +1156565 TNFRSF10B chr8 23020133 23069031 +1156659 AC107959.2 chr8 23068229 23083619 +1156664 AC107959.3 chr8 23071377 23074488 +1156671 TNFRSF10C chr8 23102590 23117437 +1156704 TNFRSF10D chr8 23135588 23164027 +1156728 TNFRSF10A-AS1 chr8 23189279 23190675 +1156732 TNFRSF10A chr8 23190452 23225102 +1156800 AC100861.1 chr8 23224471 23230926 +1156814 AC100861.2 chr8 23225233 23230915 +1156818 CHMP7 chr8 23243637 23262000 +1156959 R3HCC1 chr8 23270120 23296279 +1157107 LOXL2 chr8 23296897 23425328 +1157241 AC090197.1 chr8 23336171 23366125 +1157249 ENTPD4 chr8 23385783 23457695 +1157405 AC104561.1 chr8 23458601 23484971 +1157409 AC104561.4 chr8 23492170 23494897 +1157413 AC104561.3 chr8 23493009 23494198 +1157417 SLC25A37 chr8 23528956 23575463 +1157498 NKX3-1 chr8 23678697 23682938 +1157518 NKX2-6 chr8 23702451 23706598 +1157527 AC012574.1 chr8 23707141 23789487 +1157532 AC012574.2 chr8 23714066 23743042 +1157542 STC1 chr8 23841929 23854806 +1157569 AC023202.1 chr8 24169001 24177080 +1157574 ADAM28 chr8 24294069 24359014 +1157795 AC120193.1 chr8 24295814 24912073 +1157816 ADAMDEC1 chr8 24384285 24406013 +1157918 ADAM7 chr8 24440930 24526970 +1158073 AC024958.1 chr8 24490312 24514856 +1158093 AF106564.1 chr8 24912165 24914717 +1158096 NEFM chr8 24913758 24919098 +1158154 NEFL chr8 24950955 24957110 +1158200 AC107373.2 chr8 24956621 24957110 +1158203 AC107373.1 chr8 24992002 25009777 +1158208 AC107373.3 chr8 25000436 25003439 +1158212 AC041005.1 chr8 25179113 25184234 +1158223 DOCK5 chr8 25184689 25418082 +1158534 GNRH1 chr8 25419258 25424654 +1158559 AC091185.1 chr8 25425521 25426580 +1158563 KCTD9 chr8 25427847 25458476 +1158684 CDCA2 chr8 25459199 25507911 +1158774 AC009623.1 chr8 25593197 25688786 +1158813 AC009623.2 chr8 25776679 25777456 +1158817 AC009623.3 chr8 25820975 25833464 +1158822 AC090103.1 chr8 25834129 25840135 +1158826 EBF2 chr8 25841725 26045413 +1158928 PPP2R2A chr8 26291508 26372680 +1159254 BNIP3L chr8 26383054 26505636 +1159356 AC011726.2 chr8 26422593 26423929 +1159360 AC011726.3 chr8 26440491 26442595 +1159366 PNMA2 chr8 26504701 26514092 +1159407 DPYSL2 chr8 26514031 26658178 +1159533 ADRA1A chr8 26748150 26867278 +1159636 AC090150.2 chr8 27086076 27087783 +1159640 AC090150.1 chr8 27171914 27210783 +1159646 STMN4 chr8 27235323 27258420 +1159759 TRIM35 chr8 27284886 27311272 +1159807 PTK2B chr8 27311482 27459391 +1160197 CHRNA2 chr8 27459756 27479883 +1160347 EPHX2 chr8 27490781 27545564 +1160620 CLU chr8 27596917 27614700 +1160829 SCARA3 chr8 27633868 27676776 +1160864 AC013643.2 chr8 27732915 27758552 +1160870 CCDC25 chr8 27733316 27772653 +1161059 ESCO2 chr8 27771949 27812640 +1161171 PBK chr8 27809624 27838082 +1161246 SCARA5 chr8 27869883 27992673 +1161324 AC069113.2 chr8 27904481 27910310 +1161329 NUGGC chr8 28021964 28083936 +1161384 ELP3 chr8 28089673 28191156 +1161761 AC021678.2 chr8 28250063 28339255 +1161765 PNOC chr8 28316986 28343355 +1161802 ZNF395 chr8 28345590 28402701 +1161942 FBXO16 chr8 28348287 28490278 +1162093 AC025871.3 chr8 28414499 28416593 +1162097 AC025871.2 chr8 28415524 28420055 +1162101 AC025871.1 chr8 28447264 28455902 +1162109 FZD3 chr8 28494205 28574267 +1162160 EXTL3 chr8 28600469 28755599 +1162279 EXTL3-AS1 chr8 28690215 28702030 +1162304 INTS9 chr8 28767661 28890242 +1162625 INTS9-AS1 chr8 28798142 28802085 +1162632 HMBOX1 chr8 28890395 29064764 +1162898 HMBOX1-IT1 chr8 28949676 28955955 +1162902 AC108449.2 chr8 29055935 29056685 +1162906 KIF13B chr8 29067278 29263124 +1163122 AC108449.3 chr8 29067279 29068454 +1163126 AC108449.1 chr8 29110573 29140729 +1163134 DUSP4 chr8 29333064 29350684 +1163163 AC084262.2 chr8 29351292 29360222 +1163168 AC084262.1 chr8 29352420 29353170 +1163171 AC084026.2 chr8 29527312 29530323 +1163175 AC084026.1 chr8 29548171 29564341 +1163179 LINC00589 chr8 29673922 29748109 +1163195 LINC02099 chr8 29748309 29798492 +1163210 AC131254.1 chr8 29815004 29854543 +1163222 AC131254.3 chr8 29864644 29871661 +1163226 AC131254.2 chr8 29905735 29908956 +1163230 LINC02209 chr8 29920560 29953724 +1163250 SARAF chr8 30063003 30083208 +1163402 AC044849.1 chr8 30082758 30083467 +1163405 LEPROTL1 chr8 30095408 30177208 +1163523 MBOAT4 chr8 30131671 30144665 +1163535 AC026979.2 chr8 30155830 30156232 +1163538 DCTN6 chr8 30156319 30183639 +1163633 AC026979.1 chr8 30176554 30180888 +1163637 AC026979.4 chr8 30192429 30201332 +1163642 AC026979.3 chr8 30197404 30198048 +1163645 AC090820.2 chr8 30279549 30281455 +1163649 RBPMS-AS1 chr8 30382119 30385401 +1163667 RBPMS chr8 30384511 30572256 +1163925 GTF2E2 chr8 30578318 30658236 +1164001 AC102945.1 chr8 30596914 30597532 +1164005 SMIM18 chr8 30638580 30646064 +1164026 GSR chr8 30678066 30727846 +1164216 UBXN8 chr8 30732247 30767006 +1164355 PPP2CB chr8 30774457 30814314 +1164441 TEX15 chr8 30831544 30913003 +1164512 PURG chr8 30995802 31033715 +1164536 WRN chr8 31033788 31175916 +1164726 AC009563.1 chr8 31167078 31177167 +1164735 AC068672.2 chr8 31275542 31390805 +1164747 AC068672.3 chr8 31339197 31346479 +1164759 AC068672.1 chr8 31497423 31498612 +1164763 AC090816.1 chr8 31536630 31546735 +1164770 NRG1 chr8 31639222 32855666 +1165440 AC068931.1 chr8 31827238 31840709 +1165446 NRG1-IT1 chr8 32026210 32139495 +1165469 NRG1-IT3 chr8 32440704 32448803 +1165478 AC083977.1 chr8 32647202 32647390 +1165485 AC090204.1 chr8 32927913 33045445 +1165545 AC067838.1 chr8 33360839 33361415 +1165548 FUT10 chr8 33370824 33473146 +1165625 TTI2 chr8 33473386 33513601 +1165720 MAK16 chr8 33485182 33501262 +1165781 RNF122 chr8 33547754 33567128 +1165799 DUSP26 chr8 33591330 33600023 +1165833 AF279873.3 chr8 33604856 34039104 +1165853 AF279873.4 chr8 33973701 34009595 +1165863 AC087855.2 chr8 34174886 34207513 +1165870 AC090993.1 chr8 34228439 34346731 +1165877 AC087855.1 chr8 34229294 34248946 +1165881 LINC01288 chr8 34784028 34865364 +1165892 AC099685.1 chr8 35080592 35093509 +1165896 UNC5D chr8 35235475 35796550 +1166117 AC105230.1 chr8 35672195 35707734 +1166123 AC124290.1 chr8 35862123 36191194 +1166160 AC124290.2 chr8 36004316 36095046 +1166169 AC090809.1 chr8 36378069 36779209 +1166199 KCNU1 chr8 36784324 36936125 +1166363 AC092818.1 chr8 37067441 37069418 +1166367 AC091182.1 chr8 37326575 37331991 +1166383 AC091182.2 chr8 37405439 37406724 +1166387 LINC01605 chr8 37421341 37554183 +1166410 AC124067.1 chr8 37480089 37480809 +1166414 AC124067.2 chr8 37516399 37521447 +1166426 AC124067.3 chr8 37559992 37567477 +1166464 AC124067.4 chr8 37597480 37599858 +1166470 AC137579.2 chr8 37600537 37625873 +1166477 AC137579.1 chr8 37626015 37674387 +1166481 ZNF703 chr8 37695782 37700019 +1166491 AC138356.3 chr8 37717579 37733756 +1166500 AC138356.1 chr8 37734761 37737426 +1166504 ERLIN2 chr8 37736601 37758422 +1166685 PLPBP chr8 37762595 37779768 +1166773 ADGRA2 chr8 37784191 37844896 +1166867 BRF2 chr8 37843268 37849861 +1166922 RAB11FIP1 chr8 37858618 37899497 +1166988 GOT1L1 chr8 37934281 37940124 +1167030 ADRB3 chr8 37962990 37966599 +1167042 EIF4EBP1 chr8 38030534 38060365 +1167058 AP006545.1 chr8 38062881 38063791 +1167061 AP006545.3 chr8 38082122 38099288 +1167066 AP006545.2 chr8 38099471 38099931 +1167069 ASH2L chr8 38105493 38144076 +1167301 AC084024.1 chr8 38123274 38124651 +1167305 STAR chr8 38142700 38150992 +1167352 AC084024.3 chr8 38148741 38163772 +1167356 LSM1 chr8 38163335 38176730 +1167406 BAG4 chr8 38176533 38213301 +1167447 AC084024.4 chr8 38223957 38231695 +1167453 DDHD2 chr8 38225218 38275558 +1167757 PLPP5 chr8 38263130 38269243 +1167920 NSD3 chr8 38269704 38382272 +1168151 AC087362.2 chr8 38275888 38276680 +1168155 AC087362.1 chr8 38335981 38337551 +1168159 AC087623.2 chr8 38382364 38383461 +1168162 LETM2 chr8 38386207 38409527 +1168403 FGFR1 chr8 38400215 38468834 +1169192 AC087623.3 chr8 38408048 38408742 +1169195 AC087623.1 chr8 38421889 38426096 +1169199 C8orf86 chr8 38510834 38560939 +1169232 AC069120.1 chr8 38543276 38560877 +1169262 AC016813.1 chr8 38699274 38704855 +1169272 TACC1 chr8 38728186 38853028 +1169694 AC067817.1 chr8 38799643 38802296 +1169698 AC067817.2 chr8 38844866 38846439 +1169702 PLEKHA2 chr8 38901235 38973912 +1169837 AC108863.2 chr8 38970360 38973011 +1169841 HTRA4 chr8 38974228 38988663 +1169865 TM2D2 chr8 38988808 38996824 +1169946 ADAM9 chr8 38996869 39105261 +1170176 ADAM32 chr8 39106990 39284917 +1170418 ADAM18 chr8 39584489 39730065 +1170600 ADAM2 chr8 39743735 39838289 +1170835 IDO1 chr8 39902275 39928790 +1170969 AC007991.3 chr8 39903775 39995248 +1170974 AC007991.2 chr8 39914229 39915721 +1170978 AC007991.4 chr8 39918076 39920890 +1170982 IDO2 chr8 39934614 40016391 +1171051 AC087518.1 chr8 40104169 40107935 +1171055 AC022733.1 chr8 40114651 40127468 +1171060 TCIM chr8 40153482 40155310 +1171068 AC022733.2 chr8 40161458 40172612 +1171074 SIRLNT chr8 40298697 40353133 +1171094 AC105999.1 chr8 40369981 40402010 +1171114 AC010857.1 chr8 40519565 40520158 +1171117 ZMAT4 chr8 40530590 40897833 +1171225 AC048387.1 chr8 40900016 40901854 +1171229 SFRP1 chr8 41261962 41309473 +1171252 AC104393.1 chr8 41275115 41277003 +1171256 AC016868.1 chr8 41435298 41440419 +1171261 GOLGA7 chr8 41490396 41510980 +1171344 AC009630.1 chr8 41509593 41578421 +1171350 GINS4 chr8 41529218 41545030 +1171457 AC009630.2 chr8 41540381 41545044 +1171464 AC009630.4 chr8 41566858 41568641 +1171468 GPAT4 chr8 41577187 41625001 +1171574 AC009630.3 chr8 41609692 41621502 +1171578 NKX6-3 chr8 41645177 41650817 +1171599 ANK1 chr8 41653220 41896762 +1172067 AC113133.1 chr8 41660991 41665566 +1172077 AC027702.1 chr8 41828165 41829934 +1172080 KAT6A chr8 41929479 42051994 +1172419 AC103724.4 chr8 42139461 42139752 +1172422 AC103724.3 chr8 42151772 42152763 +1172425 AP3M2 chr8 42152946 42171673 +1172637 PLAT chr8 42174718 42207676 +1172878 AC083973.1 chr8 42233674 42271266 +1172910 IKBKB chr8 42271302 42332653 +1173655 POLB chr8 42338454 42371808 +1173925 DKK4 chr8 42374063 42377229 +1173939 VDAC3 chr8 42391624 42405937 +1174120 SLC20A2 chr8 42416475 42541926 +1174271 AC090739.1 chr8 42537529 42538304 +1174275 SMIM19 chr8 42541155 42555193 +1174363 CHRNB3 chr8 42697366 42737407 +1174397 AC103843.1 chr8 42705583 42721946 +1174402 CHRNA6 chr8 42752620 42796392 +1174457 THAP1 chr8 42836674 42843325 +1174490 AC087533.1 chr8 42842989 42844876 +1174494 RNF170 chr8 42849637 42897290 +1174632 HOOK3 chr8 42896946 43030535 +1174748 FNTA chr8 43034194 43085788 +1174924 POMK chr8 43093506 43123434 +1174964 HGSNAT chr8 43140464 43202855 +1175114 AC021451.2 chr8 46810696 46819098 +1175118 AC021451.3 chr8 46814925 46817964 +1175123 LINC00293 chr8 46822174 46907309 +1176266 AC091163.1 chr8 46922561 46928832 +1176270 AC091163.2 chr8 46930604 46951850 +1176279 AC120036.5 chr8 47129262 47132628 +1176284 AC120036.4 chr8 47190772 47193262 +1176287 IGLV8OR8-1 chr8 47202444 47202897 +1176291 SPIDR chr8 47260878 47736306 +1176809 AC024451.4 chr8 47527397 47528148 +1176812 CEBPD chr8 47736913 47738164 +1176820 PRKDC chr8 47773108 47960183 +1177223 AC021236.1 chr8 47941426 47943670 +1177227 MCM4 chr8 47960185 47978160 +1177622 UBE2V2 chr8 48008415 48064708 +1177711 AC026904.1 chr8 48515852 48518157 +1177720 AC026904.2 chr8 48551527 48556441 +1177730 AC022915.2 chr8 48551567 48698510 +1177746 LINC02599 chr8 48590401 48594621 +1177750 LINC02847 chr8 48597458 48621018 +1177756 AC022915.1 chr8 48620465 48623895 +1177760 AC022915.3 chr8 48657260 48658894 +1177764 EFCAB1 chr8 48710789 48735311 +1177871 AC100805.1 chr8 48818293 48824062 +1177875 SNAI2 chr8 48917598 48921740 +1177899 AC013701.2 chr8 48925917 48931288 +1177903 AC044893.2 chr8 49046652 49058536 +1177907 PPDPFL chr8 49054311 49076090 +1177968 AC044893.1 chr8 49086301 49229174 +1178031 AC090155.2 chr8 49496763 49512180 +1178035 AC090155.1 chr8 49536386 49554414 +1178041 AC113145.1 chr8 49817586 49820944 +1178046 AC023762.1 chr8 49906863 49907446 +1178049 SNTG1 chr8 49909789 50796692 +1178764 AC090539.1 chr8 50381015 50382275 +1178768 AC012413.1 chr8 51257688 51321118 +1178772 PXDNL chr8 51319577 51809445 +1178856 AC090186.1 chr8 51810110 51810681 +1178859 PCMTD1 chr8 51817575 51899186 +1178944 AC103769.1 chr8 51895957 51896374 +1178948 AC064807.1 chr8 51899268 51949874 +1178965 AC064807.4 chr8 51950284 51950690 +1178968 AC064807.2 chr8 51961458 52022974 +1178972 AC064807.3 chr8 51996210 52008355 +1178976 ST18 chr8 52110839 52460959 +1179323 AC021915.2 chr8 52150820 52154892 +1179327 AC021915.1 chr8 52194362 52199580 +1179331 AC103831.1 chr8 52294455 52301942 +1179340 ALKAL1 chr8 52534037 52565430 +1179369 RB1CC1 chr8 52622458 52745843 +1179563 AC113139.1 chr8 52722903 52723141 +1179566 NPBWR1 chr8 52938431 52941117 +1179574 AC009646.2 chr8 53177571 53242683 +1179582 OPRK1 chr8 53225716 53251697 +1179674 AC131902.1 chr8 53388701 53390872 +1179677 AC022034.3 chr8 53394110 53484067 +1179817 AC022034.1 chr8 53493523 53524336 +1179842 AC022034.4 chr8 53515170 53515905 +1179846 ATP6V1H chr8 53715543 53843558 +1180102 RGS20 chr8 53851795 53959303 +1180202 AC113194.1 chr8 53876150 53876649 +1180205 TCEA1 chr8 53966552 54022456 +1180415 AC100821.2 chr8 54042989 54045629 +1180420 LYPLA1 chr8 54046367 54102017 +1180612 MRPL15 chr8 54135241 54148514 +1180652 AC027250.2 chr8 54381698 54394870 +1180657 SOX17 chr8 54457935 54460892 +1180667 RP1 chr8 54509422 54871720 +1180825 AC084834.1 chr8 55067585 55081909 +1180830 XKR4 chr8 55102028 55542054 +1180858 AC022679.2 chr8 55135203 55142358 +1180863 AC022679.1 chr8 55161446 55164727 +1180873 AC090200.1 chr8 55517240 55520977 +1180877 TMEM68 chr8 55696424 55773407 +1181112 TGS1 chr8 55773446 55826445 +1181176 LYN chr8 55879835 56014169 +1181259 AC018607.1 chr8 55893595 55895739 +1181263 RPS20 chr8 56067295 56074581 +1181388 CERNA3 chr8 56074592 56075274 +1181392 MOS chr8 56112942 56113982 +1181399 PLAG1 chr8 56160909 56211324 +1181446 CHCHD7 chr8 56211686 56218809 +1181659 AC107952.2 chr8 56222688 56223173 +1181662 SDR16C5 chr8 56300010 56320776 +1181720 PENK chr8 56436674 56446671 +1181792 AC012349.1 chr8 56445807 56556513 +1181813 LINC00968 chr8 56496048 56559823 +1181845 AC013644.1 chr8 56536758 56540497 +1181853 AC009597.1 chr8 56638894 56656496 +1181875 IMPAD1 chr8 56957931 56993867 +1181913 LINC01606 chr8 57142659 57244793 +1182045 AC025674.2 chr8 57261226 57266613 +1182050 LINC00588 chr8 57279543 57286968 +1182056 AC068075.1 chr8 57341021 57365444 +1182245 AC068075.2 chr8 57420834 57423673 +1182250 AC090796.1 chr8 57492884 57592451 +1182260 AC104051.1 chr8 57594166 57805029 +1182265 AC104051.2 chr8 57746149 57750199 +1182269 LINC01602 chr8 57855500 57984126 +1182282 AC012103.1 chr8 57888975 57934329 +1182294 FAM110B chr8 57994509 58204279 +1182339 AC104350.1 chr8 58031334 58032682 +1182343 AC027698.1 chr8 58091442 58106294 +1182349 AC092819.3 chr8 58227578 58243984 +1182354 AC092819.1 chr8 58255771 58272137 +1182419 AC092819.2 chr8 58269979 58272450 +1182423 UBXN2B chr8 58411359 58451501 +1182522 CYP7A1 chr8 58490178 58500163 +1182540 SDCBP chr8 58552924 58582859 +1182745 NSMAF chr8 58583508 58659853 +1183072 TOX chr8 58805412 59119147 +1183096 AC105150.1 chr8 58991720 58992938 +1183100 AC090152.1 chr8 59119040 59123478 +1183116 AC087664.1 chr8 59561324 59604774 +1183125 AC087664.2 chr8 59601319 59620227 +1183164 AC021393.1 chr8 60046755 60136599 +1183219 CA8 chr8 60185412 60281400 +1183262 LINC01301 chr8 60289928 60516795 +1183314 RAB2A chr8 60516936 60623644 +1183451 AC068389.3 chr8 60551957 60553036 +1183455 AC068389.1 chr8 60629662 60653561 +1183470 AC068389.2 chr8 60660820 60664530 +1183474 CHD7 chr8 60678740 60868028 +1183647 AC113143.1 chr8 60808735 60809606 +1183651 AC113143.3 chr8 60876969 60904644 +1183661 AC022182.1 chr8 60910053 60966557 +1183678 AC022182.2 chr8 60965802 60967775 +1183682 CLVS1 chr8 61057158 61501645 +1183789 AC023866.2 chr8 61264624 61292039 +1183794 AC023866.1 chr8 61300164 61301069 +1183801 ASPH chr8 61500556 61714640 +1184393 AC091173.1 chr8 61759094 61765969 +1184397 LINC02842 chr8 61785047 61944180 +1184446 AC025524.1 chr8 61821481 61825252 +1184450 LINC02155 chr8 61889839 61894206 +1184456 AC023095.1 chr8 62191088 62249879 +1184462 NKAIN3 chr8 62248591 62999652 +1184506 AC018861.2 chr8 62473217 62474269 +1184510 AC090577.1 chr8 62658343 62690133 +1184515 NKAIN3-IT1 chr8 62977861 62984900 +1184520 AC120042.1 chr8 63013068 63014681 +1184524 GGH chr8 63015079 63038806 +1184583 AC120042.2 chr8 63024372 63025294 +1184587 TTPA chr8 63048553 63086053 +1184606 YTHDF3-AS1 chr8 63167725 63168442 +1184609 YTHDF3 chr8 63168553 63212786 +1184805 AC011978.2 chr8 63215981 63218034 +1184808 AC011124.1 chr8 63384839 63470205 +1184845 AC011124.2 chr8 63465831 63478745 +1184870 AC018953.1 chr8 63586000 63589408 +1184875 AC018953.2 chr8 63651457 63693249 +1184879 LINC01414 chr8 63687179 64369176 +1184924 AC069133.1 chr8 63703077 63751677 +1184935 LINC01289 chr8 63769428 63813937 +1184950 MIR124-2HG chr8 64373151 64383787 +1184991 AC012535.1 chr8 64456198 64462926 +1184995 AC090136.3 chr8 64574306 64581921 +1185011 BHLHE22 chr8 64580365 64583627 +1185019 CYP7B1 chr8 64587763 64798737 +1185043 AC104232.2 chr8 64703774 64734459 +1185050 AC104232.3 chr8 64798804 64862370 +1185055 AC104232.1 chr8 64801236 64817573 +1185066 LINC00251 chr8 65161145 65184210 +1185080 LINC01299 chr8 65526738 65562781 +1185087 AC100814.1 chr8 65591850 65592472 +1185090 ARMC1 chr8 65602458 65634217 +1185174 MTFR1 chr8 65644734 65771261 +1185316 AC055822.1 chr8 65714334 65714778 +1185319 PDE7A chr8 65717510 65842322 +1185448 AC100812.1 chr8 65842752 65843331 +1185451 DNAJC5B chr8 66021553 66101245 +1185491 AC084082.1 chr8 66112667 66126632 +1185525 TRIM55 chr8 66126896 66175485 +1185619 CRH chr8 66176376 66178464 +1185629 LINC00967 chr8 66192093 66197315 +1185647 AC009879.4 chr8 66363774 66432370 +1185651 RRS1-AS1 chr8 66419589 66428977 +1185656 RRS1 chr8 66429014 66430733 +1185664 ADHFE1 chr8 66432492 66468907 +1185978 VXN chr8 66493520 66518524 +1186096 MYBL1 chr8 66562175 66614247 +1186210 VCPIP1 chr8 66628487 66667231 +1186222 SGK3 chr8 66667552 66862022 +1186592 MCMDC2 chr8 66870749 66922048 +1186783 SNHG6 chr8 66921684 66926398 +1186805 TCF24 chr8 66946501 66962591 +1186822 PPP1R42 chr8 66964099 67056604 +1186914 COPS5 chr8 67043079 67083783 +1187076 CSPP1 chr8 67062426 67196263 +1187299 ARFGEF1 chr8 67173511 67343781 +1187527 AC021321.2 chr8 67313043 67314637 +1187531 AC021321.1 chr8 67343975 67345087 +1187534 CPA6 chr8 67422038 67746378 +1187626 AC022874.1 chr8 67732587 67735665 +1187630 PREX2 chr8 67952046 68237032 +1187776 AC011853.2 chr8 68082204 68095081 +1187780 C8orf34-AS1 chr8 68302246 68331689 +1187831 C8orf34 chr8 68330955 68819023 +1187991 AC083967.1 chr8 68848737 68852763 +1188000 LINC01592 chr8 68880139 69104242 +1188085 AC021785.1 chr8 69175579 69178189 +1188090 LINC01603 chr8 69424849 69448282 +1188114 SULF1 chr8 69466624 69660915 +1188497 SLCO5A1 chr8 69667046 69834978 +1188599 AC091047.1 chr8 69713390 69719722 +1188604 AC079089.1 chr8 69834111 69854971 +1188619 PRDM14 chr8 70051651 70071693 +1188648 NCOA2 chr8 70109782 70403808 +1188798 AC022730.3 chr8 70471112 70480623 +1188802 AC022730.4 chr8 70471134 70485687 +1188808 AC120194.1 chr8 70525053 70535646 +1188813 TRAM1 chr8 70573218 70608416 +1188896 LACTB2-AS1 chr8 70608577 70663279 +1188919 LACTB2 chr8 70635318 70669185 +1188966 XKR9 chr8 70669339 70790371 +1189030 AC022858.1 chr8 71155454 71204223 +1189046 EYA1 chr8 71197433 71592025 +1189702 AC009446.1 chr8 71675300 71702786 +1189710 AC104012.1 chr8 71779605 71792875 +1189715 MSC-AS1 chr8 71828167 72118393 +1189789 MSC chr8 71841549 71844468 +1189805 TRPA1 chr8 72019917 72075584 +1189933 AC078906.1 chr8 72196334 72202269 +1189937 AC011131.1 chr8 72462311 72470972 +1189941 KCNB2 chr8 72537225 72938349 +1189953 AC013562.1 chr8 72732045 72751843 +1189958 AC090735.1 chr8 72874859 72881740 +1189963 AC022893.2 chr8 72947150 72950445 +1189966 TERF1 chr8 73008864 73048123 +1190054 AC022893.3 chr8 73042910 73043346 +1190057 AC022893.1 chr8 73052178 73063061 +1190061 SBSPON chr8 73064543 73124088 +1190083 AC100823.1 chr8 73083787 73085879 +1190087 C8orf89 chr8 73241329 73259502 +1190125 RPL7 chr8 73290242 73295789 +1190224 RDH10 chr8 73294602 73325281 +1190274 RDH10-AS1 chr8 73297711 73356461 +1190291 AC111149.1 chr8 73326991 73370601 +1190316 AC111149.2 chr8 73358670 73364212 +1190333 STAU2-AS1 chr8 73420004 73441526 +1190341 STAU2 chr8 73420369 73747708 +1190822 AC027018.1 chr8 73670441 73732897 +1190830 UBE2W chr8 73780097 73878910 +1190983 AC022868.2 chr8 73879046 73882733 +1190988 ELOC chr8 73939169 73972287 +1191125 TMEM70 chr8 73972437 73982783 +1191177 LY96 chr8 73991392 74029079 +1191206 AC087672.2 chr8 74052340 74099853 +1191210 AC087627.1 chr8 74093545 74208536 +1191222 AC087672.1 chr8 74103516 74106744 +1191226 JPH1 chr8 74234700 74321540 +1191263 GDAP1 chr8 74321130 74488872 +1191339 AC103952.1 chr8 74347757 74350050 +1191343 MIR2052HG chr8 74599775 74823313 +1191377 AC115837.2 chr8 74609698 74633320 +1191384 AC011632.1 chr8 74798784 74866939 +1191399 PI15 chr8 74824534 74855029 +1191449 AC011632.2 chr8 74891151 74896302 +1191453 CRISPLD1 chr8 74984505 75034558 +1191568 AC100782.1 chr8 75026428 75029460 +1191572 AC022274.1 chr8 75167704 75176656 +1191576 CASC9 chr8 75223127 75324741 +1191599 HNF4G chr8 75407914 75566834 +1191664 AC011029.1 chr8 76162119 76308315 +1191669 AC067773.1 chr8 76403998 76405091 +1191672 LINC01111 chr8 76406654 76524356 +1191680 ZFHX4-AS1 chr8 76491200 76683308 +1191719 AC013509.1 chr8 76576551 76579345 +1191723 ZFHX4 chr8 76681239 76867281 +1191889 AC023200.1 chr8 76904591 76913399 +1191894 PEX2 chr8 76980258 77001044 +1191955 AC062004.1 chr8 77399072 77537290 +1191974 AC084706.1 chr8 78148101 78153913 +1191981 PKIA-AS1 chr8 78268637 78558503 +1192006 PKIA chr8 78516340 78605267 +1192042 AC068700.1 chr8 78605952 78609705 +1192045 AC068700.2 chr8 78626775 78665982 +1192049 ZC2HC1A chr8 78666089 78719765 +1192096 IL7 chr8 78675743 78805523 +1192234 AC083837.1 chr8 78805293 78956082 +1192242 LINC02605 chr8 78835307 78840525 +1192245 AC138646.1 chr8 79259402 79314951 +1192266 STMN2 chr8 79610814 79666175 +1192315 AC016240.1 chr8 79747351 79749561 +1192319 HEY1 chr8 79764010 79767857 +1192383 LINC01607 chr8 79768110 79802842 +1192397 AC036214.1 chr8 79769372 79871759 +1192413 AC036214.4 chr8 79891553 79930892 +1192430 MRPS28 chr8 79918717 80030289 +1192513 AC036214.2 chr8 79956465 79957381 +1192516 AC009686.2 chr8 80032724 80033300 +1192519 TPD52 chr8 80034745 80231232 +1192830 AC009686.1 chr8 80122852 80127670 +1192834 AC034114.2 chr8 80265907 80484481 +1192898 AC009812.1 chr8 80484561 80486699 +1192902 ZBTB10 chr8 80485619 80526265 +1192994 AC009812.3 chr8 80535006 80539135 +1192998 AC009812.4 chr8 80541300 80543104 +1193001 ZNF704 chr8 80628451 80874781 +1193055 AC012533.1 chr8 80894016 80930081 +1193061 PAG1 chr8 80967810 81112068 +1193094 AC022778.1 chr8 81036964 81040831 +1193099 AC079209.2 chr8 81058523 81067744 +1193103 AC079209.1 chr8 81149107 81165266 +1193141 AC009902.3 chr8 81275399 81277570 +1193144 AC009902.2 chr8 81279871 81281446 +1193151 FABP5 chr8 81280536 81284777 +1193184 AC018616.1 chr8 81439436 81521818 +1193190 PMP2 chr8 81440326 81447439 +1193215 FABP9 chr8 81458383 81461579 +1193229 FABP4 chr8 81478419 81483236 +1193264 AC023644.1 chr8 81521618 81533275 +1193274 FABP12 chr8 81524981 81531378 +1193299 IMPA1 chr8 81656914 81686331 +1193519 SLC10A5 chr8 81693607 81695058 +1193527 ZFAND1 chr8 81701334 81732903 +1193853 CHMP4C chr8 81732448 81759515 +1193869 AC132219.1 chr8 81791823 81815714 +1193873 SNX16 chr8 81799581 81842866 +1194038 LINC02235 chr8 81841952 81924348 +1194101 AC060765.2 chr8 82033533 82961926 +1194127 LINC02839 chr8 82098451 82160577 +1194140 AC060765.1 chr8 82514568 82677153 +1194166 AC105031.2 chr8 82862779 82958696 +1194174 LINC01419 chr8 83403758 83408900 +1194178 AC015522.1 chr8 83912713 84142463 +1194189 RALYL chr8 84182787 84921844 +1194373 LRRCC1 chr8 85107215 85146080 +1194578 AC011773.4 chr8 85172077 85177062 +1194585 E2F5 chr8 85177154 85217158 +1194716 AC011773.1 chr8 85177522 85178150 +1194720 RBIS chr8 85214048 85220421 +1194848 CA13 chr8 85220587 85284073 +1194890 AC011773.3 chr8 85222446 85245717 +1194899 AC011773.2 chr8 85246295 85249848 +1194903 CA1 chr8 85327608 85379014 +1195258 CA3 chr8 85373436 85449040 +1195294 CA3-AS1 chr8 85440596 85464915 +1195329 CA2 chr8 85463968 85481493 +1195394 AC084734.1 chr8 85495693 85540511 +1195410 AC100801.1 chr8 85833377 85951083 +1195423 LINC02849 chr8 85851446 85861562 +1195429 AC100801.2 chr8 85973793 85977154 +1195433 ATP6V0D2 chr8 85987323 86154225 +1195475 PSKH2 chr8 86047109 86088621 +1195495 AC023194.3 chr8 86098965 86154225 +1195502 AC084128.1 chr8 86180418 86212236 +1195509 SLC7A13 chr8 86214063 86321146 +1195543 AC103760.1 chr8 86333274 86343429 +1195556 WWP1 chr8 86342547 86478420 +1195739 RMDN1 chr8 86468257 86514357 +1196009 CPNE3 chr8 86514435 86561498 +1196183 CNGB3 chr8 86553977 86743675 +1196241 AC090572.3 chr8 86707547 86765023 +1196246 AC090572.2 chr8 86765935 86818558 +1196254 CNBD1 chr8 86866415 87615219 +1196344 AF121898.1 chr8 87540835 87755718 +1196365 DCAF4L2 chr8 87870747 87874015 +1196373 AC037450.1 chr8 87974165 88019113 +1196381 MMP16 chr8 88032011 88328025 +1196433 AC090578.1 chr8 88326836 88887573 +1196507 AC090578.2 chr8 88808318 88808908 +1196510 AC090578.3 chr8 88809949 88813144 +1196514 AF117829.1 chr8 89585872 89757812 +1196584 RIPK2 chr8 89757806 89791064 +1196651 OSGIN2 chr8 89901849 89927888 +1196718 NBN chr8 89933336 90003228 +1196916 DECR1 chr8 90001405 90053633 +1197170 CALB1 chr8 90058608 90095475 +1197296 AC004083.1 chr8 90198389 90620077 +1197314 LINC00534 chr8 90221341 90687863 +1197442 LINC01030 chr8 90592804 90606065 +1197447 TMEM64 chr8 90621995 90791632 +1197512 AC106038.1 chr8 90646420 90670929 +1197528 NECAB1 chr8 90791741 90959393 +1197604 AC103770.1 chr8 90806474 90859240 +1197610 C8orf88 chr8 90958471 90985238 +1197628 PIP4P2 chr8 90993802 91040872 +1197724 AC087439.1 chr8 91016588 91018655 +1197728 AC087439.2 chr8 91042690 91044762 +1197736 OTUD6B-AS1 chr8 91059318 91070583 +1197751 OTUD6B chr8 91070196 91087095 +1197857 LRRC69 chr8 91101832 91219236 +1197935 SLC26A7 chr8 91209494 91398155 +1198243 AC103409.1 chr8 91542924 91907619 +1198254 RUNX1T1 chr8 91954967 92103286 +1199032 AF181450.1 chr8 91975908 91977418 +1199036 AC022695.2 chr8 92402920 92413681 +1199056 AC022695.3 chr8 92420850 92421798 +1199060 AC091096.1 chr8 92460539 92655576 +1199093 AC104211.2 chr8 92668660 92683450 +1199114 AC104211.4 chr8 92687222 92697826 +1199118 AC104211.1 chr8 92699742 92879502 +1199134 AC104211.3 chr8 92723024 92725111 +1199138 AC117834.2 chr8 92765651 92858297 +1199151 AC117834.1 chr8 92882984 92965645 +1199165 TRIQK chr8 92883532 93017673 +1199428 C8orf87 chr8 93134095 93166850 +1199440 LINC00535 chr8 93213302 93700433 +1199466 AC016885.1 chr8 93215925 93234878 +1199472 AC016885.2 chr8 93259667 93298528 +1199481 FAM92A chr8 93698561 93731527 +1199787 AC120053.1 chr8 93715378 93716113 +1199790 AC010834.3 chr8 93719574 93721167 +1199794 RBM12B chr8 93729356 93741017 +1199866 AC010834.1 chr8 93733216 93734022 +1199870 AC010834.2 chr8 93741193 93744534 +1199874 TMEM67 chr8 93754844 93819234 +1200281 AC084346.1 chr8 93834454 93846743 +1200285 PDP1 chr8 93857807 93926068 +1200370 MIR378D2HG chr8 93915734 93916682 +1200373 AP003351.1 chr8 94097764 94104322 +1200378 CDH17 chr8 94127162 94217303 +1200520 GEM chr8 94249253 94262350 +1200564 RAD54B chr8 94371960 94475115 +1200673 FSBP chr8 94372170 94436952 +1200738 VIRMA chr8 94487689 94553529 +1200899 AC023632.5 chr8 94533628 94534391 +1200903 AC023632.2 chr8 94553668 94570648 +1200925 AC108860.2 chr8 94637285 94639467 +1200928 ESRP1 chr8 94641074 94707466 +1201186 DPY19L4 chr8 94719703 94793836 +1201317 AP003692.1 chr8 94791643 94793106 +1201324 INTS8 chr8 94813311 94881746 +1201749 CCNE2 chr8 94879770 94896678 +1201896 AC087752.4 chr8 94884609 94885070 +1201899 NDUFAF6 chr8 94895767 95116455 +1202213 TP53INP1 chr8 94925972 94949378 +1202242 AC087752.3 chr8 94950037 94951396 +1202251 AC068189.2 chr8 95039617 95042209 +1202255 MIR3150BHG chr8 95066808 95073182 +1202262 AC068189.1 chr8 95071732 95087924 +1202268 PLEKHF2 chr8 95133785 95156685 +1202287 C8orf37-AS1 chr8 95204456 95811254 +1202325 LINC01298 chr8 95206876 95216525 +1202342 C8orf37 chr8 95244913 95269201 +1202360 AC083836.1 chr8 95505406 95527524 +1202367 AC012339.1 chr8 95986108 95993103 +1202371 AP003465.2 chr8 96140572 96140944 +1202374 GDF6 chr8 96142333 96160806 +1202408 UQCRB chr8 96225920 96235634 +1202504 AP003465.1 chr8 96235427 96239149 +1202513 MTERF3 chr8 96239398 96261610 +1202599 PTDSS1 chr8 96261902 96336995 +1202698 AP003548.1 chr8 96370800 96387438 +1202707 SDC2 chr8 96493813 96611790 +1202800 CPQ chr8 96645242 97149654 +1202879 AP003117.2 chr8 97132835 97133379 +1202882 AP003117.1 chr8 97144170 97144723 +1202885 AP003115.1 chr8 97241742 97242204 +1202888 TSPYL5 chr8 97273488 97277928 +1202896 AP002982.2 chr8 97643366 97643881 +1202899 MTDH chr8 97644184 97730260 +1202997 LAPTM4B chr8 97775057 97853013 +1203068 MATN2 chr8 97868840 98036724 +1203423 RPL30 chr8 98024851 98046469 +1203533 AP003352.1 chr8 98041726 98044121 +1203537 ERICH5 chr8 98064522 98093610 +1203558 RIDA chr8 98102344 98117171 +1203629 POP1 chr8 98117293 98159835 +1203720 NIPAL2 chr8 98189826 98294393 +1203810 STK3 chr8 98371228 98942827 +1204013 KCNS2 chr8 98426958 98432853 +1204032 AP003355.2 chr8 98436669 98439290 +1204035 AP003467.1 chr8 98603253 98606340 +1204039 AC016877.3 chr8 98943595 98944098 +1204042 OSR2 chr8 98944403 98952104 +1204132 VPS13B-DT chr8 98958277 99013743 +1204157 AC016877.1 chr8 98961428 98968284 +1204162 VPS13B chr8 99013266 99877580 +1204592 AC107909.2 chr8 99091738 99094060 +1204596 AC107909.1 chr8 99119352 99120581 +1204600 AC018442.2 chr8 99796615 99799187 +1204604 COX6C chr8 99873200 99893707 +1204739 AC105328.1 chr8 99893373 99895121 +1204742 RGS22 chr8 99960936 100131268 +1205152 FBXO43 chr8 100133351 100145817 +1205187 POLR2K chr8 100150623 100154003 +1205216 SPAG1 chr8 100157906 100259278 +1205364 RNF19A chr8 100257060 100336218 +1205500 AP001574.1 chr8 100337595 100350707 +1205504 AP003472.1 chr8 100380486 100464613 +1205523 AP003472.2 chr8 100427559 100432726 +1205536 AP000424.1 chr8 100475667 100501148 +1205551 AP000424.2 chr8 100492528 100493713 +1205555 ANKRD46 chr8 100509752 100559784 +1205677 SNX31 chr8 100572889 100663415 +1205787 AP001205.1 chr8 100618581 100619993 +1205796 PABPC1 chr8 100685816 100722809 +1206136 AC027373.1 chr8 100913247 100914388 +1206139 YWHAZ chr8 100916523 100953388 +1206431 AC018781.1 chr8 101034868 101076407 +1206485 AP003469.2 chr8 101122145 101126158 +1206490 AP003469.1 chr8 101128987 101133486 +1206498 AP003469.3 chr8 101139665 101140929 +1206503 AP003469.4 chr8 101166805 101169629 +1206506 ZNF706 chr8 101177878 101206193 +1206672 AP001330.4 chr8 101208148 101208558 +1206675 LINC02844 chr8 101261541 101262903 +1206679 AP001330.5 chr8 101275425 101280835 +1206683 AP001330.1 chr8 101287445 101293783 +1206688 LINC02845 chr8 101387299 101393255 +1206697 AP001208.1 chr8 101411873 101452452 +1206701 AP001207.3 chr8 101461177 101492499 +1206705 GRHL2 chr8 101492439 101669726 +1206800 NCALD chr8 101686542 102124907 +1207128 AP000426.1 chr8 101686547 101689093 +1207132 RRM2B chr8 102204502 102239118 +1207283 UBR5-AS1 chr8 102239394 102253750 +1207294 UBR5 chr8 102252273 102412759 +1207754 AP002907.1 chr8 102256392 102257821 +1207757 AP002852.1 chr8 102528740 102539943 +1207769 ODF1 chr8 102551589 102561018 +1207788 KLF10 chr8 102648784 102655725 +1207815 AP002851.1 chr8 102656464 102687118 +1207822 GASAL1 chr8 102805517 102810039 +1207838 AZIN1 chr8 102826308 102893864 +1207962 AP003696.1 chr8 102854455 102856075 +1207966 AZIN1-AS1 chr8 102864271 103002424 +1208045 AP003354.1 chr8 102891876 102893608 +1208049 AP003550.1 chr8 103020187 103021428 +1208053 ATP6V1C1 chr8 103021063 103073051 +1208183 LINC01181 chr8 103121032 103132966 +1208187 BAALC-AS2 chr8 103132963 103141475 +1208194 BAALC chr8 103140713 103230305 +1208259 BAALC-AS1 chr8 103153394 103298772 +1208321 AC025370.1 chr8 103228425 103229314 +1208325 FZD6 chr8 103298433 103332866 +1208457 AC025370.2 chr8 103319392 103320106 +1208461 CTHRC1 chr8 103371538 103382989 +1208508 AC012213.3 chr8 103383078 103383854 +1208511 SLC25A32 chr8 103398635 103415189 +1208583 DCAF13 chr8 103414714 103443453 +1208739 AC012213.2 chr8 103464389 103468985 +1208742 AC012213.4 chr8 103481266 103481619 +1208745 AC012213.1 chr8 103483398 103501676 +1208756 RIMS2 chr8 103500696 104256094 +1209286 DPYS chr8 104330324 104467055 +1209348 DCSTAMP chr8 104339087 104356689 +1209399 AP003471.1 chr8 104419512 104421500 +1209405 LRP12 chr8 104489231 104589024 +1209465 ZFPM2 chr8 104590733 105804539 +1209574 AC012564.1 chr8 104699479 104703555 +1209578 AC021546.1 chr8 105142860 105188606 +1209583 ZFPM2-AS1 chr8 105546089 106060524 +1209636 AC103853.1 chr8 105662352 105685765 +1209641 AC103853.2 chr8 105669991 105679031 +1209646 AC090802.1 chr8 105826570 105834038 +1209650 AC027031.1 chr8 106265435 106268741 +1209654 AC027031.2 chr8 106270144 106272902 +1209667 OXR1 chr8 106359476 106752694 +1209960 AC090579.1 chr8 106520474 106657548 +1209966 ABRA chr8 106759483 106770244 +1209976 AP000428.2 chr8 107160354 107166595 +1209980 AP000428.1 chr8 107186997 107195938 +1209987 ANGPT1 chr8 107249482 107498055 +1210096 AC091010.1 chr8 107499773 107506416 +1210100 AC025508.1 chr8 107857589 107963516 +1210107 RSPO2 chr8 107899316 108083642 +1210205 EIF3E chr8 108201216 108435333 +1210435 AC087620.1 chr8 108226200 108227544 +1210439 EMC2 chr8 108443601 108489196 +1210523 AC022634.2 chr8 108581062 108626767 +1210528 TMEM74 chr8 108606850 108787594 +1210543 AC104248.1 chr8 108871128 109063417 +1210568 TRHR chr8 109086621 109119584 +1210589 NUDCD1 chr8 109240919 109334118 +1210688 AC021237.1 chr8 109298598 109316513 +1210692 ENY2 chr8 109334324 109345954 +1210838 PKHD1L1 chr8 109362461 109537207 +1211059 EBAG9 chr8 109539711 109565996 +1211219 SYBU chr8 109573978 109691791 +1211752 AC079061.1 chr8 109644115 109648084 +1211756 KCNV1 chr8 109963636 109975771 +1211781 AC027451.1 chr8 109973943 109974781 +1211785 AC073023.1 chr8 110334743 110349607 +1211790 AC025366.1 chr8 110609241 110632394 +1211795 AP005357.1 chr8 110766863 110772759 +1211799 LINC01608 chr8 110899996 111040372 +1211974 LINC01609 chr8 111093263 111236203 +1212020 AC009930.1 chr8 111179193 111179872 +1212024 LINC02237 chr8 111376639 111757710 +1212063 AC022360.2 chr8 111699519 111700276 +1212067 CSMD3 chr8 112222928 113436939 +1212659 AC024996.1 chr8 112446575 112457993 +1212669 AC055788.2 chr8 113432224 113433129 +1212673 AC055788.1 chr8 113438334 113493281 +1212677 AC103993.1 chr8 113600310 113616958 +1212684 AC064802.1 chr8 114282067 114295839 +1212705 TRPS1 chr8 115408496 115809673 +1212868 AF178030.1 chr8 115509602 115511325 +1212872 LINC00536 chr8 115950511 116325062 +1212896 AC090994.1 chr8 116289622 116298954 +1212900 AC105177.1 chr8 116402543 116403757 +1212904 EIF3H chr8 116642130 116766925 +1213066 UTP23 chr8 116766505 116849463 +1213146 RAD21 chr8 116845935 116874866 +1213275 RAD21-AS1 chr8 116874424 116876868 +1213279 AARD chr8 116938207 116944487 +1213292 SLC30A8 chr8 116950273 117176714 +1213429 AC027419.2 chr8 117128455 117130299 +1213433 AC084114.1 chr8 117265272 117318701 +1213438 MED30 chr8 117520713 117540262 +1213469 EXT1 chr8 117794490 118111853 +1213537 SAMD12 chr8 118189455 118622112 +1213630 AC023590.1 chr8 118282139 118400605 +1213661 SAMD12-AS1 chr8 118620498 118906155 +1213702 TNFRSF11B chr8 118923557 118951885 +1213737 COLEC10 chr8 118995452 119108455 +1213763 AC107953.2 chr8 119062942 119068782 +1213767 MAL2 chr8 119165034 119245673 +1213822 MAL2-AS1 chr8 119214625 119246848 +1213851 AC021733.4 chr8 119350291 119416947 +1213858 CCN3 chr8 119416446 119424434 +1213877 AC021733.2 chr8 119419910 119462350 +1213883 ENPP2 chr8 119557086 119673453 +1214195 TAF2 chr8 119730774 119832841 +1214328 AP005717.2 chr8 119832875 119855509 +1214332 DSCC1 chr8 119833976 119855894 +1214359 AP005717.1 chr8 119867419 119874488 +1214367 DEPTOR chr8 119873717 120050918 +1214417 AC091563.1 chr8 120052180 120056201 +1214424 COL14A1 chr8 120059780 120373573 +1214881 MRPL13 chr8 120380761 120445402 +1214953 MTBP chr8 120445400 120542133 +1215062 SNTB1 chr8 120535745 120813273 +1215141 AC104958.1 chr8 120761253 120776832 +1215148 AC104958.2 chr8 120812219 120813359 +1215151 AC068413.1 chr8 120913065 121119754 +1215157 HAS2 chr8 121612116 121641440 +1215170 HAS2-AS1 chr8 121639293 121994185 +1215290 LINC02855 chr8 121668934 121697600 +1215304 AC037486.1 chr8 121954640 122127184 +1215309 SMILR chr8 122414332 122428551 +1215314 LINC01151 chr8 122485194 122733804 +1215362 AC108136.1 chr8 122485515 122489815 +1215368 AC100872.2 chr8 122700269 122703423 +1215372 AC016405.3 chr8 122779971 122780830 +1215375 AC016405.2 chr8 122780760 122781071 +1215378 ZHX2 chr8 122781655 122974510 +1215399 AC016405.1 chr8 122807746 122816517 +1215412 AC104316.2 chr8 122977026 122985629 +1215416 AC104316.1 chr8 123002560 123030751 +1215420 DERL1 chr8 123013170 123042302 +1215520 TBC1D31 chr8 123041968 123152153 +1215881 AC068228.3 chr8 123157729 123165173 +1215885 FAM83A chr8 123178960 123210079 +1215965 AC068228.1 chr8 123181638 123182788 +1215969 FAM83A-AS1 chr8 123196536 123202743 +1215986 C8orf76 chr8 123219967 123241377 +1216031 ZHX1 chr8 123248451 123275541 +1216092 ATAD2 chr8 123319850 123416350 +1216367 WDYHV1 chr8 123416726 123470028 +1216531 FBXO32 chr8 123497889 123541206 +1216598 AC090193.1 chr8 123563070 123568762 +1216602 AC135166.1 chr8 123614219 123667248 +1216618 KLHL38 chr8 123645527 123652950 +1216630 ANXA13 chr8 123680794 123737402 +1216711 FAM91A1 chr8 123768439 123815452 +1216907 FER1L6 chr8 123851987 124120061 +1216995 AC090753.1 chr8 123924759 123925933 +1216999 FER1L6-AS1 chr8 123984138 124040782 +1217007 AC100871.2 chr8 124036010 124040468 +1217011 FER1L6-AS2 chr8 124044395 124171522 +1217026 AC090921.1 chr8 124192671 124247398 +1217031 AC090192.2 chr8 124271667 124279580 +1217045 TMEM65 chr8 124306189 124372692 +1217065 TRMT12 chr8 124450820 124462150 +1217087 RNF139-AS1 chr8 124462485 124474582 +1217100 RNF139 chr8 124474738 124487914 +1217117 TATDN1 chr8 124488485 124539458 +1217494 AC090198.1 chr8 124488510 124491643 +1217498 NDUFB9 chr8 124539101 124580648 +1217575 MTSS1 chr8 124550790 124728429 +1217819 AC100858.3 chr8 124811042 124857516 +1217839 LINC00964 chr8 124823702 124962531 +1218269 AC100858.2 chr8 124936328 124943765 +1218278 AC100858.4 chr8 124940041 124941909 +1218281 ZNF572 chr8 124973295 124979389 +1218293 AC009908.1 chr8 124996985 124998198 +1218297 SQLE chr8 124998497 125022283 +1218382 WASHC5 chr8 125024260 125091819 +1218543 WASHC5-AS1 chr8 125040684 125044989 +1218547 NSMCE2 chr8 125091679 125367120 +1218718 AC084083.1 chr8 125348196 125351416 +1218722 TRIB1 chr8 125430358 125438403 +1218757 AC091114.1 chr8 125466939 125541373 +1218767 AC016074.2 chr8 125648327 126008930 +1218780 AC016074.1 chr8 125749055 125750241 +1218784 LINC00861 chr8 125859721 126292788 +1218839 AC024681.2 chr8 125998994 126001001 +1218843 AC087667.1 chr8 126325454 126329538 +1218856 AC084116.2 chr8 126474189 126492596 +1218861 AC084116.1 chr8 126497385 126500440 +1218869 AC084116.3 chr8 126506326 126522360 +1218878 LRATD2 chr8 126552443 126558478 +1218898 PCAT1 chr8 126556323 127419050 +1219054 AC024382.1 chr8 126766196 126846981 +1219064 CASC19 chr8 127072694 127227541 +1219616 PRNCR1 chr8 127079874 127092600 +1219619 AC018714.2 chr8 127253213 127257630 +1219623 CASC8 chr8 127289817 127482139 +1219644 POU5F1B chr8 127322183 127420066 +1219669 CCAT2 chr8 127400399 127402150 +1219672 AC104370.1 chr8 127578473 127636867 +1219683 AC108925.1 chr8 127663280 127670990 +1219690 CASC11 chr8 127686343 127738987 +1219711 MYC chr8 127735434 127742951 +1219820 PVT1 chr8 127794526 128187101 +1220969 AC100822.1 chr8 128323131 128388636 +1220979 LINC00824 chr8 128405269 128564679 +1221010 CCDC26 chr8 128634199 129683770 +1221412 AC103833.2 chr8 129241228 129242469 +1221416 AC011257.1 chr8 129415949 129445852 +1221421 AC103718.1 chr8 129685401 129723023 +1221431 GSDMC chr8 129748196 129786624 +1221508 AC022973.5 chr8 129832301 129844504 +1221513 FAM49B chr8 129839593 130017129 +1222062 AC022973.4 chr8 129890465 129901758 +1222066 AC022973.3 chr8 129939844 129951056 +1222084 AC131568.1 chr8 129953729 129964634 +1222088 ASAP1 chr8 130052104 130443674 +1222471 ASAP1-IT2 chr8 130082738 130084768 +1222474 AC009682.1 chr8 130248287 130251051 +1222478 AC139019.1 chr8 130358787 130362461 +1222482 AC090987.1 chr8 130595299 130655712 +1222487 ADCY8 chr8 130780301 131040909 +1222580 AC103726.1 chr8 130892070 130892785 +1222584 AC103726.2 chr8 130935409 130949665 +1222589 AC087341.1 chr8 131129761 131144948 +1222594 AC104257.1 chr8 131308545 131317632 +1222612 EFR3A chr8 131904093 132013642 +1222809 OC90 chr8 132024216 132059382 +1222843 HHLA1 chr8 132061486 132111159 +1222968 KCNQ3 chr8 132120859 132481095 +1223209 HPYR1 chr8 132507962 132565246 +1223219 LRRC6 chr8 132570416 132675592 +1223440 TMEM71 chr8 132685007 132760712 +1223585 AF228727.1 chr8 132702812 132722283 +1223589 PHF20L1 chr8 132775358 132848807 +1223995 AF230666.2 chr8 132826179 132826903 +1223998 AF230666.1 chr8 132838117 132844298 +1224006 TG chr8 132866958 133134903 +1224397 SLA chr8 133036728 133102912 +1224646 AF305872.2 chr8 133054959 133057767 +1224649 CCN4 chr8 133191039 133231690 +1224709 NDRG1 chr8 133237171 133302022 +1225180 ST3GAL1 chr8 133454848 133571940 +1225358 AC103706.1 chr8 133573183 133573861 +1225361 AC133634.1 chr8 133771409 133814537 +1225366 AC090821.2 chr8 133775551 133777352 +1225371 AC110741.1 chr8 133886496 133902407 +1225377 AC105180.2 chr8 134190383 134390487 +1225382 AC105180.1 chr8 134211865 134320447 +1225386 ZFAT chr8 134477788 134713049 +1225758 ZFAT-AS1 chr8 134598071 134600689 +1225762 AC087045.2 chr8 134722947 134723949 +1225765 AC083843.3 chr8 134792020 134798272 +1225768 AC083843.2 chr8 134832747 134834482 +1225772 AC083843.1 chr8 134838069 134842637 +1225777 AC103764.1 chr8 134849935 134881899 +1225782 LINC01591 chr8 135234131 135299719 +1225813 AC040914.1 chr8 135455865 135456952 +1225818 KHDRBS3 chr8 135457456 135656722 +1225947 LINC02055 chr8 135859369 137092183 +1226137 AC103955.1 chr8 135977329 135980588 +1226141 AC023781.1 chr8 136237236 136295232 +1226152 AC105213.1 chr8 137524755 137645564 +1226158 AC046195.1 chr8 137809444 138083657 +1226173 AC046195.2 chr8 137852204 138019873 +1226190 AC079015.1 chr8 138063268 138073240 +1226194 FAM135B chr8 138130023 138497261 +1226389 COL22A1 chr8 138588235 138914041 +1226699 AC027541.1 chr8 139096305 139102830 +1226704 AC100807.2 chr8 139114193 139127953 +1226709 AC087354.1 chr8 139460062 139463016 +1226713 KCNK9 chr8 139600838 139704109 +1226816 TRAPPC9 chr8 139727725 140458579 +1227088 AC021744.1 chr8 139911238 139916620 +1227096 PEG13 chr8 140094894 140100543 +1227099 AC107375.1 chr8 140505813 140508043 +1227102 CHRAC1 chr8 140511311 140517154 +1227142 AGO2 chr8 140520156 140635633 +1227299 ERICD chr8 140636281 140638283 +1227302 PTK2 chr8 140657900 141002216 +1228509 AC100860.1 chr8 141055290 141060596 +1228519 DENND3 chr8 141117278 141195808 +1228859 AC040970.1 chr8 141124717 141130064 +1228880 SLC45A4 chr8 141207166 141308305 +1228964 AC011676.1 chr8 141252286 141253292 +1228968 AC011676.2 chr8 141254565 141256817 +1228972 AC011676.3 chr8 141278228 141292862 +1228976 AC011676.4 chr8 141326130 141327137 +1228980 LINC01300 chr8 141340505 141344621 +1228990 AC100803.3 chr8 141353403 141355365 +1228993 GPR20 chr8 141356470 141367286 +1229003 AC100803.2 chr8 141389939 141392574 +1229007 PTP4A3 chr8 141391993 141432454 +1229092 AC100803.4 chr8 141434545 141437954 +1229097 AC138647.2 chr8 141507333 141509785 +1229101 AC138647.1 chr8 141514638 141518737 +1229119 AC025839.1 chr8 141581684 141585260 +1229124 AC104417.2 chr8 142089827 142091619 +1229127 AC103758.1 chr8 142111414 142185527 +1229131 LINC00051 chr8 142198356 142209003 +1229136 TSNARE1 chr8 142212080 142403182 +1229321 AC134682.1 chr8 142403652 142407028 +1229324 ADGRB1 chr8 142449430 142545009 +1229611 ARC chr8 142611049 142614479 +1229626 AP006547.1 chr8 142620373 142621064 +1229629 AC108002.2 chr8 142638596 142640648 +1229633 JRK chr8 142657460 142681968 +1229704 PSCA chr8 142670308 142682725 +1229732 LY6K chr8 142700111 142705127 +1229778 LNCOC1 chr8 142701857 142727016 +1229821 THEM6 chr8 142727223 142736927 +1229843 AC108002.1 chr8 142727283 142727690 +1229847 SLURP1 chr8 142740949 142742406 +1229859 LYPD2 chr8 142750150 142752532 +1229871 AC083841.1 chr8 142763116 142766427 +1229875 SLURP2 chr8 142764338 142769828 +1229896 LYNX1 chr8 142771197 142777810 +1229974 LY6D chr8 142784882 142786539 +1229995 AC083841.2 chr8 142785374 142812120 +1230000 AC083841.3 chr8 142834138 142834940 +1230007 GML chr8 142834247 142916506 +1230034 CYP11B1 chr8 142872356 142879846 +1230125 CYP11B2 chr8 142910559 142917843 +1230149 LY6E-DT chr8 142981738 143018437 +1230167 LY6E chr8 143017982 143023832 +1230361 C8orf31 chr8 143039209 143060684 +1230417 LY6L chr8 143080457 143083001 +1230431 LY6H chr8 143157914 143160711 +1230494 GPIHBP1 chr8 143213218 143217170 +1230508 ZFP41 chr8 143246821 143262705 +1230543 GLI4 chr8 143267433 143276931 +1230633 MINCR chr8 143280161 143281690 +1230654 ZNF696 chr8 143289676 143299952 +1230719 AC138696.2 chr8 143290399 143290621 +1230722 TOP1MT chr8 143304384 143359979 +1231056 RHPN1-AS1 chr8 143366631 143368548 +1231059 RHPN1 chr8 143368876 143384221 +1231118 AC105118.1 chr8 143412749 143417054 +1231123 MAFA-AS1 chr8 143417679 143419150 +1231127 MAFA chr8 143419182 143430732 +1231138 ZC3H3 chr8 143437659 143541447 +1231175 AC067930.8 chr8 143541648 143545128 +1231179 AC067930.3 chr8 143541973 143549729 +1231183 GSDMD chr8 143553207 143563062 +1231391 MROH6 chr8 143566192 143572772 +1231519 AC067930.4 chr8 143573490 143577397 +1231526 NAPRT chr8 143574785 143578649 +1231733 AC067930.1 chr8 143579636 143580670 +1231737 EEF1D chr8 143579697 143599541 +1232453 TIGD5 chr8 143597831 143603224 +1232461 PYCR3 chr8 143603210 143609773 +1232566 TSTA3 chr8 143612618 143618048 +1232742 AC067930.2 chr8 143632071 143633756 +1232746 ZNF623 chr8 143636013 143656418 +1232772 ZNF707 chr8 143684452 143713898 +1233094 AC105219.1 chr8 143696154 143698413 +1233098 CCDC166 chr8 143706694 143708109 +1233107 AC105219.3 chr8 143709007 143713584 +1233113 MAPK15 chr8 143716340 143722458 +1233214 AC105219.2 chr8 143718246 143718891 +1233218 FAM83H chr8 143723933 143738234 +1233255 IQANK1 chr8 143734140 143790644 +1233315 AC105219.4 chr8 143758153 143771870 +1233320 SCRIB chr8 143790920 143815773 +1233611 PUF60 chr8 143816344 143829352 +1233942 AC234917.3 chr8 143829518 143832861 +1233946 AC234917.1 chr8 143833270 143834063 +1233950 NRBP2 chr8 143833583 143840973 +1234110 AC234917.2 chr8 143838779 143840256 +1234114 EPPK1 chr8 143857324 143878464 +1234131 AC109322.2 chr8 143888500 143901588 +1234138 PLEC chr8 143915147 143976734 +1234921 PARP10 chr8 143977153 144012772 +1235205 GRINA chr8 143990056 143993415 +1235310 SPATC1 chr8 144012280 144047114 +1235339 OPLAH chr8 144051266 144063965 +1235419 AC109322.1 chr8 144078002 144079265 +1235422 EXOSC4 chr8 144078648 144080648 +1235452 GPAA1 chr8 144082590 144086216 +1235652 CYC1 chr8 144095039 144097525 +1235686 SHARPIN chr8 144098633 144108124 +1235773 MAF1 chr8 144104461 144107611 +1235866 WDR97 chr8 144107726 144118328 +1236010 HGH1 chr8 144137774 144140851 +1236069 MROH1 chr8 144148016 144261940 +1236516 BOP1 chr8 144262045 144291438 +1236582 SCX chr8 144266453 144268481 +1236592 HSF1 chr8 144291591 144314720 +1236760 DGAT1 chr8 144314584 144326910 +1236869 AC233992.1 chr8 144314590 144315138 +1236873 SCRT1 chr8 144330565 144336482 +1236883 TMEM249 chr8 144352219 144354914 +1236913 SLC52A2 chr8 144354135 144361272 +1237058 FBXL6 chr8 144355431 144359376 +1237141 ADCK5 chr8 144373101 144393242 +1237272 CPSF1 chr8 144393229 144409335 +1237522 AC233992.3 chr8 144409492 144409976 +1237525 SLC39A4 chr8 144409742 144416895 +1237621 VPS28 chr8 144423601 144428563 +1237850 TONSL chr8 144428775 144444440 +1237971 TONSL-AS1 chr8 144437675 144439971 +1237977 CYHR1 chr8 144449582 144465677 +1238082 AC084125.1 chr8 144463817 144465101 +1238086 KIFC2 chr8 144466043 144474202 +1238247 FOXH1 chr8 144473412 144475849 +1238263 PPP1R16A chr8 144477969 144502121 +1238366 AC084125.2 chr8 144495458 144505444 +1238386 GPT chr8 144502973 144507174 +1238468 MFSD3 chr8 144509070 144511213 +1238494 RECQL4 chr8 144511288 144517845 +1238678 AC084125.4 chr8 144512567 144513672 +1238682 LRRC14 chr8 144517992 144525172 +1238750 LRRC24 chr8 144522388 144527033 +1238781 C8orf82 chr8 144525733 144529132 +1238829 ARHGAP39 chr8 144529179 144605816 +1238886 AC084125.3 chr8 144584040 144586488 +1238890 AF186192.1 chr8 144698614 144699185 +1238893 AF186192.3 chr8 144713899 144714845 +1238896 ZNF251 chr8 144720907 144756417 +1238930 ZNF34 chr8 144773114 144787345 +1238994 RPL8 chr8 144789765 144792587 +1239144 ZNF517 chr8 144798876 144811169 +1239235 ZNF7 chr8 144827464 144847509 +1239418 COMMD5 chr8 144841042 144853736 +1239476 AF235103.3 chr8 144854875 144869489 +1239480 ZNF250 chr8 144876497 144902168 +1239628 ZNF16 chr8 144930358 144950888 +1239696 AF235103.1 chr8 144992914 144994837 +1239700 ZNF252P-AS1 chr8 145002811 145006046 +1239703 C8orf33 chr8 145052465 145066685 +1239811 WASHC1 chr9 14475 73865 +1239850 AL928970.1 chr9 27657 30891 +1239854 FAM138C chr9 34394 37269 +1239866 PGM5P3-AS1 chr9 72670 89850 +1239894 AL449043.1 chr9 100804 110138 +1239911 LINC01388 chr9 112713 113754 +1239915 FOXD4 chr9 116231 118204 +1239923 CBWD1 chr9 121038 179147 +1240471 AL158832.2 chr9 197065 209554 +1240476 DOCK8-AS1 chr9 212824 215893 +1240481 DOCK8 chr9 214854 465259 +1241105 AL158832.1 chr9 267966 273002 +1241109 AL161725.1 chr9 452492 492248 +1241183 KANK1 chr9 470291 746106 +1241366 AL161725.2 chr9 487774 495610 +1241370 AL392089.1 chr9 547135 549967 +1241386 AL136979.1 chr9 673478 685555 +1241394 DMRT1 chr9 841690 969090 +1241429 DMRT3 chr9 976655 991732 +1241444 AL358976.2 chr9 1041655 1042608 +1241447 LINC01230 chr9 1045625 1048641 +1241450 DMRT2 chr9 1049858 1057552 +1241553 AL358053.1 chr9 1540321 1550103 +1241557 SMARCA2 chr9 1980290 2193624 +1242736 AL359076.1 chr9 2041900 2046023 +1242740 VLDLR-AS1 chr9 2421597 2643359 +1242877 AL353614.1 chr9 2541097 2541635 +1242881 VLDLR chr9 2621787 2660056 +1242980 AL450467.1 chr9 2652856 2654371 +1242984 KCNV2 chr9 2717510 2730037 +1242994 PUM3 chr9 2720469 2844095 +1243053 LINC01231 chr9 3181342 3200445 +1243078 RFX3 chr9 3218297 3526004 +1243312 RFX3-AS1 chr9 3526723 3691814 +1243329 AL354977.2 chr9 3630947 3648390 +1243339 AL354977.1 chr9 3684076 3689626 +1243343 GLIS3 chr9 3824127 4348392 +1243523 AL137071.1 chr9 3875584 3878809 +1243527 GLIS3-AS1 chr9 3898642 3901248 +1243531 AL359095.1 chr9 4070906 4071884 +1243535 AL162419.1 chr9 4299390 4306046 +1243539 SLC1A1 chr9 4490468 4587469 +1243584 SPATA6L chr9 4553386 4666674 +1243818 PLPP6 chr9 4662294 4665262 +1243826 CDC37L1-DT chr9 4676600 4679502 +1243833 CDC37L1 chr9 4679559 4708399 +1243875 AK3 chr9 4709556 4742043 +1243934 AL353151.2 chr9 4741741 4759639 +1243941 RCL1 chr9 4792944 4885917 +1244061 AL158147.1 chr9 4850299 4850373 +1244064 JAK2 chr9 4984390 5128183 +1244167 IGHEP2 chr9 5113549 5114804 +1244170 INSL6 chr9 5123880 5185647 +1244198 INSL4 chr9 5231419 5235304 +1244208 RLN2 chr9 5299864 5304716 +1244227 RLN1 chr9 5334930 5339876 +1244240 AL135786.2 chr9 5351796 5352410 +1244243 PLGRKT chr9 5357971 5437925 +1244276 CD274 chr9 5450503 5470566 +1244327 AL162253.2 chr9 5457477 5629748 +1244335 PDCD1LG2 chr9 5510531 5571282 +1244355 AL162253.1 chr9 5584490 5588994 +1244359 RIC1 chr9 5629025 5776557 +1244615 AL136980.1 chr9 5719021 5720244 +1244619 ERMP1 chr9 5765076 5833117 +1244783 KIAA2026 chr9 5881596 6008482 +1244862 MLANA chr9 5890889 5910606 +1244918 RANBP6 chr9 6011025 6015625 +1244942 AL162384.1 chr9 6047360 6066714 +1244946 IL33 chr9 6215786 6257983 +1245017 TPD52L3 chr9 6328375 6331900 +1245043 UHRF2 chr9 6413151 6507054 +1245193 AL133480.1 chr9 6415145 6449558 +1245197 GLDC chr9 6532464 6645783 +1245532 AL162411.1 chr9 6645956 6670635 +1245537 LINC02851 chr9 6704270 6707780 +1245546 AL354707.1 chr9 6716157 6727438 +1245572 KDM4C chr9 6720863 7175648 +1245886 AL513412.1 chr9 6902670 6978859 +1245892 AL161443.1 chr9 7177577 7203458 +1245896 AL157703.1 chr9 7304551 7343556 +1245901 AL354694.1 chr9 7786105 7786688 +1245904 DMAC1 chr9 7796500 7888380 +1245921 AL135923.2 chr9 7914514 7961224 +1245937 AL135923.1 chr9 7930827 7935137 +1245942 PTPRD chr9 8314246 10612723 +1246684 AL583805.2 chr9 8700595 8701552 +1246688 PTPRD-AS1 chr9 8858127 8864772 +1246701 AL596451.1 chr9 8936079 8963077 +1246707 AL513422.1 chr9 9799423 9803784 +1246712 PTPRD-AS2 chr9 10613202 10620420 +1246717 AL135790.1 chr9 10631750 10632203 +1246721 AL162413.1 chr9 10948372 10948481 +1246724 AL451129.1 chr9 11275314 11276314 +1246728 AL355672.1 chr9 11313397 11436244 +1246734 AL353595.1 chr9 11618530 12058227 +1246742 AL589678.1 chr9 12098660 12159148 +1246753 TYRP1 chr9 12685439 12710285 +1246811 LURAP1L-AS1 chr9 12698554 12814377 +1246826 LURAP1L chr9 12775020 12823060 +1246839 AL161449.2 chr9 12958503 13034326 +1246853 MPDZ chr9 13105704 13279590 +1247758 AL162386.2 chr9 13274510 13279187 +1247763 AL583785.1 chr9 13386130 13836571 +1247782 LINC01235 chr9 13406380 13488125 +1247812 LINC00583 chr9 13927971 13945610 +1247817 AL360089.1 chr9 14025971 14030115 +1247822 NFIB chr9 14081843 14398983 +1248278 AL136366.1 chr9 14317073 14358490 +1248288 AL137017.1 chr9 14395791 14472407 +1248294 AL159169.3 chr9 14586766 14587326 +1248297 AL159169.2 chr9 14588797 14590065 +1248300 ZDHHC21 chr9 14611071 14693471 +1248332 CER1 chr9 14719724 14722733 +1248342 FREM1 chr9 14734666 14910995 +1248649 AL512643.2 chr9 14779930 14784117 +1248653 AL512643.1 chr9 14790635 14791158 +1248656 TTC39B chr9 15163622 15307360 +1248912 SNAPC3 chr9 15422704 15465953 +1249049 PSIP1 chr9 15464066 15510995 +1249234 CCDC171 chr9 15553043 16061663 +1249365 C9orf92 chr9 16203935 16410990 +1249394 BNC2 chr9 16409503 16870843 +1249587 AL449983.1 chr9 16473188 16476237 +1249591 AL450003.1 chr9 16625676 16626390 +1249595 BNC2-AS1 chr9 16726814 16727524 +1249600 AL162725.2 chr9 16917511 17114122 +1249619 AL358117.1 chr9 16982723 16983459 +1249623 CNTLN chr9 17134982 17503923 +1249710 SH3GL2 chr9 17579066 17797124 +1249737 ADAMTSL1 chr9 17906563 18910950 +1250030 AL442638.1 chr9 18360597 18362220 +1250034 SAXO1 chr9 18858906 19049358 +1250105 RRAGA chr9 19049427 19051025 +1250113 HAUS6 chr9 19053141 19102904 +1250197 PLIN2 chr9 19108375 19149290 +1250276 DENND4C chr9 19230435 19373545 +1250575 AL161909.2 chr9 19291337 19292576 +1250579 AL391834.1 chr9 19371386 19371945 +1250582 AL391834.2 chr9 19375451 19375996 +1250585 RPS6 chr9 19375715 19380236 +1250647 AL391834.3 chr9 19386927 19408532 +1250651 ACER2 chr9 19409009 19452505 +1250669 AL158206.1 chr9 19453209 19455173 +1250672 SLC24A2 chr9 19507452 19786928 +1250721 AL158077.2 chr9 19789179 19894856 +1250725 AL591222.1 chr9 19926094 19929937 +1250728 MLLT3 chr9 20341669 20622518 +1250861 FOCAD chr9 20658309 20995955 +1251220 FOCAD-AS1 chr9 20683304 20684688 +1251227 HACD4 chr9 20999509 21031640 +1251251 IFNB1 chr9 21077104 21077942 +1251259 IFNW1 chr9 21140214 21142145 +1251267 IFNA21 chr9 21165637 21166660 +1251275 IFNA4 chr9 21186694 21187671 +1251283 IFNA7 chr9 21201469 21202205 +1251291 IFNA10 chr9 21206181 21207143 +1251299 IFNA16 chr9 21216373 21217311 +1251307 IFNA17 chr9 21227243 21228222 +1251315 IFNA14 chr9 21239002 21240005 +1251323 IFNA5 chr9 21304326 21305312 +1251331 KLHL9 chr9 21329665 21335404 +1251339 IFNA6 chr9 21349835 21351378 +1251353 IFNA13 chr9 21367424 21368962 +1251368 IFNA2 chr9 21384255 21385398 +1251376 AL353732.1 chr9 21394888 21396346 +1251379 IFNA8 chr9 21409117 21410185 +1251387 MIR31HG chr9 21410969 21559900 +1251410 IFNA1 chr9 21440439 21441316 +1251418 IFNE chr9 21480839 21482313 +1251426 MTAP chr9 21802636 21937651 +1251577 AL359922.2 chr9 21858910 21861926 +1251580 CDKN2A-DT chr9 21966929 21967751 +1251583 CDKN2A chr9 21967753 21995301 +1251714 CDKN2B-AS1 chr9 21994139 22128103 +1251920 AL449423.1 chr9 21995482 21996013 +1251924 CDKN2B chr9 22002903 22009305 +1251945 AL157937.1 chr9 22203990 22214672 +1251951 DMRTA1 chr9 22446824 22455740 +1251961 LINC01239 chr9 22646200 22824213 +1251976 AL391117.1 chr9 22703516 23438700 +1251992 AC017067.1 chr9 22767175 22768316 +1251996 AL357614.1 chr9 23291544 23293923 +1252000 AL445623.2 chr9 23500691 23672387 +1252030 AL445623.1 chr9 23671788 23672399 +1252034 ELAVL2 chr9 23690104 23826337 +1252157 AL161628.1 chr9 23826491 23828877 +1252161 AL365204.1 chr9 23829670 23849914 +1252168 AL365204.2 chr9 23894990 23898054 +1252172 AL513317.1 chr9 24069731 24088051 +1252177 IZUMO3 chr9 24542952 24545946 +1252225 AL353811.1 chr9 24545938 24592104 +1252242 AL353730.1 chr9 25579657 25584272 +1252246 TUSC1 chr9 25676389 25678440 +1252254 LINC01241 chr9 25780032 25844585 +1252300 AL353753.1 chr9 26066675 26118408 +1252309 AL451137.2 chr9 26746953 26786874 +1252315 AL356133.2 chr9 26801733 26805862 +1252319 CAAP1 chr9 26840685 26892803 +1252411 PLAA chr9 26903372 26947242 +1252522 IFT74 chr9 26947039 27062930 +1252809 IFT74-AS1 chr9 26955780 26956295 +1252813 LRRC19 chr9 26993136 27005672 +1252833 AL355432.1 chr9 27102630 27104728 +1252837 TEK chr9 27109141 27230174 +1253059 EQTN chr9 27284654 27297150 +1253117 MOB3B chr9 27325209 27529814 +1253134 AL163192.1 chr9 27391734 27397563 +1253140 AL451123.2 chr9 27495857 27498251 +1253144 IFNK chr9 27524314 27526498 +1253154 AL451123.1 chr9 27529085 27543902 +1253160 C9orf72 chr9 27535640 27573866 +1253343 AL360014.1 chr9 27829276 27844481 +1253347 AL353746.1 chr9 27937617 27944497 +1253350 LINGO2 chr9 27948078 28670286 +1253403 AL445526.1 chr9 28539735 28566733 +1253408 AL162388.2 chr9 29214322 29229229 +1253412 LINC01242 chr9 30388935 30575012 +1253418 LINC01243 chr9 31371611 31381490 +1253422 ACO1 chr9 32384603 32454769 +1253568 DDX58 chr9 32455302 32526208 +1253649 TOPORS chr9 32540544 32552586 +1253670 SMIM27 chr9 32551144 32568621 +1253725 NDUFB6 chr9 32553001 32573184 +1253761 TAF1L chr9 32629454 32635669 +1253769 AL589642.1 chr9 32633454 32648685 +1253773 AL589642.2 chr9 32643103 32645026 +1253777 TMEM215 chr9 32783540 32789201 +1253787 AL157884.2 chr9 32840598 32841762 +1253791 APTX chr9 32886601 33025130 +1254662 DNAJA1 chr9 33025273 33039907 +1254697 SMU1 chr9 33041765 33076674 +1254727 B4GALT1 chr9 33104082 33167356 +1254756 B4GALT1-AS1 chr9 33166948 33182865 +1254771 SPINK4 chr9 33218365 33248567 +1254800 BAG1 chr9 33247820 33264720 +1254949 CHMP5 chr9 33264879 33282070 +1254993 NFX1 chr9 33290512 33371157 +1255119 AQP7 chr9 33383179 33402682 +1255367 AL356218.2 chr9 33401478 33410553 +1255400 AQP3 chr9 33441156 33447596 +1255471 NOL6 chr9 33461353 33473930 +1255648 AL139008.2 chr9 33512959 33514773 +1255653 ANKRD18B chr9 33524394 33573009 +1255744 CYP4F26P chr9 33580695 33607874 +1255781 TRBV20OR9-2 chr9 33617762 33618506 +1255789 TRBV21OR9-2 chr9 33629121 33629586 +1255793 TRBV22OR9-2 chr9 33634111 33634246 +1255796 TRBV23OR9-2 chr9 33638035 33638494 +1255800 TRBV24OR9-2 chr9 33649047 33649614 +1255804 TRBV25OR9-2 chr9 33662166 33662663 +1255808 PTENP1-AS chr9 33676785 33688011 +1255822 TRBV26OR9-2 chr9 33695767 33696059 +1255825 AL356489.2 chr9 33697459 33700986 +1255828 AL356489.3 chr9 33706679 33710715 +1255833 AL356489.1 chr9 33719690 33722555 +1255837 AL356489.4 chr9 33730345 33734040 +1255844 LINC01251 chr9 33732975 33738416 +1255851 PRSS3 chr9 33750466 33799231 +1255937 UBE2R2-AS1 chr9 33775183 33818795 +1255954 TRBV29OR9-2 chr9 33786221 33786828 +1255958 UBE2R2 chr9 33817160 33920399 +1255974 UBAP2 chr9 33921693 34048949 +1256280 AL354989.1 chr9 34084332 34096225 +1256285 DCAF12 chr9 34086387 34127399 +1256342 UBAP1 chr9 34179005 34252523 +1256430 KIF24 chr9 34252381 34311371 +1256483 NUDT2 chr9 34329506 34343711 +1256538 MYORG chr9 34366666 34376898 +1256553 C9orf24 chr9 34379019 34397810 +1256637 FAM219A chr9 34398184 34458570 +1256804 DNAI1 chr9 34457414 34520988 +1256965 ENHO chr9 34521043 34522990 +1256975 AL160270.1 chr9 34521527 34524241 +1256980 CNTFR chr9 34551432 34590140 +1257070 CNTFR-AS1 chr9 34568012 34583072 +1257115 RPP25L chr9 34610486 34612104 +1257134 DCTN3 chr9 34613545 34620523 +1257259 ARID3C chr9 34621379 34628086 +1257279 SIGMAR1 chr9 34634722 34637809 +1257338 GALT chr9 34638133 34651035 +1257612 IL11RA chr9 34650702 34661892 +1257873 CCL27 chr9 34661880 34664048 +1257889 AL162231.1 chr9 34664163 34666112 +1257939 AL162231.2 chr9 34665607 34774466 +1257951 CCL19 chr9 34689570 34691276 +1257979 CCL21 chr9 34709005 34710136 +1258004 FAM205A chr9 34723053 34729488 +1258018 AL589645.1 chr9 34810020 34895175 +1258023 FAM205C chr9 34889066 34895764 +1258068 PHF24 chr9 34957608 34982544 +1258105 DNAJB5-DT chr9 34985410 34989379 +1258109 DNAJB5 chr9 34989641 34998900 +1258219 AL355377.3 chr9 35012963 35016076 +1258223 AL355377.4 chr9 35023840 35025402 +1258227 C9orf131 chr9 35041095 35045986 +1258287 VCP chr9 35056064 35072627 +1258383 FANCG chr9 35073835 35080016 +1258479 PIGO chr9 35088688 35096601 +1258590 AL353795.2 chr9 35096378 35098141 +1258594 STOML2 chr9 35099776 35103195 +1258683 FAM214B chr9 35104112 35116341 +1258851 UNC13B chr9 35161992 35405338 +1259580 RUSC2 chr9 35490111 35561898 +1259642 AL133476.1 chr9 35491133 35491969 +1259646 FAM166B chr9 35561831 35563899 +1259729 TESK1 chr9 35605262 35610041 +1259805 CD72 chr9 35609533 35646810 +1259937 AL357874.2 chr9 35642514 35643517 +1259941 AL357874.1 chr9 35646270 35647099 +1259945 SIT1 chr9 35649295 35650950 +1259985 RMRP chr9 35657751 35658018 +1259988 CCDC107 chr9 35658290 35661511 +1260077 ARHGEF39 chr9 35658875 35675866 +1260168 CA9 chr9 35673918 35681159 +1260230 TPM2 chr9 35681992 35690056 +1260372 TLN1 chr9 35696948 35732195 +1260529 CREB3 chr9 35732598 35736999 +1260562 GBA2 chr9 35736866 35749228 +1260679 RGP1 chr9 35749287 35758585 +1260713 MSMP chr9 35752990 35756613 +1260729 AL133410.2 chr9 35756712 35757940 +1260733 AL133410.1 chr9 35772163 35790432 +1260751 NPR2 chr9 35792154 35809732 +1260870 SPAG8 chr9 35808045 35812272 +1261033 HINT2 chr9 35812960 35815354 +1261078 TMEM8B chr9 35814451 35865518 +1261274 FAM221B chr9 35816391 35828747 +1261335 OR13J1 chr9 35869263 35870601 +1261343 HRCT1 chr9 35906202 35907136 +1261351 SPAAR chr9 35909490 35937153 +1261396 AL135841.1 chr9 35922159 35925554 +1261400 OR2S2 chr9 35957108 35958154 +1261408 RECK chr9 36036913 36124455 +1261478 GLIPR2 chr9 36136536 36163913 +1261534 CCIN chr9 36169388 36171334 +1261542 CLTA chr9 36190856 36304781 +1261705 GNE chr9 36214441 36277056 +1261874 RNF38 chr9 36336396 36487548 +1262092 MELK chr9 36572862 36677683 +1262503 AL450267.2 chr9 36764896 36830456 +1262525 PAX5 chr9 36833269 37034268 +1262864 AL450267.1 chr9 36856555 36861375 +1262868 AL161781.2 chr9 37002697 37008040 +1262872 LINC01400 chr9 37073531 37075792 +1262876 AL512604.3 chr9 37078813 37079776 +1262879 EBLN3P chr9 37079645 37090928 +1262952 AL512604.2 chr9 37112548 37120446 +1262963 ZCCHC7 chr9 37120539 37358149 +1263069 LINC01627 chr9 37383178 37384434 +1263073 GRHPR chr9 37422666 37436990 +1263182 ZBTB5 chr9 37438102 37465450 +1263192 POLR1E chr9 37485948 37503697 +1263280 AL513165.1 chr9 37509150 37510299 +1263284 FBXO10 chr9 37510892 37576380 +1263355 TOMM5 chr9 37582646 37592604 +1263403 FRMPD1 chr9 37650954 37746904 +1263487 TRMT10B chr9 37753803 37778972 +1263643 EXOSC3 chr9 37766978 37801437 +1263702 DCAF10 chr9 37800554 37867666 +1263754 SLC25A51 chr9 37879400 37904353 +1263782 SHB chr9 37915898 38069227 +1263800 AL135785.1 chr9 38360427 38376430 +1263806 ALDH1B1 chr9 38392702 38398661 +1263825 IGFBPL1 chr9 38406528 38424454 +1263841 ANKRD18A chr9 38571358 38620596 +1263903 FAM201A chr9 38620474 38624990 +1263919 AL591543.1 chr9 38650215 38662717 +1263926 FAM240B chr9 38694263 38720428 +1263949 AL845311.1 chr9 38804007 38851916 +1263954 AL953883.1 chr9 38949734 38998503 +1263960 CNTNAP3 chr9 39072767 39288315 +1264204 SPATA31A1 chr9 39355669 39361962 +1264234 FAM74A1 chr9 39371065 39376916 +1264240 BX005214.1 chr9 39384506 39405305 +1264245 BX005214.2 chr9 39395737 39397406 +1264249 GLIDR chr9 39748514 39810097 +1264304 BX664615.2 chr9 39816599 39874562 +1264316 AL773545.1 chr9 40130921 40153147 +1264321 ANKRD20A2 chr9 40223285 40266392 +1264375 BX664727.3 chr9 40223402 40329221 +1264458 BMS1P14 chr9 40505399 40566281 +1264462 FP325318.1 chr9 40611252 40622155 +1264469 IGKV1OR9-2 chr9 40641841 40642117 +1264472 AL353626.1 chr9 40767870 40806344 +1264482 BX255923.1 chr9 41073710 41076392 +1264489 BX255923.2 chr9 41100793 41119909 +1264534 FOXD4L6 chr9 41126430 41128463 +1264542 CBWD6 chr9 41131306 41199261 +1264906 AL845472.1 chr9 41276280 41282846 +1264911 AL354718.2 chr9 41310816 41332962 +1264916 AL591926.2 chr9 41651658 41654594 +1264921 FAM242F chr9 41657708 41699072 +1264937 AL162731.1 chr9 41760088 41764175 +1264944 CNTNAP3B chr9 41890314 42129510 +1265275 SPATA31A6 chr9 42183659 42189887 +1265293 FAM74A7 chr9 42199000 42204988 +1265297 AL445584.2 chr9 42231811 42354454 +1265303 BX088651.4 chr9 42566679 42569353 +1265311 BX088651.2 chr9 42579414 42586534 +1265316 BX664718.1 chr9 42707800 42714539 +1265321 SPATA31A5 chr9 60914374 60920650 +1265335 AL590491.2 chr9 60943311 60964196 +1265349 SPATA31A7 chr9 61190003 61196280 +1265396 BX005040.3 chr9 61194211 61203446 +1265400 BX005040.1 chr9 61229913 61231863 +1265404 CNTNAP3C chr9 61330717 61453030 +1265426 FAM242D chr9 61615835 61627683 +1265432 AL935212.1 chr9 61659733 61662690 +1265440 FAM27C chr9 61854148 62096920 +1265571 AL391987.2 chr9 61861625 61863200 +1265581 AL391987.1 chr9 61861848 61862567 +1265591 AL391987.4 chr9 61865755 61866965 +1265595 AL391987.3 chr9 61868727 61887084 +1265599 FAM242E chr9 61898805 61911022 +1265611 AL590399.3 chr9 62349941 62351536 +1265619 AL590399.1 chr9 62374128 62376836 +1265633 AL590399.5 chr9 62387171 62394004 +1265638 LINC01189 chr9 62452451 62522018 +1265652 BX005266.2 chr9 62532337 62534724 +1265664 LINC01410 chr9 62801461 62813486 +1265703 AL512625.3 chr9 62801534 62802699 +1265707 AL512625.2 chr9 62837139 62838302 +1265710 LERFS chr9 62856999 62898095 +1265805 AL512625.1 chr9 62897368 62900104 +1265826 AL772155.1 chr9 63728877 63744910 +1265831 CR786580.1 chr9 63802144 63814159 +1265842 CR769776.3 chr9 64343044 64362584 +1265852 ANKRD20A4 chr9 64369394 64413142 +1265906 IGKV1OR-2 chr9 64765054 64765535 +1265910 IGKV1OR9-1 chr9 65250543 65250826 +1265913 FOXD4L5 chr9 65282101 65285209 +1265921 FP326651.1 chr9 65385649 65396372 +1265925 CBWD5 chr9 65668805 65734041 +1266475 FOXD4L4 chr9 65736555 65738784 +1266483 IGKV1OR-3 chr9 65770955 65771434 +1266487 AL136317.2 chr9 66014525 66020816 +1266491 ANKRD20A3 chr9 66106815 66179474 +1266652 ZNF658 chr9 66856426 66932141 +1266754 AL353770.4 chr9 66942703 66952344 +1266765 AL353770.3 chr9 66979132 66988373 +1266769 SPATA31A3 chr9 66986304 66992583 +1266783 BX664730.1 chr9 67512034 67515393 +1266787 FAM27E3 chr9 67717411 67719178 +1266791 AL627230.3 chr9 67718236 67718955 +1266801 AL627230.1 chr9 67725914 67726255 +1266806 ANKRD20A1 chr9 67832765 67920552 +1266960 AL353608.2 chr9 68228651 68229312 +1266964 CBWD3 chr9 68232003 68300015 +1267417 FOXD4L3 chr9 68302867 68305084 +1267425 AL353608.3 chr9 68306528 68330626 +1267446 AL353608.1 chr9 68307393 68308445 +1267450 PGM5 chr9 68328308 68531061 +1267537 PGM5-AS1 chr9 68353614 68357893 +1267562 AL161457.2 chr9 68393881 68406500 +1267587 AL161457.1 chr9 68426843 68429369 +1267591 TMEM252 chr9 68536580 68540867 +1267601 TMEM252-DT chr9 68541036 68644442 +1267608 LINC01506 chr9 68543541 68546589 +1267619 PIP5K1B chr9 68705240 69009176 +1267796 FAM122A chr9 68780065 68785566 +1267804 AL354794.1 chr9 68822403 68843275 +1267809 PRKACG chr9 69012529 69014113 +1267817 FXN chr9 69035563 69100178 +1267914 TJP2 chr9 69121264 69274615 +1268753 BANCR chr9 69296682 69311111 +1268764 FAM189A2 chr9 69324567 69392558 +1268912 APBA1 chr9 69427532 69672371 +1268953 AL355140.1 chr9 69428248 69428721 +1268957 AL353693.1 chr9 69472466 69494513 +1268962 AL162412.1 chr9 69672749 69673713 +1268965 PTAR1 chr9 69709522 69760011 +1269027 C9orf135-DT chr9 69818394 69820773 +1269049 C9orf135 chr9 69820817 69906227 +1269144 MAMDC2-AS1 chr9 70033921 70175888 +1269261 MAMDC2 chr9 70043848 70226972 +1269298 SMC5-AS1 chr9 70193997 70258866 +1269314 SMC5 chr9 70258978 70354873 +1269386 AL162390.1 chr9 70310875 70312120 +1269389 KLF9 chr9 70384597 70414624 +1269399 TRPM3 chr9 70529063 71446904 +1270017 AL159990.2 chr9 70708047 70712863 +1270021 AL159990.1 chr9 70726040 70730856 +1270025 CEMIP2 chr9 71683366 71816690 +1270254 ABHD17B chr9 71862452 71910931 +1270283 C9orf85 chr9 71911510 71986054 +1270361 C9orf57 chr9 72051376 72072721 +1270451 AL583829.1 chr9 72060576 72081448 +1270457 GDA chr9 72114595 72257193 +1270702 AL135924.2 chr9 72257336 72257783 +1270706 LINC01504 chr9 72305367 72356721 +1270740 ZFAND5 chr9 72351413 72365235 +1270841 TMC1 chr9 72521608 72838291 +1271308 LINC01474 chr9 72871130 72874135 +1271343 ALDH1A1 chr9 72900671 73080442 +1271449 ANXA1 chr9 73151865 73170393 +1271568 AL451127.2 chr9 73509664 73548331 +1271578 AL451127.1 chr9 73573615 73579498 +1271583 AL355674.1 chr9 74371335 74384578 +1271599 RORB-AS1 chr9 74485551 74499127 +1271604 RORB chr9 74497335 74693177 +1271654 AL137018.1 chr9 74630794 74641758 +1271660 TRPM6 chr9 74722495 74888094 +1271936 C9orf40 chr9 74946583 74952912 +1271946 CARNMT1-AS1 chr9 74952968 74996293 +1271953 CARNMT1 chr9 74980790 75028423 +1271995 AL158825.2 chr9 75009828 75016036 +1271999 NMRK1 chr9 75060573 75088217 +1272097 OSTF1 chr9 75088514 75147265 +1272123 AL353780.1 chr9 75579669 75588548 +1272127 PCSK5 chr9 75890644 76362339 +1272363 RFK chr9 76385526 76394517 +1272407 GCNT1 chr9 76419850 76651203 +1272466 PRUNE2 chr9 76611376 76906114 +1272742 PCA3 chr9 76691980 76863307 +1272833 AL353637.2 chr9 76915615 76919785 +1272837 FOXB2 chr9 77019655 77020953 +1272844 VPS13A-AS1 chr9 77176760 77178180 +1272848 VPS13A chr9 77177445 77421537 +1273525 GNA14 chr9 77423079 77648322 +1273550 GNA14-AS1 chr9 77456295 77526697 +1273556 GNAQ chr9 77716097 78031811 +1273587 CEP78 chr9 78236062 78279690 +1274284 PSAT1 chr9 78297125 78330093 +1274329 AL512634.1 chr9 79135374 79198314 +1274367 LNCARSR chr9 79505804 79567802 +1274408 TLE4 chr9 79571773 79726882 +1274891 AL161912.1 chr9 79874696 79886678 +1274895 AL161912.2 chr9 79889001 79892007 +1274898 AL161782.1 chr9 79975023 79990064 +1274903 LINC01507 chr9 80030579 80034555 +1274907 AL138749.1 chr9 80869758 80871295 +1274912 TLE1 chr9 81583683 81689547 +1275022 AL591368.1 chr9 81689713 81776900 +1275031 AL158154.2 chr9 81928021 81931368 +1275035 SPATA31D4 chr9 81928514 81934948 +1275048 AL158154.3 chr9 81930226 81977089 +1275060 SPATA31D3 chr9 81943586 81950038 +1275073 SPATA31D1 chr9 81988772 81995253 +1275090 AL162726.1 chr9 82405188 82406239 +1275094 AL162726.4 chr9 82451656 82455225 +1275100 AL353774.1 chr9 82612552 82646584 +1275104 RASEF chr9 82979590 83063177 +1275153 AL499602.1 chr9 83063398 83069143 +1275157 AL137847.1 chr9 83219288 83238463 +1275172 FRMD3 chr9 83242990 83538546 +1275328 AL137847.2 chr9 83272280 83279499 +1275336 IDNK chr9 83623049 83644130 +1275423 UBQLN1 chr9 83659968 83707958 +1275508 AL354920.1 chr9 83707594 83713378 +1275515 GKAP1 chr9 83739425 83829516 +1275623 AL354733.1 chr9 83817643 83837861 +1275654 AL354733.2 chr9 83831586 83868532 +1275738 KIF27 chr9 83834099 83921465 +1275884 C9orf64 chr9 83938311 83956986 +1275924 HNRNPK chr9 83968083 83980616 +1276165 AL354733.3 chr9 83972233 83975777 +1276169 RMI1 chr9 83980711 84004074 +1276190 AL390838.1 chr9 84059298 84098984 +1276211 SLC28A3 chr9 84275457 84340758 +1276259 AL356134.1 chr9 84278219 84290131 +1276263 AL157886.1 chr9 84316514 84657077 +1276272 NTRK2 chr9 84668551 85027070 +1276575 AL354897.1 chr9 85167346 85194283 +1276584 AL354897.2 chr9 85230176 85233966 +1276588 AL583827.1 chr9 85369591 85444230 +1276605 AGTPBP1 chr9 85546539 85742029 +1276860 AL157882.1 chr9 85756042 85765112 +1276865 AL353743.2 chr9 85783668 85805154 +1277038 NAA35 chr9 85941146 86025462 +1277127 GOLM1 chr9 86026146 86100173 +1277230 AL161447.2 chr9 86127507 86128703 +1277234 C9orf153 chr9 86220265 86259657 +1277301 ISCA1 chr9 86264546 86283102 +1277352 TUT7 chr9 86287733 86354454 +1277577 AL158828.1 chr9 86414201 86488607 +1277593 AL353613.1 chr9 86632147 86696496 +1277598 LINC02834 chr9 86669349 86708307 +1277603 GAS1 chr9 86944362 86947506 +1277611 GAS1RR chr9 86948666 87002033 +1277623 AL513318.2 chr9 87008440 87042419 +1277636 C9orf170 chr9 87148644 87159556 +1277640 AL353752.2 chr9 87436215 87445795 +1277645 DAPK1 chr9 87497228 87708634 +1278094 DAPK1-IT1 chr9 87553454 87554459 +1278098 CTSL chr9 87726109 87731469 +1278178 AL772337.2 chr9 87848113 87853526 +1278184 SPATA31E1 chr9 87882877 87888903 +1278198 AL353572.3 chr9 87956214 87956883 +1278206 CDK20 chr9 87966441 87974753 +1278327 AL353572.4 chr9 88066445 88076975 +1278333 AL353748.3 chr9 88384902 88389224 +1278340 SPIN1 chr9 88388430 88478694 +1278392 NXNL2 chr9 88534033 88584274 +1278432 LINC02843 chr9 88627063 88652180 +1278499 AL390791.1 chr9 88735041 88803716 +1278506 AL772202.1 chr9 88971638 88976298 +1278510 S1PR3 chr9 88990863 89005155 +1278559 SHC3 chr9 89005771 89178818 +1278600 AL353150.1 chr9 89088604 89109934 +1278608 CKS2 chr9 89311195 89316703 +1278620 SECISBP2 chr9 89318500 89359663 +1278781 SEMA4D chr9 89360787 89498130 +1279252 AL161910.1 chr9 89563537 89604687 +1279276 GADD45G chr9 89605012 89606555 +1279305 AL606807.1 chr9 89639814 89719759 +1279326 BX470209.2 chr9 89797880 89803100 +1279334 BX470209.1 chr9 89799695 89821753 +1279339 AL161629.1 chr9 89825964 90019549 +1279497 MIR4290HG chr9 90020654 90041499 +1279503 LINC01508 chr9 90300885 90433566 +1279518 LINC01501 chr9 90462899 90583821 +1279597 DIRAS2 chr9 90609832 90642862 +1279625 SYK chr9 90801787 90898549 +1279757 AL162585.1 chr9 90921990 90922856 +1279761 AL355607.1 chr9 90957260 90965393 +1279765 AL355607.2 chr9 90996949 91001901 +1279794 AL158071.4 chr9 91077138 91163087 +1279806 AL158071.3 chr9 91104327 91213046 +1279822 AL158071.1 chr9 91118592 91182762 +1279844 LINC00484 chr9 91159573 91166272 +1279859 AL158071.5 chr9 91206175 91210299 +1279862 AUH chr9 91213815 91361913 +1279926 NFIL3 chr9 91409045 91423832 +1279936 AL353764.1 chr9 91426238 91427144 +1279940 ROR2 chr9 91563091 91950228 +1280028 SPTLC1 chr9 92000087 92115413 +1280285 AL136097.2 chr9 92205356 92210158 +1280290 IARS chr9 92210207 92293756 +1280658 NOL8 chr9 92297358 92325636 +1281268 CENPP chr9 92325953 92620529 +1281326 OGN chr9 92383268 92404696 +1281381 OMD chr9 92414245 92424461 +1281393 ASPN chr9 92456205 92482506 +1281460 ECM2 chr9 92493554 92536655 +1281533 AL157827.2 chr9 92600094 92612368 +1281538 IPPK chr9 92613183 92670131 +1281588 BICD2 chr9 92711363 92764833 +1281629 AL136981.3 chr9 92805431 92809171 +1281633 ZNF484 chr9 92844182 92878038 +1281692 FGD3 chr9 92947523 93036236 +1281906 SUSD3 chr9 93058688 93085133 +1281965 AL451065.1 chr9 93091460 93095546 +1281971 CARD19 chr9 93096217 93113283 +1282035 NINJ1 chr9 93121496 93134251 +1282066 AL390760.1 chr9 93147040 93148556 +1282071 WNK2 chr9 93184916 93320572 +1282469 C9orf129 chr9 93318199 93346414 +1282495 AL583839.1 chr9 93430342 93431299 +1282499 FAM120AOS chr9 93431441 93453581 +1282607 FAM120A chr9 93451685 93566112 +1282731 PHF2 chr9 93576584 93679587 +1282825 AL442224.1 chr9 93808347 93858340 +1282840 BARX1 chr9 93951627 93955355 +1282865 BARX1-DT chr9 93955597 93959140 +1282873 PTPDC1 chr9 94030794 94109856 +1282976 AL360020.1 chr9 94116023 94145693 +1282981 AL158152.1 chr9 94166258 94200902 +1283000 LINC02603 chr9 94176492 94259545 +1283030 ZNF169 chr9 94259298 94301829 +1283089 NUTM2F chr9 94318196 94328644 +1283130 AL691447.2 chr9 94332459 94363013 +1283135 MFSD14B chr9 94374569 94461042 +1283186 AL358232.2 chr9 94485445 94511614 +1283191 PCAT7 chr9 94555054 94603990 +1283210 FBP2 chr9 94558720 94593824 +1283230 FBP1 chr9 94603133 94640249 +1283301 AL157936.1 chr9 94725871 94726575 +1283304 AOPEP chr9 94726701 95087218 +1283597 AL807757.1 chr9 94824272 94824773 +1283601 AL807757.2 chr9 94900429 94904754 +1283606 AL353768.1 chr9 94928551 94934946 +1283610 AL353768.2 chr9 94964369 94965624 +1283614 FANCC chr9 95099054 95426796 +1283917 AL354893.2 chr9 95113708 95114461 +1283921 AL161729.3 chr9 95406990 95407662 +1283924 PTCH1 chr9 95442980 95517057 +1284521 AL161729.2 chr9 95494924 95495379 +1284524 AL161729.1 chr9 95506235 95507636 +1284527 AL161729.4 chr9 95514045 95514520 +1284530 AL392185.1 chr9 95599438 95606326 +1284539 AL354861.2 chr9 95650154 95715718 +1284547 LINC00476 chr9 95759231 95876049 +1284595 AL354861.3 chr9 95772323 95776282 +1284601 ERCC6L2 chr9 95871264 96121154 +1285032 LINC00092 chr9 96019724 96027993 +1285051 AL449403.1 chr9 96065740 96101912 +1285074 AL449403.2 chr9 96105741 96116411 +1285086 AL449403.3 chr9 96129869 96132214 +1285090 HSD17B3 chr9 96235306 96302176 +1285283 AL160269.1 chr9 96235331 96352058 +1285365 HSD17B3-AS1 chr9 96246462 96250393 +1285370 SLC35D2 chr9 96313444 96383711 +1285496 ZNF367 chr9 96385941 96418370 +1285512 AL133477.2 chr9 96416724 96417377 +1285515 AL133477.3 chr9 96419722 96421129 +1285519 HABP4 chr9 96450169 96491336 +1285560 CDC14B chr9 96490241 96619843 +1285823 PRXL2C chr9 96639577 96655317 +1285872 AL589843.1 chr9 96687050 96774318 +1285904 ZNF510 chr9 96755865 96778129 +1285955 ZNF782 chr9 96816269 96875623 +1286028 MFSD14C chr9 96887373 97013708 +1286118 NUTM2G chr9 96928310 96940253 +1286157 CTSV chr9 97029677 97039643 +1286206 AL590705.3 chr9 97195351 97197687 +1286211 AL590705.1 chr9 97200475 97238745 +1286222 AL590705.2 chr9 97222602 97235017 +1286239 CCDC180 chr9 97307304 97378751 +1286403 AL512590.3 chr9 97403709 97411908 +1286407 TDRD7 chr9 97412096 97496125 +1286450 TMOD1 chr9 97501180 97601743 +1286520 AL162385.1 chr9 97512706 97517836 +1286531 TSTD2 chr9 97600080 97633368 +1286608 NCBP1 chr9 97633668 97673748 +1286703 AL162385.2 chr9 97634515 97636051 +1286708 XPA chr9 97674909 97697357 +1286753 PTCSC2 chr9 97699625 97853080 +1286802 AL445531.1 chr9 97743208 97744935 +1286805 FOXE1 chr9 97853226 97856717 +1286813 TRMO chr9 97904489 97922570 +1286890 AL499604.1 chr9 97921590 97922181 +1286893 HEMGN chr9 97926791 97944856 +1286922 ANP32B chr9 97983341 98015943 +1286951 AL354726.1 chr9 97986551 97987656 +1286955 NANS chr9 98056732 98083077 +1287003 TRIM14 chr9 98069275 98119222 +1287083 CORO2A chr9 98120975 98192637 +1287140 TBC1D2 chr9 98199011 98255649 +1287287 GABBR2 chr9 98288109 98708935 +1287409 ANKS6 chr9 98731329 98796965 +1287527 AL807776.1 chr9 98798466 98807564 +1287531 GALNT12 chr9 98807670 98850081 +1287575 AL136084.2 chr9 98847172 98872415 +1287667 COL15A1 chr9 98943179 99070792 +1287860 AL136084.3 chr9 98943337 98943775 +1287863 TGFBR1 chr9 99104038 99154192 +1288020 AL162427.1 chr9 99183373 99184891 +1288024 ALG2 chr9 99216425 99221942 +1288054 SEC61B chr9 99222064 99230615 +1288084 NAMA chr9 99355337 99377240 +1288132 AL137067.3 chr9 99359336 99371887 +1288137 AL359710.1 chr9 99396987 99819921 +1288153 STX17-AS1 chr9 99397024 99906605 +1288172 AL162394.1 chr9 99531507 99583301 +1288181 NR4A3 chr9 99821855 99866891 +1288260 STX17 chr9 99906654 99974534 +1288419 AL358937.1 chr9 99915077 99929896 +1288423 ERP44 chr9 99979185 100099000 +1288453 INVS chr9 100099243 100302175 +1288572 TEX10 chr9 100302077 100352942 +1288659 MSANTD3 chr9 100427156 100451711 +1288728 TMEFF1 chr9 100473149 100577636 +1288754 CAVIN4 chr9 100578079 100588389 +1288764 PLPPR1 chr9 101028727 101325135 +1288827 BAAT chr9 101360417 101383519 +1288852 MRPL50 chr9 101387633 101398618 +1288862 ZNF189 chr9 101398873 101410660 +1288911 ALDOB chr9 101420560 101449664 +1289047 TMEM246-AS1 chr9 101468349 101482199 +1289066 TMEM246 chr9 101473170 101533537 +1289103 RNF20 chr9 101533853 101563344 +1289189 GRIN3A chr9 101569353 101738580 +1289217 PPP3R2 chr9 101591604 101595021 +1289240 LINC00587 chr9 102519636 102657514 +1289247 CYLC2 chr9 102995311 103018488 +1289306 LINC01492 chr9 103140523 103325034 +1289328 AL390962.1 chr9 103361952 103429892 +1289333 AL590381.1 chr9 103999755 104000469 +1289337 SMC2-AS1 chr9 104080024 104093073 +1289348 SMC2 chr9 104094260 104141419 +1289548 OR13F1 chr9 104504263 104505222 +1289555 AL450426.1 chr9 104519847 104537194 +1289573 OR13C4 chr9 104526253 104527209 +1289580 OR13C3 chr9 104535749 104536856 +1289595 OR13C8 chr9 104569168 104570130 +1289602 OR13C5 chr9 104598457 104599413 +1289609 OR13C2 chr9 104604671 104605627 +1289616 OR13C9 chr9 104617248 104618204 +1289623 OR13D1 chr9 104694379 104695485 +1289637 NIPSNAP3A chr9 104747683 104760120 +1289658 NIPSNAP3B chr9 104764129 104777764 +1289700 ABCA1 chr9 104781006 104928155 +1289847 AL359182.1 chr9 104927553 104928892 +1289851 CT70 chr9 104970593 104991818 +1289879 AL591506.1 chr9 105025932 105239221 +1289889 SLC44A1 chr9 105244622 105439171 +1290052 FSD1L chr9 105447796 105552433 +1290251 AL158070.1 chr9 105554035 105558304 +1290256 FKTN chr9 105558130 105641118 +1290593 TAL2 chr9 105662457 105663124 +1290601 TMEM38B chr9 105694541 105776629 +1290670 LINC01505 chr9 105993310 106740875 +1290846 AL732323.1 chr9 106061354 106064825 +1290850 AL451140.1 chr9 106584142 106591952 +1290854 AL512649.2 chr9 106615078 106615983 +1290865 LINC01505 chr9 106664754 106702662 +1290871 ZNF462 chr9 106863166 107013634 +1291007 AL807761.4 chr9 106974833 107102988 +1291017 AL807761.3 chr9 107117459 107121705 +1291022 RAD23B chr9 107283137 107332192 +1291108 LINC01509 chr9 107420191 107466613 +1291140 AL359552.1 chr9 107426405 107428742 +1291144 KLF4 chr9 107484852 107490482 +1291198 AL353742.1 chr9 108252154 108254820 +1291202 AL358779.1 chr9 108701370 108703092 +1291206 ACTL7B chr9 108854588 108855986 +1291214 ACTL7A chr9 108862266 108863756 +1291222 ELP1 chr9 108867517 108934124 +1291401 ABITRAM chr9 108934400 108950744 +1291445 CTNNAL1 chr9 108942569 109013522 +1291569 TMEM245 chr9 109015135 109119947 +1291683 FRRS1L chr9 109130293 109167295 +1291745 EPB41L4B chr9 109171975 109320964 +1291840 PTPN3 chr9 109375466 109498313 +1292056 PALM2-AKAP2 chr9 109640788 110172512 +1292275 AL158829.1 chr9 109760360 109772043 +1292280 C9orf152 chr9 110190048 110208189 +1292293 TXN chr9 110243810 110256507 +1292325 TXNDC8 chr9 110303521 110337884 +1292388 SVEP1 chr9 110365248 110579880 +1292654 AL592463.1 chr9 110599475 110605219 +1292659 MUSK chr9 110668779 110806558 +1292814 LPAR1 chr9 110873263 111038458 +1292886 AL162414.1 chr9 111139246 111284836 +1292891 OR2K2 chr9 111327483 111330183 +1292907 ECPAS chr9 111360692 111484745 +1293195 ZNF483 chr9 111525159 111577844 +1293256 PTGR1 chr9 111549722 111599893 +1293410 AL135787.1 chr9 111574192 111575427 +1293414 DNAJC25 chr9 111631334 111654351 +1293458 GNG10 chr9 111661605 111670226 +1293470 SHOC1 chr9 111686173 111795008 +1293716 UGCG chr9 111896814 111935369 +1293760 AL138756.1 chr9 112028570 112039143 +1293773 SUSD1 chr9 112040785 112175408 +1293970 PTBP3 chr9 112217716 112333667 +1294166 HSDL2 chr9 112380080 112472405 +1294242 C9orf147 chr9 112399512 112487204 +1294262 KIAA1958 chr9 112486847 112669397 +1294302 INIP chr9 112683926 112718149 +1294359 AL390067.1 chr9 112748902 112750565 +1294365 SNX30 chr9 112750760 112881671 +1294407 SLC46A2 chr9 112878920 112890876 +1294434 AL139041.1 chr9 112885158 112885767 +1294437 ZNF883 chr9 112997120 113050043 +1294447 ZFP37 chr9 113038380 113056759 +1294486 FAM225B chr9 113102117 113111543 +1294511 FAM225A chr9 113113042 113119928 +1294519 SLC31A2 chr9 113150976 113164140 +1294551 FKBP15 chr9 113161006 113221318 +1294720 SLC31A1 chr9 113221544 113264492 +1294739 CDC26 chr9 113255835 113275572 +1294759 PRPF4 chr9 113275343 113292905 +1294829 RNF183 chr9 113297093 113303376 +1294882 WDR31 chr9 113313222 113340298 +1295020 BSPRY chr9 113349541 113371233 +1295044 HDHD3 chr9 113373419 113376999 +1295069 ALAD chr9 113386312 113401290 +1295162 POLE3 chr9 113407235 113410675 +1295199 C9orf43 chr9 113410054 113429684 +1295272 RGS3 chr9 113444731 113597743 +1295755 AL162727.2 chr9 113570190 113590019 +1295760 AL162727.1 chr9 113619228 113622634 +1295764 AL157702.2 chr9 113650956 113682855 +1295769 ZNF618 chr9 113876282 114056591 +1295943 AMBP chr9 114060127 114078328 +1296014 KIF12 chr9 114086126 114099291 +1296213 COL27A1 chr9 114155537 114312511 +1296501 ORM1 chr9 114323056 114326475 +1296524 ORM2 chr9 114329869 114333256 +1296542 AKNA chr9 114334156 114394405 +1296794 AL138895.1 chr9 114396724 114398503 +1296798 WHRN chr9 114402080 114505473 +1296890 ATP6V1G1 chr9 114587769 114598879 +1296905 TMEM268 chr9 114611206 114646422 +1296961 TEX53 chr9 114656304 114662374 +1296974 TEX48 chr9 114666434 114682066 +1297005 TNFSF15 chr9 114784652 114806039 +1297026 DEC1 chr9 114850968 115402644 +1297078 TNFSF8 chr9 114893343 114930595 +1297110 TNC chr9 115019575 115118257 +1297491 AL162425.1 chr9 115119539 115138409 +1297499 AL355601.1 chr9 115252538 115254251 +1297504 AL691420.1 chr9 115324932 115744330 +1297538 LINC00474 chr9 115888169 115925207 +1297543 AL691426.1 chr9 116012361 116012965 +1297547 PAPPA chr9 116153791 116402321 +1297606 PAPPA-AS2 chr9 116285829 116288769 +1297610 AL137024.1 chr9 116288618 116318689 +1297616 PAPPA-AS1 chr9 116398157 116400606 +1297619 ASTN2 chr9 116425225 117415070 +1297884 ASTN2-AS1 chr9 116504283 116562293 +1297898 AL133284.1 chr9 116567636 116586328 +1297907 TRIM32 chr9 116687302 116701300 +1297935 AL157829.1 chr9 116838144 116877264 +1297942 AL445644.1 chr9 117462294 117466260 +1297946 AL161630.1 chr9 117643151 117657032 +1297961 TLR4 chr9 117704175 117724735 +1297998 AL160272.1 chr9 117759455 117879988 +1298036 AL354754.1 chr9 117840322 117897256 +1298042 AL355592.1 chr9 118687752 118732772 +1298050 LINC02578 chr9 118740563 118745312 +1298054 BRINP1 chr9 119153458 119369435 +1298096 AC006288.1 chr9 119495375 119524125 +1298101 LINC01613 chr9 119935053 119937832 +1298104 AL441989.1 chr9 119973094 119974322 +1298109 CDK5RAP2 chr9 120388869 120580170 +1298703 MEGF9 chr9 120600811 120714470 +1298721 FBXW2 chr9 120751978 120793416 +1298774 B3GNT10 chr9 120792403 120799918 +1298798 PSMD5 chr9 120815496 120842951 +1298887 PHF19 chr9 120855651 120894896 +1299083 TRAF1 chr9 120902393 120929173 +1299145 C5 chr9 120952335 121050276 +1299252 CNTRL chr9 121074863 121177610 +1299700 RAB14 chr9 121178133 121223014 +1299743 GSN chr9 121207794 121332843 +1300093 AL513122.2 chr9 121279863 121282730 +1300097 GSN-AS1 chr9 121280768 121285530 +1300100 STOM chr9 121338987 121370304 +1300148 AL359644.1 chr9 121369893 121463370 +1300172 DAB2IP chr9 121567057 121785530 +1300403 AL357936.1 chr9 121574891 121576214 +1300407 AL596244.1 chr9 121815674 121819452 +1300410 TTLL11 chr9 121821928 122093606 +1300499 TTLL11-IT1 chr9 121884636 121963719 +1300503 NDUFA8 chr9 122144058 122159779 +1300517 MORN5 chr9 122159908 122200088 +1300564 LHX6 chr9 122202577 122229626 +1300740 RBM18 chr9 122237622 122264840 +1300771 MRRF chr9 122264603 122331337 +1300952 PTGS1 chr9 122370530 122395703 +1301173 AL162424.1 chr9 122372605 122372825 +1301176 AL359636.1 chr9 122400970 122402906 +1301180 AL359636.2 chr9 122403407 122639685 +1301214 OR1J1 chr9 122476958 122477926 +1301221 OR1J2 chr9 122510802 122511743 +1301228 OR1J4 chr9 122519141 122520082 +1301235 OR1N1 chr9 122526358 122527296 +1301247 OR1N2 chr9 122553112 122554214 +1301261 OR1L8 chr9 122567117 122583384 +1301284 OR1Q1 chr9 122614738 122615682 +1301291 OR1B1 chr9 122628579 122629573 +1301299 OR1L1 chr9 122661566 122662648 +1301312 OR1L3 chr9 122675036 122676153 +1301320 OR1L4 chr9 122723990 122724925 +1301327 OR1L6 chr9 122742303 122750783 +1301343 OR5C1 chr9 122788933 122789895 +1301350 PDCL chr9 122798389 122828588 +1301382 OR1K1 chr9 122800123 122801073 +1301389 RC3H2 chr9 122844556 122905359 +1301643 ZBTB6 chr9 122908056 122913323 +1301653 ZBTB26 chr9 122915566 122931512 +1301672 AC007066.2 chr9 122937623 122940333 +1301678 AC007066.3 chr9 122940733 122941260 +1301682 RABGAP1 chr9 122940833 123104866 +1301880 GPR21 chr9 123034527 123035696 +1301888 MIR600HG chr9 123109494 123115477 +1301893 STRBP chr9 123109500 123268586 +1302116 CRB2 chr9 123356170 123380324 +1302196 DENND1A chr9 123379654 123930152 +1302442 AL445489.1 chr9 123491884 123493156 +1302446 AL390774.2 chr9 123736437 123751941 +1302450 LHX2 chr9 124001670 124033301 +1302499 AC006450.3 chr9 124006277 124009396 +1302503 AC006450.1 chr9 124010530 124011114 +1302507 AC006450.2 chr9 124031624 124032524 +1302512 NEK6 chr9 124257606 124353307 +1302837 AL162724.2 chr9 124259250 124261156 +1302841 AL162724.1 chr9 124262876 124265809 +1302845 PSMB7 chr9 124353465 124415444 +1302904 ADGRD2 chr9 124451425 124478589 +1303036 NR5A1 chr9 124481236 124507420 +1303097 AL354979.1 chr9 124514938 124516056 +1303101 NR6A1 chr9 124517275 124771311 +1303215 MIR181A2HG chr9 124658467 124698631 +1303219 AL354928.1 chr9 124770123 124772927 +1303224 OLFML2A chr9 124777133 124814885 +1303274 WDR38 chr9 124853417 124857890 +1303342 RPL35 chr9 124857880 124861981 +1303406 ARPC5L chr9 124862130 124877733 +1303441 GOLGA1 chr9 124878275 124948492 +1303574 SCAI chr9 124942608 125143506 +1303736 PPP6C chr9 125146573 125189939 +1303809 RABEPK chr9 125200542 125234161 +1303928 HSPA5 chr9 125234853 125241343 +1303950 AL354710.2 chr9 125241663 125257071 +1303955 GAPVD1 chr9 125261794 125367207 +1304590 AL359632.1 chr9 125426169 125438509 +1304595 MAPKAP1 chr9 125437393 125707234 +1304905 AL162584.1 chr9 125567579 125573023 +1304910 AL358074.1 chr9 125743754 125746552 +1304918 PBX3 chr9 125747345 125967377 +1305104 AL589923.1 chr9 126057580 126159613 +1305108 AL162391.1 chr9 126270121 126298593 +1305121 MVB12B chr9 126326829 126507041 +1305190 AL356309.2 chr9 126516417 126518808 +1305194 AL356309.1 chr9 126527618 126530343 +1305198 AL161908.1 chr9 126589594 126613700 +1305210 LMX1B chr9 126614443 126701032 +1305295 AL161908.2 chr9 126640756 126641293 +1305299 AL161731.1 chr9 126701173 126704691 +1305303 ZBTB43 chr9 126805006 126838210 +1305340 ZBTB34 chr9 126860665 126885878 +1305357 RALGPS1 chr9 126914774 127223166 +1305622 ANGPTL2 chr9 127087348 127122635 +1305657 AL450263.1 chr9 127213783 127221907 +1305665 GARNL3 chr9 127224265 127393660 +1306062 AL445222.1 chr9 127366770 127367397 +1306065 SLC2A8 chr9 127397138 127408424 +1306265 ZNF79 chr9 127424374 127445372 +1306324 RPL12 chr9 127447674 127451406 +1306377 LRSAM1 chr9 127451486 127503501 +1306646 NIBAN2 chr9 127505339 127578989 +1306737 STXBP1 chr9 127579370 127696027 +1307430 AL162426.1 chr9 127690098 127690840 +1307433 PTRH1 chr9 127690348 127724873 +1307533 CFAP157 chr9 127706988 127716002 +1307602 TTC16 chr9 127716079 127731590 +1307652 TOR2A chr9 127731524 127735313 +1307742 SH2D3C chr9 127738317 127778710 +1307956 AL162586.2 chr9 127754534 127760560 +1307961 CDK9 chr9 127785679 127790792 +1308004 FPGS chr9 127794597 127814327 +1308326 ENG chr9 127815012 127854756 +1308439 AL162586.1 chr9 127816066 127822520 +1308451 AK1 chr9 127866486 127877675 +1308540 ST6GALNAC6 chr9 127885321 127905408 +1308714 ST6GALNAC4 chr9 127907886 127917041 +1308765 PIP5KL1 chr9 127920881 127930785 +1308863 AL157935.1 chr9 127934503 127940952 +1308901 DPM2 chr9 127935099 127938484 +1308937 FAM102A chr9 127940582 127980989 +1309012 AL360268.2 chr9 128039135 128057362 +1309016 NAIF1 chr9 128061233 128068206 +1309035 SLC25A25 chr9 128068201 128109245 +1309196 AL360268.1 chr9 128090969 128094457 +1309200 SLC25A25-AS1 chr9 128108581 128118693 +1309207 PTGES2 chr9 128120693 128128462 +1309346 AL590708.1 chr9 128128529 128130628 +1309349 LCN2 chr9 128149071 128153453 +1309429 C9orf16 chr9 128160265 128163924 +1309451 CIZ1 chr9 128161251 128204383 +1310026 DNM1 chr9 128191655 128255248 +1310634 GOLGA2 chr9 128255829 128275995 +1310944 SWI5 chr9 128275379 128316123 +1311050 TRUB2 chr9 128305159 128322447 +1311085 AL359091.4 chr9 128316337 128316909 +1311088 COQ4 chr9 128322544 128334072 +1311144 SLC27A4 chr9 128340527 128361470 +1311193 URM1 chr9 128371319 128392016 +1311262 AL359091.3 chr9 128391461 128392016 +1311265 AL359091.1 chr9 128392007 128393510 +1311268 CERCAM chr9 128411751 128437351 +1311466 AL359091.5 chr9 128431598 128432006 +1311469 ODF2 chr9 128455186 128501292 +1312046 ODF2-AS1 chr9 128468957 128473012 +1312050 GLE1 chr9 128504700 128542288 +1312128 AL356481.1 chr9 128528657 128552410 +1312141 SPTAN1 chr9 128552558 128633662 +1312976 AL356481.2 chr9 128595893 128596633 +1312980 AL356481.3 chr9 128630328 128631685 +1312984 WDR34 chr9 128633661 128656787 +1313042 HMGA1P4 chr9 128663134 128684477 +1313050 SET chr9 128683424 128696400 +1313187 PKN3 chr9 128702503 128720916 +1313252 ZDHHC12 chr9 128720870 128724127 +1313312 AL441992.1 chr9 128724445 128733194 +1313316 ZER1 chr9 128729786 128772414 +1313378 TBC1D13 chr9 128787253 128810430 +1313450 ENDOG chr9 128818500 128822676 +1313462 SPOUT1 chr9 128819651 128829794 +1313520 KYAT1 chr9 128832942 128882494 +1313700 LRRC8A chr9 128882112 128918039 +1313744 PHYHD1 chr9 128920966 128942041 +1314003 DOLK chr9 128945530 128947619 +1314011 NUP188 chr9 128947699 129007096 +1314166 AL592211.1 chr9 129004502 129004998 +1314169 SH3GLB2 chr9 129007036 129028303 +1314387 MIGA2 chr9 129036621 129072082 +1314555 AL592211.2 chr9 129080355 129080765 +1314558 DOLPP1 chr9 129081111 129090438 +1314631 CRAT chr9 129094794 129111189 +1314772 AL158151.2 chr9 129097854 129100266 +1314776 PTPA chr9 129110950 129148946 +1315183 AL158151.4 chr9 129170434 129170940 +1315186 IER5L chr9 129175552 129178261 +1315194 AL158151.3 chr9 129175807 129177575 +1315199 AL158151.1 chr9 129176771 129210548 +1315206 AL161785.2 chr9 129258354 129259846 +1315211 AL161785.3 chr9 129259062 129261581 +1315215 AL161785.1 chr9 129282458 129312665 +1315226 C9orf106 chr9 129321016 129324905 +1315230 AL353803.5 chr9 129328261 129328401 +1315233 LINC01503 chr9 129332300 129359541 +1315321 AL353803.2 chr9 129430652 129451422 +1315328 AL353803.1 chr9 129438216 129447545 +1315339 LINC00963 chr9 129476946 129513687 +1315636 AL353803.4 chr9 129480605 129482538 +1315639 AL391056.2 chr9 129503461 129506433 +1315643 AL391056.1 chr9 129575117 129584556 +1315683 NTMT1 chr9 129608884 129636131 +1315812 C9orf50 chr9 129612225 129620776 +1315854 ASB6 chr9 129634604 129642169 +1315902 AL590369.1 chr9 129640476 129641282 +1315906 PRRX2 chr9 129665647 129722674 +1315920 PRRX2-AS1 chr9 129712896 129718635 +1315924 PTGES chr9 129738331 129753042 +1315941 TOR1B chr9 129803157 129811281 +1315974 TOR1A chr9 129812942 129824244 +1316019 C9orf78 chr9 129827290 129835863 +1316077 USP20 chr9 129834698 129881838 +1316283 FNBP1 chr9 129887187 130043194 +1316483 AL158207.2 chr9 129933536 129936541 +1316487 AL136141.1 chr9 130044713 130045081 +1316490 GPR107 chr9 130053426 130140169 +1316716 GPRACR chr9 130140610 130144219 +1316720 NCS1 chr9 130172404 130237303 +1316767 HMCN2 chr9 130265882 130434123 +1317079 ASS1 chr9 130444961 130501274 +1317257 FUBP3 chr9 130578965 130638352 +1317373 PRDM12 chr9 130664594 130682983 +1317389 EXOSC2 chr9 130693721 130704894 +1317540 ABL1 chr9 130713016 130887675 +1317602 QRFP chr9 130892707 130896812 +1317619 FIBCD1 chr9 130902438 130939286 +1317715 AL161733.1 chr9 130933851 130945520 +1317720 LAMC3 chr9 131009174 131094473 +1317812 AIF1L chr9 131096476 131123152 +1317954 NUP214 chr9 131125586 131234663 +1318539 AL157938.2 chr9 131132852 131167505 +1318601 AL157938.3 chr9 131189910 131194205 +1318605 FAM78A chr9 131258076 131276510 +1318643 AL157938.4 chr9 131283421 131288278 +1318647 PLPP7 chr9 131289459 131359022 +1318681 PRRC2B chr9 131373636 131500197 +1318985 AL358781.1 chr9 131497479 131500191 +1318992 POMT1 chr9 131502902 131523806 +1319352 AL358781.2 chr9 131516558 131522229 +1319356 UCK1 chr9 131523801 131531264 +1319472 PRRT1B chr9 131545514 131558620 +1319486 RAPGEF1 chr9 131576770 131740074 +1319696 AL160271.2 chr9 131816192 131820988 +1319701 MED27 chr9 131852928 132079867 +1319797 NTNG2 chr9 132161676 132244526 +1319844 SETX chr9 132261356 132354986 +1319952 TTF1 chr9 132375548 132406851 +1320008 CFAP77 chr9 132410043 132573317 +1320058 BARHL1 chr9 132582606 132590252 +1320083 DDX31 chr9 132592997 132670401 +1320280 GTF3C4 chr9 132670035 132694953 +1320307 AK8 chr9 132725578 132878777 +1320374 AL445645.1 chr9 132768965 132770212 +1320378 SPACA9 chr9 132878027 132890201 +1320420 TSC1 chr9 132891348 132946874 +1321704 GFI1B chr9 132944000 132991687 +1321814 GTF3C5 chr9 133030675 133058503 +1321970 CEL chr9 133061978 133071861 +1321998 RALGDS chr9 133097720 133149334 +1322309 GBGT1 chr9 133152948 133163933 +1322472 OBP2B chr9 133205277 133209250 +1322560 ABO chr9 133250401 133276024 +1322623 SURF6 chr9 133328776 133336188 +1322642 MED22 chr9 133338312 133348131 +1322752 RPL7A chr9 133348218 133351426 +1322845 SURF1 chr9 133351758 133356676 +1322908 SURF2 chr9 133356550 133361158 +1322935 SURF4 chr9 133361450 133376166 +1323053 STKLD1 chr9 133376366 133406096 +1323108 REXO4 chr9 133406059 133418096 +1323183 ADAMTS13 chr9 133414358 133459402 +1323569 CACFD1 chr9 133459965 133470848 +1323652 SLC2A6 chr9 133471094 133479127 +1323734 MYMK chr9 133514586 133528612 +1323755 ADAMTSL2 chr9 133532164 133575519 +1323928 FAM163B chr9 133578415 133586197 +1323949 AC002101.1 chr9 133611798 133633099 +1323953 DBH chr9 133636363 133659329 +1323990 DBH-AS1 chr9 133654586 133657313 +1323994 SARDH chr9 133663560 133739955 +1324227 VAV2 chr9 133761894 133992604 +1324422 BRD3OS chr9 134025481 134034666 +1324464 BRD3 chr9 134030305 134068535 +1324543 AL445931.1 chr9 134054290 134058805 +1324548 BX649632.1 chr9 134132242 134135772 +1324555 WDR5 chr9 134135365 134159968 +1324613 BX649601.1 chr9 134168769 134169340 +1324616 LINC02247 chr9 134293931 134295397 +1324620 RXRA chr9 134317098 134440585 +1324695 AL669970.1 chr9 134505472 134521442 +1324700 AL669970.3 chr9 134527182 134545244 +1324704 AL669970.2 chr9 134552738 134553897 +1324708 COL5A1 chr9 134641774 134844843 +1325016 COL5A1-AS1 chr9 134649385 134653073 +1325020 AL645768.1 chr9 134770651 134775671 +1325024 FCN2 chr9 134880810 134887523 +1325065 FCN1 chr9 134903232 134917912 +1325110 AL353611.1 chr9 134936524 134943207 +1325129 OLFM1 chr9 135075422 135121179 +1325272 AL390778.1 chr9 135204722 135237597 +1325276 AL390778.2 chr9 135245696 135252708 +1325280 C9orf62 chr9 135343249 135346562 +1325285 AL353615.1 chr9 135352673 135354284 +1325298 PPP1R26-AS1 chr9 135462727 135480777 +1325318 PPP1R26 chr9 135479079 135488893 +1325384 C9orf116 chr9 135495181 135501734 +1325432 MRPS2 chr9 135499984 135504673 +1325493 AL161452.1 chr9 135503273 135506447 +1325498 LCN1 chr9 135521438 135526532 +1325537 OBP2A chr9 135546139 135549969 +1325667 PAEP chr9 135561756 135566955 +1325815 LINC01502 chr9 135574935 135587112 +1325832 AL354761.1 chr9 135604345 135618952 +1325855 GLT6D1 chr9 135623648 135639540 +1325888 LCN9 chr9 135663322 135666422 +1325932 SOHLH1 chr9 135693407 135699528 +1325973 KCNT1 chr9 135702185 135795508 +1326832 CAMSAP1 chr9 135808487 135907546 +1326987 AL355574.1 chr9 135907812 135916126 +1326995 UBAC1 chr9 135932969 135961373 +1327047 NACC2 chr9 136006537 136095289 +1327083 LINC02846 chr9 136107808 136109424 +1327089 TMEM250 chr9 136114581 136118875 +1327133 AL138781.1 chr9 136122521 136124363 +1327136 LHX3 chr9 136196250 136205128 +1327194 QSOX2 chr9 136206333 136245841 +1327239 CCDC187 chr9 136249971 136306901 +1327378 CR392000.2 chr9 136263925 136267237 +1327382 AC174065.1 chr9 136322303 136327323 +1327387 GPSM1 chr9 136327476 136359605 +1327514 DNLZ chr9 136359480 136363744 +1327535 CARD9 chr9 136361903 136373681 +1327671 SNAPC4 chr9 136375577 136400168 +1327754 ENTR1 chr9 136401922 136410614 +1327878 PMPCA chr9 136410641 136423761 +1328005 INPP5E chr9 136428619 136439845 +1328033 SEC16A chr9 136440096 136483759 +1328418 C9orf163 chr9 136483495 136486067 +1328423 NOTCH1 chr9 136494433 136546048 +1328523 AL592301.1 chr9 136542881 136543835 +1328527 NALT1 chr9 136546212 136549893 +1328535 AL590226.2 chr9 136612024 136617181 +1328548 AL590226.1 chr9 136648610 136660421 +1328552 EGFL7 chr9 136658856 136672678 +1328679 AGPAT2 chr9 136673143 136687457 +1328739 DIPK1B chr9 136712572 136724742 +1328766 SNHG7 chr9 136721366 136728184 +1328799 LCN10 chr9 136738167 136743356 +1328894 LCN6 chr9 136744017 136748525 +1328947 LCN8 chr9 136754386 136758543 +1329002 LCN15 chr9 136759634 136766255 +1329034 TMEM141 chr9 136791344 136793317 +1329075 CCDC183 chr9 136796338 136807741 +1329186 CCDC183-AS1 chr9 136803927 136808848 +1329193 RABL6 chr9 136807943 136841187 +1329440 AJM1 chr9 136844415 136848801 +1329447 PHPT1 chr9 136848724 136851027 +1329491 MAMDC4 chr9 136850943 136860799 +1329663 EDF1 chr9 136862119 136866308 +1329707 TRAF2 chr9 136881912 136926607 +1329798 AL807752.5 chr9 136937169 136937988 +1329801 FBXW5 chr9 136940435 136944738 +1329899 C8G chr9 136945185 136946975 +1329957 LCN12 chr9 136949551 136955497 +1330060 LINC02692 chr9 136969243 136971990 +1330066 PTGDS chr9 136975092 136981742 +1330157 LCNL1 chr9 136981904 136986410 +1330180 PAXX chr9 136992422 136993984 +1330237 CLIC3 chr9 136994608 136996568 +1330266 ABCA2 chr9 137007234 137028922 +1331066 C9orf139 chr9 137027464 137037957 +1331082 FUT7 chr9 137030174 137033010 +1331092 NPDC1 chr9 137039463 137046179 +1331156 ENTPD2 chr9 137048107 137054061 +1331212 AL807752.4 chr9 137052662 137053375 +1331216 AL807752.2 chr9 137057663 137062461 +1331220 SAPCD2 chr9 137062127 137070557 +1331238 AL807752.3 chr9 137063535 137064581 +1331242 UAP1L1 chr9 137077517 137084539 +1331301 MAN1B1-DT chr9 137084946 137086817 +1331304 MAN1B1 chr9 137086985 137109183 +1331504 DPP7 chr9 137110546 137115177 +1331659 GRIN1 chr9 137139154 137168756 +1332052 LRRC26 chr9 137168758 137170051 +1332062 TMEM210 chr9 137170858 137172409 +1332096 ANAPC2 chr9 137174784 137188560 +1332155 SSNA1 chr9 137188660 137190370 +1332184 TPRN chr9 137191617 137204193 +1332214 TMEM203 chr9 137204082 137205648 +1332222 NDOR1 chr9 137205685 137217009 +1332365 BX255925.3 chr9 137217452 137219361 +1332373 RNF208 chr9 137220247 137221581 +1332390 CYSRT1 chr9 137224635 137226315 +1332409 RNF224 chr9 137227271 137229638 +1332421 SLC34A3 chr9 137230757 137236554 +1332484 TUBB4B chr9 137241287 137243707 +1332502 FAM166A chr9 137243584 137247770 +1332538 STPG3-AS1 chr9 137250219 137253497 +1332544 STPG3 chr9 137251261 137253483 +1332647 NELFB chr9 137255327 137273542 +1332708 TOR4A chr9 137277726 137282641 +1332718 BX255925.1 chr9 137293868 137295721 +1332721 BX255925.4 chr9 137294935 137300189 +1332727 NRARP chr9 137299631 137302271 +1332735 EXD3 chr9 137306896 137423211 +1332956 NOXA1 chr9 137423350 137434406 +1333019 ENTPD8 chr9 137434364 137441816 +1333111 NSMF chr9 137447573 137459334 +1333361 PNPLA7 chr9 137459952 137550402 +1333563 MRPL41 chr9 137551879 137552555 +1333573 DPH7 chr9 137554444 137578925 +1333675 ZMYND19 chr9 137582081 137590512 +1333696 ARRDC1 chr9 137605685 137615360 +1333806 ARRDC1-AS1 chr9 137615332 137618906 +1333820 EHMT1 chr9 137618992 137870016 +1334552 AL772363.1 chr9 137867925 137892570 +1334562 CACNA1B chr9 137877782 138124624 +1335160 AL954642.1 chr9 138199933 138203325 +1335164 AC215217.1 chr10 14061 16544 +1335171 TUBB8 chr10 46892 74163 +1335250 ZMYND11 chr10 134465 254637 +1335710 DIP2C chr10 274190 689668 +1335976 AL669841.1 chr10 437561 441170 +1335980 AL358216.1 chr10 628638 631255 +1335984 PRR26 chr10 649948 669581 +1336020 AL157709.1 chr10 743992 744958 +1336024 LARP4B chr10 806914 931705 +1336203 AL359878.2 chr10 933026 942743 +1336208 AL359878.1 chr10 971146 988341 +1336214 GTPBP4 chr10 988434 1019932 +1336287 IDI2 chr10 1018910 1025859 +1336303 IDI2-AS1 chr10 1022630 1045425 +1336338 IDI1 chr10 1039152 1049170 +1336387 WDR37 chr10 1049538 1132384 +1336563 LINC00200 chr10 1159768 1289426 +1336589 ADARB2 chr10 1177313 1737525 +1336654 AL392083.2 chr10 1201406 1208389 +1336658 AL392083.1 chr10 1290018 1293002 +1336661 AL513304.1 chr10 1361001 1361637 +1336665 ADARB2-AS1 chr10 1526637 1556984 +1336673 AL355597.1 chr10 1957589 1960190 +1336677 LINC00700 chr10 1989076 2015005 +1336720 AL441943.1 chr10 2071845 2081097 +1336724 AL441943.2 chr10 2150480 2169460 +1336733 LINC02662 chr10 2169140 2189512 +1336745 LINC00701 chr10 2305083 2315075 +1336750 LINC02645 chr10 2368561 2502200 +1336809 AL713851.2 chr10 2499721 2500570 +1336813 AL713851.1 chr10 2501600 2618739 +1336842 AL355361.1 chr10 2724819 2728267 +1336846 AL731533.1 chr10 3009976 3013111 +1336851 AL731533.3 chr10 3042535 3047083 +1336855 AL731533.2 chr10 3065424 3066001 +1336858 PFKP chr10 3066333 3137718 +1337085 PITRM1 chr10 3137728 3172841 +1337362 PITRM1-AS1 chr10 3141632 3167972 +1337378 LINC02668 chr10 3200829 3277649 +1337410 AL451164.1 chr10 3223816 3227407 +1337415 AL139280.1 chr10 3263346 3267216 +1337420 AL139280.2 chr10 3296338 3298137 +1337424 AL356433.1 chr10 3397505 3400180 +1337429 LINC02669 chr10 3433508 3502915 +1337541 AL357833.1 chr10 3532094 3556314 +1337552 AL450322.2 chr10 3748966 3763712 +1337568 AL450322.1 chr10 3767915 3768751 +1337572 KLF6 chr10 3775996 3785281 +1337621 AL513303.1 chr10 3809835 3816169 +1337627 LINC02639 chr10 3833950 3834728 +1337631 LINC02660 chr10 3911889 3935817 +1337655 AC025822.1 chr10 4024903 4053018 +1337687 AC025822.2 chr10 4051726 4089013 +1337693 LINC00702 chr10 4201141 4243912 +1337747 LINC00703 chr10 4384246 4410614 +1337757 AC022535.1 chr10 4415305 4426179 +1337763 AC022535.3 chr10 4437102 4448692 +1337767 AC022535.2 chr10 4497449 4515244 +1337773 MANCR chr10 4650158 4678185 +1337799 LINC00705 chr10 4655427 4682722 +1337844 AC018978.1 chr10 4747846 4785100 +1337850 AKR1E2 chr10 4786629 4848062 +1338048 AKR1C1 chr10 4963253 4983283 +1338116 AKR1C2 chr10 4987400 5018031 +1338222 AL391427.1 chr10 4995488 4997380 +1338231 AKR1C3 chr10 5035354 5107686 +1338349 AKR1C8P chr10 5154140 5185187 +1338418 AKR1C4 chr10 5195462 5218949 +1338472 AL355303.2 chr10 5215408 5217014 +1338476 AL355303.1 chr10 5234358 5263408 +1338480 LINC02561 chr10 5266033 5271236 +1338484 UCN3 chr10 5364966 5374692 +1338494 TUBAL3 chr10 5393101 5404828 +1338521 NET1 chr10 5412557 5459056 +1338599 CALML5 chr10 5498697 5499570 +1338607 CALML3-AS1 chr10 5510036 5526246 +1338624 CALML3 chr10 5524961 5526771 +1338632 AL732437.1 chr10 5524976 5525742 +1338636 AL732437.3 chr10 5549637 5554329 +1338655 AL732437.2 chr10 5563295 5566881 +1338659 LINC02657 chr10 5594984 5632435 +1338671 LINC02678 chr10 5608475 5610793 +1338678 LINC02677 chr10 5616626 5632499 +1338688 ASB13 chr10 5638867 5666595 +1338738 TASOR2 chr10 5684838 5763740 +1338902 AL365356.1 chr10 5712174 5744067 +1338909 GDI2 chr10 5765223 5842132 +1339052 AL596094.1 chr10 5813985 5814441 +1339056 ANKRD16 chr10 5861616 5889906 +1339119 FBH1 chr10 5890203 5937594 +1339326 AL137186.2 chr10 5934270 5945900 +1339336 IL15RA chr10 5943639 5978187 +1339667 IL2RA chr10 6010689 6062370 +1339744 AL137186.1 chr10 6025978 6036427 +1339749 RBM17 chr10 6089034 6117457 +1339891 PFKFB3 chr10 6144934 6254644 +1340431 AL157395.1 chr10 6197612 6202693 +1340435 LINC02649 chr10 6271169 6353827 +1340467 LINC02656 chr10 6350316 6352762 +1340470 PRKCQ chr10 6427143 6580301 +1340628 PRKCQ-AS1 chr10 6580419 6616921 +1340743 LINC02648 chr10 6618716 6625346 +1340749 LINP1 chr10 6709530 6740532 +1340766 LINC00706 chr10 6774307 6779180 +1340770 LINC00707 chr10 6779549 6879450 +1340820 AL392086.3 chr10 6824275 7118469 +1340873 LINC02665 chr10 7096216 7097675 +1340878 SFMBT2 chr10 7158624 7411486 +1341003 LINC02642 chr10 7444340 7472040 +1341021 AL445070.1 chr10 7533207 7536565 +1341026 ITIH5 chr10 7559270 7666998 +1341160 ITIH2 chr10 7703316 7749520 +1341287 KIN chr10 7750962 7787993 +1341354 ATP5F1C chr10 7788147 7807815 +1341449 TAF3 chr10 7818505 8016631 +1341469 GATA3 chr10 8045378 8075198 +1341524 GATA3-AS1 chr10 8050450 8053484 +1341542 AL390294.1 chr10 8051541 8053084 +1341547 LINC00708 chr10 8259331 8268342 +1341563 AL390835.1 chr10 8298897 8301667 +1341567 AC025946.1 chr10 8400860 8461863 +1341573 LINC02676 chr10 8897989 8914596 +1341579 AC044784.1 chr10 8970125 8973468 +1341583 LINC00709 chr10 9275833 9287057 +1341587 AL138773.1 chr10 9292842 9309772 +1341597 LINC02663 chr10 9758783 9878060 +1341608 LINC02670 chr10 10058722 10063502 +1341614 AL354916.1 chr10 10326875 10337876 +1341620 AL583859.1 chr10 10365180 10366487 +1341624 CELF2-DT chr10 10369809 10462361 +1341656 AL583859.3 chr10 10400340 10404203 +1341660 SFTA1P chr10 10784437 10795047 +1341717 CELF2 chr10 10798397 11336675 +1342249 LINC00710 chr10 10917866 10952234 +1342643 AL136369.2 chr10 10960148 10970816 +1342648 AL136369.1 chr10 11010164 11011119 +1342652 AL162408.1 chr10 11030334 11030868 +1342656 CELF2-AS2 chr10 11071541 11105773 +1342753 AL136320.1 chr10 11168922 11171376 +1342757 CELF2-AS1 chr10 11316833 11319884 +1342761 USP6NL chr10 11453946 11611754 +1342879 AL512631.2 chr10 11611305 11612227 +1342882 AL512631.1 chr10 11679675 11680514 +1342885 ECHDC3 chr10 11742366 11764070 +1342934 PROSER2 chr10 11823339 11872277 +1342984 PROSER2-AS1 chr10 11849608 11894700 +1342997 UPF2 chr10 11920022 12043170 +1343146 DHTKD1 chr10 12068954 12123221 +1343229 SEC61A2 chr10 12129637 12169961 +1343498 NUDT5 chr10 12165330 12196144 +1343665 CDC123 chr10 12195965 12250589 +1343807 AL512770.1 chr10 12244751 12247845 +1343814 CAMK1D chr10 12349482 12835545 +1343891 AL731559.1 chr10 12563151 12567351 +1343895 AL353586.1 chr10 12877459 12965275 +1343902 CCDC3 chr10 12896625 13099652 +1343933 OPTN chr10 13099449 13138308 +1344203 MCM10 chr10 13161554 13211104 +1344356 UCMA chr10 13221766 13234374 +1344385 PHYH chr10 13277796 13302412 +1344492 SEPHS1 chr10 13317428 13348298 +1344585 AL355870.2 chr10 13391347 13400706 +1344589 AL355870.1 chr10 13415202 13423133 +1344593 BEND7 chr10 13438484 13528974 +1344691 AL590677.1 chr10 13528516 13530262 +1344695 PRPF18 chr10 13586939 13630859 +1344761 AL157392.3 chr10 13631143 13668445 +1345074 FRMD4A chr10 13643706 14462142 +1345330 AL157392.4 chr10 13675646 13675990 +1345333 AL157392.1 chr10 13710415 13712054 +1345337 AL157392.2 chr10 13729383 13756200 +1345342 AC044781.1 chr10 13991815 14007526 +1345347 AL157896.1 chr10 14074284 14087605 +1345352 AL139405.1 chr10 14372001 14377586 +1345357 FAM107B chr10 14518557 14774897 +1345678 AL158168.1 chr10 14652689 14661691 +1345689 CDNF chr10 14819245 14838575 +1345734 HSPA14 chr10 14838160 14847018 +1345781 HSPA14 chr10 14838306 14871741 +1345834 AC069544.1 chr10 14877688 14878686 +1345837 SUV39H2 chr10 14878820 14904315 +1345944 DCLRE1C chr10 14897359 14954432 +1346341 MEIG1 chr10 14959388 14988050 +1346373 OLAH chr10 15032227 15073852 +1346481 ACBD7 chr10 15075475 15088776 +1346500 RPP38-DT chr10 15095385 15097319 +1346504 RPP38 chr10 15097180 15139818 +1346571 NMT2 chr10 15102584 15168693 +1346646 FAM171A1 chr10 15211643 15371289 +1346683 AL607028.1 chr10 15237492 15241767 +1346687 ITGA8 chr10 15513954 15719922 +1346761 MINDY3 chr10 15778170 15860507 +1346868 LINC02654 chr10 16276871 16295858 +1346931 PTER chr10 16436943 16513745 +1346991 C1QL3 chr10 16513734 16521879 +1347012 AL353576.1 chr10 16521714 16539737 +1347028 RSU1 chr10 16590611 16817463 +1347113 AC073367.1 chr10 16721352 16748377 +1347118 AL365215.2 chr10 16817699 16821207 +1347123 CUBN chr10 16823966 17129817 +1347302 AC067747.1 chr10 17137336 17137585 +1347305 TRDMT1 chr10 17137336 17202054 +1347467 VIM-AS1 chr10 17214239 17229985 +1347483 VIM chr10 17228241 17237593 +1347600 AL133415.1 chr10 17233325 17234833 +1347604 ST8SIA6 chr10 17315421 17454595 +1347658 ST8SIA6-AS1 chr10 17386919 17445758 +1347685 HACD1 chr10 17589032 17617374 +1347745 STAM-AS1 chr10 17641284 17643878 +1347748 STAM chr10 17644151 17716824 +1347823 AC069542.1 chr10 17695709 17700232 +1347828 TMEM236 chr10 17752201 17800868 +1347842 MRC1 chr10 17809348 17911164 +1347908 AC069023.1 chr10 17862887 17865471 +1347912 SLC39A12 chr10 17951839 18043292 +1348033 SLC39A12-AS1 chr10 18001786 18010562 +1348045 CACNB2 chr10 18140677 18543557 +1348734 AL390783.1 chr10 18206127 18261504 +1348755 AL450384.2 chr10 18513115 18545651 +1348765 AL450384.1 chr10 18531849 18533336 +1348769 NSUN6 chr10 18545561 18659285 +1348839 ARL5B chr10 18659431 18681639 +1348857 AL512641.1 chr10 18710269 18748342 +1348871 MALRD1 chr10 19048801 19790401 +1349054 AL590378.1 chr10 19290223 19291480 +1349058 AL157895.1 chr10 19710328 19728550 +1349079 AL353147.1 chr10 19812372 19816278 +1349083 PLXDC2 chr10 19816239 20289856 +1349162 AC069549.1 chr10 20070805 20091784 +1349166 AC069549.2 chr10 20095125 20099664 +1349173 NEBL chr10 20779973 21174187 +1349341 C10orf113 chr10 21125763 21146559 +1349365 NEBL-AS1 chr10 21174014 21175048 +1349372 LINC02643 chr10 21340233 21372950 +1349379 MIR1915HG chr10 21492658 21497260 +1349383 SKIDA1 chr10 21513475 21526368 +1349415 MLLT10 chr10 21524646 21743630 +1349959 AL358780.1 chr10 21526568 21526863 +1349962 DNAJC1 chr10 21756548 22003769 +1350019 AL359697.1 chr10 21865335 21865921 +1350022 EBLN1 chr10 22208814 22210021 +1350030 AL157831.2 chr10 22218074 22221168 +1350033 AL157831.3 chr10 22230826 22232973 +1350037 AL158211.1 chr10 22257786 22258548 +1350040 COMMD3 chr10 22316386 22320306 +1350186 BMI1 chr10 22321099 22331484 +1350284 AL158211.4 chr10 22332404 22332987 +1350287 AL158211.2 chr10 22332587 22332981 +1350290 AL158211.3 chr10 22340377 22340615 +1350293 SPAG6 chr10 22345445 22454224 +1350437 AL513128.1 chr10 22361172 22413067 +1350441 AL513128.3 chr10 22439954 22479480 +1350450 AL513128.2 chr10 22475455 22478026 +1350458 PIP4K2A chr10 22534854 22714578 +1350562 ARMC3 chr10 22928024 23038523 +1350789 AL139815.1 chr10 22964926 23133804 +1350809 MSRB2 chr10 23095579 23122013 +1350841 PTF1A chr10 23192312 23194245 +1350886 C10orf67 chr10 23201916 23344845 +1351006 AL606469.1 chr10 23343957 23345181 +1351010 OTUD1 chr10 23439458 23442390 +1351017 AL512603.2 chr10 23443036 23529801 +1351022 AL512603.1 chr10 23575012 23586224 +1351028 KIAA1217 chr10 23694746 24547848 +1351463 AL356113.1 chr10 24410183 24416459 +1351467 ARHGAP21 chr10 24583609 24723887 +1351871 AL157385.2 chr10 24816331 24822950 +1351875 PRTFDC1 chr10 24848614 24952606 +1351933 AL512598.1 chr10 24953241 24953513 +1351936 ENKUR chr10 24981979 25062279 +1352016 THNSL1 chr10 25016612 25026664 +1352039 LINC01516 chr10 25113058 25161236 +1352048 GPR158-AS1 chr10 25158072 25176276 +1352052 GPR158 chr10 25174802 25602229 +1352117 LINC00836 chr10 25651712 25732935 +1352226 AL358612.1 chr10 25924448 25933710 +1352232 MYO3A chr10 25934229 26212532 +1352488 GAD2 chr10 26216665 26304558 +1352620 APBB1IP chr10 26438341 26567803 +1352672 AL390961.1 chr10 26643228 26645016 +1352676 PDSS1 chr10 26697701 26746798 +1352737 AL390961.2 chr10 26717635 26718778 +1352741 ABI1 chr10 26746593 26861087 +1353046 ANKRD26 chr10 26991914 27100498 +1353223 YME1L1 chr10 27110112 27155266 +1353472 MASTL chr10 27154824 27186924 +1353567 ACBD5 chr10 27195214 27242130 +1353786 AL160291.1 chr10 27243130 27250804 +1353790 LINC02673 chr10 27343436 27344917 +1353794 RAB18 chr10 27504174 27542237 +1353914 LINC02680 chr10 27564430 27594588 +1353920 MKX chr10 27672874 27746060 +1353979 MKX-AS1 chr10 27744786 27767794 +1353987 ARMC4 chr10 27775186 27999079 +1354251 AL390866.1 chr10 27999788 28049615 +1354257 MPP7 chr10 28050993 28334486 +1354465 AL355501.1 chr10 28263703 28265175 +1354469 MPP7-DT chr10 28303300 28307658 +1354474 LINC02652 chr10 28433008 28495813 +1354479 WAC-AS1 chr10 28522652 28533066 +1354492 WAC chr10 28532493 28623112 +1354877 BAMBI chr10 28677510 28682932 +1354892 LINC01517 chr10 28743506 28941910 +1355002 AL355376.1 chr10 28743745 28744663 +1355006 LINC00837 chr10 28789188 28796113 +1355028 LYZL1 chr10 29289061 29318328 +1355073 AL158167.1 chr10 29373027 29409366 +1355078 SVIL chr10 29457338 29736781 +1355395 JCAD chr10 30012803 30115494 +1355416 AL353796.1 chr10 30302826 30306066 +1355419 MTPAP chr10 30309801 30374448 +1355494 AL353796.2 chr10 30309803 30312026 +1355499 MAP3K8 chr10 30434021 30461833 +1355600 AL590068.4 chr10 30529517 30554625 +1355604 AL590068.1 chr10 30553854 30554483 +1355608 AL590068.2 chr10 30576699 30580182 +1355612 AL590068.3 chr10 30587706 30591092 +1355618 LYZL2 chr10 30611779 30629762 +1355649 LINC02644 chr10 30723251 30723740 +1355653 ZNF438 chr10 30820207 31031937 +1355835 AL359532.1 chr10 30831828 30833387 +1355838 AL359546.1 chr10 31033089 31143813 +1355843 LINC02664 chr10 31187715 31261910 +1355858 ZEB1-AS1 chr10 31206278 31320447 +1355892 ZEB1 chr10 31318495 31529814 +1356215 AL161935.1 chr10 31602862 31606218 +1356234 AL161935.3 chr10 31608500 31620862 +1356239 MACORIS chr10 31693084 31707388 +1356243 ARHGAP12 chr10 31805398 31928876 +1356495 KIF5B chr10 32009015 32056425 +1356559 AL158834.2 chr10 32266289 32269474 +1356568 EPC1 chr10 32267751 32378798 +1356751 AL158834.1 chr10 32281686 32282829 +1356755 AL391839.2 chr10 32346499 32347179 +1356759 AL391839.1 chr10 32347397 32374488 +1356763 AL391839.3 chr10 32413499 32446061 +1356768 CCDC7 chr10 32446140 32882874 +1357250 AL365203.2 chr10 32887255 32889311 +1357253 ITGB1 chr10 32900318 33005792 +1357532 ITGB1-DT chr10 32958437 33082102 +1357550 IATPR chr10 33096257 33116672 +1357554 NRP1 chr10 33177492 33336262 +1357888 AL121748.1 chr10 33211277 33213804 +1357892 AL353600.1 chr10 33341655 33341905 +1357895 AL353600.2 chr10 33384891 33390935 +1357899 LINC02628 chr10 33578931 33600040 +1357905 AL450313.1 chr10 33684755 33709868 +1357915 LINC00838 chr10 33759713 33772702 +1357938 LINC02629 chr10 33909238 33917804 +1357945 PARD3 chr10 34109560 34815325 +1358567 PARD3-AS1 chr10 34815767 34816386 +1358571 LINC02635 chr10 34969881 34975578 +1358582 CUL2 chr10 35008551 35090642 +1358964 AL392046.1 chr10 35098006 35127020 +1358979 CREM chr10 35126791 35212958 +1359574 AL117336.1 chr10 35210416 35210750 +1359577 LINC02634 chr10 35219894 35230598 +1359581 CCNY chr10 35247025 35572669 +1359755 AL117336.2 chr10 35314552 35336401 +1359769 AL603824.1 chr10 35443411 35444569 +1359773 AL121749.1 chr10 35604485 35608153 +1359779 GJD4 chr10 35605341 35608935 +1359789 FZD8 chr10 35638249 35642278 +1359797 AL121749.2 chr10 35641097 35647826 +1359803 PCAT5 chr10 35778302 35800920 +1359808 LINC02630 chr10 35896874 35898963 +1359812 AL355300.1 chr10 36089086 36089389 +1359816 AL590730.1 chr10 36438616 36442392 +1359824 AL390061.1 chr10 36940109 36943932 +1359828 ANKRD30A chr10 37125725 37384111 +1360158 AL157387.1 chr10 37240887 37242049 +1360163 MTRNR2L7 chr10 37601440 37602974 +1360171 AL132657.1 chr10 37775371 37784131 +1360176 ZNF248 chr10 37776526 37858106 +1360331 AL132657.2 chr10 37791580 37791937 +1360334 AL135791.1 chr10 37857740 37859110 +1360338 ZNF25 chr10 37949573 37976647 +1360372 ZNF25-DT chr10 37976825 37992467 +1360377 ZNF33A chr10 38010650 38065088 +1360481 ZNF37A chr10 38094334 38150293 +1360559 AL117339.4 chr10 38137337 38144399 +1360562 AL133216.1 chr10 38453181 38466176 +1360567 IGKV1OR10-1 chr10 42185339 42185791 +1360571 LINC00839 chr10 42475480 42495337 +1360614 ZNF33B chr10 42574185 42638570 +1360684 AL022345.4 chr10 42638314 42645542 +1360688 LINC01518 chr10 42644445 42691723 +1360709 LINC02632 chr10 42696012 42706453 +1360718 AL022344.1 chr10 42751178 42754297 +1360721 BMS1 chr10 42782795 42834937 +1360773 LINC02623 chr10 42871521 42874060 +1360777 LINC01264 chr10 42979017 42981507 +1360782 RET chr10 43077064 43130351 +1361004 AC010864.1 chr10 43136824 43138334 +1361007 CSGALNACT2 chr10 43138445 43185302 +1361029 RASGEF1A chr10 43194535 43266919 +1361142 LINC02633 chr10 43323665 43327932 +1361147 AC068707.1 chr10 43325833 43350792 +1361152 FXYD4 chr10 43371636 43376335 +1361212 HNRNPF chr10 43385617 43409166 +1361291 AL450326.1 chr10 43420738 43422100 +1361295 ZNF487 chr10 43436841 43483181 +1361364 ZNF239 chr10 43556344 43574618 +1361410 AL450326.3 chr10 43583498 43596625 +1361414 ZNF485 chr10 43606419 43617904 +1361461 ZNF32-AS3 chr10 43628817 43674703 +1361468 AL645634.2 chr10 43630882 43631564 +1361472 ZNF32 chr10 43643860 43648881 +1361498 ZNF32-AS1 chr10 43643872 43645047 +1361502 ZNF32-AS2 chr10 43645942 43648019 +1361507 AL645634.1 chr10 43665668 43667005 +1361511 LINC02658 chr10 43777562 43778825 +1361518 LINC00840 chr10 43778946 43901004 +1361612 LINC02659 chr10 43900874 43912369 +1361631 LINC00841 chr10 43909244 43981102 +1361674 AL139237.1 chr10 43912444 43914236 +1361678 AL137026.2 chr10 44259602 44261813 +1361682 AL137026.1 chr10 44282489 44293998 +1361696 C10orf142 chr10 44292569 44294649 +1361715 AL137026.3 chr10 44296805 44310237 +1361724 CXCL12 chr10 44370165 44386493 +1361804 AL356157.3 chr10 44509708 44515421 +1361809 AL356157.1 chr10 44591208 44602104 +1361813 TMEM72-AS1 chr10 44793119 44959709 +1361979 AL353801.2 chr10 44899614 44920220 +1361984 TMEM72 chr10 44911316 44937010 +1362017 AL353801.1 chr10 44937508 44955725 +1362021 AL353801.3 chr10 44958917 44959458 +1362024 RASSF4 chr10 44959407 44995891 +1362154 DEPP1 chr10 44970981 44978809 +1362174 C10orf25 chr10 44997698 45000888 +1362178 ZNF22 chr10 45000923 45005326 +1362188 AL358394.1 chr10 45164228 45181427 +1362192 OR13A1 chr10 45302298 45315608 +1362230 ALOX5 chr10 45374176 45446119 +1362342 AL731567.1 chr10 45444570 45453121 +1362347 MARCH8 chr10 45454585 45594906 +1362435 ZFAND4 chr10 45615500 45672780 +1362565 WASHC2C chr10 45727200 45792961 +1362988 AGAP4 chr10 45825594 45853875 +1363104 TIMM23 chr10 45972489 46003742 +1363124 NCOA4 chr10 46005088 46030714 +1363296 MSMB chr10 46033307 46048180 +1363336 ANTXRL chr10 46286345 46330207 +1363495 ANXA8L1 chr10 46375627 46391784 +1363631 LINC00842 chr10 46398362 46453306 +1363637 NPY4R chr10 46461099 46465958 +1363658 GPRIN2 chr10 46549044 46555530 +1363677 SYT15 chr10 46578217 46594173 +1363769 AL356056.2 chr10 46580708 46598150 +1363779 AL356056.1 chr10 46597918 46612154 +1363808 LINC02637 chr10 46632387 46635472 +1363814 FAM245B chr10 46721002 46751738 +1363827 PTPN20 chr10 46911396 47002488 +1364380 GDF10 chr10 47300197 47313577 +1364392 GDF2 chr10 47322454 47327588 +1364402 RBP3 chr10 47348363 47357881 +1364416 ZNF488 chr10 47365496 47384293 +1364437 ANXA8 chr10 47460162 47484158 +1364589 FAM25G chr10 47487219 47491693 +1364605 AL591684.1 chr10 47496212 47502195 +1364609 AGAP9 chr10 47501854 47523638 +1364631 LINC02675 chr10 47588681 47619480 +1364646 FO681492.1 chr10 47750864 47763592 +1364706 AC245041.2 chr10 47908064 47991877 +1364724 NPY4R2 chr10 47918739 47923524 +1364745 AC245041.1 chr10 47970043 47973496 +1364749 FAM25C chr10 47995322 47999791 +1364761 FRMPD2 chr10 48153088 48274696 +1365091 AC074325.1 chr10 48246525 48248512 +1365095 MAPK8 chr10 48306639 48439360 +1365363 ARHGAP22 chr10 48446034 48656265 +1365565 ARHGAP22-IT1 chr10 48510525 48511589 +1365569 AC068898.2 chr10 48624004 48625093 +1365573 AC068898.1 chr10 48664199 48672424 +1365577 WDFY4 chr10 48684876 48982956 +1365775 AC035139.2 chr10 48835541 48845945 +1365779 AC035139.1 chr10 48878022 48878649 +1365783 AC060234.3 chr10 48883955 48935213 +1365788 LRRC18 chr10 48909483 48914232 +1365798 AC060234.2 chr10 48976554 48993046 +1365809 AC060234.1 chr10 48984564 49018897 +1365813 VSTM4 chr10 49014236 49115522 +1365849 FAM170B-AS1 chr10 49121839 49151547 +1365872 FAM170B chr10 49131154 49134008 +1365882 TMEM273 chr10 49154725 49188585 +1365993 C10orf71-AS1 chr10 49296112 49299018 +1366000 C10orf71 chr10 49299170 49327492 +1366015 DRGX chr10 49364181 49396016 +1366052 AL138760.1 chr10 49419277 49472903 +1366056 ERCC6 chr10 49454470 49539538 +1366230 CHAT chr10 49609095 49665104 +1366520 SLC18A3 chr10 49610310 49612720 +1366528 C10orf53 chr10 49679651 49710261 +1366573 OGDHL chr10 49734641 49762379 +1366734 PARG chr10 49818279 49970203 +1366897 TIMM23B chr10 49942049 49974850 +1366960 TIMM23B-AGAP6 chr10 49942056 50011654 +1367006 AL442003.1 chr10 49981420 49988899 +1367012 AGAP6 chr10 49982190 50010499 +1367063 WASHC2A chr10 50067888 50133509 +1367466 ASAH2 chr10 50182778 50279720 +1367710 SGMS1 chr10 50305586 50625163 +1367845 AC069547.2 chr10 50325697 50341585 +1367850 AL117341.1 chr10 50472814 50474246 +1367854 SGMS1-AS1 chr10 50623466 50641451 +1367868 AL589794.2 chr10 50736078 50739434 +1367872 ASAH2B chr10 50739318 50816495 +1367987 A1CF chr10 50799409 50885675 +1368238 AL512366.1 chr10 50822692 50824525 +1368244 AL731537.2 chr10 50964270 50965220 +1368247 PRKG1 chr10 50990888 52298423 +1368457 AL731537.1 chr10 51062579 51068553 +1368461 AC022537.1 chr10 51244894 51245806 +1368466 AC069079.1 chr10 51302566 51306709 +1368470 CSTF2T chr10 51695486 51699595 +1368478 PRKG1-AS1 chr10 52230398 52314507 +1368519 DKK1 chr10 52314281 52318042 +1368545 LNCAROD chr10 52450874 52755507 +1368573 MBL2 chr10 52765380 52771700 +1368587 AC073174.1 chr10 52946431 52955585 +1368591 LINC02672 chr10 52972612 53030024 +1368608 AC036101.1 chr10 53291072 53311065 +1368612 PCDH15 chr10 53802771 55627942 +1370622 AL353784.1 chr10 54486230 54656051 +1370630 AC051618.1 chr10 54864674 54869122 +1370634 AC016822.1 chr10 55247755 55597233 +1370640 AL355314.1 chr10 55468327 55469222 +1370644 AL355314.2 chr10 55506219 55513217 +1370648 MTRNR2L5 chr10 55599042 55600728 +1370656 ZWINT chr10 56357227 56361273 +1370788 AC010996.1 chr10 56361479 56364714 +1370792 IPMK chr10 58191517 58267894 +1370810 CISD1 chr10 58269162 58289586 +1370837 AC016396.1 chr10 58304553 58305621 +1370841 AC016396.2 chr10 58325614 58327030 +1370844 UBE2D1 chr10 58334979 58370751 +1370887 TFAM chr10 58385345 58399220 +1370948 BICC1 chr10 58512872 58831435 +1371024 LINC00844 chr10 58999482 59066396 +1371080 PHYHIPL chr10 59176643 59247774 +1371131 FAM13C chr10 59246130 59363181 +1371515 AC025038.1 chr10 59282147 59282835 +1371519 AL355474.1 chr10 59357007 59364075 +1371524 AC026391.1 chr10 59578467 59650345 +1371542 SLC16A9 chr10 59650761 59736002 +1371581 MRLN chr10 59736692 59756041 +1371667 CCDC6 chr10 59788747 59906556 +1371698 LINC01553 chr10 59955430 59960913 +1371708 ANK3 chr10 60026298 60733490 +1372441 AL592430.1 chr10 60050668 60060743 +1372448 AL592430.2 chr10 60139912 60140877 +1372452 ANK3-DT chr10 60734342 60741828 +1372456 CDK1 chr10 60778331 60794852 +1372585 RHOBTB1 chr10 60869438 61001440 +1372657 LINC00845 chr10 61016275 61026420 +1372661 TMEM26 chr10 61406642 61453381 +1372731 TMEM26-AS1 chr10 61452639 61481956 +1372736 AL356952.1 chr10 61493843 61496499 +1372740 CABCOCO1 chr10 61662961 61766766 +1372790 AL451049.1 chr10 61684892 61685388 +1372793 LINC02625 chr10 61781745 61821246 +1372800 ARID5B chr10 61901684 62096944 +1372864 RTKN2 chr10 62183035 62268844 +1372932 LINC02621 chr10 62289521 62304033 +1372937 AC024597.1 chr10 62339553 62375166 +1372962 ZNF365 chr10 62374192 62670301 +1373023 AC067752.1 chr10 62520448 62672011 +1373070 AC067751.1 chr10 62682652 62805887 +1373080 ADO chr10 62804720 62808479 +1373088 EGR2 chr10 62811996 62919900 +1373143 AL590502.1 chr10 63123929 63125587 +1373148 NRBF2 chr10 63133247 63155031 +1373173 JMJD1C chr10 63167221 63521850 +1373417 JMJD1C-AS1 chr10 63465229 63466563 +1373420 REEP3 chr10 63521401 63625128 +1373457 AC022387.2 chr10 63630672 63655769 +1373462 AC013287.1 chr10 63664664 64693446 +1373485 AC012558.1 chr10 64036345 64037280 +1373489 LINC02671 chr10 64901136 65017639 +1373497 AL513321.2 chr10 65123667 65141185 +1373505 AL592466.1 chr10 65271319 65315080 +1373516 LINC01515 chr10 65570338 65880289 +1373801 CTNNA3 chr10 65912523 67696195 +1373880 AC022017.1 chr10 66079243 66118326 +1373887 LRRTM3 chr10 66926036 67101551 +1373907 AL139240.1 chr10 67052609 67055028 +1373911 DNAJC12 chr10 67796669 67838188 +1373983 AL133551.1 chr10 67849525 67850746 +1373986 SIRT1 chr10 67884656 67918390 +1374077 HERC4 chr10 67921899 68075348 +1374461 MYPN chr10 68106117 68212017 +1374673 ATOH7 chr10 68230595 68232113 +1374681 LINC02640 chr10 68233251 68242379 +1374689 PBLD chr10 68282660 68333049 +1374803 HNRNPH3 chr10 68331174 68343191 +1374915 RUFY2 chr10 68341107 68407294 +1375154 DNA2 chr10 68414064 68472121 +1375375 SLC25A16 chr10 68477998 68527523 +1375469 TET1 chr10 68560337 68694487 +1375499 AL513534.2 chr10 68698500 68700794 +1375502 CCAR1 chr10 68721012 68792377 +1375994 STOX1 chr10 68827531 68895432 +1376057 AL359844.1 chr10 68896920 68900768 +1376061 DDX50 chr10 68901286 68946847 +1376196 DDX21 chr10 68956170 68985068 +1376267 KIF1BP chr10 68988721 69043544 +1376490 SRGN chr10 69088103 69104805 +1376505 VPS26A chr10 69123512 69174412 +1376636 SUPV3L1 chr10 69180234 69209099 +1376718 AL596223.1 chr10 69215333 69232490 +1376725 HKDC1 chr10 69220332 69267552 +1376773 AL596223.2 chr10 69265342 69268148 +1376777 HK1 chr10 69269984 69401884 +1377204 TACR2 chr10 69403903 69416918 +1377247 TSPAN15 chr10 69451465 69507666 +1377320 AC016821.1 chr10 69510166 69544257 +1377325 NEUROG3 chr10 69571698 69573422 +1377335 AL450311.1 chr10 69575807 69577154 +1377339 FAM241B chr10 69630247 69633596 +1377368 LINC02651 chr10 69684899 69692452 +1377374 COL13A1 chr10 69801867 69964275 +1378233 LINC02636 chr10 69994276 70019496 +1378262 H2AFY2 chr10 70052846 70112282 +1378303 AIFM2 chr10 70098223 70132934 +1378378 TYSND1 chr10 70137981 70146700 +1378410 SAR1A chr10 70147289 70170523 +1378527 PPA1 chr10 70202835 70233911 +1378606 NPFFR1 chr10 70247329 70284004 +1378620 LRRC20 chr10 70298970 70382650 +1378717 EIF4EBP2 chr10 70404145 70428618 +1378729 NODAL chr10 70431936 70447951 +1378750 PALD1 chr10 70478767 70568450 +1378796 PRF1 chr10 70597348 70602759 +1378833 ADAMTS14 chr10 70672506 70762441 +1378931 TBATA chr10 70771239 70785401 +1378989 SGPL1 chr10 70815948 70881184 +1379074 PCBD1 chr10 70882280 70888565 +1379097 AC073176.2 chr10 70927055 71077810 +1379104 AC073176.1 chr10 70929925 70932057 +1379108 LINC02622 chr10 70939036 70955947 +1379122 UNC5B chr10 71212570 71302864 +1379199 UNC5B-AS1 chr10 71217224 71218228 +1379206 SLC29A3 chr10 71319259 71381423 +1379413 CDH23 chr10 71396920 71815947 +1380354 CDH23-AS1 chr10 71508153 71511873 +1380359 C10orf105 chr10 71711701 71737824 +1380378 VSIR chr10 71747556 71773520 +1380407 PSAP chr10 71816298 71851325 +1380517 AC073370.1 chr10 71878356 71879107 +1380521 CHST3 chr10 71964395 72013558 +1380533 AC022392.1 chr10 72053294 72054037 +1380536 SPOCK2 chr10 72059034 72089032 +1380658 ASCC1 chr10 72096032 72217134 +1381112 ANAPC16 chr10 72216000 72235860 +1381160 DDIT4 chr10 72273924 72276036 +1381178 DDIT4-AS1 chr10 72274915 72275980 +1381182 DNAJB12 chr10 72332830 72355149 +1381291 MICU1 chr10 72367327 72626191 +1381537 AC091769.2 chr10 72467749 72473304 +1381541 AL513185.1 chr10 72501746 72502956 +1381545 MCU chr10 72692131 72887694 +1381714 AC016542.1 chr10 72766560 72767052 +1381717 OIT3 chr10 72893584 72933036 +1381762 PLA2G12B chr10 72934762 72954806 +1381776 P4HA1 chr10 73007217 73096974 +1381955 AL731563.2 chr10 73071295 73074008 +1381959 AL731563.3 chr10 73098044 73101297 +1381963 NUDT13 chr10 73110375 73131828 +1382109 AC016394.2 chr10 73124573 73125532 +1382114 ECD chr10 73130155 73169055 +1382285 FAM149B1 chr10 73168119 73244504 +1382391 DNAJC9 chr10 73183362 73248268 +1382418 DNAJC9-AS1 chr10 73247360 73276984 +1382427 MRPS16 chr10 73248843 73252693 +1382462 AC016394.1 chr10 73252791 73254349 +1382473 CFAP70 chr10 73253759 73358859 +1382718 ANXA7 chr10 73375101 73414076 +1382809 AL512656.1 chr10 73381433 73383496 +1382813 MSS51 chr10 73423579 73433561 +1382869 PPP3CB chr10 73436428 73496024 +1383019 PPP3CB-AS1 chr10 73495525 73520070 +1383102 USP54 chr10 73497538 73625953 +1383361 AC073389.1 chr10 73625996 73626790 +1383364 AC073389.3 chr10 73630556 73631490 +1383367 MYOZ1 chr10 73631612 73641474 +1383385 SYNPO2L chr10 73644881 73663803 +1383417 AC073389.2 chr10 73653980 73675450 +1383431 AGAP5 chr10 73674285 73698159 +1383504 AC022400.4 chr10 73703735 73713581 +1383512 SEC24C chr10 73744372 73772161 +1383737 FUT11 chr10 73772276 73780251 +1383766 CHCHD1 chr10 73782047 73783652 +1383787 ZSWIM8 chr10 73785582 73801797 +1384347 ZSWIM8-AS1 chr10 73796514 73801399 +1384353 NDST2 chr10 73801911 73811798 +1384464 CAMK2G chr10 73812501 73874591 +1384907 AC022400.1 chr10 73813518 73814737 +1384911 AC022400.2 chr10 73841833 73847115 +1384915 PLAU chr10 73909177 73917496 +1384991 C10orf55 chr10 73909969 73922777 +1385011 VCL chr10 73995193 74121363 +1385192 AL596247.1 chr10 74005137 74027915 +1385196 AP3M1 chr10 74120255 74151063 +1385251 ADK chr10 74151202 74709963 +1385558 AC022540.1 chr10 74506081 74530553 +1385573 AC063962.1 chr10 74821610 74822130 +1385576 KAT6B chr10 74824927 75032624 +1386509 AC018511.2 chr10 75003055 75025174 +1386513 AC018511.1 chr10 75023475 75024251 +1386517 DUPD1 chr10 75037836 75058514 +1386528 AC018511.5 chr10 75041876 75055754 +1386534 DUSP13 chr10 75094432 75109221 +1386754 SAMD8 chr10 75099586 75182123 +1386851 VDAC2 chr10 75210154 75231448 +1387050 COMTD1 chr10 75233641 75236030 +1387111 ZNF503-AS1 chr10 75243568 75373500 +1387240 AC010997.3 chr10 75279726 75401246 +1387251 ZNF503 chr10 75397830 75401764 +1387261 ZNF503-AS2 chr10 75401519 75408982 +1387280 AC010997.5 chr10 75408973 75409326 +1387283 AC010997.4 chr10 75409142 75411842 +1387288 AC010997.2 chr10 75430571 75431588 +1387292 LRMDA chr10 75431624 76560168 +1387395 AL589863.2 chr10 75592644 75628120 +1387399 AL589863.1 chr10 75642476 75643106 +1387402 AL731568.1 chr10 75742740 75743755 +1387406 AC013286.1 chr10 76437408 76438775 +1387410 AC024603.1 chr10 76558350 76560994 +1387414 KCNMA1 chr10 76869601 77638369 +1391791 KCNMA1-AS1 chr10 76888044 76980624 +1391832 KCNMA1-AS2 chr10 77147652 77150100 +1391839 AL731575.1 chr10 77313941 77315694 +1391843 KCNMA1-AS3 chr10 77354404 77376613 +1391850 AL450306.1 chr10 77782866 77793176 +1391858 DLG5 chr10 77790791 77926755 +1392113 AL391421.1 chr10 77866875 77869610 +1392117 DLG5-AS1 chr10 77927372 77929824 +1392123 POLR3A chr10 77969251 78029515 +1392241 RPS24 chr10 78033760 78056813 +1392439 AL731555.1 chr10 78176928 78178186 +1392442 AC012560.1 chr10 78179174 78675109 +1392457 LINC00595 chr10 78179185 78551355 +1392551 AC010163.3 chr10 78288059 78290565 +1392555 AC010163.1 chr10 78293842 78301003 +1392559 AC010163.2 chr10 78352597 78356100 +1392563 AL583852.1 chr10 78538391 78551719 +1392568 AC016820.1 chr10 78696062 78697022 +1392572 ZMIZ1-AS1 chr10 78943328 79067895 +1392602 AL356753.1 chr10 79000484 79003803 +1392606 ZMIZ1 chr10 79068966 79316528 +1392734 PPIF chr10 79347469 79355334 +1392793 ZCCHC24 chr10 79382325 79445624 +1392820 AL133481.1 chr10 79382328 79409274 +1392824 AL133481.3 chr10 79504073 79506281 +1392828 EIF5AL1 chr10 79512601 79516440 +1392836 SFTPA2 chr10 79555852 79560407 +1392901 SFTPA1 chr10 79610939 79615455 +1392982 LINC02679 chr10 79628757 79632188 +1392990 AL132656.2 chr10 79660891 79677996 +1392997 NUTM2B-AS1 chr10 79661394 79826594 +1393133 AL132656.3 chr10 79663192 79664786 +1393136 NUTM2B chr10 79703227 79714681 +1393190 AL135925.1 chr10 79825902 79827602 +1393193 NUTM2E chr10 79841358 79850878 +1393230 AL512662.2 chr10 79904898 79951029 +1393245 SFTPD chr10 79937740 79982614 +1393282 SFTPD-AS1 chr10 79968213 79973213 +1393285 TMEM254-AS1 chr10 80046860 80078912 +1393304 TMEM254 chr10 80078646 80092557 +1393435 PLAC9 chr10 80131682 80145359 +1393476 ANXA11 chr10 80150889 80205572 +1393663 LINC00857 chr10 80207372 80219657 +1393676 MAT1A chr10 80271820 80289658 +1393721 AL359195.1 chr10 80333771 80334426 +1393725 DYDC1 chr10 80336105 80356755 +1393809 DYDC2 chr10 80344745 80368073 +1393907 PRXL2A chr10 80407829 80437115 +1394008 TSPAN14 chr10 80454166 80533124 +1394196 AC021028.1 chr10 80529597 80535942 +1394200 SH2D4B chr10 80537902 80646560 +1394266 LINC02655 chr10 80649797 80653732 +1394271 AL096706.1 chr10 81870778 81875133 +1394275 NRG3 chr10 81875194 82987179 +1394493 AC010157.2 chr10 82207620 82210345 +1394497 AC010157.1 chr10 82224213 82229179 +1394502 NRG3-AS1 chr10 82228985 82232920 +1394514 LINC02650 chr10 83672406 83677122 +1394521 AC069540.2 chr10 83708841 83724834 +1394526 AL390786.1 chr10 83911654 83912922 +1394530 AL603756.1 chr10 84138420 84140582 +1394533 GHITM chr10 84139509 84153568 +1394557 CERNA2 chr10 84167228 84172093 +1394561 C10orf99 chr10 84173801 84185294 +1394576 CDHR1 chr10 84194537 84219621 +1394716 LRIT2 chr10 84220495 84225589 +1394741 RGR chr10 84230666 84259960 +1395018 LRIT1 chr10 84231520 84241546 +1395032 LINC00858 chr10 84267747 84294659 +1395086 CCSER2 chr10 84328586 84518521 +1395245 LINC01519 chr10 85193421 85197958 +1395250 AL358787.1 chr10 85199002 85212800 +1395254 LINC02647 chr10 85378327 85432775 +1395273 AC025428.1 chr10 85432863 85448961 +1395278 LINC01520 chr10 85449592 85492001 +1395299 GRID1-AS1 chr10 85577731 85607213 +1395316 GRID1 chr10 85599552 86366795 +1395392 AC022028.2 chr10 85644073 85648066 +1395396 AL844892.2 chr10 86395187 86400943 +1395408 AL844892.1 chr10 86402119 86403201 +1395412 WAPL chr10 86435256 86521792 +1395575 AL731569.1 chr10 86521945 86525101 +1395579 OPN4 chr10 86654547 86666848 +1395657 LDB3 chr10 86668449 86736068 +1395873 AC067750.1 chr10 86749754 86756298 +1395876 BMPR1A chr10 86756601 86932838 +1396014 MMRN2 chr10 86935540 86969481 +1396094 SNCG chr10 86958599 86963258 +1396135 ADIRF-AS1 chr10 86965345 86971311 +1396149 ADIRF chr10 86968432 86983934 +1396181 AL136982.7 chr10 86970237 86970826 +1396185 AL136982.2 chr10 87009785 87015782 +1396189 FAM25A chr10 87020294 87024730 +1396201 GLUD1 chr10 87050202 87094843 +1396244 SHLD2 chr10 87094161 87191468 +1396302 AL136982.3 chr10 87113954 87115523 +1396306 NUTM2A-AS1 chr10 87201647 87342612 +1396500 AL157893.2 chr10 87203717 87206615 +1396504 NUTM2A chr10 87225448 87236908 +1396543 LINC00863 chr10 87341685 87357882 +1396574 NUTM2D chr10 87357668 87370695 +1396620 FAM245A chr10 87396561 87435035 +1396644 AL355334.2 chr10 87500337 87504837 +1396648 MINPP1 chr10 87504875 87553461 +1396694 AL138767.2 chr10 87591607 87606024 +1396698 AL138767.3 chr10 87607985 87659279 +1396704 AL138767.1 chr10 87610163 87660003 +1396710 PAPSS2 chr10 87659613 87747705 +1396779 ATAD1 chr10 87751512 87841343 +1396834 KLLN chr10 87859158 87863437 +1396842 PTEN chr10 87863625 87971930 +1396887 AC063965.2 chr10 87878692 87880427 +1396892 RNLS chr10 88273864 88584530 +1396951 LIPJ chr10 88586753 88606976 +1396993 LIPF chr10 88664441 88678814 +1397107 LIPK chr10 88724544 88752756 +1397130 LIPN chr10 88761406 88778242 +1397153 LIPM chr10 88802730 88820546 +1397199 ANKRD22 chr10 88819896 88851844 +1397220 STAMBPL1 chr10 88879734 88975153 +1397324 ACTA2-AS1 chr10 88932390 88940820 +1397340 ACTA2 chr10 88935074 88991339 +1397404 AL157394.3 chr10 88990045 88994249 +1397407 FAS chr10 88990531 89017059 +1397706 AL157394.1 chr10 89015836 89017059 +1397709 CH25H chr10 89205629 89207317 +1397717 LIPA chr10 89213569 89414557 +1397832 IFIT2 chr10 89283694 89309271 +1397868 AL353751.1 chr10 89283765 89292125 +1397882 IFIT3 chr10 89327997 89340971 +1397901 IFIT1B chr10 89378056 89385205 +1397911 IFIT1 chr10 89392546 89406487 +1397932 IFIT5 chr10 89414568 89420997 +1397942 SLC16A12 chr10 89430299 89556641 +1397973 SLC16A12-AS1 chr10 89456064 89468140 +1397982 PANK1 chr10 89579497 89645572 +1398046 AL157400.2 chr10 89645272 89652144 +1398062 AL157400.1 chr10 89646289 89650822 +1398066 AL157400.3 chr10 89667181 89701274 +1398080 AL157400.4 chr10 89694295 89697928 +1398084 KIF20B chr10 89701610 89774939 +1398263 LINC00865 chr10 89829483 89840861 +1398278 LINC01374 chr10 89853595 90225443 +1398287 LINC01375 chr10 89915489 89957373 +1398298 AL139340.1 chr10 90059061 90099083 +1398302 LINC02653 chr10 90402521 90628852 +1398315 AL391704.1 chr10 90454170 90502968 +1398328 AL391704.2 chr10 90462717 90467952 +1398333 AL390862.1 chr10 90622143 90623611 +1398336 HTR7 chr10 90740823 90858039 +1398372 RPP30 chr10 90871716 90908553 +1398517 ANKRD1 chr10 90912096 90921276 +1398541 AL365434.1 chr10 90994620 91006390 +1398545 AL365434.2 chr10 90997480 90997713 +1398548 LINC00502 chr10 91033157 91062164 +1398558 AL731553.1 chr10 91153669 91161315 +1398562 PCGF5 chr10 91163012 91284337 +1398646 HECTD2 chr10 91409280 91514829 +1398801 PPP1R3C chr10 91628442 91633071 +1398811 TNKS2-AS1 chr10 91782835 91798304 +1398824 TNKS2 chr10 91798426 91865475 +1398884 FGFBP3 chr10 91906584 91909486 +1398894 AL359198.1 chr10 91908131 91909348 +1398898 BTAF1 chr10 91923770 92030325 +1399079 CPEB3 chr10 92046692 92291078 +1399155 MARCH5 chr10 92291167 92353964 +1399186 AL161652.1 chr10 92423386 92427620 +1399190 IDE chr10 92451684 92574093 +1399429 KIF11 chr10 92593130 92655395 +1399479 HHEX chr10 92689955 92695647 +1399520 EXOC6 chr10 92826831 93059493 +1399820 AL358613.1 chr10 93059663 93060426 +1399824 CYP26C1 chr10 93060798 93069540 +1399859 AL358613.2 chr10 93071972 93073466 +1399863 CYP26A1 chr10 93073475 93077885 +1399930 MYOF chr10 93306429 93482334 +1400292 CEP55 chr10 93496612 93529092 +1400331 FFAR4 chr10 93566665 93604480 +1400367 RBP4 chr10 93591687 93601744 +1400435 PDE6C chr10 93612537 93666010 +1400489 FRA10AC1 chr10 93667883 93702592 +1400539 LGI1 chr10 93757840 93806272 +1400947 AL157396.1 chr10 93762453 93771991 +1400951 AL358154.1 chr10 93772681 93788605 +1400957 SLC35G1 chr10 93893973 93956062 +1401030 PLCE1 chr10 94030812 94332823 +1401238 PLCE1-AS2 chr10 94081950 94108814 +1401306 AL139118.1 chr10 94109116 94121107 +1401310 AL389885.1 chr10 94225160 94227288 +1401314 PLCE1-AS1 chr10 94278681 94287478 +1401331 AL139124.1 chr10 94314907 94315327 +1401334 NOC3L chr10 94333226 94362959 +1401397 TBC1D12 chr10 94402541 94536332 +1401437 HELLS chr10 94501434 94613905 +1401739 AL138759.1 chr10 94577439 94611238 +1401743 CYP2C18 chr10 94683729 94736190 +1401788 CYP2C19 chr10 94762681 94855547 +1401831 CYP2C9 chr10 94938658 94990091 +1401896 CYP2C8 chr10 95036772 95069497 +1402114 AL157834.1 chr10 95109136 95168425 +1402125 ACSM6 chr10 95194200 95228928 +1402226 AL157834.2 chr10 95228243 95231144 +1402230 PDLIM1 chr10 95237572 95291012 +1402268 SORBS1 chr10 95311771 95561414 +1403142 ALDH18A1 chr10 95605941 95656711 +1403242 TCTN3 chr10 95663396 95694143 +1403399 ENTPD1 chr10 95711779 95877266 +1403589 ENTPD1-AS1 chr10 95732976 96090250 +1403742 AL365273.1 chr10 95833508 95873758 +1403746 CC2D2B chr10 95907603 96032684 +1404056 CCNJ chr10 96043394 96060870 +1404108 AC021037.1 chr10 96129055 96130528 +1404111 ZNF518A chr10 96129715 96205288 +1404202 BLNK chr10 96191702 96271587 +1404402 AL136181.1 chr10 96292685 96306695 +1404408 DNTT chr10 96304409 96338564 +1404463 OPALIN chr10 96343221 96359365 +1404555 TLL2 chr10 96364608 96513926 +1404620 TM9SF3 chr10 96518110 96587452 +1404709 PIK3AP1 chr10 96593315 96720514 +1404832 LCOR chr10 96832282 96995959 +1404958 SLIT1 chr10 96998038 97185959 +1405209 SLIT1-AS1 chr10 97102756 97104355 +1405221 AL512424.1 chr10 97195907 97203721 +1405226 ARHGAP19 chr10 97222173 97292673 +1405365 FRAT1 chr10 97319271 97321915 +1405376 FRAT2 chr10 97332497 97334729 +1405384 AL355490.1 chr10 97334564 97343203 +1405388 RRP12 chr10 97356358 97426076 +1405766 AL355490.2 chr10 97401115 97419524 +1405770 PGAM1 chr10 97426191 97433444 +1405792 EXOSC1 chr10 97435909 97446017 +1405925 ZDHHC16 chr10 97446170 97457370 +1406236 MMS19 chr10 97458324 97498794 +1406797 UBTD1 chr10 97498924 97571206 +1406809 ANKRD2 chr10 97572499 97583884 +1406898 HOGA1 chr10 97584323 97612802 +1406944 C10orf62 chr10 97589721 97590934 +1406952 MORN4 chr10 97614553 97633500 +1406990 PI4K2A chr10 97640686 97676434 +1407014 AVPI1 chr10 97677424 97687241 +1407026 MARVELD1 chr10 97713173 97718150 +1407050 ZFYVE27 chr10 97737121 97760907 +1407255 SFRP5 chr10 97766751 97771999 +1407267 LINC00866 chr10 97828478 97849798 +1407272 GOLGA7B chr10 97849843 97871580 +1407302 CRTAC1 chr10 97865000 98030828 +1407445 R3HCC1L chr10 98134624 98244897 +1407572 LOXL4 chr10 98247690 98268194 +1407608 AL139241.1 chr10 98252023 98256575 +1407612 PYROXD2 chr10 98383565 98415182 +1407677 HPS1 chr10 98416198 98446947 +1407939 AL139243.1 chr10 98446346 98453805 +1407944 HPSE2 chr10 98457077 99235862 +1408084 CNNM1 chr10 99329356 99394330 +1408115 GOT1 chr10 99396870 99430624 +1408146 AL391684.1 chr10 99430919 99463259 +1408188 LINC01475 chr10 99526350 99531177 +1408199 AL513542.1 chr10 99526948 99528467 +1408203 NKX2-3 chr10 99532942 99536524 +1408224 SLC25A28 chr10 99610522 99620609 +1408255 AL353719.1 chr10 99621055 99621918 +1408258 AL133353.1 chr10 99651595 99659284 +1408263 ENTPD7 chr10 99659509 99711241 +1408304 CUTC chr10 99702558 99756134 +1408374 COX15 chr10 99711844 99732100 +1408424 ABCC2 chr10 99782640 99852594 +1408616 DNMBP chr10 99875577 100009947 +1408725 DNMBP-AS1 chr10 99927010 99959050 +1408745 CPN1 chr10 100042193 100081869 +1408782 ERLIN1 chr10 100150094 100186033 +1408864 CHUK chr10 100188300 100229596 +1408924 AL138921.2 chr10 100190036 100190747 +1408928 AL138921.1 chr10 100229629 100234398 +1408940 CWF19L1 chr10 100232298 100267680 +1409076 BLOC1S2 chr10 100273280 100286680 +1409145 PKD2L1 chr10 100288149 100330264 +1409236 AL139819.1 chr10 100335563 100346390 +1409242 SCD chr10 100347233 100364826 +1409260 OLMALINC chr10 100373099 100454043 +1409430 WNT8B chr10 100463009 100483744 +1409448 SEC31B chr10 100486646 100519864 +1409780 NDUFB8 chr10 100523740 100530000 +1409860 HIF1AN chr10 100529072 100559998 +1409919 PAX2 chr10 100735603 100829941 +1410071 AL138762.1 chr10 100911103 100912739 +1410074 SLF2 chr10 100912963 100965134 +1410237 AL133215.3 chr10 100967688 100968135 +1410240 MRPL43 chr10 100969458 100987515 +1410403 SEMA4G chr10 100969518 100985871 +1410617 AL133215.1 chr10 100980507 100985614 +1410621 TWNK chr10 100987367 100994403 +1410735 LZTS2 chr10 100996618 101007836 +1410801 PDZD7 chr10 101007679 101032295 +1410979 SFXN3 chr10 101031234 101041244 +1411073 AL133215.2 chr10 101060029 101061005 +1411076 KAZALD1 chr10 101061841 101068131 +1411112 TLX1NB chr10 101089321 101131126 +1411121 TLX1 chr10 101131300 101137789 +1411155 LINC01514 chr10 101176306 101194147 +1411189 LBX1 chr10 101226195 101229794 +1411199 LBX1-AS1 chr10 101229577 101270148 +1411222 LINC02681 chr10 101252821 101263550 +1411227 AL133387.1 chr10 101311018 101311505 +1411231 AL133387.2 chr10 101322485 101323394 +1411236 BTRC chr10 101354033 101557321 +1411371 DPCD chr10 101570560 101609662 +1411447 POLL chr10 101578882 101588270 +1411684 FBXW4 chr10 101610664 101695295 +1411750 AC010789.2 chr10 101694401 101705119 +1411754 AC010789.1 chr10 101701994 101730037 +1411766 FGF8 chr10 101770130 101780369 +1411866 NPM3 chr10 101781325 101783413 +1411900 OGA chr10 101784443 101818465 +1412076 KCNIP2-AS1 chr10 101818800 101828885 +1412081 KCNIP2 chr10 101825974 101843920 +1412317 ARMH3 chr10 101845599 102056193 +1412407 HPS6 chr10 102065390 102068038 +1412415 LDB1 chr10 102107560 102120453 +1412481 PPRC1 chr10 102132994 102150333 +1412584 NOLC1 chr10 102152176 102163871 +1412794 ELOVL3 chr10 102226299 102229589 +1412808 PITX3 chr10 102230186 102241512 +1412835 GBF1 chr10 102245532 102382899 +1412924 NFKB2 chr10 102394110 102402524 +1413220 PSD chr10 102402617 102421539 +1413374 FBXL15 chr10 102419189 102423136 +1413446 CUEDC2 chr10 102423245 102432584 +1413486 RPARP-AS1 chr10 102449816 102461106 +1413535 C10orf95 chr10 102449837 102451543 +1413545 MFSD13A chr10 102461395 102477045 +1413608 ACTR1A chr10 102461881 102502712 +1413703 AL121928.1 chr10 102483039 102483559 +1413706 SUFU chr10 102503987 102633535 +1413795 TRIM8 chr10 102642310 102660680 +1413954 AL391121.1 chr10 102642792 102644140 +1413957 ARL3 chr10 102673731 102714397 +1413975 SFXN2 chr10 102714538 102743492 +1414165 WBP1L chr10 102743948 102834516 +1414216 CYP17A1 chr10 102830531 102837472 +1414326 AL358790.1 chr10 102845761 102854513 +1414342 BORCS7 chr10 102854259 102864961 +1414379 AS3MT chr10 102869470 102901899 +1414440 AL356608.3 chr10 102898649 102918335 +1414445 AL356608.1 chr10 102914585 102915404 +1414448 CNNM2 chr10 102918294 103090222 +1414502 NT5C2 chr10 103088017 103193306 +1414743 RPEL1 chr10 103245887 103248016 +1414751 INA chr10 103277138 103290346 +1414763 PCGF6 chr10 103302796 103351144 +1414847 TAF5 chr10 103367976 103389065 +1414875 ATP5MD chr10 103389041 103396492 +1414949 PDCD11 chr10 103396626 103446294 +1415134 CALHM2 chr10 103446786 103452402 +1415178 AL139339.2 chr10 103450196 103450852 +1415181 AL139339.1 chr10 103452846 103462695 +1415185 CALHM1 chr10 103453387 103458888 +1415195 CALHM3 chr10 103472804 103479240 +1415207 NEURL1-AS1 chr10 103479603 103517393 +1415216 NEURL1 chr10 103493979 103592552 +1415255 AL121929.1 chr10 103549075 103550964 +1415259 AL121929.3 chr10 103573157 103583687 +1415264 SH3PXD2A chr10 103594027 103855543 +1415375 AL121929.2 chr10 103608619 103610050 +1415378 SH3PXD2A-AS1 chr10 103745966 103755423 +1415388 AL133355.1 chr10 103877374 103879761 +1415391 STN1 chr10 103877569 103918184 +1415459 SLK chr10 103967140 104029233 +1415555 COL17A1 chr10 104031286 104085880 +1415938 SFR1 chr10 104122058 104126385 +1415968 CFAP43 chr10 104129888 104232362 +1416227 GSTO1 chr10 104235356 104267459 +1416313 GSTO2 chr10 104268873 104304950 +1416386 ITPRIP chr10 104309698 104338465 +1416436 AL162742.1 chr10 104312141 104313881 +1416440 ITPRIP-AS1 chr10 104323369 104327004 +1416445 CFAP58-DT chr10 104351591 104353575 +1416449 CFAP58 chr10 104353833 104455102 +1416501 LINC02620 chr10 104474939 104480274 +1416506 AL161646.1 chr10 104566931 104624795 +1416520 SORCS3 chr10 104641290 105265242 +1416651 SORCS3-AS1 chr10 104664608 104666200 +1416655 LINC02627 chr10 105808225 105820349 +1416670 AL731574.1 chr10 105844834 105904771 +1416674 AL589166.1 chr10 105985679 105987727 +1416678 LINC02624 chr10 106140143 106188722 +1416699 SORCS1 chr10 106573663 107164534 +1416997 AL133395.1 chr10 106648899 106676780 +1417001 LINC01435 chr10 107694973 108197849 +1417165 AL353740.1 chr10 108547975 108561815 +1417170 LINC02661 chr10 108708539 108840686 +1417181 XPNPEP1 chr10 109864766 109923553 +1417528 ADD3-AS1 chr10 109940104 110008381 +1417556 ADD3 chr10 109996368 110135565 +1417747 MXI1 chr10 110207605 110287365 +1418370 AL360182.2 chr10 110207850 110208591 +1418375 SMNDC1 chr10 110290730 110304938 +1418423 AL355512.1 chr10 110428840 110496590 +1418435 DUSP5 chr10 110497907 110511533 +1418454 SMC3 chr10 110567691 110604636 +1418528 RBM20 chr10 110644336 110839468 +1418572 AL136368.1 chr10 110869743 110871594 +1418576 PDCD4-AS1 chr10 110869868 110872233 +1418580 PDCD4 chr10 110871795 110900006 +1418704 BBIP1 chr10 110898728 110919201 +1418872 AL158163.2 chr10 110907483 110908182 +1418875 AL158163.1 chr10 110910596 110912244 +1418878 SHOC2 chr10 110919547 111013667 +1418956 ADRA2A chr10 111077029 111080907 +1418964 AC021035.1 chr10 111349939 111352103 +1418968 AL136119.1 chr10 111787233 111989909 +1418973 GPAM chr10 112149865 112215377 +1419076 TECTB chr10 112283400 112305038 +1419183 ACSL5 chr10 112374018 112428380 +1419444 AL157786.1 chr10 112395813 112425589 +1419480 ZDHHC6 chr10 112424428 112446917 +1419575 VTI1A chr10 112446998 112818744 +1419652 AL139120.1 chr10 112671812 112677819 +1419657 AL158212.5 chr10 112810031 112821838 +1419662 AL158212.3 chr10 112823490 112827726 +1419665 AL158212.1 chr10 112888735 112906111 +1419670 TCF7L2 chr10 112950247 113167678 +1420260 AL158212.2 chr10 112950646 112951875 +1420264 AL133482.1 chr10 113482069 113492054 +1420268 HABP2 chr10 113550837 113589602 +1420334 NRAP chr10 113588716 113664127 +1420687 CASP7 chr10 113679162 113730907 +1420899 AL592546.2 chr10 113710681 113719332 +1420904 PLEKHS1 chr10 113751262 113783429 +1421088 DCLRE1A chr10 113834725 113854383 +1421140 NHLRC2 chr10 113854661 113917194 +1421171 AL592546.3 chr10 113865811 113869614 +1421175 ADRB1 chr10 114043866 114046904 +1421183 AC022023.2 chr10 114109856 114118700 +1421187 CCDC186 chr10 114120862 114174232 +1421313 TDRD1 chr10 114179270 114232304 +1421479 VWA2 chr10 114239254 114294489 +1421553 AC005383.1 chr10 114280725 114281258 +1421556 AFAP1L2 chr10 114294824 114404756 +1421683 ABLIM1 chr10 114431113 114768061 +1422233 AL137025.1 chr10 114764788 114794344 +1422273 FAM160B1 chr10 114821744 114899832 +1422372 TRUB1 chr10 114938195 114977676 +1422399 LINC02626 chr10 114994657 114996593 +1422404 ATRNL1 chr10 115093365 115948999 +1422644 AC016042.1 chr10 115123482 115218819 +1422649 GFRA1 chr10 116056925 116273467 +1422753 AC012470.1 chr10 116274270 116281071 +1422757 CCDC172 chr10 116324448 116380029 +1422789 PNLIPRP3 chr10 116427847 116477957 +1422819 PNLIP chr10 116545931 116567855 +1422855 PNLIPRP1 chr10 116590385 116609175 +1423115 C10orf82 chr10 116663696 116670264 +1423158 AC016825.1 chr10 116670034 116672750 +1423167 HSPA12A chr10 116671192 116850236 +1423258 ENO4 chr10 116849499 116911788 +1423373 SHTN1 chr10 116881477 117126586 +1423585 AC023283.1 chr10 117005462 117006416 +1423588 VAX1 chr10 117128521 117138301 +1423613 MIR3663HG chr10 117144564 117169108 +1423637 KCNK18 chr10 117197489 117210299 +1423648 AL731557.1 chr10 117239600 117241923 +1423653 SLC18A2 chr10 117241093 117279430 +1423707 AL391988.1 chr10 117267116 117268668 +1423710 PDZD8 chr10 117277274 117375440 +1423738 AC005871.2 chr10 117425194 117490419 +1423743 EMX2OS chr10 117473215 117545068 +1423780 EMX2 chr10 117542445 117549546 +1423812 AC005871.1 chr10 117562084 117572457 +1423817 AL356419.1 chr10 117579854 117593896 +1423823 LINC02674 chr10 117734510 117753329 +1423844 AL513324.1 chr10 117825894 117831244 +1423874 RAB11FIP2 chr10 118004916 118046941 +1423914 AC022395.1 chr10 118017487 118045810 +1423930 CASC2 chr10 118046279 118210158 +1423976 AL354863.1 chr10 118241468 118267710 +1424022 FAM204A chr10 118297925 118342328 +1424132 LINC00867 chr10 118341437 118398468 +1424166 PRLHR chr10 118589997 118595648 +1424183 CACUL1 chr10 118674167 118755249 +1424256 AL139407.1 chr10 118692361 118693535 +1424259 AL157388.1 chr10 118784563 119029544 +1424268 NANOS1 chr10 119029714 119033730 +1424281 EIF3A chr10 119033670 119080823 +1424386 DENND10 chr10 119104086 119137984 +1424495 SFXN4 chr10 119140767 119165714 +1424621 PRDX3 chr10 119167720 119178812 +1424647 GRK5 chr10 119207571 119459745 +1424689 GRK5-IT1 chr10 119208531 119211760 +1424693 AL583824.1 chr10 119330233 119336182 +1424704 RGS10 chr10 119499817 119542719 +1424755 TIAL1 chr10 119571802 119597029 +1424938 BAG3 chr10 119651370 119677819 +1424965 INPP5F chr10 119726042 119829147 +1425667 MCMBP chr10 119829404 119892556 +1425770 SEC23IP chr10 119892730 119944657 +1425869 PLPP4 chr10 120456954 120589855 +1425927 LINC01561 chr10 120597949 120600124 +1425932 AC023282.1 chr10 120608580 120825317 +1425988 WDR11-AS1 chr10 120759898 120851457 +1426033 AL391425.1 chr10 120842521 120845146 +1426037 WDR11 chr10 120851305 120909524 +1426312 AC010998.2 chr10 120879256 120880667 +1426316 AC010998.1 chr10 120925547 120980700 +1426320 AC010998.3 chr10 120984966 120985596 +1426323 LINC01153 chr10 121178700 121185966 +1426327 FGFR2 chr10 121478334 121598458 +1427044 AC009988.1 chr10 121615425 121615839 +1427048 AC025947.1 chr10 121736303 121739730 +1427053 ATE1 chr10 121740421 121928801 +1427242 AL731566.3 chr10 121956782 121957098 +1427245 NSMCE4A chr10 121957091 121975217 +1427345 AL731566.2 chr10 121965764 121967700 +1427348 TACC2 chr10 121989163 122254545 +1428055 AC063960.1 chr10 122017982 122019160 +1428059 AC063960.2 chr10 122145106 122155197 +1428080 BTBD16 chr10 122271296 122338170 +1428126 PLEKHA1 chr10 122374696 122442602 +1428302 BX842242.1 chr10 122435924 122461383 +1428310 ARMS2 chr10 122454653 122457352 +1428320 HTRA1 chr10 122458551 122514907 +1428382 DMBT1 chr10 122560665 122643740 +1429738 AL603764.2 chr10 122672850 122679494 +1429752 C10orf120 chr10 122697709 122699846 +1429775 CUZD1 chr10 122832158 122846175 +1429861 FAM24B chr10 122849078 122879641 +1429895 FAM24A chr10 122910610 122913111 +1429907 C10orf88 chr10 122930901 122954311 +1429940 PSTK chr10 122954381 122997513 +1430027 IKZF5 chr10 122990806 123008817 +1430071 ACADSB chr10 123008979 123058311 +1430132 HMX3 chr10 123135970 123139423 +1430142 HMX2 chr10 123148122 123150672 +1430152 BUB3 chr10 123154402 123170467 +1430225 LINC02641 chr10 123356450 123537767 +1430284 AL160290.1 chr10 123425713 123427640 +1430288 AL357127.2 chr10 123560326 123562213 +1430292 AL357127.1 chr10 123574227 123583767 +1430297 GPR26 chr10 123666355 123697399 +1430309 CPXM2 chr10 123706207 123940267 +1430402 AC009987.1 chr10 123776670 123777749 +1430406 AC068058.1 chr10 123913574 123931597 +1430411 BX469938.1 chr10 123943255 123944099 +1430415 CHST15 chr10 124007668 124093598 +1430485 OAT chr10 124397303 124418976 +1430565 NKX1-2 chr10 124445243 124450035 +1430575 AL445237.1 chr10 124447152 124450048 +1430582 LHPP chr10 124461823 124617888 +1430657 FAM53B chr10 124619292 124744378 +1430703 AL513190.1 chr10 124623353 124624079 +1430706 FAM53B-AS1 chr10 124703625 124714217 +1430717 EEF1AKMT2 chr10 124748149 124791887 +1430806 ABRAXAS2 chr10 124801819 124836667 +1430830 AL731577.2 chr10 124917143 124942881 +1430834 ZRANB1 chr10 124942123 124988189 +1430862 AL731577.1 chr10 124945204 124946432 +1430866 CTBP2 chr10 124984317 125161170 +1431069 AL731571.1 chr10 124996064 125001491 +1431072 AL157888.1 chr10 125162379 125162971 +1431075 TEX36-AS1 chr10 125574371 125578445 +1431086 TEX36 chr10 125576522 125683163 +1431124 AL158835.1 chr10 125683229 125709677 +1431176 EDRF1-DT chr10 125700436 125719566 +1431204 AL158835.2 chr10 125718771 125719365 +1431208 EDRF1 chr10 125719515 125764143 +1431566 EDRF1-AS1 chr10 125725634 125752110 +1431649 MMP21 chr10 125753580 125775821 +1431699 UROS chr10 125784980 125823258 +1432060 BCCIP chr10 125823546 125853695 +1432130 DHX32 chr10 125836337 125896436 +1432188 FANK1 chr10 125896539 126009592 +1432344 FANK1-AS1 chr10 125972188 125973126 +1432349 ADAM12 chr10 126012381 126388455 +1432481 AL589787.2 chr10 126393489 126398789 +1432485 LINC00601 chr10 126413869 126421879 +1432491 C10orf90 chr10 126424997 126798708 +1432622 AL589787.1 chr10 126425930 126460957 +1432631 DOCK1 chr10 126905409 127452517 +1432867 AL359094.1 chr10 126988095 127026507 +1432921 AL359094.2 chr10 127013501 127026475 +1432927 INSYN2A chr10 127135426 127196591 +1432971 NPS chr10 127549369 127552639 +1432982 FOXI2 chr10 127737185 127741183 +1432992 CLRN3 chr10 127877841 127892941 +1433004 PTPRE chr10 127907061 128085855 +1433232 AL158166.2 chr10 127929376 127934517 +1433236 AL158166.1 chr10 127934698 127936167 +1433240 AL390236.1 chr10 128026878 128029444 +1433244 MKI67 chr10 128096659 128126423 +1433325 LINC01163 chr10 128181032 128317726 +1433339 AL390763.1 chr10 128316282 128320214 +1433343 LINC02667 chr10 128912810 128916429 +1433370 AL355537.1 chr10 128958772 128960062 +1433375 AL355537.2 chr10 128965406 128968740 +1433379 AL391869.1 chr10 129278251 129291722 +1433383 AL359508.1 chr10 129372194 129380753 +1433388 MGMT chr10 129467190 129770983 +1433431 AL355531.1 chr10 129621988 129626664 +1433437 AL157832.2 chr10 129693722 129702117 +1433457 AL157832.1 chr10 129768844 129769435 +1433461 LINC02666 chr10 129784983 129806971 +1433470 EBF3 chr10 129835283 129963841 +1433558 AL354950.2 chr10 129837505 129837794 +1433561 AL354950.1 chr10 129845328 129845895 +1433564 AL354950.3 chr10 129857638 129867384 +1433571 C10orf143 chr10 130020025 130110830 +1433640 AL139123.1 chr10 130104569 130104998 +1433643 GLRX3 chr10 130136391 130184521 +1433741 LINC02646 chr10 130213488 130483193 +1433756 AC016816.1 chr10 130525712 130537406 +1433761 TCERG1L chr10 131092391 131311721 +1433804 TCERG1L-AS1 chr10 131095218 131095777 +1433808 LINC01164 chr10 131772398 131790199 +1433827 AL450307.1 chr10 131776386 131795277 +1433831 FP565171.1 chr10 131891640 131895297 +1433835 PPP2R2D chr10 131901008 131959834 +1433956 BNIP3 chr10 131966455 131982013 +1434005 AL162274.2 chr10 131971202 131971533 +1434008 AL162274.1 chr10 131980240 131981337 +1434011 JAKMIP3 chr10 132036336 132184858 +1435012 AL512622.1 chr10 132181225 132185962 +1435021 DPYSL4 chr10 132186948 132205759 +1435095 STK32C chr10 132207492 132331847 +1435197 LRRC27 chr10 132332154 132381508 +1435376 PWWP2B chr10 132397168 132417859 +1435399 AL451069.2 chr10 132419083 132420953 +1435403 AL451069.3 chr10 132433733 132441484 +1435407 C10orf91 chr10 132444327 132449408 +1435421 AL451069.1 chr10 132508394 132518367 +1435439 LINC01165 chr10 132520827 132522449 +1435442 INPP5A chr10 132537787 132783480 +1435570 NKX6-2 chr10 132783179 132786147 +1435585 CFAP46 chr10 132808392 132942823 +1435784 LINC01166 chr10 132943967 132965289 +1435788 LINC01167 chr10 132961340 132962237 +1435792 LINC01168 chr10 132965534 132976354 +1435804 ADGRA1 chr10 133070929 133131675 +1435873 ADGRA1-AS1 chr10 133083073 133088491 +1435892 KNDC1 chr10 133160219 133226412 +1436014 UTF1 chr10 133230217 133231558 +1436024 VENTX chr10 133237855 133241928 +1436036 MIR202HG chr10 133246478 133247891 +1436046 AL592071.1 chr10 133257144 133257551 +1436049 ADAM8 chr10 133262420 133276868 +1436270 TUBGCP2 chr10 133278630 133312337 +1436525 AL360181.2 chr10 133295187 133295977 +1436530 ZNF511 chr10 133308914 133313162 +1436573 CALY chr10 133324072 133336935 +1436623 AL360181.1 chr10 133345754 133350726 +1436627 PRAP1 chr10 133347368 133352683 +1436658 FUOM chr10 133355158 133358025 +1436734 ECHS1 chr10 133362485 133373354 +1436756 AL360181.4 chr10 133374736 133374869 +1436759 PAOX chr10 133379261 133391694 +1436889 MTG1 chr10 133394094 133422520 +1437008 SPRN chr10 133420666 133424572 +1437018 SCART1 chr10 133453928 133523558 +1437093 CYP2E1 chr10 133520406 133561220 +1437221 AL161645.1 chr10 133526259 133527513 +1437224 AL161645.2 chr10 133541809 133542575 +1437227 SYCE1 chr10 133553901 133569835 +1437342 AL731769.2 chr10 133565797 133629507 +1437361 AL731769.1 chr10 133588914 133589413 +1437364 FRG2B chr10 133623895 133626795 +1437391 AC069287.1 chr11 112967 125927 +1437400 LINC01001 chr11 127204 139612 +1437423 AC069287.3 chr11 129279 186136 +1437428 BET1L chr11 167784 207428 +1437510 SCGB1C1 chr11 193078 194575 +1437522 ODF3 chr11 196738 200261 +1437576 AC069287.2 chr11 203623 205470 +1437580 RIC8A chr11 207511 215113 +1437748 SIRT3 chr11 215030 236931 +1437958 PSMD13 chr11 236966 252984 +1438227 NLRP6 chr11 278365 285359 +1438272 AC136475.3 chr11 287305 288987 +1438283 PGGHG chr11 289126 296107 +1438430 IFITM5 chr11 298200 299526 +1438440 IFITM2 chr11 307631 315272 +1438495 AC136475.2 chr11 310139 311141 +1438499 IFITM1 chr11 313506 315272 +1438534 AC136475.1 chr11 318640 325631 +1438544 IFITM3 chr11 319676 327537 +1438585 AC136475.4 chr11 321991 322426 +1438589 AC136475.8 chr11 322186 322727 +1438593 AC136475.7 chr11 325703 326294 +1438596 AC136475.5 chr11 327171 330122 +1438607 AC136475.9 chr11 333192 333688 +1438610 B4GALNT4 chr11 369499 382117 +1438684 PKP3 chr11 392614 404908 +1438794 SIGIRR chr11 405716 417455 +1439019 ANO9 chr11 417933 442011 +1439148 PTDSS2 chr11 448268 491399 +1439265 AC138230.1 chr11 462930 463899 +1439269 RNH1 chr11 494512 507300 +1439650 AC137894.3 chr11 512513 518134 +1439654 AC137894.1 chr11 528907 529659 +1439658 HRAS chr11 532242 537287 +1439777 LRRC56 chr11 537527 554912 +1439811 LMNTD2 chr11 554850 560738 +1439892 AP006284.1 chr11 557595 560107 +1439906 RASSF7 chr11 560404 564025 +1439997 MIR210HG chr11 565660 568457 +1440013 PHRF1 chr11 576470 612222 +1440224 IRF7 chr11 612553 615983 +1440501 CDHR5 chr11 616565 626078 +1440707 SCT chr11 626309 627181 +1440721 DRD4 chr11 637269 640706 +1440739 DEAF1 chr11 644233 706715 +1440847 AC131934.1 chr11 665910 678391 +1440852 EPS8L2 chr11 694438 727727 +1441412 TMEM80 chr11 695428 705028 +1441491 AP006621.4 chr11 708564 727047 +1441495 TALDO1 chr11 747415 765012 +1441590 GATD1 chr11 767220 777488 +1441787 AP006621.3 chr11 777578 784297 +1441802 AP006621.2 chr11 781645 782105 +1441806 CEND1 chr11 787115 790113 +1441819 SLC25A22 chr11 790475 798281 +1442254 PANO1 chr11 797511 799185 +1442262 PIDD1 chr11 799179 809753 +1442472 RPLP2 chr11 809965 812880 +1442532 PNPLA2 chr11 818914 825573 +1442580 AP006621.1 chr11 823634 832883 +1442588 CRACR2B chr11 826144 831991 +1442721 CD151 chr11 832887 839831 +1443006 POLR2L chr11 837356 842529 +1443027 TSPAN4 chr11 842812 867116 +1443330 AP006623.1 chr11 856880 859795 +1443334 CHID1 chr11 867859 915058 +1443726 AP2A2 chr11 924894 1012245 +1444036 MUC6 chr11 1012823 1036718 +1444131 LINC02688 chr11 1049880 1055749 +1444139 MUC2 chr11 1074875 1110511 +1444202 MUC5AC chr11 1157953 1201138 +1444306 AC061979.1 chr11 1218530 1220242 +1444310 MUC5B chr11 1223066 1262172 +1444461 MUC5B-AS1 chr11 1242261 1249676 +1444465 TOLLIP chr11 1274371 1309654 +1444594 TOLLIP-AS1 chr11 1309769 1310707 +1444597 AC136297.1 chr11 1333250 1337068 +1444602 LINC02689 chr11 1350359 1364286 +1444609 BRSK2 chr11 1389899 1462689 +1445051 AC091196.1 chr11 1464582 1467632 +1445055 MOB2 chr11 1469457 1501247 +1445102 DUSP8 chr11 1554051 1572271 +1445145 KRTAP5-AS1 chr11 1571353 1599184 +1445161 KRTAP5-1 chr11 1584342 1585283 +1445169 KRTAP5-2 chr11 1597177 1598294 +1445177 KRTAP5-3 chr11 1607565 1608463 +1445185 KRTAP5-4 chr11 1620958 1622138 +1445201 KRTAP5-5 chr11 1629775 1630707 +1445209 AP006285.1 chr11 1662584 1663343 +1445213 FAM99A chr11 1665597 1667856 +1445225 FAM99B chr11 1683269 1685629 +1445230 LINC02708 chr11 1688297 1689056 +1445234 KRTAP5-6 chr11 1697195 1697755 +1445242 IFITM10 chr11 1732406 1750595 +1445273 CTSD chr11 1752755 1764573 +1445501 AC068580.3 chr11 1760348 1762486 +1445505 AC068580.1 chr11 1763009 1763749 +1445509 AC068580.5 chr11 1773745 1774903 +1445513 AC068580.2 chr11 1776930 1778388 +1445517 SYT8 chr11 1828307 1837521 +1445668 TNNI2 chr11 1838981 1841680 +1445766 LSP1 chr11 1852970 1892267 +1446048 AC051649.1 chr11 1864177 1866667 +1446052 PRR33 chr11 1888577 1891895 +1446060 LINC01150 chr11 1897015 1908656 +1446072 TNNT3 chr11 1919703 1938706 +1446570 MRPL23 chr11 1947278 1984522 +1446679 MRPL23-AS1 chr11 1983237 1989920 +1446685 LINC01219 chr11 1991096 1993670 +1446690 H19 chr11 1995176 2001470 +1446749 IGF2 chr11 2129112 2141238 +1446843 AC132217.2 chr11 2129112 2158391 +1446867 AC132217.1 chr11 2129121 2129964 +1446871 IGF2-AS chr11 2140501 2148666 +1446883 INS chr11 2159779 2161341 +1446930 TH chr11 2163929 2171877 +1447154 ASCL2 chr11 2268495 2270952 +1447164 C11orf21 chr11 2295645 2303049 +1447200 TSPAN32 chr11 2301997 2318200 +1447445 CD81-AS1 chr11 2328749 2377992 +1447454 CD81 chr11 2376177 2397419 +1447688 TSSC4 chr11 2400488 2403878 +1447791 AC124057.1 chr11 2404515 2407908 +1447795 TRPM5 chr11 2404515 2423045 +1448006 KCNQ1 chr11 2444684 2848991 +1448147 KCNQ1OT1 chr11 2608328 2699994 +1448150 KCNQ1-AS1 chr11 2840135 2861568 +1448155 KCNQ1DN chr11 2870033 2872105 +1448159 CDKN1C chr11 2883213 2885773 +1448224 SLC22A18AS chr11 2887344 2903575 +1448258 SLC22A18 chr11 2899721 2925246 +1448416 PHLDA2 chr11 2928273 2929420 +1448426 NAP1L4 chr11 2944431 2992377 +1448797 AC131971.1 chr11 2989863 2991344 +1448800 CARS chr11 3000922 3057613 +1449154 CARS-AS1 chr11 3029009 3041260 +1449161 AC108448.3 chr11 3057538 3064707 +1449165 OSBPL5 chr11 3087107 3166739 +1449543 AC108448.1 chr11 3189546 3189929 +1449547 MRGPRG chr11 3217944 3218813 +1449554 MRGPRG-AS1 chr11 3218332 3223131 +1449566 MRGPRE chr11 3225030 3232417 +1449576 AC109309.1 chr11 3226061 3232838 +1449581 AC123788.1 chr11 3336721 3340630 +1449585 ZNF195 chr11 3339261 3379222 +1449964 AC127526.1 chr11 3469319 3531328 +1449969 AC127526.5 chr11 3475280 3477065 +1449973 AC127526.2 chr11 3481520 3581211 +1449984 AC127526.4 chr11 3511559 3520886 +1449989 ART5 chr11 3638512 3642316 +1450047 ART1 chr11 3645128 3664416 +1450068 CHRNA10 chr11 3665587 3671384 +1450117 NUP98 chr11 3671083 3797792 +1450630 PGAP2 chr11 3797724 3826371 +1451120 RHOG chr11 3826978 3840959 +1451157 AC090587.1 chr11 3854318 3855509 +1451161 STIM1 chr11 3854527 4093210 +1451421 AC090587.2 chr11 3854612 3855399 +1451425 RRM1 chr11 4094707 4138932 +1451672 RRM1-AS1 chr11 4137116 4138257 +1451676 LINC02749 chr11 4179675 4202663 +1451684 SSU72P5 chr11 4233288 4233872 +1451691 SSU72P2 chr11 4242056 4242640 +1451698 SSU72P4 chr11 4287499 4288083 +1451705 SSU72P3 chr11 4329865 4330449 +1451712 SSU72P7 chr11 4338660 4339244 +1451719 OR52B4 chr11 4367263 4368386 +1451727 TRIM21 chr11 4384897 4393702 +1451756 OR52K2 chr11 4449295 4450361 +1451764 OR52K1 chr11 4482646 4493497 +1451790 OR52M1 chr11 4545191 4546144 +1451797 C11orf40 chr11 4571423 4577820 +1451803 OR52I2 chr11 4581743 4593340 +1451827 OR52I1 chr11 4593614 4596574 +1451844 TRIM68 chr11 4598672 4608231 +1451920 OR51D1 chr11 4637477 4643060 +1451937 OR51E1 chr11 4643420 4655488 +1451958 OR51E2 chr11 4680171 4697854 +1451986 OR51C1P chr11 4690423 4697831 +1451996 MMP26 chr11 4704927 4992429 +1452038 OR51F1 chr11 4768979 4769938 +1452051 OR52R1 chr11 4803433 4804380 +1452058 OR51F2 chr11 4821321 4822456 +1452072 OR51S1 chr11 4847489 4849238 +1452080 OR51T1 chr11 4881819 4882883 +1452093 OR51A7 chr11 4903783 4909462 +1452110 OR51G2 chr11 4912588 4919350 +1452127 OR51G1 chr11 4923374 4924339 +1452134 OR51A4 chr11 4942831 4947605 +1452151 OR51A2 chr11 4954772 4955713 +1452158 OR51L1 chr11 4994851 5005536 +1452185 OR52J3 chr11 5046526 5047461 +1452192 OR52E2 chr11 5058650 5059627 +1452199 AC113331.1 chr11 5106062 5107530 +1452203 OR52A5 chr11 5128776 5138356 +1452222 OR52A1 chr11 5143219 5154757 +1452238 OR51V1 chr11 5199735 5200700 +1452251 AC104389.2 chr11 5205041 5207308 +1452255 HBB chr11 5225464 5229395 +1452312 HBD chr11 5232678 5243657 +1452364 BGLT3 chr11 5244554 5245546 +1452367 HBG1 chr11 5248079 5249859 +1452393 HBG2 chr11 5253188 5505605 +1452427 AC104389.5 chr11 5254392 5678434 +1452473 HBE1 chr11 5268345 5505652 +1452513 OR51B4 chr11 5301014 5301946 +1452520 OR51B5 chr11 5303444 5505652 +1452558 OR51B2 chr11 5323359 5324297 +1452565 OR51B6 chr11 5351508 5352446 +1452572 OR51M1 chr11 5383812 5393263 +1452595 OR51Q1 chr11 5422111 5423206 +1452603 OR51I1 chr11 5440570 5441514 +1452610 OR51I2 chr11 5449323 5456518 +1452627 OR52D1 chr11 5488685 5489749 +1452635 UBQLN3 chr11 5507300 5509958 +1452652 UBQLNL chr11 5514393 5516699 +1452660 OR52H1 chr11 5544489 5548533 +1452677 OR52B6 chr11 5580877 5581884 +1452684 TRIM6 chr11 5596109 5612958 +1452879 TRIM34 chr11 5619764 5644398 +1452933 TRIM5 chr11 5663195 5938619 +1453078 TRIM22 chr11 5689697 5737089 +1453208 OR56B1 chr11 5736448 5738523 +1453216 OR52N4 chr11 5754243 5755905 +1453233 OR52N5 chr11 5776165 5783355 +1453252 OR52N1 chr11 5786471 5791265 +1453268 OR52N2 chr11 5820314 5821348 +1453276 OR52E6 chr11 5840928 5841952 +1453291 OR52E8 chr11 5856674 5857734 +1453299 OR52E4 chr11 5880629 5887079 +1453316 OR52E5 chr11 5893208 5902730 +1453328 OR56A3 chr11 5938751 5951347 +1453367 OR56A5 chr11 5967177 5968494 +1453379 OR52L1 chr11 5985892 5986985 +1453387 OR56A4 chr11 5999445 6006946 +1453422 OR56A1 chr11 6019336 6034338 +1453455 OR56B4 chr11 6107684 6108835 +1453463 AC022762.1 chr11 6108135 6185576 +1453468 OR52B2 chr11 6169330 6170408 +1453476 OR52W1 chr11 6199146 6200259 +1453484 AC022762.2 chr11 6201901 6203253 +1453487 C11orf42 chr11 6205557 6211135 +1453499 FAM160A2 chr11 6211335 6234711 +1453588 CNGA4 chr11 6234765 6244479 +1453621 CCKBR chr11 6259806 6272127 +1453686 CAVIN3 chr11 6318946 6320532 +1453713 AC068733.3 chr11 6319140 6360454 +1453752 AC068733.1 chr11 6362799 6365267 +1453758 SMPD1 chr11 6390440 6394998 +1453870 APBB1 chr11 6395124 6419414 +1454445 HPX chr11 6431049 6442617 +1454546 TRIM3 chr11 6448613 6474459 +1454750 ARFIP2 chr11 6474683 6481479 +1454900 TIMM10B chr11 6481501 6484681 +1454948 DNHD1 chr11 6497260 6593758 +1455297 RRP8 chr11 6595072 6603616 +1455360 AC091564.2 chr11 6603642 6604420 +1455364 ILK chr11 6603708 6610874 +1455665 TAF10 chr11 6606294 6612539 +1455704 AC091564.3 chr11 6608667 6610135 +1455709 TPP1 chr11 6612768 6619448 +1456273 AC091564.6 chr11 6618790 6619764 +1456277 DCHS1 chr11 6621330 6655809 +1456325 AC091564.4 chr11 6621451 6622322 +1456329 AC091564.5 chr11 6630504 6658396 +1456338 MRPL17 chr11 6680385 6683340 +1456363 OR2AG2 chr11 6765626 6771976 +1456389 OR2AG1 chr11 6783020 6791558 +1456410 OR6A2 chr11 6791736 6799689 +1456427 AC087280.2 chr11 6821942 6926878 +1456433 OR10A5 chr11 6845652 6846705 +1456441 OR10A2 chr11 6863057 6874717 +1456458 OR10A4 chr11 6876625 6877619 +1456466 OR2D2 chr11 6891490 6892599 +1456474 OR2D3 chr11 6920974 6922043 +1456482 ZNF215 chr11 6926404 7001004 +1456613 ZNF214 chr11 6997085 7020346 +1456647 NLRP14 chr11 7020446 7071308 +1456677 RBMXL2 chr11 7088998 7091148 +1456685 AC027804.1 chr11 7222933 7230863 +1456689 SYT9 chr11 7238778 7469043 +1456749 AC107884.1 chr11 7418826 7513644 +1456827 OLFML1 chr11 7485388 7511377 +1456873 PPFIBP2 chr11 7513298 7657127 +1457276 AC107884.2 chr11 7568866 7572046 +1457280 CYB5R2 chr11 7665100 7677222 +1457443 OVCH2 chr11 7689438 7706421 +1457518 AC104237.2 chr11 7698951 7699393 +1457521 AC104237.3 chr11 7699562 7699988 +1457524 AC104237.1 chr11 7705288 7709517 +1457529 AC044810.2 chr11 7754393 7905955 +1457550 OR5P2 chr11 7795905 7796973 +1457558 OR5P3 chr11 7824818 7830840 +1457574 OR10A6 chr11 7924592 7931268 +1457607 OR10A3 chr11 7937171 7941708 +1457624 NLRP10 chr11 7957537 7965426 +1457641 EIF3F chr11 7970251 8001862 +1457737 CASC23 chr11 8011278 8016520 +1457742 TUB chr11 8019244 8106112 +1457832 AC116456.1 chr11 8035446 8039718 +1457839 TUB-AS1 chr11 8060038 8069373 +1457849 RIC3 chr11 8106056 8169055 +1457980 RIC3-DT chr11 8169167 8178903 +1457985 LMO1 chr11 8224309 8268716 +1458030 STK33 chr11 8391868 8594289 +1458320 TRIM66 chr11 8612037 8682694 +1458547 AC091053.2 chr11 8679089 8680913 +1458551 RPL27A chr11 8682788 8714759 +1458680 ST5 chr11 8693351 8910951 +1459531 AC091053.1 chr11 8693357 8696607 +1459535 AC026894.1 chr11 8768778 8810231 +1459548 AKIP1 chr11 8911139 8920084 +1459698 C11orf16 chr11 8920076 8933006 +1459765 ASCL3 chr11 8937579 8938211 +1459773 TMEM9B chr11 8947202 8965011 +1459841 TMEM9B-AS1 chr11 8964510 8977527 +1459863 NRIP3 chr11 8980576 9004049 +1459927 AC079296.1 chr11 9004093 9067776 +1459946 SCUBE2 chr11 9019498 9138114 +1460201 AC079296.2 chr11 9089283 9090456 +1460205 DENND5A chr11 9138825 9265350 +1460471 AP006259.1 chr11 9242448 9245509 +1460475 TMEM41B chr11 9280654 9314636 +1460588 IPO7 chr11 9384652 9448127 +1460689 AC132192.1 chr11 9430356 9433486 +1460693 AC132192.2 chr11 9459556 9460702 +1460696 ZNF143 chr11 9460319 9528524 +1461038 WEE1 chr11 9573670 9593457 +1461156 SWAP70 chr11 9664077 9752993 +1461276 LINC02709 chr11 9754770 9759533 +1461284 SBF2-AS1 chr11 9758268 9811335 +1461327 SBF2 chr11 9778667 10294207 +1461528 AC011092.2 chr11 9839143 9929263 +1461533 AC011092.3 chr11 9982753 10000290 +1461537 AC100763.1 chr11 10149192 10165109 +1461541 AC080023.1 chr11 10302657 10303704 +1461545 ADM chr11 10305073 10307397 +1461638 AMPD3 chr11 10308313 10507579 +1461958 MTRNR2L8 chr11 10507894 10509186 +1461966 RNF141 chr11 10511673 10541230 +1462029 MRVI1-AS1 chr11 10541258 10599936 +1462055 LYVE1 chr11 10556966 10611689 +1462107 MRVI1 chr11 10573091 10693988 +1462617 CTR9 chr11 10751246 10801625 +1462714 EIF4G2 chr11 10797050 10808940 +1463225 AC116535.1 chr11 10809204 10822931 +1463230 ZBED5 chr11 10812074 10858796 +1463307 ZBED5-AS1 chr11 10858179 10908972 +1463341 AC069360.1 chr11 10884158 10899364 +1463354 LINC02752 chr11 11020883 11183611 +1463371 KC877392.1 chr11 11243188 11243715 +1463375 GALNT18 chr11 11270877 11622005 +1463407 CSNK2A3 chr11 11351942 11353250 +1463415 AC023946.1 chr11 11352426 11353307 +1463419 AC104031.1 chr11 11570084 11573782 +1463423 AC104383.2 chr11 11781971 11811530 +1463427 USP47 chr11 11841423 11961887 +1463650 DKK3 chr11 11956207 12009769 +1463802 LINC02547 chr11 12030875 12061785 +1463806 AC124276.1 chr11 12066929 12073014 +1463810 AC124276.2 chr11 12086891 12089441 +1463814 MICAL2 chr11 12094008 12359144 +1464267 AC079329.1 chr11 12261426 12263173 +1464271 AC025300.1 chr11 12303533 12308216 +1464275 PARVA chr11 12377563 12535356 +1464350 AC009806.1 chr11 12538083 12540967 +1464354 AC107881.1 chr11 12619326 12668495 +1464360 TEAD1 chr11 12674421 12944737 +1464501 AC013549.3 chr11 12822435 12823667 +1464505 AC013549.4 chr11 12848795 12849433 +1464509 AC013549.1 chr11 12921186 12922925 +1464513 LINC00958 chr11 12961541 12989597 +1464582 RASSF10-DT chr11 13001090 13009159 +1464586 RASSF10 chr11 13009316 13012119 +1464594 AC013762.1 chr11 13054615 13134839 +1464598 ARNTL chr11 13276652 13387266 +1465007 BTBD10 chr11 13388001 13463297 +1465159 AC021269.3 chr11 13463377 13464717 +1465162 PTH chr11 13492054 13496181 +1465185 FAR1 chr11 13668668 13732346 +1465260 FAR1-IT1 chr11 13669327 13670149 +1465264 LINC02548 chr11 13784017 13848002 +1465313 AC027779.1 chr11 13826843 13879499 +1465317 LINC02545 chr11 13844862 13870616 +1465323 LINC02683 chr11 13921450 13924863 +1465327 SPON1 chr11 13962723 14268133 +1465368 SPON1-AS1 chr11 14262846 14273691 +1465372 RRAS2 chr11 14277922 14364506 +1465550 COPB1 chr11 14443440 14500027 +1465729 PSMA1 chr11 14504874 14643635 +1465872 PDE3B chr11 14643804 14872044 +1465958 CYP2R1 chr11 14877440 14892252 +1466059 CALCB chr11 14904997 15082342 +1466115 CALCA chr11 14966668 14972354 +1466191 INSC chr11 15112424 15247208 +1466387 LINC02751 chr11 15552855 15604169 +1466402 AC073172.1 chr11 15571817 15622447 +1466413 AC087379.2 chr11 15605484 15705376 +1466419 AC087379.1 chr11 15701265 15758898 +1466439 AC009869.1 chr11 15864452 15883653 +1466444 LINC02682 chr11 15910528 15930951 +1466514 SOX6 chr11 15966449 16739591 +1466824 AC103794.1 chr11 16023190 16031515 +1466828 C11orf58 chr11 16613132 16758340 +1466907 PLEKHA7 chr11 16777297 17014414 +1467253 RPS13 chr11 17074388 17077715 +1467331 PIK3C2A chr11 17077730 17207983 +1467444 NUCB2 chr11 17208153 17349980 +1467797 AC124798.2 chr11 17349053 17351703 +1467801 NCR3LG1 chr11 17351800 17377341 +1467834 AC124798.1 chr11 17380649 17383531 +1467837 KCNJ11 chr11 17385859 17389331 +1467871 ABCC8 chr11 17392498 17476879 +1470381 AC124798.3 chr11 17476595 17492367 +1470388 USH1C chr11 17493895 17544416 +1470680 OTOG chr11 17547373 17647150 +1470964 AC124301.1 chr11 17695010 17697556 +1470972 LINC02729 chr11 17695266 17696994 +1470986 MYOD1 chr11 17719571 17722136 +1470998 KCNC1 chr11 17734774 17856804 +1471101 SERGEF chr11 17788048 18013047 +1471443 TPH1 chr11 18017564 18042426 +1471507 SAAL1 chr11 18069935 18106087 +1471720 MRGPRX3 chr11 18120955 18138480 +1471748 AC090099.1 chr11 18140186 18189495 +1471752 AC090099.2 chr11 18142341 18145142 +1471756 MRGPRX4 chr11 18172837 18174280 +1471764 SAA4 chr11 18231355 18236802 +1471778 SAA2 chr11 18239223 18248643 +1471857 SAA1 chr11 18266260 18269977 +1471912 HPS5 chr11 18278668 18322198 +1472152 GTF2H1 chr11 18322295 18367045 +1472372 LDHA chr11 18394560 18408425 +1472706 AC084117.1 chr11 18405609 18406731 +1472710 LDHC chr11 18412318 18452063 +1472878 LDHAL6A chr11 18455824 18479601 +1472940 TSG101 chr11 18468336 18526951 +1473058 AC027544.2 chr11 18507608 18508820 +1473062 UEVLD chr11 18529609 18588747 +1473296 SPTY2D1OS chr11 18588781 18610255 +1473374 SPTY2D1 chr11 18606403 18634791 +1473401 TMEM86A chr11 18693122 18704785 +1473429 IGSF22 chr11 18704305 18726230 +1473556 AC103974.1 chr11 18706537 18740568 +1473561 PTPN5 chr11 18727928 18792721 +1473709 AC103974.2 chr11 18761664 18764965 +1473713 MRGPRX1 chr11 18933813 18939507 +1473728 AC023078.1 chr11 18934985 18939721 +1473732 MRGPRX2 chr11 19054455 19060717 +1473742 ZDHHC13 chr11 19117099 19176422 +1473861 CSRP3 chr11 19182030 19210571 +1473960 CSRP3-AS1 chr11 19196775 19281426 +1473966 E2F8 chr11 19224063 19241620 +1474074 AC009652.1 chr11 19299883 19308358 +1474084 NAV2 chr11 19350724 20121601 +1474723 NAV2-IT1 chr11 19380484 19385014 +1474727 NAV2-AS5 chr11 19502672 19507229 +1474736 NAV2-AS4 chr11 19510890 19519896 +1474741 AC009549.1 chr11 19710934 19712619 +1474744 NAV2-AS3 chr11 19978699 19981337 +1474748 NAV2-AS2 chr11 20043846 20049303 +1474752 NAV2-AS1 chr11 20119684 20120632 +1474756 DBX1 chr11 20156155 20160475 +1474770 HTATIP2 chr11 20363685 20383783 +1474885 PRMT3 chr11 20387558 20509338 +1475029 AC090707.2 chr11 20596522 20596979 +1475032 SLC6A5 chr11 20599400 20659285 +1475114 NELL1 chr11 20669551 21575686 +1475335 AC090707.1 chr11 20670425 20671297 +1475339 AC090857.2 chr11 21260061 21262570 +1475343 AC130307.1 chr11 21782659 21843210 +1475348 ANO5 chr11 21799934 22283357 +1475429 AC116534.1 chr11 22010402 22170001 +1475436 AC107882.1 chr11 22113448 22117001 +1475440 AC107886.1 chr11 22261209 22262256 +1475444 AC104009.1 chr11 22283730 22338245 +1475459 SLC17A6 chr11 22338381 22379503 +1475498 AC040936.1 chr11 22361213 22362294 +1475502 LINC01495 chr11 22445673 22492073 +1475518 AC055878.1 chr11 22492087 22510396 +1475527 FANCF chr11 22622890 22625841 +1475535 GAS2 chr11 22625509 22813055 +1475678 SVIP chr11 22813799 22830299 +1475711 AC006299.1 chr11 22829380 22945393 +1475736 CCDC179 chr11 22846922 22860474 +1475753 LINC02718 chr11 23154683 23203161 +1475788 LINC02726 chr11 23730588 23796970 +1475794 AC100768.1 chr11 23761330 23808255 +1475800 LINC02686 chr11 24235477 24262218 +1475812 LUZP2 chr11 24496970 25082638 +1475939 LINC02699 chr11 25734757 25782017 +1475964 AC013799.1 chr11 25924188 25926808 +1475968 ANO3 chr11 26188842 26663289 +1476225 AC021698.1 chr11 26244640 26269415 +1476230 ANO3-AS1 chr11 26285578 26331289 +1476237 MUC15 chr11 26559032 26572263 +1476310 SLC5A12 chr11 26667020 26723427 +1476430 FIBIN chr11 26994112 26997087 +1476438 BBOX1 chr11 27040725 27127809 +1476544 BBOX1-AS1 chr11 27047186 27220113 +1476568 CCDC34 chr11 27330827 27363234 +1476604 LGR4 chr11 27365961 27472790 +1476705 AC100771.2 chr11 27471729 27482433 +1476717 LIN7C chr11 27494418 27506769 +1476746 BDNF-AS chr11 27506830 27698231 +1477132 LINC00678 chr11 27617626 27634627 +1477142 BDNF chr11 27654893 27722058 +1477318 AC103796.1 chr11 27696312 27877648 +1477322 AC090159.1 chr11 27978669 28019575 +1477328 KIF18A chr11 28020619 28108156 +1477385 METTL15 chr11 28108248 28527041 +1477585 AC013714.1 chr11 28516832 28519341 +1477589 LINC02758 chr11 28679183 28683469 +1477594 LINC02742 chr11 28702607 29064322 +1477613 AC090791.1 chr11 29159956 29266734 +1477620 LINC02755 chr11 29335878 29989328 +1477649 AC090124.1 chr11 29445487 29457393 +1477657 AC110058.1 chr11 29482807 29552861 +1477665 LINC02546 chr11 29594326 29631515 +1477714 AC107973.1 chr11 29713909 29881714 +1477719 LINC01616 chr11 29980113 29982392 +1477722 KCNA4 chr11 30009730 30017030 +1477735 AL358944.1 chr11 30044053 30322988 +1477749 FSHB chr11 30231016 30235261 +1477781 ARL14EP chr11 30323104 30338223 +1477808 MPPED2 chr11 30384493 30586872 +1477892 AL353699.1 chr11 30425552 30429268 +1477896 MPPED2-AS1 chr11 30584130 30632583 +1477906 AL122014.1 chr11 30773913 30850559 +1477912 DCDC1 chr11 30830369 31369810 +1478222 AL137804.1 chr11 31305685 31314548 +1478228 DNAJC24 chr11 31369840 31432835 +1478328 IMMP1L chr11 31432401 31509645 +1478495 ELP4 chr11 31509755 31790324 +1479048 AC131571.1 chr11 31618124 31767953 +1479087 PAX6 chr11 31784779 31817961 +1480752 PAUPAR chr11 31812307 32002405 +1480823 AL035078.1 chr11 32035979 32041318 +1480831 AL035078.3 chr11 32052843 32053260 +1480835 AL035078.2 chr11 32064912 32072173 +1480840 RCN1 chr11 32090904 32105755 +1480899 AL078612.1 chr11 32097143 32105091 +1480903 AL078612.2 chr11 32132657 32143723 +1480914 WT1 chr11 32387775 32435885 +1481200 WT1-AS chr11 32435518 32458769 +1481227 EIF3M chr11 32583798 32606264 +1481413 CCDC73 chr11 32602246 32794658 +1481497 PRRG4 chr11 32829927 32858120 +1481515 QSER1 chr11 32892820 32993316 +1481630 DEPDC7 chr11 33015876 33033582 +1481684 TCP11L1 chr11 33039417 33105943 +1481867 LINC00294 chr11 33076149 33079454 +1481870 CSTF3 chr11 33077188 33162371 +1482028 CSTF3-DT chr11 33161657 33191598 +1482041 HIPK3 chr11 33256672 33357023 +1482204 KIAA1549L chr11 33376083 33674102 +1482355 AL049629.1 chr11 33665220 33696701 +1482361 C11orf91 chr11 33698261 33700801 +1482380 CD59 chr11 33703010 33736491 +1482597 FBXO3 chr11 33740939 33774543 +1482829 FBXO3-DT chr11 33774699 33775670 +1482838 AC113192.3 chr11 33776188 33779495 +1482842 LINC02722 chr11 33804768 33805641 +1482847 AC113192.1 chr11 33810145 33811178 +1482851 LINC02721 chr11 33813873 33822378 +1482856 LMO2 chr11 33858576 33892076 +1482907 AC132216.1 chr11 33880643 33881800 +1482912 AC090469.1 chr11 34049967 34052132 +1482916 CAPRIN1 chr11 34051731 34102610 +1483191 NAT10 chr11 34105617 34147670 +1483423 ABTB2 chr11 34150987 34358010 +1483468 CAT chr11 34438934 34472060 +1483534 ELF5 chr11 34478793 34513805 +1483621 AL137224.1 chr11 34533014 34557924 +1483626 LINC02707 chr11 34570876 34573982 +1483630 EHF chr11 34621093 34661057 +1483816 APIP chr11 34853094 34916379 +1483864 PDHX chr11 34915829 35020591 +1483980 AL356215.1 chr11 35132655 35138032 +1483991 CD44 chr11 35138870 35232402 +1484514 CD44-AS1 chr11 35210343 35214985 +1484518 AL133330.1 chr11 35212550 35214007 +1484522 SLC1A2 chr11 35251205 35420063 +1485416 AL133330.2 chr11 35281813 35286009 +1485420 AC090625.2 chr11 35419057 35421002 +1485424 PAMR1 chr11 35431823 35530300 +1485616 AL135934.1 chr11 35579430 35585310 +1485622 FJX1 chr11 35618460 35620865 +1485633 AL138812.1 chr11 35656694 35661339 +1485638 TRIM44 chr11 35662775 35818007 +1485659 AC090692.2 chr11 35824192 35838523 +1485664 AC090692.3 chr11 35894987 35897735 +1485668 AC090692.1 chr11 35915051 35918739 +1485676 LDLRAD3 chr11 35943981 36232136 +1485739 AL136146.2 chr11 35972428 35989007 +1485743 COMMD9 chr11 36269284 36289449 +1485810 PRR5L chr11 36296288 36465204 +1485995 AC087277.1 chr11 36321158 36323440 +1485999 AC087277.2 chr11 36386521 36388250 +1486003 AC009656.1 chr11 36425447 36426122 +1486007 TRAF6 chr11 36483769 36510272 +1486053 RAG1 chr11 36510709 36593156 +1486092 RAG2 chr11 36575574 36598279 +1486150 C11orf74 chr11 36594493 36659290 +1486301 LINC02760 chr11 37938601 37954663 +1486306 AC021713.1 chr11 38498995 38500186 +1486310 LINC02759 chr11 38618264 38646384 +1486341 LINC01493 chr11 38646451 38686323 +1486378 AC021723.2 chr11 39024631 39161638 +1486383 LRRC4C chr11 40114203 41459773 +1486463 AC090138.1 chr11 41394595 41426504 +1486468 LINC02741 chr11 41518895 41714492 +1486497 LINC01499 chr11 41714534 41857733 +1486535 AC023442.3 chr11 41855920 41875997 +1486547 AC023442.2 chr11 41876634 41877078 +1486551 LINC02745 chr11 41993381 42163851 +1486577 LINC02740 chr11 42183292 42253721 +1486615 API5 chr11 43311963 43344529 +1486824 AC087276.2 chr11 43328748 43359296 +1486830 TTC17 chr11 43358920 43494933 +1487019 AC087276.3 chr11 43378882 43385671 +1487023 AC087276.1 chr11 43390283 43395495 +1487027 AC068205.1 chr11 43556436 43673393 +1487045 MIR670HG chr11 43569306 43570395 +1487049 AC068205.2 chr11 43578889 43840030 +1487078 HSD17B12 chr11 43680680 43856617 +1487262 AC087521.2 chr11 43827517 43880726 +1487280 AC087521.4 chr11 43855913 43856404 +1487284 ALKBH3 chr11 43880811 43920274 +1487443 ALKBH3-AS1 chr11 43909289 43920944 +1487470 AC087521.3 chr11 43921059 44001157 +1487484 C11orf96 chr11 43925342 43943878 +1487504 AC087521.1 chr11 43943787 43947206 +1487508 ACCSL chr11 44047981 44059977 +1487575 ACCS chr11 44065925 44084237 +1487687 AC134775.1 chr11 44071462 44072403 +1487691 EXT2 chr11 44095673 44251981 +1487871 ALX4 chr11 44260440 44310139 +1487885 AC010768.4 chr11 44468464 44470429 +1487890 CD82 chr11 44564427 44620358 +1488080 AC010768.1 chr11 44604508 44605337 +1488084 AC010768.2 chr11 44606170 44608101 +1488090 LINC02704 chr11 44694863 44696301 +1488094 TSPAN18-AS1 chr11 44719392 44736692 +1488099 TSPAN18 chr11 44726465 44932423 +1488267 TP53I11 chr11 44885903 44951306 +1488593 LINC02685 chr11 44973770 44978028 +1488615 AC068858.1 chr11 45008266 45044053 +1488620 PRDM11 chr11 45095806 45235110 +1488712 AC103681.2 chr11 45215815 45235292 +1488716 SYT13 chr11 45240302 45286341 +1488762 AC103681.1 chr11 45253884 45254649 +1488770 LINC02696 chr11 45355371 45367490 +1488799 LINC02687 chr11 45371397 45388511 +1488810 AC103855.3 chr11 45387215 45513802 +1488815 AC018716.2 chr11 45397590 45412745 +1488828 AC018716.1 chr11 45399448 45400528 +1488832 AC103855.2 chr11 45486867 45542487 +1488873 AC103855.1 chr11 45582525 45583474 +1488877 CHST1 chr11 45647689 45665622 +1488898 AC087442.1 chr11 45651529 45652691 +1488902 AC044839.1 chr11 45722279 45748029 +1489196 AC044839.2 chr11 45733994 45735766 +1489200 LINC02690 chr11 45749454 45752279 +1489216 LINC02716 chr11 45771432 45772358 +1489220 SLC35C1 chr11 45804072 45813015 +1489255 AC044839.3 chr11 45813219 45825258 +1489260 CRY2 chr11 45847118 45883248 +1489409 MAPK8IP1 chr11 45885651 45906465 +1489471 AC068385.1 chr11 45905941 45906461 +1489475 C11orf94 chr11 45906513 45907272 +1489489 PEX16 chr11 45909663 45918812 +1489667 LARGE2 chr11 45921621 45929096 +1489844 PHF21A chr11 45929323 46121178 +1490142 AC024475.1 chr11 46116578 46117318 +1490146 AC024475.3 chr11 46123031 46177106 +1490169 LINC02710 chr11 46213150 46220438 +1490196 AC116021.1 chr11 46238382 46239267 +1490200 LINC02489 chr11 46256355 46274547 +1490204 CREB3L1 chr11 46277662 46321409 +1490269 DGKZ chr11 46332905 46380554 +1491010 MDK chr11 46380756 46383837 +1491159 CHRM4 chr11 46385098 46386608 +1491167 AMBRA1 chr11 46396414 46594125 +1491411 AC127035.1 chr11 46572948 46587808 +1491416 HARBI1 chr11 46602861 46617909 +1491442 ATG13 chr11 46617527 46674818 +1491912 ARHGAP1 chr11 46677080 46700619 +1492007 ZNF408 chr11 46701030 46705912 +1492036 F2 chr11 46719180 46739506 +1492128 CKAP5 chr11 46743048 46846308 +1492490 LRP4-AS1 chr11 46846412 46874421 +1492500 LRP4 chr11 46856717 46918642 +1492605 AC021573.1 chr11 46920880 46929320 +1492609 C11orf49 chr11 46936689 47164385 +1492913 AC090589.2 chr11 47123104 47130801 +1492917 ARFGAP2 chr11 47164299 47177125 +1493364 AC090589.3 chr11 47168281 47169563 +1493368 PACSIN3 chr11 47177522 47186443 +1493564 DDB2 chr11 47214465 47239240 +1493776 AC018410.2 chr11 47220218 47221751 +1493780 ACP2 chr11 47239302 47248906 +1494054 NR1H3 chr11 47248300 47269033 +1494468 MADD chr11 47269161 47330031 +1495243 AC018410.1 chr11 47270657 47272110 +1495252 MYBPC3 chr11 47331406 47352702 +1495531 SPI1 chr11 47354860 47378576 +1495584 AC090559.1 chr11 47381509 47409369 +1495607 SLC39A13 chr11 47407132 47416496 +1495781 PSMC3 chr11 47418769 47426473 +1496018 RAPSN chr11 47437764 47449143 +1496094 CELF1 chr11 47465933 47565569 +1496444 AC090559.2 chr11 47513605 47514889 +1496448 NDUFS3 chr11 47565336 47584562 +1496557 PTPMT1 chr11 47565430 47573461 +1496606 KBTBD4 chr11 47572197 47578976 +1496707 KF459542.1 chr11 47577725 47578277 +1496710 FAM180B chr11 47586693 47589194 +1496722 C1QTNF4 chr11 47589667 47594411 +1496739 MTCH2 chr11 47617315 47642607 +1496826 AGBL2 chr11 47659591 47715389 +1497067 FNBP4 chr11 47716494 47767443 +1497181 NUP160 chr11 47778087 47848555 +1497456 PTPRJ chr11 47980558 48170841 +1497677 PTPRJ-AS1 chr11 48014406 48015855 +1497681 OR4B1 chr11 48216810 48217739 +1497688 OR4X2 chr11 48245056 48246080 +1497696 OR4X1 chr11 48263861 48264778 +1497703 OR4S1 chr11 48306223 48307152 +1497710 OR4C3 chr11 48324920 48328471 +1497731 OR4C5 chr11 48365485 48366465 +1497738 OR4A47 chr11 48488717 48489780 +1497746 TRIM51GP chr11 48975324 48983826 +1497782 TRIM49B chr11 49027501 49038451 +1497823 TRIM64C chr11 49053714 49059112 +1497840 FOLH1 chr11 49145092 49208638 +1498125 OR4C13 chr11 49952391 49953419 +1498133 OR4C12 chr11 49981473 49982535 +1498141 AC109635.7 chr11 50184250 50208794 +1498145 AC109635.6 chr11 50213420 50223969 +1498150 LINC02750 chr11 50298579 50304656 +1498158 OR4C46 chr11 54603069 54603998 +1498165 OR4A5 chr11 54706832 54707902 +1498173 TRIM48 chr11 55262155 55271114 +1498191 OR4A16 chr11 55343151 55344231 +1498199 OR4A15 chr11 55367884 55368918 +1498212 OR4C15 chr11 55554307 55555419 +1498225 OR4C16 chr11 55572128 55573060 +1498232 OR4C11 chr11 55602360 55607645 +1498253 OR4P4 chr11 55635113 55640309 +1498269 OR4S2 chr11 55648327 55652854 +1498285 OR4C6 chr11 55662201 55666195 +1498302 AP006437.1 chr11 55684141 55686160 +1498306 OR5D3P chr11 55723776 55729621 +1498316 OR5D13 chr11 55773438 55774382 +1498323 OR5D14 chr11 55795556 55796500 +1498330 OR5L1 chr11 55811367 55812476 +1498338 OR5D18 chr11 55819607 55820597 +1498346 OR5L2 chr11 55827219 55828154 +1498353 OR5D16 chr11 55838752 55839738 +1498360 TRIM51 chr11 55883297 55891810 +1498395 OR5W2 chr11 55913650 55914582 +1498402 OR5I1 chr11 55935456 55936400 +1498409 OR10AG1 chr11 55965755 55969945 +1498426 OR5F1 chr11 55993681 55994625 +1498433 OR5AS1 chr11 56027654 56038191 +1498449 OR8I2 chr11 56093277 56094286 +1498457 OR8H2 chr11 56103687 56107658 +1498483 OR8H3 chr11 56122373 56123311 +1498490 OR8J3 chr11 56134721 56140201 +1498518 OR8K5 chr11 56159394 56160317 +1498525 OR5J2 chr11 56176618 56177556 +1498532 OR5T2 chr11 56231282 56234255 +1498549 OR5T3 chr11 56252200 56253222 +1498562 OR5T1 chr11 56274154 56276819 +1498581 OR8H1 chr11 56288462 56292254 +1498603 OR8K3 chr11 56315144 56320639 +1498630 OR8K1 chr11 56345945 56347031 +1498638 OR8J1 chr11 56354291 56361511 +1498658 OR8U1 chr11 56375624 56376553 +1498665 OR5R1 chr11 56417258 56418232 +1498672 OR5M9 chr11 56462469 56463401 +1498679 OR5M3 chr11 56469274 56473352 +1498696 OR5M8 chr11 56490349 56491395 +1498704 OR5M11 chr11 56542262 56543281 +1498712 OR5M10 chr11 56576736 56577787 +1498720 OR5M1 chr11 56609236 56614874 +1498736 OR5AP2 chr11 56641466 56642471 +1498744 OR5AR1 chr11 56663662 56664687 +1498752 OR9G1 chr11 56699095 56703884 +1498768 OR9G4 chr11 56741223 56748697 +1498799 LINC02735 chr11 56848478 56878078 +1498809 OR5AK2 chr11 56988872 56989867 +1498817 LRRC55 chr11 57181747 57191717 +1498836 APLNR chr11 57233577 57237314 +1498862 TNKS1BP1 chr11 57299638 57324952 +1498964 AP000781.1 chr11 57325603 57327958 +1498968 SSRP1 chr11 57325986 57335892 +1499065 P2RX3 chr11 57338352 57372396 +1499142 PRG3 chr11 57376769 57381150 +1499160 PRG2 chr11 57386780 57390650 +1499218 SLC43A3 chr11 57406954 57427580 +1499611 RTN4RL2 chr11 57460528 57477534 +1499644 AP002893.1 chr11 57476493 57477534 +1499648 SLC43A1 chr11 57484534 57515780 +1499826 TIMM10 chr11 57528464 57530803 +1499860 SMTNL1 chr11 57542641 57550274 +1499900 UBE2L6 chr11 57551656 57568284 +1499953 SERPING1 chr11 57597387 57614853 +1500131 AP000662.1 chr11 57638024 57652790 +1500150 YPEL4 chr11 57645087 57649944 +1500245 CLP1 chr11 57648992 57661865 +1500304 ZDHHC5 chr11 57667747 57701182 +1500417 MED19 chr11 57703714 57712323 +1500494 TMX2 chr11 57712593 57740973 +1500632 SELENOH chr11 57741250 57743554 +1500695 BTBD18 chr11 57743514 57751781 +1500725 CTNND1 chr11 57753243 57819546 +1502012 OR9Q1 chr11 58023881 58181616 +1502031 OR6Q1 chr11 58030930 58031931 +1502039 AP004247.2 chr11 58044110 58060138 +1502045 OR9I1 chr11 58116742 58125530 +1502074 OR9Q2 chr11 58189070 58194053 +1502091 OR1S2 chr11 58203202 58204181 +1502104 OR1S1 chr11 58212720 58216084 +1502120 OR10Q1 chr11 58227882 58228918 +1502128 OR10W1 chr11 58266792 58268260 +1502136 OR5B17 chr11 58358124 58359069 +1502143 OR5B3 chr11 58402464 58406874 +1502159 OR5B2 chr11 58421264 58428121 +1502178 OR5B12 chr11 58439077 58442758 +1502195 AP003557.2 chr11 58491773 58493480 +1502199 AP003557.1 chr11 58497888 58505758 +1502213 OR5B21 chr11 58507175 58508105 +1502220 LPXN chr11 58526871 58578220 +1502316 ZFP91 chr11 58579063 58621550 +1502344 AP001350.1 chr11 58611119 58612642 +1502347 CNTF chr11 58622665 58625733 +1502357 GLYAT chr11 58640426 58731974 +1502433 GLYATL2 chr11 58834065 58904215 +1502476 GLYATL1 chr11 58905398 59043527 +1502690 AP001652.1 chr11 58917015 58928689 +1502694 AP001636.3 chr11 58933643 59058659 +1502717 GLYATL1B chr11 59086307 59094786 +1502732 FAM111B chr11 59107185 59127412 +1502786 FAM111A-DT chr11 59130133 59143015 +1502810 FAM111A chr11 59142748 59155039 +1502910 DTX4 chr11 59171430 59208588 +1502967 MPEG1 chr11 59208510 59212927 +1502975 AP002358.1 chr11 59268876 59284033 +1502979 OR5AN1 chr11 59358895 59371714 +1503005 OR5A2 chr11 59416969 59426412 +1503031 OR5A1 chr11 59436469 59451380 +1503048 OR4D6 chr11 59456938 59457991 +1503056 OR4D10 chr11 59473315 59479361 +1503068 OR4D11 chr11 59503576 59504511 +1503075 OR4D9 chr11 59511368 59520703 +1503104 AP003778.1 chr11 59545602 59558882 +1503108 LINC02739 chr11 59560298 59566283 +1503123 AP000442.1 chr11 59565923 59639861 +1503141 OSBP chr11 59574398 59615774 +1503195 PATL1 chr11 59636716 59669037 +1503242 AP000640.2 chr11 59669312 59676041 +1503249 OR10V1 chr11 59712916 59713845 +1503256 STX3 chr11 59713456 59805882 +1503422 AP000640.1 chr11 59752578 59754975 +1503429 MRPL16 chr11 59806140 59810778 +1503461 CBLIF chr11 59829273 59845499 +1503519 TCN1 chr11 59852800 59866489 +1503563 OOSP3 chr11 59878809 59896481 +1503578 OOSP1 chr11 59938432 59957480 +1503609 OOSP4A chr11 59964033 59970146 +1503624 OOSP4B chr11 59978020 60031077 +1503657 OOSP2 chr11 60040409 60048044 +1503687 MS4A3 chr11 60056587 60071115 +1503782 MS4A2 chr11 60088261 60098467 +1503834 LINC02705 chr11 60159687 60160822 +1503839 MS4A6A chr11 60172014 60184666 +1504071 MS4A4A chr11 60185702 60317944 +1504185 MS4A4E chr11 60200270 60243137 +1504298 MS4A6E chr11 60334831 60396596 +1504336 MS4A7 chr11 60378485 60395951 +1504457 MS4A14 chr11 60378530 60417756 +1504611 MS4A5 chr11 60429572 60455214 +1504684 MS4A1 chr11 60455752 60470760 +1504828 MS4A12 chr11 60492778 60507430 +1504891 MS4A13 chr11 60515392 60542721 +1504954 MS4A8 chr11 60699585 60715807 +1505044 MS4A18 chr11 60729304 60744212 +1505076 MS4A15 chr11 60756867 60776733 +1505151 MS4A10 chr11 60785333 60801305 +1505173 AP000777.1 chr11 60813932 60821739 +1505178 AP000777.2 chr11 60835996 60842965 +1505182 AP000777.3 chr11 60841806 60851081 +1505186 CCDC86 chr11 60842113 60851081 +1505230 PTGDR2 chr11 60850933 60855950 +1505240 ZP1 chr11 60867562 60875693 +1505296 PRPF19 chr11 60890547 60906585 +1505407 AP003721.4 chr11 60906789 60909742 +1505411 AP003721.3 chr11 60913166 60914052 +1505415 TMEM109 chr11 60914158 60923443 +1505443 AP003721.1 chr11 60916339 60925397 +1505448 TMEM132A chr11 60924463 60937159 +1505573 SLC15A3 chr11 60937084 60952530 +1505668 CD6 chr11 60971680 61020377 +1505859 AP003721.2 chr11 61055392 61067597 +1505874 CD5 chr11 61102489 61127852 +1505915 VPS37C chr11 61130257 61161615 +1505952 PGA3 chr11 61203307 61213098 +1506031 PGA4 chr11 61222216 61231927 +1506099 PGA5 chr11 61241042 61251448 +1506158 VWCE chr11 61258286 61295316 +1506354 DDB1 chr11 61299451 61342596 +1506654 TKFC chr11 61333210 61353295 +1506841 CYB561A3 chr11 61348745 61362299 +1507074 TMEM138 chr11 61362344 61369509 +1507152 TMEM216 chr11 61392360 61398863 +1507207 CPSF7 chr11 61402641 61430031 +1507570 SDHAF2 chr11 61430042 61447529 +1507673 PPP1R32 chr11 61481120 61490931 +1507794 AP003108.1 chr11 61496440 61506649 +1507806 LRRC10B chr11 61508749 61511018 +1507814 SYT7 chr11 61515313 61581148 +1508055 AP003559.1 chr11 61539516 61542259 +1508059 AP002754.1 chr11 61588442 61607550 +1508089 AP002754.2 chr11 61654665 61655702 +1508093 DAGLA chr11 61680391 61747001 +1508184 MYRF-AS1 chr11 61746493 61757655 +1508201 MYRF chr11 61752642 61788518 +1508379 TMEM258 chr11 61768501 61792802 +1508465 FEN1 chr11 61792911 61797238 +1508489 FADS2 chr11 61792980 61867354 +1508710 FADS1 chr11 61799627 61829318 +1508994 FADS3 chr11 61873519 61892051 +1509191 RAB3IL1 chr11 61897301 61920269 +1509282 BEST1 chr11 61950063 61965515 +1509440 FTH1 chr11 61959718 61967634 +1509567 LINC02733 chr11 62049863 62082184 +1509575 AP002793.1 chr11 62116470 62123767 +1509579 INCENP chr11 62123998 62153169 +1509693 SCGB1D1 chr11 62190216 62193539 +1509705 SCGB2A1 chr11 62208673 62213943 +1509717 AP003306.1 chr11 62213427 62260549 +1509722 SCGB1D2 chr11 62242239 62244812 +1509734 SCGB2A2 chr11 62270158 62273160 +1509755 SCGB1D4 chr11 62296281 62299075 +1509767 AP003306.2 chr11 62336911 62338090 +1509771 ASRGL1 chr11 62337448 62393412 +1509893 AP003064.1 chr11 62391516 62393372 +1509897 SCGB1A1 chr11 62405103 62423195 +1509922 AP003064.2 chr11 62421845 62426724 +1509926 AHNAK chr11 62433542 62556235 +1510020 AP001363.1 chr11 62537312 62542018 +1510024 AP001363.2 chr11 62545999 62547699 +1510028 EEF1G chr11 62559596 62574086 +1510076 TUT1 chr11 62575045 62591637 +1510163 MTA2 chr11 62593214 62601865 +1510300 EML3 chr11 62602218 62612765 +1510708 AP001458.1 chr11 62606161 62606405 +1510712 ROM1 chr11 62611722 62615120 +1510754 B3GAT3 chr11 62615296 62622154 +1510831 GANAB chr11 62624826 62646726 +1511241 INTS5 chr11 62646848 62653302 +1511251 C11orf98 chr11 62662816 62665217 +1511280 LBHD1 chr11 62662817 62672255 +1511382 CSKMT chr11 62665309 62668496 +1511403 UQCC3 chr11 62670273 62673686 +1511424 UBXN1 chr11 62676498 62679117 +1511623 LRRN4CL chr11 62686406 62689530 +1511633 BSCL2 chr11 62690275 62709845 +1511989 GNG3 chr11 62707676 62709201 +1512001 HNRNPUL2 chr11 62712630 62727457 +1512038 TTC9C chr11 62728069 62740293 +1512096 ZBTB3 chr11 62748319 62754160 +1512120 POLR2G chr11 62761565 62766710 +1512246 AP001160.2 chr11 62771120 62771606 +1512249 TAF6L chr11 62771357 62787342 +1512337 TMEM223 chr11 62771629 62792006 +1512370 AP001160.3 chr11 62786023 62786785 +1512373 TMEM179B chr11 62787402 62790400 +1512419 NXF1 chr11 62792123 62806302 +1512721 STX5 chr11 62806860 62832051 +1512898 AP001160.4 chr11 62807682 62808063 +1512901 AP001160.1 chr11 62832234 62834043 +1512908 TEX54 chr11 62832319 62832803 +1512916 WDR74 chr11 62832342 62841809 +1513141 SNHG1 chr11 62851984 62855953 +1513563 SLC3A2 chr11 62856102 62888875 +1513856 CHRM1 chr11 62908679 62921807 +1513882 AP000438.1 chr11 62909546 62918361 +1513887 SLC22A6 chr11 62936385 62984983 +1514018 SLC22A8 chr11 62989154 63015841 +1514167 SLC22A24 chr11 63079940 63144221 +1514231 SLC22A10 chr11 63137867 63369718 +1514333 SLC22A25 chr11 63163776 63229652 +1514422 SLC22A9 chr11 63369785 63410294 +1514467 PLAAT5 chr11 63461404 63491194 +1514552 AP001591.1 chr11 63495484 63500610 +1514556 LGALS12 chr11 63506084 63516774 +1514664 PLAAT4 chr11 63536808 63546462 +1514709 PLAAT2 chr11 63552770 63563379 +1514723 PLAAT3 chr11 63573195 63616883 +1514779 AP000753.1 chr11 63616308 63621671 +1514783 ATL3 chr11 63624087 63671921 +1514861 AP000753.2 chr11 63637677 63658962 +1514866 RTN3 chr11 63681446 63759891 +1515054 C11orf95 chr11 63759892 63768775 +1515095 SPINDOC chr11 63813456 63827716 +1515131 MARK2 chr11 63838928 63911019 +1515584 RCOR2 chr11 63911230 63917164 +1515621 NAA40 chr11 63938959 63957319 +1515739 COX8A chr11 63974620 63976543 +1515749 OTUB1 chr11 63985853 64001811 +1515920 MACROD1 chr11 63998558 64166113 +1515984 AP000721.2 chr11 64035970 64103653 +1515991 AP006333.2 chr11 64081690 64087175 +1515996 FLRT1 chr11 64103188 64119173 +1516006 AP006333.1 chr11 64118272 64119210 +1516010 STIP1 chr11 64185272 64204543 +1516180 FERMT3 chr11 64206678 64223886 +1516310 TRPT1 chr11 64223799 64226254 +1516486 NUDT22 chr11 64225941 64230686 +1516590 AP001453.1 chr11 64229214 64234352 +1516597 DNAJC4 chr11 64230278 64234286 +1516705 VEGFB chr11 64234538 64238793 +1516755 FKBP2 chr11 64241003 64244134 +1516874 AP001453.3 chr11 64241144 64244134 +1516909 PPP1R14B chr11 64244479 64246943 +1516947 PPP1R14B-AS1 chr11 64245961 64248218 +1516960 AP001453.2 chr11 64246939 64249494 +1516966 PLCB3 chr11 64251523 64269150 +1517171 BAD chr11 64269830 64284704 +1517240 GPR137 chr11 64270062 64289500 +1517475 KCNK4 chr11 64291302 64300031 +1517588 CATSPERZ chr11 64300358 64304770 +1517620 ESRRA chr11 64305524 64316743 +1517710 TRMT112 chr11 64316460 64318084 +1517771 PRDX5 chr11 64318121 64321811 +1517817 AP003774.2 chr11 64325050 64329504 +1517822 CCDC88B chr11 64340204 64357534 +1518005 RPS6KA4 chr11 64359148 64372215 +1518179 LINC02723 chr11 64394342 64395831 +1518183 AP003774.1 chr11 64420311 64432670 +1518195 LINC02724 chr11 64449074 64451657 +1518199 AP005273.2 chr11 64486136 64490674 +1518204 AP005273.1 chr11 64500846 64505386 +1518209 SLC22A11 chr11 64555690 64572875 +1518315 SLC22A12 chr11 64590641 64602353 +1518435 NRXN2 chr11 64606174 64723188 +1518730 AP001092.1 chr11 64646399 64659681 +1518734 RASGRP2 chr11 64726911 64745456 +1519140 PYGM chr11 64746389 64759974 +1519239 SF1 chr11 64764606 64778786 +1519566 AP001462.1 chr11 64778954 64779405 +1519569 MAP4K2 chr11 64784918 64803241 +1519981 MEN1 chr11 64803510 64811294 +1520351 CDC42BPG chr11 64823052 64844653 +1520443 EHD1 chr11 64851642 64888296 +1520564 MIR194-2HG chr11 64889560 64893449 +1520568 ATG2A chr11 64894546 64917211 +1520762 PPP2R5B chr11 64917553 64934475 +1520832 GPHA2 chr11 64934471 64935893 +1520866 MAJIN chr11 64937517 64972108 +1520983 BATF2 chr11 64987945 64997018 +1521024 ARL2 chr11 65014160 65022184 +1521079 SNX15 chr11 65027439 65040572 +1521181 SAC3D1 chr11 65040901 65044828 +1521230 NAALADL1 chr11 65044818 65058553 +1521593 CDCA5 chr11 65066300 65084164 +1521703 ZFPL1 chr11 65084210 65088398 +1521855 TMEM262 chr11 65084979 65089375 +1521899 VPS51 chr11 65089324 65111862 +1522078 AP003068.1 chr11 65110714 65111695 +1522082 TM7SF2 chr11 65111845 65116396 +1522403 ZNHIT2 chr11 65116403 65117701 +1522418 AP003068.3 chr11 65117157 65117458 +1522422 FAU chr11 65120630 65122177 +1522527 SYVN1 chr11 65121780 65134533 +1522792 MRPL49 chr11 65122183 65127371 +1522875 SPDYC chr11 65170154 65173244 +1522895 AP003068.2 chr11 65177606 65181834 +1522902 CAPN1 chr11 65180566 65212006 +1523344 AP000944.6 chr11 65260996 65261748 +1523347 POLA2 chr11 65261920 65305589 +1523492 AP000944.7 chr11 65305406 65314244 +1523501 CDC42EP2 chr11 65314866 65322417 +1523520 DPF2 chr11 65333852 65354262 +1523665 TIGD3 chr11 65354751 65357613 +1523675 AP000944.1 chr11 65367438 65375299 +1523680 SLC25A45 chr11 65375192 65383701 +1523889 FRMD8 chr11 65386621 65413525 +1524018 NEAT1 chr11 65422774 65445540 +1524047 LINC02736 chr11 65487241 65488714 +1524062 AP000769.6 chr11 65487884 65488896 +1524066 MALAT1 chr11 65497688 65506516 +1524124 AP000769.2 chr11 65498010 65498405 +1524127 SCYL1 chr11 65525077 65538704 +1524460 LTBP3 chr11 65538805 65558930 +1524947 SSSCA1-AS1 chr11 65568482 65570423 +1524952 ZNRD2 chr11 65570460 65573942 +1525024 FAM89B chr11 65572349 65574198 +1525052 EHBP1L1 chr11 65576046 65592650 +1525187 KCNK7 chr11 65592855 65595996 +1525248 MAP3K11 chr11 65597756 65615382 +1525380 PCNX3 chr11 65615773 65637439 +1525484 SIPA1 chr11 65638101 65650918 +1525637 RELA chr11 65653597 65663090 +1526046 RELA-DT chr11 65663006 65671716 +1526063 KAT5 chr11 65711996 65719604 +1526328 RNASEH2C chr11 65714005 65720947 +1526433 AP001266.2 chr11 65745729 65771585 +1526437 AP5B1 chr11 65773898 65780976 +1526447 OVOL1 chr11 65787063 65797214 +1526476 OVOL1-AS1 chr11 65789051 65790868 +1526486 AP001266.1 chr11 65795946 65797219 +1526490 CFL1 chr11 65823022 65862026 +1526635 SNX32 chr11 65833834 65856896 +1526713 MUS81 chr11 65857126 65867653 +1526952 EFEMP2 chr11 65866441 65873592 +1527183 CTSW chr11 65879837 65883741 +1527248 FIBP chr11 65883741 65888539 +1527414 CCDC85B chr11 65890673 65891635 +1527422 FOSL1 chr11 65892049 65900573 +1527478 C11orf68 chr11 65916810 65919062 +1527504 DRAP1 chr11 65919274 65921563 +1527610 TSGA10IP chr11 65945445 65959963 +1527680 SART1 chr11 65961728 65980137 +1527772 EIF1AD chr11 65996545 66002176 +1527927 BANF1 chr11 66002228 66004149 +1527990 CST6 chr11 66012008 66013505 +1528002 CATSPER1 chr11 66016752 66026479 +1528039 GAL3ST3 chr11 66040765 66049161 +1528063 AP006287.3 chr11 66043298 66044381 +1528066 SF3B2 chr11 66050729 66069308 +1528293 AP006287.2 chr11 66067277 66069619 +1528297 PACS1 chr11 66070272 66244744 +1528497 AP000759.1 chr11 66244840 66246239 +1528501 KLC2 chr11 66257294 66267860 +1528787 AP001107.4 chr11 66259567 66261834 +1528792 AP001107.8 chr11 66264777 66265666 +1528797 AP001107.7 chr11 66267635 66268129 +1528801 RAB1B chr11 66268590 66277492 +1528834 AP001107.1 chr11 66269832 66278525 +1528838 AP001107.2 chr11 66276779 66277492 +1528845 CNIH2 chr11 66278175 66285301 +1528920 YIF1A chr11 66284580 66289145 +1529054 TMEM151A chr11 66291894 66296664 +1529064 AP001107.3 chr11 66312853 66319237 +1529068 CD248 chr11 66314494 66317044 +1529076 RIN1 chr11 66330241 66336840 +1529189 AP001107.6 chr11 66334494 66339875 +1529194 BRMS1 chr11 66337333 66345125 +1529332 B4GAT1 chr11 66345374 66347629 +1529342 AP001107.9 chr11 66347950 66364804 +1529358 SLC29A2 chr11 66362521 66372214 +1529564 AP001107.5 chr11 66409158 66417137 +1529579 NPAS4 chr11 66421004 66426707 +1529636 MRPL11 chr11 66435075 66466738 +1529714 PELI3 chr11 66466327 66477337 +1529848 AP002748.4 chr11 66473490 66480233 +1529866 DPP3 chr11 66480013 66509657 +1530134 BBS1 chr11 66510606 66533613 +1530555 AP002748.6 chr11 66514306 66519720 +1530559 ZDHHC24 chr11 66520637 66546235 +1530605 ACTN3 chr11 66546395 66563334 +1530715 AP002748.2 chr11 66558866 66560384 +1530719 CTSF chr11 66563464 66568841 +1530826 CCDC87 chr11 66590176 66593063 +1530834 CCS chr11 66593153 66606019 +1530935 RBM14 chr11 66616582 66627347 +1531002 RBM4 chr11 66638617 66668374 +1531132 RBM4B chr11 66664998 66677887 +1531205 SPTBN2 chr11 66685248 66729226 +1531617 C11orf80 chr11 66744451 66843328 +1532009 RCE1 chr11 66842835 66846552 +1532113 PC chr11 66848417 66958386 +1532688 LRFN4 chr11 66856647 66860475 +1532712 C11orf86 chr11 66975277 66977004 +1532722 SYT12 chr11 67006778 67050863 +1532815 RHOD chr11 67056847 67072017 +1532847 KDM2A chr11 67119263 67258082 +1533083 AP001885.3 chr11 67252336 67261545 +1533088 GRK2 chr11 67266473 67286556 +1533252 ANKRD13D chr11 67288547 67302485 +1533489 SSH3 chr11 67303478 67312607 +1533671 AP001885.2 chr11 67316539 67317431 +1533674 RAD9A chr11 67317871 67398410 +1533807 POLD4 chr11 67350772 67356972 +1533903 AP003419.2 chr11 67353629 67354348 +1533907 CLCF1 chr11 67364168 67374177 +1533930 AP003419.3 chr11 67374416 67374932 +1533933 PPP1CA chr11 67398183 67421183 +1534052 TBC1D10C chr11 67403915 67410089 +1534168 CARNS1 chr11 67414968 67425607 +1534265 RPS6KB2 chr11 67428460 67435401 +1534450 RPS6KB2-AS1 chr11 67431367 67435399 +1534454 PTPRCAP chr11 67435510 67437682 +1534464 CORO1B chr11 67435510 67443821 +1534629 GPR152 chr11 67451301 67452729 +1534637 CABP4 chr11 67452406 67460313 +1534699 TMEM134 chr11 67461710 67469272 +1534855 AIP chr11 67483026 67491103 +1534899 PITPNM1 chr11 67491768 67506263 +1535147 CDK2AP2 chr11 67506497 67508649 +1535192 CABP2 chr11 67518912 67524517 +1535266 GSTP1 chr11 67583595 67586656 +1535355 C11orf72 chr11 67602880 67606706 +1535363 AP003385.3 chr11 67605521 67606642 +1535367 NDUFV1 chr11 67605653 67612554 +1535684 NUDT8 chr11 67627938 67629937 +1535712 TBX10 chr11 67631303 67639560 +1535734 ACY3 chr11 67642555 67650730 +1535775 ALDH3B2 chr11 67662162 67681200 +1535886 LINC02754 chr11 67886477 67906350 +1535898 UNC93B1 chr11 67991100 68004982 +1535994 ALDH3B1 chr11 68008578 68029282 +1536182 AC004923.4 chr11 68024809 68030461 +1536188 NDUFS8 chr11 68030617 68036644 +1536347 TCIRG1 chr11 68039025 68050895 +1536581 AP002807.1 chr11 68050740 68053762 +1536593 CHKA chr11 68052859 68121444 +1536704 AP002992.1 chr11 68121624 68130518 +1536712 KMT5B chr11 68154863 68213828 +1536983 C11orf24 chr11 68261338 68272001 +1537044 AP002813.1 chr11 68272102 68284879 +1537049 LRP5 chr11 68312591 68449275 +1537176 PPP6R3 chr11 68460731 68615334 +1537814 AP003096.1 chr11 68612899 68616711 +1537826 GAL chr11 68683779 68691175 +1537846 TESMIN chr11 68707440 68751520 +1537936 CPT1A chr11 68754620 68844410 +1538155 LINC02701 chr11 68870664 68874542 +1538159 MRPL21 chr11 68891276 68903835 +1538287 IGHMBP2 chr11 68903842 68940602 +1538398 AP000808.1 chr11 68941503 68942852 +1538402 MRGPRD chr11 68980021 68980986 +1538409 AP003071.4 chr11 69000765 69002048 +1538412 AP003071.3 chr11 69004394 69005100 +1538416 MRGPRF chr11 69004395 69013382 +1538448 MRGPRF-AS1 chr11 69012283 69018447 +1538462 TPCN2 chr11 69048932 69136316 +1538751 AP003071.1 chr11 69103493 69109094 +1538755 AP003071.2 chr11 69147228 69171564 +1538760 SMIM38 chr11 69155478 69159752 +1538775 MYEOV chr11 69294151 69367726 +1538841 AP005233.2 chr11 69371463 69372512 +1538845 AP005233.1 chr11 69414307 69416832 +1538849 AP000439.2 chr11 69425690 69429621 +1538853 AP000439.1 chr11 69438365 69444743 +1538857 AP000439.3 chr11 69467598 69469705 +1538861 LINC02747 chr11 69475567 69481545 +1538868 LINC01488 chr11 69481662 69494952 +1538882 CCND1 chr11 69641087 69654474 +1538920 LTO1 chr11 69653076 69675416 +1539092 FGF19 chr11 69698238 69704022 +1539104 FGF4 chr11 69771022 69775341 +1539119 FGF3 chr11 69809968 69819416 +1539135 AP007216.1 chr11 69909184 69910994 +1539139 AP007216.2 chr11 69921638 69926813 +1539143 AP003555.2 chr11 69985876 70015815 +1539147 AP003555.1 chr11 70014858 70021059 +1539155 LINC02753 chr11 70056230 70065371 +1539162 LINC02584 chr11 70072434 70075433 +1539170 ANO1 chr11 70078302 70189528 +1539438 AP000879.2 chr11 70129297 70149623 +1539442 ANO1-AS1 chr11 70187788 70188509 +1539446 FADD chr11 70203163 70207390 +1539456 AP000879.1 chr11 70206291 70207390 +1539463 PPFIA1 chr11 70270700 70385312 +1540016 AP002336.2 chr11 70282367 70363368 +1540020 AP002336.1 chr11 70319928 70321415 +1540024 AP002336.3 chr11 70324871 70327209 +1540028 AP000487.2 chr11 70358198 70358677 +1540032 AP000487.1 chr11 70372246 70398488 +1540042 CTTN chr11 70398404 70436584 +1540246 SHANK2 chr11 70467856 71252577 +1540641 AP001271.1 chr11 70477277 70477592 +1540645 SHANK2-AS1 chr11 70626441 70635658 +1540654 SHANK2-AS2 chr11 70646165 70647562 +1540658 SHANK2-AS3 chr11 70862790 70865115 +1540663 AP003783.1 chr11 70886090 70896305 +1540669 DHCR7 chr11 71428193 71452868 +1540823 AP002387.2 chr11 71448674 71452157 +1540827 NADSYN1 chr11 71453109 71524107 +1541120 KRTAP5-7 chr11 71527267 71528669 +1541128 KRTAP5-8 chr11 71538025 71539209 +1541136 KRTAP5-9 chr11 71548418 71549553 +1541144 AP000867.5 chr11 71563389 71565608 +1541148 KRTAP5-10 chr11 71565563 71566735 +1541156 KRTAP5-11 chr11 71579714 71603353 +1541176 ALG1L9P chr11 71673885 71818238 +1541215 AP003498.1 chr11 71701268 71705404 +1541220 AP003498.2 chr11 71745331 71747051 +1541224 FAM86C1 chr11 71787510 71801237 +1541308 ZNF705E chr11 71814045 71821548 +1541324 DEFB108B chr11 71833200 71837710 +1541337 AP002495.1 chr11 71865509 71928654 +1541433 DEFB131B chr11 71878453 71884561 +1541442 RNF121 chr11 71929018 71997597 +1541639 IL18BP chr11 71998613 72005715 +1541831 NUMA1 chr11 72002864 72080693 +1542596 AP002490.1 chr11 72014291 72020910 +1542602 LRTOMT chr11 72080331 72110782 +1542943 LAMTOR1 chr11 72085895 72103297 +1543034 AP000812.4 chr11 72105924 72109329 +1543046 ANAPC15 chr11 72106378 72112780 +1543294 FOLR3 chr11 72114869 72139892 +1543364 AP000812.1 chr11 72163322 72209241 +1543369 FOLR1 chr11 72189558 72196323 +1543430 FOLR2 chr11 72216601 72221950 +1543569 INPPL1 chr11 72223701 72239147 +1543853 PHOX2A chr11 72239077 72245664 +1543876 AP000593.4 chr11 72261731 72290688 +1543880 CLPB chr11 72285495 72434680 +1544346 AP000593.3 chr11 72302139 72302965 +1544350 AP002892.2 chr11 72351347 72353210 +1544354 AP002892.1 chr11 72354516 72363555 +1544359 AP003785.1 chr11 72410716 72412079 +1544363 LINC01537 chr11 72570660 72573229 +1544367 PDE2A chr11 72576141 72674591 +1545065 AP005019.1 chr11 72584572 72587979 +1545069 AP003065.1 chr11 72643237 72659407 +1545075 ARAP1 chr11 72685069 72793599 +1545698 ARAP1-AS1 chr11 72685075 72693808 +1545702 AP003065.2 chr11 72689650 72695821 +1545706 ARAP1-AS2 chr11 72700474 72705607 +1545710 STARD10 chr11 72754729 72793681 +1545942 AP002381.2 chr11 72793624 72814054 +1545949 ATG16L2 chr11 72814406 72843674 +1546297 FCHSD2 chr11 72836745 73142318 +1546569 AP002761.2 chr11 73157946 73181724 +1546577 AP002761.1 chr11 73214998 73215913 +1546581 P2RY2 chr11 73218298 73236352 +1546615 AP002761.4 chr11 73238975 73242335 +1546618 P2RY6 chr11 73264505 73298617 +1546747 AP002761.3 chr11 73307235 73309361 +1546752 ARHGEF17 chr11 73308276 73369388 +1546866 RELT chr11 73376399 73397474 +1546969 AP000763.4 chr11 73395559 73396436 +1546973 FAM168A chr11 73400487 73598189 +1547045 AP000763.3 chr11 73405297 73410682 +1547053 PLEKHB1 chr11 73646178 73662819 +1547346 RAB6A chr11 73675638 73761137 +1547500 AP002993.1 chr11 73722349 73722694 +1547504 AP002770.1 chr11 73760563 73761070 +1547508 MRPL48 chr11 73787872 73865133 +1547748 COA4 chr11 73872667 73876901 +1547793 PAAF1 chr11 73876699 73931124 +1548102 DNAJB13 chr11 73950319 73970366 +1548173 AP003717.1 chr11 73963657 73970287 +1548186 UCP2 chr11 73974672 73983246 +1548289 AP003717.4 chr11 73983449 73985562 +1548292 UCP3 chr11 74000277 74009085 +1548339 C2CD3 chr11 74012714 74171210 +1548638 PPME1 chr11 74171267 74254703 +1548749 P4HA3 chr11 74235801 74311640 +1548896 P4HA3-AS1 chr11 74311362 74324705 +1548905 PGM2L1 chr11 74330316 74398433 +1548941 AP001372.1 chr11 74397549 74485742 +1548951 AP001085.1 chr11 74398825 74416379 +1548960 KCNE3 chr11 74454841 74467729 +1549025 AP001372.3 chr11 74455348 74456825 +1549029 LIPT2 chr11 74490519 74493724 +1549051 AP001372.2 chr11 74493366 74498533 +1549057 POLD3 chr11 74493851 74669117 +1549213 CHRDL2 chr11 74696429 74731385 +1549404 RNF169 chr11 74748849 74842413 +1549429 XRRA1 chr11 74807739 74949200 +1549740 AP001992.2 chr11 74931724 74936937 +1549744 SPCS2 chr11 74949247 74979033 +1549836 NEU3 chr11 74988279 75018893 +1549914 OR2AT4 chr11 75081753 75096876 +1549966 AP001972.4 chr11 75099172 75140148 +1549972 SLCO2B1 chr11 75100563 75206549 +1550219 AP001972.3 chr11 75206048 75241173 +1550241 TPBGL chr11 75240774 75243704 +1550249 ARRB1 chr11 75260122 75351705 +1550441 AP001972.1 chr11 75260127 75261025 +1550445 AP001972.2 chr11 75264289 75265170 +1550449 RPS3 chr11 75399515 75422280 +1550730 KLHL35 chr11 75422394 75430629 +1550775 GDPD5 chr11 75434640 75525941 +1551091 AP002815.1 chr11 75506937 75508391 +1551095 SERPINH1 chr11 75562056 75572783 +1551280 AP001922.5 chr11 75583196 75594665 +1551284 MAP6 chr11 75586918 75669120 +1551325 AP001922.6 chr11 75596144 75597270 +1551329 AP001922.2 chr11 75635883 75638587 +1551333 MOGAT2 chr11 75717838 75732958 +1551382 AP001922.1 chr11 75758455 75768647 +1551388 DGAT2 chr11 75759512 75801535 +1551497 AP001922.3 chr11 75775904 75776929 +1551501 AP003031.1 chr11 75800877 75803415 +1551506 UVRAG-DT chr11 75803431 75815406 +1551534 UVRAG chr11 75815210 76144232 +1551706 AP003168.2 chr11 75914201 75915213 +1551710 AP002340.1 chr11 76137315 76137731 +1551714 WNT11 chr11 76186325 76210736 +1551758 AP000785.1 chr11 76190725 76195071 +1551762 LINC02761 chr11 76210956 76216025 +1551767 THAP12 chr11 76349956 76381132 +1551814 GVQW3 chr11 76381303 76414619 +1551890 AP002360.1 chr11 76435559 76444687 +1551906 EMSY chr11 76444923 76553025 +1552308 LINC02757 chr11 76607853 76630465 +1552322 AP001189.5 chr11 76625462 76626834 +1552326 AP001189.3 chr11 76654169 76656712 +1552330 AP001189.1 chr11 76657056 76663866 +1552335 LRRC32 chr11 76657524 76670747 +1552383 AP001189.4 chr11 76675079 76703195 +1552388 AP003119.1 chr11 76759916 76768622 +1552396 TSKU chr11 76782251 76798153 +1552438 AP003119.2 chr11 76782581 76783062 +1552448 AP003119.3 chr11 76800364 76804555 +1552451 ACER3 chr11 76860867 77026797 +1552742 AP002498.1 chr11 76955417 76978619 +1552747 B3GNT6 chr11 77034398 77041973 +1552764 CAPN5 chr11 77066961 77126155 +1552936 OMP chr11 77102840 77103331 +1552943 MYO7A chr11 77128246 77215241 +1553540 GDPD4 chr11 77216558 77301687 +1553634 PAK1 chr11 77321707 77474635 +1553926 AP003680.1 chr11 77473371 77477030 +1553929 CLNS1A chr11 77514936 77637794 +1554070 AQP11 chr11 77589391 77610356 +1554087 RSF1 chr11 77659996 77821017 +1554232 RSF1-IT2 chr11 77717712 77718411 +1554236 RSF1-IT1 chr11 77738680 77739568 +1554240 AAMDC chr11 77821109 77918432 +1554402 AP002812.2 chr11 77829654 77872262 +1554406 AP002812.3 chr11 77850604 77851511 +1554410 AP002812.5 chr11 77866412 77870091 +1554414 INTS4 chr11 77878720 77994671 +1554629 AP003032.2 chr11 78015715 78016495 +1554633 KCTD14 chr11 78015715 78046191 +1554653 AP003032.1 chr11 78022933 78023721 +1554657 THRSP chr11 78063861 78068351 +1554667 NDUFC2 chr11 78068297 78079862 +1554719 ALG8 chr11 78100936 78139653 +1555062 KCTD21-AS1 chr11 78139771 78225909 +1555101 KCTD21 chr11 78171249 78188626 +1555157 USP35 chr11 78188812 78215232 +1555273 GAB2 chr11 78215293 78418348 +1555355 AP003086.1 chr11 78324758 78444049 +1555359 AP003086.2 chr11 78388061 78392405 +1555363 LINC02728 chr11 78423982 78429836 +1555376 NARS2 chr11 78435968 78574874 +1555506 AP003110.1 chr11 78533176 78558565 +1555512 TENM4 chr11 78652829 79441030 +1555656 AP002768.1 chr11 78749250 78756480 +1555660 AP002957.1 chr11 79092848 79098003 +1555672 AP001547.1 chr11 79191558 79193160 +1555676 AP001978.1 chr11 79604967 79612300 +1555680 AP006295.1 chr11 80321620 80327911 +1555684 LINC02720 chr11 80751200 80762826 +1555689 AP003398.2 chr11 81015849 81040236 +1555696 AP003464.1 chr11 81175201 81431520 +1555707 MIR4300HG chr11 81821272 82718299 +1555794 AP002802.1 chr11 81970994 81987813 +1555798 AP000793.1 chr11 82603529 82643445 +1555810 FAM181B chr11 82729940 82733864 +1555818 LINC02734 chr11 82781502 82817741 +1555827 PRCP chr11 82822936 82970584 +1556033 DDIAS chr11 82899975 82958277 +1556191 AP000893.2 chr11 82963681 83039115 +1556195 RAB30 chr11 82973133 83071923 +1556396 RAB30-DT chr11 83072052 83107789 +1556455 AP001767.3 chr11 83072402 83097196 +1556460 PCF11 chr11 83156988 83187451 +1556565 AP000873.4 chr11 83180144 83184520 +1556569 AP000873.2 chr11 83184491 83193794 +1556611 PCF11-AS1 chr11 83185521 83187036 +1556614 ANKRD42 chr11 83193712 83260694 +1556791 AP000873.3 chr11 83209431 83213379 +1556795 CCDC90B chr11 83259097 83286407 +1557122 AP000446.1 chr11 83286120 83423516 +1557137 DLG2 chr11 83455012 85627922 +1557941 AP002370.2 chr11 83643602 83725390 +1557965 AP001825.1 chr11 84720826 84800701 +1557971 AP000857.2 chr11 84936689 84955705 +1557975 TMEM126B chr11 85628573 85636539 +1558133 TMEM126A chr11 85647967 85656547 +1558210 CREBZF chr11 85659708 85682908 +1558289 CCDC89 chr11 85683848 85686195 +1558297 SYTL2 chr11 85694224 85811159 +1558944 CCDC83 chr11 85855101 85920021 +1559026 AP003128.1 chr11 85916502 85923682 +1559032 PICALM chr11 85957175 86069882 +1559544 LINC02695 chr11 86192787 86193482 +1559548 EED chr11 86244753 86278813 +1559768 HIKESHI chr11 86302211 86345943 +1559847 CCDC81 chr11 86374736 86423109 +1559979 AP001831.1 chr11 86431590 86622867 +1559984 ME3 chr11 86441108 86672636 +1560189 AP003059.1 chr11 86703099 86714092 +1560193 AP003059.2 chr11 86727355 86765467 +1560208 PRSS23 chr11 86791059 86952910 +1560270 AP000654.1 chr11 86833068 86837615 +1560274 AP001528.1 chr11 86892214 86925037 +1560282 FZD4 chr11 86945679 86955395 +1560292 FZD4-DT chr11 86955616 87021909 +1560306 TMEM135 chr11 87037844 87328824 +1560445 LINC02711 chr11 87718354 87719411 +1560449 AP000676.5 chr11 87847259 88045608 +1560455 AP005436.3 chr11 88050106 88062110 +1560460 AP005436.1 chr11 88061774 88098147 +1560464 AP005436.2 chr11 88098591 88115835 +1560469 RAB38 chr11 88113251 88175443 +1560497 CTSC chr11 88293592 88337761 +1560580 AP003120.1 chr11 88422400 88428176 +1560584 GRM5-AS1 chr11 88504576 88524054 +1560595 GRM5 chr11 88504576 89065945 +1560687 TYR chr11 89177875 89295759 +1560711 NOX4 chr11 89324353 89498187 +1561154 AP003400.1 chr11 89546637 89589611 +1561158 TRIM77 chr11 89710299 89717872 +1561186 AP003122.2 chr11 89753982 89754953 +1561190 TRIM49 chr11 89797655 89808575 +1561229 TRIM64B chr11 89869282 89876017 +1561246 TRIM49D1 chr11 89911111 89921767 +1561304 TRIM49D2 chr11 89924064 89933063 +1561340 TRIM64 chr11 89968502 89974072 +1561358 TRIM49C chr11 90031106 90042025 +1561380 UBTFL1 chr11 90085950 90087131 +1561387 AP000648.9 chr11 90110638 90112022 +1561391 NAALAD2 chr11 90131515 90192894 +1561588 CHORDC1 chr11 90200429 90223077 +1561773 DISC1FP1 chr11 90251204 90915052 +1561820 LINC02748 chr11 91157994 91234388 +1561833 LINC02756 chr11 91794319 91872086 +1561883 FAT3 chr11 92352096 92896470 +1562031 AP000722.1 chr11 92400191 92408176 +1562038 AP003718.1 chr11 92748732 92766867 +1562042 LINC02746 chr11 92913227 92915644 +1562047 AP003171.1 chr11 92965797 92966603 +1562051 MTNR1B chr11 92969720 92985066 +1562078 SLC36A4 chr11 93144174 93197991 +1562179 AP003969.1 chr11 93240133 93241168 +1562183 DEUP1 chr11 93329971 93438487 +1562437 SMCO4 chr11 93478472 93543391 +1562493 CEP295 chr11 93661682 93730358 +1562655 SCARNA9 chr11 93721513 93721865 +1562658 TAF1D chr11 93729948 93784391 +1562913 C11orf54 chr11 93741591 93764749 +1563167 MED17 chr11 93784227 93814963 +1563656 VSTM5 chr11 93818232 93850618 +1563682 HEPHL1 chr11 94021354 94114208 +1563728 PANX1 chr11 94128841 94181968 +1563759 AP002784.1 chr11 94185439 94282203 +1563789 IZUMO1R chr11 94305592 94307721 +1563816 GPR83 chr11 94377316 94401419 +1563841 MRE11 chr11 94415578 94493908 +1564082 AP000786.1 chr11 94472908 94473570 +1564086 ANKRD49 chr11 94493979 94499578 +1564181 C11orf97 chr11 94512461 94532123 +1564195 FUT4 chr11 94543840 94549898 +1564203 PIWIL4 chr11 94543840 94621421 +1564351 AP000943.2 chr11 94545330 94740355 +1564363 AP000943.1 chr11 94638038 94640833 +1564371 LINC02700 chr11 94638045 94652884 +1564410 AMOTL1 chr11 94706431 94876748 +1564491 AP002383.2 chr11 94874052 94925521 +1564495 CWC15 chr11 94962620 94973586 +1564540 KDM4D chr11 94973709 94999519 +1564568 KDM4E chr11 95025258 95027596 +1564576 KDM4F chr11 95049422 95051338 +1564583 SRSF8 chr11 95067197 95071224 +1564598 ENDOD1 chr11 95089846 95132645 +1564608 AP000787.1 chr11 95150539 95234391 +1564667 SESN3 chr11 95165513 95232541 +1564764 AP001790.1 chr11 95482406 95497553 +1564769 AP000820.2 chr11 95571040 95748715 +1564776 AP000820.1 chr11 95698086 95700623 +1564781 FAM76B chr11 95768953 95790409 +1564959 CEP57 chr11 95789965 95832693 +1565224 MTMR2 chr11 95832882 95925315 +1565471 MAML2 chr11 95976598 96343195 +1565498 AP000779.1 chr11 96092374 96137827 +1565504 CCDC82 chr11 96352769 96389956 +1565854 JRKL chr11 96389989 96507574 +1565868 JRKL-AS1 chr11 96447132 96506826 +1565874 LINC02737 chr11 96508425 96514748 +1565880 AP003066.1 chr11 96590317 96985810 +1565892 LINC02553 chr11 97222644 97259987 +1565897 LINC02713 chr11 97878475 97959558 +1565937 AP003715.1 chr11 98676391 98683735 +1565942 AP002428.1 chr11 98938912 98945079 +1565946 CNTN5 chr11 99020949 100358885 +1566289 AP001351.1 chr11 100684162 100687955 +1566293 ARHGAP42 chr11 100687288 100993941 +1566471 PGR chr11 101029624 101129813 +1566639 PGR-AS1 chr11 101129077 101209591 +1566652 TRPC6 chr11 101451564 101872562 +1566776 ANGPTL5 chr11 101890674 101916522 +1566813 CEP126 chr11 101915010 102001062 +1566933 CFAP300 chr11 102047437 102084554 +1566997 AP001527.1 chr11 102107886 102109842 +1567000 AP001527.2 chr11 102109827 102110457 +1567003 YAP1 chr11 102110447 102233424 +1567194 AP000942.2 chr11 102229851 102230922 +1567198 BIRC3 chr11 102317450 102339403 +1567297 BIRC2 chr11 102347211 102378670 +1567483 TMEM123 chr11 102396332 102470384 +1567570 AP001830.1 chr11 102452919 102462008 +1567574 AP001830.2 chr11 102467255 102498801 +1567579 MMP7 chr11 102520508 102530750 +1567606 MMP20 chr11 102576832 102625332 +1567642 AP000851.1 chr11 102606916 102628070 +1567652 AP000851.2 chr11 102681310 102683913 +1567657 MMP27 chr11 102691487 102705769 +1567683 MMP8 chr11 102711796 102727050 +1567804 MMP10 chr11 102770502 102780628 +1567841 MMP1 chr11 102789919 102798160 +1567867 MMP3 chr11 102835801 102843609 +1567913 MMP12 chr11 102862736 102874982 +1567939 MMP13 chr11 102942995 102955732 +1568013 DCUN1D5 chr11 103050686 103092194 +1568183 AP001486.2 chr11 103050687 103055799 +1568186 DYNC2H1 chr11 103109410 103479863 +1568832 AP002961.1 chr11 103252217 103293705 +1568836 AP002989.1 chr11 103675994 103895271 +1568843 PDGFD chr11 103907189 104164379 +1568891 AP003043.1 chr11 103945548 103946546 +1568895 DDI1 chr11 104036640 104039196 +1568903 LINC02552 chr11 104445868 104609498 +1569026 CASP4 chr11 104942866 104969366 +1569136 CASP5 chr11 104994235 105023168 +1569313 CASP1 chr11 105025443 105035250 +1569568 CARD16 chr11 105041326 105101431 +1569618 CARD17 chr11 105092469 105101431 +1569647 CARD18 chr11 105137714 105531697 +1569706 GRIA4 chr11 105609994 105982092 +1569986 AP000813.1 chr11 105995185 105999213 +1569990 MSANTD4 chr11 105995623 106022403 +1570042 KBTBD3 chr11 106051098 106077459 +1570098 AASDHPPT chr11 106075501 106098699 +1570158 AP001001.1 chr11 106085990 106101975 +1570168 LINC02719 chr11 106112459 106132116 +1570173 AP002001.3 chr11 106241974 106260146 +1570177 AP003173.1 chr11 106465985 106469296 +1570181 GUCY1A2 chr11 106674012 107018524 +1570249 AP000766.1 chr11 107312132 107316271 +1570252 CWF19L2 chr11 107326345 107457844 +1570365 ALKBH8 chr11 107502726 107565746 +1570527 ELMOD1 chr11 107591091 107666779 +1570630 SLN chr11 107707378 107719693 +1570660 SLC35F2 chr11 107790991 107928293 +1570783 RAB39A chr11 107928448 107963482 +1570793 AP003307.1 chr11 108008678 108009282 +1570796 CUL5 chr11 108008898 108107761 +1570916 AP002433.1 chr11 108105074 108121684 +1570922 ACAT1 chr11 108116695 108147603 +1571273 AP002433.2 chr11 108142458 108150381 +1571277 NPAT chr11 108157215 108222638 +1571364 ATM chr11 108222484 108369102 +1571961 C11orf65 chr11 108308519 108467531 +1572113 POGLUT3 chr11 108472112 108498384 +1572194 EXPH5 chr11 108505435 108593768 +1572277 DDX10 chr11 108665069 108940927 +1572425 AP003027.1 chr11 108957718 108959797 +1572432 AP003123.1 chr11 109002465 109037967 +1572436 AP003049.2 chr11 109355085 109583907 +1572448 C11orf87 chr11 109422190 109429167 +1572458 LINC02715 chr11 109741625 109823893 +1572477 RDX chr11 109864295 110296712 +1572924 AP001981.2 chr11 109946581 109975996 +1572929 ZC3H12C chr11 110093392 110171841 +1572979 LINC02732 chr11 110355130 110407613 +1573004 FDX1 chr11 110429948 110464884 +1573018 ARHGAP20 chr11 110577042 110713189 +1573215 AP003973.4 chr11 111013452 111027636 +1573219 AP003973.2 chr11 111089870 111090368 +1573222 LINC02550 chr11 111091932 111179641 +1573231 AP003973.3 chr11 111097155 111106001 +1573236 C11orf53 chr11 111245726 111286401 +1573283 COLCA1 chr11 111290787 111305498 +1573302 COLCA2 chr11 111298555 111308735 +1573410 AP002448.1 chr11 111320379 111323816 +1573418 POU2AF1 chr11 111352255 111455630 +1573488 AP002008.3 chr11 111414242 111418186 +1573494 BTG4 chr11 111467526 111512354 +1573538 AP002008.4 chr11 111510600 111513888 +1573542 AP002008.1 chr11 111514043 111526755 +1573546 C11orf88 chr11 111514785 111537031 +1573610 LAYN chr11 111540280 111561745 +1573771 SIK2 chr11 111602449 111730855 +1573811 PPP2R1B chr11 111726908 111766389 +1574064 AP001781.1 chr11 111768668 111778350 +1574075 ALG9 chr11 111782195 111871581 +1574381 ALG9-IT1 chr11 111817214 111829212 +1574385 FDXACB1 chr11 111874056 111881243 +1574425 C11orf1 chr11 111878935 111885975 +1574489 CRYAB chr11 111908564 111923722 +1574709 HSPB2 chr11 111912734 111914093 +1574719 C11orf52 chr11 111918032 111926871 +1574753 DIXDC1 chr11 111927144 112022653 +1574908 AP000907.2 chr11 112015307 112016124 +1574912 DLAT chr11 112024814 112064390 +1575038 PIH1D2 chr11 112064010 112074274 +1575142 NKAPD1 chr11 112074086 112085150 +1575276 TIMM8B chr11 112084800 112086798 +1575310 SDHD chr11 112086824 112120016 +1575437 IL18 chr11 112143253 112164096 +1575502 AP002884.1 chr11 112165197 112172606 +1575508 TEX12 chr11 112167372 112172556 +1575539 BCO2 chr11 112175510 112224699 +1575821 PTS chr11 112226367 112269955 +1575918 PLET1 chr11 112248153 112260860 +1575932 AP002884.3 chr11 112260265 112261396 +1575935 LINC02762 chr11 112270749 112362534 +1575958 LINC02763 chr11 112393118 112624567 +1575980 LINC02764 chr11 112534220 112555802 +1575986 AP003100.2 chr11 112637342 112751131 +1575997 AP003100.3 chr11 112698772 112721151 +1576002 AP003100.1 chr11 112787304 112795854 +1576006 AC016902.1 chr11 112822806 112835124 +1576011 AP000802.1 chr11 112959279 112963460 +1576027 NCAM1 chr11 112961247 113278436 +1576694 NCAM1-AS1 chr11 113265137 113274032 +1576709 AP000880.1 chr11 113278250 113314482 +1576724 TTC12 chr11 113314529 113383544 +1577210 AP002840.2 chr11 113368478 113369117 +1577213 ANKK1 chr11 113387779 113400416 +1577248 AP002840.1 chr11 113405321 113412117 +1577254 DRD2 chr11 113409605 113475691 +1577389 TMPRSS5 chr11 113687547 113706373 +1577668 ZW10 chr11 113733187 113773735 +1577759 AP003170.4 chr11 113770393 113771691 +1577763 CLDN25 chr11 113779747 113780500 +1577771 USP28 chr11 113797874 113875570 +1578123 AP003170.3 chr11 113818077 113822458 +1578128 HTR3B chr11 113904677 113949078 +1578186 HTR3A chr11 113974881 113990313 +1578325 ZBTB16 chr11 114059711 114256765 +1578413 AP002755.1 chr11 114159791 114161166 +1578417 AP002518.2 chr11 114210616 114356571 +1578422 NNMT chr11 114257787 114313285 +1578470 AP002518.1 chr11 114343052 114396219 +1578480 C11orf71 chr11 114391443 114400511 +1578497 RBM7 chr11 114400030 114414203 +1578611 REXO2 chr11 114439386 114450279 +1578816 NXPE1 chr11 114521645 114559895 +1578912 NXPE4 chr11 114570591 114595786 +1578947 NXPE2 chr11 114678527 114707069 +1578965 CADM1 chr11 115169218 115504957 +1579274 AP000465.1 chr11 115332529 115333418 +1579278 AP000462.3 chr11 115333577 115340262 +1579282 AP000462.1 chr11 115363629 115377931 +1579286 AP000462.2 chr11 115396756 115397658 +1579296 AP003174.2 chr11 115532322 115532953 +1579300 AP003174.1 chr11 115582297 115600339 +1579305 AP000997.2 chr11 115628065 115629743 +1579310 AP000997.3 chr11 115638563 115646962 +1579313 LINC02698 chr11 115659658 115843146 +1579318 AP002991.2 chr11 115734848 115756926 +1579324 LINC00900 chr11 115753889 115760646 +1579357 LINC02703 chr11 115920248 115943181 +1579375 LINC02151 chr11 116496899 116500630 +1579379 LINC02702 chr11 116639422 116658295 +1579398 BUD13 chr11 116748170 116772987 +1579460 AP006216.1 chr11 116773389 116774205 +1579464 ZPR1 chr11 116773799 116788039 +1579612 APOA5 chr11 116789367 116792420 +1579648 AP006216.2 chr11 116813204 116814003 +1579652 AP006216.3 chr11 116820645 116821541 +1579656 APOA4 chr11 116820700 116823304 +1579668 APOC3 chr11 116829706 116833072 +1579719 APOA1 chr11 116835751 116837950 +1579779 APOA1-AS chr11 116836117 116856018 +1579787 SIK3 chr11 116843402 117098437 +1580087 AP000936.1 chr11 117098987 117108170 +1580092 PAFAH1B2 chr11 117144284 117176894 +1580184 SIDT2 chr11 117178736 117197445 +1580607 TAGLN chr11 117199370 117207464 +1580706 PCSK7 chr11 117204337 117232525 +1580872 RNF214 chr11 117232625 117286454 +1581038 BACE1 chr11 117285207 117316259 +1581235 BACE1-AS chr11 117288453 117293571 +1581246 AP000892.3 chr11 117297005 117297328 +1581249 CEP164 chr11 117314557 117413266 +1581483 AP000892.1 chr11 117316362 117328038 +1581488 DSCAML1 chr11 117427772 117817525 +1581777 AP001554.1 chr11 117668483 117668858 +1581780 FXYD2 chr11 117800844 117828698 +1581870 AP000757.2 chr11 117818443 117821992 +1581875 AP000757.1 chr11 117833719 117838942 +1581888 FXYD6 chr11 117836976 117877486 +1582149 TMPRSS13 chr11 117900641 117929459 +1582310 IL10RA chr11 117986348 118003037 +1582410 SMIM35 chr11 118003634 118088299 +1582444 TMPRSS4 chr11 118077012 118121890 +1582790 SCN4B chr11 118133377 118152888 +1582833 SCN2B chr11 118157849 118176639 +1582874 JAML chr11 118193725 118225094 +1583076 MPZL3 chr11 118226690 118252365 +1583137 MPZL2 chr11 118253416 118264536 +1583191 CD3E chr11 118304545 118316175 +1583261 CD3D chr11 118338954 118342744 +1583318 CD3G chr11 118344344 118355161 +1583402 UBE4A chr11 118359585 118399211 +1583520 AP001267.1 chr11 118397095 118401895 +1583527 ATP5MG chr11 118401606 118431496 +1583590 AP001267.4 chr11 118415977 118416521 +1583593 AP001267.2 chr11 118433121 118435206 +1583596 KMT2A chr11 118436490 118526832 +1583980 AP001267.3 chr11 118510273 118531094 +1584002 TTC36 chr11 118527472 118531197 +1584040 TMEM25 chr11 118531041 118547280 +1584381 IFT46 chr11 118544528 118572970 +1584604 ARCN1 chr11 118572390 118603033 +1584706 PHLDB1 chr11 118606440 118658031 +1585164 AP000941.1 chr11 118636620 118638097 +1585168 TREH chr11 118657316 118679690 +1585283 AP002954.1 chr11 118700427 118750263 +1585292 AP002954.2 chr11 118721104 118729412 +1585296 DDX6 chr11 118747763 118791164 +1585430 AP004609.3 chr11 118791254 118793137 +1585433 CXCR5 chr11 118883892 118897787 +1585443 AP004609.1 chr11 118885841 118887742 +1585447 BCL9L chr11 118893875 118925608 +1585510 UPK2 chr11 118925164 118958559 +1585533 FOXR1 chr11 118971712 118981287 +1585577 CCDC84-DT chr11 118994824 118998004 +1585584 CCDC84 chr11 118998138 119015793 +1585703 AP003392.1 chr11 119003742 119004893 +1585707 RPS25 chr11 119015712 119018691 +1585763 TRAPPC4 chr11 119018763 119025454 +1585900 SLC37A4 chr11 119024114 119030906 +1586144 AP003392.3 chr11 119044188 119045493 +1586148 HYOU1 chr11 119044188 119057227 +1586702 AP003392.4 chr11 119065263 119065677 +1586705 AP003392.5 chr11 119067374 119067698 +1586708 VPS11 chr11 119067692 119081978 +1586853 HMBS chr11 119084866 119093549 +1587503 H2AFX chr11 119093854 119095467 +1587520 DPAGT1 chr11 119096503 119108331 +1587758 C2CD2L chr11 119102198 119118544 +1587884 HINFP chr11 119121580 119136059 +1588002 ABCG4 chr11 119149052 119162653 +1588132 NLRX1 chr11 119166568 119184016 +1588324 PDZD3 chr11 119185457 119190223 +1588503 CCDC153 chr11 119189638 119196769 +1588552 CBL chr11 119206276 119313926 +1588712 MCAM chr11 119308529 119321521 +1588855 RNF26 chr11 119334527 119337309 +1588863 AP003396.1 chr11 119336249 119337309 +1588867 C1QTNF5 chr11 119338942 119340940 +1588900 MFRP chr11 119338942 119346705 +1588996 USP2 chr11 119355215 119381711 +1589114 USP2-AS1 chr11 119364359 119526664 +1589181 AP003396.3 chr11 119372706 119381613 +1589188 THY1 chr11 119417378 119424985 +1589277 AP003396.5 chr11 119417951 119419114 +1589281 AP003393.1 chr11 119608423 119659284 +1589294 NECTIN1 chr11 119623408 119729200 +1589363 NECTIN1-AS1 chr11 119709920 119713925 +1589368 AP003390.1 chr11 119729583 119739623 +1589374 AP001994.2 chr11 119832966 119867682 +1589378 AP001994.3 chr11 119892700 119919996 +1589383 AP001360.3 chr11 119976111 120009588 +1589387 LINC02744 chr11 119987952 119995037 +1589405 AP001360.1 chr11 120008044 120013620 +1589425 AP001360.2 chr11 120026753 120028341 +1589429 TRIM29 chr11 120111286 120185529 +1589640 AP000679.1 chr11 120168977 120171679 +1589647 OAF chr11 120211032 120230334 +1589677 POU2F3 chr11 120236640 120319945 +1589794 AP001150.1 chr11 120249759 120265932 +1589808 TLCD5 chr11 120325129 120333682 +1589850 ARHGEF12 chr11 120336413 120489937 +1590198 GRIK4 chr11 120511700 120988904 +1590375 AP004147.1 chr11 120867933 120894797 +1590379 TBCEL chr11 121024072 121090775 +1590536 TECTA chr11 121101173 121191493 +1590742 SC5D chr11 121292681 121313410 +1590822 AP000977.1 chr11 121447331 121453013 +1590829 SORL1 chr11 121452314 121633763 +1591193 AP001977.1 chr11 121674261 121928976 +1591210 AP001924.1 chr11 121979571 122025937 +1591215 AP001924.2 chr11 122026093 122027667 +1591219 MIR100HG chr11 122028325 122556721 +1591654 BLID chr11 122115340 122116215 +1591662 AP000755.1 chr11 122294938 122301763 +1591666 AP000755.2 chr11 122295190 122308019 +1591671 UBASH3B chr11 122655722 122814473 +1591736 AP002762.3 chr11 122679801 122681942 +1591740 AP002762.2 chr11 122751147 122851617 +1591749 CRTAM chr11 122838500 122872643 +1591795 JHY chr11 122882528 122959798 +1591856 BSX chr11 122977570 122981834 +1591868 HSPA8 chr11 123057489 123063230 +1592157 AP000926.2 chr11 123062655 123084870 +1592162 CLMP chr11 123069872 123195248 +1592198 AP001970.1 chr11 123188802 123228502 +1592205 LINC02727 chr11 123313657 123315340 +1592221 GRAMD1B chr11 123358428 123627774 +1592725 SCN3B chr11 123629187 123655244 +1592861 AP002765.1 chr11 123668499 123675569 +1592867 ZNF202 chr11 123723914 123741675 +1592980 OR6X1 chr11 123753488 123754545 +1592988 OR6M1 chr11 123805335 123806387 +1592996 TMEM225 chr11 123882920 123885670 +1593021 OR8D4 chr11 123902167 123909229 +1593038 OR4D5 chr11 123939543 123940637 +1593046 OR6T1 chr11 123942785 123943873 +1593054 OR10S1 chr11 123976661 123977781 +1593069 OR10G6 chr11 123994163 123995161 +1593076 OR10G4 chr11 124012997 124018732 +1593103 OR10G9 chr11 124023013 124023948 +1593110 OR10G8 chr11 124026798 124030634 +1593127 OR10G7 chr11 124036013 124041325 +1593143 VWA5A chr11 124115404 124147721 +1593308 OR10D3 chr11 124183345 124188780 +1593334 OR8G1 chr11 124241095 124254364 +1593352 OR8G5 chr11 124256376 124266218 +1593375 OR8D1 chr11 124302831 124315099 +1593407 OR8D2 chr11 124319238 124320288 +1593415 OR8B2 chr11 124382394 124384462 +1593431 OR8B3 chr11 124395534 124399024 +1593447 AP001804.1 chr11 124406997 124414792 +1593452 OR8B4 chr11 124423904 124424893 +1593460 OR8B8 chr11 124437445 124445696 +1593479 OR8B12 chr11 124539635 124545333 +1593491 OR8A1 chr11 124566660 124582942 +1593519 PANX3 chr11 124611428 124620356 +1593533 TBRG1 chr11 124622836 124635926 +1593656 SIAE chr11 124633113 124695707 +1593751 SPA17 chr11 124673798 124697518 +1593790 NRGN chr11 124739942 124747210 +1593817 AP000866.5 chr11 124744634 124746337 +1593822 VSIG2 chr11 124747474 124752255 +1593859 ESAM chr11 124752583 124762290 +1593931 AP000866.2 chr11 124759129 124766119 +1593941 MSANTD2 chr11 124766498 124800673 +1594016 AP000866.6 chr11 124789240 124792818 +1594021 AP000866.1 chr11 124800424 124834487 +1594108 ROBO3 chr11 124865432 124881471 +1594374 AP003501.1 chr11 124883691 124887789 +1594378 ROBO4 chr11 124883691 124898500 +1594506 AP003501.2 chr11 124891304 124892126 +1594510 HEPACAM chr11 124919205 124936412 +1594536 HEPN1 chr11 124919244 124920677 +1594544 CCDC15-DT chr11 124949205 124954044 +1594557 CCDC15 chr11 124954121 125041489 +1594640 SLC37A2 chr11 125063067 125090312 +1594776 TMEM218 chr11 125096545 125111763 +1594987 AP001007.2 chr11 125132847 125139587 +1594991 PKNOX2-AS1 chr11 125158461 125164609 +1594996 PKNOX2 chr11 125164687 125433389 +1595163 AP001007.3 chr11 125188115 125191404 +1595171 AP001007.1 chr11 125258626 125266798 +1595175 FEZ1 chr11 125442881 125592568 +1595317 AP000708.1 chr11 125495214 125499528 +1595321 EI24 chr11 125569280 125584684 +1595593 STT3A chr11 125591712 125625215 +1595858 CHEK1 chr11 125625665 125676255 +1596204 ACRV1 chr11 125671522 125680874 +1596261 PATE1 chr11 125746279 125749867 +1596293 PATE2 chr11 125776113 125778828 +1596318 PATE3 chr11 125788127 125791600 +1596330 PATE4 chr11 125833316 125840072 +1596354 AP000842.3 chr11 125873031 125874528 +1596360 HYLS1 chr11 125883614 125900648 +1596396 PUS3 chr11 125893485 125903221 +1596450 AP000842.2 chr11 125903247 125938916 +1596459 DDX25 chr11 125903348 125943702 +1596623 AP000842.1 chr11 125940496 125941193 +1596626 VSIG10L2 chr11 125946056 125958647 +1596666 CDON chr11 125955796 126063335 +1596856 AP000821.1 chr11 126100505 126102413 +1596859 AP000821.2 chr11 126121889 126128081 +1596864 AP001893.3 chr11 126160714 126176035 +1596868 RPUSD4 chr11 126202096 126211692 +1596950 AP001893.1 chr11 126208611 126209027 +1596954 FAM118B chr11 126211724 126262984 +1597099 SRPRA chr11 126262938 126269144 +1597185 FOXRED1 chr11 126269055 126278131 +1597372 TIRAP chr11 126283065 126298845 +1597460 AP001318.1 chr11 126292922 126294254 +1597464 AP001318.2 chr11 126294298 126304318 +1597471 DCPS chr11 126304060 126350005 +1597516 GSEC chr11 126340889 126355587 +1597524 ST3GAL4 chr11 126355640 126440344 +1597918 KIRREL3 chr11 126423358 127003460 +1598056 KIRREL3-AS1 chr11 126543947 126610948 +1598060 AP001783.1 chr11 126652852 126682104 +1598067 AP002833.1 chr11 126920188 126940659 +1598071 KIRREL3-AS2 chr11 126940746 126945090 +1598080 AP002833.2 chr11 126992452 126995458 +1598084 KIRREL3-AS3 chr11 127002910 127006058 +1598092 AP001993.1 chr11 127021736 127172363 +1598294 AP003121.1 chr11 127188885 127223449 +1598307 LINC02712 chr11 127271029 127337033 +1598316 LINC02725 chr11 128095758 128183671 +1598366 LINC02098 chr11 128208749 128241441 +1598387 ETS1 chr11 128458761 128587558 +1598506 ETS1-AS1 chr11 128526142 128530389 +1598512 AP001122.1 chr11 128614340 128686922 +1598533 FLI1 chr11 128686535 128813267 +1598688 SENCR chr11 128691672 128696023 +1598693 KCNJ1 chr11 128836315 128867373 +1598760 KCNJ5 chr11 128891356 128921163 +1598794 C11orf45 chr11 128899565 128906069 +1598835 TP53AIP1 chr11 128934731 128943399 +1598895 ARHGAP32 chr11 128965060 129279324 +1599089 BARX2 chr11 129375848 129452279 +1599105 AP003500.1 chr11 129591493 129612110 +1599109 LINC01395 chr11 129612116 129617269 +1599115 AP003327.2 chr11 129761713 129814690 +1599121 TMEM45B chr11 129815848 129860003 +1599170 NFRKB chr11 129863636 129895590 +1599481 PRDM10 chr11 129899706 130002835 +1599801 LINC00167 chr11 130002938 130004356 +1599804 APLP2 chr11 130068147 130144811 +1600188 ST14 chr11 130159782 130210362 +1600252 ZBTB44 chr11 130226677 130314917 +1600405 ZBTB44-DT chr11 130314993 130403657 +1600434 ADAMTS8 chr11 130404923 130428609 +1600463 ADAMTS15 chr11 130448974 130476641 +1600484 C11orf44 chr11 130672956 130717352 +1600489 AP003486.2 chr11 130771413 130785533 +1600494 LINC02551 chr11 130844191 130865561 +1600508 AP003486.1 chr11 130866254 130870247 +1600511 SNX19 chr11 130875436 130916509 +1600688 AP002856.3 chr11 131187022 131189753 +1600692 AP002856.1 chr11 131204999 131215163 +1600696 AP002856.4 chr11 131234538 131251816 +1600700 AP002856.2 chr11 131253422 131350917 +1600707 NTM chr11 131370478 132336822 +1600924 AP003025.1 chr11 131502735 131540867 +1600942 AP003025.2 chr11 131542030 131581145 +1600954 NTM-AS1 chr11 131622451 131663583 +1600964 AP000844.2 chr11 131877680 131897108 +1600968 AP000844.1 chr11 131981096 131984661 +1600972 NTM-IT chr11 132284302 132285081 +1600976 OPCML chr11 132414977 133532519 +1601094 OPCML-IT2 chr11 132859245 132860077 +1601098 OPCML-IT1 chr11 133360029 133366080 +1601102 AP004606.1 chr11 133532415 133549866 +1601106 LINC02743 chr11 133783671 133810376 +1601111 SPATA19 chr11 133840631 133845538 +1601150 IGSF9B chr11 133896438 133956985 +1601277 LINC02730 chr11 134008215 134030167 +1601297 LINC02731 chr11 134032216 134067936 +1601334 AP000911.1 chr11 134035832 134037107 +1601338 JAM3 chr11 134069071 134152001 +1601431 NCAPD3 chr11 134150119 134225454 +1601749 AP001775.2 chr11 134178824 134186166 +1601753 VPS26B chr11 134224671 134247788 +1601821 THYN1 chr11 134248279 134253370 +1601924 ACAD8 chr11 134253495 134265855 +1602098 GLB1L3 chr11 134274245 134319564 +1602232 GLB1L2 chr11 134331874 134378341 +1602357 B3GAT1 chr11 134378504 134412242 +1602420 AP004608.1 chr11 134412284 134505665 +1602460 AP004550.1 chr11 134563396 134573056 +1602465 AP001999.3 chr11 134655769 134661206 +1602469 AP001999.1 chr11 134671426 134672024 +1602473 AP001999.2 chr11 134685044 134702004 +1602480 LINC02706 chr11 134712539 134716250 +1602500 LINC02714 chr11 134735596 134763810 +1602504 AP003062.2 chr11 134945118 134980574 +1602508 LINC02697 chr11 134950708 134951568 +1602512 LINC02717 chr11 134994982 135007779 +1602522 LINC02684 chr11 135061781 135075908 +1602531 FAM138D chr12 36602 38133 +1602539 IQSEC3 chr12 66767 178455 +1602616 AC026369.3 chr12 106524 111850 +1602620 AC026369.1 chr12 137411 149169 +1602640 AC026369.2 chr12 164664 166321 +1602644 AC007406.3 chr12 166856 182399 +1602652 SLC6A12 chr12 190077 214570 +1602877 AC007406.1 chr12 193036 194130 +1602881 AC007406.4 chr12 203642 205094 +1602886 SLC6A13 chr12 220621 262873 +1603033 AC007406.2 chr12 253442 257299 +1603038 AC007406.5 chr12 273954 277123 +1603041 KDM5A chr12 280057 389320 +1603182 CCDC77 chr12 389273 442642 +1603365 B4GALNT3 chr12 459939 563509 +1603483 NINJ2 chr12 564296 663779 +1603548 AC006205.2 chr12 585865 586486 +1603552 AC006205.1 chr12 590633 591269 +1603556 AC021054.1 chr12 630858 664196 +1603586 LINC02455 chr12 674801 684127 +1603591 WNK1 chr12 752579 911452 +1604008 AC004765.1 chr12 865288 867139 +1604012 RAD52 chr12 911736 990053 +1604325 AC004803.1 chr12 974133 991190 +1604340 ERC1 chr12 990509 1495933 +1604919 AC004672.1 chr12 1380060 1391502 +1604923 AC004672.2 chr12 1385833 1386987 +1604927 LINC00942 chr12 1500525 1504424 +1604931 WNT5B chr12 1529891 1647212 +1605031 FBXL14 chr12 1565993 1594581 +1605044 ADIPOR2 chr12 1688574 1788674 +1605088 AC005343.1 chr12 1741197 1747099 +1605093 CACNA2D4 chr12 1791963 1918666 +1605906 AC005343.4 chr12 1800862 1807486 +1605911 LRTM2 chr12 1820267 1836753 +1606005 AC005342.2 chr12 1917951 1922867 +1606009 LINC00940 chr12 1929202 1936574 +1606013 DCP1B chr12 1946053 2004535 +1606105 CACNA1C chr12 1970786 2697950 +1608467 AC005342.1 chr12 2004666 2011392 +1608471 CACNA1C-IT1 chr12 2018213 2020532 +1608475 CACNA1C-IT2 chr12 2048352 2049463 +1608479 AC005344.1 chr12 2217462 2217920 +1608482 CACNA1C-AS4 chr12 2219485 2223479 +1608492 CACNA1C-IT3 chr12 2269776 2288937 +1608497 AC005293.1 chr12 2332861 2335702 +1608502 AC005414.1 chr12 2440189 2457392 +1608507 CACNA1C-AS3 chr12 2603350 2607440 +1608511 CACNA1C-AS2 chr12 2668500 2672220 +1608515 CACNA1C-AS1 chr12 2676001 2691200 +1608528 LINC02371 chr12 2740064 2746662 +1608539 FKBP4 chr12 2794970 2805423 +1608615 ITFG2-AS1 chr12 2796877 2812902 +1608625 AC005841.1 chr12 2797136 2803938 +1608629 ITFG2 chr12 2812622 2859791 +1608861 NRIP2 chr12 2825348 2835544 +1608903 TEX52 chr12 2849046 2857039 +1608915 FOXM1 chr12 2857681 2877155 +1609049 RHNO1 chr12 2876258 2889524 +1609133 TULP3 chr12 2877223 2941138 +1609297 AC005911.1 chr12 2885819 2886329 +1609301 TEAD4 chr12 2959330 3040676 +1609456 AC125807.2 chr12 3041437 3044950 +1609459 TSPAN9 chr12 3077355 3286564 +1609576 TSPAN9-IT1 chr12 3149797 3151476 +1609580 AC005912.2 chr12 3171657 3174056 +1609583 AC005865.2 chr12 3300698 3318677 +1609588 LINC02827 chr12 3318718 3325343 +1609596 LINC02417 chr12 3367833 3371346 +1609601 PRMT8 chr12 3381349 3593973 +1609675 AC005908.2 chr12 3462718 3463586 +1609679 AC005908.3 chr12 3483714 3492819 +1609690 CRACR2A chr12 3606633 3764819 +1609815 AC006207.1 chr12 3752518 3757842 +1609822 PARP11 chr12 3791047 3873448 +1609966 AC005842.1 chr12 3871579 3910382 +1609988 AC084375.1 chr12 4012902 4026658 +1610006 CCND2-AS1 chr12 4247981 4276252 +1610032 CCND2 chr12 4273762 4305353 +1610063 TIGAR chr12 4307763 4360028 +1610107 FGF23 chr12 4368227 4379712 +1610122 FGF6 chr12 4428155 4445614 +1610144 C12orf4 chr12 4487735 4538508 +1610289 RAD51AP1 chr12 4538798 4560048 +1610540 DYRK4 chr12 4562204 4615302 +1610740 AKAP3 chr12 4615508 4649051 +1610798 AC005832.1 chr12 4645496 4648027 +1610802 NDUFA9 chr12 4649095 4694317 +1610885 GAU1 chr12 4700417 4720102 +1610891 GALNT8 chr12 4720400 4851927 +1610958 AC005833.2 chr12 4804499 4830747 +1610971 KCNA6 chr12 4809176 4813412 +1610979 AC006063.1 chr12 4838955 4842675 +1610983 AC006063.3 chr12 4857283 4859904 +1610987 AC006063.4 chr12 4906393 4909265 +1610991 AC005906.2 chr12 4909867 5026012 +1611117 KCNA1 chr12 4909905 4918256 +1611146 AC006063.2 chr12 4960113 4963450 +1611151 KCNA5 chr12 5043879 5046788 +1611159 AC005906.3 chr12 5088002 5092742 +1611163 LINC02443 chr12 5226196 5244199 +1611246 AC006206.2 chr12 5290480 5383653 +1611256 AC006206.1 chr12 5315961 5319347 +1611259 AC007848.2 chr12 5366048 5367774 +1611262 AC007848.1 chr12 5388589 5406651 +1611269 NTF3 chr12 5432108 5521536 +1611303 ANO2 chr12 5531869 5946232 +1611596 VWF chr12 5948874 6124770 +1611762 AC005845.1 chr12 6155035 6160719 +1611767 CD9 chr12 6199715 6238271 +1612010 PLEKHG6 chr12 6310436 6328506 +1612176 TNFRSF1A chr12 6328757 6342114 +1612378 SCNN1A chr12 6346843 6377730 +1612626 LTBR chr12 6375045 6391571 +1612783 AC005840.2 chr12 6393879 6396148 +1612792 CD27-AS1 chr12 6439001 6451567 +1612892 CD27 chr12 6444867 6451718 +1612916 TAPBPL chr12 6451690 6466517 +1612988 VAMP1 chr12 6462237 6470987 +1613069 AC005840.4 chr12 6466537 6467135 +1613072 MRPL51 chr12 6491886 6493841 +1613144 NCAPD2 chr12 6493356 6531955 +1613383 AC006064.5 chr12 6510275 6510522 +1613386 AC006064.3 chr12 6532290 6533498 +1613390 GAPDH chr12 6534512 6538374 +1613554 AC006064.4 chr12 6537794 6538370 +1613558 IFFO1 chr12 6538375 6556083 +1613794 AC006064.1 chr12 6543504 6544931 +1613798 NOP2 chr12 6556863 6568691 +1614243 CHD4 chr12 6570082 6614524 +1616219 AC006064.2 chr12 6578622 6584739 +1616223 LPAR5 chr12 6618835 6635960 +1616246 ACRBP chr12 6638075 6647433 +1616355 ING4 chr12 6650301 6663142 +1616631 AC125494.1 chr12 6663260 6672069 +1616639 ZNF384 chr12 6666477 6689572 +1616863 PIANP chr12 6693792 6700800 +1616938 AC125494.3 chr12 6723233 6723687 +1616941 COPS7A chr12 6724014 6731875 +1617290 AC125494.2 chr12 6742985 6743641 +1617293 MLF2 chr12 6747996 6767475 +1617444 PTMS chr12 6765516 6770952 +1617517 LAG3 chr12 6772512 6778455 +1617564 CD4 chr12 6786858 6820799 +1617665 GPR162 chr12 6821624 6829972 +1617728 P3H3 chr12 6828407 6839847 +1617846 GNB3 chr12 6839954 6847393 +1617991 CDCA3 chr12 6844793 6852066 +1618100 USP5 chr12 6852128 6866632 +1618236 TPI1 chr12 6867119 6870948 +1618375 SPSB2 chr12 6870935 6889358 +1618423 LRRC23 chr12 6873569 6914241 +1618625 U47924.3 chr12 6899752 6900212 +1618628 ENO2 chr12 6913745 6923698 +1618829 ATN1 chr12 6924463 6942321 +1618887 C12orf57 chr12 6942978 6946003 +1618949 U47924.2 chr12 6943508 6944604 +1618952 PTPN6 chr12 6946468 6961316 +1619248 MIR200CHG chr12 6963246 6964447 +1619252 U47924.1 chr12 6964949 6965382 +1619255 PHB2 chr12 6965327 6970753 +1619439 EMG1 chr12 6970913 6997428 +1619516 LPCAT3 chr12 6976185 7018477 +1619684 C1S chr12 6988259 7071032 +1619958 C1R chr12 7080214 7092540 +1620164 C1RL chr12 7089587 7109238 +1620293 C1RL-AS1 chr12 7108052 7122501 +1620326 RBP5 chr12 7115736 7128889 +1620371 AC018653.3 chr12 7129079 7131198 +1620379 CLSTN3 chr12 7129698 7158945 +1620551 AC018653.4 chr12 7146482 7147817 +1620555 AC018653.1 chr12 7166674 7189069 +1620563 PEX5 chr12 7188685 7218574 +1620967 ACSM4 chr12 7304284 7328724 +1621003 CD163L1 chr12 7346685 7479897 +1621153 CD163 chr12 7470813 7503893 +1621361 APOBEC1 chr12 7649400 7665908 +1621390 GDF3 chr12 7689784 7695775 +1621400 DPPA3 chr12 7711433 7717559 +1621414 CLEC4C chr12 7729415 7751605 +1621505 NANOGNB chr12 7765216 7774121 +1621532 NANOG chr12 7787794 7799146 +1621576 SLC2A14 chr12 7812512 7891148 +1621955 AC006517.2 chr12 7838914 7844395 +1621959 SLC2A3 chr12 7919230 7936187 +1622047 AC006511.6 chr12 7954216 7972759 +1622051 AC006511.4 chr12 8014093 8019007 +1622055 FOXJ2 chr12 8032716 8055517 +1622112 C3AR1 chr12 8056844 8066359 +1622129 NECAP1 chr12 8076939 8097881 +1622466 CLEC4A chr12 8123632 8138607 +1622536 ZNF705A chr12 8157034 8188537 +1622593 FAM66C chr12 8180209 8216151 +1622654 AC092111.2 chr12 8205984 8207397 +1622657 AC092111.1 chr12 8217758 8221115 +1622660 FAM90A1 chr12 8221260 8227618 +1622708 LINC02449 chr12 8235415 8242564 +1622723 AC092745.5 chr12 8243147 8342048 +1622732 AC092745.4 chr12 8282677 8286518 +1622736 LINC00937 chr12 8295986 8396803 +1622769 AC092745.1 chr12 8321876 8329614 +1622778 CLEC6A chr12 8455962 8478330 +1622796 CLEC4D chr12 8509475 8522366 +1622829 CLEC4E chr12 8533305 8540905 +1622903 AC092746.1 chr12 8548361 8567613 +1622908 AICDA chr12 8602170 8612867 +1622969 MFAP5 chr12 8637346 8662888 +1623237 AC092490.2 chr12 8664011 8669011 +1623244 RIMKLB chr12 8681600 8783095 +1623397 A2ML1-AS1 chr12 8776219 8830947 +1623401 AC092490.1 chr12 8788253 8795789 +1623418 A2ML1-AS2 chr12 8819816 8820713 +1623422 A2ML1 chr12 8822621 8887001 +1623662 AC006581.2 chr12 8858143 8915276 +1623666 PHC1 chr12 8913896 8941467 +1623920 M6PR chr12 8940361 8949761 +1624054 KLRG1 chr12 8950044 9010760 +1624125 AC006581.1 chr12 8987175 8996566 +1624130 LINC00612 chr12 9055586 9065070 +1624135 A2M-AS1 chr12 9065163 9068689 +1624150 A2M chr12 9067664 9116229 +1624317 PZP chr12 9148840 9208395 +1624498 LINC00987 chr12 9240003 9257960 +1624506 AC010175.1 chr12 9240406 9261050 +1624517 AC009533.3 chr12 9347028 9350947 +1624522 LINC02367 chr12 9347056 9400387 +1624574 AC009533.4 chr12 9348030 9349268 +1624578 AC092821.3 chr12 9448295 9658392 +1624629 KLRB1 chr12 9594551 9607916 +1624647 AC010186.1 chr12 9647014 9648084 +1624658 AC010186.3 chr12 9658567 9662085 +1624662 CLEC2D chr12 9664969 9699553 +1624866 LINC02390 chr12 9704077 9709350 +1624870 CLECL1 chr12 9715860 9733299 +1624909 CD69 chr12 9752486 9760901 +1624945 KLRF1 chr12 9827481 9845007 +1625049 CLEC2B chr12 9852984 9870136 +1625081 AC091814.1 chr12 9867027 9869808 +1625085 KLRF2 chr12 9881489 9895833 +1625103 CLEC2A chr12 9898673 9932370 +1625134 LINC02470 chr12 9936504 9943495 +1625159 CLEC12A-AS1 chr12 9948137 9953336 +1625164 CLEC12A chr12 9951316 9995694 +1625258 CLEC1B chr12 9985642 10013424 +1625321 CLEC12B chr12 10010627 10018796 +1625389 AC024224.2 chr12 10015240 10030606 +1625394 CLEC9A chr12 10030678 10066031 +1625425 CLEC1A chr12 10069554 10111627 +1625493 CLEC7A chr12 10116777 10130258 +1625669 OLR1 chr12 10158301 10172138 +1625801 TMEM52B chr12 10170542 10191801 +1625852 GABARAPL1 chr12 10212458 10223128 +1626092 AC115676.1 chr12 10214161 10214761 +1626096 KLRD1 chr12 10226058 10329608 +1626250 LINC02617 chr12 10332861 10338292 +1626255 LINC02598 chr12 10358464 10361045 +1626259 AC022075.1 chr12 10363638 10398506 +1626288 KLRK1 chr12 10372353 10391874 +1626364 KLRC4 chr12 10407382 10409757 +1626378 KLRC3 chr12 10412312 10420595 +1626414 KLRC2 chr12 10426854 10442300 +1626506 KLRC1 chr12 10442264 10454685 +1626617 EIF2S3B chr12 10505602 10523135 +1626634 LINC02446 chr12 10553362 10572688 +1626642 MAGOHB chr12 10604193 10613609 +1626775 STYK1 chr12 10618923 10674318 +1626856 YBX3 chr12 10699089 10723323 +1627001 LINC02366 chr12 10750188 10777446 +1627076 TAS2R7 chr12 10801532 10802627 +1627084 TAS2R8 chr12 10806051 10807293 +1627092 TAS2R9 chr12 10809094 10810168 +1627100 PRH1 chr12 10824960 11171608 +1627160 TAS2R10 chr12 10825317 10826358 +1627168 PRR4 chr12 10845849 10849475 +1627227 TAS2R13 chr12 10907926 10909562 +1627235 PRH2 chr12 10929236 10934845 +1627260 TAS2R14 chr12 10937406 11171573 +1627274 TAS2R50 chr12 10985913 10986912 +1627282 TAS2R20 chr12 10996495 10997875 +1627289 TAS2R19 chr12 11021619 11022620 +1627297 TAS2R31 chr12 11030387 11031407 +1627305 TAS2R46 chr12 11061365 11062294 +1627312 TAS2R43 chr12 11091287 11092313 +1627320 TAS2R30 chr12 11132958 11134644 +1627328 AC134349.1 chr12 11166090 11171353 +1627332 SMIM10L1 chr12 11171194 11176016 +1627340 TAS2R42 chr12 11185993 11186937 +1627347 AC244131.2 chr12 11212219 11251389 +1627351 PRB3 chr12 11265924 11269805 +1627383 PRB4 chr12 11307083 11310435 +1627436 PRB1 chr12 11351823 11395566 +1627495 PRB2 chr12 11391540 11501041 +1627518 AC078950.1 chr12 11399381 11486708 +1627548 AC007450.1 chr12 11541395 11555838 +1627552 LINC01252 chr12 11548030 11590369 +1627578 ETV6 chr12 11649854 11895402 +1627625 BCL2L14 chr12 12049844 12211084 +1627788 LRP6 chr12 12116025 12267044 +1627970 MANSC1 chr12 12326056 12350242 +1628017 LOH12CR2 chr12 12355406 12357067 +1628021 BORCS5 chr12 12357078 12471233 +1628064 DUSP16 chr12 12473282 12562863 +1628125 AC007619.1 chr12 12485353 12491581 +1628129 CREBL2 chr12 12611827 12645108 +1628148 AC008115.4 chr12 12648939 12649713 +1628151 GPR19 chr12 12660890 12696207 +1628207 AC008115.2 chr12 12668982 12685075 +1628211 CDKN1B chr12 12715058 12722369 +1628246 AC008115.3 chr12 12718973 12719521 +1628249 AC008115.1 chr12 12723297 12724011 +1628253 APOLD1 chr12 12725917 12829975 +1628323 DDX47 chr12 12813316 12829981 +1628455 GPRC5A chr12 12890782 12917937 +1628501 GPRC5D-AS1 chr12 12927726 12984645 +1628544 GPRC5D chr12 12940775 12952147 +1628570 AC007688.3 chr12 12962300 12963539 +1628574 HEBP1 chr12 12974870 13000265 +1628623 AC023790.2 chr12 13000451 13040679 +1628630 FAM234B chr12 13044381 13142521 +1628730 GSG1 chr12 13083532 13103683 +1628889 EMP1 chr12 13196723 13219941 +1628989 AC022276.1 chr12 13238582 13278376 +1628995 LINC01559 chr12 13371089 13387167 +1629015 GRIN2B chr12 13437942 13981957 +1629091 AC007527.1 chr12 13526854 13547582 +1629098 AC007527.2 chr12 13540231 13544540 +1629102 AC007535.1 chr12 13582031 13620077 +1629107 AC092112.1 chr12 14216590 14221297 +1629111 ATF7IP chr12 14365632 14502935 +1629439 PLBD1 chr12 14503661 14567883 +1629501 AC008114.1 chr12 14530124 14543575 +1629512 PLBD1-AS1 chr12 14567393 14624191 +1629530 GUCY2C chr12 14612632 14696599 +1629599 AC010168.1 chr12 14665655 14757963 +1629606 AC010168.2 chr12 14762504 14767931 +1629609 HIST4H4 chr12 14767999 14771131 +1629638 H2AFJ chr12 14774383 14778002 +1629662 WBP11 chr12 14784582 14803486 +1629732 C12orf60 chr12 14803666 14906586 +1629757 SMCO3 chr12 14804650 14814182 +1629767 AC007655.2 chr12 14805108 14808177 +1629771 ART4 chr12 14825569 14843526 +1629806 AC007655.1 chr12 14841092 14844708 +1629810 MGP chr12 14880864 14885857 +1629849 ERP27 chr12 14914039 14938537 +1629887 ARHGDIB chr12 14942031 14961728 +1629999 PDE6H chr12 14973042 14981865 +1630013 LINC01489 chr12 15001787 15006999 +1630019 RERG chr12 15107783 15348675 +1630117 RERG-IT1 chr12 15112363 15114698 +1630121 RERG-AS1 chr12 15151923 15155283 +1630126 PTPRO chr12 15322508 15598331 +1630436 EPS8 chr12 15620134 15882329 +1631261 AC073651.1 chr12 15780068 15782120 +1631265 STRAP chr12 15882387 15903478 +1631356 DERA chr12 15911302 16037381 +1631525 SLC15A5 chr12 16188485 16277685 +1631548 MGST1 chr12 16347142 16609259 +1631702 AC007528.1 chr12 16420653 16447217 +1631706 LMO3 chr12 16548372 16610594 +1632113 AC007552.2 chr12 16567411 16573940 +1632117 AC007529.2 chr12 16661766 16788375 +1632126 AC007529.1 chr12 16693800 16695977 +1632129 AC092793.1 chr12 17066368 17075631 +1632139 AC092110.1 chr12 17083531 17167790 +1632159 AC048352.1 chr12 17479446 17709867 +1632185 LINC02378 chr12 17509353 17590049 +1632214 RERGL chr12 18080869 18320107 +1632277 PIK3C2G chr12 18247614 18648416 +1632601 PLCZ1 chr12 18683169 18738100 +1632943 AC087242.1 chr12 18714795 18737878 +1632948 CAPZA3 chr12 18738119 18739188 +1632956 PLEKHA5 chr12 19129752 19376400 +1633404 AC092828.1 chr12 19147074 19154659 +1633408 AEBP2 chr12 19404045 19720801 +1633534 AC137561.1 chr12 19582317 19583274 +1633538 AC024901.1 chr12 19775451 20012261 +1633566 LINC02398 chr12 20014780 20098868 +1633571 AC126468.1 chr12 20104590 20109893 +1633576 LINC02468 chr12 20120980 20136163 +1633612 AC129102.1 chr12 20361732 20370262 +1633616 PDE3A chr12 20369245 20684381 +1633673 SLCO1C1 chr12 20695355 20753386 +1633860 SLCO1B3 chr12 20810702 20916911 +1633978 SLCO1B7 chr12 20962768 21092745 +1634033 SLCO1B1 chr12 21131194 21239796 +1634069 SLCO1A2 chr12 21264600 21419594 +1634351 IAPP chr12 21354959 21379980 +1634405 PYROXD1 chr12 21437615 21471250 +1634566 RECQL chr12 21468910 21501669 +1634721 GOLT1B chr12 21501781 21518408 +1634843 SPX chr12 21526296 21541249 +1634912 GYS2 chr12 21536107 21604847 +1634950 LDHB chr12 21635342 21757857 +1635074 AC010197.1 chr12 21662313 21760032 +1635078 AC010185.1 chr12 21759980 21766705 +1635082 KCNJ8 chr12 21764955 21775600 +1635130 ABCC9 chr12 21797401 21942529 +1635421 AC008250.1 chr12 21827210 21887957 +1635427 AC008250.2 chr12 21828360 21828564 +1635430 CMAS chr12 22046218 22065674 +1635501 ST8SIA1 chr12 22063773 22437041 +1635618 AC007671.1 chr12 22104491 22105320 +1635621 AC087318.1 chr12 22395088 22398075 +1635625 AC053513.1 chr12 22409237 22618868 +1635647 C2CD5 chr12 22448583 22544546 +1636106 AC053513.2 chr12 22460519 22463914 +1636110 AC087241.2 chr12 22609228 22625015 +1636114 ETNK1 chr12 22625075 22690665 +1636256 AC084816.1 chr12 22699859 23188807 +1636361 AC084819.1 chr12 22742582 22743091 +1636365 AC087235.2 chr12 23175648 23191587 +1636372 AC087235.1 chr12 23181334 23251499 +1636376 SOX5 chr12 23529504 24562544 +1636765 AC087260.1 chr12 23637973 23638487 +1636769 SOX5-AS1 chr12 24223233 24260056 +1636880 LINC00477 chr12 24566964 24584168 +1636886 AC023796.1 chr12 24704503 24775565 +1636931 BCAT1 chr12 24810024 24949101 +1637100 AC023796.2 chr12 24830421 24836558 +1637104 AC026310.2 chr12 24949163 24960158 +1637110 C12orf77 chr12 24993424 25006403 +1637125 LRMP chr12 25004342 25108334 +1637641 AC023510.1 chr12 25096868 25100980 +1637646 AC023510.2 chr12 25103124 25103869 +1637649 CASC1 chr12 25108289 25195162 +1637952 ETFRF1 chr12 25195216 25209645 +1638068 KRAS chr12 25205246 25250936 +1638123 AC092794.1 chr12 25210652 25211233 +1638126 AC092794.2 chr12 25225103 25225665 +1638129 AC087239.1 chr12 25385670 25386241 +1638132 LMNTD1 chr12 25409307 25648579 +1638320 AC022367.1 chr12 25585994 25592928 +1638327 AC019209.3 chr12 25782706 25814171 +1638332 AC019209.2 chr12 25831416 25834182 +1638336 AC019209.1 chr12 25882955 25885855 +1638340 RASSF8-AS1 chr12 25936683 25959765 +1638448 RASSF8 chr12 25959029 26079892 +1638626 BHLHE41 chr12 26120030 26125037 +1638649 SSPN chr12 26121991 26299290 +1638715 AC022509.3 chr12 26125155 26126617 +1638724 AC022509.5 chr12 26139249 26167741 +1638729 AC022509.2 chr12 26211164 26335856 +1638735 AC022509.1 chr12 26229548 26319720 +1638751 AC022509.4 chr12 26273329 26273900 +1638754 AC055720.1 chr12 26301098 26317813 +1638761 AC024145.1 chr12 26318953 26421462 +1638769 ITPR2 chr12 26335352 26833194 +1638984 AC055720.2 chr12 26335864 26336950 +1638988 AC023051.1 chr12 26623369 26649479 +1638993 INTS13 chr12 26905181 26938326 +1639115 FGFR1OP2 chr12 26938470 26966650 +1639186 TM7SF3 chr12 26971579 27014434 +1639406 AC024896.1 chr12 26971586 26979582 +1639410 MED21 chr12 27022546 27066343 +1639471 AC092747.4 chr12 27037100 27038960 +1639474 C12orf71 chr12 27081058 27082514 +1639484 AC092747.1 chr12 27105151 27161393 +1639491 STK38L chr12 27243968 27325959 +1639674 ARNTL2 chr12 27332854 27425289 +1639962 ARNTL2-AS1 chr12 27389789 27446625 +1639968 SMCO2 chr12 27466810 27502185 +1640044 PPFIBP1 chr12 27523431 27695564 +1640484 AC087257.1 chr12 27547050 27552773 +1640488 AC009509.1 chr12 27696388 27710803 +1640507 REP15 chr12 27696447 27697596 +1640515 AC009509.4 chr12 27700066 27700574 +1640518 AC009509.2 chr12 27704568 27708365 +1640522 MRPS35 chr12 27710822 27756295 +1640604 MANSC4 chr12 27762738 27771276 +1640615 AC009511.2 chr12 27779821 27781067 +1640619 KLHL42 chr12 27780048 27803040 +1640658 AC009511.1 chr12 27798641 27800708 +1640662 PTHLH chr12 27958084 27972733 +1640770 AC008011.2 chr12 27958517 27969813 +1640774 CCDC91 chr12 28133249 28581511 +1641137 AC022364.1 chr12 28163298 28190738 +1641145 AC022079.2 chr12 28185625 28186190 +1641148 AC022079.1 chr12 28236227 28236828 +1641151 AC022081.1 chr12 28821975 28825831 +1641155 AC012150.1 chr12 29142969 29158537 +1641163 FAR2 chr12 29149103 29340980 +1641303 AC012150.2 chr12 29156448 29156991 +1641306 AC009318.4 chr12 29277397 29277882 +1641309 AC009318.1 chr12 29277955 29317848 +1641324 AC009318.3 chr12 29331434 29331936 +1641327 AC009318.2 chr12 29332733 29333383 +1641330 ERGIC2 chr12 29337352 29381189 +1641546 OVCH1-AS1 chr12 29389289 29487488 +1641559 OVCH1 chr12 29412474 29497686 +1641642 TMTC1 chr12 29500840 29784759 +1641866 AC009320.1 chr12 29519731 29529974 +1641871 AC023511.3 chr12 30086342 30130590 +1641875 AC023511.1 chr12 30200983 30217916 +1641880 LINC02386 chr12 30230779 30296707 +1641918 AC078776.1 chr12 30320834 30321617 +1641922 IPO8 chr12 30628988 30695869 +1642108 AC012673.1 chr12 30696121 30700220 +1642112 CAPRIN2 chr12 30709552 30754951 +1642500 AC010198.1 chr12 30755074 30780739 +1642504 AC010198.2 chr12 30795458 30879268 +1642574 TSPAN11 chr12 30926428 30996602 +1642645 DDX11-AS1 chr12 31019434 31073847 +1642659 DDX11 chr12 31073860 31104799 +1643292 AC024940.6 chr12 31280422 31280895 +1643295 SINHCAF chr12 31280584 31327058 +1643406 AC024940.1 chr12 31324316 31325829 +1643409 LINC02387 chr12 31363481 31369301 +1643413 DENND5B chr12 31382226 31591136 +1643566 AC068792.1 chr12 31443792 31444208 +1643569 DENND5B-AS1 chr12 31589923 31615666 +1643578 AC068774.1 chr12 31627575 31652095 +1643582 ETFBKMT chr12 31647160 31673114 +1643653 AMN1 chr12 31671142 31729121 +1643828 AC023157.3 chr12 31729117 31731204 +1643831 H3F3C chr12 31791185 31792298 +1643839 LINC02422 chr12 31876969 31959316 +1643847 RESF1 chr12 31959370 31993107 +1643905 AC016957.2 chr12 32000375 32001222 +1643908 AC048344.1 chr12 32104117 32107528 +1643913 BICD1 chr12 32106835 32383633 +1644053 AC048344.4 chr12 32109076 32109602 +1644056 AC026356.1 chr12 32339368 32340724 +1644059 AC026356.2 chr12 32352349 32354144 +1644062 FGD4 chr12 32399529 32646050 +1644462 DNM1L chr12 32679200 32745650 +1645074 AC084824.5 chr12 32725248 32725660 +1645077 YARS2 chr12 32727490 32755897 +1645110 AC084824.3 chr12 32728169 32729024 +1645113 AC084824.4 chr12 32736930 32737660 +1645116 AC087588.3 chr12 32755510 32756463 +1645119 PKP2 chr12 32790745 32896840 +1645205 AC087588.2 chr12 32820142 32820567 +1645208 AC087311.2 chr12 32988763 32993754 +1645212 SYT10 chr12 33374238 33439819 +1645258 AC023158.1 chr12 33404872 33405896 +1645261 AC023158.2 chr12 33432311 33432853 +1645264 AC046130.1 chr12 34022281 34046417 +1645268 ALG10 chr12 34022468 34029694 +1645305 AC046130.2 chr12 34037232 34058745 +1645315 AC140847.1 chr12 34149839 34162238 +1645320 AC140847.2 chr12 34190471 34219246 +1645344 AC079460.2 chr12 38155476 38167631 +1645349 ALG10B chr12 38316762 38329721 +1645386 AC087897.2 chr12 38544177 38589812 +1645395 CPNE8 chr12 38646822 38907430 +1645552 CPNE8-AS1 chr12 38906451 38909592 +1645556 LINC02406 chr12 39087347 39145482 +1645575 KIF21A chr12 39293228 39443390 +1646113 AC121334.4 chr12 39447404 39448314 +1646117 ABCD2 chr12 39550033 39619803 +1646143 AC121334.3 chr12 39611819 39614648 +1646147 C12orf40 chr12 39626167 39908300 +1646249 SLC2A13 chr12 39755025 40106089 +1646295 LINC02555 chr12 40140926 40142876 +1646298 LINC02471 chr12 40156113 40211419 +1646319 AC079630.1 chr12 40186009 40224915 +1646327 LRRK2 chr12 40196744 40369285 +1646673 MUC19 chr12 40393395 40570832 +1646970 AC107023.1 chr12 40395853 40443847 +1646976 CNTN1 chr12 40692439 41072415 +1647274 AC015540.1 chr12 40978744 40979244 +1647277 PDZRN4 chr12 41188320 41574745 +1647379 AC090531.1 chr12 41409467 41473510 +1647390 LINC02400 chr12 41764144 41774671 +1647416 AC090630.1 chr12 41829898 41932592 +1647420 AC006197.2 chr12 41951493 42024329 +1647432 GXYLT1 chr12 42081845 42144874 +1647473 YAF2 chr12 42157104 42238349 +1647667 PPHLN1 chr12 42238447 42459715 +1648135 ZCRB1 chr12 42312086 42326118 +1648199 AC079684.1 chr12 42361267 42361703 +1648202 PRICKLE1 chr12 42456757 42590355 +1648502 AC079601.1 chr12 42459366 42466128 +1648506 AC079600.3 chr12 42485353 42498979 +1648514 LINC02402 chr12 42615221 42646547 +1648528 LINC02451 chr12 42646583 42686701 +1648541 LINC02450 chr12 42687195 42717120 +1648576 AC012038.2 chr12 42966122 42967353 +1648580 AC012038.1 chr12 42979254 42996486 +1648585 LINC02461 chr12 43155315 43163110 +1648591 ADAMTS20 chr12 43353866 43552203 +1648824 PUS7L chr12 43718993 43758817 +1648965 IRAK4 chr12 43758944 43789543 +1649281 TWF1 chr12 43793723 43806375 +1649452 TMEM117 chr12 43835967 44389762 +1649547 AC025030.2 chr12 44244394 44263982 +1649551 AC025253.1 chr12 44498616 44499158 +1649554 AC025253.2 chr12 44499961 44503596 +1649558 NELL2 chr12 44508275 44921848 +1650013 DBX2 chr12 45014672 45051099 +1650027 AC008127.1 chr12 45050901 45103107 +1650031 AC009248.3 chr12 45164186 45170809 +1650036 ANO6 chr12 45215987 45440404 +1650256 AC009248.2 chr12 45256473 45256726 +1650259 AC079950.1 chr12 45475520 45610620 +1650270 AC008124.1 chr12 45718046 45727775 +1650273 ARID2 chr12 45729706 45908040 +1650454 AC009464.1 chr12 45789189 45789657 +1650457 SCAF11 chr12 45919131 45992120 +1650639 SLC38A1 chr12 46183063 46270017 +1650908 AC025031.3 chr12 46239106 46239473 +1650911 SLC38A2 chr12 46358188 46372773 +1651090 AC025031.2 chr12 46371463 46373778 +1651094 AC008014.1 chr12 46383652 46876784 +1651131 AC025031.1 chr12 46384233 46386991 +1651135 AC025031.4 chr12 46388856 46392126 +1651138 AC008035.1 chr12 46537502 46652550 +1651143 SLC38A4 chr12 46764761 46832408 +1651265 AC079906.1 chr12 46970504 46972155 +1651269 AMIGO2 chr12 47075707 47079951 +1651301 PCED1B chr12 47079603 47236662 +1651358 PCED1B-AS1 chr12 47205898 47216456 +1651420 AC008083.2 chr12 47237734 47279021 +1651424 AC008083.3 chr12 47248124 47257539 +1651432 AC008083.4 chr12 47265665 47266108 +1651435 LINC02416 chr12 47353754 47369935 +1651440 LINC02156 chr12 47377638 47420192 +1651493 RPAP3 chr12 47661249 47706030 +1651621 AC004241.3 chr12 47699401 47699917 +1651624 AC004241.1 chr12 47706083 47742294 +1651666 ENDOU chr12 47709734 47725567 +1651740 AC004241.2 chr12 47731908 47732351 +1651743 RAPGEF3 chr12 47734363 47771040 +1652309 SLC48A1 chr12 47753916 47782751 +1652394 AC004241.4 chr12 47768529 47769648 +1652397 HDAC7 chr12 47782722 47833132 +1653062 AC004466.1 chr12 47784923 47786002 +1653065 AC004466.3 chr12 47788426 47788971 +1653068 AC004466.2 chr12 47817451 47817966 +1653071 LINC02354 chr12 47826854 47837898 +1653089 VDR chr12 47841537 47943048 +1653252 AC121338.1 chr12 47882649 47901525 +1653258 AC121338.2 chr12 47905122 47906865 +1653261 TMEM106C chr12 47963569 47968878 +1653547 COL2A1 chr12 47972967 48004554 +1653844 AC004801.5 chr12 48005277 48011227 +1653856 AC004801.4 chr12 48011304 48025469 +1653862 AC004801.3 chr12 48019771 48025382 +1653866 AC004801.6 chr12 48039784 48040761 +1653869 SENP1 chr12 48042897 48106079 +1654074 PFKM chr12 48105139 48146404 +1654915 ASB8 chr12 48147789 48181213 +1655130 AC074029.3 chr12 48152817 48153128 +1655133 CCDC184 chr12 48183644 48185926 +1655141 AC024257.3 chr12 48198357 48230275 +1655155 OR10AD1 chr12 48202083 48203387 +1655163 AC024257.1 chr12 48231098 48284210 +1655169 AC024257.5 chr12 48327942 48328472 +1655172 H1FNT chr12 48328980 48330279 +1655180 ZNF641 chr12 48337180 48351414 +1655301 AC090115.1 chr12 48350945 48442411 +1655307 AC024257.4 chr12 48360920 48361377 +1655310 ANP32D chr12 48472665 48473622 +1655317 C12orf54 chr12 48482498 48496386 +1655384 AC089987.2 chr12 48483287 48500961 +1655389 OR8S1 chr12 48525632 48528103 +1655404 OR5BS1P chr12 48559882 48562956 +1655413 LALBA chr12 48567684 48570066 +1655438 KANSL2 chr12 48653401 48682238 +1655648 CCNT1 chr12 48688458 48716998 +1655736 TEX49 chr12 48727435 48765790 +1655765 AC117498.1 chr12 48766194 48767323 +1655769 ADCY6 chr12 48766194 48789037 +1655952 ADCY6-DT chr12 48789147 48790535 +1655961 CACNB3 chr12 48813794 48828941 +1656328 DDX23 chr12 48829756 48852842 +1656505 RND1 chr12 48857145 48865870 +1656554 CCDC65 chr12 48904110 48931840 +1656639 FKBP11 chr12 48921518 48926474 +1656772 ARF3 chr12 48935723 48957487 +1656863 WNT10B chr12 48965340 48971735 +1656936 WNT1 chr12 48978322 48982620 +1656965 DDN chr12 48995149 48999375 +1656975 AC011603.3 chr12 48995150 48996334 +1656979 DDN-AS1 chr12 48998367 49019235 +1656994 PRKAG1 chr12 49002274 49018807 +1657347 KMT2D chr12 49018975 49059774 +1657510 RHEBL1 chr12 49064676 49070025 +1657585 DHH chr12 49086656 49094801 +1657597 AC011603.1 chr12 49090208 49093312 +1657606 LMBR1L chr12 49096551 49110900 +1658018 TUBA1B chr12 49127782 49131397 +1658098 AC011603.2 chr12 49127782 49188484 +1658126 TUBA1A chr12 49184795 49189080 +1658213 TUBA1C chr12 49188736 49274603 +1658313 AC010173.1 chr12 49232790 49264756 +1658317 AC125611.3 chr12 49265156 49273306 +1658321 AC125611.4 chr12 49292631 49324576 +1658331 PRPH chr12 49293252 49298686 +1658404 TROAP chr12 49323236 49331731 +1658699 C1QL4 chr12 49332409 49337188 +1658709 DNAJC22 chr12 49346888 49357546 +1658753 SPATS2 chr12 49366584 49527424 +1659084 AC020612.4 chr12 49536677 49538894 +1659088 KCNH3 chr12 49539030 49558337 +1659174 MCRS1 chr12 49556544 49568145 +1659474 PRPF40B chr12 49568218 49644666 +1659723 AC020612.3 chr12 49576840 49577505 +1659727 FAM186B chr12 49582885 49605639 +1659805 FMNL3 chr12 49636499 49708165 +1660010 TMBIM6 chr12 49707725 49764934 +1660415 NCKAP5L chr12 49791146 49828750 +1660470 BCDIN3D-AS1 chr12 49827913 49841143 +1660491 BCDIN3D chr12 49836043 49843106 +1660504 AC131157.1 chr12 49861207 49865802 +1660510 FAIM2 chr12 49866896 49904217 +1660674 LINC02395 chr12 49900311 49932764 +1661188 LINC02396 chr12 49908882 49911863 +1661207 AQP2 chr12 49950741 49958881 +1661247 AC025154.2 chr12 49951512 49962924 +1661259 AC025154.1 chr12 49954639 49956125 +1661263 AQP5 chr12 49961872 49965682 +1661280 AQP6 chr12 49967194 49977139 +1661342 RACGAP1 chr12 49976923 50033136 +1661846 ASIC1 chr12 50057548 50083611 +1662014 SMARCD1 chr12 50085200 50100707 +1662180 GPD1 chr12 50103982 50111313 +1662259 COX14 chr12 50112082 50120457 +1662300 AC074032.1 chr12 50112197 50165618 +1662307 CERS5 chr12 50129299 50167533 +1662643 LIMA1 chr12 50175788 50283546 +1662870 AC008147.2 chr12 50185580 50191363 +1662874 AC008147.1 chr12 50219604 50229984 +1662878 FAM186A chr12 50326230 50396622 +1662945 LARP4 chr12 50392383 50480004 +1663392 DIP2B chr12 50504985 50748657 +1663551 ATF1 chr12 50763710 50821162 +1663631 TMPRSS12 chr12 50842920 50887884 +1663660 METTL7A chr12 50923472 50932510 +1663710 AC008121.2 chr12 50934942 50935464 +1663713 HIGD1C chr12 50953922 50970506 +1663725 AC008121.3 chr12 50953924 50954356 +1663728 SLC11A2 chr12 50979401 51028566 +1664414 LETMD1 chr12 51047962 51060424 +1664834 CSRNP2 chr12 51061205 51083664 +1664902 TFCP2 chr12 51093656 51173135 +1665040 POU6F1 chr12 51186936 51217708 +1665165 AC139768.1 chr12 51201684 51202581 +1665168 DAZAP2 chr12 51238724 51271362 +1665311 SMAGP chr12 51244558 51270415 +1665410 BIN2 chr12 51281038 51324668 +1665599 CELA1 chr12 51328442 51346679 +1665621 GALNT6 chr12 51351247 51392867 +1665827 SLC4A8 chr12 51391317 51515763 +1666135 AC107031.1 chr12 51421956 51424611 +1666139 SCN8A chr12 51590266 51812864 +1666734 AC068987.1 chr12 51809705 51810600 +1666737 C12orf81 chr12 51813940 51814926 +1666745 AC068987.2 chr12 51815043 51842106 +1666758 FIGNL2 chr12 51817840 51848766 +1666777 AC068987.3 chr12 51817899 51820150 +1666781 FIGNL2-DT chr12 51848223 51852729 +1666786 ANKRD33 chr12 51888009 51891727 +1666857 ACVRL1 chr12 51906908 51923361 +1666958 ACVR1B chr12 51951699 51997078 +1667084 GRASP chr12 52006946 52015889 +1667164 NR4A1 chr12 52022832 52059507 +1667385 AC025259.3 chr12 52058459 52059503 +1667392 ATG101 chr12 52069246 52077494 +1667444 AC025259.1 chr12 52076841 52082084 +1667448 SMIM41 chr12 52079696 52108239 +1667460 AC078864.1 chr12 52092485 52104297 +1667465 LINC00592 chr12 52164115 52223813 +1667543 KRT80 chr12 52168996 52192014 +1667598 C12orf80 chr12 52205392 52213583 +1667624 KRT7 chr12 52232520 52252186 +1667708 KRT7-AS chr12 52245048 52247448 +1667712 KRT86 chr12 52249300 52309163 +1667772 AC021066.1 chr12 52274647 52279156 +1667776 KRT81 chr12 52285913 52291534 +1667825 AC121757.2 chr12 52298856 52306287 +1667830 AC121757.1 chr12 52306616 52308371 +1667834 KRT83 chr12 52314301 52321398 +1667858 KRT85 chr12 52360006 52367481 +1667906 KRT84 chr12 52377812 52385652 +1667930 AC078865.1 chr12 52380460 52402407 +1667934 KRT82 chr12 52393931 52406355 +1667958 AC055736.1 chr12 52407580 52428494 +1667963 KRT75 chr12 52424070 52434371 +1667987 KRT6B chr12 52446651 52452146 +1668011 KRT6C chr12 52468516 52473805 +1668038 KRT6A chr12 52487176 52493257 +1668080 KRT5 chr12 52514575 52520530 +1668184 KRT71 chr12 52543909 52553145 +1668208 KRT74 chr12 52565782 52573843 +1668261 KRT72 chr12 52585589 52601538 +1668361 KRT73-AS1 chr12 52601467 52615305 +1668375 KRT73 chr12 52607570 52618559 +1668423 KRT2 chr12 52644558 52652211 +1668452 KRT1 chr12 52674736 52680407 +1668481 KRT77 chr12 52689626 52703524 +1668533 AC055716.3 chr12 52692605 52696788 +1668538 KRT76 chr12 52768155 52777345 +1668562 KRT3 chr12 52789685 52796117 +1668586 KRT4 chr12 52806549 52814116 +1668652 KRT79 chr12 52821408 52834311 +1668691 KRT78 chr12 52837804 52849092 +1668756 KRT8 chr12 52897187 52949954 +1668958 KRT18 chr12 52948871 52952906 +1669034 EIF4B chr12 53006158 53042209 +1669282 AC068888.2 chr12 53012104 53013921 +1669286 AC068888.1 chr12 53012884 53054450 +1669399 TNS2 chr12 53046969 53064372 +1669883 SPRYD3 chr12 53064316 53079404 +1669982 IGFBP6 chr12 53097436 53102345 +1670050 SOAT2 chr12 53103486 53124535 +1670132 CSAD chr12 53157663 53180909 +1670514 AC073573.1 chr12 53159586 53161000 +1670519 ZNF740 chr12 53180704 53195142 +1670552 ITGB7 chr12 53191323 53207282 +1670753 RARG chr12 53210567 53232980 +1670927 AC021072.1 chr12 53241889 53242723 +1670935 MFSD5 chr12 53251251 53254405 +1670967 ESPL1 chr12 53268299 53293643 +1671213 PFDN5 chr12 53295291 53299450 +1671395 AC073611.1 chr12 53298655 53300314 +1671399 C12orf10 chr12 53299695 53307177 +1671485 AAAS chr12 53307456 53324864 +1671833 SP7 chr12 53326575 53345315 +1671870 SP1 chr12 53380176 53416446 +1671921 AMHR2 chr12 53423855 53431672 +1672027 PRR13 chr12 53441678 53446645 +1672171 PCBP2 chr12 53452102 53481162 +1672719 PCBP2-OT1 chr12 53464468 53465057 +1672722 MAP3K12 chr12 53479669 53500063 +1672888 AC023509.3 chr12 53500162 53500936 +1672891 TARBP2 chr12 53500921 53506431 +1673176 NPFF chr12 53506690 53507638 +1673188 ATF7 chr12 53507856 53626410 +1673361 AC023509.2 chr12 53513891 53517608 +1673366 AC023509.6 chr12 53531752 53621218 +1673375 ATP5MC2 chr12 53632726 53677408 +1673479 CALCOCO1 chr12 53708517 53727745 +1673788 AC076968.2 chr12 53739611 53898976 +1673810 CISTR chr12 53746337 53757227 +1673826 AC076968.1 chr12 53754358 53762104 +1673830 HOXC13-AS chr12 53935328 53939643 +1673835 HOXC13 chr12 53938831 53946544 +1673845 HOXC12 chr12 53954903 53958956 +1673855 HOTAIR chr12 53962308 53974956 +1673887 HOXC11 chr12 53973126 53977643 +1673906 HOXC-AS3 chr12 53981509 53985519 +1673919 HOXC10 chr12 53985065 53990279 +1673945 HOXC6 chr12 53990624 54030823 +1673982 HOXC-AS2 chr12 53993810 53996785 +1673989 HOXC9 chr12 53994895 54003337 +1674013 HOXC-AS1 chr12 53999022 54000010 +1674020 HOXC8 chr12 54008985 54012769 +1674030 HOXC4 chr12 54016931 54056030 +1674057 AC012531.1 chr12 54019910 54022589 +1674060 HOXC5 chr12 54032853 54035358 +1674070 AC023794.1 chr12 54058254 54122235 +1674077 AC023794.3 chr12 54081736 54102699 +1674109 FAM242C chr12 54085132 54125992 +1674125 SMUG1 chr12 54121277 54189008 +1674371 LINC02381 chr12 54126082 54147485 +1674391 AC023794.6 chr12 54145069 54147225 +1674394 AC023794.5 chr12 54162065 54164452 +1674398 AC023794.2 chr12 54163139 54168595 +1674403 CBX5 chr12 54230942 54280133 +1674465 SCAT2 chr12 54262615 54279063 +1674469 AC078778.1 chr12 54276631 54345083 +1674473 HNRNPA1 chr12 54280193 54287088 +1674683 NFE2 chr12 54292111 54301015 +1674737 COPZ1 chr12 54301202 54351846 +1675038 AC079313.2 chr12 54353661 54497688 +1675048 AC079313.1 chr12 54353792 54466985 +1675054 GPR84 chr12 54362445 54364487 +1675071 ZNF385A chr12 54369133 54391298 +1675296 ITGA5 chr12 54395261 54419266 +1675475 LINC01154 chr12 54428303 54429403 +1675479 GTSF1 chr12 54455950 54473602 +1675582 NCKAP1L chr12 54497752 54548243 +1675807 AC068789.1 chr12 54543111 54544105 +1675811 PDE1B chr12 54549601 54579239 +1676017 PPP1R1A chr12 54575387 54588659 +1676084 LACRT chr12 54630811 54634895 +1676130 DCD chr12 54644589 54648493 +1676180 AC079310.1 chr12 54682973 54687434 +1676185 MUCL1 chr12 54830518 54896008 +1676240 TESPA1 chr12 54948015 54984762 +1676493 AC027287.2 chr12 55009746 55014247 +1676498 NEUROD4 chr12 55019974 55030017 +1676508 OR9K2 chr12 55126406 55132750 +1676542 OR10A7 chr12 55221025 55221975 +1676549 OR6C74 chr12 55247198 55248302 +1676557 OR6C6 chr12 55293988 55296569 +1676567 OR6C1 chr12 55314343 55322364 +1676584 OR6C3 chr12 55330043 55332687 +1676609 OR6C75 chr12 55362975 55369279 +1676636 OR6C65 chr12 55400430 55401505 +1676644 OR6C76 chr12 55426254 55427192 +1676651 AC122685.1 chr12 55434734 55585471 +1676669 OR6C2 chr12 55444069 55453347 +1676694 OR6C70 chr12 55469200 55470138 +1676701 OR6C68 chr12 55492378 55493316 +1676708 OR6C4 chr12 55549602 55555832 +1676734 OR2AP1 chr12 55572468 55575612 +1676750 OR10P1 chr12 55636860 55637854 +1676758 AC009779.5 chr12 55638912 55659795 +1676762 METTL7B chr12 55681678 55684611 +1676783 ITGA7 chr12 55684568 55716043 +1677213 BLOC1S1 chr12 55716037 55720087 +1677282 RDH5 chr12 55720367 55724705 +1677367 CD63 chr12 55725323 55729707 +1677633 AC009779.2 chr12 55729104 55730852 +1677637 GDF11 chr12 55743122 55757264 +1677660 SARNP chr12 55752463 55817724 +1677780 AC073487.1 chr12 55761550 55762628 +1677784 ORMDL2 chr12 55818041 55821879 +1677838 DNAJC14 chr12 55820960 55830824 +1677925 MMP19 chr12 55835433 55842966 +1678054 PYM1 chr12 55901413 55932618 +1678122 DGKA chr12 55927319 55954027 +1678846 AC025162.2 chr12 55929170 55929729 +1678849 PMEL chr12 55954105 55973317 +1679124 CDK2 chr12 55966781 55972789 +1679258 AC025162.1 chr12 55966838 55967474 +1679262 RAB5B chr12 55973913 55996683 +1679386 SUOX chr12 55997180 56006641 +1679559 IKZF4 chr12 56007659 56038435 +1679720 AC034102.8 chr12 56010091 56010574 +1679723 AC034102.3 chr12 56029649 56041806 +1679727 RPS26 chr12 56041351 56044697 +1679775 ERBB3 chr12 56076799 56103505 +1680173 PA2G4 chr12 56104537 56113910 +1680268 AC034102.4 chr12 56104614 56113905 +1680272 RPL41 chr12 56116590 56117967 +1680313 ESYT1 chr12 56118250 56144671 +1680500 ZC3H10 chr12 56118260 56127514 +1680540 AC034102.7 chr12 56118968 56119939 +1680544 AC034102.6 chr12 56120033 56129619 +1680553 AC034102.5 chr12 56150796 56158220 +1680558 MYL6B chr12 56152256 56159647 +1680661 MYL6 chr12 56158161 56163496 +1680923 SMARCC2 chr12 56162359 56189567 +1681317 AC073896.4 chr12 56162359 56190284 +1681321 RNF41 chr12 56202179 56221933 +1681495 NABP2 chr12 56222015 56229854 +1681590 SLC39A5 chr12 56230049 56237846 +1681724 ANKRD52 chr12 56237807 56258384 +1681802 COQ10A chr12 56266858 56270966 +1681885 AC073896.5 chr12 56267793 56270104 +1681889 CS chr12 56271699 56300391 +1682327 AC073896.2 chr12 56300076 56317992 +1682338 AC073896.3 chr12 56308868 56309449 +1682342 CNPY2 chr12 56309842 56316119 +1682434 PAN2 chr12 56316223 56334053 +1682832 IL23A chr12 56334174 56340410 +1682858 STAT2 chr12 56341597 56360167 +1683517 APOF chr12 56360568 56362857 +1683527 AC024884.2 chr12 56411944 56413190 +1683530 TIMELESS chr12 56416363 56449426 +1683678 MIP chr12 56449502 56469166 +1683709 SPRYD4 chr12 56468578 56479708 +1683719 GLS2 chr12 56470944 56488414 +1684091 RBMS2 chr12 56521820 56596193 +1684280 BAZ2A chr12 56595596 56636816 +1684589 ATP5F1B chr12 56638175 56645984 +1684699 PTGES3 chr12 56663341 56688408 +1684834 NACA chr12 56712428 56731628 +1685140 PRIM1 chr12 56731296 56752374 +1685288 HSD17B6 chr12 56752161 56787790 +1685399 SDR9C7 chr12 56923133 56934408 +1685413 RDH16 chr12 56951431 56959374 +1685431 AC026120.3 chr12 56987734 56990756 +1685435 GPR182 chr12 56994492 56998447 +1685458 ZBTB39 chr12 56998836 57006546 +1685468 TAC3 chr12 57010000 57028883 +1685684 MYO1A chr12 57028517 57051198 +1685905 NEMP1 chr12 57055643 57088063 +1685975 NAB2 chr12 57089043 57095476 +1686022 STAT6 chr12 57095408 57132139 +1686656 LRP1 chr12 57128483 57213361 +1686956 LRP1-AS chr12 57144620 57147619 +1686963 NXPH4 chr12 57216794 57226449 +1686987 AC137834.2 chr12 57229498 57230198 +1686990 SHMT2 chr12 57229573 57234935 +1687538 NDUFA4L2 chr12 57234903 57240715 +1687593 STAC3 chr12 57243453 57251188 +1687716 R3HDM2 chr12 57253762 57431005 +1688132 AC126614.1 chr12 57431116 57433935 +1688136 INHBC chr12 57434784 57452062 +1688146 INHBE chr12 57452323 57459280 +1688172 AC022506.2 chr12 57457596 57462818 +1688176 GLI1 chr12 57459785 57472268 +1688312 ARHGAP9 chr12 57472264 57488814 +1688741 MARS chr12 57475445 57517569 +1689179 DDIT3 chr12 57516588 57521737 +1689254 AC022506.1 chr12 57517712 57520480 +1689263 MBD6 chr12 57520710 57530148 +1689434 DCTN2 chr12 57530102 57547331 +1689764 KIF5A chr12 57550044 57586633 +1689888 PIP4K2C chr12 57591174 57603418 +1690044 DTX3 chr12 57604622 57609804 +1690166 ARHGEF25 chr12 57610180 57617245 +1690301 AC025165.1 chr12 57612118 57619638 +1690316 SLC26A10 chr12 57619527 57626151 +1690439 B4GALNT1 chr12 57623409 57633239 +1690673 OS9 chr12 57693955 57721557 +1691088 AC025165.2 chr12 57694132 57721510 +1691092 AGAP2 chr12 57723761 57742157 +1691228 AGAP2-AS1 chr12 57726271 57728356 +1691232 TSPAN31 chr12 57738013 57750219 +1691369 CDK4 chr12 57747727 57756013 +1691561 MARCH9 chr12 57755103 57760411 +1691587 CYP27B1 chr12 57762334 57768986 +1691653 METTL1 chr12 57768471 57772119 +1691738 EEF1AKMT3 chr12 57771492 57782541 +1691791 TSFM chr12 57782761 57808071 +1691982 AVIL chr12 57797376 57818704 +1692124 AC025165.5 chr12 57803838 57804415 +1692127 AC025165.4 chr12 57814494 57814926 +1692130 CTDSP2 chr12 57819927 57846729 +1692238 AC083805.2 chr12 57837092 57842745 +1692242 AC083805.1 chr12 57869834 57896482 +1692281 AC083805.3 chr12 57894232 57896846 +1692285 ATP23 chr12 57906039 57959148 +1692330 GIHCG chr12 57930115 57936345 +1692377 LINC02403 chr12 58087892 58093362 +1692383 AC020637.1 chr12 58544124 58813060 +1692412 LINC02388 chr12 58565959 58781747 +1692445 LRIG3 chr12 58872149 58920522 +1692611 AC068305.2 chr12 58920639 59064238 +1692617 AC046129.1 chr12 59129511 59130875 +1692621 AC108721.2 chr12 59322765 59436874 +1692625 AC108721.1 chr12 59366218 59411171 +1692631 LINC02448 chr12 59523278 59524184 +1692636 SLC16A7 chr12 59596029 59789855 +1692850 AC080011.1 chr12 60092864 60096071 +1692854 AC087883.2 chr12 60150187 60269686 +1692858 AC090629.1 chr12 61668302 61702771 +1692867 TAFA2 chr12 61708259 62279150 +1693019 AC078789.1 chr12 62139999 62145643 +1693023 USP15 chr12 62260338 62417431 +1693272 MON2 chr12 62466817 62600476 +1693821 AC079035.1 chr12 62482349 62484932 +1693825 LINC01465 chr12 62601751 62603690 +1693830 AC048341.1 chr12 62602752 62622213 +1693834 AC048341.2 chr12 62603909 62604399 +1693837 PPM1H chr12 62643994 62935150 +1693884 AC078814.1 chr12 63004338 63006541 +1693889 AVPR1A chr12 63142759 63150942 +1693909 AC026116.1 chr12 63292625 63360037 +1693913 DPY19L2 chr12 63558913 63668939 +1694071 AC084357.2 chr12 63623788 63795718 +1694075 RXYLT1 chr12 63779842 63809562 +1694147 RXYLT1-AS1 chr12 63804739 63822156 +1694156 SRGAP1 chr12 63844700 64162217 +1694322 AC079866.2 chr12 63878787 63879474 +1694326 AC020611.2 chr12 64038562 64097618 +1694331 AC025576.3 chr12 64099415 64130539 +1694335 AC025576.2 chr12 64108763 64120489 +1694339 AC025576.1 chr12 64146388 64147857 +1694343 C12orf66 chr12 64186316 64222296 +1694384 C12orf56 chr12 64264762 64390758 +1694480 XPOT chr12 64404392 64451125 +1694592 AC135279.4 chr12 64451591 64452901 +1694595 TBK1 chr12 64452092 64502114 +1695217 RASSF3 chr12 64507001 64697564 +1695289 AC078962.2 chr12 64507166 64533638 +1695294 AC078962.4 chr12 64599078 64609459 +1695298 AC078962.1 chr12 64628344 64629976 +1695302 AC078962.3 chr12 64654060 64655019 +1695306 GNS chr12 64713445 64759431 +1695493 AC025262.1 chr12 64759521 64779318 +1695498 TBC1D30 chr12 64780516 64881033 +1695605 AC025262.4 chr12 64820179 64825955 +1695609 LINC02389 chr12 64883394 64990646 +1695679 LINC02231 chr12 64920845 64982524 +1695684 AC135895.1 chr12 65017468 65054124 +1695689 WIF1 chr12 65050626 65121305 +1695739 LEMD3 chr12 65169583 65248355 +1695789 AC026124.2 chr12 65171262 65171917 +1695792 MSRB3 chr12 65278643 65491430 +1696047 AC026124.1 chr12 65281657 65286728 +1696051 AC025419.1 chr12 65466820 65642372 +1696100 AC090023.1 chr12 65556925 65560889 +1696112 LINC02454 chr12 65589111 65613000 +1696127 AC090023.2 chr12 65622273 65663299 +1696141 HMGA2 chr12 65824131 65966295 +1696283 AC107308.1 chr12 65830750 65831050 +1696286 HMGA2-AS1 chr12 65851340 65882167 +1696303 AC090673.1 chr12 65934777 65948479 +1696308 LINC02425 chr12 66027725 66031066 +1696313 LLPH chr12 66116555 66130750 +1696336 LLPH-DT chr12 66130751 66134449 +1696340 TMBIM4 chr12 66135846 66170072 +1696567 IRAK3 chr12 66189195 66254622 +1696633 AC078889.1 chr12 66251745 66257434 +1696639 HELB chr12 66302545 66347645 +1696772 GRIP1 chr12 66347431 67069162 +1697192 AC073530.1 chr12 66950754 67096410 +1697224 CAND1 chr12 67269358 67319953 +1697327 AC078983.1 chr12 67329014 67350924 +1697331 LINC02420 chr12 67440998 67442559 +1697335 LINC02408 chr12 67443105 67590771 +1697350 LINC02442 chr12 67571197 67589987 +1697358 DYRK2 chr12 67648338 67665406 +1697404 AC078777.1 chr12 67658991 67670919 +1697409 LINC02421 chr12 67709047 67729475 +1697416 LINC01479 chr12 67929235 67970017 +1697425 IFNG-AS1 chr12 67989445 68234686 +1697444 IFNG chr12 68154768 68159740 +1697458 IL26 chr12 68201349 68225810 +1697474 IL22 chr12 68248242 68253604 +1697507 MDM1 chr12 68272443 68332381 +1697690 LINC02384 chr12 68332888 68451663 +1697723 AC022511.1 chr12 68344664 68349959 +1697727 AC008033.3 chr12 68426331 68427737 +1697730 RAP1B chr12 68610855 68671901 +1698201 AC090061.1 chr12 68674371 68687755 +1698213 NUP107 chr12 68686951 68745809 +1698519 SLC35E3 chr12 68746176 68793964 +1698552 MDM2 chr12 68808177 68850686 +1699140 AC025423.1 chr12 68828118 68828553 +1699144 AC025423.4 chr12 68841288 68843237 +1699148 CPM chr12 68842197 68971570 +1699314 AC127894.1 chr12 69212108 69224242 +1699325 CPSF6 chr12 69239569 69274358 +1699468 AC020656.2 chr12 69326574 69331882 +1699471 LYZ chr12 69348341 69354234 +1699505 AC020656.1 chr12 69353493 69354225 +1699509 YEATS4 chr12 69359710 69390870 +1699581 LINC02373 chr12 69449470 69460724 +1699586 FRS2 chr12 69470349 69579789 +1699778 CCT2 chr12 69585426 69601570 +1699973 LRRC10 chr12 69608564 69610907 +1699981 BEST3 chr12 69643360 69699476 +1700166 AC025263.1 chr12 69713633 69738574 +1700180 RAB3IP chr12 69738681 69823204 +1700502 MYRFL chr12 69825227 69959097 +1700685 AC025159.1 chr12 69901918 70243379 +1700712 AC078922.1 chr12 69946543 69947081 +1700716 LINC02821 chr12 70180338 70202004 +1700721 LINC01481 chr12 70219132 70221862 +1700725 AC092881.2 chr12 70239114 70242430 +1700729 CNOT2 chr12 70242994 70354993 +1701340 KCNMB4 chr12 70366290 70434292 +1701361 AC025569.1 chr12 70468080 70543040 +1701426 PTPRB chr12 70515866 70637440 +1701883 AC083809.1 chr12 70570969 70571440 +1701886 PTPRR chr12 70638073 70920738 +1702101 AC123905.1 chr12 71007773 71032083 +1702107 AC025575.1 chr12 71034122 71104526 +1702114 AC025575.2 chr12 71047402 71118247 +1702119 TSPAN8 chr12 71125085 71441898 +1702214 LGR5 chr12 71439798 71586310 +1702364 AC090116.1 chr12 71448405 71448850 +1702367 AC078860.2 chr12 71582293 71594404 +1702376 ZFC3H1 chr12 71609472 71667725 +1702575 THAP2 chr12 71664301 71680644 +1702614 TMEM19 chr12 71686082 71705047 +1702695 AC011601.1 chr12 71709171 71710374 +1702699 RAB21 chr12 71754863 71800286 +1702731 AC089984.1 chr12 71793855 71799627 +1702735 TBC1D15 chr12 71839707 71927248 +1703039 TPH2 chr12 71938845 72186618 +1703099 AC090109.1 chr12 72046149 72057377 +1703106 TRHDE chr12 72087266 72670758 +1703193 TRHDE-AS1 chr12 72249964 72276954 +1703310 AC133480.1 chr12 72727923 72728844 +1703314 AC090503.2 chr12 73115957 73143858 +1703331 LINC02444 chr12 73159190 73208317 +1703337 AC090503.1 chr12 73203815 73206835 +1703341 LINC02445 chr12 73758657 73846188 +1703353 AC090015.1 chr12 73820315 74402600 +1703507 AC136188.1 chr12 73906940 73919337 +1703512 LINC02394 chr12 74039024 74049981 +1703522 AC090502.2 chr12 74248637 74283669 +1703528 ATXN7L3B chr12 74537835 74545430 +1703536 AC025257.1 chr12 74538145 74538633 +1703540 AC073525.1 chr12 75020969 75044793 +1703552 KCNC2 chr12 75040077 75209868 +1703683 AC091534.1 chr12 75234740 75298508 +1703696 CAPS2 chr12 75275979 75390928 +1703962 AC121761.2 chr12 75333798 75334486 +1703965 GLIPR1L1 chr12 75334670 75370560 +1704016 GLIPR1L2 chr12 75391089 75432688 +1704076 GLIPR1 chr12 75480753 75503863 +1704132 AC121761.1 chr12 75483454 75489820 +1704136 KRR1 chr12 75490863 75511636 +1704198 AC078923.1 chr12 75563202 75984015 +1704209 AC078820.2 chr12 75649195 75691937 +1704217 AC078820.1 chr12 75694010 75698816 +1704223 AC011611.2 chr12 75964440 75967062 +1704228 PHLDA1 chr12 76025447 76033932 +1704256 AC011611.3 chr12 76030494 76031378 +1704260 AC011611.4 chr12 76032658 76033897 +1704264 NAP1L1 chr12 76036585 76084958 +1704858 LNCOG chr12 76259836 76305969 +1704870 BBS10 chr12 76344474 76348415 +1704880 OSBPL8 chr12 76351797 76559809 +1705292 AC107032.2 chr12 76562294 76615567 +1705297 AC107032.3 chr12 76589476 76600644 +1705302 ZDHHC17 chr12 76763588 76853696 +1705519 CSRP2 chr12 76858709 76879023 +1705598 AC124784.1 chr12 76878193 76880352 +1705602 E2F7 chr12 77021248 77065569 +1705724 AC079030.1 chr12 77129178 77163638 +1705728 LINC02464 chr12 77219603 77317234 +1705735 NAV3 chr12 77324641 78213010 +1706145 AC073591.1 chr12 77379770 77390869 +1706150 AC138331.1 chr12 77775783 77783576 +1706154 AC073571.1 chr12 78052181 78091737 +1706160 LINC02424 chr12 78326680 78359746 +1706164 AC128707.1 chr12 78352519 78483030 +1706201 AC130415.1 chr12 78426826 78442952 +1706206 AC079362.1 chr12 78448995 78540675 +1706214 AC068993.2 chr12 78794132 78808995 +1706231 SYT1 chr12 78863993 79452008 +1706433 AC090709.1 chr12 78960258 79045644 +1706439 AC027288.3 chr12 79341205 79503396 +1706449 AC027288.1 chr12 79540203 79550535 +1706462 PAWR chr12 79574979 79690964 +1706541 AC073569.2 chr12 79690144 79778451 +1706545 PPP1R12A chr12 79773563 79935460 +1707058 AC073569.3 chr12 79818784 79819465 +1707061 AC073569.1 chr12 79823778 79825496 +1707065 PPP1R12A-AS1 chr12 79934901 79942712 +1707070 OTOGL chr12 80099537 80380879 +1707585 PTPRQ chr12 80402178 80680273 +1707886 AC074031.1 chr12 80583683 80593701 +1707891 MYF6 chr12 80707634 80709474 +1707903 MYF5 chr12 80716912 80719671 +1707915 LINC01490 chr12 80763151 80770717 +1707975 LIN7A chr12 80792520 80937925 +1708034 ACSS3 chr12 80936414 81261210 +1708160 AC078955.1 chr12 81094371 81125863 +1708172 PPFIA2 chr12 81257975 81759553 +1709053 PPFIA2-AS1 chr12 81270669 81312422 +1709123 AC069228.1 chr12 81378042 81556637 +1709165 LINC02426 chr12 81953719 81993136 +1709174 CCDC59 chr12 82223681 82358805 +1709216 METTL25 chr12 82358528 82479239 +1709319 AC089998.4 chr12 82481118 82497560 +1709324 AC089998.2 chr12 82505211 82506188 +1709328 AC089998.1 chr12 82512677 82515817 +1709331 AC091214.1 chr12 82673070 82686632 +1709337 TMTC2 chr12 82686880 83134870 +1709450 AC090680.1 chr12 83171590 83172740 +1709454 AC093025.1 chr12 83661009 83661719 +1709458 AC090679.3 chr12 84147304 84154338 +1709462 AC090679.2 chr12 84154434 84294562 +1709479 SLC6A15 chr12 84859491 84913615 +1709611 TSPAN19 chr12 85014311 85036277 +1709712 LRRIQ1 chr12 85036314 85264457 +1709845 ALX1 chr12 85280220 85301784 +1709859 LINC02820 chr12 85318060 85342912 +1709864 RASSF9 chr12 85800703 85836409 +1709874 NTS chr12 85874295 85882992 +1709902 MGAT4C chr12 85955666 86838904 +1710046 AC016993.1 chr12 85958686 85960946 +1710050 AC010196.1 chr12 86599578 86838998 +1710055 LINC02258 chr12 87795733 87802028 +1710059 AC079598.1 chr12 87816486 87817831 +1710064 C12orf50 chr12 87980035 88034037 +1710151 C12orf29 chr12 88033846 88050160 +1710266 CEP290 chr12 88049014 88142088 +1710900 TMTC3 chr12 88142296 88199887 +1710987 KITLG chr12 88492793 88580851 +1711099 AC024941.2 chr12 88580531 88600725 +1711108 AC024941.1 chr12 88601862 88602195 +1711111 LINC02458 chr12 89010681 89309566 +1711124 DUSP6 chr12 89347235 89352501 +1711165 AC024909.1 chr12 89351015 89353271 +1711168 AC010201.3 chr12 89353798 89418559 +1711173 AC010201.2 chr12 89367807 89369301 +1711176 AC010201.1 chr12 89371820 89372359 +1711179 POC1B chr12 89419718 89526047 +1711384 GALNT4 chr12 89519412 89524796 +1711392 POC1B-AS1 chr12 89524594 89548005 +1711401 AC025034.1 chr12 89561129 89594878 +1711405 ATP2B1 chr12 89588049 89709300 +1711625 ATP2B1-AS1 chr12 89708959 89712590 +1711628 AC009522.1 chr12 89712048 90100763 +1711650 LINC02399 chr12 89947693 89949726 +1711655 AC126178.1 chr12 90107739 90112779 +1711659 LINC02392 chr12 90280894 90300974 +1711686 LINC02822 chr12 90576402 90889917 +1711744 AC084365.1 chr12 90617759 90622822 +1711748 AC112481.2 chr12 90617759 90808748 +1711758 AC112481.1 chr12 90809207 90810689 +1711769 CCER1 chr12 90905622 90955176 +1711789 LINC00615 chr12 90918023 90948669 +1711796 EPYC chr12 90963682 91005026 +1711833 KERA chr12 91050491 91057983 +1711845 LUM chr12 91102629 91111494 +1711865 DCN chr12 91140484 91182824 +1712108 LINC02823 chr12 91327045 91368607 +1712143 AC090016.1 chr12 91423781 91426936 +1712147 AC126175.2 chr12 91634887 91635644 +1712150 AC025254.1 chr12 91680131 91680873 +1712154 LINC02404 chr12 91876924 91880659 +1712162 AC090049.1 chr12 91901458 91906187 +1712167 LINC01619 chr12 91984976 92142914 +1712232 AC123512.1 chr12 92008052 92022595 +1712244 AC025164.2 chr12 92026447 92032392 +1712248 BTG1 chr12 92140278 92145846 +1712265 AC025164.1 chr12 92145573 92226557 +1712286 LINC02391 chr12 92247697 92363832 +1712293 CLLU1OS chr12 92420094 92428148 +1712311 CLLU1 chr12 92421531 92431002 +1712326 LINC02397 chr12 92466451 92492091 +1712330 C12orf74 chr12 92702843 92772455 +1712469 EEA1 chr12 92770637 92929331 +1712604 LINC02413 chr12 92999218 93019820 +1712613 AC138123.1 chr12 93003415 93215679 +1712638 AC138123.2 chr12 93090480 93108629 +1712661 LINC02412 chr12 93173470 93182299 +1712684 AC124947.1 chr12 93316722 93377753 +1712697 NUDT4 chr12 93377883 93408146 +1712803 UBE2N chr12 93405673 93441947 +1712868 MRPL42 chr12 93467488 93516214 +1713014 SOCS2-AS1 chr12 93542022 93571768 +1713046 SOCS2 chr12 93569814 93583487 +1713159 CRADD chr12 93677375 93894840 +1713249 AC012085.2 chr12 93707791 93737823 +1713257 AC012464.2 chr12 93836167 93838038 +1713261 AC012464.1 chr12 93894965 93943603 +1713266 AC012464.3 chr12 93945041 93947813 +1713269 PLXNC1 chr12 94148577 94307675 +1713481 AC123567.2 chr12 94167528 94187724 +1713494 AC073655.3 chr12 94260548 94262299 +1713498 AC073655.1 chr12 94272150 94277195 +1713502 AC073655.2 chr12 94277758 94282844 +1713510 CEP83 chr12 94306449 94459988 +1713739 CEP83-DT chr12 94460003 94462484 +1713742 AC023161.1 chr12 94491546 94496442 +1713746 TMCC3 chr12 94567122 94650557 +1713784 NDUFA12 chr12 94897055 95003748 +1713872 NR2C1 chr12 95020229 95073628 +1714090 FGD6 chr12 95076749 95217482 +1714299 VEZT chr12 95217746 95302799 +1714876 AC084879.2 chr12 95387890 95388558 +1714880 METAP2 chr12 95473520 95515839 +1715082 USP44 chr12 95516560 95551476 +1715167 NTN4 chr12 95657807 95791152 +1715283 AC090001.1 chr12 95791733 95858839 +1715298 LINC02410 chr12 95803097 95823307 +1715302 SNRPF chr12 95858928 95903828 +1715348 CCDC38 chr12 95867048 95942635 +1715447 AMDHD1 chr12 95943331 95968720 +1715504 HAL chr12 95972662 95996365 +1715796 AC007298.2 chr12 95996521 96011489 +1715802 LTA4H chr12 96000753 96043520 +1716020 AC007298.1 chr12 96025323 96027971 +1716024 LINC02452 chr12 96160692 96172126 +1716029 ELK3 chr12 96194375 96269824 +1716095 AC008149.1 chr12 96222797 96223973 +1716099 AC008149.2 chr12 96229563 96235650 +1716111 CDK17 chr12 96278261 96400480 +1716294 AC007513.1 chr12 96422326 96485442 +1716300 CFAP54 chr12 96489571 96875555 +1716645 NEDD1 chr12 96907223 96953777 +1716912 AC007656.2 chr12 96985656 97185609 +1716916 AC007656.1 chr12 97024021 97127626 +1716931 AC007656.4 chr12 97155234 97160538 +1716935 LINC02409 chr12 97272692 97276209 +1716940 RMST chr12 97430884 97598415 +1717269 AC016152.1 chr12 98113014 98292445 +1717276 AC008055.2 chr12 98420448 98423721 +1717280 LINC02453 chr12 98485544 98503855 +1717289 TMPO-AS1 chr12 98512973 98516422 +1717297 TMPO chr12 98515512 98550379 +1717429 SLC25A3 chr12 98593591 98606379 +1717651 IKBIP chr12 98613405 98645113 +1717683 APAF1 chr12 98645141 98735433 +1718091 ANKS1B chr12 98726457 99984654 +1718678 AC069437.1 chr12 98931682 98976656 +1718684 AC117377.1 chr12 99093359 99105011 +1718691 FAM71C chr12 99647753 99650114 +1718701 AC078916.1 chr12 99985045 99985619 +1718704 UHRF1BP1L chr12 100028455 100142874 +1718897 AC010203.2 chr12 100143058 100144671 +1718901 ACTR6 chr12 100199122 100241865 +1719133 DEPDC4 chr12 100203669 100267079 +1719266 SCYL2 chr12 100267140 100341715 +1719447 SLC17A8 chr12 100357074 100422055 +1719512 NR1H4 chr12 100473708 100564414 +1719744 GAS2L3 chr12 100573683 100628288 +1719870 ANO4 chr12 100717526 101128641 +1720124 AC138360.1 chr12 100852331 100859262 +1720128 AC063947.1 chr12 101038420 101039094 +1720132 SLC5A8 chr12 101155493 101210238 +1720168 UTP20 chr12 101280105 101386618 +1720313 ARL1 chr12 101393116 101407772 +1720445 AC063948.1 chr12 101408372 101409060 +1720449 SPIC chr12 101475336 101486997 +1720467 MYBPC1 chr12 101568353 101686028 +1721375 AC117505.1 chr12 101646720 101659970 +1721382 AC010205.1 chr12 101696002 101696450 +1721385 CHPT1 chr12 101696947 101744140 +1721535 SYCP3 chr12 101728648 101739472 +1721615 GNPTAB chr12 101745499 101830959 +1721759 DRAM1 chr12 101877580 102012130 +1721836 AC084398.2 chr12 101923410 101924719 +1721841 AC079907.2 chr12 101954992 101962414 +1721852 WASHC3 chr12 102012840 102062149 +1722031 AC079907.1 chr12 102063355 102074820 +1722036 NUP37 chr12 102073103 102120120 +1722151 PARPBP chr12 102120185 102197520 +1722340 PMCH chr12 102196459 102197833 +1722352 HELLPAR chr12 102197585 102402596 +1722355 LINC02456 chr12 102304355 102463491 +1722363 IGF1 chr12 102395874 102481744 +1722453 LINC00485 chr12 102809280 102824399 +1722460 PAH chr12 102836889 102958410 +1722639 AC026108.1 chr12 102953289 102953835 +1722642 ASCL1 chr12 102957674 102960513 +1722652 AC026108.2 chr12 103013362 103016095 +1722656 AC068643.1 chr12 103079634 103178675 +1722675 AC068643.2 chr12 103151834 103179247 +1722726 C12orf42 chr12 103237591 103496010 +1722905 AC084364.3 chr12 103518334 103571337 +1722911 LINC02401 chr12 103547751 103578947 +1723008 STAB2 chr12 103587273 103766719 +1723180 AC025265.2 chr12 103654780 103657995 +1723184 AC025265.3 chr12 103668575 103669406 +1723188 AC025265.1 chr12 103746315 103768858 +1723196 NT5DC3 chr12 103770453 103841234 +1723269 AC012555.2 chr12 103819610 103822085 +1723274 AC012555.1 chr12 103841451 103844664 +1723278 HSP90B1 chr12 103930107 103953645 +1723437 C12orf73 chr12 103940763 103965708 +1723561 TDG chr12 103965822 103988874 +1723703 GLT8D2 chr12 103988984 104064183 +1723820 HCFC2 chr12 104064531 104106524 +1723917 NFYB chr12 104117086 104138241 +1723992 LINC02385 chr12 104170395 104177659 +1723997 AC089983.2 chr12 104171600 104177799 +1724001 TXNRD1 chr12 104215779 104350307 +1724568 AC089983.1 chr12 104262314 104280722 +1724572 EID3 chr12 104303739 104305205 +1724580 CHST11 chr12 104455295 104762014 +1724633 SLC41A2 chr12 104802553 104958744 +1724724 AC089985.1 chr12 104858838 104871765 +1724728 C12orf45 chr12 104986316 105074197 +1724816 ALDH1L2 chr12 105019784 105107643 +1725004 WASHC4 chr12 105107324 105169134 +1725332 APPL2 chr12 105173297 105236203 +1725642 C12orf75 chr12 105235290 105396097 +1725732 AC078874.1 chr12 105236338 105243173 +1725737 AC011313.1 chr12 105304867 105327017 +1725742 AC079851.1 chr12 105699168 105703520 +1725746 CASC18 chr12 105704203 105744062 +1725761 AC011595.2 chr12 106050961 106058254 +1725767 NUAK1 chr12 106063340 106140033 +1725818 AC011595.1 chr12 106103163 106106165 +1725823 CKAP4 chr12 106237881 106304279 +1725848 AC079174.1 chr12 106245613 106246956 +1725852 AC079174.2 chr12 106250759 106252786 +1725855 TCP11L2 chr12 106301929 106347003 +1725987 POLR3B chr12 106357748 106510198 +1726127 AC079385.1 chr12 106495958 106774926 +1726142 RFX4 chr12 106582907 106762803 +1726393 AC079385.2 chr12 106678583 106684707 +1726406 AC079385.3 chr12 106714924 106733066 +1726410 RIC8B chr12 106774621 106889316 +1726640 AC007695.1 chr12 106867177 106871505 +1726644 AC007541.1 chr12 106954029 106955497 +1726647 TMEM263 chr12 106955719 106978778 +1726745 MTERF2 chr12 106977277 106987160 +1726805 CRY1 chr12 106991364 107093549 +1726869 AC078929.1 chr12 107093298 107123314 +1726875 AC007649.1 chr12 107219764 107223576 +1726879 BTBD11 chr12 107318421 107659642 +1727064 AC007540.1 chr12 107610034 107617721 +1727068 PWP1 chr12 107685799 107713162 +1727176 PRDM4 chr12 107732871 107761272 +1727264 AC007622.2 chr12 107736555 107759968 +1727276 ASCL4 chr12 107774385 107776644 +1727284 AC126177.3 chr12 107809483 107864562 +1727325 WSCD2 chr12 108129288 108250537 +1727443 CMKLR1 chr12 108288044 108339317 +1727508 LINC01498 chr12 108434130 108515023 +1727538 FICD chr12 108515277 108525837 +1727580 SART3 chr12 108522214 108561400 +1727901 AC008119.1 chr12 108532074 108539738 +1727905 ISCU chr12 108562582 108569384 +1728044 TMEM119 chr12 108589851 108598320 +1728081 SELPLG chr12 108622277 108633959 +1728109 AC007569.1 chr12 108628668 108642349 +1728122 CORO1C chr12 108645109 108731596 +1728395 SSH1 chr12 108778191 108857590 +1728559 AC087893.2 chr12 108833721 108834384 +1728562 DAO chr12 108858932 108901043 +1728704 SVOP chr12 108907741 109021068 +1728779 USP30 chr12 109023089 109088023 +1728936 USP30-AS1 chr12 109052350 109053952 +1728940 ALKBH2 chr12 109088188 109093631 +1729013 UNG chr12 109097574 109110992 +1729087 AC007637.1 chr12 109111218 109125594 +1729092 ACACB chr12 109116595 109268226 +1729528 FOXN4 chr12 109277978 109309284 +1729598 MYO1H chr12 109347903 109455523 +1729770 LINC01486 chr12 109354083 109359488 +1729775 AC007570.1 chr12 109445410 109447497 +1729779 KCTD10 chr12 109448655 109477359 +1729968 UBE3B chr12 109477402 109536705 +1730333 MMAB chr12 109553715 109573580 +1730500 MVK chr12 109573255 109598125 +1730791 FAM222A chr12 109714228 109770507 +1730817 FAM222A-AS1 chr12 109734166 109773508 +1730830 TRPV4 chr12 109783085 109833401 +1731073 GLTP chr12 109850945 109880541 +1731165 AC007834.1 chr12 109880676 109888467 +1731169 TCHP chr12 109900264 109983841 +1731301 GIT2 chr12 109929802 109996389 +1731731 AC084876.1 chr12 109948389 109949029 +1731734 ANKRD13A chr12 109999186 110039763 +1731869 C12orf76 chr12 110027028 110073634 +1731929 AC007546.1 chr12 110032245 110032803 +1731932 IFT81 chr12 110124335 110218793 +1732144 ATP2A2 chr12 110280756 110351093 +1732362 ANAPC7 chr12 110372900 110403730 +1732473 ARPC3 chr12 110434823 110450422 +1732541 GPN3 chr12 110452486 110469268 +1732657 FAM216A chr12 110468415 110490385 +1732710 VPS29 chr12 110491083 110502111 +1732834 RAD9B chr12 110501655 110532086 +1733016 PPTC7 chr12 110533245 110583318 +1733039 TCTN1 chr12 110614027 110649430 +1733543 HVCN1 chr12 110627841 110704950 +1733686 PPP1CC chr12 110719680 110742939 +1733819 AC002375.1 chr12 110831779 110845963 +1733823 CCDC63 chr12 110846769 110907535 +1733910 MYL2 chr12 110910819 110921443 +1733978 LINC01405 chr12 110934590 110959093 +1734015 AC002351.1 chr12 110951683 110957820 +1734036 CUX2 chr12 111034165 111350554 +1734110 PHETA1 chr12 111360651 111369121 +1734158 LINC02356 chr12 111369261 111403310 +1734166 SH2B3 chr12 111405948 111451623 +1734212 ATXN2 chr12 111443485 111599676 +1735438 ATXN2-AS chr12 111599498 111600256 +1735442 BRAP chr12 111642146 111685956 +1735510 ACAD10 chr12 111686056 111757107 +1735799 ALDH2 chr12 111766887 111817532 +1735907 MAPKAPK5-AS1 chr12 111839764 111842902 +1735947 MAPKAPK5 chr12 111842228 111902222 +1736087 TMEM116 chr12 111931282 112013185 +1736370 ERP29 chr12 112013348 112023449 +1736410 AC073575.2 chr12 112018804 112019430 +1736413 NAA25 chr12 112026689 112108796 +1736616 AC073575.1 chr12 112063909 112065755 +1736620 TRAFD1 chr12 112125538 112153604 +1736776 HECTD4 chr12 112160188 112382439 +1737248 AC004217.1 chr12 112256800 112259091 +1737252 RPL6 chr12 112405190 112418838 +1737372 PTPN11 chr12 112418351 112509913 +1737511 RPH3A chr12 112570380 112898881 +1738048 OAS1 chr12 112906783 112933222 +1738170 AC004551.1 chr12 112907628 113017751 +1738175 OAS3 chr12 112938444 112973251 +1738252 OAS2 chr12 112978395 113011723 +1738375 DTX1 chr12 113056709 113098028 +1738418 RASAL1 chr12 113098819 113136239 +1738695 CFAP73 chr12 113149858 113159276 +1738729 DDX54 chr12 113157174 113185479 +1738890 RITA1 chr12 113185526 113192368 +1738933 AC089999.1 chr12 113185624 113192161 +1738937 IQCD chr12 113195441 113221094 +1738975 TPCN1 chr12 113221050 113298585 +1739455 AC089999.2 chr12 113249466 113250042 +1739458 SLC8B1 chr12 113298759 113359493 +1739736 PLBD2 chr12 113358566 113391629 +1739807 SDS chr12 113392445 113426301 +1739867 SDSL chr12 113422380 113438276 +1739953 LHX5 chr12 113462033 113472280 +1739972 LHX5-AS1 chr12 113472003 113480624 +1739976 LINC01234 chr12 113583886 113773726 +1740046 RBM19 chr12 113816738 113966325 +1740236 AC009731.1 chr12 113863402 113871597 +1740240 AC073863.1 chr12 113932569 113937255 +1740244 AC010183.1 chr12 114077133 114079902 +1740248 AC010183.2 chr12 114080381 114113489 +1740257 LINC02459 chr12 114238970 114241770 +1740261 TBX5 chr12 114353931 114408442 +1740353 TBX5-AS1 chr12 114408173 114412831 +1740372 AC010177.1 chr12 114621761 114622922 +1740376 TBX3 chr12 114670255 114684175 +1740423 AC026765.3 chr12 114682292 114767989 +1740453 AC026765.4 chr12 114733757 114735244 +1740457 AC026765.2 chr12 114768674 114771851 +1740461 AC009804.2 chr12 114894632 114898529 +1740465 AC008125.1 chr12 115077325 115080153 +1740469 AC078880.1 chr12 115263170 115270596 +1740473 AC078880.3 chr12 115299588 115300708 +1740476 AC078880.4 chr12 115318657 115320405 +1740479 AC078880.5 chr12 115332146 115332566 +1740482 AC078880.2 chr12 115363012 115364745 +1740486 AC009803.2 chr12 115569394 115581739 +1740502 AC009803.1 chr12 115582061 115639734 +1740513 AC009387.1 chr12 115755262 115799936 +1740518 LINC02463 chr12 115810359 115886137 +1740523 AC012157.3 chr12 115878748 115885967 +1740527 MED13L chr12 115953872 116277719 +1741003 AC012157.2 chr12 115961187 115962733 +1741007 AC130895.1 chr12 116174502 116181295 +1741011 AC079384.2 chr12 116357578 116359096 +1741015 AC079384.1 chr12 116368764 116389471 +1741022 LINC02457 chr12 116482073 116521047 +1741030 LINC00173 chr12 116533422 116536518 +1741047 MAP1LC3B2 chr12 116548105 116576606 +1741071 AC125603.4 chr12 116580974 116583672 +1741074 AC125603.3 chr12 116599270 116603585 +1741078 AC125603.2 chr12 116661582 116698065 +1741082 AC125603.1 chr12 116698336 116703130 +1741086 C12orf49 chr12 116710171 116738070 +1741131 RNFT2 chr12 116738178 116853631 +1741292 AC083806.3 chr12 116801023 116801477 +1741295 HRK chr12 116856144 116881441 +1741325 FBXW8 chr12 116910950 117031148 +1741410 AC083806.2 chr12 116948738 116951422 +1741413 AC127164.1 chr12 116977442 116987337 +1741419 AC026368.1 chr12 117002463 117003152 +1741422 TESC chr12 117038923 117099479 +1741526 TESC-AS1 chr12 117099481 117142091 +1741531 FBXO21 chr12 117141988 117190531 +1741674 NOS1 chr12 117208142 117452170 +1741939 AC073864.1 chr12 117453012 117456986 +1741943 KSR2 chr12 117453012 117968990 +1742051 AC084291.1 chr12 117889454 117891008 +1742055 RFC5 chr12 118013588 118033130 +1742201 AC131159.2 chr12 118024817 118025518 +1742204 WSB2 chr12 118032694 118062430 +1742366 AC131159.1 chr12 118037869 118038081 +1742369 VSIG10 chr12 118063593 118136026 +1742443 AC131238.1 chr12 118066398 118066725 +1742446 PEBP1 chr12 118136124 118145584 +1742464 TAOK3 chr12 118149801 118372907 +1742742 AC026367.1 chr12 118375350 118376275 +1742746 SUDS3 chr12 118376555 118418033 +1742790 AC026367.3 chr12 118428281 118428870 +1742793 AC026367.2 chr12 118430147 118430699 +1742796 LINC02460 chr12 118645315 118648724 +1742801 LINC02423 chr12 118758217 118761739 +1742812 LINC02440 chr12 118773031 118775137 +1742822 LINC02439 chr12 118782926 118833536 +1742832 AC087863.2 chr12 118849354 118908930 +1742839 SRRM4 chr12 118981541 119163051 +1742909 AC087885.1 chr12 118988010 118989594 +1742913 AC084361.1 chr12 119031039 119116961 +1742919 AC084880.4 chr12 119174065 119176484 +1742923 HSPB8 chr12 119178642 119221131 +1742949 AC084880.3 chr12 119182048 119183259 +1742953 AC084880.2 chr12 119225834 119259017 +1742960 LINC00934 chr12 119283825 119303380 +1742968 CCDC60 chr12 119334712 119541040 +1743033 AC002070.1 chr12 119361247 119668079 +1743051 TMEM233 chr12 119593774 119643075 +1743068 PRKAB1 chr12 119667864 119681624 +1743174 CIT chr12 119685791 119877320 +1743628 AC002563.1 chr12 119699768 119701011 +1743632 BICDL1 chr12 119989869 120094494 +1743726 RAB35 chr12 120095099 120117502 +1743803 AC004812.2 chr12 120116907 120119000 +1743806 GCN1 chr12 120127202 120194715 +1743962 RPLP0 chr12 120196699 120201235 +1744287 PXN-AS1 chr12 120201291 120213231 +1744328 PXN chr12 120210439 120265771 +1744678 AC004263.2 chr12 120218070 120222668 +1744683 AC004263.1 chr12 120224744 120225421 +1744686 SIRT4 chr12 120302316 120313249 +1744711 PLA2G1B chr12 120322115 120327779 +1744747 MSI1 chr12 120341330 120369164 +1744808 AC003982.1 chr12 120389502 120395995 +1744818 COX6A1 chr12 120438090 120440737 +1744835 TRIAP1 chr12 120443964 120446384 +1744848 GATC chr12 120446444 120463749 +1744886 SRSF9 chr12 120461672 120469748 +1744930 DYNLL1 chr12 120469850 120498493 +1745041 NRAV chr12 120488079 120495946 +1745051 AC063943.1 chr12 120500735 120501090 +1745054 COQ5 chr12 120503279 120534434 +1745145 RNF10 chr12 120533480 120577588 +1745422 POP5 chr12 120578764 120581402 +1745478 AC125616.1 chr12 120628830 120641591 +1745488 CABP1 chr12 120640552 120667324 +1745562 MLEC chr12 120687149 120701859 +1745612 AC069234.2 chr12 120697124 120699541 +1745619 AC069234.5 chr12 120703867 120704282 +1745622 AC069234.4 chr12 120709112 120709523 +1745625 UNC119B chr12 120710458 120723640 +1745648 AC069234.3 chr12 120721507 120723639 +1745652 ACADS chr12 120725774 120740008 +1745707 AC069234.1 chr12 120740470 120761592 +1745712 SPPL3 chr12 120762510 120904358 +1745833 AC069214.1 chr12 120904702 120907937 +1745837 HNF1A-AS1 chr12 120941728 120980965 +1745864 HNF1A chr12 120978543 121002512 +1746123 C12orf43 chr12 121000486 121016502 +1746245 OASL chr12 121019111 121039242 +1746300 P2RX7 chr12 121132819 121188032 +1746622 AC069209.2 chr12 121177919 121191477 +1746627 AC069209.1 chr12 121190868 121191518 +1746630 P2RX4 chr12 121209857 121234106 +1746877 CAMKK2 chr12 121237675 121298308 +1747355 ANAPC5 chr12 121308245 121399896 +1747656 AC048337.1 chr12 121391962 121399859 +1747660 RNF34 chr12 121400041 121430623 +1747781 KDM2B chr12 121429096 121581023 +1748195 KDM2B-DT chr12 121580792 121593504 +1748199 ORAI1 chr12 121626550 121642677 +1748217 MORN3 chr12 121648742 121672631 +1748267 AC084018.4 chr12 121687187 121689380 +1748271 TMEM120B chr12 121712752 121783001 +1748386 RHOF chr12 121777754 121803403 +1748472 LINC01089 chr12 121795267 121803906 +1748534 AC084018.1 chr12 121797511 121801972 +1748538 AC084018.2 chr12 121800797 121803403 +1748541 SETD1B chr12 121804180 121832584 +1748696 HPD chr12 121839527 121863596 +1748777 AC079360.1 chr12 121856259 121857059 +1748782 AC069503.3 chr12 121874193 121874337 +1748785 AC069503.4 chr12 121887540 121888643 +1748788 PSMD9 chr12 121888732 121918297 +1748923 WDR66 chr12 121918592 122003927 +1749046 AC069503.1 chr12 122007434 122020063 +1749052 BCL7A chr12 122019422 122062044 +1749092 AC156455.1 chr12 122063306 122068616 +1749116 MLXIP chr12 122078756 122147344 +1749248 LRRC43 chr12 122167738 122203471 +1749312 IL31 chr12 122172029 122174221 +1749324 B3GNT4 chr12 122203681 122208952 +1749370 AC048338.2 chr12 122207662 122227534 +1749425 DIABLO chr12 122207668 122227456 +1749632 VPS33A chr12 122229564 122266494 +1749807 CLIP1 chr12 122271432 122422632 +1750334 CLIP1-AS1 chr12 122395542 122400857 +1750342 ZCCHC8 chr12 122471599 122501073 +1750541 AC127002.2 chr12 122501187 122501641 +1750544 RSRC2 chr12 122503454 122527000 +1750775 KNTC1 chr12 122527246 122626396 +1751123 AC026333.4 chr12 122634130 122634673 +1751126 AC026333.3 chr12 122687125 122715979 +1751134 HCAR2 chr12 122701293 122703357 +1751142 HCAR3 chr12 122714756 122716811 +1751150 HCAR1 chr12 122726076 122730844 +1751158 DENR chr12 122752824 122771064 +1751209 CCDC62 chr12 122774526 122827528 +1751354 HIP1R chr12 122834453 122862961 +1751516 VPS37B chr12 122865330 122896127 +1751555 AC027290.1 chr12 122865335 122867021 +1751559 ABCB9 chr12 122920951 122981649 +1751940 OGFOD2 chr12 122974580 122980043 +1752234 ARL6IP4 chr12 122980060 122982913 +1752469 PITPNM2 chr12 122983480 123150015 +1752696 PITPNM2-AS1 chr12 123081384 123084744 +1752704 MPHOSPH9 chr12 123152320 123244014 +1753087 C12orf65 chr12 123233436 123257960 +1753152 CDK2AP1 chr12 123250112 123272334 +1753275 AC068768.1 chr12 123262060 123262402 +1753278 SBNO1 chr12 123289109 123364847 +1753481 SBNO1-AS1 chr12 123363868 123366113 +1753487 KMT5A chr12 123383773 123409353 +1753592 RILPL2 chr12 123410683 123436717 +1753606 SNRNP35 chr12 123458088 123473154 +1753643 RILPL1 chr12 123470054 123533719 +1753698 AC145423.2 chr12 123515275 123515513 +1753701 AC145423.3 chr12 123519390 123519856 +1753704 TMED2-DT chr12 123575891 123585115 +1753709 TMED2 chr12 123584533 123598582 +1753753 DDX55 chr12 123602077 123620943 +1753941 EIF2B1 chr12 123620406 123633766 +1754024 GTF2H3 chr12 123633739 123662604 +1754295 TCTN2 chr12 123671113 123708399 +1754398 AC117503.1 chr12 123707602 123708386 +1754402 ATP6V0A2 chr12 123712353 123761755 +1754546 AC117503.5 chr12 123713408 123723169 +1754551 DNAH10 chr12 123762188 123936206 +1755035 CCDC92 chr12 123918660 123972831 +1755138 DNAH10OS chr12 123925461 123934984 +1755142 AC068790.7 chr12 123960717 123961244 +1755145 AC068790.4 chr12 123962555 123962817 +1755148 AC068790.3 chr12 123966077 123966629 +1755151 AC068790.2 chr12 123968023 123968579 +1755154 AC068790.5 chr12 123969990 123970344 +1755157 AC068790.6 chr12 123971457 123971714 +1755160 ZNF664 chr12 123971845 124015439 +1755269 RFLNA chr12 123973241 124316024 +1755321 AC068790.9 chr12 124085761 124088598 +1755324 AC026358.1 chr12 124206228 124209018 +1755328 NCOR2 chr12 124324415 124567589 +1756002 AC073592.1 chr12 124513222 124516798 +1756010 SCARB1 chr12 124776856 124882668 +1756204 AC073593.2 chr12 124786783 124808790 +1756209 UBC chr12 124911604 124917368 +1756316 DHX37 chr12 124946825 124989131 +1756440 BRI3BP chr12 124993645 125031231 +1756474 THRIL chr12 125025434 125027410 +1756477 AACS chr12 125065434 125143333 +1756609 AC122688.2 chr12 125150058 125151394 +1756613 AC122688.5 chr12 125159331 125160397 +1756617 TMEM132B chr12 125186836 125662377 +1756674 AC005252.4 chr12 125858132 125880724 +1756679 LINC00939 chr12 125958688 125983665 +1756712 LINC02826 chr12 125983702 126043485 +1756793 LINC02359 chr12 126094112 126177632 +1756877 AC005888.1 chr12 126165730 126191406 +1756882 AC007368.1 chr12 126191151 126434227 +1756934 LINC02825 chr12 126400792 126405528 +1756938 LINC02347 chr12 126438837 126472790 +1757135 AC006065.4 chr12 126610034 126690318 +1757149 AC006065.3 chr12 126628172 126690322 +1757154 LINC02824 chr12 126688341 126720333 +1757183 LINC00943 chr12 126723412 126749027 +1757423 LINC00944 chr12 126729787 126772519 +1757528 LINC02372 chr12 126869010 126874725 +1757549 AC078878.2 chr12 126874804 126888718 +1757573 LINC02405 chr12 126915199 127060565 +1757653 AC079949.3 chr12 127130005 127207706 +1757660 AC079949.1 chr12 127142029 127146532 +1757679 AC079949.5 chr12 127146535 127151330 +1757684 AC079949.2 chr12 127147149 127150081 +1757687 AC079949.6 chr12 127149955 127161259 +1757691 LINC02376 chr12 127274265 127284328 +1757702 LINC02375 chr12 127324152 127340109 +1757715 AC068787.4 chr12 127451346 127455634 +1757719 AC068787.3 chr12 127484243 127486675 +1757723 AC068787.2 chr12 127486938 127533242 +1757731 AC068787.5 chr12 127563908 127590930 +1757736 AC025252.1 chr12 127598168 127599715 +1757740 LINC02411 chr12 127631248 127636488 +1757813 AC025160.1 chr12 127726339 127821183 +1757835 LINC02393 chr12 127881616 127898645 +1757847 LINC00507 chr12 127914707 127960028 +1757965 LINC00508 chr12 127933689 127983854 +1757974 LINC02441 chr12 128023788 128027166 +1757979 AC140121.1 chr12 128052122 128068361 +1757984 LINC02369 chr12 128086621 128118656 +1758043 LINC02368 chr12 128116730 128123103 +1758069 AC061709.2 chr12 128187225 128191495 +1758082 TMEM132C chr12 128267403 128707915 +1758105 AC023595.1 chr12 128399978 128404814 +1758109 SLC15A4 chr12 128793194 128823958 +1758184 AC108704.1 chr12 128826836 128827579 +1758187 GLT1D1 chr12 128853427 128984968 +1758338 TMEM132D chr12 129071725 129904025 +1758375 TMEM132D-AS1 chr12 129109629 129113294 +1758403 TMEM132D-AS2 chr12 129208601 129212662 +1758410 AC130404.1 chr12 129521303 129522763 +1758414 AC130404.2 chr12 129622929 129625366 +1758418 AC117373.1 chr12 129681427 129698227 +1758423 AC117373.2 chr12 129696599 129700122 +1758427 AC055717.1 chr12 129852208 129854944 +1758431 AC055717.2 chr12 130024493 130044956 +1758436 LINC02418 chr12 130032928 130045057 +1758448 AC135388.1 chr12 130047132 130048376 +1758452 LINC02419 chr12 130070325 130072685 +1758456 AC026336.3 chr12 130138693 130140768 +1758459 FZD10-AS1 chr12 130144315 130162256 +1758477 FZD10 chr12 130162459 130165740 +1758492 AC026336.2 chr12 130249679 130266725 +1758496 PIWIL1 chr12 130337887 130372637 +1758617 RIMBP2 chr12 130396137 130716281 +1758827 AC063926.1 chr12 130419535 130421019 +1758831 AC095350.1 chr12 130651342 130669233 +1758856 STX2 chr12 130789600 130839266 +1758932 AC073912.1 chr12 130810606 130812438 +1758936 AC073912.2 chr12 130810821 130812622 +1758940 RAN chr12 130872037 130877678 +1759089 ADGRD1 chr12 130953907 131141469 +1759368 AC073862.1 chr12 130977562 130978768 +1759372 ADGRD1-AS1 chr12 130990138 130993976 +1759380 AC078925.1 chr12 131029110 131035487 +1759384 LINC01257 chr12 131165011 131232940 +1759415 LINC02415 chr12 131296110 131297972 +1759419 AC092850.2 chr12 131310045 131312811 +1759423 LINC02370 chr12 131347470 131367555 +1759428 AC140118.2 chr12 131350844 131371721 +1759433 AC140118.1 chr12 131366660 131371059 +1759437 AC073578.2 chr12 131447337 131455436 +1759444 AC073578.5 chr12 131457018 131458324 +1759448 AC073578.1 chr12 131462853 131529894 +1759479 AC117500.3 chr12 131621891 131623203 +1759483 LINC02414 chr12 131639396 131661823 +1759491 AC117500.6 chr12 131644172 131645651 +1759495 AC117500.1 chr12 131662596 131664704 +1759499 SFSWAP chr12 131711081 131799737 +1759671 AC117500.2 chr12 131756966 131758047 +1759675 MMP17 chr12 131828393 131851783 +1759807 AC131009.2 chr12 131857420 131864538 +1759812 ULK1 chr12 131894622 131923150 +1759906 AC131009.1 chr12 131924736 131929351 +1759911 PUS1 chr12 131929200 131945896 +1760040 AC131009.3 chr12 131934642 131934928 +1760043 EP400 chr12 131949920 132081102 +1760358 AC137590.1 chr12 132077803 132080460 +1760362 AC137590.2 chr12 132083540 132083779 +1760365 DDX51 chr12 132136594 132144319 +1760436 NOC4L chr12 132144457 132152473 +1760508 AC138466.3 chr12 132169823 132170043 +1760511 LINC02361 chr12 132186735 132189695 +1760515 AC138466.1 chr12 132190213 132190997 +1760519 GALNT9 chr12 132196372 132329589 +1760638 AC148477.3 chr12 132275391 132278329 +1760646 AC148477.2 chr12 132277349 132280900 +1760650 AC148477.4 chr12 132282814 132284606 +1760653 AC148477.1 chr12 132329850 132331575 +1760657 AC148477.10 chr12 132344477 132345352 +1760661 AC148476.1 chr12 132424504 132425208 +1760664 AC079031.1 chr12 132457160 132460024 +1760668 AC079031.2 chr12 132462242 132462856 +1760671 FBRSL1 chr12 132489551 132585188 +1760796 AC131212.1 chr12 132593031 132593698 +1760799 LRCOL1 chr12 132603150 132610582 +1760870 P2RX2 chr12 132618776 132622388 +1761068 POLE chr12 132623753 132687376 +1761662 PXMP2 chr12 132687587 132704985 +1761718 PGAM5 chr12 132710819 132722734 +1761785 ANKLE2 chr12 132725503 132761832 +1761914 GOLGA3 chr12 132768914 132829078 +1762135 CHFR chr12 132822187 132956304 +1762506 AC127070.1 chr12 132887842 132888583 +1762510 AC127070.2 chr12 132911470 132914732 +1762513 ZNF605 chr12 132918306 132956306 +1762560 ZNF26 chr12 132986365 133032952 +1762617 ZNF84-DT chr12 133030389 133037222 +1762627 ZNF84 chr12 133037292 133063304 +1762787 ZNF140 chr12 133079838 133107544 +1762923 ZNF891 chr12 133106817 133130473 +1762946 AC026786.2 chr12 133115692 133122340 +1762950 ZNF10 chr12 133130575 133159465 +1763050 ZNF268 chr12 133181409 133214831 +1763306 ANHX chr12 133218312 133236095 +1763351 FAM230C chr13 18195297 18232024 +1763377 LINC00349 chr13 18538880 18551214 +1763386 LINC00388 chr13 18610298 18611675 +1763390 LINC00387 chr13 18672827 18676163 +1763394 LINC00408 chr13 18905419 18935554 +1763447 AL355516.1 chr13 18921888 18944284 +1763453 LINC00442 chr13 19008259 19026802 +1763474 AL137001.1 chr13 19027837 19028701 +1763478 AL137001.2 chr13 19074038 19118315 +1763484 TUBA3C chr13 19173772 19181824 +1763517 AL139327.2 chr13 19262797 19284823 +1763540 LINC00421 chr13 19345049 19346749 +1763544 AL356259.1 chr13 19408042 19409529 +1763548 TPTE2 chr13 19422877 19536762 +1763794 LINC00350 chr13 19561328 19588603 +1763810 MPHOSPH8 chr13 19633659 19673441 +1763874 PSPC1-AS2 chr13 19674624 19675884 +1763878 PSPC1 chr13 19674752 19783019 +1763997 ZMYM5 chr13 19823482 19863649 +1764075 AL355001.1 chr13 19841827 19843672 +1764079 AL355001.2 chr13 19863858 19865048 +1764082 ZMYM2 chr13 19958670 20091829 +1764333 LINC01072 chr13 20102701 20103230 +1764337 GJA3 chr13 20138255 20161052 +1764347 LINC00556 chr13 20181531 20181942 +1764350 GJB2 chr13 20187463 20192938 +1764367 GJB6 chr13 20221962 20232365 +1764534 CRYL1 chr13 20403666 20525873 +1764754 AL590096.1 chr13 20564708 20567045 +1764764 IFT88 chr13 20567069 20691437 +1764939 AL161772.1 chr13 20699307 20703718 +1764942 IL17D chr13 20702127 20723098 +1764970 EEF1AKMT1 chr13 20728731 20773961 +1765004 AL512652.1 chr13 20768876 20769375 +1765007 XPO4 chr13 20777329 20903048 +1765119 LATS2 chr13 20973036 21061586 +1765145 LATS2-AS1 chr13 21005157 21018122 +1765149 SAP18 chr13 21140514 21149084 +1765223 SKA3 chr13 21153595 21176552 +1765324 MRPL57 chr13 21176658 21179084 +1765334 LINC01046 chr13 21224521 21235204 +1765346 LINC00539 chr13 21302862 21348721 +1765431 ZDHHC20 chr13 21372573 21459370 +1765616 ZDHHC20-IT1 chr13 21376977 21377874 +1765620 MICU2 chr13 21492691 21604181 +1765708 FGF9 chr13 21671073 21704498 +1765727 LINC00424 chr13 21872763 21878256 +1765750 AL136962.1 chr13 22040972 22276526 +1765778 AL512484.1 chr13 22589699 22593871 +1765782 LINC00621 chr13 22859050 22916369 +1765810 AL157931.1 chr13 22918591 22924602 +1765814 AL157931.2 chr13 22931537 22931999 +1765817 LINC00362 chr13 23169835 23170597 +1765821 SGCG chr13 23180952 23325165 +1765842 SACS chr13 23328826 23433740 +1765944 SACS-AS1 chr13 23418971 23428869 +1765948 LINC00327 chr13 23465776 23487712 +1765981 LINC00352 chr13 23498796 23502874 +1765985 TNFRSF19 chr13 23570370 23676104 +1766086 MIPEP chr13 23730189 23889400 +1766149 PCOTH chr13 23888842 23897263 +1766166 C1QTNF9B chr13 23890525 23902655 +1766214 AL445985.2 chr13 23954493 23970188 +1766219 SPATA13 chr13 23979805 24307074 +1766442 AL445985.1 chr13 23979810 24035027 +1766449 SPATA13-AS1 chr13 24252749 24254439 +1766454 C1QTNF9 chr13 24307166 24322535 +1766481 C1QTNF9-AS1 chr13 24315725 24321598 +1766485 LINC00566 chr13 24331450 24337121 +1766489 PARP4 chr13 24420931 24512778 +1766571 AL359538.4 chr13 24517794 24530461 +1766575 AL359538.3 chr13 24539139 24541720 +1766579 ATP12A chr13 24680411 24712493 +1766682 AL391560.1 chr13 24723101 24738690 +1766687 AL391560.2 chr13 24747658 24755201 +1766693 RNF17 chr13 24764169 24879921 +1766899 CENPJ chr13 24882279 24922889 +1767037 PABPC3 chr13 25095868 25099254 +1767045 AMER2 chr13 25161684 25172288 +1767064 LINC01053 chr13 25168969 25190643 +1767073 LINC00463 chr13 25172828 25180079 +1767086 LINC01076 chr13 25193107 25210295 +1767090 MTMR6 chr13 25246201 25288009 +1767128 AL590787.1 chr13 25300124 25301438 +1767131 NUP58 chr13 25301556 25349800 +1767375 ATP8A2 chr13 25371974 26025851 +1767628 SHISA2 chr13 26044597 26051031 +1767638 LINC00415 chr13 26052276 26053385 +1767642 RNF6 chr13 26132115 26222314 +1767708 AL138966.2 chr13 26222191 26222654 +1767711 CDK8 chr13 26254104 26405238 +1767810 AL353789.1 chr13 26488952 26496120 +1767815 WASF3 chr13 26557683 26688948 +1767894 WASF3-AS1 chr13 26606544 26641793 +1767928 AL159978.1 chr13 26685640 26698804 +1767932 GPR12 chr13 26755200 26760786 +1767949 AL160035.1 chr13 26965967 26991996 +1767954 USP12 chr13 27066156 27171811 +1767996 USP12-AS1 chr13 27162855 27169135 +1768000 USP12-AS2 chr13 27172259 27182998 +1768004 LINC02340 chr13 27178263 27251288 +1768017 LINC00412 chr13 27236282 27250711 +1768027 RPL21 chr13 27251309 27256691 +1768149 RASL11A chr13 27270327 27273690 +1768171 LINC01079 chr13 27373348 27374366 +1768175 GTF3A chr13 27424619 27435823 +1768298 MTIF3 chr13 27435643 27450591 +1768389 LNX2 chr13 27545913 27620529 +1768442 POLR1D chr13 27620742 27744237 +1768596 AL136439.1 chr13 27667395 27680581 +1768601 GSX1 chr13 27792483 27794768 +1768611 PLUT chr13 27819376 27917298 +1768618 PDX1 chr13 27920000 27926313 +1768628 LINC00543 chr13 27953526 27955370 +1768631 CDX2 chr13 27960918 27969315 +1768647 URAD chr13 27977717 27988693 +1768657 FLT3 chr13 28003274 28100592 +1768770 PAN3-AS1 chr13 28136843 28138193 +1768773 PAN3 chr13 28138506 28295335 +1768876 FLT1 chr13 28300346 28495145 +1769174 POMP chr13 28659104 28678959 +1769211 SLC46A3 chr13 28700064 28718970 +1769251 MTUS2 chr13 28820348 29505947 +1769378 MTUS2-AS2 chr13 29239379 29250554 +1769390 MTUS2-AS1 chr13 29476515 29490105 +1769404 SLC7A1 chr13 29509414 29595688 +1769449 UBL3 chr13 29764371 29850617 +1769465 LINC00297 chr13 29872613 29888405 +1769469 LINC00572 chr13 29918647 29926651 +1769473 LINC00544 chr13 29935771 29950488 +1769502 AL354674.1 chr13 30022021 30023800 +1769505 LINC00365 chr13 30103178 30108895 +1769515 LINC00384 chr13 30151886 30159621 +1769523 LINC00385 chr13 30153744 30160592 +1769528 KATNAL1 chr13 30202630 30307551 +1769608 LINC00427 chr13 30316360 30319903 +1769612 LINC00426 chr13 30340267 30377145 +1769673 AL161893.1 chr13 30388785 30404967 +1769679 LINC01058 chr13 30419519 30422237 +1769683 UBE2L5 chr13 30422488 30429758 +1769714 HMGB1 chr13 30456704 30617597 +1769811 AL353648.1 chr13 30466117 30482312 +1769817 USPL1 chr13 30617693 30660770 +1769864 ALOX5AP chr13 30713478 30764426 +1769900 LINC00398 chr13 30803206 30810645 +1769904 LINC00545 chr13 30880912 30883395 +1769912 TEX26-AS1 chr13 30881933 30933846 +1769991 MEDAG chr13 30906271 30925572 +1770018 TEX26 chr13 30932656 30975500 +1770059 AL353680.1 chr13 30973289 30977623 +1770064 LINC01066 chr13 30995162 30996138 +1770068 AL158065.1 chr13 31049715 31053250 +1770073 HSPH1 chr13 31134973 31162388 +1770301 B3GLCT chr13 31199975 31332276 +1770345 AL161616.2 chr13 31419989 31437999 +1770350 RXFP2 chr13 31739526 31803389 +1770431 AL138708.1 chr13 31838752 31846539 +1770435 FRY chr13 31846713 32299125 +1771137 FRY-AS1 chr13 32025314 32031639 +1771143 ZAR1L chr13 32303700 32315344 +1771174 BRCA2 chr13 32315086 32400266 +1771421 N4BP2L1 chr13 32400723 32428311 +1771602 N4BP2L2 chr13 32432417 32538885 +1771776 N4BP2L2-IT2 chr13 32504506 32509395 +1771779 PDS5B chr13 32586452 32778019 +1771974 AL138820.1 chr13 32782874 32788178 +1771977 LINC00423 chr13 32877431 32911650 +1771983 KL chr13 33016423 33066143 +1772005 STARD13 chr13 33103137 33350630 +1772146 STARD13-IT1 chr13 33158587 33164409 +1772150 STARD13-AS chr13 33180401 33281584 +1772412 AL627232.1 chr13 33285866 33290561 +1772416 LINC02344 chr13 33333679 33335277 +1772420 AL138999.2 chr13 33335497 33349619 +1772428 AL138999.1 chr13 33336216 33336716 +1772431 AL139383.1 chr13 33355206 33676796 +1772463 AL161719.1 chr13 33610967 33611522 +1772467 AL139081.1 chr13 33657436 33659928 +1772472 AL139081.2 chr13 33800138 33802853 +1772476 RFC3 chr13 33818069 33966558 +1772534 AL161891.1 chr13 33846190 33850825 +1772537 LINC02343 chr13 34347986 34616216 +1772547 LINC00457 chr13 34435450 34640803 +1772563 AL161716.1 chr13 34545929 34696612 +1772574 AL138690.1 chr13 34925834 34928076 +1772577 NBEA chr13 34942287 35673022 +1773140 MAB21L1 chr13 35473789 35476689 +1773148 AL390071.1 chr13 35494178 35496615 +1773152 LINC00445 chr13 35697487 35699938 +1773169 DCLK1 chr13 35768652 36131306 +1773343 SOHLH2 chr13 36168217 36214588 +1773390 CCDC169 chr13 36222008 36297840 +1773577 SPART chr13 36301638 36370180 +1773729 SPART-AS1 chr13 36346431 36369601 +1773751 CCNA1 chr13 36431520 36442870 +1773844 SERTM1 chr13 36674020 36697839 +1773854 RFXAP chr13 36819224 36829104 +1773871 SMAD9 chr13 36844831 36920765 +1773928 SMAD9-IT1 chr13 36849366 36850046 +1773932 ALG5 chr13 36949738 37000261 +1773995 EXOSC8 chr13 36998816 37009614 +1774121 SUPT20H chr13 37009312 37059713 +1774713 CSNK1A1L chr13 37103259 37105664 +1774721 LINC01048 chr13 37481467 37484769 +1774727 LINC00547 chr13 37534940 37551536 +1774734 POSTN chr13 37562583 37598844 +1775039 TRPC4 chr13 37636636 37870425 +1775271 AL356495.1 chr13 37869825 37874444 +1775275 LINC02334 chr13 37934298 38066444 +1775312 LINC00571 chr13 38050817 38350259 +1775332 UFM1 chr13 38349849 38363619 +1775387 LINC00437 chr13 38533343 38545299 +1775391 LINC00366 chr13 38567715 38622671 +1775414 FREM2 chr13 38687077 38887131 +1775473 FREM2-AS1 chr13 38821798 38827570 +1775477 STOML3 chr13 38965925 38990859 +1775518 PROSER1 chr13 39009865 39038089 +1775624 NHLRC3 chr13 39038306 39050109 +1775686 AL354809.1 chr13 39053019 39223238 +1775722 LHFPL6 chr13 39209116 39603528 +1775773 COG6 chr13 39655627 39791665 +1775987 LINC00598 chr13 40079106 40535807 +1776121 LINC00332 chr13 40172505 40195361 +1776132 FOXO1 chr13 40469953 40666641 +1776160 MRPS31 chr13 40729128 40771190 +1776191 SLC25A15 chr13 40789412 40812460 +1776240 AL590064.1 chr13 40874685 40877861 +1776244 ELF1 chr13 40931924 41061440 +1776340 WBP4 chr13 41061509 41084006 +1776367 KBTBD6 chr13 41127569 41132802 +1776375 AL354696.2 chr13 41132939 41236686 +1776404 KBTBD7 chr13 41189834 41194569 +1776412 MTRF1 chr13 41216369 41263577 +1776553 AL354696.1 chr13 41229180 41229676 +1776556 NAA16 chr13 41311267 41377030 +1776716 RGCC chr13 41457550 41470871 +1776736 VWA8 chr13 41566835 41961120 +1776900 VWA8-AS1 chr13 41955808 41981565 +1776911 DGKH chr13 42040036 42256578 +1777388 AL157932.1 chr13 42043727 42044247 +1777392 AKAP11 chr13 42272152 42323261 +1777424 LINC02341 chr13 42339188 42485956 +1777439 TNFSF11 chr13 42562736 42608013 +1777522 FAM216B chr13 42781550 42791549 +1777549 LINC01050 chr13 42810366 42814897 +1777556 LINC00428 chr13 42842414 42842887 +1777560 EPSTI1 chr13 42886388 42992271 +1777720 DNAJC15 chr13 43023203 43114213 +1777743 LINC00400 chr13 43158631 43159466 +1777747 ENOX1 chr13 43213518 43786908 +1777790 ENOX1-AS2 chr13 43458465 43459484 +1777794 ENOX1-AS1 chr13 43543918 43548056 +1777798 AL161714.1 chr13 43607313 43629464 +1777803 AL162713.2 chr13 43786781 43814798 +1777808 AL162713.1 chr13 43787591 43787852 +1777811 CCDC122 chr13 43823909 43879740 +1777852 AL512506.1 chr13 43877715 43878163 +1777855 LACC1 chr13 43879284 43893932 +1777901 NRAD1 chr13 43908669 44030461 +1777955 LINC00390 chr13 44094822 44147762 +1777992 SMIM2-AS1 chr13 44110451 44240517 +1778027 SMIM2 chr13 44143150 44161257 +1778043 SMIM2-IT1 chr13 44146470 44158222 +1778048 AL589745.2 chr13 44196006 44197298 +1778052 AL589745.1 chr13 44234118 44256596 +1778061 AL138960.1 chr13 44369365 44369877 +1778064 SERP2 chr13 44373665 44397714 +1778111 TUSC8 chr13 44400250 44405984 +1778122 TSC22D1 chr13 44432143 44577147 +1778218 TSC22D1-AS1 chr13 44575893 44580432 +1778229 LINC00407 chr13 44651812 44701016 +1778234 AL356515.1 chr13 44684487 44715393 +1778238 LINC00330 chr13 44799503 44809630 +1778243 NUFIP1 chr13 44939249 44989471 +1778269 AL359706.1 chr13 44982077 45083125 +1778274 GPALPP1 chr13 44989529 45037669 +1778376 GTF2F2 chr13 45120510 45284893 +1778407 KCTD4 chr13 45192853 45194717 +1778415 TPT1 chr13 45333471 45341370 +1778560 AL138963.4 chr13 45340039 45341183 +1778564 TPT1-AS1 chr13 45341345 45417975 +1778995 AL138963.1 chr13 45350323 45351350 +1778999 SLC25A30 chr13 45393316 45418455 +1779132 SLC25A30-AS1 chr13 45418162 45420371 +1779136 COG3 chr13 45464898 45536701 +1779250 ERICH6B chr13 45534522 45615739 +1779305 LINC01055 chr13 45680184 45701184 +1779311 SPERT chr13 45702320 45714559 +1779350 SIAH3 chr13 45777242 45851753 +1779360 ZC3H13 chr13 45954465 46052759 +1779470 CPB2-AS1 chr13 46052497 46161379 +1779559 CPB2 chr13 46053186 46105033 +1779612 LCP1 chr13 46125920 46211871 +1779742 LRRC63 chr13 46211943 46277366 +1779811 AL139801.1 chr13 46290300 46298110 +1779816 LINC00563 chr13 46296445 46297844 +1779819 RUBCNL chr13 46342000 46438190 +1780149 LINC01198 chr13 46455131 46515958 +1780512 AL138686.1 chr13 46474246 46493268 +1780517 LRCH1 chr13 46553168 46753040 +1780691 AL359880.1 chr13 46717423 46717688 +1780694 ESD chr13 46771256 46797161 +1780780 HTR2A chr13 46831550 46897076 +1780821 HTR2A-AS1 chr13 46852143 46856299 +1780832 SUCLA2 chr13 47745736 48037968 +1781162 AL138962.1 chr13 47825330 47835956 +1781167 LINC00562 chr13 47930153 47932622 +1781170 AL157369.1 chr13 47946053 47956830 +1781174 SUCLA2-AS1 chr13 48001389 48002552 +1781178 NUDT15 chr13 48037726 48047221 +1781190 AL158196.1 chr13 48041751 48042184 +1781193 MED4 chr13 48053323 48095131 +1781258 MED4-AS1 chr13 48077137 48079991 +1781263 ITM2B chr13 48232612 48270357 +1781401 RB1-DT chr13 48296162 48303661 +1781414 RB1 chr13 48303726 48599436 +1781581 AL392048.1 chr13 48340797 48341330 +1781584 LPAR6 chr13 48389567 48444704 +1781657 RCBTB2 chr13 48488959 48533256 +1781797 AL157813.2 chr13 48531800 48556358 +1781801 AL157813.1 chr13 48532013 48532599 +1781804 LINC01077 chr13 48570639 48573317 +1781808 LINC00462 chr13 48576974 48578088 +1781812 CYSLTR2 chr13 48653711 48711226 +1781872 AL161421.1 chr13 48974967 48976867 +1781876 FNDC3A chr13 48975912 49209779 +1782135 MLNR chr13 49220338 49222377 +1782144 CDADC1 chr13 49247925 49293485 +1782223 CAB39L chr13 49308650 49444064 +1782437 SETDB2 chr13 49444374 49495003 +1782568 PHF11 chr13 49495610 49528981 +1782805 RCBTB1 chr13 49531946 49585558 +1782871 ARL11 chr13 49628507 49633872 +1782885 EBPL chr13 49660674 49691486 +1782955 KPNA3 chr13 49699320 49792682 +1783006 AL136301.1 chr13 49792886 49793307 +1783009 SPRYD7 chr13 49912702 49936490 +1783056 DLEU2 chr13 49956670 50125720 +1783163 TRIM13 chr13 49995888 50020481 +1783236 KCNRG chr13 50015254 50020922 +1783257 DLEU1 chr13 50082169 50906856 +1783500 AL137060.3 chr13 50125816 50128463 +1783503 AL158195.1 chr13 50372788 50387158 +1783507 DLEU7 chr13 50519364 50843939 +1783545 RNASEH2B-AS1 chr13 50862172 50910764 +1783605 RNASEH2B chr13 50909678 51024120 +1784516 C13orf42 chr13 51082119 51200252 +1784546 AL157817.1 chr13 51180178 51180967 +1784549 FAM124A chr13 51222334 51284241 +1784593 SERPINE3 chr13 51335773 51364735 +1784670 INTS6 chr13 51354077 51454264 +1784986 INTS6-AS1 chr13 51452364 51554678 +1785144 WDFY2 chr13 51584455 51767709 +1785187 DHRS12 chr13 51767993 51804162 +1785322 AL162377.1 chr13 51803838 51813832 +1785328 TMEM272 chr13 51813347 51845177 +1785368 CCDC70 chr13 51861981 51866232 +1785378 ATP7B chr13 51930436 52012125 +1785818 ALG11 chr13 52012398 52033600 +1785888 UTP14C chr13 52024691 52033600 +1785898 NEK5 chr13 52033611 52129092 +1786155 AL139082.1 chr13 52128891 52132723 +1786159 NEK3 chr13 52132639 52159861 +1786402 LINC02333 chr13 52334295 52341896 +1786415 THSD1 chr13 52377167 52416373 +1786457 VPS36 chr13 52412602 52450634 +1786584 AL359513.1 chr13 52454775 52455331 +1786587 CKAP2 chr13 52455429 52476628 +1786697 LINC00345 chr13 52482804 52489216 +1786704 HNRNPA1L2 chr13 52642425 52643796 +1786712 AL139089.1 chr13 52651305 52652279 +1786715 SUGT1 chr13 52652709 52700909 +1786793 CNMD chr13 52703264 52739820 +1786843 PCDH8 chr13 52842889 52848641 +1786869 OLFM4 chr13 53028813 53052057 +1786885 LINC01065 chr13 53099397 53151914 +1786931 AL136359.1 chr13 53193667 53198540 +1786935 AL356295.1 chr13 53207831 53801489 +1786948 AL450423.2 chr13 53323784 53331065 +1786952 AL450423.1 chr13 53345211 53410880 +1786957 LINC00558 chr13 53815419 53939960 +1786984 LINC00458 chr13 54115783 54142319 +1787018 AL442636.1 chr13 54572354 54687547 +1787027 AL512655.1 chr13 54816352 54819238 +1787031 AL390964.1 chr13 54938604 54986720 +1787329 LINC02335 chr13 55062945 55161490 +1787334 AL354821.1 chr13 55535697 55583524 +1787339 AL138997.1 chr13 56051034 56054397 +1787343 PRR20A chr13 57140918 57143939 +1787355 PRR20C chr13 57140918 57157082 +1787378 PRR20B chr13 57147488 57150509 +1787390 PRR20D chr13 57160632 57163653 +1787402 PRR20E chr13 57167197 57170218 +1787414 PCDH17 chr13 57631744 57729311 +1787461 AL445288.1 chr13 57632759 57633575 +1787465 LINC02338 chr13 58165827 58209483 +1787470 LINC00374 chr13 58211697 58233117 +1787479 AL159156.1 chr13 59121879 59230636 +1787486 DIAPH3 chr13 59665583 60163928 +1787870 DIAPH3-AS1 chr13 60012734 60044357 +1787889 DIAPH3-AS2 chr13 60144648 60153678 +1787894 LINC00434 chr13 60214352 60214946 +1787898 TDRD3 chr13 60396457 60573878 +1788151 LINC00378 chr13 60618991 61176758 +1788204 LINC01442 chr13 60916981 60945955 +1788218 PCDH20 chr13 61409685 61415522 +1788228 LINC02339 chr13 61424689 61427946 +1788232 LINC00358 chr13 61997136 62029572 +1788240 LINC01075 chr13 62212577 62249947 +1788246 LINC01074 chr13 62321305 62322398 +1788250 LINC00459 chr13 62323657 62328833 +1788254 AL445668.1 chr13 62539351 62574905 +1788259 LINC00448 chr13 62672285 62796714 +1788309 AL354810.1 chr13 63034668 63097797 +1788318 LINC00376 chr13 63183096 63328129 +1788327 AL359208.1 chr13 63397011 63513393 +1788341 LINC00395 chr13 63667681 63738018 +1788352 AL445989.1 chr13 63746741 63751080 +1788363 AL445238.2 chr13 63814653 63825534 +1788367 AL445238.1 chr13 63832361 63833531 +1788375 LINC00355 chr13 63851197 64076044 +1788401 LINC01052 chr13 65866070 65922731 +1788414 AL158038.1 chr13 65941073 65973699 +1788418 PCDH9 chr13 66302834 67230445 +1788485 PCDH9-AS1 chr13 66303871 66323561 +1788489 PCDH9-AS2 chr13 66825169 66915031 +1788500 PCDH9-AS3 chr13 66977432 66985776 +1788505 PCDH9-AS4 chr13 66990886 67002007 +1788510 AL160254.1 chr13 67121081 67156624 +1788515 LINC00364 chr13 67326177 67379994 +1788524 AL512452.1 chr13 67577624 67787804 +1788531 AL590027.1 chr13 68025839 68037131 +1788536 LINC00550 chr13 68861284 68885325 +1788544 LINC02342 chr13 68878380 68893573 +1788552 LINC00383 chr13 69221866 69322190 +1788572 KLHL1 chr13 69700594 70108493 +1788625 ATXN8OS chr13 70107213 70149092 +1788647 AL160391.1 chr13 70137831 70139431 +1788650 LINC00348 chr13 71015042 71168417 +1788763 DACH1 chr13 71437966 71867204 +1788859 MZT1 chr13 72708367 72727629 +1788871 BORA chr13 72727749 72756198 +1789085 DIS3 chr13 72752169 72782096 +1789280 PIBF1 chr13 72782133 73016461 +1789406 KLF5 chr13 73054976 73077541 +1789442 LINC00393 chr13 73413473 73661891 +1789493 LINC00392 chr13 73564244 73588070 +1789506 KLF12 chr13 73686089 73995056 +1789531 AL159972.1 chr13 73844683 73845130 +1789534 LINC00402 chr13 74231457 74259976 +1789538 AL353660.1 chr13 74288070 74408810 +1789603 AL355390.1 chr13 74412957 74419115 +1789607 LINC00381 chr13 74419158 74444735 +1789620 LINC00347 chr13 74552503 74565445 +1789650 LINC01078 chr13 75250480 75252012 +1789654 TBC1D4 chr13 75283503 75482169 +1789864 AL139230.1 chr13 75375511 75377294 +1789869 COMMD6 chr13 75525219 75549439 +1789973 UCHL3 chr13 75549480 75606020 +1790051 LMO7-AS1 chr13 75604700 75635994 +1790064 LMO7 chr13 75620434 75859870 +1790701 AL137244.1 chr13 75631271 75632135 +1790704 LMO7DN chr13 75871038 75883811 +1790710 LMO7DN-IT1 chr13 75876886 75881127 +1790716 LINC00561 chr13 75932395 75935132 +1790719 LINC01034 chr13 76013023 76014501 +1790723 AL136441.1 chr13 76552807 76846524 +1790734 AL161717.1 chr13 76664144 76693051 +1790738 AL365394.1 chr13 76833839 76846594 +1790744 KCTD12 chr13 76880175 76886405 +1790752 AC000403.1 chr13 76887551 76891135 +1790755 ACOD1 chr13 76948511 76958638 +1790782 CLN5 chr13 76990660 77019143 +1790982 FBXL3 chr13 76992598 77027195 +1791024 MYCBP2-AS1 chr13 77026767 77129717 +1791062 AC001226.1 chr13 77027944 77028482 +1791065 MYCBP2 chr13 77044657 77327094 +1791519 MYCBP2-AS2 chr13 77080511 77081190 +1791523 AL159158.1 chr13 77417821 77422847 +1791528 SCEL chr13 77535674 77645263 +1791790 AL137140.1 chr13 77569175 77586812 +1791796 SCEL-AS1 chr13 77599755 77606551 +1791806 SLAIN1 chr13 77697687 77764242 +1792035 EDNRB-AS1 chr13 77779723 77844145 +1792054 EDNRB chr13 77895481 77975529 +1792209 OBI1-AS1 chr13 77919689 78617328 +1792286 AL139002.1 chr13 77939016 77975539 +1792295 LINC01069 chr13 77979817 77997881 +1792324 LINC00446 chr13 77997909 78053604 +1792356 AL138957.1 chr13 78275720 78277514 +1792360 AL445209.1 chr13 78596129 78599619 +1792363 POU4F1 chr13 78598362 78603552 +1792373 OBI1 chr13 78614289 78659155 +1792391 LINC00331 chr13 78786272 78840051 +1792452 RBM26 chr13 79311824 79406477 +1792665 RBM26-AS1 chr13 79406293 79427317 +1792715 NDFIP2-AS1 chr13 79477364 79481231 +1792720 NDFIP2 chr13 79481124 79556075 +1792850 LINC01068 chr13 79566678 79571445 +1792861 AL136442.1 chr13 79637433 79667344 +1792866 LINC01038 chr13 79804418 79805685 +1792870 LINC00382 chr13 79872586 79918042 +1792925 AL158064.1 chr13 79941531 80074640 +1792985 LINC01080 chr13 80011077 80028283 +1792989 AL137781.1 chr13 80115733 80134368 +1792994 SPRY2 chr13 80335976 80341126 +1793013 AL590807.1 chr13 80697177 81017737 +1793040 LINC00377 chr13 81018176 81044691 +1793049 LINC00564 chr13 81225865 81226983 +1793052 AL353633.1 chr13 81250438 81302407 +1793060 AL445255.1 chr13 82778208 83102335 +1793065 AL353688.1 chr13 83650249 83654789 +1793070 SLITRK1 chr13 83877205 83882393 +1793078 AL355481.1 chr13 83877888 83895211 +1793094 AL590681.1 chr13 83996173 83997597 +1793098 AL445604.1 chr13 84063106 84069408 +1793103 AL162493.1 chr13 84086802 84448603 +1793114 LINC00333 chr13 84562364 84563236 +1793119 AL445588.1 chr13 84867514 84902424 +1793130 AL356313.1 chr13 85046001 85050096 +1793135 LINC00375 chr13 85065087 85078920 +1793142 AL160154.1 chr13 85144623 85148121 +1793146 LINC00351 chr13 85363601 85544570 +1793156 AL356413.1 chr13 85693937 85783203 +1793162 SLITRK6 chr13 85792790 85806683 +1793186 AL354994.1 chr13 86060813 86170890 +1793191 AL445207.1 chr13 86402982 86462734 +1793195 LINC00430 chr13 86909586 86937108 +1793204 AL360267.2 chr13 87423493 87458407 +1793208 AL360267.1 chr13 87427200 87447235 +1793214 MIR4500HG chr13 87427214 87674235 +1793297 AL355578.1 chr13 87607907 87609234 +1793300 SLITRK5 chr13 87672615 87696272 +1793310 LINC00397 chr13 87801036 87803808 +1793318 AL445647.1 chr13 87807634 87811232 +1793321 LINC00373 chr13 88142867 88236082 +1793328 AL355677.1 chr13 88472151 88477267 +1793332 LINC00433 chr13 88494789 88607814 +1793353 AL445242.1 chr13 88522185 89163186 +1793361 LINC00560 chr13 88626853 88630397 +1793365 LINC00440 chr13 89181324 89280240 +1793374 LINC01047 chr13 89214847 89236890 +1793386 LINC02336 chr13 89402398 89818453 +1793402 LINC01040 chr13 89477608 89500509 +1793406 LINC00353 chr13 89548691 89553804 +1793411 LINC00559 chr13 90060247 90119719 +1793447 LINC01049 chr13 90493287 90535080 +1793455 LINC00410 chr13 90890954 90926597 +1793463 LINC00380 chr13 91087254 91089593 +1793467 LINC00379 chr13 91127613 91131407 +1793475 MIR17HG chr13 91347820 91354579 +1793494 GPC5 chr13 91398621 92873682 +1793535 AL162456.1 chr13 91994518 91996523 +1793538 GPC5-AS2 chr13 92339794 92379536 +1793547 GPC5-IT1 chr13 92484606 92510094 +1793551 AL356737.2 chr13 92610646 92677725 +1793556 GPC5-AS1 chr13 92701389 92721614 +1793567 LINC00363 chr13 93032972 93057926 +1793576 AL354811.2 chr13 93150623 93157452 +1793581 AL354811.1 chr13 93226612 93227317 +1793584 GPC6 chr13 93226807 94408020 +1793621 AL160159.1 chr13 93309669 93311063 +1793625 GPC6-AS2 chr13 93818424 93836144 +1793630 GPC6-AS1 chr13 94154193 94187991 +1793636 DCT chr13 94436811 94479682 +1793713 TGDS chr13 94574054 94596242 +1793755 GPR180 chr13 94601857 94634661 +1793779 LINC00391 chr13 94698725 94708475 +1793788 SOX21-AS1 chr13 94703454 94803430 +1793797 SOX21 chr13 94709622 94712545 +1793805 LINC00557 chr13 94960041 94961319 +1793808 AL139381.1 chr13 94960771 95007420 +1793812 ABCC4 chr13 95019835 95301475 +1794358 CLDN10 chr13 95433604 95579759 +1794398 CLDN10-AS1 chr13 95479444 95533910 +1794404 DZIP1 chr13 95578202 95644703 +1794641 DNAJC3-DT chr13 95648733 95676955 +1794655 DNAJC3 chr13 95677139 95794988 +1794712 AL138955.1 chr13 95744726 95745765 +1794715 UGGT2 chr13 95801580 96053482 +1794954 HS6ST3 chr13 96090839 96839562 +1794969 AL353581.1 chr13 96948018 96949584 +1794975 OXGR1 chr13 96985719 96994730 +1795024 LINC00456 chr13 97168751 97187578 +1795032 MBNL2 chr13 97221434 97394120 +1795154 AL161430.1 chr13 97278768 97295400 +1795159 AL442067.3 chr13 97405169 97433994 +1795167 RAP2A chr13 97434169 97469128 +1795187 AL442067.1 chr13 97435946 97436168 +1795190 AL442067.2 chr13 97437268 97437630 +1795193 AL359502.1 chr13 97675011 97677963 +1795197 AL359502.2 chr13 97725172 97730339 +1795201 AL356580.1 chr13 97939356 97953539 +1795205 IPO5 chr13 97953658 98024296 +1795797 FARP1 chr13 98142562 98455176 +1796222 RNF113B chr13 98175785 98177269 +1796232 AL445223.1 chr13 98233650 98234700 +1796235 AL161896.1 chr13 98329655 98333236 +1796239 FARP1-AS1 chr13 98435405 98435840 +1796243 STK24 chr13 98445185 98577940 +1796381 STK24-AS1 chr13 98577244 98578830 +1796385 SLC15A1 chr13 98683801 98752672 +1796443 DOCK9 chr13 98793429 99086625 +1797420 DOCK9-AS1 chr13 98832084 98834629 +1797425 DOCK9-DT chr13 99087819 99088625 +1797428 UBAC2-AS1 chr13 99181223 99200757 +1797455 UBAC2 chr13 99200774 99386504 +1797573 GPR18 chr13 99254714 99261744 +1797614 GPR183 chr13 99294539 99307399 +1797624 AL136961.1 chr13 99429211 99432702 +1797629 TM9SF2 chr13 99446311 99564048 +1797740 LINC01232 chr13 99486962 99499306 +1797765 AL139035.1 chr13 99498737 99501250 +1797770 LINC00449 chr13 99499727 99501052 +1797774 LINC01039 chr13 99577112 99580368 +1797779 AL139035.2 chr13 99584014 99590508 +1797783 CLYBL chr13 99606669 99897134 +1797882 CLYBL-AS2 chr13 99690081 99690971 +1797886 CLYBL-AS1 chr13 99726245 99728971 +1797894 AL137139.2 chr13 99835813 99957167 +1797924 ZIC5 chr13 99962964 99971909 +1797934 AL355338.1 chr13 99973526 99980034 +1797938 ZIC2 chr13 99981784 99986765 +1797964 LINC00554 chr13 99994899 99997909 +1797967 PCCA-DT chr13 100053074 100088950 +1797975 PCCA chr13 100089015 100530437 +1798418 AL353697.1 chr13 100338982 100364959 +1798423 PCCA-AS1 chr13 100464440 100481205 +1798438 GGACT chr13 100530164 100589528 +1798493 AL356966.1 chr13 100535741 100587146 +1798506 AL136526.1 chr13 100537365 100539567 +1798509 TMTC4 chr13 100603927 100675093 +1798695 NALCN-AS1 chr13 100708325 101059286 +1798705 LINC00411 chr13 100934023 100944553 +1798717 NALCN chr13 101053776 101416508 +1798962 ITGBL1 chr13 101452593 101720856 +1799116 FGF14 chr13 101710804 102402457 +1799152 AL160153.1 chr13 101717564 101723106 +1799157 FGF14-IT1 chr13 102292327 102394519 +1799168 FGF14-AS1 chr13 102367539 102373666 +1799175 FGF14-AS2 chr13 102394630 102395703 +1799178 LINC00555 chr13 102589372 102589813 +1799181 AL158063.1 chr13 102593338 102593873 +1799184 TPP2 chr13 102596986 102679958 +1799626 METTL21C chr13 102685744 102694504 +1799640 CCDC168 chr13 102729367 102759072 +1799654 LINC00283 chr13 102742990 102745224 +1799658 AL157769.1 chr13 102760023 102766653 +1799663 TEX30 chr13 102765888 102773811 +1799757 POGLUT2 chr13 102784281 102798976 +1799802 BIVM chr13 102799119 102841533 +1800129 ERCC5 chr13 102807146 102876001 +1800415 AL137246.1 chr13 102888858 102889834 +1800418 AL137246.2 chr13 102903339 102904000 +1800421 SLC10A2 chr13 103043998 103066417 +1800439 AL162717.1 chr13 103343660 103396450 +1800444 LINC01309 chr13 103420825 103428298 +1800453 AL136524.1 chr13 104125930 104134257 +1800458 AL138954.1 chr13 105410816 105414224 +1800462 DAOA-AS1 chr13 105459055 105505681 +1800471 DAOA chr13 105465867 105491034 +1800642 AL359745.1 chr13 105690429 105702689 +1800650 LINC00343 chr13 105702699 105797539 +1801416 AL138701.2 chr13 105950292 106064069 +1801425 AL139379.1 chr13 106232131 106371082 +1801430 LINC00460 chr13 106374477 106384315 +1801462 EFNB2 chr13 106489745 106535662 +1801483 AL138689.2 chr13 106491147 106521630 +1801499 AL138689.1 chr13 106506046 106506713 +1801502 ARGLU1 chr13 106541673 106568137 +1801531 LINC00551 chr13 106568261 106716679 +1801556 LINC00443 chr13 106653897 106672177 +1801574 AL163534.1 chr13 106753247 106757065 +1801578 AL162574.2 chr13 106773623 106774279 +1801581 AL162574.1 chr13 106903150 106904099 +1801584 AL354741.1 chr13 106955689 106961392 +1801588 FAM155A chr13 107163510 107867496 +1801600 AL445649.1 chr13 107465984 107466674 +1801603 FAM155A-IT1 chr13 107788342 107835451 +1801607 AL359436.1 chr13 107868823 107933503 +1801611 AL136964.1 chr13 107870383 107873372 +1801614 LIG4 chr13 108207439 108218368 +1801666 ABHD13 chr13 108218392 108234243 +1801676 TNFSF13B chr13 108251240 108308484 +1801733 AL157762.1 chr13 108267320 108267734 +1801736 AL138694.1 chr13 108335354 108448316 +1801751 MYO16 chr13 108596152 109208005 +1801989 MYO16-AS2 chr13 109101261 109101919 +1801993 MYO16-AS1 chr13 109163902 109201483 +1801999 AL161431.1 chr13 109269634 109278512 +1802005 LINC00370 chr13 109281973 109297690 +1802015 LINC01067 chr13 109310135 109311773 +1802019 LINC00399 chr13 109400696 109401641 +1802023 AL163541.1 chr13 109478739 109731700 +1802029 LINC00676 chr13 109728282 109730007 +1802034 IRS2 chr13 109752695 109786583 +1802044 AL162497.1 chr13 109785831 109808252 +1802049 AL355810.1 chr13 109805317 109805868 +1802052 AL355974.1 chr13 109984858 109986565 +1802055 AL390755.1 chr13 109988097 110129136 +1802103 AL355974.2 chr13 110031101 110031567 +1802106 LINC00396 chr13 110053285 110054952 +1802112 AL390755.3 chr13 110132003 110136906 +1802117 COL4A1 chr13 110148963 110307157 +1802521 COL4A2 chr13 110305812 110513209 +1802798 COL4A2-AS2 chr13 110456396 110463287 +1802805 COL4A2-AS1 chr13 110502575 110508179 +1802810 RAB20 chr13 110523066 110561722 +1802820 AL139385.1 chr13 110613082 110616353 +1802823 NAXD chr13 110615460 110639993 +1802878 CARS2 chr13 110641412 110713603 +1803160 ING1 chr13 110712736 110723339 +1803204 LINC00567 chr13 110809676 110813084 +1803207 LINC00346 chr13 110863987 110870251 +1803210 ANKRD10 chr13 110878540 110915069 +1803297 ANKRD10-IT1 chr13 110894639 110899172 +1803301 AL442128.2 chr13 110916004 110917827 +1803304 LINC00368 chr13 111095838 111103097 +1803309 AL353704.2 chr13 111096586 111113697 +1803313 ARHGEF7-AS2 chr13 111113812 111115678 +1803317 ARHGEF7 chr13 111114559 111305737 +1803847 ARHGEF7-IT1 chr13 111122652 111144264 +1803851 ARHGEF7-AS1 chr13 111144305 111144733 +1803855 AL353704.1 chr13 111148196 111153171 +1803859 TEX29 chr13 111316184 111344249 +1803896 AL359649.1 chr13 111588201 111672608 +1803904 LINC02337 chr13 111596009 111642079 +1803908 LINC00354 chr13 111865136 111901264 +1803949 SOX1-OT chr13 112056845 112108015 +1803982 SOX1 chr13 112067149 112071706 +1803990 AL356961.1 chr13 112083549 112085471 +1803993 LINC00404 chr13 112106095 112106882 +1803997 LINC01070 chr13 112197350 112201000 +1804005 LINC01043 chr13 112313467 112321758 +1804009 LINC01044 chr13 112322567 112331225 +1804014 SPACA7 chr13 112376355 112434689 +1804081 TUBGCP3 chr13 112485011 112588205 +1804278 AL139384.2 chr13 112602828 112606417 +1804281 ATP11AUN chr13 112647044 112684497 +1804286 AL139384.1 chr13 112686769 112689815 +1804289 ATP11A chr13 112690329 112887168 +1804637 ATP11A-AS1 chr13 112745449 112754693 +1804641 AL356752.1 chr13 112811566 112812158 +1804644 MCF2L chr13 112894378 113099742 +1805306 AL356740.1 chr13 112964835 112966131 +1805309 MCF2L-AS1 chr13 112967484 112968824 +1805313 AL356740.2 chr13 113008778 113009424 +1805316 AL356740.3 chr13 113009671 113010319 +1805319 F7 chr13 113105788 113120681 +1805406 F10 chr13 113122799 113149529 +1805504 F10-AS1 chr13 113128155 113128880 +1805508 AL137002.2 chr13 113149432 113154002 +1805512 PROZ chr13 113158648 113172386 +1805563 AL137002.1 chr13 113165002 113165183 +1805566 PCID2 chr13 113177536 113208715 +1805878 CUL4A chr13 113208193 113267108 +1806157 LAMP1 chr13 113297239 113323672 +1806191 GRTP1 chr13 113324163 113364148 +1806268 AL136221.1 chr13 113339450 113339958 +1806271 GRTP1-AS1 chr13 113351645 113361868 +1806281 ADPRHL1 chr13 113399610 113453524 +1806354 DCUN1D2 chr13 113455819 113490951 +1806474 DCUN1D2-AS chr13 113468901 113476135 +1806481 TMCO3 chr13 113491021 113554590 +1806618 AL442125.2 chr13 113511747 113514473 +1806622 AL442125.1 chr13 113527260 113530621 +1806625 TFDP1 chr13 113584721 113641473 +1806742 ATP4B chr13 113648804 113658198 +1806762 GRK1 chr13 113667219 113737736 +1806789 TMEM255B chr13 113759226 113816995 +1806848 GAS6-AS1 chr13 113815630 113845744 +1806857 GAS6 chr13 113820549 113864076 +1806918 GAS6-DT chr13 113864112 113866834 +1806929 BX072579.1 chr13 113877608 113879376 +1806936 LINC00454 chr13 113878489 113883651 +1806974 BX072579.2 chr13 113883667 113887149 +1806990 LINC00452 chr13 113888306 113923512 +1807014 LINC00565 chr13 113926514 113928844 +1807017 C13orf46 chr13 113953705 113974076 +1807042 RASA3 chr13 113977783 114132623 +1807103 RASA3-IT1 chr13 114107569 114108820 +1807107 CFAP97D2 chr13 114154691 114223084 +1807170 AL160396.1 chr13 114175485 114215835 +1807176 CDC16 chr13 114234887 114272723 +1807538 AL160396.2 chr13 114275326 114277323 +1807542 UPF3A chr13 114281601 114305817 +1807655 CHAMP1 chr13 114314482 114337626 +1807712 LINC01054 chr13 114329559 114333948 +1807717 CR383656.10 chr14 18555677 18596310 +1807721 OR11H12 chr14 18601045 18602129 +1807729 LINC02297 chr14 18630318 18633634 +1807734 CR383656.12 chr14 18636043 18637421 +1807738 AL929601.1 chr14 18920109 18934078 +1807747 AL929601.2 chr14 18944199 18945139 +1807751 POTEM chr14 18967434 19003752 +1807836 AL929601.3 chr14 18977180 18980742 +1807840 AL589182.1 chr14 19024090 19055551 +1807848 AL589743.4 chr14 19124807 19175530 +1807858 AL589743.1 chr14 19244962 19247673 +1807861 LINC01297 chr14 19344578 19384587 +1807871 POTEG chr14 19402486 19434341 +1807956 AL512624.2 chr14 19420975 19425017 +1807960 AL512310.10 chr14 19637225 19641306 +1807965 AL512310.9 chr14 19677644 19679016 +1807969 AL512310.2 chr14 19681420 19684739 +1807974 OR11H2 chr14 19712904 19714332 +1807990 OR4N2 chr14 19719015 19830253 +1808028 OR4Q3 chr14 19743571 19749469 +1808045 OR4M1 chr14 19773504 19783696 +1808069 OR4K2 chr14 19875142 19883932 +1808095 OR4K5 chr14 19920582 19921659 +1808103 OR4K1 chr14 19930917 19936757 +1808131 OR4K15 chr14 19975444 19976659 +1808146 OR4K14 chr14 20014143 20019307 +1808162 OR4K13 chr14 20029399 20036038 +1808187 OR4L1 chr14 20060045 20060983 +1808194 OR4K17 chr14 20110739 20122199 +1808221 OR4N5 chr14 20138820 20145471 +1808239 OR11G2 chr14 20190894 20201075 +1808264 OR11H6 chr14 20223710 20224702 +1808271 OR11H4 chr14 20239286 20244349 +1808295 TTC5 chr14 20256558 20305960 +1808378 AL356019.2 chr14 20260480 20264308 +1808381 AL356019.1 chr14 20305730 20306811 +1808385 CCNB1IP1 chr14 20311368 20333312 +1808600 AL355075.6 chr14 20317949 20319707 +1808604 AL355075.4 chr14 20343048 20343685 +1808607 PARP2 chr14 20343582 20357905 +1808775 AL355075.1 chr14 20344233 20346888 +1808779 TEP1 chr14 20365667 20413501 +1809333 KLHL33 chr14 20425852 20436166 +1809374 OSGEP chr14 20446401 20455089 +1809480 AL355075.2 chr14 20451305 20451918 +1809484 APEX1 chr14 20455191 20457772 +1809684 PIP4P1 chr14 20457719 20461612 +1809756 PNP chr14 20468954 20477094 +1809825 AL355075.3 chr14 20474789 20477089 +1809829 RNASE10 chr14 20505537 20511169 +1809846 RNASE9 chr14 20556093 20560931 +1809985 RNASE11 chr14 20583559 20609884 +1810095 AL163195.2 chr14 20587644 20607221 +1810123 RNASE12 chr14 20590193 20590823 +1810131 OR6S1 chr14 20640696 20641691 +1810138 ANG chr14 20684177 20698971 +1810160 RNASE4 chr14 20684560 20701216 +1810188 AL163636.1 chr14 20693480 20707120 +1810194 EDDM3A chr14 20745887 20748380 +1810204 EDDM3B chr14 20768404 20770948 +1810214 RNASE6 chr14 20781268 20782467 +1810224 AL133371.2 chr14 20783888 20784293 +1810228 RNASE1 chr14 20801228 20802855 +1810278 AL133371.3 chr14 20870278 20873848 +1810289 AL133371.1 chr14 20874305 20875768 +1810293 RNASE3 chr14 20891399 20892348 +1810303 AL355922.4 chr14 20897985 20936255 +1810307 AL355922.3 chr14 20916766 20928580 +1810311 AL355922.1 chr14 20919361 20920299 +1810315 RNASE2 chr14 20955487 20956436 +1810325 METTL17 chr14 20989770 20997035 +1810648 AL161668.3 chr14 20995837 21014822 +1810660 SLC39A2 chr14 20999255 21001871 +1810690 NDRG2 chr14 21016763 21070872 +1812253 TPPP2 chr14 21024109 21036276 +1812349 AL161668.4 chr14 21024172 21029271 +1812357 AL161668.2 chr14 21032818 21033895 +1812361 RNASE13 chr14 21032818 21034807 +1812371 RNASE7 chr14 21042316 21044234 +1812392 RNASE8 chr14 21057822 21058455 +1812400 ARHGEF40 chr14 21070273 21090248 +1812603 ZNF219 chr14 21090077 21104722 +1812722 TMEM253 chr14 21098937 21103724 +1812789 AL161668.1 chr14 21108043 21116703 +1812793 OR5AU1 chr14 21148370 21159060 +1812826 LINC00641 chr14 21200079 21206900 +1812832 HNRNPC chr14 21209136 21269494 +1813394 RPGRIP1 chr14 21287939 21351301 +1813712 SUPT16H chr14 21351476 21384019 +1813834 AL135744.1 chr14 21384292 21384920 +1813837 CHD8 chr14 21385194 21456126 +1814650 RAB2B chr14 21459020 21476960 +1814726 TOX4 chr14 21476597 21499175 +1814870 METTL3 chr14 21498133 21511342 +1815038 SALL2 chr14 21521080 21537216 +1815110 AL161747.2 chr14 21521083 21522660 +1815114 OR10G3 chr14 21568520 21580076 +1815144 TRAV1-1 chr14 21621838 21622567 +1815152 OR10G2 chr14 21633836 21634940 +1815160 TRAV1-2 chr14 21642889 21643578 +1815168 OR4E2 chr14 21653835 21667642 +1815188 OR4E1 chr14 21667940 21673818 +1815201 TRAV2 chr14 21712321 21712843 +1815209 AC243972.1 chr14 21714795 21716262 +1815213 TRAV3 chr14 21723713 21724321 +1815221 TRAV4 chr14 21736152 21736982 +1815229 TRAV5 chr14 21749178 21749705 +1815237 TRAV6 chr14 21768489 21769080 +1815245 TRAV7 chr14 21782993 21783503 +1815252 TRAV8-1 chr14 21797287 21797886 +1815260 TRAV9-1 chr14 21811502 21811977 +1815267 TRAV10 chr14 21825472 21826075 +1815275 TRAV11 chr14 21829539 21830070 +1815279 TRAV12-1 chr14 21841240 21841774 +1815287 TRAV8-2 chr14 21846537 21847221 +1815295 TRAV8-3 chr14 21852558 21853006 +1815302 TRAV13-1 chr14 21868839 21869365 +1815310 TRAV12-2 chr14 21887857 21888502 +1815318 TRAV8-4 chr14 21894433 21895030 +1815326 TRAV8-5 chr14 21903077 21904598 +1815331 TRAV13-2 chr14 21918188 21918756 +1815339 TRAV14DV4 chr14 21924063 21924651 +1815347 TRAV9-2 chr14 21941128 21941657 +1815355 TRAV15 chr14 21950406 21950654 +1815358 TRAV12-3 chr14 21965451 21966061 +1815366 TRAV8-6 chr14 21978459 21979120 +1815374 TRAV16 chr14 21990496 21990938 +1815381 TRAV17 chr14 21997539 21998168 +1815389 TRAV18 chr14 22003106 22003673 +1815397 TRAV19 chr14 22007512 22008181 +1815405 TRAV20 chr14 22040594 22041153 +1815413 TRAV21 chr14 22052514 22053056 +1815421 TRAV22 chr14 22070557 22071208 +1815429 TRAV23DV6 chr14 22086407 22086961 +1815437 TRDV1 chr14 22096032 22096619 +1815448 TRAV24 chr14 22105343 22105846 +1815455 TRAV25 chr14 22112347 22113031 +1815463 TRAV26-1 chr14 22123318 22124285 +1815471 TRAV8-7 chr14 22132553 22133034 +1815478 TRAV27 chr14 22147995 22148633 +1815486 TRAV28 chr14 22155079 22155638 +1815490 TRAV29DV5 chr14 22163238 22163870 +1815498 TRAV30 chr14 22168429 22168988 +1815505 TRAV31 chr14 22177273 22177864 +1815509 TRAV32 chr14 22185562 22186057 +1815513 TRAV33 chr14 22190158 22190713 +1815517 AC244502.1 chr14 22197446 22482959 +1815574 TRAV26-2 chr14 22202583 22203368 +1815581 TRAV34 chr14 22207522 22208129 +1815589 TRAV35 chr14 22221896 22222475 +1815593 TRAV36DV7 chr14 22226746 22227254 +1815601 TRAV37 chr14 22265749 22266264 +1815605 TRAV38-1 chr14 22271968 22272563 +1815613 TRAV38-2DV8 chr14 22281105 22281748 +1815621 TRAV39 chr14 22304054 22304553 +1815628 TRAV40 chr14 22314490 22314919 +1815635 TRAV41 chr14 22320188 22320691 +1815642 AC244502.3 chr14 22415362 22418657 +1815647 TRDV2 chr14 22422371 22423042 +1815655 TRDD1 chr14 22438547 22438554 +1815659 TRDD2 chr14 22439007 22439015 +1815663 TRDD3 chr14 22449113 22449125 +1815667 TRDJ1 chr14 22450089 22450139 +1815671 TRDJ4 chr14 22455249 22455296 +1815675 TRDJ2 chr14 22456689 22456742 +1815679 TRDJ3 chr14 22459098 22459156 +1815683 TRDC chr14 22462932 22465787 +1815695 TRDV3 chr14 22469041 22469698 +1815703 TRAJ61 chr14 22475316 22475375 +1815707 TRAJ60 chr14 22476306 22476362 +1815710 TRAJ59 chr14 22476553 22476606 +1815714 TRAJ58 chr14 22477707 22477769 +1815718 TRAJ57 chr14 22478872 22478934 +1815722 TRAJ56 chr14 22479521 22479582 +1815726 TRAJ55 chr14 22481697 22481753 +1815729 TRAJ54 chr14 22482287 22482346 +1815733 TRAJ53 chr14 22483004 22483069 +1815737 TRAJ52 chr14 22486228 22486296 +1815741 TRAJ51 chr14 22487183 22487245 +1815744 TRAJ50 chr14 22488593 22488652 +1815748 TRAJ49 chr14 22489488 22489543 +1815752 TRAJ48 chr14 22490491 22490553 +1815756 TRAJ47 chr14 22492851 22492907 +1815760 TRAJ46 chr14 22493403 22493465 +1815764 TRAJ45 chr14 22493925 22493990 +1815768 TRAJ44 chr14 22494821 22494883 +1815772 TRAJ43 chr14 22495913 22495966 +1815776 TRAJ42 chr14 22496887 22496952 +1815780 TRAJ41 chr14 22497657 22497718 +1815784 TRAJ40 chr14 22499689 22499749 +1815788 TRAJ39 chr14 22501601 22501663 +1815792 TRAJ38 chr14 22502231 22502292 +1815796 TRAJ37 chr14 22503750 22503814 +1815800 TRAJ36 chr14 22505110 22505167 +1815804 TRAJ35 chr14 22506644 22506702 +1815808 TRAJ34 chr14 22507666 22507723 +1815812 TRAJ33 chr14 22508602 22508658 +1815816 TRAJ32 chr14 22509341 22509406 +1815820 TRAJ31 chr14 22510968 22511024 +1815824 TRAJ30 chr14 22512852 22512908 +1815828 TRAJ29 chr14 22513939 22513998 +1815832 TRAJ28 chr14 22515623 22515688 +1815836 TRAJ27 chr14 22516273 22516331 +1815840 TRAJ26 chr14 22518446 22518505 +1815844 TRAJ25 chr14 22518812 22518871 +1815848 TRAJ24 chr14 22519969 22520031 +1815852 TRAJ23 chr14 22520416 22520478 +1815856 TRAJ22 chr14 22522040 22522102 +1815860 TRAJ21 chr14 22523600 22523654 +1815864 TRAJ20 chr14 22524325 22524381 +1815868 TRAJ19 chr14 22525263 22525322 +1815872 TRAJ18 chr14 22525650 22525715 +1815876 TRAJ17 chr14 22526844 22526906 +1815880 TRAJ16 chr14 22528527 22528586 +1815884 TRAJ14 chr14 22530327 22530378 +1815888 TRAJ13 chr14 22531076 22531138 +1815892 TRAJ12 chr14 22531939 22531998 +1815896 TRAJ11 chr14 22532502 22532561 +1815900 TRAJ10 chr14 22533497 22533560 +1815904 TRAJ9 chr14 22535554 22535614 +1815908 TRAJ8 chr14 22536145 22536204 +1815911 TRAJ7 chr14 22537622 22537680 +1815915 TRAJ6 chr14 22539073 22539134 +1815919 TRAJ5 chr14 22540247 22540306 +1815923 TRAJ4 chr14 22542199 22542261 +1815927 TRAJ3 chr14 22543179 22543240 +1815931 TRAJ2 chr14 22544071 22544136 +1815935 TRAJ1 chr14 22545037 22545098 +1815939 TRAC chr14 22547506 22552156 +1815951 LINC02332 chr14 22556311 22557062 +1815956 AC243965.1 chr14 22556640 22559037 +1815962 DAD1 chr14 22564907 22589224 +1816008 AC243965.2 chr14 22595808 22598946 +1816012 ABHD4 chr14 22598237 22613215 +1816127 OR6J1 chr14 22630929 22644352 +1816137 AL160314.2 chr14 22701476 22766562 +1816168 OXA1L chr14 22766522 22773042 +1816332 SLC7A7 chr14 22773222 22829820 +1816625 MRPL52 chr14 22829879 22835037 +1816802 MMP14 chr14 22836560 22849027 +1816862 LRP10 chr14 22871740 22881713 +1816922 REM2 chr14 22883222 22887678 +1816949 RBM23 chr14 22893204 22919182 +1817365 PRMT5-AS1 chr14 22918947 22926900 +1817393 PRMT5 chr14 22920525 22929408 +1817844 AL132780.1 chr14 22929607 22956374 +1817857 HAUS4 chr14 22946228 22957161 +1818162 AJUBA chr14 22971177 22982551 +1818279 AL132780.2 chr14 22982698 22999078 +1818294 C14orf93 chr14 22985894 23010166 +1818527 PSMB5 chr14 23016543 23035230 +1818592 PSMB11 chr14 23042212 23044060 +1818600 CDH24 chr14 23047062 23057538 +1818744 ACIN1 chr14 23058564 23095614 +1819142 C14orf119 chr14 23095505 23100456 +1819161 LMLN2 chr14 23099062 23104989 +1819270 CEBPE chr14 23117304 23119616 +1819280 SLC7A8 chr14 23125295 23183674 +1819495 RNF212B chr14 23185316 23273477 +1819630 HOMEZ chr14 23272422 23299447 +1819660 PPP1R3E chr14 23295652 23302859 +1819746 BCL2L2 chr14 23298790 23311759 +1819807 BCL2L2-PABPN1 chr14 23306835 23325369 +1819857 PABPN1 chr14 23321289 23326185 +1819950 SLC22A17 chr14 23346306 23352912 +1820114 EFS chr14 23356403 23365752 +1820164 AL049829.2 chr14 23356406 23357003 +1820168 IL25 chr14 23372809 23376403 +1820189 CMTM5 chr14 23376773 23379772 +1820298 MYH6 chr14 23381982 23408273 +1820401 MYH7 chr14 23412740 23435660 +1820487 AL132855.1 chr14 23415339 23415686 +1820491 NGDN chr14 23469689 23509862 +1820628 ZFHX2-AS1 chr14 23511760 23560778 +1820650 ZFHX2 chr14 23520857 23556192 +1820710 AL135999.2 chr14 23530682 23532367 +1820713 THTPA chr14 23555988 23560271 +1820782 AP1G2 chr14 23559565 23568070 +1821144 AL135999.1 chr14 23561097 23568073 +1821150 JPH4 chr14 23568035 23578790 +1821220 AL135999.3 chr14 23619201 23620012 +1821223 DHRS2 chr14 23630115 23645639 +1821366 AL160237.1 chr14 23699797 23729757 +1821422 AL136419.2 chr14 23875938 23882428 +1821427 LINC00596 chr14 23922247 23934568 +1821432 DHRS4-AS1 chr14 23938219 24052555 +1821488 DHRS4 chr14 23953734 23969279 +1821613 DHRS4L2 chr14 23969874 24006408 +1821785 AL136419.3 chr14 24007185 24027782 +1821789 CARMIL3 chr14 24052009 24069729 +1821916 CPNE6 chr14 24070837 24078100 +1822209 NRL chr14 24080107 24115014 +1822272 PCK2 chr14 24094053 24110598 +1822515 DCAF11 chr14 24114195 24125242 +1823087 FITM1 chr14 24131275 24132849 +1823104 PSME1 chr14 24136163 24138967 +1823265 EMC9 chr14 24138959 24141591 +1823339 AL136295.2 chr14 24139445 24140444 +1823343 PSME2 chr14 24143362 24147570 +1823560 RNF31 chr14 24146683 24160660 +1823942 IRF9 chr14 24161265 24166565 +1824101 REC8 chr14 24171853 24180257 +1824283 IPO4 chr14 24180219 24188869 +1824794 AL136295.17 chr14 24188914 24193106 +1824798 TM9SF1 chr14 24189149 24195687 +1824939 AL136295.6 chr14 24198433 24199090 +1824942 AL136295.7 chr14 24201612 24202811 +1824945 TSSK4 chr14 24205696 24208362 +1825014 CHMP4A chr14 24209583 24213869 +1825128 MDP1 chr14 24213943 24216070 +1825197 NEDD8 chr14 24216857 24232367 +1825257 GMPR2 chr14 24232422 24239242 +1825754 TINF2 chr14 24239643 24242674 +1825917 TGM1 chr14 24249114 24264432 +1826043 RABGGTA chr14 24265538 24271739 +1826373 AL096870.8 chr14 24271213 24298846 +1826377 AL096870.6 chr14 24271726 24279089 +1826382 DHRS1 chr14 24290598 24299780 +1826487 NOP9 chr14 24299850 24309124 +1826574 CIDEB chr14 24305096 24311430 +1826643 LTB4R2 chr14 24305734 24312053 +1826685 LTB4R chr14 24311450 24318036 +1826727 ADCY4 chr14 24318349 24335093 +1827102 RIPK3 chr14 24336025 24340022 +1827174 NFATC4 chr14 24365673 24379604 +1827786 NYNRIN chr14 24399003 24419283 +1827815 CBLN3 chr14 24426545 24430954 +1827838 KHNYN chr14 24429286 24441843 +1827928 SDR39U1 chr14 24439766 24442905 +1828102 AL132800.1 chr14 24443016 24508688 +1828110 CMA1 chr14 24505353 24508265 +1828139 CTSG chr14 24573518 24576250 +1828160 AL136018.1 chr14 24595723 24657774 +1828170 GZMH chr14 24606480 24609699 +1828210 GZMB chr14 24630954 24634267 +1828328 STXBP6 chr14 24809656 25050297 +1828448 AL161663.2 chr14 24818385 24820157 +1828452 AL161663.1 chr14 24861172 24865978 +1828456 LINC02286 chr14 25124467 25156314 +1828474 LINC02306 chr14 25647304 26143305 +1828494 AL132633.1 chr14 25916015 25998805 +1828499 NOVA1 chr14 26443090 26598033 +1828650 AL079343.1 chr14 26592747 26594517 +1828653 LINC02588 chr14 26598369 26806467 +1828707 AL110292.1 chr14 26599755 27295516 +1828729 LINC02294 chr14 26775495 26822107 +1828735 LINC02293 chr14 26809340 26836458 +1828779 AL132718.1 chr14 26831401 26873036 +1828784 MIR4307HG chr14 26873092 26918594 +1828929 LINC00645 chr14 27612577 27639636 +1828958 AL139023.1 chr14 28318141 28418612 +1828963 LINC02300 chr14 28592223 28613623 +1828968 FOXG1-AS1 chr14 28726675 28765292 +1828995 FOXG1 chr14 28760330 28770277 +1829024 LINC01551 chr14 28771676 28823817 +1829060 LINC02282 chr14 28782909 28785798 +1829071 LINC02281 chr14 28800084 28830204 +1829082 LINC02327 chr14 28829881 28968400 +1829199 LINC02326 chr14 28875404 29064993 +1829232 AL135878.1 chr14 28936889 29372406 +1829276 AL133166.1 chr14 29210986 29392048 +1829355 AL158058.1 chr14 29390074 29436412 +1829369 AL158058.2 chr14 29415856 29500460 +1829376 PRKD1 chr14 29576479 30191898 +1829629 AL356756.1 chr14 29652809 29657916 +1829633 AL355053.1 chr14 29928445 29932756 +1829637 AL133372.3 chr14 29940745 29980212 +1829644 AL133372.2 chr14 29952397 30297043 +1829657 G2E3-AS1 chr14 30437992 30573629 +1829678 G2E3 chr14 30559158 30620064 +1829930 SCFD1 chr14 30622311 30735850 +1830495 AL121852.1 chr14 30734926 30822702 +1830500 COCH chr14 30874514 30895065 +1830790 AL049830.3 chr14 30876179 30889808 +1830811 STRN3 chr14 30893799 31026401 +1830963 AP4S1 chr14 31025106 31130996 +1831190 HECTD1 chr14 31100112 31207804 +1831675 AL136418.1 chr14 31248628 31302739 +1831683 HEATR5A chr14 31291788 31420550 +1831900 AL139353.2 chr14 31420286 31452883 +1831918 DTD2 chr14 31446036 31457506 +1831956 GPR33 chr14 31482875 31488039 +1831966 NUBPL chr14 31489956 31861224 +1832135 AL163973.3 chr14 31553358 31558498 +1832140 AL163973.2 chr14 31558507 31561334 +1832144 AL355112.1 chr14 31925801 31930146 +1832148 LINC02313 chr14 31944853 31950382 +1832152 AL352984.1 chr14 32006902 32018685 +1832156 ARHGAP5-AS1 chr14 32074946 32076793 +1832159 ARHGAP5 chr14 32076114 32159728 +1832322 AL161665.1 chr14 32149176 32158008 +1832326 AL161665.2 chr14 32200433 32201736 +1832329 AKAP6 chr14 32329298 32837684 +1832495 AL136298.1 chr14 32373337 32417974 +1832504 NPAS3 chr14 32934933 33804176 +1832740 AL161851.1 chr14 33597057 33600989 +1832744 AL161851.2 chr14 33677360 33682886 +1832748 EGLN3 chr14 33924227 34462774 +1832835 EGLN3-AS1 chr14 34040097 34059300 +1832840 SPTSSA chr14 34432788 34462240 +1832850 EAPP chr14 34515938 34539711 +1832922 AL445363.1 chr14 34541740 34546329 +1832930 AL445363.2 chr14 34556774 34561298 +1832938 SNX6 chr14 34561093 34630160 +1833182 CFL2 chr14 34709113 34714823 +1833304 BAZ1A chr14 34752731 34875647 +1833538 AL121603.2 chr14 34874343 34876459 +1833541 SRP54 chr14 34981957 35029567 +1833762 FAM177A1 chr14 35044907 35113130 +1833892 PPP2R3C chr14 35085467 35122517 +1834239 PRORP chr14 35121846 35277622 +1834396 PSMA6 chr14 35278633 35317493 +1834623 AL133163.2 chr14 35362232 35363628 +1834627 NFKBIA chr14 35401511 35404749 +1834721 AL133163.3 chr14 35447003 35447625 +1834725 INSM2 chr14 35534164 35537054 +1834733 RALGAPA1 chr14 35538352 35809304 +1835285 AL162311.3 chr14 35819224 35826765 +1835289 BRMS1L chr14 35826338 35932325 +1835388 AL162311.1 chr14 35873857 35875303 +1835392 AL133304.3 chr14 35897936 36068261 +1835427 AL133304.1 chr14 35947556 35950044 +1835431 AL133304.2 chr14 36061026 36067190 +1835436 LINC00609 chr14 36070427 36165288 +1835441 PTCSC3 chr14 36136108 36176468 +1835447 AL162511.1 chr14 36213200 36235608 +1835452 MBIP chr14 36298564 36320637 +1835614 AL132857.1 chr14 36320753 36656163 +1835625 SFTA3 chr14 36473288 36513829 +1835719 NKX2-1 chr14 36516392 36521149 +1835773 NKX2-1-AS1 chr14 36519278 36523016 +1835777 NKX2-8 chr14 36580004 36582614 +1835787 AL079303.1 chr14 36647083 36658801 +1835791 PAX9 chr14 36657568 36679715 +1835843 SLC25A21 chr14 36677921 37172606 +1835910 AL162464.2 chr14 36788644 36807163 +1835914 AL162464.1 chr14 36808871 36828729 +1835918 AL079304.1 chr14 37097062 37098563 +1835922 SLC25A21-AS1 chr14 37171888 37173811 +1835925 MIPOL1 chr14 37197913 37552361 +1836212 AL121790.2 chr14 37556158 37567095 +1836219 AL121790.1 chr14 37564047 37579125 +1836223 FOXA1 chr14 37589552 37596059 +1836253 TTC6 chr14 37595847 38041442 +1836516 LINC00517 chr14 37896060 37902372 +1836523 AL359233.1 chr14 38003113 38004847 +1836527 AL392023.2 chr14 38034287 38194281 +1836537 AL392023.1 chr14 38190983 38202923 +1836542 SSTR1 chr14 38207904 38213067 +1836554 CLEC14A chr14 38254000 38256093 +1836562 AL355835.1 chr14 38256202 38371338 +1836608 LINC00639 chr14 38738155 38948273 +1836711 SEC23A chr14 39031919 39109646 +1836939 SEC23A-AS1 chr14 39103140 39103812 +1836943 GEMIN2 chr14 39114223 39136973 +1837160 TRAPPC6B chr14 39147811 39170532 +1837245 AL109628.2 chr14 39147833 39151363 +1837249 AL132639.3 chr14 39174885 39175880 +1837253 PNN chr14 39175183 39183220 +1837319 MIA2 chr14 39230231 39388513 +1837994 AL132639.2 chr14 39265703 39267061 +1838000 FBXO33 chr14 39397669 39432500 +1838030 AL049828.1 chr14 39432599 40390547 +1838151 AL049828.2 chr14 40267283 40348331 +1838156 AL390800.1 chr14 40630006 40905513 +1838175 LINC02315 chr14 40954693 41149309 +1838186 AL121821.2 chr14 41583657 41604988 +1838194 LRFN5 chr14 41607570 41904549 +1838252 AL445074.1 chr14 42259731 42268586 +1838256 AL442163.1 chr14 42362983 42703655 +1838262 AL450442.1 chr14 42412573 42528888 +1838266 AL583809.1 chr14 43308648 43314803 +1838271 LINC02307 chr14 43990539 44386064 +1838281 AL161752.1 chr14 44392531 44393716 +1838288 LINC02277 chr14 44444747 44480626 +1838302 FSCB chr14 44504149 44507283 +1838310 AL356022.1 chr14 44507385 44567467 +1838326 LINC02302 chr14 44763153 44782829 +1838337 AL049870.2 chr14 44876874 44897077 +1838341 C14orf28 chr14 44897275 44907257 +1838379 AL049870.3 chr14 44898908 44911863 +1838384 KLHL28 chr14 44924319 45042322 +1838448 TOGARAM1 chr14 44962190 45074431 +1838624 AL121809.2 chr14 45079849 45080189 +1838627 AL121809.1 chr14 45083045 45083977 +1838631 PRPF39 chr14 45084107 45116282 +1838858 FKBP3 chr14 45115599 45135319 +1838920 FANCM chr14 45135930 45200890 +1839139 MIS18BP1 chr14 45203190 45253540 +1839283 AL162632.3 chr14 45369215 45370839 +1839286 AL162632.1 chr14 45377268 45389286 +1839290 AL139354.1 chr14 45567995 45569069 +1839294 LINC02303 chr14 45706250 45715952 +1839314 LINC00871 chr14 45891087 46501903 +1839358 RPL10L chr14 46651010 46651781 +1839366 MDGA2 chr14 46840092 47675605 +1839572 LINC00648 chr14 47764954 47795302 +1839589 AL512358.1 chr14 48194174 48228216 +1839596 AL512358.2 chr14 48262021 48265609 +1839600 AL358335.2 chr14 48394815 48491767 +1839615 AL110505.1 chr14 49057713 49077505 +1839621 RPS29 chr14 49570984 49599164 +1839691 LRR1 chr14 49598761 49614672 +1839751 RPL36AL chr14 49618530 49620626 +1839761 MGAT2 chr14 49620799 49623481 +1839769 AL139099.1 chr14 49620815 49623480 +1839773 DNAAF2 chr14 49625174 49635230 +1839794 AL139099.2 chr14 49629291 49629890 +1839798 POLE2 chr14 49643555 49688422 +1839979 KLHDC1 chr14 49693105 49753150 +1840114 AL591767.1 chr14 49707667 49708792 +1840118 KLHDC2 chr14 49768130 49786385 +1840294 NEMF chr14 49782083 49852821 +1840557 AL627171.2 chr14 49861176 49864326 +1840577 AL627171.1 chr14 49863072 49864379 +1840580 ARF6 chr14 49893082 49897054 +1840590 LINC01588 chr14 49927571 50105043 +1840698 VCPKMT chr14 50108632 50116600 +1840760 SOS2 chr14 50117130 50231578 +1840900 L2HGDH chr14 50237563 50312229 +1841032 DMAC2L chr14 50312324 50335558 +1841179 AL359397.2 chr14 50326526 50327909 +1841183 CDKL1 chr14 50329404 50416461 +1841294 AL359397.1 chr14 50397013 50398345 +1841299 MAP4K5 chr14 50418501 50561126 +1841480 AL118556.1 chr14 50448807 50456742 +1841484 ATL1 chr14 50532509 50633068 +1841624 SAV1 chr14 50632058 50668306 +1841678 AL606834.1 chr14 50662511 50663178 +1841681 NIN chr14 50719763 50831121 +1842295 AL606834.2 chr14 50723777 50724272 +1842298 AL133485.2 chr14 50821880 50823501 +1842302 AL133485.3 chr14 50831962 50838100 +1842306 AL358334.1 chr14 50848122 50865659 +1842310 PYGL chr14 50857891 50944483 +1842462 ABHD12B chr14 50872053 50904970 +1842607 AL358334.3 chr14 50912226 50913358 +1842611 AL358334.2 chr14 50956259 50962002 +1842615 TRIM9 chr14 50975262 51096061 +1842701 AL358334.4 chr14 51022967 51031032 +1842706 AL591770.1 chr14 51088957 51091288 +1842711 TMX1 chr14 51240162 51257655 +1842758 LINC00519 chr14 51304108 51331918 +1842766 LINC00640 chr14 51333068 51365557 +1842797 AL358332.1 chr14 51344914 51385603 +1842803 LINC02310 chr14 51392128 51397135 +1842809 FRMD6-AS2 chr14 51454512 51599952 +1842819 FRMD6 chr14 51489100 51730727 +1843031 AL122125.1 chr14 51637348 51637947 +1843034 FRMD6-AS1 chr14 51649516 51651744 +1843037 AL079307.2 chr14 51750560 51763114 +1843042 AL079307.1 chr14 51765276 51825422 +1843054 GNG2 chr14 51826195 51979342 +1843225 AL358333.2 chr14 51916145 51918571 +1843230 AL358333.3 chr14 51967003 51969800 +1843234 AL358333.1 chr14 51982520 51987219 +1843238 RTRAF chr14 51989514 52010694 +1843318 NID2 chr14 52004803 52069228 +1843462 LINC02319 chr14 52111122 52129625 +1843467 PTGDR chr14 52267698 52276724 +1843488 PTGER2 chr14 52314305 52328598 +1843509 TXNDC16 chr14 52430596 52552522 +1843585 GPR137C chr14 52552836 52637713 +1843641 ERO1A chr14 52639915 52695900 +1843828 AL133453.1 chr14 52640839 52641566 +1843832 PSMC6 chr14 52707178 52728590 +1844065 STYX chr14 52730166 52774989 +1844125 GNPNAT1 chr14 52775193 52791668 +1844200 AL139317.3 chr14 52775237 52777740 +1844207 AL139317.5 chr14 52791756 52930185 +1844248 AL139317.1 chr14 52792875 52820034 +1844252 FERMT2 chr14 52857268 52952435 +1844567 AL352979.4 chr14 52951432 52952864 +1844570 DDHD1 chr14 53036745 53153282 +1844726 AL352979.2 chr14 53036755 53038251 +1844730 AL356020.1 chr14 53153354 53157528 +1844735 AL365295.1 chr14 53169010 53883740 +1844882 AL365295.2 chr14 53364146 53392048 +1844886 AL163953.1 chr14 53599832 53614026 +1844890 LINC02331 chr14 53685139 53850882 +1844898 BMP4 chr14 53949736 53958761 +1844982 AL138479.2 chr14 53954671 53962234 +1844986 CDKN3 chr14 54396849 54420218 +1845173 CNIH1 chr14 54423561 54441391 +1845275 AL359792.1 chr14 54470709 54471218 +1845279 GMFB chr14 54474484 54489026 +1845404 CGRRF1 chr14 54509812 54539292 +1845492 SAMD4A chr14 54567097 54793315 +1845668 AL133444.1 chr14 54684753 54687918 +1845677 GCH1 chr14 54842008 54902826 +1845779 WDHD1 chr14 54938949 55027105 +1845939 SOCS4 chr14 55027230 55049489 +1845972 MAPK1IP1L chr14 55051647 55070194 +1846011 LGALS3 chr14 55124110 55145423 +1846074 DLGAP5 chr14 55148112 55191608 +1846194 AL139316.1 chr14 55196727 55199013 +1846198 AL158801.2 chr14 55262222 55272075 +1846208 FBXO34 chr14 55271421 55361918 +1846252 AL158801.3 chr14 55325834 55339501 +1846257 ATG14 chr14 55366392 55411858 +1846291 TBPL2 chr14 55413541 55456726 +1846322 KTN1-AS1 chr14 55496786 55580888 +1846354 KTN1 chr14 55559072 55701526 +1847260 AL355773.1 chr14 55748208 55773203 +1847266 LINC00520 chr14 55781132 55796731 +1847318 AL163952.1 chr14 55896443 55962970 +1847352 AL138995.1 chr14 56117316 56117990 +1847355 PELI2 chr14 56117814 56301524 +1847399 AL355073.1 chr14 56303490 56310761 +1847405 AL355073.2 chr14 56305838 56306394 +1847408 LINC02284 chr14 56310880 56427032 +1847449 TMEM260 chr14 56488354 56650606 +1847716 AL355103.1 chr14 56514331 56551309 +1847720 AL161757.2 chr14 56633244 56648658 +1847729 AL161757.5 chr14 56648965 56730535 +1847738 AL161757.3 chr14 56759379 56765757 +1847742 OTX2 chr14 56799905 56816693 +1847886 OTX2-AS1 chr14 56813183 57152177 +1847908 AL161757.4 chr14 56817570 56893710 +1847923 AL137100.3 chr14 56951008 57060715 +1847961 AL391152.1 chr14 57066260 57112660 +1847969 EXOC5 chr14 57200507 57268905 +1848182 AP5M1 chr14 57268924 57298742 +1848277 AL355834.2 chr14 57335203 57344724 +1848281 AL355834.1 chr14 57355446 57359410 +1848284 NAA30 chr14 57390544 57415906 +1848335 CCDC198 chr14 57469301 57493867 +1848486 SLC35F4 chr14 57563920 57982194 +1848596 AL161804.1 chr14 57578409 57600404 +1848609 AL049838.1 chr14 57993545 57994525 +1848612 ARMH4 chr14 57999735 58298139 +1848659 ACTR10 chr14 58200080 58235636 +1848899 PSMA3 chr14 58244843 58272012 +1849072 AL132989.1 chr14 58264662 58269681 +1849076 PSMA3-AS1 chr14 58265365 58298134 +1849146 AL132989.2 chr14 58288033 58289158 +1849151 ARID4A chr14 58298504 58373887 +1849444 AL139021.2 chr14 58370023 58395641 +1849448 TOMM20L chr14 58395928 58408702 +1849477 AL139021.1 chr14 58398557 58427125 +1849481 TIMM9 chr14 58408495 58427531 +1849604 KIAA0586 chr14 58427385 58551297 +1850558 DACT1 chr14 58633967 58648321 +1850627 LINC01500 chr14 58646631 59184247 +1850873 DAAM1 chr14 59188646 59371405 +1851049 GPR135 chr14 59429022 59465342 +1851076 L3HYPDH chr14 59460363 59484408 +1851140 JKAMP chr14 59484443 59505410 +1851304 CCDC175 chr14 59504539 59576812 +1851410 RTN1 chr14 59595976 59870776 +1851529 AL133299.1 chr14 59919423 59920339 +1851533 LRRC9 chr14 59919713 60063559 +1851797 AL157911.1 chr14 59969116 60091783 +1851808 PCNX4 chr14 60091911 60169133 +1851962 DHRS7 chr14 60144119 60169856 +1852082 AL157756.1 chr14 60240121 60248765 +1852098 PPM1A chr14 60245752 60299087 +1852211 LINC02322 chr14 60323236 60323907 +1852215 C14orf39 chr14 60396469 60515543 +1852329 SIX6 chr14 60509146 60512850 +1852339 AL049874.3 chr14 60515119 60554916 +1852343 SALRNA1 chr14 60639216 60642589 +1852347 SIX1 chr14 60643421 60658259 +1852376 SIX4 chr14 60709539 60724351 +1852402 MNAT1 chr14 60734742 60969965 +1852490 TRMT5 chr14 60971441 60981170 +1852520 SLC38A6 chr14 60981114 61083733 +1852945 PRKCH chr14 61187559 61550976 +1853238 TMEM30B chr14 61277370 61281761 +1853252 AL359220.1 chr14 61294909 61322838 +1853265 AL355916.2 chr14 61535385 61545484 +1853292 LINC01303 chr14 61556273 61570653 +1853307 AL355916.1 chr14 61570405 61658696 +1853322 HIF1A-AS1 chr14 61681041 61695823 +1853326 HIF1A chr14 61695513 61748259 +1853529 HIF1A-AS3 chr14 61707564 61751099 +1853538 SNAPC1 chr14 61762420 61796428 +1853564 SYT16 chr14 61811974 62112550 +1853636 AL390816.1 chr14 62069518 62081154 +1853641 AL390816.2 chr14 62103122 62117175 +1853651 LINC00644 chr14 62134149 62139973 +1853655 KCNH5 chr14 62699464 63102037 +1853742 AL137191.1 chr14 63122888 63178190 +1853751 RHOJ chr14 63204114 63293508 +1853798 AL049871.1 chr14 63298126 63299547 +1853802 GPHB5 chr14 63312835 63318935 +1853822 PPP2R5E chr14 63371364 63543377 +1853960 AL136038.3 chr14 63543569 63544664 +1853963 WDR89 chr14 63597039 63641861 +1854002 AL136038.2 chr14 63598874 63599248 +1854006 AL136038.5 chr14 63642035 63665593 +1854021 SGPP1 chr14 63684216 63728065 +1854033 SYNE2 chr14 63852983 64226433 +1855530 ESR2 chr14 64084232 64338112 +1855769 AL161756.1 chr14 64329431 64338639 +1855781 AL161756.3 chr14 64349677 64352284 +1855785 MTHFD1 chr14 64388031 64463457 +1856370 AL122035.1 chr14 64422935 64448557 +1856374 AL122035.2 chr14 64440369 64442238 +1856377 ZBTB25 chr14 64449106 64505213 +1856427 AKAP5 chr14 64465499 64474503 +1856444 ZBTB1 chr14 64503712 64533690 +1856497 AL049869.3 chr14 64513952 64540368 +1856508 HSPA2 chr14 64535905 64546173 +1856528 PPP1R36 chr14 64549920 64589381 +1856631 AL049869.2 chr14 64552694 64596536 +1856639 PLEKHG3 chr14 64704102 64750249 +1856821 SPTB chr14 64746283 64879907 +1857096 CHURC1 chr14 64914361 64944591 +1857178 GPX2 chr14 64939152 64942905 +1857231 RAB15 chr14 64945814 64973226 +1857401 FNTB chr14 64986895 65062652 +1857474 AL139022.2 chr14 65003325 65003767 +1857477 MAX chr14 65006174 65102695 +1857724 AL139022.1 chr14 65082034 65094212 +1857741 LINC02324 chr14 65197254 65222443 +1857762 AL355076.2 chr14 65236480 65318790 +1857772 FUT8 chr14 65410592 65744121 +1857977 FUT8-AS1 chr14 65411170 65412690 +1857980 AL391261.2 chr14 65957297 66004523 +1857986 AL391261.4 chr14 65986967 65987447 +1857989 LINC02290 chr14 66111557 66131716 +1858137 AL359232.1 chr14 66212810 66509394 +1858160 AL157997.1 chr14 66248811 66278875 +1858164 CCDC196 chr14 66411704 66498677 +1858417 GPHN chr14 66507407 67181803 +1858754 AL049835.1 chr14 66969038 66969816 +1858758 FAM71D chr14 67189393 67228550 +1858933 MPP5 chr14 67241342 67336061 +1859040 AL135978.2 chr14 67283749 67294073 +1859046 ATP6V1D chr14 67294371 67360265 +1859254 EIF2S1 chr14 67360328 67386516 +1859334 PLEK2 chr14 67386984 67412167 +1859418 TMEM229B chr14 67447084 67533739 +1859507 PLEKHH1 chr14 67533290 67589612 +1859705 PIGH chr14 67581955 67600286 +1859832 ARG2 chr14 67619920 67651708 +1859870 AL049779.4 chr14 67627299 67639675 +1859874 VTI1B chr14 67647085 67674820 +1859945 RDH11 chr14 67676800 67695793 +1860078 RDH12 chr14 67701886 67734451 +1860129 ZFYVE26 chr14 67727374 67816590 +1860491 RAD51B chr14 67819779 68730218 +1860762 AL133370.1 chr14 68125004 68130196 +1860766 AL121820.3 chr14 68605396 68611732 +1860771 AL121820.2 chr14 68627166 68628445 +1860775 AL121820.1 chr14 68683411 68685565 +1860779 AL133313.1 chr14 68693656 68695734 +1860783 AL132986.1 chr14 68731234 68736678 +1860787 ZFP36L1 chr14 68787660 68796253 +1860840 ACTN1 chr14 68874143 68979440 +1861253 ACTN1-AS1 chr14 68979682 68987463 +1861262 DCAF5 chr14 69050881 69153150 +1861419 AL391262.1 chr14 69154311 69154804 +1861422 AL359317.2 chr14 69183017 69214092 +1861437 EXD2 chr14 69191511 69244020 +1861628 AL359317.1 chr14 69239166 69260567 +1861633 GALNT16 chr14 69259277 69357033 +1861801 ERH chr14 69380128 69398299 +1861833 SLC39A9 chr14 69398015 69462390 +1861978 AL157996.2 chr14 69479057 69483714 +1861982 PLEKHD1 chr14 69484692 69531551 +1862017 CCDC177 chr14 69569799 69574871 +1862027 AL133445.3 chr14 69582916 69584946 +1862031 SUSD6 chr14 69611596 69715144 +1862055 AL133445.2 chr14 69617122 69617648 +1862058 SRSF5 chr14 69726900 69772005 +1862282 SLC10A1 chr14 69775416 69797241 +1862298 SMOC1 chr14 69854131 70032366 +1862371 SLC8A3 chr14 70044217 70189070 +1862537 AL160191.1 chr14 70187123 70230187 +1862553 AL356804.1 chr14 70255629 70343388 +1862567 COX16 chr14 70325081 70416984 +1862603 SYNJ2BP chr14 70366499 70417090 +1862621 AL357153.2 chr14 70425812 70547464 +1862626 ADAM21 chr14 70452174 70459905 +1862636 ADAM20 chr14 70522358 70535015 +1862655 MED6 chr14 70581257 70600690 +1862799 AL357153.1 chr14 70608798 70641298 +1862804 TTC9 chr14 70641916 70675366 +1862816 LINC01269 chr14 70698698 70712153 +1862822 MAP3K9 chr14 70722526 70809534 +1862994 AC004816.1 chr14 70809841 70815994 +1863008 AC004816.2 chr14 70822004 70823984 +1863012 AC004825.2 chr14 70906657 70907111 +1863015 PCNX1 chr14 70907405 71115382 +1863296 AC004825.3 chr14 70945640 70959029 +1863300 AC004817.3 chr14 71141125 71143253 +1863303 AC004817.5 chr14 71179053 71243841 +1863310 AC004817.2 chr14 71181456 71182106 +1863313 AC004817.1 chr14 71212633 71218216 +1863317 AC004817.4 chr14 71219100 71222724 +1863320 AC005476.2 chr14 71292729 71321882 +1863333 SIPA1L1 chr14 71320449 71741229 +1863633 AC004974.1 chr14 71586269 71590354 +1863637 AC004900.1 chr14 71734927 71739794 +1863642 AC005993.1 chr14 71848606 71928596 +1863664 RGS6 chr14 71932429 72566530 +1864239 AC004828.2 chr14 72515407 72544622 +1864243 AC004828.1 chr14 72552580 72595125 +1864248 DPF3 chr14 72619296 72894116 +1864467 AL392024.1 chr14 72701762 72704280 +1864471 DCAF4 chr14 72926377 72959703 +1864721 ZFYVE1 chr14 72969451 73027131 +1864874 AL442663.3 chr14 73057925 73059415 +1864878 RBM25 chr14 73058532 73123899 +1865138 PSEN1 chr14 73136418 73223691 +1865532 PAPLN chr14 73237497 73274640 +1865933 AC004846.1 chr14 73242651 73245979 +1865937 AC004846.2 chr14 73272182 73274081 +1865942 NUMB chr14 73275107 73458617 +1866415 AC005280.2 chr14 73458850 73466167 +1866434 AC005280.1 chr14 73462362 73477175 +1866447 HEATR4 chr14 73478484 73558947 +1866561 RIOX1 chr14 73490933 73493394 +1866569 AC005225.1 chr14 73517233 73520648 +1866573 AC005225.3 chr14 73522878 73530610 +1866577 ACOT1 chr14 73537143 73543796 +1866600 AC005225.2 chr14 73555115 73633941 +1866610 ACOT2 chr14 73567620 73575658 +1866662 ACOT4 chr14 73591706 73596496 +1866674 ACOT6 chr14 73610945 73619888 +1866706 DNAL1 chr14 73644875 73703732 +1866860 AC006146.1 chr14 73698103 73700351 +1866864 PNMA1 chr14 73711783 73714384 +1866872 ELMSAN1 chr14 73715122 73790285 +1867044 AC005520.2 chr14 73787355 73803300 +1867055 LINC02274 chr14 73822559 73830135 +1867059 PTGR2 chr14 73851844 73886827 +1867175 AC005520.5 chr14 73873689 73885555 +1867181 ZNF410 chr14 73886617 73932511 +1867593 AC005480.1 chr14 73896164 73938114 +1867604 AC005520.3 chr14 73905267 73905636 +1867607 FAM161B chr14 73931501 73950414 +1867665 COQ6 chr14 73949926 73963670 +1867904 ENTPD5 chr14 73958010 74019399 +1868037 BBOF1 chr14 74019349 74082863 +1868123 ALDH6A1 chr14 74056847 74084492 +1868230 LIN52 chr14 74084796 74201235 +1868279 VSX2 chr14 74239449 74262738 +1868295 ABCD4 chr14 74285269 74303055 +1868744 AC005519.1 chr14 74289127 74294425 +1868748 VRTN chr14 74303069 74360008 +1868767 SYNDIG1L chr14 74405894 74426210 +1868799 AC005479.2 chr14 74471930 74472360 +1868802 AC005479.1 chr14 74474007 74474864 +1868806 NPC2 chr14 74476192 74494177 +1868926 ISCA2 chr14 74493756 74497106 +1868968 LTBP2 chr14 74498183 74612378 +1869219 AC013451.1 chr14 74552181 74560048 +1869223 AC013451.2 chr14 74614693 74616647 +1869230 AREL1 chr14 74653437 74713108 +1869504 FCF1 chr14 74713144 74738620 +1869640 YLPM1 chr14 74763316 74859435 +1869820 PROX2 chr14 74852871 74871940 +1869854 DLST chr14 74881891 74903743 +1870118 RPS6KL1 chr14 74903954 74923396 +1870329 PGF chr14 74941834 74955626 +1870421 EIF2B2 chr14 75002921 75012366 +1870500 AL049780.1 chr14 75004719 75008481 +1870504 MLH3 chr14 75013764 75051532 +1870720 ACYP1 chr14 75053237 75069483 +1870789 ZC2HC1C chr14 75064170 75079988 +1870863 NEK9 chr14 75079353 75127344 +1871022 AL049780.2 chr14 75127153 75136930 +1871026 TMED10 chr14 75131469 75176612 +1871078 AL691403.2 chr14 75176929 75177418 +1871081 AL691403.1 chr14 75238616 75269283 +1871085 AF111167.1 chr14 75259411 75271950 +1871096 FOS chr14 75278826 75282230 +1871185 LINC01220 chr14 75294404 75298109 +1871201 AF111167.2 chr14 75423683 75427741 +1871207 JDP2 chr14 75427716 75474111 +1871292 BATF chr14 75522455 75547004 +1871319 AC007182.1 chr14 75574888 75579588 +1871324 FLVCR2 chr14 75578620 75663214 +1871489 TTLL5 chr14 75633625 75955079 +1871846 ERG28 chr14 75649791 75660876 +1871862 AF107885.2 chr14 75814502 75847698 +1871874 IFT43 chr14 75902136 76084585 +1872012 TGFB3 chr14 75958099 75982991 +1872067 TGFB3-AS1 chr14 75970924 75971587 +1872071 AC016526.4 chr14 76131707 76152627 +1872075 GPATCH2L chr14 76151916 76254342 +1872277 AC016526.2 chr14 76235817 76263474 +1872282 AC016526.1 chr14 76280943 76310066 +1872287 ESRRB chr14 76310712 76501837 +1872425 AC008050.1 chr14 76495363 76726712 +1872431 AC007376.2 chr14 76710658 76761388 +1872436 VASH1 chr14 76761468 76783015 +1872489 AF111169.3 chr14 76774284 76781518 +1872496 AF111169.1 chr14 76778952 76782249 +1872500 VASH1-AS1 chr14 76781733 76786724 +1872508 ANGEL1 chr14 76786168 76826246 +1872585 AF111169.4 chr14 76790267 76793807 +1872589 LRRC74A chr14 76826372 76870302 +1872715 AF111169.2 chr14 76921840 76924649 +1872721 AC007686.4 chr14 76958098 77000609 +1872725 LINC01629 chr14 76959638 76965802 +1872730 IRF2BPL chr14 77024543 77028708 +1872738 AC007686.3 chr14 77028086 77031572 +1872741 LINC02288 chr14 77041064 77069503 +1872747 AC007686.2 chr14 77048172 77086457 +1872752 LINC02289 chr14 77069169 77076392 +1872775 AC007686.5 chr14 77084689 77085977 +1872779 CIPC chr14 77098126 77117287 +1872868 TMEM63C chr14 77116568 77259495 +1872997 ZDHHC22 chr14 77131270 77142734 +1873025 AC007375.3 chr14 77140683 77142996 +1873028 NGB chr14 77265483 77271312 +1873042 POMT2 chr14 77274956 77320884 +1873282 GSTZ1 chr14 77320996 77331597 +1873557 TMED8 chr14 77335029 77377094 +1873575 SAMD15 chr14 77376689 77391497 +1873598 NOXRED1 chr14 77394021 77423517 +1873635 VIPAS39 chr14 77426675 77457952 +1873938 AHSA1 chr14 77457870 77469472 +1874082 ISM2 chr14 77474394 77498816 +1874178 SPTLC2 chr14 77505997 77616773 +1874250 ALKBH1 chr14 77672404 77708023 +1874300 SLIRP chr14 77708071 77761104 +1874429 SNW1 chr14 77717599 77761207 +1874581 C14orf178 chr14 77760830 77769742 +1874613 ADCK1 chr14 77800109 77935014 +1874738 NRXN3 chr14 78170373 79868290 +1875091 AF099810.1 chr14 78279572 78283376 +1875096 AC009396.2 chr14 78695321 78698122 +1875100 AC009396.3 chr14 78703615 78709934 +1875104 AC009396.1 chr14 78744398 78753878 +1875108 AC026888.1 chr14 79072132 79074767 +1875115 AC022469.1 chr14 79199982 79201632 +1875119 AC022469.2 chr14 79246668 79249023 +1875126 AC008056.2 chr14 79611418 79633311 +1875131 AC008056.3 chr14 79639754 79644431 +1875135 AC008056.1 chr14 79661666 79791263 +1875141 AF123462.1 chr14 79893080 79974169 +1875146 DIO2 chr14 80197527 80387757 +1875262 DIO2-AS1 chr14 80211419 80455469 +1875273 CEP128 chr14 80476983 80959517 +1875572 TSHR chr14 80954989 81146302 +1875742 AC007262.2 chr14 81012099 81170429 +1875780 AL136040.2 chr14 81169776 81175400 +1875784 GTF2A1 chr14 81175452 81221377 +1875862 AL136040.1 chr14 81221218 81222460 +1875866 STON2 chr14 81260656 81436465 +1875975 LINC02308 chr14 81441987 81450371 +1875992 SEL1L chr14 81471547 81533853 +1876087 LINC01467 chr14 81605338 81623086 +1876101 LINC02311 chr14 81727780 81743749 +1876119 AL355838.1 chr14 81741002 82030349 +1876149 LINC02301 chr14 82642605 82746664 +1876212 AL355095.1 chr14 82788478 82796221 +1876216 AL359238.1 chr14 83017106 83018144 +1876220 AL162872.1 chr14 83018201 83039602 +1876224 LINC02305 chr14 83903437 83915377 +1876237 AL356807.1 chr14 83986776 84140544 +1876245 AL357172.1 chr14 85202849 85239474 +1876250 AL049775.2 chr14 85362457 85516934 +1876257 LINC02329 chr14 85385927 85388765 +1876262 LINC00911 chr14 85393828 85420550 +1876283 AL049775.1 chr14 85518871 85531585 +1876294 AL049775.3 chr14 85528599 85529386 +1876298 FLRT2 chr14 85530144 85654428 +1876337 LINC02328 chr14 85911438 86161500 +1876409 LINC02316 chr14 86006893 86062981 +1876471 AL161753.1 chr14 86283243 86304863 +1876476 LINC02309 chr14 86332376 86401285 +1876481 LINC01148 chr14 86905778 86922755 +1876488 AL358292.1 chr14 86936640 86989125 +1876493 AL352955.1 chr14 87251103 87251679 +1876497 AL157688.1 chr14 87323753 87332390 +1876502 LINC02296 chr14 87353070 87573022 +1876511 AL135746.1 chr14 87568181 87569399 +1876516 LINC02330 chr14 87634379 87655294 +1876521 AL359237.1 chr14 87710419 87872291 +1876537 AL136501.1 chr14 87810982 87838339 +1876542 GALC chr14 87837820 87993665 +1876872 GPR65 chr14 88005135 88014811 +1876882 AL157955.1 chr14 88010787 88015611 +1876887 LINC01147 chr14 88018181 88036319 +1876898 LINC01146 chr14 88024519 88098025 +1877347 AL133279.2 chr14 88136733 88159845 +1877352 AL133279.3 chr14 88158240 88160591 +1877355 AL133279.1 chr14 88175391 88180198 +1877364 KCNK10 chr14 88180103 88326907 +1877432 SPATA7 chr14 88384924 88470350 +1877782 PTPN21 chr14 88465778 88555007 +1877972 AL162171.2 chr14 88499334 88515502 +1877979 AL162171.1 chr14 88551597 88552493 +1877983 ZC3H14 chr14 88562970 88627596 +1878514 AL162171.3 chr14 88589231 88592408 +1878517 EML5 chr14 88612431 88792752 +1878834 AL121768.1 chr14 88819608 88822151 +1878837 TTC8 chr14 88824153 88881078 +1879268 AL137785.1 chr14 89013386 89025807 +1879272 FOXN3 chr14 89124871 89619149 +1879470 AL138478.1 chr14 89156743 89157574 +1879473 AL357093.2 chr14 89349377 89366081 +1879483 AL357093.1 chr14 89355060 89356571 +1879487 AL356805.1 chr14 89399995 89409469 +1879491 FOXN3-AS1 chr14 89417354 89419793 +1879495 FOXN3-AS2 chr14 89576216 89577477 +1879498 AL137230.1 chr14 89628921 89642671 +1879509 EFCAB11 chr14 89794669 89954777 +1879662 TDP1 chr14 89954939 90044764 +1880035 KCNK13 chr14 90061994 90185853 +1880045 PSMC1 chr14 90256527 90275429 +1880132 NRDE2 chr14 90267860 90331969 +1880256 AL161662.1 chr14 90291516 90294942 +1880260 AL512791.2 chr14 90383365 90387973 +1880263 CALM1 chr14 90396502 90408268 +1880471 AL512791.1 chr14 90402523 90405235 +1880475 LINC02317 chr14 90452063 90455127 +1880484 LINC00642 chr14 90453571 90490763 +1880570 AL096869.3 chr14 90489010 90491637 +1880578 TTC7B chr14 90524564 90816479 +1880786 AL096869.1 chr14 90567495 90569976 +1880790 AL096869.2 chr14 90642638 90648894 +1880804 AL139193.1 chr14 90675118 90676294 +1880808 AL139193.2 chr14 90697333 90699374 +1880812 AL122020.2 chr14 90758599 90760061 +1880816 LINC02321 chr14 90820064 90828199 +1880828 RPS6KA5 chr14 90847861 91060641 +1881053 DGLUCY chr14 91060333 91225632 +1881776 GPR68 chr14 91232532 91253925 +1881815 AL135818.1 chr14 91242759 91252211 +1881830 AL135818.2 chr14 91258299 91259003 +1881833 AL135818.3 chr14 91264903 91266666 +1881837 CCDC88C chr14 91271323 91417844 +1882005 AL133153.2 chr14 91418266 91421176 +1882009 PPP4R3A chr14 91457611 91510554 +1882236 CATSPERB chr14 91580696 91780707 +1882379 AL121839.2 chr14 91752856 91759798 +1882382 TC2N chr14 91779746 91867536 +1882518 FBLN5 chr14 91869412 91947987 +1882659 TRIP11 chr14 91965991 92040896 +1882776 ATXN3 chr14 92044496 92106621 +1883765 NDUFB1 chr14 92116122 92121917 +1883829 CPSF2 chr14 92121969 92172145 +1883905 AL133240.1 chr14 92253493 92263656 +1883909 AL133240.2 chr14 92294771 92297648 +1883913 SLC24A4 chr14 92322581 92501483 +1884107 RIN3 chr14 92513781 92688994 +1884236 LGMN chr14 92703807 92748679 +1884538 GOLGA5 chr14 92794305 92839947 +1884582 LINC02833 chr14 92886352 92893508 +1884598 LINC02287 chr14 92905697 92907482 +1884602 CHGA chr14 92923150 92935285 +1884671 ITPK1 chr14 92936914 93116320 +1884870 ITPK1-AS1 chr14 93067452 93072152 +1884873 MOAP1 chr14 93182199 93184923 +1884894 TMEM251 chr14 93184951 93187089 +1884913 GON7 chr14 93202894 93207065 +1884930 UBR7 chr14 93207241 93229215 +1885048 BTBD7 chr14 93237550 93333092 +1885173 UNC79 chr14 93333219 93707876 +1885696 AL122023.1 chr14 93334528 93335057 +1885699 COX8C chr14 93347182 93348356 +1885709 PRIMA1 chr14 93718298 93788485 +1885770 FAM181A-AS1 chr14 93904730 93927066 +1885795 FAM181A chr14 93918894 93929608 +1885841 ASB2 chr14 93934166 93976739 +1885949 AL132642.1 chr14 93939497 93944194 +1885962 CCDC197 chr14 93987225 94008863 +1886055 OTUB2 chr14 94026340 94048930 +1886084 DDX24 chr14 94048287 94081212 +1886242 IFI27L1 chr14 94081301 94103846 +1886401 IFI27 chr14 94104836 94116698 +1886564 IFI27L2 chr14 94127779 94130253 +1886604 PPP4R4 chr14 94146128 94279734 +1886722 SERPINA10 chr14 94280460 94293268 +1886781 SERPINA6 chr14 94304248 94323389 +1886819 SERPINA1 chr14 94376747 94390693 +1887061 AL132708.1 chr14 94430633 94464730 +1887066 SERPINA11 chr14 94442464 94452800 +1887082 SERPINA9 chr14 94462717 94479689 +1887191 SERPINA12 chr14 94487274 94517844 +1887224 AL132990.1 chr14 94545310 94547762 +1887228 SERPINA4 chr14 94561442 94569913 +1887274 SERPINA5 chr14 94561442 94593118 +1887402 AL049839.3 chr14 94599460 94607839 +1887406 SERPINA3 chr14 94612377 94624055 +1887496 GSC chr14 94768216 94770230 +1887508 AL121612.2 chr14 94770271 94774858 +1887511 AL121612.1 chr14 94918253 94918734 +1887514 LINC02279 chr14 94960277 94962976 +1887521 AL390254.1 chr14 95047353 95050957 +1887526 DICER1 chr14 95086228 95158010 +1887917 DICER1-AS1 chr14 95157645 95181475 +1887945 CLMN chr14 95181940 95319908 +1888056 AL356017.1 chr14 95185117 95185854 +1888060 LINC02292 chr14 95319483 95335757 +1888106 SYNE3 chr14 95407266 95475836 +1888251 AL133467.1 chr14 95516136 95517911 +1888255 SNHG10 chr14 95521943 95534889 +1888291 GLRX5 chr14 95533503 95544724 +1888311 LINC02318 chr14 95573520 95582305 +1888387 AL133467.2 chr14 95620914 95643285 +1888412 AL133467.4 chr14 95644508 95645232 +1888415 TCL6 chr14 95650498 95679833 +1888491 TCL1B chr14 95686426 95692628 +1888513 TCL1A chr14 95709947 95714196 +1888619 AL139020.1 chr14 95711747 95757656 +1888632 AL133167.1 chr14 95828763 95866486 +1888645 TUNAR chr14 95876392 95925571 +1888675 C14orf132 chr14 96039324 96093889 +1888718 BDKRB2 chr14 96204679 96244166 +1888754 AL355102.1 chr14 96210860 96214818 +1888758 AL355102.5 chr14 96233431 96234101 +1888762 BDKRB1 chr14 96256210 96268967 +1888799 AL355102.4 chr14 96259411 96268624 +1888803 AL355102.3 chr14 96275046 96276723 +1888808 ATG2B chr14 96279195 96363341 +1888932 GSKIP chr14 96363452 96387288 +1889006 AK7 chr14 96392128 96489427 +1889076 AL163051.1 chr14 96500810 96502321 +1889079 PAPOLA chr14 96501433 96567111 +1889419 AL137786.1 chr14 96592399 96605974 +1889509 AL137786.2 chr14 96663791 96681827 +1889514 LINC02299 chr14 96738021 96793084 +1889537 AL137786.3 chr14 96749695 96755556 +1889541 VRK1 chr14 96797382 96931722 +1889625 LINC00618 chr14 96931367 96945394 +1889634 AL049833.4 chr14 97005592 97007624 +1889638 AL049833.2 chr14 97110416 97119247 +1889647 AL049833.1 chr14 97116355 97121501 +1889653 LINC02304 chr14 97154857 97158736 +1889657 AL158800.1 chr14 97180525 97217778 +1889667 LINC02325 chr14 97427071 97582146 +1889724 LINC02291 chr14 97632647 97686658 +1889739 AL163872.1 chr14 97662638 97688600 +1889747 LINC02312 chr14 97749264 97763989 +1889754 AL355097.1 chr14 97786565 97789256 +1889758 LINC01550 chr14 97924637 97978124 +1889791 AL163932.1 chr14 98068161 98205143 +1889801 LINC02295 chr14 98136074 98139242 +1889805 AL132719.1 chr14 98497132 98514798 +1889810 C14orf177 chr14 98711613 98717766 +1889838 AL132796.1 chr14 98844896 98845597 +1889843 AL132796.2 chr14 98925137 98927805 +1889847 AL162151.3 chr14 98999571 99003545 +1889851 AL162151.1 chr14 99158416 99159669 +1889855 BCL11B chr14 99169287 99272197 +1889889 AL109767.1 chr14 99262948 99264735 +1889894 AL132819.1 chr14 99324799 99332015 +1889898 SETD3 chr14 99397748 99480889 +1890072 CCNK chr14 99481169 99535044 +1890183 CCDC85C chr14 99500190 99604207 +1890285 AL110504.1 chr14 99512501 99513576 +1890289 AL160313.1 chr14 99604556 99625740 +1890293 HHIPL1 chr14 99645110 99680569 +1890338 CYP46A1 chr14 99684298 99727301 +1890477 AL160313.2 chr14 99691445 99693648 +1890482 EML1 chr14 99737693 99942060 +1890880 EVL chr14 99971449 100144236 +1891181 AL133368.2 chr14 99977115 99978098 +1891185 AL157912.1 chr14 100052803 100074878 +1891189 DEGS2 chr14 100143957 100159645 +1891213 AL133523.1 chr14 100207407 100238555 +1891217 YY1 chr14 100238298 100282788 +1891280 AL157871.5 chr14 100263781 100265405 +1891284 AL157871.6 chr14 100279959 100291456 +1891288 SLC25A29 chr14 100291116 100306547 +1891445 AL157871.1 chr14 100291117 100294656 +1891452 SLC25A47 chr14 100323339 100330421 +1891487 AL157871.4 chr14 100333790 100354061 +1891491 WARS chr14 100333790 100376805 +1892056 AL157871.2 chr14 100339832 100340554 +1892060 WDR25 chr14 100376418 100530303 +1892191 AL135838.1 chr14 100406599 100408928 +1892201 BEGAIN chr14 100537147 100587413 +1892370 AL845552.2 chr14 100538939 100540409 +1892374 AL163974.1 chr14 100587775 100589326 +1892378 LINC00523 chr14 100657250 100676069 +1892418 AL132711.1 chr14 100675930 100679884 +1892422 DLK1 chr14 100725705 100738224 +1892484 MEG3 chr14 100779410 100861031 +1892825 AL117190.2 chr14 100834432 100861026 +1892829 RTL1 chr14 100879753 100903722 +1892850 MEG8 chr14 100894770 101038859 +1893461 MIR381HG chr14 101045157 101051795 +1893466 MEG9 chr14 101068283 101072937 +1893482 AL132709.7 chr14 101071978 101077910 +1893518 AL132709.8 chr14 101120514 101121309 +1893522 LINC02285 chr14 101120840 101123545 +1893526 AL355836.2 chr14 101133730 101151988 +1893533 AL355836.4 chr14 101160476 101172549 +1893538 AL355836.3 chr14 101185787 101197089 +1893546 AL359682.1 chr14 101257332 101278318 +1893550 AL355096.1 chr14 101332511 101335497 +1893559 LINC00524 chr14 101405984 101408258 +1893570 LINC02314 chr14 101442076 101444315 +1893574 AL049836.2 chr14 101447642 101457117 +1893579 DIO3OS chr14 101552221 101560431 +1893622 DIO3 chr14 101561351 101563452 +1893631 AL049836.1 chr14 101628984 101632530 +1893635 LINC02320 chr14 101634454 101731108 +1893640 LINC00239 chr14 101730437 101732522 +1893646 PPP2R5C chr14 101761798 101927989 +1894091 AL137779.2 chr14 101796555 101810321 +1894095 AL137779.1 chr14 101833435 101839531 +1894099 AL118558.3 chr14 101948347 101949425 +1894102 AL118558.4 chr14 101952416 101953063 +1894105 DYNC1H1 chr14 101964573 102056443 +1894992 HSP90AA1 chr14 102080738 102139699 +1895107 WDR20 chr14 102139503 102224847 +1895283 MOK chr14 102224500 102305190 +1895776 ZNF839 chr14 102317377 102342702 +1895951 CINP chr14 102341102 102362916 +1896054 TECPR2 chr14 102362941 102502477 +1896164 ANKRD9 chr14 102501767 102509799 +1896216 LINC02323 chr14 102545254 102555826 +1896221 RCOR1 chr14 102592649 102730561 +1896266 AL132801.1 chr14 102770040 102774791 +1896273 TRAF3 chr14 102777476 102911500 +1896453 AMN chr14 102922656 102933596 +1896528 CDC42BPB chr14 102932380 103057549 +1896672 AL117209.1 chr14 102933574 102937177 +1896676 LBHD2 chr14 103084210 103090027 +1896690 AL161669.1 chr14 103094723 103098885 +1896694 EXOC3L4 chr14 103100144 103110559 +1896775 LINC00677 chr14 103120847 103123007 +1896782 TNFAIP2 chr14 103123442 103137439 +1896957 LINC00605 chr14 103187221 103189028 +1896962 AL161669.3 chr14 103208100 103208876 +1896965 AL138976.2 chr14 103331674 103332367 +1896968 EIF5 chr14 103333544 103345025 +1897175 MARK3 chr14 103385392 103503831 +1897608 CKB chr14 103519667 103522833 +1897741 AL133367.1 chr14 103525010 103529072 +1897744 TRMT61A chr14 103529196 103537073 +1897767 AL139300.2 chr14 103553421 103561877 +1897771 BAG5 chr14 103556544 103562831 +1897806 KLC1 chr14 103561896 103714249 +1898450 COA8 chr14 103562962 103607523 +1898622 AL049840.2 chr14 103682362 103684015 +1898626 AL049840.6 chr14 103687576 103688127 +1898629 AL049840.3 chr14 103694516 103695050 +1898632 AL049840.4 chr14 103694560 103695170 +1898635 AL049840.5 chr14 103696353 103697163 +1898638 XRCC3 chr14 103697609 103715504 +1898871 ZFYVE21 chr14 103715730 103733668 +1898977 PPP1R13B chr14 103733195 103847575 +1899201 LINC00637 chr14 103847721 103858049 +1899206 AL132712.1 chr14 103854366 103880111 +1899212 AL132712.2 chr14 103873148 103880381 +1899233 ATP5MPL chr14 103912288 103928269 +1899341 TDRD9 chr14 103928456 104052667 +1899568 RD3L chr14 103940426 103942561 +1899583 ASPG chr14 104085686 104115582 +1899705 AL359399.1 chr14 104137150 104137898 +1899709 KIF26A chr14 104138723 104180894 +1899777 LINC02691 chr14 104223584 104288069 +1899791 AL512357.2 chr14 104293678 104294921 +1899797 AL512357.1 chr14 104376530 104378951 +1899802 TMEM179 chr14 104474678 104605647 +1899864 C14orf180 chr14 104579684 104590515 +1899910 BX927359.1 chr14 104589021 104589847 +1899914 AL583722.3 chr14 104653548 104655787 +1899921 LINC02280 chr14 104661120 104665558 +1899925 AL583722.1 chr14 104681146 104684932 +1899929 INF2 chr14 104689606 104722535 +1900137 AL583722.4 chr14 104690091 104691284 +1900141 ADSSL1 chr14 104724186 104747325 +1900294 SIVA1 chr14 104753147 104768494 +1900377 AL583722.2 chr14 104769349 104770271 +1900381 AKT1 chr14 104769349 104795751 +1900720 ZBTB42 chr14 104800596 104804712 +1900737 LINC00638 chr14 104821201 104823718 +1900740 AL583810.2 chr14 104842663 104845916 +1900743 AL583810.1 chr14 104857792 104858836 +1900746 CEP170B chr14 104865268 104896770 +1900878 AL583810.3 chr14 104904342 104905204 +1900883 PLD4 chr14 104924713 104937790 +1900997 AHNAK2 chr14 104937244 104978374 +1901038 CLBA1 chr14 104985775 105010482 +1901136 CDCA4 chr14 105009573 105021083 +1901157 GPR132 chr14 105049395 105065445 +1901218 LINC02298 chr14 105093609 105100131 +1901240 AL512356.4 chr14 105095045 105096945 +1901244 AL512356.5 chr14 105126750 105136974 +1901248 JAG2 chr14 105140982 105168824 +1901381 NUDT14 chr14 105172938 105181323 +1901431 BRF1 chr14 105209286 105315589 +1901848 BTBD6 chr14 105248490 105251093 +1901919 PACS2 chr14 105300563 105398147 +1902208 TEX22 chr14 105398538 105450106 +1902239 AL928654.1 chr14 105416884 105419739 +1902255 MTA1 chr14 105419820 105470729 +1902631 AL928654.2 chr14 105467793 105470617 +1902635 CRIP2 chr14 105472962 105480170 +1902755 CRIP1 chr14 105486317 105488947 +1902817 TEDC1 chr14 105489855 105499575 +1903102 TMEM121 chr14 105526583 105530202 +1903124 IGHA2 chr14 105583731 105588395 +1903147 IGHE chr14 105597691 105601728 +1903174 IGHG4 chr14 105620506 105626066 +1903201 IGHG2 chr14 105639559 105644790 +1903228 COPDA1 chr14 105647924 105649057 +1903233 IGHGP chr14 105664633 105669843 +1903241 IGHA1 chr14 105703995 105708665 +1903264 IGHEP1 chr14 105721794 105722527 +1903268 IGHG1 chr14 105736343 105743071 +1903308 IGHG3 chr14 105764503 105771405 +1903347 IGHD chr14 105836765 105845678 +1903380 IGHM chr14 105851705 105856218 +1903407 IGHJ6 chr14 105863198 105863258 +1903411 IGHJ3P chr14 105863416 105863465 +1903414 IGHJ5 chr14 105863814 105863862 +1903418 IGHJ4 chr14 105864215 105864260 +1903422 IGHJ3 chr14 105864587 105864635 +1903426 IGHJ2P chr14 105864793 105864852 +1903429 IGHJ2 chr14 105865199 105865250 +1903433 IGHJ1 chr14 105865407 105865458 +1903437 IGHD7-27 chr14 105865551 105865561 +1903441 IGHJ1P chr14 105865624 105865678 +1903444 IGHD1-26 chr14 105881034 105881053 +1903448 IGHD6-25 chr14 105881539 105881556 +1903452 IGHD5-24 chr14 105883903 105883922 +1903456 IGHD4-23 chr14 105884870 105884888 +1903460 IGHD3-22 chr14 105886031 105886061 +1903464 IGHD2-21 chr14 105888551 105888578 +1903468 AC246787.2 chr14 105890084 105896577 +1903477 IGHD1-20 chr14 105891191 105891207 +1903481 IGHD6-19 chr14 105891699 105891719 +1903485 IGHD5-18 chr14 105893542 105893561 +1903489 IGHD4-17 chr14 105894508 105894523 +1903493 IGHD3-16 chr14 105895634 105895670 +1903497 IGHD2-15 chr14 105897957 105897987 +1903501 IGHD1-14 chr14 105900638 105900654 +1903505 IGHD6-13 chr14 105901142 105901162 +1903509 IGHD5-12 chr14 105902649 105902671 +1903513 IGHD4-11 chr14 105903616 105903631 +1903517 IGHD3-10 chr14 105904497 105904527 +1903523 IGHD3-9 chr14 105904681 105904711 +1903529 IGHD2-8 chr14 105907211 105907241 +1903533 IGHD1-7 chr14 105909907 105909923 +1903537 IGHD6-6 chr14 105910410 105910427 +1903541 IGHD5-5 chr14 105912257 105912276 +1903545 IGHD4-4 chr14 105913222 105913237 +1903549 IGHD3-3 chr14 105914359 105914389 +1903553 IGHD2-2 chr14 105916826 105916856 +1903557 FAM30A chr14 105917979 105932642 +1903586 IGHD1-1 chr14 105919502 105919518 +1903590 IGHV6-1 chr14 105939756 105940253 +1903598 IGHVII-1-1 chr14 105945210 105945389 +1903601 IGHV1-2 chr14 105986582 105987083 +1903609 IGHVIII-2-1 chr14 106001534 106001824 +1903612 IGHV1-3 chr14 106005095 106005574 +1903620 IGHV4-4 chr14 106011922 106012420 +1903628 IGHV7-4-1 chr14 106025145 106025630 +1903636 IGHV2-5 chr14 106037902 106038365 +1903644 IGHVIII-5-1 chr14 106039666 106039764 +1903647 IGHVIII-5-2 chr14 106045600 106045860 +1903650 IGHV3-6 chr14 106055549 106055998 +1903654 IGHV3-7 chr14 106062151 106062683 +1903662 IGHV3-64D chr14 106088122 106088573 +1903669 IGHV5-10-1 chr14 106107972 106108464 +1903677 IGHV3-11 chr14 106116635 106117204 +1903685 IGHVIII-11-1 chr14 106120207 106120473 +1903688 IGHV1-12 chr14 106122420 106122709 +1903692 IGHV3-13 chr14 106129540 106130072 +1903700 IGHVIII-13-1 chr14 106142287 106142577 +1903703 IGHV1-14 chr14 106145891 106146131 +1903706 IGHV3-15 chr14 106153624 106154163 +1903714 IGHVII-15-1 chr14 106163583 106163802 +1903717 IGHV3-16 chr14 106165205 106165730 +1903725 IGHVIII-16-1 chr14 106170749 106171052 +1903728 IGHV1-17 chr14 106174342 106174760 +1903732 IGHV1-18 chr14 106184901 106185394 +1903740 IGHV3-19 chr14 106196700 106196990 +1903743 AC247036.1 chr14 106206603 106208571 +1903747 IGHV3-20 chr14 106210936 106211453 +1903755 IGHV3-21 chr14 106235064 106235594 +1903763 IGHV3-22 chr14 106257762 106258223 +1903767 IGHVII-22-1 chr14 106263362 106263626 +1903770 IGHVIII-22-2 chr14 106264688 106264715 +1903773 IGHV3-23 chr14 106268606 106269140 +1903781 IGHV1-24 chr14 106276548 106277043 +1903789 LINC00226 chr14 106287674 106288828 +1903796 IGHV3-25 chr14 106289029 106289479 +1903800 IGHVIII-25-1 chr14 106293568 106293808 +1903803 IGHV2-26 chr14 106301396 106301862 +1903811 IGHVIII-26-1 chr14 106309417 106309666 +1903814 IGHVII-26-2 chr14 106314651 106314975 +1903817 IGHV7-27 chr14 106317823 106318236 +1903821 IGHV4-28 chr14 106324254 106324760 +1903829 IGHVII-28-1 chr14 106329432 106329684 +1903832 IGHV3-32 chr14 106331106 106331563 +1903836 IGHV3-30 chr14 106335082 106335613 +1903844 IGHVII-30-1 chr14 106342680 106342980 +1903847 IGHV3-30-2 chr14 106344385 106344833 +1903851 IGHV4-31 chr14 106349283 106349792 +1903859 IGHVII-30-21 chr14 106354448 106354704 +1903862 IGHV3-29 chr14 106356145 106356591 +1903866 IGHV3-33 chr14 106359793 106360324 +1903874 IGHVII-33-1 chr14 106367385 106367664 +1903877 IGHV3-33-2 chr14 106369107 106369546 +1903881 IGHV4-34 chr14 106373663 106374145 +1903889 IGHV7-34-1 chr14 106377300 106377733 +1903893 IGHV3-35 chr14 106389392 106389858 +1903901 IGHV3-36 chr14 106392774 106393231 +1903905 IGHV3-37 chr14 106396676 106397114 +1903909 IGHV3-38 chr14 106410493 106411021 +1903917 IGHVIII-38-1 chr14 106418018 106418299 +1903920 IGHV4-39 chr14 106421711 106422218 +1903928 IGHV7-40 chr14 106425359 106425654 +1903931 IGHVII-40-1 chr14 106440950 106441007 +1903934 IGHV3-41 chr14 106443133 106443583 +1903938 IGHV3-42 chr14 106463256 106463691 +1903942 IGHV3-43 chr14 106470264 106470800 +1903950 IGHVII-43-1 chr14 106472791 106473000 +1903953 IGHVIII-44 chr14 106478006 106478393 +1903957 AC244452.3 chr14 106481424 106481706 +1903960 LINC00221 chr14 106482435 106521073 +1903980 IGHVIV-44-1 chr14 106489345 106489756 +1903984 IGHVII-44-2 chr14 106494134 106494383 +1903987 IGHV1-45 chr14 106506996 106507491 +1903995 IGHV1-46 chr14 106511117 106511856 +1904003 IGHVII-46-1 chr14 106515818 106515854 +1904006 IGHV3-47 chr14 106518582 106519027 +1904010 IGHVIII-47-1 chr14 106531141 106531471 +1904013 IGHV3-48 chr14 106537810 106538344 +1904021 IGHV3-49 chr14 106556936 106557477 +1904029 IGHVII-49-1 chr14 106564375 106564598 +1904032 IGHV3-50 chr14 106566117 106566555 +1904036 IGHV5-51 chr14 106578744 106579236 +1904044 IGHVIII-51-1 chr14 106583506 106583807 +1904047 IGHVII-51-2 chr14 106584718 106584976 +1904050 IGHV3-52 chr14 106586376 106586826 +1904054 IGHV3-53 chr14 106592676 106593347 +1904062 IGHVII-53-1 chr14 106599670 106599924 +1904065 IGHV3-54 chr14 106601346 106601792 +1904069 IGHV4-55 chr14 106606101 106606551 +1904073 IGHV7-56 chr14 106609762 106610196 +1904077 IGHV3-57 chr14 106618894 106619173 +1904080 IGHV1-58 chr14 106622357 106622855 +1904088 IGHV4-59 chr14 106627249 106627825 +1904096 IGHV3-60 chr14 106631197 106631653 +1904100 IGHVII-60-1 chr14 106637718 106637973 +1904103 IGHV4-61 chr14 106639119 106639657 +1904111 IGHV3-62 chr14 106643142 106643585 +1904115 IGHVII-62-1 chr14 106650551 106650785 +1904118 IGHV3-63 chr14 106652237 106652681 +1904122 IGHV3-64 chr14 106657725 106658258 +1904130 IGHV3-65 chr14 106666092 106666532 +1904134 IGHVII-65-1 chr14 106671772 106672073 +1904137 IGHV3-66 chr14 106675017 106675544 +1904145 IGHV1-67 chr14 106680603 106681042 +1904149 IGHVII-67-1 chr14 106686517 106686562 +1904152 IGHVIII-67-2 chr14 106687113 106687200 +1904155 IGHVIII-67-3 chr14 106692657 106692888 +1904158 IGHVIII-67-4 chr14 106695102 106695397 +1904161 IGHV1-68 chr14 106703846 106704286 +1904165 IGHV1-69 chr14 106714684 106715181 +1904173 IGHV2-70D chr14 106723574 106724093 +1904181 IGHV3-69-1 chr14 106728163 106728615 +1904185 IGHV1-69-2 chr14 106737110 106737547 +1904192 IGHV1-69D chr14 106762092 106762588 +1904200 IGHV2-70 chr14 106770577 106771020 +1904207 IGHV3-71 chr14 106775157 106775618 +1904211 IGHV3-72 chr14 106790691 106791233 +1904222 IGHV3-73 chr14 106802694 106803233 +1904230 IGHV3-74 chr14 106810442 106811131 +1904238 IGHVII-74-1 chr14 106821174 106821414 +1904241 IGHV3-75 chr14 106823687 106824147 +1904245 IGHV3-76 chr14 106827869 106828163 +1904248 IGHVIII-76-1 chr14 106831767 106832052 +1904251 IGHV5-78 chr14 106851123 106851417 +1904254 IGHVII-78-1 chr14 106865627 106865895 +1904257 IGHV3-79 chr14 106867660 106868092 +1904261 IGHV4-80 chr14 106872783 106873186 +1904265 IGHV7-81 chr14 106874583 106875071 +1904273 IGHVIII-82 chr14 106879563 106879812 +1904276 IGHV1OR15-9 chr15 19964666 19965101 +1904283 IGHV1OR15-2 chr15 19972782 19973218 +1904287 IGHV3OR15-7 chr15 19987656 19988117 +1904294 IGHD5OR15-5A chr15 20003840 20003862 +1904298 IGHD4OR15-4A chr15 20004797 20004815 +1904302 IGHD3OR15-3A chr15 20005905 20005935 +1904306 IGHD2OR15-2A chr15 20008402 20008432 +1904310 IGHD1OR15-1A chr15 20011153 20011169 +1904314 AC087386.1 chr15 20128745 20147953 +1904320 AC026495.2 chr15 20301481 20331583 +1904325 AC026495.1 chr15 20344736 20359166 +1904335 GOLGA6L6 chr15 20531856 20541800 +1904359 IGHV1OR15-6 chr15 20639464 20639890 +1904363 AC023310.4 chr15 20642799 20643448 +1904366 AC012414.5 chr15 20729747 20756183 +1904370 AC012414.3 chr15 20759311 20774794 +1904374 AC012414.4 chr15 20773084 20774871 +1904378 POTEB2 chr15 20835372 20866314 +1904429 LINC01193 chr15 20940380 21058440 +1904601 IGHD5OR15-5B chr15 21010494 21010516 +1904605 IGHD4OR15-4B chr15 21011451 21011469 +1904609 IGHD3OR15-3B chr15 21012559 21012589 +1904613 IGHD2OR15-2B chr15 21015048 21015078 +1904617 IGHD1OR15-1B chr15 21017800 21017816 +1904621 AC126335.1 chr15 21127698 21130095 +1904625 AC068446.2 chr15 21298233 21325241 +1904629 AC060814.5 chr15 21328380 21343881 +1904633 AC060814.4 chr15 21342171 21343958 +1904637 AC060814.3 chr15 21368459 21370621 +1904640 POTEB3 chr15 21408243 21440451 +1904714 AC183088.3 chr15 21514144 21544394 +1904719 LINC02203 chr15 21552815 21557161 +1904724 AC135068.1 chr15 21637909 21638992 +1904732 AC135068.3 chr15 21651844 21652968 +1904740 AC135068.7 chr15 21703428 21705627 +1904744 AC135068.8 chr15 21717808 21718245 +1904751 AC135068.9 chr15 21735506 21735945 +1904755 AC135068.2 chr15 21742364 21742799 +1904762 AC134981.1 chr15 21752278 21752710 +1904766 POTEB chr15 21846329 21877703 +1904831 AC134980.2 chr15 21990074 22059831 +1904867 OR4M2 chr15 22070241 22083221 +1904879 OR4N4 chr15 22094522 22095472 +1904886 AC010760.1 chr15 22145939 22148226 +1904890 IGHV1OR15-1 chr15 22160431 22160868 +1904897 IGHV1OR15-3 chr15 22178107 22178542 +1904901 IGHV4OR15-8 chr15 22184967 22185402 +1904908 IGHV1OR15-4 chr15 22194885 22195317 +1904912 GOLGA6L22 chr15 22458903 22469230 +1904962 AC138649.1 chr15 22757841 22778741 +1904977 NIPA1 chr15 22773063 22829789 +1905066 NIPA2 chr15 22838641 22868384 +1905184 CYFIP1 chr15 22867052 22981063 +1905468 TUBGCP5 chr15 22983192 23039572 +1905673 GOLGA6L1 chr15 23127066 23136822 +1905697 GOLGA8S chr15 23354748 23367231 +1905759 AC100756.4 chr15 23403848 23407335 +1905763 GOLGA6L2 chr15 23439038 23447243 +1905848 MKRN3 chr15 23565674 23630075 +1905909 AC126407.1 chr15 23567264 23569657 +1905913 MAGEL2 chr15 23643549 23647867 +1905921 NDN chr15 23685400 23687305 +1905929 AC087490.1 chr15 23757115 23856375 +1905934 PWRN4 chr15 23912411 24090821 +1905979 PWRN1 chr15 24101827 24823365 +1906446 PWRN2 chr15 24162754 24169948 +1906456 AC087463.1 chr15 24206784 24225854 +1906461 AC087463.2 chr15 24238145 24240192 +1906465 AC087463.3 chr15 24341729 24343464 +1906469 NPAP1 chr15 24675704 24683393 +1906477 SNRPN chr15 24823637 24978723 +1906761 AC090983.1 chr15 24848355 24852253 +1906768 SNURF chr15 24954986 24977850 +1906812 SNHG14 chr15 24978583 25420336 +1909870 AC124312.2 chr15 25027736 25032047 +1909874 AC124312.3 chr15 25087661 25088896 +1909877 AC124312.5 chr15 25091786 25107469 +1909881 UBE3A chr15 25333728 25439051 +1910437 AC100774.1 chr15 25345633 25347235 +1910440 LINC02250 chr15 25456271 25578813 +1910474 ATP10A chr15 25677273 25865172 +1910617 AC023449.2 chr15 25708470 25710869 +1910620 AC016266.1 chr15 25865295 25877211 +1910624 LINC02346 chr15 25902119 26053123 +1910677 AC100836.1 chr15 26050538 26052276 +1910681 LINC00929 chr15 26115726 26134001 +1910812 AC012060.1 chr15 26261669 26265918 +1910816 LINC02248 chr15 26395037 26455217 +1910839 AC009878.2 chr15 26403480 26477840 +1910847 GABRB3 chr15 26543546 26939539 +1911171 AC009878.1 chr15 26557598 26557937 +1911174 AC011196.1 chr15 26657030 26658763 +1911178 GABRA5 chr15 26866911 26949208 +1911343 GABRG3 chr15 26971181 27541984 +1911443 GABRG3-AS1 chr15 27038978 27161319 +1911464 AC144833.1 chr15 27362310 27366398 +1911467 AC104002.1 chr15 27418796 27420735 +1911471 AC104002.2 chr15 27422381 27428338 +1911475 AC104002.3 chr15 27483035 27541991 +1911482 AC021979.1 chr15 27621534 27629289 +1911487 AC021979.3 chr15 27662715 27667273 +1911491 AC021979.2 chr15 27684498 27685768 +1911495 OCA2 chr15 27754875 28099315 +1911632 AC090696.1 chr15 27775621 27776798 +1911636 HERC2 chr15 28111040 28322172 +1912016 GOLGA8F chr15 28378621 28392018 +1912125 GOLGA8G chr15 28519611 28533014 +1912257 GOLGA8M chr15 28701954 28738384 +1912307 GOLGA8M chr15 28719377 28738431 +1912311 GOLGA6L7 chr15 28841833 28848675 +1912342 AC174469.1 chr15 28881667 28884655 +1912346 APBA2 chr15 28884483 29118315 +1912589 AC127522.1 chr15 28970196 28977464 +1912593 FAM189A1 chr15 29120254 29570723 +1912643 NSMCE3 chr15 29264989 29269822 +1912651 AC107980.1 chr15 29373602 29376956 +1912654 AC102941.1 chr15 29609676 29611212 +1912657 AC102941.2 chr15 29664477 29669482 +1912661 AC022613.1 chr15 29674990 29680957 +1912668 TJP1 chr15 29699367 29968865 +1913029 AC022613.3 chr15 29728186 29729531 +1913032 AC022613.2 chr15 29822631 29824081 +1913035 AC111152.2 chr15 30005443 30045848 +1913039 GOLGA8J chr15 30083053 30093499 +1913091 GOLGA8T chr15 30135149 30145567 +1913142 AC120045.1 chr15 30170563 30179943 +1913149 LINC02249 chr15 30195809 30217552 +1913160 CHRFAM7A chr15 30357766 30393849 +1913266 GOLGA8R chr15 30403740 30414162 +1913311 AC127502.2 chr15 30487963 30490313 +1913314 AC026150.1 chr15 30540093 30545969 +1913319 GOLGA8Q chr15 30552078 30562501 +1913366 GOLGA8H chr15 30604126 30614561 +1913409 AC026150.3 chr15 30607695 30608193 +1913412 AC091057.3 chr15 30616958 30617749 +1913415 AC091057.2 chr15 30616998 30625773 +1913419 AC091057.6 chr15 30624494 30649529 +1913466 ARHGAP11B chr15 30624548 30685606 +1913533 FAN1 chr15 30890559 30943108 +1914076 MTMR10 chr15 30938941 30991628 +1914303 AC009562.1 chr15 30992171 31042302 +1914317 TRPM1 chr15 31001061 31161273 +1914723 LINC02352 chr15 31215622 31224445 +1914733 AC012236.1 chr15 31221999 31230838 +1914756 KLF13 chr15 31326835 31435665 +1914795 OTUD7A chr15 31475398 31870789 +1914866 CHRNA7 chr15 31923438 32173018 +1915407 AC139426.2 chr15 32359538 32367784 +1915412 GOLGA8K chr15 32392782 32403292 +1915458 GOLGA8O chr15 32441914 32455634 +1915519 LINC02256 chr15 32536047 32587613 +1915527 AC123768.4 chr15 32583612 32584312 +1915530 AC123768.3 chr15 32585524 32615158 +1915544 GOLGA8N chr15 32593456 32607310 +1915659 AC123768.2 chr15 32613733 32615111 +1915664 ARHGAP11A chr15 32615144 32639941 +1915829 AC123768.5 chr15 32624106 32641615 +1915836 SCG5 chr15 32641676 32697098 +1915930 AC123768.1 chr15 32656084 32673065 +1915940 AC090877.2 chr15 32717270 32719007 +1915946 GREM1 chr15 32718004 32745106 +1915987 FMN1 chr15 32765545 33194733 +1916257 AC055874.1 chr15 33293568 33310659 +1916273 RYR3 chr15 33310945 33866121 +1917711 AC010809.3 chr15 33850538 33851178 +1917714 AC010809.2 chr15 33851785 33856809 +1917719 AC010809.1 chr15 33858602 33864825 +1917723 AVEN chr15 33866227 34039204 +1917758 CHRM5 chr15 33968720 34067457 +1917786 AC009268.2 chr15 33972059 33972515 +1917789 AC009268.3 chr15 33985406 33988268 +1917793 EMC7 chr15 34084017 34101862 +1917836 PGBD4 chr15 34102083 34108686 +1917844 KATNBL1 chr15 34140674 34210096 +1918021 EMC4 chr15 34225013 34230156 +1918152 SLC12A6 chr15 34229784 34338060 +1918884 AC079203.2 chr15 34255286 34257832 +1918888 NOP10 chr15 34341713 34343177 +1918907 NUTM1 chr15 34343315 34357737 +1918988 LPCAT4 chr15 34358633 34367196 +1919098 GOLGA8A chr15 34379068 34437466 +1919205 GOLGA8B chr15 34525207 34588503 +1919369 LINC02252 chr15 34651135 34671095 +1919377 AC100834.2 chr15 34657736 34670512 +1919382 GJD2 chr15 34751032 34754998 +1919392 AC087457.1 chr15 34755084 34813505 +1919407 ACTC1 chr15 34790230 34795549 +1919454 AQR chr15 34851782 34969742 +1919630 ZNF770 chr15 34978341 34988287 +1919649 AC114546.1 chr15 34993646 35003221 +1919653 AC114546.2 chr15 35007844 35011191 +1919660 NANOGP8 chr15 35084193 35085110 +1919675 AC021231.1 chr15 35099022 35169698 +1919679 DPH6 chr15 35217345 35546193 +1919769 DPH6-DT chr15 35546154 35860199 +1919785 LINC02853 chr15 35919892 36049537 +1919795 AC021351.1 chr15 35939167 36252257 +1919813 AC087516.1 chr15 36341739 36344166 +1919816 AC087516.2 chr15 36438972 36471016 +1919834 C15orf41 chr15 36579626 36810248 +1920240 AC013640.1 chr15 36641186 36669097 +1920245 AC018563.1 chr15 36876379 36887035 +1920258 MEIS2 chr15 36889204 37101299 +1920712 AC078909.1 chr15 37099339 37100173 +1920716 AC078909.2 chr15 37109587 37109984 +1920719 AC068875.1 chr15 37364020 37490864 +1920740 TMCO5A chr15 37921939 37967724 +1920899 LINC02345 chr15 37980676 38062340 +1920928 LINC01852 chr15 38068812 38072990 +1920943 AC087473.1 chr15 38139595 38226897 +1920961 SPRED1 chr15 38252836 38357249 +1921002 FAM98B chr15 38454127 38487710 +1921056 RASGRP1 chr15 38488103 38565575 +1921410 AC116158.3 chr15 38493308 38499985 +1921414 AC116158.1 chr15 38502853 38504981 +1921417 AC116158.2 chr15 38524070 38534655 +1921422 LINC02694 chr15 38628005 39180499 +1921466 AC022929.1 chr15 38756552 38759413 +1921472 AC022929.2 chr15 38851306 38853432 +1921475 AC013652.1 chr15 38865322 39427195 +1921517 AC087878.1 chr15 39019193 39026521 +1921526 AC113146.1 chr15 39167676 39180048 +1921543 C15orf54 chr15 39250684 39254845 +1921550 AC013652.2 chr15 39300418 39310782 +1921558 AC109630.1 chr15 39472703 39497074 +1921666 AC022196.1 chr15 39512335 39519954 +1921677 THBS1 chr15 39581079 39599466 +1921758 AC037198.1 chr15 39586561 39587293 +1921761 AC037198.2 chr15 39588357 39588882 +1921764 FSIP1 chr15 39588357 39782841 +1921825 AC023908.3 chr15 39782571 39785617 +1921828 GPR176 chr15 39799032 39920892 +1921875 AC023908.1 chr15 39813223 39815429 +1921880 GPR176-DT chr15 39921042 39925880 +1921886 EIF2AK4 chr15 39934115 40035591 +1922145 SRP14 chr15 40035690 40039181 +1922222 SRP14-AS1 chr15 40039242 40076539 +1922264 AC021755.2 chr15 40075204 40078704 +1922268 AC021755.3 chr15 40078892 40079347 +1922271 BMF chr15 40087890 40108892 +1922383 BMF-AS1 chr15 40088832 40089386 +1922387 BUB1B chr15 40161023 40221136 +1922555 PAK6 chr15 40217428 40277487 +1922860 AC020658.4 chr15 40226386 40227069 +1922863 AC020658.3 chr15 40232082 40236109 +1922866 C15orf56 chr15 40250664 40252969 +1922872 PLCB2 chr15 40278176 40307935 +1923188 ANKRD63 chr15 40281444 40282586 +1923195 AC020658.5 chr15 40285468 40285909 +1923198 PLCB2-AS1 chr15 40300670 40301820 +1923202 AC020658.2 chr15 40312615 40316634 +1923205 INAFM2 chr15 40323692 40326715 +1923216 CCDC9B chr15 40331452 40340967 +1923308 PHGR1 chr15 40351033 40356434 +1923325 DISP2 chr15 40358219 40378621 +1923356 AC013356.4 chr15 40368925 40369640 +1923360 KNSTRN chr15 40382721 40394246 +1923602 IVD chr15 40405485 40435947 +1923839 BAHD1 chr15 40439721 40468236 +1923897 AC013356.3 chr15 40453444 40454639 +1923902 AC013356.2 chr15 40464193 40466726 +1923907 CHST14 chr15 40470998 40474571 +1923924 AC091045.1 chr15 40488041 40558019 +1923934 CCDC32 chr15 40528683 40565057 +1924107 RPUSD2 chr15 40569299 40574949 +1924135 KNL1 chr15 40594020 40664342 +1924407 AC022405.1 chr15 40642933 40646857 +1924411 RAD51-AS1 chr15 40686183 40695107 +1924431 RAD51 chr15 40694774 40732340 +1924653 RMDN3 chr15 40735884 40755851 +1924825 GCHFR chr15 40764068 40767708 +1924886 DNAJC17 chr15 40765161 40807478 +1925077 C15orf62 chr15 40769980 40772449 +1925085 ZFYVE19 chr15 40807086 40815084 +1925355 PPP1R14D chr15 40815445 40828709 +1925384 SPINT1-AS1 chr15 40835808 40844387 +1925403 SPINT1 chr15 40844018 40858207 +1925559 RHOV chr15 40872214 40874234 +1925571 AC025166.1 chr15 40874433 40874595 +1925574 VPS18 chr15 40894450 40903975 +1925618 AC020661.1 chr15 40906811 40910337 +1925626 DLL4 chr15 40929340 40939073 +1925663 CHAC1 chr15 40952962 40956512 +1925697 INO80 chr15 40978880 41116280 +1926081 AC020661.3 chr15 40999274 41004865 +1926085 AC020661.2 chr15 41011597 41013300 +1926089 INO80-AS1 chr15 41016807 41027893 +1926098 AC020661.4 chr15 41016990 41018843 +1926101 EXD1 chr15 41182725 41230743 +1926175 CHP1 chr15 41230839 41281887 +1926296 OIP5-AS1 chr15 41283990 41309737 +1926346 OIP5 chr15 41309273 41332591 +1926371 NUSAP1 chr15 41320794 41381050 +1926628 AC087721.1 chr15 41343080 41344225 +1926632 NDUFAF1 chr15 41387353 41402519 +1926681 RTF1 chr15 41408408 41483563 +1926761 ITPKA chr15 41493393 41503551 +1926807 LTK chr15 41503637 41513887 +1926996 RPAP1 chr15 41517176 41544269 +1927218 TYRO3 chr15 41557675 41583589 +1927363 AC016134.1 chr15 41609457 41630908 +1927414 MGA chr15 41621224 41773081 +1927709 AC073657.1 chr15 41770756 41772732 +1927716 MAPKBP1 chr15 41774434 41827855 +1928142 AC020659.2 chr15 41825099 41827936 +1928150 JMJD7 chr15 41828092 41837581 +1928220 PLA2G4B chr15 41837775 41848147 +1928348 SPTBN5 chr15 41848146 41894053 +1928493 AC020659.1 chr15 41892777 41899528 +1928539 EHD4 chr15 41895933 41972557 +1928561 AC039056.2 chr15 41908204 41908714 +1928564 EHD4-AS1 chr15 41921417 41929286 +1928570 PLA2G4E-AS1 chr15 41972763 41999094 +1928576 PLA2G4E chr15 41981582 42051190 +1928638 AC039056.1 chr15 42006132 42010117 +1928643 PLA2G4D chr15 42067009 42094562 +1928700 PLA2G4F chr15 42139034 42156636 +1928880 VPS39 chr15 42158701 42208316 +1929051 AC036103.1 chr15 42208413 42226990 +1929062 TMEM87A chr15 42210447 42273584 +1929331 GANC chr15 42273233 42356935 +1929527 CAPN3 chr15 42359500 42412318 +1930047 ZNF106 chr15 42412823 42491141 +1930331 SNAP23 chr15 42491233 42545356 +1930631 AC018362.1 chr15 42497394 42532840 +1930640 LRRC57 chr15 42537820 42548802 +1930710 HAUS2 chr15 42548828 42569994 +1930875 AC018362.2 chr15 42567031 42569994 +1930882 STARD9 chr15 42575606 42720998 +1931031 CDAN1 chr15 42723544 42737128 +1931192 AC090510.3 chr15 42724102 42724922 +1931195 AC090510.2 chr15 42726583 42727211 +1931198 TTBK2 chr15 42738730 42920809 +1931374 AC090510.1 chr15 42739118 42743202 +1931382 AC090510.4 chr15 42749081 42749936 +1931386 UBR1 chr15 42942897 43106113 +1931663 AC068724.3 chr15 43106225 43185779 +1931671 TMEM62 chr15 43123279 43185144 +1931847 AC068724.1 chr15 43184079 43185141 +1931851 CCNDBP1 chr15 43185118 43197177 +1932086 EPB42 chr15 43197227 43221125 +1932234 TGM5 chr15 43232590 43266928 +1932396 TGM7 chr15 43276271 43302255 +1932431 AC009852.1 chr15 43302096 43302772 +1932435 LCMT2 chr15 43323649 43330582 +1932452 ADAL chr15 43330657 43354555 +1932611 ZSCAN29 chr15 43358172 43371025 +1932704 TUBGCP4 chr15 43369221 43409771 +1932907 TP53BP1 chr15 43403061 43510728 +1933315 MAP1A chr15 43510958 43531620 +1933352 PPIP5K1 chr15 43533462 43590253 +1934045 CKMT1B chr15 43593054 43604901 +1934220 STRC chr15 43599563 43618800 +1934567 CATSPER2 chr15 43628503 43668118 +1934757 AC011330.2 chr15 43642389 43643023 +1934760 CKMT1A chr15 43692886 43699222 +1934870 PDIA3 chr15 43746410 43773278 +1934971 ELL3 chr15 43772605 43777315 +1935052 SERF2 chr15 43777087 43802589 +1935234 SERINC4 chr15 43794162 43800221 +1935358 HYPK chr15 43796142 43803043 +1935402 MFAP1 chr15 43804492 43824690 +1935430 WDR76 chr15 43826980 43868412 +1935515 FRMD5 chr15 43870761 44195271 +1935820 CASC4 chr15 44288719 44415758 +1935974 AC090519.2 chr15 44387320 44390451 +1935978 AC025043.1 chr15 44402685 44427144 +1935985 CTDSPL2 chr15 44427622 44529038 +1936145 AC025430.1 chr15 44516650 44517483 +1936149 EIF3J-DT chr15 44527257 44537046 +1936174 EIF3J chr15 44537125 44563029 +1936260 AC009996.1 chr15 44557829 44559188 +1936264 SPG11 chr15 44562696 44663678 +1936759 PATL2 chr15 44665732 44711316 +1936916 B2M chr15 44711487 44718877 +1937031 TRIM69 chr15 44728988 44767829 +1937166 AC122108.2 chr15 44778196 44778721 +1937169 AC122108.1 chr15 44826540 44827094 +1937173 TERB2 chr15 44956687 44979229 +1937225 SORD chr15 45023181 45077185 +1937325 AC091117.2 chr15 45041716 45058707 +1937331 AC091117.1 chr15 45073492 45074048 +1937335 DUOX2 chr15 45092650 45114344 +1937506 DUOXA2 chr15 45114326 45118421 +1937547 DUOXA1 chr15 45117367 45129938 +1937805 DUOX1 chr15 45129933 45165576 +1938122 AC051619.6 chr15 45152664 45167526 +1938126 SHF chr15 45167214 45201175 +1938268 AC051619.4 chr15 45170344 45199958 +1938272 AC051619.7 chr15 45198517 45199139 +1938275 AC051619.8 chr15 45200325 45200632 +1938278 AC051619.5 chr15 45235930 45279251 +1938298 SLC28A2 chr15 45252234 45277846 +1938373 AC051619.11 chr15 45279423 45280474 +1938377 GATM chr15 45361124 45402327 +1938505 AC025580.3 chr15 45378700 45380123 +1938508 SPATA5L1 chr15 45402336 45421415 +1938600 C15orf48 chr15 45430529 45448761 +1938645 AC025580.1 chr15 45430652 45441808 +1938650 AC025580.2 chr15 45448427 45513767 +1938674 SLC30A4 chr15 45479606 45522755 +1938700 AC090527.1 chr15 45558598 45562877 +1938704 AC090527.3 chr15 45585757 45586304 +1938707 BLOC1S6 chr15 45587214 45615945 +1938941 SQOR chr15 45631148 45691281 +1939052 AC068722.2 chr15 45702640 45703183 +1939055 AC068722.1 chr15 45705078 45931069 +1939073 AC091074.3 chr15 46317393 46351753 +1939078 AC091074.2 chr15 46365836 46381043 +1939083 AC012405.1 chr15 46410309 46661103 +1939087 AC073941.1 chr15 46693288 46804844 +1939091 SEMA6D chr15 47184101 47774223 +1939541 AC084882.1 chr15 47274183 47275164 +1939545 AC023905.1 chr15 47359430 47396732 +1939561 AC009558.1 chr15 47397501 47399554 +1939565 AC009558.2 chr15 47525169 47527756 +1939569 AC012050.1 chr15 47603880 47606352 +1939574 LINC01491 chr15 47774219 47846266 +1939684 AC092078.2 chr15 47812729 48050507 +1939705 AC092078.1 chr15 47944044 47949509 +1939709 AC092078.3 chr15 47956521 47988044 +1939714 SLC24A5 chr15 48120990 48142672 +1939774 MYEF2 chr15 48134632 48178353 +1940037 CTXN2 chr15 48178122 48203758 +1940076 SLC12A1 chr15 48178438 48304078 +1940525 AC066612.1 chr15 48187121 48191691 +1940540 AC066612.2 chr15 48192191 48201684 +1940544 AC023355.1 chr15 48312353 48331856 +1940555 DUT chr15 48331011 48343373 +1940719 FBN1 chr15 48408306 48645849 +1941013 AC022467.2 chr15 48524308 48526051 +1941017 AC022467.1 chr15 48528980 48529728 +1941020 AC084757.3 chr15 48645951 48652016 +1941024 AC084757.4 chr15 48662531 48663056 +1941027 CEP152 chr15 48712928 48811146 +1941265 AC084757.2 chr15 48729080 48729844 +1941269 AC012379.1 chr15 48783190 48784121 +1941273 AC012379.2 chr15 48810701 48811909 +1941279 SHC4 chr15 48823741 48963919 +1941392 EID1 chr15 48878134 48880173 +1941409 AC091073.1 chr15 48938236 48948031 +1941415 SECISBP2L chr15 48988476 49046447 +1941583 AC013452.2 chr15 49101791 49103264 +1941587 COPS2 chr15 49106068 49155661 +1941731 GALK2 chr15 49155656 49367869 +1942107 FAM227B chr15 49326962 49620929 +1942296 AC022306.2 chr15 49343608 49344254 +1942299 AC022306.3 chr15 49353485 49354034 +1942302 FGF7 chr15 49423178 49488775 +1942366 DTWD1 chr15 49621037 49656232 +1942491 ATP8B4 chr15 49858238 50182817 +1942890 AC025040.1 chr15 49877299 49883525 +1942903 SLC27A2 chr15 50182196 50236385 +1942983 HDC chr15 50241947 50265965 +1943076 GABPB1 chr15 50275392 50355408 +1943262 GABPB1-IT1 chr15 50348936 50354861 +1943265 GABPB1-AS1 chr15 50354959 50372202 +1943299 AC022087.1 chr15 50359450 50360194 +1943303 USP8 chr15 50424380 50514421 +1943625 AC012170.3 chr15 50494018 50497080 +1943629 AC012170.2 chr15 50497195 50498744 +1943634 USP50 chr15 50500562 50546708 +1943706 TRPM7 chr15 50552473 50686797 +1943951 AC084756.1 chr15 50557601 50560500 +1943956 SPPL2A chr15 50702266 50765709 +1944051 AC012100.2 chr15 50746709 50749829 +1944055 AC021752.1 chr15 50839875 50908603 +1944080 AP4E1 chr15 50908672 51005895 +1944305 MIR4713HG chr15 51037488 51293912 +1944310 TNFAIP8L3 chr15 51056598 51105276 +1944340 AC073964.1 chr15 51064609 51069586 +1944344 CYP19A1 chr15 51208057 51338601 +1944623 AC020891.3 chr15 51278927 51280015 +1944627 AC020891.2 chr15 51315841 51321996 +1944632 GLDN chr15 51341655 51408005 +1944755 AC020891.1 chr15 51367377 51369110 +1944759 AC066613.2 chr15 51414097 51498833 +1944767 DMXL2 chr15 51447711 51622833 +1945146 AC066613.1 chr15 51455268 51460582 +1945161 SCG3 chr15 51681492 51721026 +1945231 AC020892.1 chr15 51693216 51695765 +1945235 AC020892.2 chr15 51707995 51715220 +1945240 LYSMD2 chr15 51723011 51751585 +1945283 TMOD2 chr15 51751597 51816363 +1945379 AC026770.1 chr15 51752485 51756475 +1945383 TMOD3 chr15 51829628 51947295 +1945491 AC090971.5 chr15 51833134 51833426 +1945494 AC090971.2 chr15 51887560 51901123 +1945500 AC090971.1 chr15 51908902 51909642 +1945504 LEO1 chr15 51938025 51971778 +1945562 MAPK6 chr15 51952106 52067375 +1945605 MAPK6-DT chr15 52010999 52019095 +1945609 AC090970.2 chr15 52017167 52018032 +1945612 AC090970.1 chr15 52033707 52035625 +1945616 AC023906.5 chr15 52056675 52100523 +1945620 AC023906.2 chr15 52082302 52086574 +1945625 BCL2L10 chr15 52109263 52112775 +1945644 GNB5 chr15 52115105 52191369 +1945803 AC023906.3 chr15 52116574 52122131 +1945807 AC023906.4 chr15 52124561 52140246 +1945816 CERNA1 chr15 52179999 52206915 +1945828 MYO5C chr15 52192322 52295804 +1946118 MYO5A chr15 52307283 52529050 +1946750 ARPP19 chr15 52547045 52569883 +1946898 AC025917.1 chr15 52577842 52598709 +1946908 FAM214A chr15 52581317 52709817 +1947158 AC009754.1 chr15 52648634 52649866 +1947162 AC009754.2 chr15 52679474 52690077 +1947167 ONECUT1 chr15 52755053 52791078 +1947202 AC016044.1 chr15 52800168 52805972 +1947225 LINC02490 chr15 53116365 53129698 +1947230 AC066614.1 chr15 53419865 53453487 +1947234 WDR72 chr15 53513741 53762878 +1947465 AC084759.2 chr15 53946709 53984010 +1947510 UNC13C chr15 53978201 54633414 +1947698 AC025272.1 chr15 55056723 55092177 +1947708 AC011912.1 chr15 55171378 55176739 +1947711 RSL24D1 chr15 55180806 55197049 +1947769 RAB27A chr15 55202966 55319113 +1947930 AC018926.2 chr15 55288849 55289346 +1947933 PIGBOS1 chr15 55317184 55319161 +1947959 PIGB chr15 55318960 55355648 +1948106 CCPG1 chr15 55340032 55408510 +1948293 AC018926.1 chr15 55343141 55343575 +1948296 AC018926.3 chr15 55346347 55346752 +1948299 C15orf65 chr15 55408495 55418798 +1948312 DNAAF4 chr15 55410525 55508234 +1948445 PYGO1 chr15 55538890 55588947 +1948481 AC012378.2 chr15 55588666 55589811 +1948485 PRTG chr15 55611544 55743152 +1948565 AC012378.1 chr15 55680385 55681463 +1948569 NEDD4 chr15 55826922 55993746 +1949011 RFX7 chr15 56087280 56243266 +1949075 TEX9 chr15 56244009 56445997 +1949225 AC068726.1 chr15 56248787 56249127 +1949228 AC084782.1 chr15 56394321 56396785 +1949231 AC084782.2 chr15 56408483 56410186 +1949235 MNS1 chr15 56421544 56465137 +1949269 AC084782.3 chr15 56447120 56447697 +1949272 AC090518.1 chr15 56542952 56629592 +1949293 ZNF280D chr15 56630181 56734086 +1949557 AC090517.2 chr15 56729932 56730611 +1949560 AC090517.5 chr15 56795460 56918499 +1949583 AC010999.2 chr15 56887107 56888219 +1949587 AC010999.1 chr15 56908312 56908635 +1949590 TCF12 chr15 56918623 57299281 +1950084 LINC00926 chr15 57300365 57307769 +1950098 LINC01413 chr15 57319138 57325039 +1950110 CGNL1 chr15 57375967 57550727 +1950167 AC025271.3 chr15 57477484 57478329 +1950171 AC025271.2 chr15 57527187 57529009 +1950175 AC025271.4 chr15 57553955 57555680 +1950178 MYZAP chr15 57591904 57685364 +1950267 GCOM1 chr15 57591908 57714745 +1950695 POLR2M chr15 57706695 57782762 +1950782 AC090651.1 chr15 57720295 57720928 +1950785 ALDH1A2 chr15 57953424 58497866 +1951085 AC012653.2 chr15 57990217 57990636 +1951088 AC025431.1 chr15 58065225 58071043 +1951093 AQP9 chr15 58138169 58185911 +1951150 LIPC chr15 58410569 58569844 +1951264 LIPC-AS1 chr15 58434890 58498735 +1951269 AC084781.1 chr15 58454327 58454982 +1951272 AC084781.2 chr15 58456188 58456348 +1951275 AC018904.2 chr15 58521311 58523371 +1951279 AC018904.1 chr15 58587507 58591676 +1951283 ADAM10 chr15 58588809 58749791 +1951460 AC090515.6 chr15 58749923 58761004 +1951464 AC090515.2 chr15 58768072 58770974 +1951468 MINDY2 chr15 58771192 58861900 +1951565 AC090515.5 chr15 58815272 58817728 +1951569 AC090515.4 chr15 58856831 58865063 +1951573 RNF111 chr15 58865175 59097419 +1951751 SLTM chr15 58879050 58933679 +1952131 AC025918.1 chr15 58889967 58894082 +1952135 CCNB2 chr15 59105126 59125045 +1952204 AC092757.3 chr15 59115547 59116089 +1952207 AC092757.2 chr15 59121034 59133250 +1952211 MYO1E chr15 59132434 59372871 +1952365 LDHAL6B chr15 59206843 59208588 +1952373 AC092756.1 chr15 59266720 59271162 +1952377 AC092868.2 chr15 59348648 59359889 +1952381 FAM81A chr15 59372693 59523555 +1952531 GCNT3 chr15 59594875 59640239 +1952607 GTF2A2 chr15 59638062 59657541 +1952707 AC092755.1 chr15 59644298 59672302 +1952711 BNIP2 chr15 59659146 59689534 +1952881 AC092755.2 chr15 59688517 59689418 +1952885 AC092079.2 chr15 59801347 59814749 +1952890 FOXB1 chr15 60004234 60061730 +1952908 AC009654.1 chr15 60073554 60118320 +1952913 AC037433.1 chr15 60215537 60223272 +1952918 ANXA2 chr15 60347134 60402883 +1953567 ICE2 chr15 60419609 60479160 +1953808 RORA-AS1 chr15 60479152 60630637 +1953850 RORA chr15 60488284 61229302 +1954021 AC107241.1 chr15 60529973 60545159 +1954025 AC009560.1 chr15 60593027 60593460 +1954028 AC009560.3 chr15 60634503 60640915 +1954034 AC009560.4 chr15 60642054 60659791 +1954040 RORA-AS2 chr15 60681564 60687248 +1954051 AC022898.1 chr15 60763593 60765625 +1954061 AC022898.2 chr15 60847757 60849068 +1954064 AC012404.1 chr15 61181249 61195938 +1954070 AC012404.2 chr15 61211913 61214231 +1954074 AC107905.1 chr15 61239906 61240331 +1954077 AC104574.2 chr15 61298791 61635449 +1954084 AC104574.1 chr15 61598514 61605241 +1954088 AC018618.1 chr15 61638928 61715171 +1954102 LINC02349 chr15 61729765 61731389 +1954113 AC009554.1 chr15 61834682 61935738 +1954124 VPS13C chr15 61852389 62060473 +1954992 AC009554.2 chr15 61861109 61894164 +1954997 AC104590.1 chr15 62060503 62062434 +1955003 C2CD4A chr15 62066977 62070917 +1955013 C2CD4B chr15 62163535 62165285 +1955023 AC126323.2 chr15 62196066 62222911 +1955037 AC126323.3 chr15 62230384 62231895 +1955043 AC126323.6 chr15 62274163 62278365 +1955050 AC126323.5 chr15 62284190 62285006 +1955054 AC032011.1 chr15 62387327 62388875 +1955057 TLN2 chr15 62390526 62844631 +1955398 AC100839.1 chr15 62637172 62645291 +1955407 AC100839.2 chr15 62682916 62690448 +1955413 AC103740.1 chr15 62827675 62884034 +1955430 AC103740.2 chr15 62895812 62899543 +1955434 TPM1 chr15 63042632 63071915 +1956035 TPM1-AS chr15 63046034 63049387 +1956041 AC079328.2 chr15 63070025 63071911 +1956045 AC087612.1 chr15 63091085 63110589 +1956070 LACTB chr15 63121833 63142061 +1956115 RPS27L chr15 63125872 63158021 +1956198 RAB8B chr15 63189560 63267776 +1956302 APH1B chr15 63276018 63309126 +1956410 CA12 chr15 63321378 63381846 +1956497 LINC02568 chr15 63390136 63438320 +1956521 AC007950.1 chr15 63456294 63469356 +1956526 AC007950.2 chr15 63500737 63503083 +1956529 USP3 chr15 63504511 63594640 +1956960 USP3-AS1 chr15 63544247 63601589 +1957030 FBXL22 chr15 63597353 63602428 +1957067 HERC1 chr15 63608618 63833948 +1957348 AC073167.1 chr15 63675146 63713758 +1957354 DAPK2 chr15 63907036 64072033 +1957553 AC015914.1 chr15 63928274 63935953 +1957559 CIAO2A chr15 64072565 64093857 +1957632 SNX1 chr15 64094123 64146090 +1957899 SNX22 chr15 64151715 64157481 +1957966 PPIB chr15 64155812 64163205 +1957990 CSNK1G1 chr15 64165525 64356173 +1958348 PCLAF chr15 64364304 64387687 +1958427 TRIP4 chr15 64387748 64455303 +1958566 ZNF609 chr15 64460742 64686068 +1958608 AC091231.1 chr15 64470253 64471364 +1958612 OAZ2 chr15 64687573 64703281 +1958693 AC100830.3 chr15 64695041 64695594 +1958696 AC100830.2 chr15 64696622 64696861 +1958699 AC100830.1 chr15 64701248 64719602 +1958703 RBPMS2 chr15 64739891 64775589 +1958746 PIF1 chr15 64815632 64825668 +1958864 PLEKHO2 chr15 64841883 64868002 +1958897 AC069368.2 chr15 64878428 64882385 +1958901 ANKDD1A chr15 64911902 64958691 +1959090 AC103691.2 chr15 64943240 64943672 +1959093 AC103691.1 chr15 64950916 64951435 +1959096 SPG21 chr15 64963022 64990310 +1959290 MTFMT chr15 65001512 65029639 +1959383 SLC51B chr15 65045387 65053397 +1959397 AC013553.3 chr15 65049188 65049802 +1959400 RASL12 chr15 65053337 65076690 +1959444 KBTBD13 chr15 65076816 65079939 +1959451 AC013553.4 chr15 65083042 65083663 +1959454 UBAP1L chr15 65092770 65115197 +1959503 PDCD7 chr15 65117379 65133808 +1959529 CLPX chr15 65148219 65185342 +1959623 CILP chr15 65194760 65211473 +1959647 PARP16 chr15 65234460 65300618 +1959717 IGDCC3 chr15 65327127 65378002 +1959798 IGDCC4 chr15 65381484 65422947 +1959872 DPP8 chr15 65442463 65517704 +1960234 HACD3 chr15 65530418 65578349 +1960482 INTS14 chr15 65578753 65611289 +1960799 SLC24A1 chr15 65611366 65660995 +1960970 AC011939.3 chr15 65655620 65656085 +1960973 DENND4A chr15 65658046 65792293 +1961266 RAB11A chr15 65726054 65891989 +1961364 AC011939.2 chr15 65766460 65767398 +1961368 MEGF11 chr15 65895079 66253747 +1961692 AC055855.2 chr15 66278498 66293357 +1961696 DIS3L chr15 66293217 66333898 +1961926 AC055855.1 chr15 66314914 66331703 +1961930 TIPIN chr15 66336191 66386746 +1962019 MAP2K1 chr15 66386817 66492312 +1962072 AC116913.1 chr15 66488658 66492109 +1962076 SNAPC5 chr15 66490135 66497780 +1962167 RPL4 chr15 66498015 66524532 +1962317 ZWILCH chr15 66504959 66550130 +1962590 LCTL chr15 66547179 66565979 +1962683 LINC01169 chr15 66582190 66685794 +1962690 SMAD6 chr15 66702236 66782849 +1962740 AC013564.1 chr15 66740445 66741151 +1962743 AC110048.2 chr15 66860303 66867023 +1962746 AC093334.1 chr15 66919811 66931755 +1962750 LINC02206 chr15 66931537 66956518 +1962755 AC087482.1 chr15 66984103 67065268 +1962794 SMAD3 chr15 67063763 67195169 +1962987 AC012568.1 chr15 67142734 67146939 +1962992 AAGAB chr15 67200667 67255195 +1963099 IQCH chr15 67254786 67502260 +1963359 IQCH-AS1 chr15 67290636 67521844 +1963407 C15orf61 chr15 67521131 67530146 +1963432 AC016355.1 chr15 67541072 67542604 +1963435 MAP2K5 chr15 67542703 67807117 +1963715 SKOR1 chr15 67819704 67834582 +1963819 AC009292.2 chr15 67832725 67873866 +1963827 AC009292.1 chr15 67834310 67838879 +1963832 PIAS1 chr15 68054179 68198603 +1963956 CALML4 chr15 68190705 68206110 +1964039 CLN6 chr15 68206992 68257211 +1964349 AC107871.2 chr15 68267792 68277994 +1964356 FEM1B chr15 68277745 68295862 +1964387 ITGA11 chr15 68296532 68432163 +1964544 AC100825.1 chr15 68483202 68487149 +1964549 CORO2B chr15 68578969 68727806 +1964663 ANP32A chr15 68778535 68820897 +1964754 SPESP1 chr15 68818221 68946811 +1964770 AC087639.2 chr15 68880663 68928941 +1964775 NOX5 chr15 68930525 69062762 +1965020 AC027088.5 chr15 68985795 68998679 +1965025 AC027088.3 chr15 69037549 69043565 +1965029 EWSAT1 chr15 69072926 69095820 +1965067 AC027088.2 chr15 69080879 69099987 +1965074 GLCE chr15 69160584 69272217 +1965108 AC026992.2 chr15 69278328 69298795 +1965119 AC026992.1 chr15 69278675 69295322 +1965128 PAQR5 chr15 69298912 69407780 +1965216 AC027237.4 chr15 69391192 69392149 +1965220 AC027237.3 chr15 69396904 69415029 +1965240 KIF23 chr15 69414246 69448427 +1965671 RPLP1 chr15 69452814 69456205 +1965713 AC027237.2 chr15 69458522 69461806 +1965717 DRAIC chr15 69462921 69843120 +1966086 AC100826.1 chr15 69564724 69565790 +1966090 AC021818.1 chr15 69820756 69835111 +1966101 TLE3 chr15 70047790 70098176 +1966927 AC026583.1 chr15 70195638 70198509 +1966932 AC048383.1 chr15 70321576 70326742 +1966936 LINC02205 chr15 70503907 70505928 +1966940 AC009434.1 chr15 70556521 70562722 +1966944 LINC02204 chr15 70570958 70586606 +1966948 SALRNA3 chr15 70615547 70616567 +1966951 SALRNA2 chr15 70635249 70637314 +1966954 UACA chr15 70654554 70763558 +1967220 AC009269.2 chr15 70748932 70754177 +1967224 AC009269.5 chr15 70758269 70758856 +1967227 AC009269.3 chr15 70768011 70778868 +1967231 LARP6 chr15 70829130 70854157 +1967271 AC009269.4 chr15 70848883 70849770 +1967275 LRRC49 chr15 70853239 71053657 +1967793 THAP10 chr15 70881342 70892433 +1967814 THSD4 chr15 71096952 71783383 +1967929 CT62 chr15 71110244 71115500 +1967960 THSD4-AS1 chr15 71147650 71189064 +1967993 AC064799.2 chr15 71332120 71352460 +1968002 AC108861.1 chr15 71547280 71549832 +1968007 NR2E3 chr15 71792638 71818259 +1968076 AC104938.1 chr15 71818396 71823384 +1968091 MYO9A chr15 71822291 72118577 +1968622 AC022872.1 chr15 71972206 72040265 +1968629 SENP8 chr15 72114258 72143692 +1968675 AC020779.2 chr15 72140504 72155459 +1968679 GRAMD2A chr15 72159806 72197787 +1968817 PKM chr15 72199029 72231822 +1969190 PARP6 chr15 72241181 72272999 +1969783 AC009690.2 chr15 72278867 72351794 +1969788 CELF6 chr15 72284727 72320157 +1969933 HEXA chr15 72340919 72376476 +1970215 HEXA-AS1 chr15 72376113 72378788 +1970218 TMEM202 chr15 72398302 72408367 +1970273 TMEM202-AS1 chr15 72407778 72475168 +1970281 AC079322.1 chr15 72465128 72466262 +1970284 ARIH1 chr15 72474330 72602987 +1970384 AC100827.3 chr15 72589691 72591845 +1970387 LINC02259 chr15 72608481 72636962 +1970397 AC100827.4 chr15 72615810 72618250 +1970400 GOLGA6B chr15 72654738 72666394 +1970446 HIGD2B chr15 72675788 72686182 +1970458 BBS4 chr15 72686179 72738475 +1970825 ADPGK chr15 72751369 72785846 +1970972 ADPGK-AS1 chr15 72782835 72798199 +1970985 AC103874.1 chr15 72858354 72887128 +1970989 NEO1 chr15 73051710 73305205 +1971316 AC068397.1 chr15 73255334 73256109 +1971320 HCN4 chr15 73319859 73368958 +1971342 AC068397.2 chr15 73335260 73342387 +1971352 REC114 chr15 73443164 73560013 +1971385 NPTN chr15 73560014 73634134 +1971527 NPTN-IT1 chr15 73567012 73569294 +1971530 CD276 chr15 73683966 73714514 +1971792 AC022188.1 chr15 73730048 73731711 +1971795 INSYN1 chr15 73735431 73752747 +1971828 INSYN1-AS1 chr15 73752317 73770613 +1971840 AC018943.1 chr15 73870949 73873540 +1971848 TBC1D21 chr15 73873564 73889214 +1971926 LOXL1-AS1 chr15 73908071 73928248 +1971984 LOXL1 chr15 73925989 73952137 +1972038 STOML1 chr15 73978926 73994622 +1972199 PML chr15 73994673 74047827 +1972530 AC013486.1 chr15 74040190 74043332 +1972534 GOLGA6A chr15 74069857 74082550 +1972588 ISLR2 chr15 74100311 74138540 +1972707 AC010931.2 chr15 74125915 74129341 +1972720 AC010931.3 chr15 74152800 74179226 +1972725 ISLR chr15 74173710 74176872 +1972758 STRA6 chr15 74179466 74212267 +1973297 CCDC33 chr15 74202705 74336472 +1973484 AC023300.1 chr15 74303005 74304343 +1973488 AC023300.2 chr15 74311516 74319688 +1973492 CYP11A1 chr15 74337759 74367646 +1973615 AC090826.1 chr15 74365435 74371211 +1973620 AC090826.2 chr15 74374678 74375511 +1973623 LINC02255 chr15 74379083 74390535 +1973628 SEMA7A chr15 74409289 74433958 +1973729 AC090826.3 chr15 74429445 74431449 +1973733 UBL7 chr15 74445977 74461182 +1973929 UBL7-AS1 chr15 74461265 74513636 +1973977 AC012435.3 chr15 74489602 74516959 +1973983 ARID3B chr15 74541177 74598131 +1974050 CLK3 chr15 74598500 74645414 +1974373 AC100835.2 chr15 74598919 74599397 +1974376 AC100835.1 chr15 74613194 74615596 +1974380 EDC3 chr15 74630558 74696292 +1974605 CYP1A1 chr15 74719542 74725536 +1974791 CYP1A2 chr15 74748845 74756607 +1974811 CSK chr15 74782057 74803198 +1974992 LMAN1L chr15 74812716 74825757 +1975116 CPLX3 chr15 74826627 74831802 +1975128 ULK3 chr15 74836118 74843346 +1975575 SCAMP2 chr15 74843730 74873365 +1975731 MPI chr15 74890005 74902219 +1976043 FAM219B chr15 74899992 74906883 +1976280 COX5A chr15 74919791 74938083 +1976361 RPP25 chr15 74954416 74957464 +1976369 SCAMP5 chr15 74957219 75021495 +1976620 PPCDC chr15 75023586 75117462 +1976727 C15orf39 chr15 75195643 75212169 +1976790 AC113208.4 chr15 75211301 75212167 +1976794 AC113208.5 chr15 75225784 75227185 +1976798 GOLGA6C chr15 75258599 75270199 +1976839 GOLGA6D chr15 75282835 75295807 +1976916 COMMD4 chr15 75336020 75343224 +1977166 AC068338.3 chr15 75346744 75347161 +1977169 NEIL1 chr15 75346955 75357115 +1977401 MAN2C1 chr15 75355207 75368612 +1977983 AC068338.2 chr15 75368155 75369584 +1977986 SIN3A chr15 75369379 75455842 +1978232 AC105137.2 chr15 75452964 75453947 +1978235 PTPN9 chr15 75463251 75579315 +1978323 SNUPN chr15 75598083 75626469 +1978496 AC105020.3 chr15 75624793 75625690 +1978500 AC105020.2 chr15 75636139 75639239 +1978505 IMP3 chr15 75639085 75648706 +1978526 AC105020.6 chr15 75639760 75640976 +1978529 AC105020.5 chr15 75645020 75645442 +1978532 SNX33 chr15 75647906 75662301 +1978551 CSPG4 chr15 75674322 75712848 +1978577 AC105020.4 chr15 75676227 75677162 +1978581 AC105020.1 chr15 75678548 75680752 +1978584 ODF3L1 chr15 75724041 75727688 +1978598 DNM1P35 chr15 75727670 75738623 +1978603 AC019294.2 chr15 75737820 75763322 +1978665 AC019294.3 chr15 75759501 75762405 +1978668 UBE2Q2 chr15 75843307 75901078 +1978818 FBXO22 chr15 75903876 75942511 +1978940 NRG4 chr15 75935969 76059795 +1979194 TMEM266 chr15 76059958 76229121 +1979285 AC091100.1 chr15 76174891 76181486 +1979290 ETFA chr15 76215353 76311472 +1979629 AC027243.3 chr15 76263197 76275387 +1979633 ISL2 chr15 76336773 76342475 +1979669 AC027243.1 chr15 76339609 76342063 +1979674 AC027243.2 chr15 76343642 76344365 +1979677 SCAPER chr15 76347904 76905444 +1980178 RCN2 chr15 76931738 76954393 +1980256 PSTPIP1 chr15 76993359 77037475 +1980611 TSPAN3 chr15 77041404 77083984 +1980734 AC090181.1 chr15 77043680 77045160 +1980738 AC090181.2 chr15 77067654 77068325 +1980741 PEAK1 chr15 77100656 77420144 +1980845 HMG20A chr15 77420412 77485607 +1980989 AC046168.1 chr15 77525540 77534110 +1980993 AC046168.2 chr15 77568970 77608888 +1981003 LINGO1 chr15 77613027 77820900 +1981149 LINGO1-AS1 chr15 77641764 77652292 +1981167 LINGO1-AS2 chr15 77660052 77668074 +1981172 AC105133.1 chr15 77787193 77788674 +1981179 AC104758.4 chr15 77916522 77922019 +1981183 AC104758.5 chr15 77954075 77963654 +1981187 TBC1D2B chr15 77984036 78077724 +1981297 AC104758.2 chr15 77993405 77995289 +1981302 SH2D7 chr15 78077808 78104909 +1981336 CIB2 chr15 78104606 78131535 +1981471 IDH3A chr15 78131498 78171945 +1981813 AC090260.1 chr15 78141243 78143173 +1981816 ACSBG1 chr15 78167468 78245688 +1982011 AC090607.3 chr15 78250502 78264156 +1982019 DNAJA4 chr15 78264086 78282196 +1982194 WDR61 chr15 78277835 78299703 +1982403 AC090607.4 chr15 78280950 78282190 +1982407 AC090607.1 chr15 78293286 78296049 +1982411 AC090607.5 chr15 78299701 78299924 +1982414 CRABP1 chr15 78340353 78348225 +1982441 IREB2 chr15 78437431 78501453 +1982624 AC027228.1 chr15 78480057 78481820 +1982628 HYKK chr15 78507564 78537372 +1982713 PSMA4 chr15 78540405 78552417 +1983000 CHRNA5 chr15 78565520 78595269 +1983055 AC027228.2 chr15 78589123 78591276 +1983058 CHRNA3 chr15 78593052 78621295 +1983134 CHRNB4 chr15 78624111 78727754 +1983211 AC067863.1 chr15 78625895 78628193 +1983215 ADAMTS7 chr15 78759206 78811464 +1983312 MORF4L1 chr15 78810487 78898139 +1983688 CTSH chr15 78921058 78949574 +1983945 RASGRF1 chr15 78959947 79090773 +1984144 AC011944.1 chr15 78978889 78985926 +1984148 ANKRD34C-AS1 chr15 79141939 79283949 +1984199 ANKRD34C chr15 79293285 79298235 +1984206 TMED3 chr15 79311112 79427432 +1984266 AC027811.1 chr15 79331591 79337277 +1984270 MINAR1 chr15 79432516 79472290 +1984297 AC021483.1 chr15 79832466 79833554 +1984301 MTHFS chr15 79833585 79897379 +1984344 AC021483.2 chr15 79843547 79844304 +1984347 AC015871.7 chr15 79894502 79896695 +1984350 AC015871.1 chr15 79898840 79923702 +1984382 AC015871.4 chr15 79920195 79922455 +1984385 ST20-AS1 chr15 79922771 79926993 +1984390 BCL2A1 chr15 79960892 79971196 +1984411 ZFAND6 chr15 80059568 80138393 +1984748 FAH chr15 80152490 80186946 +1984949 AC087761.1 chr15 80165923 80166980 +1984953 CTXND1 chr15 80195481 80252213 +1984965 LINC00927 chr15 80263068 80341805 +1984987 AC016705.2 chr15 80344853 80404214 +1985007 ARNT2 chr15 80404350 80597933 +1985222 AC016705.1 chr15 80433795 80445152 +1985230 AC016705.3 chr15 80440294 80442751 +1985234 AC108451.1 chr15 80554609 80562944 +1985239 AC108451.2 chr15 80580029 80580566 +1985242 ABHD17C chr15 80679684 80755621 +1985285 AC023302.1 chr15 80693216 80693707 +1985288 AC023302.2 chr15 80769600 80773135 +1985292 CEMIP chr15 80779343 80951776 +1985509 AC027808.2 chr15 80896191 80909777 +1985524 MESD chr15 80946289 80989828 +1985597 AC068870.1 chr15 80990804 80993258 +1985600 AC068870.2 chr15 80999593 80999981 +1985603 TLNRD1 chr15 81000923 81005788 +1985611 CFAP161 chr15 81007033 81149179 +1985655 IL16 chr15 81159575 81314058 +1985932 AC103858.1 chr15 81303215 81309391 +1985936 STARD5 chr15 81309053 81324183 +1985993 AC103858.3 chr15 81315806 81321258 +1986002 TMC3-AS1 chr15 81324338 81518200 +1986106 TMC3 chr15 81331088 81374213 +1986225 AC103858.2 chr15 81335577 81336119 +1986228 AC109809.1 chr15 81403026 81403570 +1986231 AC060809.1 chr15 81427448 81755217 +1986237 AC023034.1 chr15 81554003 81696780 +1986255 AC104041.1 chr15 81633426 82013579 +1986294 MEX3B chr15 82041778 82046119 +1986311 LINC01583 chr15 82088569 82097694 +1986329 AC026956.2 chr15 82113384 82119570 +1986333 EFL1 chr15 82130233 82262734 +1986521 AC026624.1 chr15 82180743 82182700 +1986525 SAXO2 chr15 82262810 82284930 +1986589 GOLGA6L10 chr15 82339993 82349475 +1986668 GOLGA6L9 chr15 82430018 82439153 +1986702 RPS17 chr15 82536750 82540459 +1986777 AC245033.2 chr15 82540870 82562374 +1986782 CPEB1 chr15 82543201 82648861 +1987141 CPEB1-AS1 chr15 82647770 82692820 +1987153 AP3B2 chr15 82659281 82709946 +1988222 AC105339.3 chr15 82744223 82750289 +1988226 AC105339.6 chr15 82749252 82750455 +1988229 SNHG21 chr15 82750564 82757206 +1988251 FSD2 chr15 82755362 82806070 +1988321 WHAMM chr15 82809628 82836108 +1988353 HOMER2 chr15 82836946 82986153 +1988442 AC022558.2 chr15 82925884 83103443 +1988446 RAMAC chr15 82986210 82991057 +1988460 C15orf40 chr15 82988441 83011641 +1988570 AC024270.4 chr15 83012661 83061845 +1988574 BTBD1 chr15 83016423 83067252 +1988636 AC022558.3 chr15 83020115 83020802 +1988639 AC022558.1 chr15 83022236 83024336 +1988643 AC024270.2 chr15 83022571 83090782 +1988647 AC024270.5 chr15 83095333 83108754 +1988657 TM6SF1 chr15 83107572 83144854 +1988798 HDGFL3 chr15 83112738 83207823 +1988867 AC024270.3 chr15 83113617 83114566 +1988871 AC103876.1 chr15 83179182 83439445 +1988883 BNC1 chr15 83255903 83284714 +1988914 SH3GL3 chr15 83447228 83618743 +1989001 ADAMTSL3 chr15 83654088 84039842 +1989189 AC027807.2 chr15 83962176 83962583 +1989192 AC136698.1 chr15 84171178 84173194 +1989196 UBE2Q2L chr15 84172490 84182234 +1989224 GOLGA6L4 chr15 84235773 84245368 +1989296 AC243562.3 chr15 84422618 84425882 +1989302 AC048382.4 chr15 84500378 84502381 +1989306 AC048382.5 chr15 84597809 84633988 +1989318 ZSCAN2 chr15 84600986 84627796 +1989469 AC048382.1 chr15 84611689 84614969 +1989473 AC048382.6 chr15 84622015 84623237 +1989476 WDR73 chr15 84639281 84654343 +1989656 NMB chr15 84655129 84658563 +1989679 SEC11A chr15 84669538 84716460 +1989815 AC115102.1 chr15 84685884 84686946 +1989819 AC012291.3 chr15 84717474 84746837 +1989823 ZNF592 chr15 84748592 84806445 +1989898 AC012291.2 chr15 84753122 84754502 +1989902 ALPK3 chr15 84816680 84873482 +1989941 SLC28A1 chr15 84884654 84945798 +1990080 AC087468.2 chr15 84913144 84915705 +1990084 PDE8A chr15 84980440 85139145 +1990494 AKAP13 chr15 85380571 85749358 +1990989 AC087286.3 chr15 85579046 85580178 +1990993 AC087286.2 chr15 85619623 85670948 +1990997 AC087286.1 chr15 85621264 85627689 +1991002 AC087286.4 chr15 85701109 85702771 +1991006 AC021739.4 chr15 85726115 85727227 +1991010 AC021739.2 chr15 85744109 85750281 +1991015 AC021739.5 chr15 85750336 85752901 +1991019 AC021739.3 chr15 85754941 85756237 +1991024 KLHL25 chr15 85759326 85794925 +1991041 LINC01584 chr15 86078809 86116747 +1991248 AGBL1 chr15 86079973 87029052 +1991386 AGBL1-AS1 chr15 86295649 86317173 +1991399 AC012229.1 chr15 86630266 86631136 +1991403 AC016987.2 chr15 86932880 86946331 +1991408 AC016987.1 chr15 86938797 86988426 +1991413 AC078905.1 chr15 87038717 87047303 +1991418 AC020687.1 chr15 87325829 87703852 +1991436 LINC00052 chr15 87576929 87579866 +1991441 AC103871.1 chr15 87638688 87668488 +1991447 NTRK3 chr15 87859751 88256768 +1991947 NTRK3-AS1 chr15 88252730 88271066 +1991953 MRPL46 chr15 88459477 88467390 +1991999 MRPS11 chr15 88467453 88480776 +1992084 DET1 chr15 88494440 88546675 +1992187 LINC01586 chr15 88585566 88605110 +1992205 AEN chr15 88621337 88632281 +1992238 ISG20 chr15 88636153 88656483 +1992314 AC103982.1 chr15 88797413 88798734 +1992318 ACAN chr15 88803440 88875354 +1992582 HAPLN3 chr15 88877288 88895626 +1992648 MFGE8 chr15 88898683 88913381 +1992815 AC013565.1 chr15 89041223 89082819 +1992826 AC013565.3 chr15 89087078 89088377 +1992836 ABHD2 chr15 89087459 89202355 +1992965 RLBP1 chr15 89209869 89221614 +1993022 FANCI chr15 89243949 89317261 +1993483 POLG chr15 89305198 89334861 +1994085 AC124068.2 chr15 89335053 89336161 +1994091 AC133637.2 chr15 89361157 89362421 +1994094 MIR9-3HG chr15 89361579 89398487 +1994447 RHCG chr15 89471398 89496589 +1994593 LINC00928 chr15 89504909 89524049 +1994619 AC013391.3 chr15 89508961 89510416 +1994622 AC013391.2 chr15 89518523 89591956 +1994626 TICRR chr15 89575469 89631056 +1994735 AC013391.1 chr15 89579765 89582297 +1994739 KIF7 chr15 89608789 89655467 +1994802 PLIN1 chr15 89664367 89679427 +1994861 PEX11A chr15 89677764 89690783 +1994908 WDR93 chr15 89690811 89743638 +1995017 AC079075.1 chr15 89704665 89705415 +1995021 MESP1 chr15 89748661 89751310 +1995034 MESP2 chr15 89760591 89778754 +1995058 ANPEP chr15 89784895 89815401 +1995172 AP3S2 chr15 89830599 89894638 +1995351 ARPIN chr15 89895006 89912952 +1995393 ZNF710 chr15 90001324 90082206 +1995437 AC087284.1 chr15 90024955 90026003 +1995440 ZNF710-AS1 chr15 90074512 90082207 +1995446 IDH2 chr15 90083045 90102504 +1995546 IDH2-DT chr15 90102649 90138016 +1995553 SEMA4B chr15 90160604 90229679 +1995797 CIB1 chr15 90229975 90234047 +1995857 GDPGP1 chr15 90233808 90245811 +1995913 TTLL13P chr15 90249530 90265482 +1996047 NGRN chr15 90265659 90278141 +1996069 AC091167.5 chr15 90281858 90282270 +1996072 ZNF774 chr15 90352284 90369146 +1996129 IQGAP1 chr15 90388242 90502239 +1996426 AC018946.1 chr15 90393490 90397881 +1996430 CRTC3 chr15 90529923 90645345 +1996577 AC103739.1 chr15 90595840 90596447 +1996581 AC103739.2 chr15 90604225 90614558 +1996586 CRTC3-AS1 chr15 90620007 90717141 +1996596 AC103739.3 chr15 90630535 90631755 +1996600 AC021422.1 chr15 90650631 90651103 +1996603 LINC01585 chr15 90660207 90664967 +1996617 BLM chr15 90717346 90816166 +1996857 AC124248.2 chr15 90811528 90815544 +1996861 AC124248.1 chr15 90839641 90853608 +1996869 FURIN chr15 90868588 90883458 +1997032 FES chr15 90883695 90895776 +1997353 MAN2A2 chr15 90902218 90922584 +1997801 AC068831.4 chr15 90920218 90921186 +1997805 HDDC3 chr15 90929964 90935196 +1997884 UNC45A chr15 90930180 90954093 +1998163 AC068831.1 chr15 90952239 90955225 +1998167 RCCD1 chr15 90954870 90963125 +1998272 PRC1 chr15 90966040 90995629 +1998493 PRC1-AS1 chr15 90966340 90988625 +1998518 VPS33B chr15 90998416 91022603 +1998699 VPS33B-DT chr15 91022619 91036611 +1998719 AC068831.6 chr15 91022766 91023200 +1998722 AC127520.1 chr15 91094847 91099838 +1998726 SV2B chr15 91099950 91301309 +1998858 AC123784.1 chr15 91303756 91306321 +1998863 AC104035.1 chr15 91408708 91605873 +1998878 AC107958.3 chr15 91532891 91535095 +1998882 AC107958.2 chr15 91643017 91649114 +1998887 SLCO3A1 chr15 91853708 92172435 +1999021 AC116903.2 chr15 92148752 92331037 +1999027 AC116903.1 chr15 92162798 92172436 +1999031 ST8SIA2 chr15 92393881 92468728 +1999080 AC090985.2 chr15 92470233 92471546 +1999084 C15orf32 chr15 92471654 92501117 +1999093 LINC00930 chr15 92567817 92574529 +1999115 AC091544.2 chr15 92580741 92600545 +1999135 AC091544.4 chr15 92592574 92596462 +1999148 AC091544.5 chr15 92602910 92620015 +1999152 FAM174B chr15 92617448 92809884 +1999250 AC091544.7 chr15 92634305 92634665 +1999253 AC106028.3 chr15 92779757 92781492 +1999256 AC106028.2 chr15 92805770 92808567 +1999260 AC106028.4 chr15 92808451 92809057 +1999263 LINC01578 chr15 92819540 92899701 +1999315 CHD2 chr15 92900189 93027996 +1999884 RGMA chr15 93035273 93089204 +2000013 AC108457.1 chr15 93177269 93179999 +2000017 AC091078.1 chr15 93230034 93569483 +2000095 AC112693.1 chr15 93257198 93260475 +2000099 AC091078.2 chr15 93416850 93422576 +2000103 AC110023.1 chr15 93589867 93760886 +2000113 LINC01579 chr15 93718542 94070898 +2000201 LINC02207 chr15 93835490 93878822 +2000425 AC103996.3 chr15 93837611 93852981 +2000429 AC103996.2 chr15 93882082 93886743 +2000434 LINC01580 chr15 93894431 93984150 +2000505 LINC01581 chr15 93905405 94107938 +2000522 MCTP2 chr15 94231538 94483952 +2000740 AC009432.2 chr15 94455469 94550572 +2000744 LINC02852 chr15 94583506 94589259 +2000749 AC009432.1 chr15 94600014 94600821 +2000753 AC022308.1 chr15 94724928 94726519 +2000757 AC107976.1 chr15 94855586 94857011 +2000761 AC087633.1 chr15 95034108 95047108 +2000771 AC087636.1 chr15 95078481 95150534 +2000801 LINC01197 chr15 95186634 95327129 +2000939 AC104260.1 chr15 95225326 95225864 +2000942 AC104260.3 chr15 95287934 95291643 +2000946 LINC00924 chr15 95326528 95507865 +2000990 AC027013.1 chr15 95463587 95493843 +2001016 AC015574.1 chr15 95638316 95826499 +2001068 AC012409.2 chr15 95990582 96300990 +2001078 AC024337.1 chr15 96045341 96064357 +2001090 AC024337.2 chr15 96080713 96084584 +2001094 NR2F2-AS1 chr15 96110040 96327361 +2001182 AC012409.3 chr15 96139472 96140452 +2001185 AC012409.1 chr15 96171575 96174339 +2001196 AC012409.4 chr15 96230897 96231145 +2001199 LINC02157 chr15 96235785 96237010 +2001206 NR2F2 chr15 96325938 96340263 +2001258 AC103746.1 chr15 96342953 96345651 +2001262 AC087477.2 chr15 96354237 96405235 +2001292 AC087477.5 chr15 96393146 96405189 +2001306 AC087477.3 chr15 96438570 96444266 +2001310 AC087477.4 chr15 96448842 96449749 +2001314 SPATA8-AS1 chr15 96772005 96783312 +2001324 SPATA8 chr15 96783389 96785615 +2001343 LINC02253 chr15 97215812 97432094 +2001405 AC020704.1 chr15 97272020 97319321 +2001415 LINC02254 chr15 97339693 97523442 +2001488 AC026523.1 chr15 97540597 97560702 +2001502 AC026523.3 chr15 97557808 97559097 +2001506 AC026523.4 chr15 97560849 97572707 +2001512 LINC00923 chr15 97572185 97875650 +2001597 AC024651.2 chr15 97876289 97878386 +2001600 AC024651.3 chr15 97945208 97950018 +2001604 ARRDC4 chr15 97960703 97973833 +2001626 AC024651.1 chr15 97982509 97991142 +2001632 LINC02251 chr15 98003038 98087384 +2001668 AC022523.1 chr15 98038571 98293199 +2001675 LINC01582 chr15 98081993 98103761 +2001725 AC022523.3 chr15 98111729 98131707 +2001743 AC015722.1 chr15 98282075 98285907 +2001748 AC015722.2 chr15 98319687 98320237 +2001751 LINC02351 chr15 98323902 98420998 +2001764 FAM169B chr15 98437162 98547728 +2001798 IRAIN chr15 98646951 98647371 +2001802 IGF1R chr15 98648539 98964530 +2001985 AC118658.1 chr15 98660210 98660668 +2001988 AC055807.1 chr15 98839292 98840147 +2001992 AC069029.1 chr15 98880659 98893535 +2001996 AC036108.1 chr15 98954149 99105824 +2002002 PGPEP1L chr15 98968229 99007792 +2002045 LUNAR1 chr15 99014526 99031054 +2002090 SYNM chr15 99098217 99135593 +2002147 AC036108.2 chr15 99128832 99131806 +2002151 TTC23 chr15 99136323 99251223 +2002448 AC036108.3 chr15 99139317 99145370 +2002452 AC022819.1 chr15 99157231 99161140 +2002455 LRRC28 chr15 99251362 99390729 +2002699 LINC02244 chr15 99395179 99396593 +2002703 AC015660.2 chr15 99396613 99401315 +2002707 AC015660.3 chr15 99416584 99417204 +2002710 AC015660.1 chr15 99423769 99435160 +2002716 AC015660.5 chr15 99473454 99476314 +2002720 MEF2A chr15 99565417 99716466 +2002931 LYSMD4 chr15 99715697 99733561 +2003023 AC090825.1 chr15 99805793 99916818 +2003106 AC084855.1 chr15 99970215 99974010 +2003111 ADAMTS17 chr15 99971437 100342005 +2003226 AC084855.2 chr15 99976481 99980774 +2003230 AC022710.1 chr15 100126106 100129743 +2003234 SPATA41 chr15 100344047 100350725 +2003247 CERS3-AS1 chr15 100372936 100437914 +2003261 CERS3 chr15 100400395 100544995 +2003398 AC027020.2 chr15 100547765 100550153 +2003401 AC027020.1 chr15 100558677 100559798 +2003409 LINS1 chr15 100559369 100603230 +2003547 ASB7 chr15 100602534 100651705 +2003598 AC087762.1 chr15 100716249 100828497 +2003603 AC015712.1 chr15 100849561 100861756 +2003627 AC015712.4 chr15 100861843 100874369 +2003640 ALDH1A3 chr15 100877714 100916626 +2003744 AC015712.7 chr15 100888472 100889106 +2003747 AC015712.2 chr15 100892343 100919391 +2003764 LRRK1 chr15 100919327 101078257 +2004049 AC090907.1 chr15 101043716 101049456 +2004053 AC090907.2 chr15 101050732 101086066 +2004058 AC090907.3 chr15 101058647 101063904 +2004063 AC019254.2 chr15 101116603 101117546 +2004067 AC019254.1 chr15 101168530 101170821 +2004074 CHSY1 chr15 101175727 101252048 +2004108 SELENOS chr15 101270817 101277500 +2004198 SNRPA1 chr15 101281510 101295282 +2004354 AC023024.1 chr15 101295419 101305737 +2004358 PCSK6 chr15 101297142 101525202 +2004795 PCSK6-AS1 chr15 101334437 101337428 +2004800 AC090164.2 chr15 101495052 101495567 +2004803 AC090164.3 chr15 101522597 101524739 +2004806 AC090164.4 chr15 101527581 101528349 +2004810 AC090164.5 chr15 101602786 101614531 +2004822 TM2D3 chr15 101621444 101652391 +2004966 TARSL2 chr15 101653596 101724473 +2005140 OR4F6 chr15 101803509 101806887 +2005150 OR4F15 chr15 101812202 101820197 +2005160 OR4F4 chr15 101922042 101923113 +2005173 FAM138E chr15 101954885 101956412 +2005181 AC140725.1 chr15 101959539 101961408 +2005192 WASIR2 chr16 22910 25123 +2005196 POLR3K chr16 46407 53608 +2005211 SNRNP25 chr16 53010 57669 +2005283 RHBDF1 chr16 58059 76355 +2005434 MPG chr16 77007 85853 +2005490 NPRL3 chr16 84271 138860 +2005770 Z69720.1 chr16 90631 91102 +2005773 Z69666.1 chr16 125737 127219 +2005777 HBZ chr16 142728 154503 +2005798 HBM chr16 153892 166764 +2005818 HBA2 chr16 172876 173710 +2005849 HBA1 chr16 176680 177522 +2005878 HBQ1 chr16 180459 181179 +2005890 Z69706.1 chr16 185748 186294 +2005893 LUC7L chr16 188969 229463 +2006199 FAM234A chr16 234521 272183 +2006611 RGS11 chr16 268301 275980 +2006795 ARHGDIG chr16 280450 283010 +2006849 PDIA2 chr16 283152 287215 +2006952 AXIN1 chr16 287440 352723 +2007029 MRPL28 chr16 366969 371289 +2007152 TMEM8A chr16 370788 387113 +2007267 NME4 chr16 396725 410367 +2007437 DECR2 chr16 401858 412487 +2007673 AL023881.1 chr16 424243 424543 +2007676 RAB11FIP3 chr16 425649 523011 +2007833 LINC00235 chr16 525155 527407 +2007836 CAPN15 chr16 527712 554636 +2007916 Z97986.1 chr16 547185 553847 +2007920 PRR35 chr16 560394 565529 +2007932 PIGQ chr16 566995 584136 +2008267 NHLRC4 chr16 567005 569495 +2008286 RAB40C chr16 589357 629272 +2008465 WFIKKN1 chr16 629239 634117 +2008477 METTL26 chr16 634427 636366 +2008640 MCRIP2 chr16 636817 648474 +2008725 AL022341.1 chr16 648473 649200 +2008729 WDR90 chr16 649311 667833 +2009198 AL022341.2 chr16 654611 656194 +2009202 RHOT2 chr16 668105 674174 +2009586 RHBDL1 chr16 675666 678268 +2009651 Z92544.1 chr16 678504 679777 +2009659 STUB1 chr16 680224 682870 +2009783 JMJD8 chr16 681670 684528 +2009956 WDR24 chr16 684622 690444 +2010040 Z92544.2 chr16 689001 692554 +2010046 FBXL16 chr16 692498 705808 +2010104 Z97653.1 chr16 710746 711277 +2010108 METRN chr16 715118 719655 +2010167 ANTKMT chr16 720581 722590 +2010234 CCDC78 chr16 722582 726954 +2010424 HAGHL chr16 726936 735525 +2010634 CIAO3 chr16 729760 741329 +2010867 MSLN chr16 760734 768865 +2011104 MSLNL chr16 769428 783370 +2011178 RPUSD1 chr16 784974 788397 +2011325 CHTF18 chr16 788046 800737 +2011694 GNG13 chr16 798041 800734 +2011706 AL023882.1 chr16 817489 862843 +2011712 AL031008.1 chr16 848525 849065 +2011715 LMF1 chr16 853634 981318 +2011946 AL031716.1 chr16 883780 885090 +2011950 AL008727.1 chr16 898967 905224 +2011955 LMF1-AS1 chr16 921033 934495 +2011963 AC009041.4 chr16 968375 969012 +2011966 AC009041.2 chr16 975761 981596 +2012010 SOX8 chr16 981770 986979 +2012025 AC009041.1 chr16 991151 1000926 +2012038 SSTR5-AS1 chr16 1064093 1078731 +2012059 AC009041.3 chr16 1065240 1066502 +2012063 SSTR5 chr16 1078781 1080142 +2012071 C1QTNF8 chr16 1088226 1096244 +2012108 AL031598.1 chr16 1111627 1113399 +2012111 AC120498.8 chr16 1148224 1148754 +2012114 CACNA1H chr16 1153106 1221771 +2012695 AC120498.3 chr16 1156976 1157974 +2012699 AC120498.1 chr16 1159548 1160176 +2012703 AC120498.6 chr16 1206560 1207124 +2012707 TPSG1 chr16 1221651 1225257 +2012729 AC120498.10 chr16 1223639 1224143 +2012732 TPSB2 chr16 1227272 1230184 +2012784 TPSAB1 chr16 1240705 1242554 +2012832 TPSD1 chr16 1256059 1259008 +2012864 AC120498.2 chr16 1257339 1258074 +2012868 AC120498.4 chr16 1294551 1299166 +2012873 AC120498.9 chr16 1305547 1309413 +2012876 UBE2I chr16 1308880 1327018 +2013104 AL031714.1 chr16 1317891 1322845 +2013111 BAIAP3 chr16 1333601 1349441 +2013698 TSR3 chr16 1349240 1351878 +2013727 GNPTG chr16 1351931 1364113 +2013842 AL031709.1 chr16 1358900 1361405 +2013846 UNKL chr16 1363205 1414751 +2014055 AL032819.1 chr16 1408834 1412248 +2014059 C16orf91 chr16 1419752 1420756 +2014071 AL032819.3 chr16 1431035 1433397 +2014081 CCDC154 chr16 1434383 1444556 +2014177 CLCN7 chr16 1444934 1475084 +2014424 AL031600.3 chr16 1445343 1446519 +2014428 AL031600.1 chr16 1451760 1452653 +2014432 AL031600.2 chr16 1467673 1472684 +2014436 PTX4 chr16 1485886 1488981 +2014469 TELO2 chr16 1493344 1510457 +2014585 IFT140 chr16 1510427 1612072 +2014815 AL031705.1 chr16 1512979 1514675 +2014819 TMEM204 chr16 1528688 1555580 +2014844 AL133297.1 chr16 1579242 1580308 +2014848 AL133297.2 chr16 1580527 1610328 +2014853 CRAMP1 chr16 1612325 1677908 +2014980 Z97652.1 chr16 1625628 1626160 +2014984 JPT2 chr16 1678256 1702280 +2015157 MAPK8IP3 chr16 1706183 1770317 +2015439 AL031710.2 chr16 1707252 1707973 +2015442 AL031710.1 chr16 1713527 1714208 +2015446 AL031717.1 chr16 1751559 1752262 +2015450 NME3 chr16 1770286 1771730 +2015540 MRPS34 chr16 1771890 1773155 +2015566 EME2 chr16 1772810 1781708 +2015629 SPSB3 chr16 1776712 1793700 +2015727 NUBP2 chr16 1782932 1789186 +2015914 IGFALS chr16 1790413 1794971 +2015942 HAGH chr16 1795620 1827157 +2016106 FAHD1 chr16 1826941 1840207 +2016143 MEIOB chr16 1833987 1884294 +2016275 AL031722.1 chr16 1841020 1843547 +2016279 LINC00254 chr16 1878285 1884233 +2016289 LINC02124 chr16 1889114 1890434 +2016293 HS3ST6 chr16 1911475 1918415 +2016303 MSRB1 chr16 1938210 1943326 +2016372 RPL3L chr16 1943974 1957606 +2016410 NDUFB10 chr16 1959538 1961975 +2016462 RPS2 chr16 1962058 1964841 +2016627 SNHG9 chr16 1964959 1965509 +2016633 RNF151 chr16 1966823 1968975 +2016670 AC005363.2 chr16 1971655 1971896 +2016673 TBL3 chr16 1972053 1982929 +2016878 NOXO1 chr16 1978917 1984192 +2016985 GFER chr16 1984193 1987749 +2017025 AC005606.2 chr16 1984877 1990477 +2017039 SYNGR3 chr16 1989660 1994275 +2017098 AC005606.1 chr16 1997654 1998374 +2017102 ZNF598 chr16 1997654 2009821 +2017238 NPW chr16 2009926 2020755 +2017264 SLC9A3R2 chr16 2025356 2039026 +2017387 NTHL1 chr16 2039815 2047866 +2017516 TSC2 chr16 2047967 2089491 +2019649 PKD1 chr16 2088710 2135898 +2020216 AC009065.2 chr16 2091436 2095433 +2020226 AC009065.5 chr16 2094830 2097026 +2020230 AC009065.6 chr16 2112335 2113342 +2020234 AC009065.3 chr16 2119207 2120248 +2020238 RAB26 chr16 2140803 2154165 +2020347 SNHG19 chr16 2154797 2155358 +2020351 TRAF7 chr16 2155698 2178129 +2020476 CASKIN1 chr16 2177180 2196605 +2020530 MLST8 chr16 2204248 2209453 +2020983 BRICD5 chr16 2209253 2211950 +2021029 PGP chr16 2211593 2214840 +2021046 AC009065.7 chr16 2211997 2212863 +2021050 E4F1 chr16 2223580 2235742 +2021192 AC009065.1 chr16 2235689 2236913 +2021195 DNASE1L2 chr16 2235816 2238711 +2021302 ECI1 chr16 2239402 2252300 +2021389 AC009065.8 chr16 2240487 2241818 +2021393 RNPS1 chr16 2253116 2268397 +2021760 AC009065.4 chr16 2268155 2273418 +2021771 ABCA3 chr16 2275881 2340746 +2021959 CCNF chr16 2429394 2458854 +2022056 AC106820.6 chr16 2430702 2437103 +2022061 AC106820.3 chr16 2452581 2452977 +2022064 AC106820.5 chr16 2456252 2459979 +2022075 TEDC2 chr16 2460086 2464963 +2022246 AC106820.2 chr16 2464950 2468213 +2022249 NTN3 chr16 2471297 2474145 +2022267 TBC1D24 chr16 2475051 2509560 +2022417 AC106820.4 chr16 2476558 2482173 +2022420 ATP6V0C chr16 2513952 2520218 +2022463 AMDHD2 chr16 2520357 2531422 +2022709 CEMP1 chr16 2530035 2531417 +2022726 PDPK1 chr16 2537979 2603188 +2022949 AC093525.6 chr16 2554060 2556060 +2022952 AC093525.5 chr16 2554975 2556105 +2022956 AC093525.7 chr16 2561471 2565096 +2022959 AC093525.4 chr16 2569043 2571936 +2022963 AC093525.3 chr16 2571570 2572353 +2022967 AC141586.3 chr16 2597881 2599718 +2022970 AC141586.2 chr16 2644084 2645214 +2022974 ERVK13-1 chr16 2660348 2682379 +2023199 KCTD5 chr16 2682523 2709030 +2023244 PRSS27 chr16 2712419 2720551 +2023296 SRRM2-AS1 chr16 2737076 2752600 +2023327 SRRM2 chr16 2752626 2772538 +2023610 ELOB chr16 2771414 2777297 +2023670 AC092117.1 chr16 2777319 2780568 +2023673 PRSS33 chr16 2783953 2787948 +2023734 PRSS41 chr16 2798485 2805302 +2023749 PRSS21 chr16 2817180 2826304 +2023852 ZG16B chr16 2830169 2839585 +2023904 PRSS22 chr16 2852730 2858170 +2023972 AC003965.2 chr16 2857898 2859726 +2023977 AC003965.1 chr16 2866325 2868251 +2023989 FLYWCH2 chr16 2883213 2899382 +2024037 FLYWCH1 chr16 2911937 2951208 +2024197 AC004034.1 chr16 2939714 2954276 +2024202 KREMEN2 chr16 2964216 2968383 +2024330 PKMYT1 chr16 2968024 2980479 +2024580 PAQR4 chr16 2969270 2973484 +2024632 AC004233.3 chr16 2981175 2981591 +2024635 LINC00514 chr16 2988256 3002016 +2024731 AC004233.1 chr16 3003431 3005101 +2024735 AC004233.2 chr16 3006120 3007388 +2024738 CLDN9 chr16 3012923 3014505 +2024746 CLDN6 chr16 3014712 3020071 +2024778 TNFRSF12A chr16 3018445 3022383 +2024851 HCFC1R1 chr16 3022620 3024286 +2024940 THOC6 chr16 3024027 3027755 +2025101 BICDL2 chr16 3027682 3036944 +2025211 AC108134.1 chr16 3032481 3039133 +2025221 MMP25-AS1 chr16 3037400 3059370 +2025268 MMP25 chr16 3046561 3060726 +2025319 IL32 chr16 3065297 3082192 +2025862 AC108134.3 chr16 3076911 3087111 +2025881 ZSCAN10 chr16 3088890 3099295 +2025992 AC108134.4 chr16 3106764 3109576 +2025997 ZNF213-AS1 chr16 3110460 3134882 +2026124 ZNF205 chr16 3112560 3120517 +2026219 ZNF213 chr16 3129777 3142804 +2026339 AC108134.2 chr16 3156736 3157483 +2026342 AJ003147.1 chr16 3181233 3184018 +2026346 AJ003147.2 chr16 3188204 3224779 +2026357 OR1F1 chr16 3204247 3205188 +2026364 ZNF200 chr16 3222325 3236221 +2026473 MEFV chr16 3242028 3256627 +2026753 LINC00921 chr16 3263743 3267567 +2026761 ZNF263 chr16 3263800 3301401 +2026840 TIGD7 chr16 3298808 3305729 +2026877 ZNF75A chr16 3305406 3318852 +2026975 AC004232.1 chr16 3307573 3308393 +2026978 OR2C1 chr16 3355889 3357306 +2026986 AC025283.2 chr16 3365099 3479550 +2027005 MTRNR2L4 chr16 3370979 3372668 +2027013 ZSCAN32 chr16 3382081 3401065 +2027207 ZNF174 chr16 3401215 3409364 +2027265 ZNF597 chr16 3432414 3443504 +2027279 NAA60 chr16 3443649 3486953 +2027745 C16orf90 chr16 3493484 3495489 +2027766 CLUAP1 chr16 3500976 3539048 +2027988 NLRC3 chr16 3539033 3577403 +2028143 AC004494.1 chr16 3542739 3545785 +2028149 AC006111.1 chr16 3581181 3583266 +2028153 SLX4 chr16 3581181 3611606 +2028202 DNASE1 chr16 3611728 3680143 +2028407 AC006111.2 chr16 3650636 3651703 +2028410 TRAP1 chr16 3651639 3717553 +2028656 AC006111.3 chr16 3686998 3687380 +2028659 CREBBP chr16 3725054 3880726 +2028931 AC005736.1 chr16 3930806 3950586 +2028946 ADCY9 chr16 3953387 4116442 +2029023 AC005736.2 chr16 4032012 4032936 +2029027 AC009171.2 chr16 4180117 4183515 +2029031 SRL chr16 4189374 4242080 +2029085 LINC01569 chr16 4243943 4253817 +2029118 TFAP4 chr16 4257186 4273075 +2029192 GLIS2 chr16 4314761 4339597 +2029231 GLIS2-AS1 chr16 4324667 4328340 +2029237 PAM16 chr16 4331549 4355607 +2029399 AC012676.1 chr16 4335870 4337818 +2029402 CORO7 chr16 4354542 4425705 +2030045 VASN chr16 4371848 4383538 +2030055 DNAJA3 chr16 4425805 4456775 +2030227 AC012676.3 chr16 4426902 4427380 +2030230 AC012676.4 chr16 4430522 4431103 +2030233 NMRAL1 chr16 4461680 4495763 +2030416 HMOX2 chr16 4474690 4510347 +2030678 CDIP1 chr16 4510669 4538828 +2030856 AC023830.3 chr16 4532216 4533670 +2030859 C16orf96 chr16 4556490 4600714 +2030896 AC023830.2 chr16 4560001 4561662 +2030899 UBALD1 chr16 4608883 4615027 +2030989 MGRN1 chr16 4616493 4690974 +2031344 AC023830.1 chr16 4634329 4640623 +2031348 NUDT16L1 chr16 4693694 4695859 +2031400 ANKS3 chr16 4696510 4734378 +2031953 C16orf71 chr16 4734344 4749396 +2032031 ZNF500 chr16 4748239 4767624 +2032113 SEPTIN12 chr16 4777669 4788521 +2032233 SMIM22 chr16 4788397 4796491 +2032357 AC020663.2 chr16 4795265 4796532 +2032361 ROGDI chr16 4796968 4802950 +2032586 GLYR1 chr16 4803203 4847288 +2032830 AC020663.3 chr16 4839244 4840334 +2032833 UBN1 chr16 4846665 4882401 +2033006 PPL chr16 4882507 4960741 +2033137 SEC14L5 chr16 4958330 5019157 +2033188 NAGPA-AS1 chr16 5010909 5043999 +2033195 NAGPA chr16 5024844 5034141 +2033398 ALG1 chr16 5033923 5087379 +2033577 C16orf89 chr16 5044122 5066110 +2033656 EEF2KMT chr16 5084284 5097795 +2033784 AC026458.2 chr16 5098739 5142595 +2033790 AC074051.5 chr16 5103339 5235822 +2033805 LINC02164 chr16 5215243 5220843 +2033810 RBFOX1 chr16 5239802 7713340 +2034382 LINC01570 chr16 5596856 5616373 +2034405 AC009135.1 chr16 6056975 6092954 +2034411 AC006112.1 chr16 6380476 6395578 +2034415 AC007223.1 chr16 6573767 6577359 +2034419 AC007222.2 chr16 7301605 7304638 +2034423 AC005774.2 chr16 7614230 7614992 +2034427 AC093515.1 chr16 7878799 8112756 +2034444 AC018767.2 chr16 8276263 8295700 +2034451 LINC02152 chr16 8298492 8299772 +2034454 AC018767.3 chr16 8309962 8357860 +2034460 AC018767.1 chr16 8369864 8376276 +2034465 AC074052.2 chr16 8526549 8532013 +2034469 TMEM114 chr16 8537605 8590193 +2034512 AC138420.1 chr16 8615855 8618033 +2034516 METTL22 chr16 8621683 8649654 +2034721 ABAT chr16 8674596 8784575 +2035034 TMEM186 chr16 8780384 8797642 +2035048 PMM2 chr16 8788823 8849325 +2035285 AC012173.1 chr16 8847650 8848724 +2035289 AC022167.2 chr16 8848105 8860456 +2035298 CARHSP1 chr16 8852942 8869012 +2035517 AC022167.1 chr16 8853312 8854347 +2035521 AC022167.4 chr16 8869251 8870032 +2035525 LITAFD chr16 8881634 8885351 +2035565 USP7 chr16 8892097 8964514 +2036046 AC022167.3 chr16 8962706 8966990 +2036050 AC087190.2 chr16 9068554 9072412 +2036055 C16orf72 chr16 9091644 9121635 +2036078 AC087190.3 chr16 9104848 9113181 +2036081 AC087190.1 chr16 9105834 9107174 +2036085 LINC02177 chr16 9355588 9408093 +2036111 AC012178.1 chr16 9365540 9518325 +2036228 LINC01177 chr16 9441294 9444985 +2036234 LINC01195 chr16 9446010 9455505 +2036241 AC007221.1 chr16 9541970 9614899 +2036255 AC007218.1 chr16 9666885 9676843 +2036259 GRIN2A chr16 9753404 10182754 +2036453 AC007218.2 chr16 9794637 9805571 +2036457 AC007218.3 chr16 9808856 9810726 +2036461 AC133565.1 chr16 10033684 10037297 +2036465 AC022168.1 chr16 10214784 10227581 +2036471 ATF7IP2 chr16 10326434 10483638 +2036728 AC131649.1 chr16 10351440 10352752 +2036731 LINC01290 chr16 10514842 10528202 +2036735 EMP2 chr16 10528422 10580632 +2036769 AC027277.1 chr16 10529440 10532082 +2036773 AC027277.2 chr16 10576499 10578183 +2036777 TEKT5 chr16 10627501 10694930 +2036814 AC007595.1 chr16 10691273 10692973 +2036818 NUBP1 chr16 10743786 10769351 +2036931 TVP23A chr16 10760919 10818794 +2037131 AC133065.1 chr16 10864914 10888752 +2037138 CIITA chr16 10866222 10943021 +2037463 DEXI chr16 10928891 10942468 +2037495 CLEC16A chr16 10944564 11182186 +2037695 AC007014.2 chr16 11056556 11057034 +2037698 AC007014.1 chr16 11066496 11071102 +2037703 AC007220.2 chr16 11155298 11162818 +2037707 AC007220.1 chr16 11196177 11224969 +2037712 RMI2 chr16 11249619 11381662 +2037767 SOCS1 chr16 11254405 11256200 +2037784 TNP2 chr16 11267748 11269533 +2037801 PRM3 chr16 11273199 11273629 +2037809 PRM2 chr16 11275639 11276480 +2037828 PRM1 chr16 11280841 11281330 +2037838 AC009121.4 chr16 11290569 11294906 +2037842 AC009121.3 chr16 11341809 11345211 +2037849 AC009121.2 chr16 11348143 11349321 +2037853 AC099489.1 chr16 11359845 11527245 +2038090 AC099489.3 chr16 11465260 11473174 +2038095 LITAF chr16 11547722 11636381 +2038347 SNN chr16 11668455 11679152 +2038357 TXNDC11 chr16 11679080 11742878 +2038479 AC007613.1 chr16 11741910 11744506 +2038482 ZC3H7A chr16 11750586 11797258 +2038768 AC010654.1 chr16 11797468 11798275 +2038771 BCAR4 chr16 11819829 11828845 +2038799 RSL1D1 chr16 11833850 11851580 +2038978 AC007216.4 chr16 11851649 11895611 +2038982 GSPT1 chr16 11868128 11916082 +2039188 AC007216.3 chr16 11881075 11882569 +2039191 AC007216.2 chr16 11908208 11908916 +2039195 NPIPB2 chr16 11927259 11976643 +2039304 TNFRSF17 chr16 11965210 11968068 +2039336 SNX29 chr16 11976734 12574287 +2039469 AC007216.1 chr16 11976851 11977850 +2039473 AC007601.1 chr16 12086746 12090302 +2039477 AC007601.2 chr16 12093627 12095307 +2039481 AC007598.2 chr16 12366982 12372582 +2039485 AC007598.1 chr16 12372812 12373899 +2039492 AC131391.1 chr16 12545482 12546684 +2039496 AC010333.1 chr16 12556353 12557694 +2039500 AC010333.2 chr16 12560756 12611044 +2039504 AC010333.3 chr16 12614451 12614852 +2039507 CPPED1 chr16 12659799 12803887 +2039546 AC109597.1 chr16 12745873 12757835 +2039553 AC109597.2 chr16 12759282 12761162 +2039557 SHISA9 chr16 12901598 13240416 +2039596 AC009134.1 chr16 13197606 13204907 +2039601 U91319.1 chr16 13246232 13563388 +2039641 AC003009.1 chr16 13331368 13332583 +2039645 U95743.1 chr16 13728654 13779760 +2039660 ERCC4 chr16 13920157 13952345 +2039745 AC010401.1 chr16 13930677 13935635 +2039751 AC010401.2 chr16 13953155 13954825 +2039755 LINC02185 chr16 14001320 14016056 +2039776 LINC02186 chr16 14018880 14021077 +2039781 MRTFB chr16 14071321 14266773 +2039997 AC130650.2 chr16 14150833 14153235 +2040000 AC130650.1 chr16 14191820 14200277 +2040005 MIR193BHG chr16 14301389 14331067 +2040080 LINC02130 chr16 14363109 14370266 +2040084 AC040173.1 chr16 14407668 14418908 +2040099 PARN chr16 14435700 14632728 +2041258 BFAR chr16 14632931 14669236 +2041388 PLA2G10 chr16 14672545 14694669 +2041417 AC009167.1 chr16 14695567 14707055 +2041422 NPIPA3 chr16 14708944 14726338 +2041481 AC136443.4 chr16 14734685 14746177 +2041486 NPIPA2 chr16 14748066 14765413 +2041545 NOMO1 chr16 14833721 14896157 +2041783 AC136443.3 chr16 14901499 14902174 +2041786 AC138932.2 chr16 14909887 14911345 +2041789 NPIPA1 chr16 14922802 14952060 +2041907 PDXDC1 chr16 14974591 15139339 +2042398 AC138932.5 chr16 15015828 15016390 +2042401 NTAN1 chr16 15037854 15056079 +2042579 RRN3 chr16 15060022 15094317 +2042774 AC126763.1 chr16 15154903 15157020 +2042777 NPIPA5 chr16 15363628 15381047 +2042836 MPV17L chr16 15395754 15413271 +2042874 BMERB1 chr16 15434475 15625028 +2043009 MARF1 chr16 15594387 15643154 +2043351 AC026401.1 chr16 15608474 15610563 +2043355 NDE1 chr16 15643267 15726353 +2043520 AC026401.2 chr16 15683290 15684570 +2043524 AC026401.3 chr16 15701237 15702118 +2043527 MYH11 chr16 15703135 15857028 +2044023 AF001548.2 chr16 15726674 15732993 +2044027 AF001548.1 chr16 15741151 15741791 +2044031 FOPNL chr16 15865719 15888625 +2044157 AC130651.1 chr16 15885029 15886158 +2044161 ABCC1 chr16 15949577 16143074 +2044403 ABCC6 chr16 16148928 16223522 +2044679 AC136624.1 chr16 16223027 16224261 +2044683 NOMO3 chr16 16232528 16294811 +2044989 AC136624.2 chr16 16290135 16292242 +2044993 AC138969.3 chr16 16308542 16310000 +2044996 AC138969.1 chr16 16317444 16350590 +2045147 NPIPA7 chr16 16379055 16393954 +2045182 AC136431.1 chr16 16499533 16664135 +2045189 AC136431.2 chr16 16612378 16633991 +2045193 XYLT1 chr16 17101769 17470960 +2045235 AC109446.3 chr16 17134504 17138736 +2045240 AC009152.6 chr16 17405678 17408073 +2045244 AC009152.1 chr16 17445825 17446380 +2045247 AC009152.3 chr16 17453470 17456236 +2045251 AC109495.1 chr16 17540331 17540985 +2045255 AC025277.1 chr16 17825252 17826906 +2045258 AC010601.1 chr16 17933189 18151595 +2045268 AC091489.1 chr16 18002806 18173063 +2045272 NPIPA8 chr16 18317942 18336736 +2045329 NPIPA9 chr16 18358086 18379331 +2045446 AC126755.3 chr16 18402146 18403604 +2045449 AC126755.2 chr16 18411309 18411851 +2045452 NOMO2 chr16 18417325 18562211 +2045936 AC136618.1 chr16 18570448 18571683 +2045942 RPS15A chr16 18781295 18790383 +2046103 ARL6IP1 chr16 18791669 18801572 +2046189 AC138811.1 chr16 18803083 18812181 +2046193 SMG1 chr16 18804853 18926454 +2046664 AC092287.1 chr16 18926863 18937043 +2046668 TMC7 chr16 18983934 19063942 +2046793 AC099518.4 chr16 19062144 19067691 +2046813 AC099518.2 chr16 19065991 19066694 +2046816 COQ7 chr16 19067614 19080095 +2046950 AC099518.1 chr16 19086831 19098332 +2046955 AC099518.6 chr16 19111035 19111484 +2046958 ITPRIPL2 chr16 19113932 19121629 +2046969 AC099518.5 chr16 19119976 19121629 +2046973 SYT17 chr16 19167971 19268332 +2047103 AC010494.1 chr16 19180748 19184060 +2047107 CLEC19A chr16 19285731 19322145 +2047162 AC130456.1 chr16 19315164 19316526 +2047165 LINC02858 chr16 19334011 19337804 +2047170 AC130456.2 chr16 19343647 19401693 +2047180 TMC5 chr16 19410496 19499113 +2047545 AC130456.4 chr16 19410729 19411662 +2047549 AC130456.3 chr16 19476916 19487899 +2047554 AC130456.5 chr16 19501689 19502286 +2047558 GDE1 chr16 19501693 19522123 +2047618 CCP110 chr16 19523811 19553408 +2047766 VPS35L chr16 19555240 19706793 +2048333 AC002550.2 chr16 19694035 19694428 +2048336 KNOP1 chr16 19701937 19718235 +2048384 AC002550.1 chr16 19706351 19715383 +2048388 IQCK chr16 19716456 19858467 +2048577 AC027130.1 chr16 19761172 19766099 +2048589 GPRC5B chr16 19856691 19886167 +2048690 GPR139 chr16 20031485 20073917 +2048711 AC092132.1 chr16 20208925 20209525 +2048715 GP2 chr16 20309572 20327808 +2048889 UMOD chr16 20333052 20356301 +2049083 PDILT chr16 20359175 20404737 +2049124 AC106796.1 chr16 20385957 20391164 +2049128 ACSM5 chr16 20409534 20441336 +2049211 AC137056.1 chr16 20440266 20447000 +2049220 ACSM2A chr16 20451461 20487669 +2049488 ACSM2B chr16 20536226 20576427 +2049795 AC141273.1 chr16 20580999 20586640 +2049804 ACSM3 chr16 20610243 20797581 +2049991 ACSM1 chr16 20623237 20698890 +2050126 THUMPD1 chr16 20702816 20742084 +2050197 AC004381.1 chr16 20743663 20766620 +2050202 ERI2 chr16 20780193 20900349 +2050387 REXO5 chr16 20806429 20849668 +2050748 DCUN1D3 chr16 20854925 20900358 +2050771 LYRM1 chr16 20899868 20925006 +2050909 DNAH3 chr16 20933111 21159441 +2051096 AC008551.1 chr16 21120758 21130108 +2051101 TMEM159 chr16 21158377 21180616 +2051225 AF001550.1 chr16 21194847 21205977 +2051231 ZP2 chr16 21197450 21214510 +2051339 ANKS4B chr16 21233699 21253850 +2051349 CRYM chr16 21238874 21303083 +2051484 NPIPB3 chr16 21402237 21448567 +2051618 AC005632.6 chr16 21511635 21515131 +2051622 AC005632.5 chr16 21526824 21531141 +2051626 METTL9 chr16 21597218 21657473 +2051738 AC005632.3 chr16 21626742 21627569 +2051741 IGSF6 chr16 21639550 21652608 +2051771 OTOA chr16 21663971 21761935 +2052150 AC092375.2 chr16 21794095 21795759 +2052153 NPIPB4 chr16 21834569 21880827 +2052369 AC092119.2 chr16 21950218 21951708 +2052372 UQCRC2 chr16 21953288 21983660 +2052567 PDZD9 chr16 21983865 22001110 +2052607 AC092119.3 chr16 22007480 22008062 +2052610 MOSMO chr16 22007638 22087534 +2052689 AC009019.1 chr16 22083256 22092485 +2052700 VWA3A chr16 22092538 22156964 +2052945 SDR42E2 chr16 22165583 22191754 +2052974 AC009019.2 chr16 22170309 22175524 +2052978 EEF2K chr16 22206278 22288738 +2053059 AC009034.1 chr16 22286708 22288738 +2053069 POLR3E chr16 22297375 22335101 +2053498 AC092338.3 chr16 22331039 22342938 +2053503 CDR2 chr16 22345936 22437165 +2053587 AC092338.1 chr16 22365121 22369047 +2053592 AC092338.2 chr16 22374859 22378180 +2053599 NPIPB5 chr16 22479121 22536521 +2053953 AC009021.2 chr16 22610531 22612196 +2053956 AC009021.1 chr16 22612543 22613483 +2053960 AC130466.1 chr16 22806289 22813680 +2053968 HS3ST2 chr16 22814162 22916338 +2053991 AC127459.2 chr16 23017723 23026285 +2054009 AC127459.1 chr16 23061406 23064173 +2054012 USP31 chr16 23061406 23149270 +2054071 AC099482.2 chr16 23167577 23186395 +2054077 SCNN1G chr16 23182745 23216883 +2054109 AC099482.1 chr16 23194878 23213104 +2054115 SCNN1B chr16 23278231 23381294 +2054285 COG7 chr16 23388493 23453189 +2054357 AC008915.1 chr16 23446446 23447282 +2054360 AC008915.2 chr16 23452758 23457606 +2054374 GGA2 chr16 23463542 23521995 +2054563 EARS2 chr16 23522014 23557731 +2054747 UBFD1 chr16 23557721 23574389 +2054830 AC008870.2 chr16 23568673 23569696 +2054833 NDUFAB1 chr16 23581014 23596316 +2054901 PALB2 chr16 23603160 23641310 +2055001 AC008870.4 chr16 23605841 23624107 +2055007 DCTN5 chr16 23641466 23677472 +2055113 AC008870.1 chr16 23670011 23675499 +2055120 PLK1 chr16 23677656 23690367 +2055210 AC008870.3 chr16 23687049 23687689 +2055213 ERN2 chr16 23690310 23713226 +2055381 AC012317.1 chr16 23711990 23712793 +2055385 CHP2 chr16 23755026 23758935 +2055405 PRKCB chr16 23835983 24220611 +2055545 LINC2194 chr16 24236104 24252863 +2055554 CACNG3 chr16 24255553 24362801 +2055568 AC008938.1 chr16 24472798 24495177 +2055572 RBBP6 chr16 24537693 24572863 +2055842 TNRC6A chr16 24610209 24827632 +2056127 LINC01567 chr16 24661422 24671062 +2056132 AC008731.1 chr16 24803451 24819739 +2056136 SLC5A11 chr16 24845841 24911628 +2056482 ARHGAP17 chr16 24919389 25015666 +2056739 LINC02175 chr16 25066937 25088618 +2056792 LCMT1-AS1 chr16 25085168 25111555 +2056807 AC133552.5 chr16 25106569 25107102 +2056810 LCMT1 chr16 25111731 25178231 +2056983 LCMT1-AS2 chr16 25140577 25149032 +2056990 AQP8 chr16 25215731 25228932 +2057025 ZKSCAN2 chr16 25236001 25257845 +2057070 AC008741.1 chr16 25238318 25239287 +2057074 ZKSCAN2-DT chr16 25257952 25261066 +2057077 LINC02191 chr16 25419812 25433686 +2057083 HS3ST4 chr16 25691959 26137685 +2057096 AC093516.1 chr16 25787987 26042347 +2057102 AC009158.1 chr16 26302064 26340815 +2057165 AC002331.1 chr16 26546802 26607396 +2057173 LINC02195 chr16 26584755 26594813 +2057177 AC009035.1 chr16 26721874 26729126 +2057181 C16orf82 chr16 27066707 27069165 +2057189 AC092725.1 chr16 27066928 27067858 +2057193 LINC02129 chr16 27158451 27176587 +2057199 KDM8 chr16 27203495 27221768 +2057312 AC109449.1 chr16 27213308 27214993 +2057315 NSMCE1 chr16 27224994 27268772 +2057474 NSMCE1-DT chr16 27268205 27290492 +2057494 AC106739.1 chr16 27313387 27314101 +2057497 IL4R chr16 27313668 27364778 +2057743 IL21R chr16 27402174 27452042 +2057824 IL21R-AS1 chr16 27447669 27453393 +2057829 GTF3C1 chr16 27459555 27549913 +2058071 KIAA0556 chr16 27550133 27780369 +2058210 AC002551.1 chr16 27643199 27644663 +2058214 AC016597.1 chr16 27678940 27718806 +2058235 AC016597.2 chr16 27687182 27687522 +2058238 GSG1L chr16 27787528 28063714 +2058325 XPO6 chr16 28097979 28211920 +2058585 AC138904.3 chr16 28258686 28292173 +2058589 SBK1 chr16 28259246 28323849 +2058615 AC138904.1 chr16 28284885 28292064 +2058619 NPIPB6 chr16 28342555 28363508 +2058658 EIF3CL chr16 28379579 28403879 +2058753 AC138894.2 chr16 28454141 28454511 +2058756 NPIPB7 chr16 28456372 28471175 +2058812 CLN3 chr16 28474111 28495575 +2060119 APOBR chr16 28494643 28498970 +2060148 IL27 chr16 28499362 28512051 +2060175 NUPR1 chr16 28532708 28539174 +2060211 AC020765.2 chr16 28553709 28554140 +2060214 SGF29 chr16 28553915 28591790 +2060290 SULT1A2 chr16 28591943 28597050 +2060378 SULT1A1 chr16 28605196 28623625 +2060596 NPIPB8 chr16 28637654 28658682 +2060625 EIF3C chr16 28688558 28735730 +2060931 NPIPB9 chr16 28751787 28772807 +2060972 AC145285.2 chr16 28802743 28817828 +2060976 AC145285.3 chr16 28820570 28822033 +2060980 AC145285.6 chr16 28822431 28823969 +2060983 ATXN2L chr16 28823035 28837237 +2061545 AC133550.2 chr16 28830612 28837200 +2061549 TUFM chr16 28842411 28846348 +2061601 SH2B1 chr16 28846600 28874212 +2061848 AC133550.3 chr16 28862166 28863340 +2061852 ATP2A1 chr16 28878405 28904509 +2062057 ATP2A1-AS1 chr16 28878957 28879920 +2062064 RABEP2 chr16 28904421 28936526 +2062236 CD19 chr16 28931939 28939347 +2062332 NFATC2IP chr16 28950807 28967097 +2062395 AC109460.2 chr16 28952816 28966883 +2062405 AC109460.1 chr16 28973962 28978824 +2062409 SPNS1 chr16 28974221 28984548 +2062644 LAT chr16 28984826 28990783 +2062942 AC109460.4 chr16 28989140 28990778 +2062946 AC009093.2 chr16 29139661 29216706 +2062953 AC009093.1 chr16 29215385 29221040 +2062967 AC009093.5 chr16 29225594 29226348 +2062971 AC009093.4 chr16 29262273 29264479 +2062975 AC009093.6 chr16 29272220 29272772 +2062978 NPIPB11 chr16 29381354 29404029 +2063017 BOLA2 chr16 29443056 29454964 +2063046 SLX1B chr16 29454501 29458219 +2063097 SULT1A4 chr16 29459889 29464976 +2063174 NPIPB12 chr16 29483642 29505999 +2063304 SPN chr16 29662979 29670876 +2063352 QPRT chr16 29663279 29698699 +2063400 C16orf54 chr16 29742463 29745990 +2063409 AC009133.3 chr16 29745247 29748299 +2063413 ZG16 chr16 29778256 29782973 +2063427 KIF22 chr16 29790719 29805385 +2063614 AC009133.4 chr16 29804430 29804990 +2063617 MAZ chr16 29806106 29811164 +2063810 AC009133.2 chr16 29806496 29807732 +2063814 AC009133.1 chr16 29808636 29821252 +2063834 PRRT2 chr16 29811382 29815892 +2064021 PAGR1 chr16 29816152 29822489 +2064033 MVP chr16 29820394 29848039 +2064253 CDIPT chr16 29858357 29863414 +2064385 AC120114.2 chr16 29862760 29863417 +2064388 SEZ6L2 chr16 29871159 29899547 +2064617 ASPHD1 chr16 29900375 29919864 +2064694 KCTD13 chr16 29905012 29926236 +2064824 AC120114.1 chr16 29926836 29928933 +2064828 TMEM219 chr16 29940885 29973050 +2064941 TAOK2 chr16 29973868 29992261 +2065089 HIRIP3 chr16 29992330 29996074 +2065147 INO80E chr16 29995715 30005793 +2065342 DOC2A chr16 30005514 30023270 +2065621 C16orf92 chr16 30023334 30027736 +2065666 TLCD3B chr16 30024427 30052978 +2065755 AC093512.2 chr16 30053090 30070420 +2065933 ALDOA chr16 30064164 30070457 +2066210 AC093512.1 chr16 30064306 30064825 +2066213 PPP4C chr16 30075978 30085376 +2066411 TBX6 chr16 30085793 30091887 +2066511 YPEL3 chr16 30092314 30096915 +2066643 AC012645.1 chr16 30096430 30104116 +2066647 GDPD3 chr16 30104810 30113537 +2066704 AC012645.2 chr16 30107675 30110541 +2066708 AC012645.4 chr16 30110895 30111955 +2066711 MAPK3 chr16 30114105 30123506 +2066935 CORO1A chr16 30182827 30189076 +2067125 AC012645.3 chr16 30183505 30184957 +2067137 BOLA2B chr16 30192932 30194306 +2067183 SLX1A chr16 30193887 30197561 +2067241 SULT1A3 chr16 30199228 30204310 +2067353 NPIPB13 chr16 30222937 30254510 +2067452 CD2BP2 chr16 30350773 30355308 +2067493 CD2BP2-DT chr16 30355441 30357104 +2067497 TBC1D10B chr16 30357102 30370494 +2067560 AC106782.5 chr16 30359825 30360336 +2067563 MYLPF chr16 30370934 30377991 +2067635 ZNF48 chr16 30378106 30400108 +2067686 SEPTIN1 chr16 30378133 30395991 +2067826 ZNF771 chr16 30407414 30431108 +2067869 DCTPP1 chr16 30423615 30430030 +2067921 SEPHS2 chr16 30443631 30445874 +2067930 ITGAL chr16 30472719 30523185 +2068239 AC116348.3 chr16 30477180 30489353 +2068244 AC116348.1 chr16 30480588 30481346 +2068248 AC116348.2 chr16 30498766 30499554 +2068252 ZNF768 chr16 30524004 30526821 +2068271 ZNF747 chr16 30530367 30535347 +2068301 AC002310.1 chr16 30534752 30537149 +2068311 ZNF764 chr16 30553764 30558498 +2068337 ZNF688 chr16 30569346 30572734 +2068393 AC002310.2 chr16 30572039 30583860 +2068404 ZNF785 chr16 30573740 30585769 +2068447 AC093249.2 chr16 30585907 30608593 +2068451 ZNF689 chr16 30602558 30624012 +2068483 PRR14 chr16 30650717 30656440 +2068626 FBRS chr16 30658431 30670810 +2068747 AC093249.6 chr16 30697707 30699058 +2068757 SRCAP chr16 30698209 30741409 +2068947 TMEM265 chr16 30740642 30745196 +2068959 PHKG2 chr16 30748293 30761176 +2069124 CCDC189 chr16 30757423 30762221 +2069258 RNF40 chr16 30761745 30776307 +2069485 ZNF629 chr16 30778456 30787205 +2069497 AC106886.3 chr16 30821338 30821884 +2069500 BCL7C chr16 30833626 30894960 +2069568 MIR762HG chr16 30875222 30895220 +2069596 AC135048.2 chr16 30875766 30895216 +2069600 CTF1 chr16 30896607 30903560 +2069623 FBXL19-AS1 chr16 30919319 30923269 +2069626 FBXL19 chr16 30923055 30948783 +2069806 ORAI3 chr16 30949068 30956461 +2069847 AC135048.3 chr16 30956872 30957199 +2069850 SETD1A chr16 30957754 30984664 +2069906 HSD3B7 chr16 30985207 30989147 +2069969 STX1B chr16 30989256 31010638 +2070020 STX4 chr16 31032889 31042975 +2070213 AC135050.3 chr16 31043150 31049868 +2070217 AC135050.1 chr16 31056460 31062803 +2070223 ZNF668 chr16 31060843 31074240 +2070320 AC135050.4 chr16 31065495 31069246 +2070324 ZNF646 chr16 31074422 31084196 +2070357 PRSS53 chr16 31083425 31089628 +2070393 VKORC1 chr16 31090842 31095980 +2070474 BCKDK chr16 31106107 31112791 +2070662 KAT8 chr16 31114489 31131393 +2070782 AC135050.5 chr16 31118078 31118747 +2070786 AC135050.6 chr16 31122235 31124064 +2070792 AC009088.3 chr16 31131433 31131877 +2070796 PRSS8 chr16 31131433 31135727 +2070860 PRSS36 chr16 31138926 31150083 +2071002 FUS chr16 31180110 31194871 +2071192 AC009088.2 chr16 31182511 31183285 +2071196 AC009088.1 chr16 31196131 31196963 +2071199 PYCARD chr16 31201486 31203450 +2071230 PYCARD-AS1 chr16 31201885 31203452 +2071234 TRIM72 chr16 31214091 31231537 +2071273 PYDC1 chr16 31215962 31217359 +2071286 ITGAM chr16 31259967 31332892 +2071453 ITGAX chr16 31355134 31382997 +2071636 ITGAD chr16 31393335 31426505 +2071715 AC093520.1 chr16 31402565 31404699 +2071719 COX6A2 chr16 31427731 31428360 +2071734 AC026471.5 chr16 31428180 31428646 +2071737 ZNF843 chr16 31432593 31443160 +2071767 AC026471.4 chr16 31449535 31453493 +2071771 AC026471.1 chr16 31456711 31459736 +2071774 ARMC5 chr16 31458080 31467166 +2071893 TGFB1I1 chr16 31471585 31477960 +2072154 SLC5A2 chr16 31483002 31490860 +2072253 AC026471.3 chr16 31487370 31488492 +2072257 C16orf58 chr16 31489471 31509309 +2072454 AC026471.2 chr16 31508464 31509560 +2072461 AHSP chr16 31527900 31528803 +2072486 LINC02190 chr16 31542748 31553604 +2072500 AC106730.1 chr16 31546698 31547237 +2072503 AC074050.2 chr16 31699676 31700465 +2072508 AC074050.4 chr16 31704728 31705260 +2072511 AC074050.3 chr16 31709113 31711984 +2072515 ZNF720 chr16 31713229 31794869 +2072656 AC002519.1 chr16 31788202 31790993 +2072659 ZNF267 chr16 31873807 31917357 +2072729 IGHV1OR16-1 chr16 32034853 32035326 +2072733 IGHV1OR16-3 chr16 32059084 32059372 +2072737 IGHV3OR16-9 chr16 32066065 32066358 +2072744 AC133485.7 chr16 32126432 32132724 +2072753 AC133485.5 chr16 32188333 32193530 +2072757 AC133485.3 chr16 32250620 32254422 +2072761 TP53TG3D chr16 32252719 32255922 +2072818 AC133485.2 chr16 32262827 32265514 +2072825 AC138915.3 chr16 32454612 32458758 +2072828 AC138907.7 chr16 32649193 32663956 +2072837 AC138907.1 chr16 32663925 32666533 +2072844 TP53TG3 chr16 32673528 32676732 +2072899 AC138907.3 chr16 32675037 32678831 +2072903 AC138907.2 chr16 32735909 32741094 +2072907 AC137761.1 chr16 32809556 32824645 +2072913 IGHV2OR16-5 chr16 32847713 32848156 +2072920 AC142086.1 chr16 32882586 32888874 +2072936 IGHV3OR16-15 chr16 32903442 32903894 +2072940 IGHV3OR16-6 chr16 32915074 32915536 +2072944 IGHV1OR16-2 chr16 32978461 32978891 +2072948 IGHV3OR16-10 chr16 32995048 32995505 +2072955 AC142086.4 chr16 32995537 32996770 +2072960 IGHV1OR16-4 chr16 33002333 33002621 +2072964 IGHV3OR16-8 chr16 33009175 33009620 +2072971 AC145350.2 chr16 33043609 33095431 +2072981 AC145350.4 chr16 33129316 33134499 +2072985 AC138869.2 chr16 33191561 33195354 +2072989 TP53TG3C chr16 33193659 33196858 +2073042 AC138869.3 chr16 33203773 33206462 +2073049 AC141257.2 chr16 33206431 33330342 +2073054 TP53TG3E chr16 33303739 33306935 +2073073 TP53TG3B chr16 33360274 33363478 +2073116 AC141257.1 chr16 33370473 33372915 +2073123 TP53TG3F chr16 33459045 33462249 +2073142 AC136944.1 chr16 33533816 33534976 +2073146 AC136944.2 chr16 33541842 33545812 +2073149 AC136944.4 chr16 33548297 33554408 +2073154 IGHV3OR16-12 chr16 33802764 33803217 +2073161 IGHV3OR16-13 chr16 33827214 33827661 +2073168 AC136428.1 chr16 33844784 33845229 +2073175 AC140658.2 chr16 33857935 33858864 +2073180 IGHV3OR16-11 chr16 33858896 33859352 +2073184 IGHV3OR16-7 chr16 33938337 33938799 +2073188 AC140658.1 chr16 33964547 33976346 +2073208 LINC00273 chr16 34158585 34160036 +2073211 FP325313.3 chr16 34387599 34389827 +2073214 LINC02184 chr16 34978744 34979844 +2073218 AC135776.1 chr16 35021749 35024229 +2073221 AC135776.2 chr16 35022851 35024250 +2073225 AC023824.5 chr16 35143722 35146129 +2073238 AC023824.1 chr16 35192687 35195661 +2073241 AC023824.4 chr16 35195779 35197544 +2073244 AC023824.3 chr16 35207884 35284146 +2073258 LINC01566 chr16 35363412 35390584 +2073275 AC018558.6 chr16 35450898 35452987 +2073279 AC018558.2 chr16 35491174 35492395 +2073283 AC018558.3 chr16 35493754 35496457 +2073288 AC018558.7 chr16 35499494 35522465 +2073294 AC018558.1 chr16 35504370 35506567 +2073325 AC092325.1 chr16 35640029 35640582 +2073328 LINC02167 chr16 35743268 35756515 +2073342 AC106785.2 chr16 35785569 35786887 +2073345 SHCBP1 chr16 46578591 46621379 +2073411 AC092368.3 chr16 46622861 46624451 +2073417 VPS35 chr16 46656132 46689518 +2073592 AC012186.2 chr16 46660696 46661591 +2073596 ORC6 chr16 46689643 46698394 +2073695 MYLK3 chr16 46702282 46790407 +2073780 C16orf87 chr16 46796603 46831180 +2073823 GPT2 chr16 46884362 46931289 +2073906 DNAJA2 chr16 46955362 46973674 +2073967 AC018845.3 chr16 46973989 46978983 +2073971 AC018845.1 chr16 47004513 47035385 +2073976 NETO2 chr16 47077703 47143945 +2074052 ITFG1-AS1 chr16 47144323 47162749 +2074064 ITFG1 chr16 47154387 47464149 +2074249 AC007494.2 chr16 47196311 47202429 +2074253 AC007533.1 chr16 47299447 47317814 +2074258 PHKB chr16 47461123 47701523 +2074602 AC007599.2 chr16 47529190 47529916 +2074606 LINC02133 chr16 47724568 47908431 +2074618 LINC02192 chr16 47849314 47887130 +2074622 LINC02134 chr16 47965620 47971693 +2074631 AC096996.3 chr16 48050588 48055099 +2074635 ABCC12 chr16 48081006 48156018 +2075081 AC096996.2 chr16 48164952 48167238 +2075086 ABCC11 chr16 48166910 48247568 +2075392 LONP2 chr16 48244300 48363122 +2075565 SIAH1 chr16 48356364 48448402 +2075629 AC026470.3 chr16 48447904 48448398 +2075633 N4BP1 chr16 48538726 48620148 +2075678 AC026470.2 chr16 48559661 48587403 +2075683 AC023813.1 chr16 48620319 48622033 +2075687 AC007611.1 chr16 48623422 48746318 +2075701 AC023813.3 chr16 48637143 48638719 +2075705 AC023813.4 chr16 48640473 48641052 +2075708 AC044798.3 chr16 49072543 49275579 +2075717 AC044798.1 chr16 49159508 49162023 +2075721 AC044798.2 chr16 49170552 49171786 +2075724 CBLN1 chr16 49277917 49281838 +2075758 AC007614.1 chr16 49282021 49350504 +2076251 C16orf78 chr16 49373804 49399431 +2076267 AC007861.1 chr16 49442910 49454109 +2076277 AC007861.2 chr16 49454229 49457269 +2076281 LINC02179 chr16 49466106 49469875 +2076285 ZNF423 chr16 49487524 49857919 +2076432 AC027348.1 chr16 49847018 49847632 +2076435 AC007603.1 chr16 49920730 49924154 +2076439 CNEP1R1 chr16 50024410 50037088 +2076595 AC007610.1 chr16 50046429 50066224 +2076600 HEATR3 chr16 50065970 50107272 +2076656 AC007610.2 chr16 50100339 50121943 +2076661 AC007610.5 chr16 50120064 50129904 +2076665 TENT4B chr16 50152918 50235310 +2076762 ADCY7 chr16 50246137 50318135 +2077055 BRD7 chr16 50313487 50368934 +2077174 AC007493.2 chr16 50368580 50371480 +2077178 LINC02178 chr16 50390916 50395133 +2077182 AC007493.1 chr16 50407184 50546347 +2077218 NKD1 chr16 50548396 50649249 +2077256 AC007608.2 chr16 50551824 50553940 +2077260 AC007608.1 chr16 50606076 50613684 +2077264 AC007608.3 chr16 50664903 50671639 +2077272 SNX20 chr16 50666300 50681353 +2077342 NOD2 chr16 50693588 50734041 +2077533 AC007728.3 chr16 50712844 50713589 +2077536 AC007728.2 chr16 50727417 50742815 +2077547 CYLD chr16 50742050 50801935 +2077908 AC007728.1 chr16 50783859 50803338 +2077916 LINC02168 chr16 50806668 50807629 +2077920 LINC02128 chr16 50840017 50901063 +2078056 AC025810.1 chr16 50856614 50879278 +2078060 LINC02127 chr16 51017544 51035784 +2078090 AC027688.1 chr16 51035118 51038764 +2078096 AC027688.2 chr16 51054728 51056399 +2078100 AC009166.3 chr16 51089466 51095952 +2078105 SALL1 chr16 51135975 51151367 +2078148 AC009166.1 chr16 51149239 51149819 +2078152 AC087564.1 chr16 51150770 51442519 +2078182 AC137494.1 chr16 51197804 51268117 +2078187 AC007344.1 chr16 51354456 51525157 +2078201 HNRNPA1P48 chr16 51553436 51647132 +2078213 LINC01571 chr16 51755325 51788208 +2078227 C16orf97 chr16 52005487 52078474 +2078259 AC009039.1 chr16 52078622 52080489 +2078263 LINC00919 chr16 52083064 52085109 +2078274 LINC02180 chr16 52085210 52099120 +2078333 AC007333.2 chr16 52198012 52227956 +2078337 AC007333.1 chr16 52238081 52269574 +2078362 CASC22 chr16 52258564 52280638 +2078424 TOX3 chr16 52436417 52547802 +2078492 CASC16 chr16 52552084 52652132 +2078519 AC026462.5 chr16 52583694 52588879 +2078525 AC026462.3 chr16 52607006 52614640 +2078567 AC026462.2 chr16 52607762 52608158 +2078571 AC026462.4 chr16 52622115 52677747 +2078598 AC007906.2 chr16 53035690 53052873 +2078614 CHD9 chr16 53055033 53329150 +2079244 AC007906.1 chr16 53168522 53169450 +2079248 AC007342.4 chr16 53373479 53385019 +2079256 AC007342.5 chr16 53386944 53389085 +2079259 RBL2 chr16 53433977 53491648 +2079392 AC007342.1 chr16 53448748 53449590 +2079396 AKTIP chr16 53491040 53504411 +2079573 AC007497.2 chr16 53544339 53545689 +2079577 RPGRIP1L chr16 53598153 53703938 +2079940 AC007497.1 chr16 53628256 53628816 +2079943 FTO chr16 53701692 54158512 +2080294 AC007496.2 chr16 53981229 53981912 +2080298 AC007496.1 chr16 53998313 53999969 +2080302 AC007347.1 chr16 54033997 54054583 +2080307 AC007907.1 chr16 54239693 54240654 +2080311 LINC02169 chr16 54245544 54270879 +2080321 IRX3 chr16 54283304 54286787 +2080347 AC018553.2 chr16 54285604 54289568 +2080351 AC018553.1 chr16 54290965 54292422 +2080354 LINC02140 chr16 54365996 54370794 +2080374 AC018553.3 chr16 54370265 54374728 +2080379 AC007343.1 chr16 54490281 54491396 +2080383 LINC02183 chr16 54542808 54559100 +2080391 AC007491.1 chr16 54628963 54657662 +2080402 CRNDE chr16 54845189 54929189 +2080517 AC106742.1 chr16 54847316 54854991 +2080522 IRX5 chr16 54930865 54934485 +2080569 AC106738.1 chr16 54934913 54954665 +2080573 AC106738.2 chr16 54937786 54938671 +2080580 AC109136.1 chr16 55045700 55049318 +2080585 AC109462.1 chr16 55259969 55333588 +2080591 AC109462.3 chr16 55321575 55322686 +2080596 IRX6 chr16 55323760 55330760 +2080620 AC109462.2 chr16 55332355 55332967 +2080623 MMP2 chr16 55389700 55506691 +2080794 AC007336.2 chr16 55425574 55426130 +2080797 MMP2-AS1 chr16 55426797 55462297 +2080815 LPCAT2 chr16 55509072 55586666 +2080895 AC007336.1 chr16 55538200 55542027 +2080898 CAPNS2 chr16 55566684 55567687 +2080906 SLC6A2 chr16 55655604 55706192 +2081167 CES1 chr16 55802851 55833337 +2081318 CES5A chr16 55846154 55956031 +2081548 AC040168.1 chr16 55984009 56191118 +2081607 AC007495.1 chr16 56109537 56137000 +2081616 GNAO1 chr16 56191489 56357444 +2081905 AC079411.1 chr16 56192614 56194518 +2081908 AC009102.4 chr16 56282886 56299351 +2081914 AC009102.1 chr16 56300616 56302904 +2081918 AC009102.2 chr16 56351886 56353524 +2081921 AMFR chr16 56361452 56425545 +2082045 AC092140.1 chr16 56409320 56411683 +2082049 NUDT21 chr16 56429133 56452199 +2082106 OGFOD1 chr16 56451521 56479104 +2082272 AC092140.2 chr16 56465642 56466162 +2082275 BBS2 chr16 56466836 56520087 +2082499 MT4 chr16 56565073 56568957 +2082511 MT3 chr16 56589074 56591088 +2082562 MT2A chr16 56608584 56609497 +2082592 AC026461.3 chr16 56609501 56611375 +2082596 MT1E chr16 56625475 56627112 +2082626 MT1M chr16 56632659 56633981 +2082645 MT1A chr16 56638666 56640087 +2082657 MT1B chr16 56651886 56653204 +2082680 MT1F chr16 56657731 56660698 +2082708 MT1G chr16 56666731 56668065 +2082749 MT1H chr16 56669814 56671129 +2082770 MT1X chr16 56682470 56684196 +2082804 AC106779.1 chr16 56708450 56730010 +2082817 NUP93 chr16 56730118 56850286 +2083180 SLC12A3 chr16 56865207 56915850 +2083415 HERPUD1 chr16 56932142 56944864 +2083615 AC012181.2 chr16 56940278 56941342 +2083619 AC012181.1 chr16 56941028 56941726 +2083622 CETP chr16 56961923 56983845 +2083748 NLRC5 chr16 56989485 57083531 +2084700 AC023825.2 chr16 57052505 57058497 +2084704 AC009090.2 chr16 57091213 57092303 +2084708 CPNE2 chr16 57092583 57148369 +2084883 FAM192A chr16 57152466 57186116 +2085175 AC009090.6 chr16 57177349 57181390 +2085179 RSPRY1 chr16 57186137 57240469 +2085334 ARL2BP chr16 57245259 57253635 +2085385 AC009090.3 chr16 57245832 57246396 +2085388 AC009090.1 chr16 57247350 57248492 +2085392 PLLP chr16 57248547 57284672 +2085444 CCL22 chr16 57358783 57366189 +2085456 CX3CL1 chr16 57372477 57385044 +2085497 CCL17 chr16 57404767 57416063 +2085522 CIAPIN1 chr16 57428187 57447420 +2085733 COQ9 chr16 57447425 57461270 +2085908 POLR2C chr16 57462660 57472009 +2085986 DOK4 chr16 57471922 57487327 +2086225 CCDC102A chr16 57512181 57536571 +2086253 ADGRG5 chr16 57542643 57591681 +2086361 ADGRG1 chr16 57610652 57665580 +2087402 AC018552.3 chr16 57622034 57631647 +2087408 ADGRG3 chr16 57668277 57689378 +2087523 AC018552.2 chr16 57681124 57701730 +2087531 DRC7 chr16 57694793 57731805 +2087734 KATNB1 chr16 57735739 57757244 +2087898 KIFC3 chr16 57758217 57863053 +2088532 AC092118.2 chr16 57759358 57760024 +2088535 AC092118.1 chr16 57798186 57816946 +2088547 CNGB1 chr16 57882340 57971128 +2088779 TEPP chr16 57976435 57988116 +2088835 ZNF319 chr16 57994668 58000453 +2088852 USB1 chr16 57999546 58021618 +2089005 MMP15 chr16 58025754 58046901 +2089038 CFAP20 chr16 58113592 58129381 +2089087 AC026771.1 chr16 58116885 58119353 +2089091 AC009107.2 chr16 58129519 58163246 +2089106 CSNK2A2 chr16 58157907 58198106 +2089198 AC009107.1 chr16 58197112 58217805 +2089202 CCDC113 chr16 58231157 58283836 +2089295 PRSS54 chr16 58279997 58295047 +2089384 GINS3 chr16 58295080 58406144 +2089442 AC009118.1 chr16 58382989 58383798 +2089446 AC009118.2 chr16 58392153 58392807 +2089449 LINC02137 chr16 58421326 58462470 +2089463 NDRG4 chr16 58462846 58513628 +2090357 SETD6 chr16 58515479 58521181 +2090510 CNOT1 chr16 58519951 58629885 +2091062 AC009118.3 chr16 58522970 58523842 +2091065 SLC38A7 chr16 58665109 58684770 +2091288 GOT2 chr16 58707131 58734342 +2091371 AC106793.1 chr16 58733910 59199395 +2091390 AC092378.1 chr16 58847715 58880351 +2091402 LINC02141 chr16 59855353 60053973 +2091408 AC009081.2 chr16 60346478 60499364 +2091463 AC009081.1 chr16 60486819 60523250 +2091468 AC092125.2 chr16 61638233 61642577 +2091472 CDH8 chr16 61647242 62037035 +2091660 AC092125.1 chr16 61691756 61693750 +2091663 AC012174.1 chr16 61918321 61940697 +2091669 AC009110.1 chr16 62596372 62598449 +2091673 AC040174.1 chr16 63056786 63129654 +2091685 AC040174.2 chr16 63066526 63066990 +2091688 AC138305.1 chr16 63314264 63618046 +2091709 AC138305.2 chr16 63368844 63369456 +2091713 LINC02165 chr16 63730205 63755884 +2091742 AC092337.1 chr16 63935778 63936906 +2091745 AC093536.2 chr16 64155169 64156574 +2091748 AC012322.1 chr16 64242608 64343909 +2091755 AC092131.1 chr16 64364781 64600247 +2091762 CDH11 chr16 64943753 65126112 +2091953 LINC02126 chr16 65141751 65176713 +2091964 AC009055.2 chr16 65190973 65234914 +2091973 AC009055.1 chr16 65233056 65432820 +2091980 LINC00922 chr16 65284496 65576345 +2092050 AC092138.2 chr16 65580668 65646947 +2092055 AC092138.1 chr16 65601101 65601698 +2092059 AC022164.1 chr16 65861112 65863784 +2092062 AC012325.1 chr16 66327349 66335138 +2092067 CDH5 chr16 66366622 66404784 +2092237 LINC00920 chr16 66408524 66412135 +2092241 BEAN1 chr16 66427295 66493529 +2092351 BEAN1-AS1 chr16 66469796 66481230 +2092365 TK2 chr16 66508003 66552544 +2092747 AC010542.2 chr16 66509437 66510048 +2092751 AC010542.4 chr16 66549280 66551189 +2092754 CKLF chr16 66552563 66566251 +2092830 AC010542.5 chr16 66565620 66566001 +2092833 CMTM1 chr16 66566393 66579137 +2093079 CMTM2 chr16 66579448 66588275 +2093120 AC010542.1 chr16 66579983 66580716 +2093124 CMTM3 chr16 66603874 66613892 +2093327 CMTM4 chr16 66614750 66696707 +2093384 DYNC1LI2 chr16 66720893 66751609 +2093570 AC018557.1 chr16 66720897 66731785 +2093574 AC018557.3 chr16 66729152 66741416 +2093578 AC018557.2 chr16 66738238 66739722 +2093585 AC044802.1 chr16 66751752 66754740 +2093589 TERB1 chr16 66754976 66801620 +2093747 NAE1 chr16 66802875 66873256 +2094134 AC044802.2 chr16 66841433 66853448 +2094138 CA7 chr16 66844414 66854153 +2094194 PDP2 chr16 66878589 66895754 +2094254 CDH16 chr16 66908122 66918917 +2094550 RRAD chr16 66921679 66925536 +2094601 CIAO2B chr16 66932065 66934423 +2094669 CES2 chr16 66934444 66945096 +2094871 CES3 chr16 66961245 66975149 +2095008 CES4A chr16 66988589 67009758 +2095228 CBFB chr16 67028984 67101058 +2095362 C16orf70 chr16 67109941 67148544 +2095540 B3GNT9 chr16 67148104 67150998 +2095550 TRADD chr16 67154185 67159909 +2095587 FBXL8 chr16 67159932 67164570 +2095675 HSF4 chr16 67164681 67169945 +2096063 NOL3 chr16 67170154 67175735 +2096177 KIAA0895L chr16 67175599 67184040 +2096284 EXOC3L1 chr16 67184379 67190185 +2096422 E2F4 chr16 67192155 67198918 +2096549 ELMO3 chr16 67199111 67204029 +2096757 LRRC29 chr16 67207139 67227048 +2096854 TMEM208 chr16 67227103 67229278 +2096961 FHOD1 chr16 67229387 67247481 +2097111 SLC9A5 chr16 67237683 67272191 +2097263 PLEKHG4 chr16 67277510 67289499 +2097597 KCTD19 chr16 67289428 67326760 +2097732 LRRC36 chr16 67326798 67385204 +2098025 TPPP3 chr16 67389809 67393518 +2098081 ZDHHC1 chr16 67394152 67416833 +2098159 HSD11B2 chr16 67430652 67437553 +2098192 AC009061.1 chr16 67430667 67431464 +2098196 ATP6V0D1 chr16 67438014 67481181 +2098436 AC009061.2 chr16 67481314 67505977 +2098463 AGRP chr16 67482571 67483813 +2098477 AC027682.6 chr16 67517862 67528675 +2098484 RIPOR1 chr16 67518418 67546788 +2098933 AC027682.5 chr16 67538557 67540106 +2098938 AC027682.2 chr16 67542123 67542963 +2098942 AC027682.3 chr16 67542304 67542572 +2098946 AC027682.4 chr16 67549214 67563958 +2098952 AC027682.1 chr16 67561411 67562309 +2098955 CTCF chr16 67562467 67639177 +2099266 AC009095.1 chr16 67614381 67616146 +2099270 CARMIL2 chr16 67644988 67657569 +2099519 ACD chr16 67657512 67660815 +2099741 PARD6A chr16 67660946 67662778 +2099778 ENKD1 chr16 67662945 67667265 +2099840 C16orf86 chr16 67666814 67668757 +2099891 GFOD2 chr16 67674531 67719339 +2099956 RANBP10 chr16 67723070 67806652 +2100171 AC010530.1 chr16 67738588 67739922 +2100175 TSNAXIP1 chr16 67806765 67832148 +2100472 CENPT chr16 67828157 67847811 +2100893 THAP11 chr16 67842320 67844195 +2100901 NUTF2 chr16 67846923 67872567 +2100977 EDC4 chr16 67873052 67884499 +2101183 NRN1L chr16 67884885 67888855 +2101213 PSKH1 chr16 67893254 67929676 +2101237 CTRL chr16 67927640 67932365 +2101309 PSMB10 chr16 67934506 67936864 +2101359 LCAT chr16 67939750 67944131 +2101451 SLC12A4 chr16 67943474 67969601 +2101894 DPEP3 chr16 67975663 67980549 +2101948 DPEP2 chr16 67987394 68000586 +2102081 DUS2 chr16 67987746 68079320 +2102386 DPEP2NB chr16 68013436 68015911 +2102396 DDX28 chr16 68021274 68023442 +2102404 NFATC3 chr16 68084751 68229259 +2102733 AC020978.6 chr16 68199795 68200981 +2102736 AC020978.3 chr16 68212401 68221671 +2102740 AC020978.7 chr16 68224713 68227734 +2102743 AC020978.5 chr16 68225969 68229145 +2102746 ESRP2 chr16 68229033 68238102 +2102903 AC020978.4 chr16 68236845 68237667 +2102907 PLA2G15 chr16 68245304 68261058 +2103037 AC020978.2 chr16 68256162 68260443 +2103045 SLC7A6 chr16 68264516 68301823 +2103297 SLC7A6OS chr16 68284503 68310946 +2103343 PRMT7 chr16 68310974 68358563 +2103706 AC020978.1 chr16 68316801 68319036 +2103710 SMPD3 chr16 68358327 68448508 +2103823 AC099521.3 chr16 68448843 68450002 +2103827 AC099521.1 chr16 68450283 68452318 +2103830 ZFP90 chr16 68530090 68576072 +2104049 AC126773.3 chr16 68573782 68589512 +2104053 AC126773.6 chr16 68591382 68594424 +2104056 CDH3 chr16 68636189 68722616 +2104227 AC126773.4 chr16 68644248 68646168 +2104231 CDH1 chr16 68737292 68835541 +2104527 AC099314.1 chr16 68814330 68823526 +2104532 TANGO6 chr16 68843531 69085182 +2104626 AC009137.1 chr16 68927547 68948261 +2104630 AC009137.2 chr16 68933820 68937725 +2104634 HAS3 chr16 69105653 69118719 +2104684 DERPC chr16 69118010 69132151 +2104707 CHTF8 chr16 69118010 69132578 +2104785 UTP4 chr16 69131291 69231130 +2105041 SNTB2 chr16 69187129 69309052 +2105112 AC026474.1 chr16 69240549 69241929 +2105116 VPS4A chr16 69311350 69326939 +2105154 COG8 chr16 69320140 69339667 +2105230 PDF chr16 69326913 69330588 +2105240 NIP7 chr16 69337996 69343106 +2105310 TMED6 chr16 69343250 69351786 +2105327 TERF2 chr16 69355567 69408571 +2105470 CYB5B chr16 69424525 69466266 +2105545 AC026464.2 chr16 69463844 69466264 +2105548 NFAT5 chr16 69565094 69704666 +2105893 AC009032.1 chr16 69632141 69632571 +2105896 AC012321.1 chr16 69703065 69704652 +2105899 NQO1 chr16 69706996 69726668 +2105998 AC092115.2 chr16 69709874 69710583 +2106002 AC092115.3 chr16 69727013 69742563 +2106006 NOB1 chr16 69741871 69754926 +2106083 WWP2 chr16 69762306 69941741 +2106397 CLEC18A chr16 69950705 69964452 +2106581 PDPR chr16 70113626 70162537 +2106838 AC009060.1 chr16 70138337 70173483 +2106854 CLEC18C chr16 70173322 70187361 +2107065 EXOSC6 chr16 70246778 70251940 +2107073 AARS chr16 70252295 70289543 +2107159 DDX19B chr16 70289663 70335283 +2107476 AC012184.3 chr16 70315442 70346806 +2107492 DDX19A chr16 70346861 70373383 +2107714 AC012184.4 chr16 70349085 70372166 +2107722 ST3GAL2 chr16 70375977 70439237 +2107775 AC012184.1 chr16 70379457 70399502 +2107779 FCSK chr16 70454595 70480274 +2108048 COG4 chr16 70480568 70523558 +2108332 SF3B3 chr16 70523791 70577670 +2108485 IL34 chr16 70579895 70660682 +2108555 MTSS2 chr16 70661204 70686053 +2108647 VAC14 chr16 70687439 70801160 +2108836 AC020763.1 chr16 70747057 70747926 +2108840 VAC14-AS1 chr16 70755035 70773251 +2108860 AC027281.1 chr16 70802083 70802840 +2108863 HYDIN chr16 70802084 71230722 +2109491 AC138625.2 chr16 71080866 71093667 +2109501 AC138625.1 chr16 71113352 71114000 +2109505 CMTR2 chr16 71281389 71289715 +2109568 AC106736.1 chr16 71288775 71309963 +2109582 CALB2 chr16 71358713 71390436 +2109674 LINC02136 chr16 71366933 71426464 +2109682 TLE7 chr16 71430262 71442060 +2109708 ZNF23 chr16 71447597 71463095 +2109843 AC010547.1 chr16 71462278 71465941 +2109851 ZNF19 chr16 71464555 71565089 +2110032 AC010547.3 chr16 71513863 71517849 +2110037 CHST4 chr16 71525233 71538746 +2110060 AC010547.2 chr16 71539834 71541825 +2110064 TAT-AS1 chr16 71564952 71578187 +2110082 TAT chr16 71565660 71577092 +2110122 AC009097.2 chr16 71623708 71626816 +2110126 MARVELD3 chr16 71626161 71642114 +2110183 PHLPP2 chr16 71637835 71724701 +2110377 AC009097.1 chr16 71655027 71664212 +2110381 AC009097.4 chr16 71723180 71724230 +2110385 AC009097.3 chr16 71726975 71727992 +2110388 AP1G1 chr16 71729000 71809201 +2110818 ATXN1L chr16 71845976 71885268 +2110838 IST1 chr16 71845996 71931199 +2111235 ZNF821 chr16 71859680 71895336 +2111567 AC009127.1 chr16 71881553 71882273 +2111571 PKD1L3 chr16 71929538 71999978 +2111636 DHODH chr16 72008588 72027664 +2111742 TXNL4B chr16 72044289 72094431 +2111817 HP chr16 72054505 72061055 +2112042 HPR chr16 72063148 72077246 +2112109 AC009087.1 chr16 72084857 72087443 +2112113 DHX38 chr16 72093613 72112912 +2112297 PMFBP1 chr16 72112157 72176878 +2112581 AC009075.1 chr16 72224565 72225144 +2112585 LINC01572 chr16 72236281 72665014 +2112718 AC004158.1 chr16 72425948 72533892 +2112724 AC004943.2 chr16 72665123 72822781 +2112743 AC004943.3 chr16 72772673 72773272 +2112746 ZFHX3 chr16 72782885 73891871 +2112859 AC004943.1 chr16 72805998 72809872 +2112868 AC002044.1 chr16 73014319 73014476 +2112871 AC116667.1 chr16 73060245 73062316 +2112874 HCCAT5 chr16 73092349 73099337 +2112893 AC116667.2 chr16 73123296 73137580 +2112899 AC140912.1 chr16 73232055 73233970 +2112905 LINC01568 chr16 73386771 73504954 +2113007 AC092114.1 chr16 73543927 73569309 +2113021 AC087565.2 chr16 73794057 73809733 +2113031 AC087565.1 chr16 73812560 73816054 +2113037 AC138627.1 chr16 73943078 74296762 +2113091 AC009120.4 chr16 74282415 74287519 +2113095 AC009120.5 chr16 74289593 74291052 +2113098 PSMD7 chr16 74296814 74306288 +2113181 AC009120.2 chr16 74305127 74335346 +2113203 AC009120.3 chr16 74313337 74315634 +2113207 AC009053.2 chr16 74367462 74369826 +2113210 NPIPB15 chr16 74377878 74392080 +2113232 CLEC18B chr16 74408270 74421953 +2113369 AC009053.3 chr16 74422120 74441937 +2113382 GLG1 chr16 74447427 74607144 +2113746 RFWD3 chr16 74621399 74666877 +2113875 MLKL chr16 74671855 74700960 +2113974 FA2H chr16 74712955 74774831 +2114030 WDR59 chr16 74871362 75000173 +2114315 ZNRF1 chr16 74999024 75110994 +2114409 AC099508.1 chr16 75108601 75110712 +2114413 LDHD chr16 75111860 75116771 +2114499 AC099508.2 chr16 75119558 75144200 +2114506 ZFP1 chr16 75148494 75172236 +2114593 CTRB2 chr16 75204103 75207161 +2114656 CTRB1 chr16 75218988 75226338 +2114694 BCAR1 chr16 75228181 75268053 +2114949 CFDP1 chr16 75293698 75433503 +2115026 AC009054.1 chr16 75321890 75325048 +2115030 AC009054.2 chr16 75379818 75381260 +2115034 AC009163.7 chr16 75433836 75436392 +2115037 TMEM170A chr16 75443054 75465497 +2115116 AC009163.4 chr16 75458252 75460017 +2115120 CHST6 chr16 75472052 75495445 +2115171 AC009163.1 chr16 75475896 75495407 +2115175 AC009163.6 chr16 75497948 75498289 +2115178 CHST5 chr16 75528535 75535247 +2115200 TMEM231 chr16 75536741 75556268 +2115315 AC025287.2 chr16 75556392 75557059 +2115318 GABARAPL2 chr16 75566375 75577881 +2115369 AC025287.3 chr16 75572185 75572685 +2115372 ADAT1 chr16 75596981 75623300 +2115508 KARS chr16 75627474 75648643 +2115708 TERF2IP chr16 75647773 75761872 +2115755 AC025287.4 chr16 75660227 75677009 +2115767 DUXB chr16 75693893 75701461 +2115783 CPHXL chr16 75714131 75726490 +2115795 AC105430.1 chr16 75838576 75860869 +2115814 AC099511.1 chr16 76107283 76147806 +2115826 AC010528.1 chr16 76228379 76262365 +2115831 AC010528.2 chr16 76264776 76277303 +2115835 CNTNAP4 chr16 76277278 76560757 +2116167 AC108125.1 chr16 76582556 76583098 +2116170 LINC02125 chr16 76634998 76658478 +2116176 AC106729.1 chr16 76736342 76928169 +2116181 MON1B chr16 77190835 77202398 +2116286 SYCE1L chr16 77199408 77213215 +2116324 AC009139.2 chr16 77201474 77249957 +2116328 AC009139.1 chr16 77234877 77299950 +2116336 ADAMTS18 chr16 77247813 77435034 +2116442 AC025284.1 chr16 77433382 77446798 +2116456 LINC02131 chr16 77590806 77610681 +2116461 NUDT7 chr16 77722492 77742260 +2116537 AC092134.1 chr16 77741468 77743000 +2116541 AC092134.3 chr16 77752372 77756681 +2116545 VAT1L chr16 77788564 77980107 +2116574 AC079414.1 chr16 78014683 78059454 +2116578 CLEC3A chr16 78022515 78066761 +2116615 WWOX chr16 78099430 79212667 +2116836 AC079414.3 chr16 78123243 78124332 +2116839 WWOX-AS1 chr16 78234652 78241989 +2116854 AC106743.1 chr16 78273497 78275607 +2116858 AC046158.1 chr16 78495926 78506568 +2116863 AC046158.2 chr16 78534374 78535648 +2116867 AC009141.1 chr16 78793584 78796362 +2116871 AC027279.1 chr16 78895361 78899644 +2116874 AC027279.2 chr16 78994345 79004730 +2116879 AC009145.3 chr16 79077376 79078234 +2116883 AC009145.1 chr16 79090050 79101754 +2116888 AC009145.2 chr16 79105957 79110882 +2116893 AC092376.2 chr16 79202624 79206739 +2116896 AC092376.3 chr16 79208493 79211264 +2116901 AC092376.1 chr16 79212711 79229453 +2116905 AC084064.1 chr16 79505603 79516293 +2116909 MAF chr16 79585843 79600737 +2116934 AC009159.2 chr16 79603572 79604177 +2116937 AC009159.3 chr16 79605802 79606605 +2116940 AC009159.1 chr16 79619469 79620110 +2116943 LINC01229 chr16 79676048 79809716 +2117203 MAFTRR chr16 79715220 79770651 +2117266 LINC01228 chr16 79798050 79827150 +2117270 AC092130.1 chr16 80040662 80045745 +2117274 AC022166.1 chr16 80065836 80167577 +2117284 AC105411.1 chr16 80154979 80563354 +2117339 AC022166.2 chr16 80179129 80180682 +2117343 DYNLRB2 chr16 80540734 80550811 +2117413 AC108097.1 chr16 80547842 80552514 +2117417 LINC01227 chr16 80553256 80572808 +2117482 CDYL2 chr16 80597907 80804598 +2117576 AC092332.1 chr16 80627551 80628379 +2117579 AC099313.1 chr16 80736360 80742305 +2117584 ARLNC1 chr16 80826074 80892682 +2117853 CMC2 chr16 80966448 81020270 +2118125 CENPN chr16 81006498 81033114 +2118295 AC092718.2 chr16 81016792 81035759 +2118316 AC092718.4 chr16 81030770 81031485 +2118319 ATMIN chr16 81035842 81047350 +2118373 C16orf46 chr16 81053497 81077267 +2118412 AC092718.5 chr16 81055301 81056426 +2118416 AC092718.6 chr16 81069854 81076598 +2118423 AC092718.1 chr16 81077319 81078861 +2118427 GCSH chr16 81081938 81096425 +2118540 AC092718.9 chr16 81151820 81153976 +2118544 BCO1 chr16 81238689 81291142 +2118610 AC009148.1 chr16 81310731 81313423 +2118613 GAN chr16 81314966 81380198 +2118691 AC092139.1 chr16 81385463 81387560 +2118695 CMIP chr16 81445170 81711762 +2118960 AC099524.1 chr16 81738248 81767868 +2118991 PLCG2 chr16 81739097 81962685 +2119251 AC092142.2 chr16 81987948 81989016 +2119255 SDR42E1 chr16 81988855 82011481 +2119283 HSD17B2 chr16 82035004 82098534 +2119346 AC092142.1 chr16 82044336 82139631 +2119356 MPHOSPH6 chr16 82147798 82170224 +2119444 AC138304.1 chr16 82170296 82175803 +2119448 AC009117.2 chr16 82491738 82575518 +2119469 CDH13 chr16 82626965 83800640 +2119705 AC099506.1 chr16 82773319 82829638 +2119710 AC099506.3 chr16 82816831 82832997 +2119716 AC125793.1 chr16 82953230 82990298 +2119721 AC009142.1 chr16 83383007 83398170 +2119730 AC009063.3 chr16 83687779 83717898 +2119739 AC009063.2 chr16 83720402 83772974 +2119771 AC009063.1 chr16 83725676 83726377 +2119774 AC009119.1 chr16 83789967 83807834 +2119796 HSBP1 chr16 83807978 83819737 +2119837 MLYCD chr16 83899115 83951445 +2119894 AC009119.2 chr16 83929796 83931223 +2119901 OSGIN1 chr16 83931311 83966332 +2119984 NECAB2 chr16 83968632 84002776 +2120073 SLC38A8 chr16 84009667 84042636 +2120128 AC040169.4 chr16 84040790 84045333 +2120132 MBTPS1 chr16 84053761 84116942 +2120288 AC040169.3 chr16 84085979 84086590 +2120291 AC040169.1 chr16 84117051 84117571 +2120294 HSDL1 chr16 84122141 84145192 +2120373 DNAAF1 chr16 84145287 84178767 +2120496 TAF1C chr16 84177847 84187070 +2120877 ADAD2 chr16 84191138 84197168 +2120976 AC009123.1 chr16 84192558 84197053 +2120994 KCNG4 chr16 84218667 84239750 +2121015 AC010551.3 chr16 84255270 84261049 +2121020 WFDC1 chr16 84294846 84329844 +2121073 AC010551.2 chr16 84295498 84296985 +2121077 AC010551.1 chr16 84342464 84343407 +2121081 ATP2C2 chr16 84368527 84464187 +2121315 ATP2C2-AS1 chr16 84459259 84467361 +2121320 MEAK7 chr16 84476355 84554033 +2121435 AC022165.1 chr16 84495599 84497495 +2121439 COTL1 chr16 84565596 84618078 +2121480 AC092145.1 chr16 84594393 84596826 +2121483 KLHL36 chr16 84648511 84667686 +2121546 USP10 chr16 84699978 84779922 +2121803 AC025280.3 chr16 84817182 84856665 +2121811 CRISPLD2 chr16 84819985 84920768 +2121996 AC025280.1 chr16 84828263 84829242 +2122000 AC025280.2 chr16 84917377 84924808 +2122005 LINC02176 chr16 84928353 84939603 +2122010 ZDHHC7 chr16 84974181 85011535 +2122114 KIAA0513 chr16 85027751 85094230 +2122258 FAM92B chr16 85098358 85112472 +2122320 LINC02139 chr16 85137150 85149443 +2122325 AC026469.1 chr16 85142696 85146001 +2122328 GSE1 chr16 85169525 85676204 +2122537 AC092275.1 chr16 85227203 85309176 +2122541 LINC00311 chr16 85282958 85285963 +2122545 AC092377.1 chr16 85345271 85352961 +2122549 AC133540.1 chr16 85489813 85490831 +2122552 AC092127.2 chr16 85580009 85583571 +2122557 AC092127.1 chr16 85592266 85595720 +2122560 GINS2 chr16 85676198 85690073 +2122598 C16orf74 chr16 85690084 85751129 +2122676 AC018695.6 chr16 85697335 85697868 +2122679 AC018695.9 chr16 85699820 85711186 +2122684 AC018695.2 chr16 85743287 85744225 +2122688 EMC8 chr16 85771758 85799608 +2122738 AC018695.4 chr16 85784382 85787617 +2122742 AC018695.3 chr16 85792415 85792933 +2122746 COX4I1 chr16 85798633 85807054 +2122902 AC018695.8 chr16 85846309 85848138 +2122906 IRF8 chr16 85899162 85922606 +2123032 AC092723.5 chr16 85924984 85948824 +2123048 LINC02132 chr16 85935281 85936223 +2123052 AC092723.4 chr16 85963328 85985386 +2123057 AC092723.1 chr16 85981750 85984881 +2123061 AC092723.3 chr16 85986764 85995899 +2123066 AC135012.1 chr16 86081409 86089526 +2123070 AC135012.2 chr16 86158206 86158798 +2123074 AC135012.3 chr16 86192793 86198913 +2123079 LINC01082 chr16 86195954 86199720 +2123092 LINC01081 chr16 86221420 86301303 +2123112 LINC02135 chr16 86286427 86293389 +2123117 LINC00917 chr16 86331632 86349688 +2123230 AC092327.2 chr16 86347387 86349611 +2123235 FENDRR chr16 86474529 86509099 +2123302 FOXF1 chr16 86510527 86515422 +2123312 AC009108.3 chr16 86520383 86523897 +2123315 MTHFSD chr16 86530178 86555235 +2123610 FOXC2-AS1 chr16 86565145 86567761 +2123614 FOXC2 chr16 86566829 86569728 +2123622 FOXL1 chr16 86576368 86582160 +2123637 AC009108.2 chr16 86636328 86637145 +2123641 AC009154.1 chr16 86646301 86668923 +2123646 AC009154.2 chr16 86698118 86698841 +2123649 LINC02188 chr16 86710122 86742083 +2123695 LINC02189 chr16 86720575 86722042 +2123717 AC130467.1 chr16 86764298 86771041 +2123723 AC093519.2 chr16 86899356 86961268 +2123732 LINC02181 chr16 87057784 87070105 +2123741 AC106745.1 chr16 87066705 87069752 +2123745 C16orf95 chr16 87083562 87317420 +2123812 AC136285.3 chr16 87129857 87133107 +2123816 AC136285.1 chr16 87212122 87226430 +2123821 AC136285.2 chr16 87215915 87216452 +2123825 AC010531.4 chr16 87262759 87292438 +2123844 AC010531.6 chr16 87317509 87318043 +2123848 AC010531.7 chr16 87326987 87327584 +2123852 FBXO31 chr16 87326987 87392142 +2123940 AC010531.5 chr16 87362536 87367476 +2123944 MAP1LC3B chr16 87383953 87404779 +2124017 AC010531.3 chr16 87396704 87400295 +2124021 ZCCHC14 chr16 87406246 87493024 +2124141 AC105429.1 chr16 87470370 87474370 +2124144 AC092720.1 chr16 87492555 87600337 +2124167 AC092720.2 chr16 87600526 87602190 +2124170 JPH3 chr16 87601835 87698156 +2124201 AC010536.3 chr16 87683945 87684477 +2124204 AC010536.1 chr16 87693537 87696147 +2124207 KLHDC4 chr16 87696485 87765992 +2124562 AC010536.2 chr16 87739771 87747706 +2124567 AC126696.3 chr16 87773304 87779374 +2124582 AC126696.1 chr16 87780134 87806476 +2124586 SLC7A5 chr16 87830023 87869507 +2124641 AC126696.2 chr16 87836532 87837663 +2124645 CA5A chr16 87881546 87936580 +2124727 BANP chr16 87949244 88077318 +2125111 AC134312.4 chr16 88079161 88087383 +2125115 AC134312.3 chr16 88087241 88089970 +2125120 AC134312.1 chr16 88088041 88100985 +2125127 AC134312.2 chr16 88177289 88178646 +2125131 AC134312.5 chr16 88177298 88186929 +2125141 LINC02182 chr16 88186605 88195217 +2125150 AC134312.6 chr16 88191486 88193667 +2125155 AC138512.1 chr16 88234785 88302511 +2125161 ZNF469 chr16 88382989 88440757 +2125181 ZFPM1 chr16 88453280 88537031 +2125256 AC116552.1 chr16 88512960 88531053 +2125262 ZC3H18 chr16 88570381 88631966 +2125424 IL17C chr16 88638572 88640468 +2125439 CYBA chr16 88643289 88651054 +2125546 MVD chr16 88651935 88663161 +2125697 SNAI3-AS1 chr16 88663298 88687278 +2125750 SNAI3 chr16 88677688 88686507 +2125762 RNF166 chr16 88696499 88706408 +2125870 AC138028.3 chr16 88696501 88698610 +2125874 CTU2 chr16 88706483 88715396 +2126061 AC138028.6 chr16 88708956 88710437 +2126064 PIEZO1 chr16 88715338 88785220 +2126293 AC138028.4 chr16 88718615 88720459 +2126296 AC138028.2 chr16 88731180 88741425 +2126304 AC138028.5 chr16 88741631 88742367 +2126308 AC138028.1 chr16 88742767 88745748 +2126316 CDT1 chr16 88803789 88809258 +2126359 APRT chr16 88809339 88811937 +2126466 GALNS chr16 88813734 88856970 +2126636 TRAPPC2L chr16 88856220 88862686 +2126805 PABPN1L chr16 88863333 88866660 +2126857 CBFA2T3 chr16 88874858 88977207 +2127000 AC092384.2 chr16 88881038 88887136 +2127014 AC092384.3 chr16 88936779 88939651 +2127020 AC092384.1 chr16 88939789 88951524 +2127024 AC135782.2 chr16 88984032 88995369 +2127029 AC135782.1 chr16 89046172 89052966 +2127037 ACSF3 chr16 89088375 89164121 +2127307 AC135782.3 chr16 89113175 89115279 +2127310 LINC00304 chr16 89159146 89164245 +2127321 LINC02138 chr16 89166383 89169147 +2127326 CDH15 chr16 89171748 89195492 +2127370 SLC22A31 chr16 89195761 89201651 +2127434 AC009113.1 chr16 89215211 89217653 +2127437 ZNF778 chr16 89217703 89237071 +2127522 AC009113.2 chr16 89226807 89228692 +2127526 ANKRD11 chr16 89267630 89490561 +2128080 AC137932.3 chr16 89268104 89273044 +2128084 AC137932.1 chr16 89296128 89298317 +2128095 AC137932.2 chr16 89321133 89325110 +2128104 AC092120.1 chr16 89420075 89422226 +2128108 AC092120.3 chr16 89430988 89453678 +2128115 SPG7 chr16 89490719 89557768 +2129921 AC092123.1 chr16 89492017 89504460 +2129929 RPL13 chr16 89560657 89566828 +2130073 CPNE7 chr16 89575758 89597246 +2130212 DPEP1 chr16 89613308 89638456 +2130339 CHMP1A chr16 89644435 89657721 +2130441 SPATA33 chr16 89657802 89671272 +2130525 AC010538.1 chr16 89671568 89685304 +2130530 CDK10 chr16 89680737 89696354 +2130859 LINC02166 chr16 89682620 89686569 +2130864 SPATA2L chr16 89696357 89701705 +2130898 VPS9D1 chr16 89707134 89720898 +2131016 VPS9D1-AS1 chr16 89711856 89718165 +2131025 ZNF276 chr16 89720400 89740925 +2131209 FANCA chr16 89737549 89816657 +2131804 SPIRE2 chr16 89818179 89871319 +2131941 TCF25 chr16 89873570 89913627 +2132301 MC1R chr16 89912119 89920977 +2132336 AC092143.2 chr16 89919827 89922662 +2132340 TUBB3 chr16 89921392 89938761 +2132521 DEF8 chr16 89947925 89968060 +2132977 CENPBD1 chr16 89969773 89972832 +2132992 DBNDD1 chr16 90004865 90020128 +2133061 GAS8 chr16 90019629 90044975 +2133274 GAS8-AS1 chr16 90028908 90029901 +2133279 PRDM7 chr16 90056566 90092072 +2133375 FAM157C chr16 90102271 90178344 +2133431 AC133919.1 chr16 90105095 90106316 +2133435 AC133919.2 chr16 90110574 90168225 +2133443 LINC02193 chr16 90173217 90222851 +2133520 AC240565.2 chr17 64099 76866 +2133527 AC240565.1 chr17 88641 118578 +2133537 SCGB1C2 chr17 137526 139067 +2133549 DOC2B chr17 142789 181650 +2133582 LINC02091 chr17 183824 191587 +2133587 RPH3AL chr17 212389 386254 +2133855 AC129507.4 chr17 321392 322453 +2133862 AC129507.1 chr17 331205 333488 +2133882 AC129507.2 chr17 352638 357581 +2133886 AC129507.3 chr17 354737 356882 +2133890 AC141424.1 chr17 404468 414023 +2133901 C17orf97 chr17 410325 431062 +2133942 RFLNB chr17 439978 445939 +2133950 AC015853.2 chr17 503171 511347 +2133955 VPS53 chr17 508668 721717 +2134306 AC015853.3 chr17 523140 540576 +2134310 AC015853.1 chr17 552566 553417 +2134314 TLCD3A chr17 732412 742968 +2134388 GEMIN4 chr17 744421 753999 +2134450 GLOD4 chr17 757097 783390 +2134722 AC087392.3 chr17 763565 765319 +2134728 MRM3 chr17 782353 792509 +2134765 AC087392.4 chr17 789744 790525 +2134769 AC087392.5 chr17 795306 795794 +2134772 NXN chr17 799310 979776 +2134882 AC087392.2 chr17 877902 880093 +2134886 AC087392.1 chr17 909632 911212 +2134890 TIMM22 chr17 997129 1003671 +2134904 ABR chr17 1003518 1229738 +2135408 AC016292.1 chr17 1181893 1185086 +2135413 AC144836.1 chr17 1241939 1254000 +2135417 BHLHA9 chr17 1270559 1271460 +2135425 TRARG1 chr17 1279662 1300978 +2135437 YWHAE chr17 1344275 1400222 +2135549 CRK chr17 1420689 1463162 +2135587 AC032044.1 chr17 1424473 1426484 +2135594 MYO1C chr17 1464186 1492686 +2136173 INPP5K chr17 1494577 1516742 +2136452 PITPNA-AS1 chr17 1516931 1518096 +2136456 PITPNA chr17 1517718 1562792 +2136668 SLC43A2 chr17 1569267 1628886 +2136854 SCARF1 chr17 1633858 1645744 +2137011 RILP chr17 1646145 1649866 +2137054 PRPF8 chr17 1650629 1684867 +2137340 AC130343.2 chr17 1684726 1685151 +2137343 TLCD2 chr17 1702816 1710377 +2137357 MIR22HG chr17 1711493 1717174 +2137444 WDR81 chr17 1716523 1738599 +2137640 AC130343.1 chr17 1725748 1738585 +2137644 SERPINF2 chr17 1742836 1755268 +2137756 SERPINF1 chr17 1762029 1777565 +2137882 SMYD4 chr17 1779485 1830634 +2137972 RPA1 chr17 1829702 1900082 +2138079 RTN4RL1 chr17 1934677 2025334 +2138089 AC099684.2 chr17 1995614 2003671 +2138094 AC099684.1 chr17 2017716 2020706 +2138104 AC099684.3 chr17 2019952 2023664 +2138108 DPH1 chr17 2030110 2043430 +2138322 AC090617.10 chr17 2040953 2041932 +2138325 OVCA2 chr17 2042022 2043425 +2138335 AC090617.3 chr17 2042900 2043425 +2138339 AC090617.5 chr17 2043475 2044968 +2138343 HIC1 chr17 2054154 2063241 +2138400 SMG6 chr17 2059839 2303785 +2138651 AC090617.4 chr17 2089681 2101560 +2138655 AC090617.2 chr17 2213697 2214414 +2138659 AC090617.1 chr17 2215482 2216015 +2138663 AL450226.1 chr17 2232680 2233610 +2138667 SRR chr17 2303383 2325260 +2138766 TSR1 chr17 2322503 2337507 +2138846 SGSM2 chr17 2337498 2381058 +2139091 AC006435.3 chr17 2366589 2366791 +2139094 AC006435.2 chr17 2375061 2379306 +2139103 MNT chr17 2384073 2401104 +2139154 AC006435.1 chr17 2384847 2386664 +2139158 METTL16 chr17 2405562 2511891 +2139275 PAFAH1B1 chr17 2593210 2685615 +2139390 AC005696.2 chr17 2683305 2685088 +2139394 AC005696.3 chr17 2688473 2688960 +2139398 CLUH chr17 2689386 2712663 +2139748 AC005696.1 chr17 2712309 2712833 +2139752 AC005696.4 chr17 2720801 2723947 +2139755 hsa-mir-1253 chr17 2748078 2748182 +2139758 RAP1GAP2 chr17 2755705 3037741 +2140053 AC015921.1 chr17 2962248 2965895 +2140058 OR1D5 chr17 3062669 3063607 +2140065 OR1D2 chr17 3088484 3104422 +2140090 OR1G1 chr17 3126584 3127581 +2140098 AC090282.1 chr17 3134969 3177031 +2140108 OR1A2 chr17 3197519 3198448 +2140115 OR1A1 chr17 3207539 3218896 +2140146 OR3A2 chr17 3276942 3386317 +2140198 OR3A1 chr17 3291017 3298360 +2140213 AC087498.1 chr17 3385930 3386874 +2140220 OR1E1 chr17 3397104 3398410 +2140227 OR3A3 chr17 3411370 3424070 +2140252 OR1E2 chr17 3432870 3433841 +2140259 SPATA22 chr17 3440019 3513852 +2140506 ASPA chr17 3472374 3503405 +2140565 TRPV3 chr17 3510502 3557995 +2140869 TRPV1 chr17 3565444 3609411 +2141176 AC027796.5 chr17 3577955 3578853 +2141180 AC027796.1 chr17 3601761 3602272 +2141183 SHPK chr17 3608253 3636250 +2141203 CTNS chr17 3636468 3661542 +2141361 AC027796.4 chr17 3655621 3658092 +2141366 TAX1BP3 chr17 3662895 3668679 +2141391 EMC6 chr17 3668812 3669668 +2141410 P2RX5 chr17 3672199 3696240 +2141623 ITGAE chr17 3714628 3801188 +2141743 AC116914.2 chr17 3721628 3722488 +2141747 HASPIN chr17 3723903 3726699 +2141755 AC116914.1 chr17 3729361 3730493 +2141759 NCBP3 chr17 3802158 3846246 +2141841 CAMKK1 chr17 3860315 3894891 +2141962 P2RX1 chr17 3896592 3916476 +2142018 ATP2A3 chr17 3923870 3964464 +2142370 LINC01975 chr17 3977103 3981899 +2142374 ZZEF1 chr17 4004445 4143030 +2142638 CYB5D2 chr17 4143168 4187310 +2142696 ANKFY1 chr17 4163821 4263995 +2143023 AC087292.1 chr17 4163910 4164713 +2143027 AC087742.1 chr17 4267691 4268430 +2143030 UBE2G1 chr17 4269259 4366628 +2143122 SPNS3 chr17 4433940 4488208 +2143199 AC127521.1 chr17 4481966 4486353 +2143209 AC118754.1 chr17 4497394 4499674 +2143213 SPNS2 chr17 4498881 4539035 +2143284 MYBBP1A chr17 4538897 4555631 +2143525 GGT6 chr17 4556927 4560818 +2143588 AC118754.2 chr17 4565752 4571760 +2143592 SMTNL2 chr17 4583999 4608319 +2143647 LINC01996 chr17 4610449 4617650 +2143651 ALOX15 chr17 4630902 4642294 +2143778 PELP1 chr17 4669774 4704337 +2144065 AC091153.2 chr17 4673830 4696831 +2144073 AC091153.3 chr17 4704230 4705529 +2144077 ARRB2 chr17 4710596 4721499 +2144467 MED11 chr17 4731428 4733607 +2144499 AC091153.4 chr17 4731756 4732371 +2144503 CXCL16 chr17 4733533 4739928 +2144554 ZMYND15 chr17 4739833 4746119 +2144697 TM4SF5 chr17 4771884 4783213 +2144718 VMO1 chr17 4785285 4786433 +2144761 GLTPD2 chr17 4788964 4790589 +2144775 PSMB6 chr17 4796144 4798502 +2144831 AC233723.1 chr17 4801159 4807013 +2144844 PLD2 chr17 4807152 4823434 +2145086 MINK1 chr17 4833340 4898061 +2145534 CHRNE chr17 4897771 4934438 +2145611 C17orf107 chr17 4899418 4902934 +2145632 GP1BA chr17 4932277 4935023 +2145653 SLC25A11 chr17 4937130 4940053 +2145723 RNF167 chr17 4940008 4945222 +2145946 PFN1 chr17 4945652 4949061 +2145976 ENO3 chr17 4948092 4957131 +2146214 SPAG7 chr17 4959226 4967817 +2146299 CAMTA2 chr17 4967992 4987675 +2146667 AC004771.4 chr17 4967995 4968822 +2146671 AC004771.2 chr17 4972851 4974681 +2146675 AC004771.5 chr17 4986466 4987324 +2146679 AC004771.3 chr17 4987706 4988446 +2146683 INCA1 chr17 4988130 4997610 +2146766 KIF1C chr17 4997950 5028401 +2146845 AC004771.1 chr17 5019214 5020093 +2146849 SLC52A1 chr17 5032600 5052009 +2146903 AC012146.3 chr17 5075678 5078113 +2146907 ZFP3 chr17 5078467 5096374 +2146917 ZNF232 chr17 5105541 5123116 +2147003 AC012146.1 chr17 5111468 5115004 +2147021 USP6 chr17 5116438 5175034 +2147312 ZNF594 chr17 5179535 5191868 +2147336 AC087500.1 chr17 5192027 5248182 +2147394 SCIMP chr17 5208920 5234860 +2147455 AC087500.2 chr17 5240508 5241543 +2147460 RABEP1 chr17 5282265 5386340 +2147591 NUP88 chr17 5360963 5419676 +2147754 AC015727.1 chr17 5364315 5371626 +2147758 RPAIN chr17 5419641 5432876 +2147964 AC004148.1 chr17 5425139 5432876 +2147968 C1QBP chr17 5432777 5448830 +2148036 DHX33 chr17 5440917 5468982 +2148147 DHX33-DT chr17 5469092 5470360 +2148152 DERL2 chr17 5471254 5486811 +2148310 MIS12 chr17 5486285 5490814 +2148363 NLRP1 chr17 5499427 5619424 +2148816 AC055839.2 chr17 5499439 5501145 +2148826 AC135726.1 chr17 5700226 5704056 +2148831 AC007846.1 chr17 5772234 5930696 +2148837 WSCD1 chr17 6057807 6124427 +2149007 AC104770.1 chr17 6163893 6190541 +2149019 AC055872.2 chr17 6373833 6375080 +2149023 AIPL1 chr17 6393693 6435199 +2149187 PIMREG chr17 6444441 6451469 +2149317 PITPNM3 chr17 6451263 6556555 +2149442 KIAA0753 chr17 6578147 6640711 +2149641 AC004706.3 chr17 6628619 6640456 +2149653 TXNDC17 chr17 6640985 6644541 +2149729 MED31 chr17 6643311 6651634 +2149770 C17orf100 chr17 6651762 6693202 +2149794 AC004706.1 chr17 6653464 6655009 +2149798 SLC13A5 chr17 6684713 6713567 +2149981 XAF1 chr17 6755447 6775647 +2150197 FBXO39 chr17 6776215 6797101 +2150231 TEKT1 chr17 6789133 6831761 +2150293 ALOX12-AS1 chr17 6875232 7012530 +2150354 AC027763.2 chr17 6954098 6978960 +2150361 AC040977.1 chr17 6994642 6995189 +2150365 ALOX12 chr17 6996049 7010754 +2150414 RNASEK chr17 7012417 7014532 +2150512 C17orf49 chr17 7014495 7017525 +2150616 MIR497HG chr17 7015818 7019659 +2150623 BCL6B chr17 7023050 7030290 +2150682 SLC16A13 chr17 7036015 7040117 +2150698 SLC16A11 chr17 7041630 7043923 +2150752 CLEC10A chr17 7074537 7080307 +2150855 ASGR2 chr17 7101322 7115700 +2150952 ASGR1 chr17 7173431 7179564 +2151093 DLG4 chr17 7187169 7219841 +2151756 ACADVL chr17 7217125 7225266 +2152219 DVL2 chr17 7225342 7234517 +2152397 PHF23 chr17 7235029 7239722 +2152547 GABARAP chr17 7240008 7242449 +2152620 CTDNEP1 chr17 7243591 7252491 +2152822 ELP5 chr17 7251416 7259940 +2153062 CLDN7 chr17 7259903 7263983 +2153147 SLC2A4 chr17 7281718 7288257 +2153277 AC003688.2 chr17 7282947 7284071 +2153281 YBX2 chr17 7288263 7294639 +2153348 EIF5A chr17 7306999 7312463 +2153506 GPS2 chr17 7311324 7315564 +2153692 NEURL4 chr17 7315628 7329393 +2154069 ACAP1 chr17 7336529 7351477 +2154191 KCTD11 chr17 7351889 7354944 +2154206 AC026954.3 chr17 7352687 7354944 +2154210 TMEM95 chr17 7355123 7357219 +2154268 TNK1 chr17 7380534 7389774 +2154374 PLSCR3 chr17 7389727 7394842 +2154564 TMEM256 chr17 7402975 7404097 +2154590 NLGN2 chr17 7404874 7419860 +2154643 SPEM1 chr17 7420324 7421632 +2154655 SPEM2 chr17 7425616 7427568 +2154678 SPEM3 chr17 7428857 7432820 +2154699 TMEM102 chr17 7435435 7437679 +2154720 AC113189.1 chr17 7436557 7437523 +2154724 FGF11 chr17 7438273 7444937 +2154802 AC113189.3 chr17 7439159 7443327 +2154806 CHRNB1 chr17 7445061 7457710 +2154935 ZBTB4 chr17 7459366 7484263 +2154962 SLC35G6 chr17 7481332 7483496 +2154972 POLR2A chr17 7484366 7514618 +2155153 TNFSF12 chr17 7549058 7557890 +2155213 AC016876.3 chr17 7557820 7558245 +2155216 TNFSF13 chr17 7558292 7561608 +2155358 SENP3 chr17 7561919 7571969 +2155492 EIF4A1 chr17 7572706 7579006 +2155907 CD68 chr17 7579491 7582111 +2155960 AC016876.1 chr17 7581964 7584086 +2155976 MPDU1 chr17 7583529 7592789 +2156311 SOX15 chr17 7588178 7590094 +2156339 FXR2 chr17 7591230 7614897 +2156412 SHBG chr17 7613946 7633382 +2156743 SAT2 chr17 7626234 7627876 +2156854 ATP1B2 chr17 7646627 7657770 +2156904 TP53 chr17 7661779 7687550 +2157489 WRAP53 chr17 7686071 7703502 +2157675 EFNB3 chr17 7705202 7711372 +2157691 DNAH2 chr17 7717354 7833744 +2158174 KDM6B chr17 7839904 7854796 +2158307 TMEM88 chr17 7855066 7856099 +2158326 NAA38 chr17 7856685 7885238 +2158399 CYB5D1 chr17 7857746 7862282 +2158451 CHD3 chr17 7884796 7912760 +2158921 RNF227 chr17 7913324 7916276 +2158947 KCNAB3 chr17 7921859 7929803 +2159041 TRAPPC1 chr17 7930345 7932123 +2159115 CNTROB chr17 7932101 7949920 +2159384 GUCY2D chr17 8002594 8020339 +2159433 ALOX15B chr17 8039034 8049134 +2159573 AC129492.2 chr17 8056225 8057621 +2159577 ALOX12B chr17 8072636 8087716 +2159654 AC129492.1 chr17 8079482 8081565 +2159658 ALOXE3 chr17 8095900 8119047 +2159771 HES7 chr17 8120592 8124106 +2159810 PER1 chr17 8140472 8156506 +2160120 VAMP2 chr17 8159149 8163546 +2160179 TMEM107 chr17 8172457 8176399 +2160267 AC129492.4 chr17 8176812 8182812 +2160272 BORCS6 chr17 8188345 8190180 +2160280 AURKB chr17 8204733 8210600 +2160481 LINC00324 chr17 8220642 8224043 +2160486 CTC1 chr17 8224815 8248056 +2160732 PFAS chr17 8247618 8270491 +2160949 AC135178.6 chr17 8277763 8278436 +2160952 SLC25A35 chr17 8287763 8295400 +2161065 RANGRF chr17 8288654 8290092 +2161125 ARHGEF15 chr17 8310241 8322514 +2161266 AC135178.2 chr17 8318088 8318712 +2161270 AC135178.5 chr17 8337697 8338758 +2161274 ODF4 chr17 8339840 8346048 +2161321 KRBA2 chr17 8356902 8376711 +2161381 AC135178.4 chr17 8365563 8381328 +2161398 RPL26 chr17 8377516 8383213 +2161516 RNF222 chr17 8390704 8397826 +2161535 NDEL1 chr17 8413131 8490411 +2161741 MYH10 chr17 8474205 8630761 +2162054 CCDC42 chr17 8729935 8745219 +2162098 SPDYE4 chr17 8753106 8758559 +2162142 MFSD6L chr17 8797110 8799365 +2162150 PIK3R6 chr17 8802723 8867677 +2162328 PIK3R5 chr17 8878911 8965712 +2162721 AC002091.2 chr17 8965896 8967070 +2162725 AC002091.1 chr17 8967523 8976995 +2162729 NTN1 chr17 9021510 9244000 +2162760 AC005695.1 chr17 9171068 9179118 +2162766 AC005695.3 chr17 9244666 9244897 +2162769 STX8 chr17 9250471 9576591 +2162882 AC005695.2 chr17 9283174 9305651 +2162886 AC087501.1 chr17 9452197 9470014 +2162893 AC087501.2 chr17 9464742 9467422 +2162897 AC087501.3 chr17 9547298 9548541 +2162901 AC087501.4 chr17 9553323 9555696 +2162904 CFAP52 chr17 9576627 9643447 +2163083 AC118755.2 chr17 9638768 9645325 +2163087 USP43 chr17 9644698 9729687 +2163221 AC118755.1 chr17 9647020 9647660 +2163225 AC027045.2 chr17 9764186 9805100 +2163231 DHRS7C chr17 9771434 9791297 +2163275 GSG1L2 chr17 9802386 9822071 +2163290 AC027045.3 chr17 9805443 9811047 +2163295 GLP2R chr17 9822206 9892099 +2163396 RCVRN chr17 9896320 9905271 +2163411 GAS7 chr17 9910609 10198551 +2163764 AC005291.2 chr17 10291820 10317926 +2163768 MYH13 chr17 10300865 10373130 +2164024 AC005291.1 chr17 10320392 10341458 +2164029 AC005323.2 chr17 10383132 10537862 +2164040 MYH8 chr17 10390322 10421950 +2164126 MYH4 chr17 10443290 10469559 +2164212 MYH1 chr17 10492307 10518542 +2164298 MYH2 chr17 10521148 10549700 +2164579 AC005323.1 chr17 10579040 10623036 +2164598 MYH3 chr17 10628526 10657309 +2164703 AC002347.1 chr17 10658542 10659082 +2164706 SCO1 chr17 10672474 10698375 +2164766 AC002347.2 chr17 10680734 10683988 +2164770 ADPRM chr17 10697594 10711558 +2164811 TMEM220 chr17 10699015 10730316 +2164882 TMEM220-AS1 chr17 10729777 10815164 +2164922 AC015908.3 chr17 10741257 10769089 +2164932 AC015908.4 chr17 10792059 10794985 +2164937 TMEM238L chr17 10794913 10804099 +2164950 PIRT chr17 10822470 10838087 +2164960 AC015908.2 chr17 10844674 10880895 +2164972 AC005548.1 chr17 11197883 11242062 +2164976 SHISA6 chr17 11241213 11564063 +2165030 AC005725.1 chr17 11288205 11290811 +2165033 DNAH9 chr17 11598470 11969748 +2165442 AC005209.1 chr17 11874727 11881670 +2165447 AC005410.2 chr17 11953889 11977594 +2165451 ZNF18 chr17 11977439 11997475 +2165559 MAP2K4 chr17 12020829 12143830 +2165798 AC005244.2 chr17 12201600 12215267 +2165804 AC084167.1 chr17 12390738 12395177 +2165810 LINC00670 chr17 12549764 12642854 +2165836 AC068442.1 chr17 12596743 12632959 +2165841 MYOCD chr17 12665890 12768949 +2165945 AC005358.1 chr17 12671862 12706135 +2165950 AC005358.2 chr17 12760140 12790242 +2165954 ARHGAP44 chr17 12789498 12991643 +2166244 AC005277.2 chr17 12982613 12983002 +2166247 AC005277.1 chr17 12990149 12990610 +2166251 ELAC2 chr17 12991612 13018065 +2166698 AC005303.1 chr17 13095695 13100939 +2166709 LINC02093 chr17 13299184 13306771 +2166723 HS3ST3A1 chr17 13494032 13601929 +2166742 COX10-AS1 chr17 13755574 14069495 +2166823 AC005304.2 chr17 13909231 13911212 +2166826 AC005304.1 chr17 13932720 13940594 +2166831 AC005304.3 chr17 13957748 13966952 +2166836 COX10 chr17 14069490 14231736 +2166965 CDRT15 chr17 14235673 14236862 +2166988 AC005224.1 chr17 14295512 14297600 +2166992 HS3ST3B1 chr17 14301081 14349404 +2167013 AC005224.3 chr17 14303854 14305505 +2167016 AC005224.2 chr17 14327335 14329474 +2167019 AC022816.1 chr17 14374139 14421472 +2167031 AC013248.1 chr17 14725729 14729686 +2167035 AC005863.1 chr17 14767583 14780686 +2167052 LINC02096 chr17 14834557 14957216 +2167097 AC005772.1 chr17 15014805 15052276 +2167101 CDRT7 chr17 15030975 15031957 +2167106 AC005772.2 chr17 15062087 15104517 +2167110 CDRT8 chr17 15105237 15106187 +2167114 PMP22 chr17 15229777 15265326 +2167265 AC005703.3 chr17 15261015 15265707 +2167269 AC005703.7 chr17 15266848 15311760 +2167274 AC005703.1 chr17 15267461 15272290 +2167278 AC005703.2 chr17 15276562 15279477 +2167283 TEKT3 chr17 15303811 15341632 +2167400 AC005703.4 chr17 15379864 15417878 +2167406 CDRT4 chr17 15436015 15503608 +2167435 TVP23C chr17 15502264 15563595 +2167590 AC005838.2 chr17 15530773 15531089 +2167593 CDRT1 chr17 15565483 15619512 +2167714 TRIM16 chr17 15627960 15684311 +2167994 AC005324.5 chr17 15651590 15654489 +2167998 ZNF286A chr17 15699577 15720787 +2168228 TBC1D26 chr17 15732247 15749192 +2168429 AC005324.1 chr17 15735023 15749192 +2168441 AC005324.2 chr17 15761614 15763769 +2168445 AC015922.2 chr17 15787787 15788205 +2168449 AC015922.3 chr17 15789016 15789705 +2168452 LINC02087 chr17 15806241 15847996 +2168468 ADORA2B chr17 15944917 15975746 +2168480 ZSWIM7 chr17 15976560 15999717 +2168728 TTC19 chr17 15999784 16045015 +2168842 AC002553.2 chr17 16023323 16023653 +2168845 NCOR1 chr17 16029157 16218185 +2169491 AC002553.1 chr17 16040472 16041273 +2169494 PIGL chr17 16217191 16351797 +2169642 CENPV chr17 16342534 16353656 +2169697 UBB chr17 16380798 16382745 +2169769 AC093484.3 chr17 16382152 16382669 +2169773 AC093484.2 chr17 16414524 16416689 +2169776 TRPV2 chr17 16415571 16437003 +2169872 SNHG29 chr17 16438767 16478678 +2170170 AC093484.4 chr17 16440479 16440952 +2170174 LRRC75A chr17 16441577 16492193 +2170203 AC127540.2 chr17 16525832 16529290 +2170207 ZNF287 chr17 16546954 16569204 +2170260 AC127540.1 chr17 16557985 16559269 +2170264 ZNF624 chr17 16620734 16653856 +2170316 AC098850.2 chr17 16653904 16654787 +2170320 CCDC144A chr17 16689537 16777881 +2170535 AC098850.1 chr17 16788248 16789234 +2170539 FAM106C chr17 16788879 16790501 +2170542 AC022596.1 chr17 16804627 16805707 +2170546 AC022596.2 chr17 16861146 16864223 +2170549 TNFRSF13B chr17 16929816 16972118 +2170627 AC104024.1 chr17 16975999 16981353 +2170632 LINC02090 chr17 16988329 16990177 +2170637 AC104024.2 chr17 17011914 17014990 +2170640 AC104024.3 chr17 17028360 17035057 +2170645 AC104024.4 chr17 17033531 17042305 +2170649 MPRIP chr17 17042545 17217679 +2171005 MPRIP-AS1 chr17 17076038 17077752 +2171009 AC055811.1 chr17 17167946 17185554 +2171013 PLD6 chr17 17200995 17206333 +2171023 FLCN chr17 17212212 17237188 +2171118 AC055811.3 chr17 17235433 17236118 +2171121 COPS3 chr17 17246616 17281273 +2171390 NT5M chr17 17303335 17347663 +2171473 MED9 chr17 17476994 17493221 +2171507 RASD1 chr17 17494437 17496395 +2171526 AC020558.6 chr17 17504005 17512266 +2171531 PEMT chr17 17505563 17591708 +2171692 AC020558.2 chr17 17507351 17508308 +2171696 AC020558.1 chr17 17591428 17610485 +2171700 SMCR2 chr17 17674026 17677688 +2171706 RAI1 chr17 17681458 17811453 +2171773 RAI1-AS1 chr17 17759154 17770821 +2171778 SMCR5 chr17 17776686 17779529 +2171781 AC122129.2 chr17 17777781 17779094 +2171785 SREBF1 chr17 17810399 17837011 +2172097 TOM1L2 chr17 17843511 17972422 +2172389 AC122129.1 chr17 17858227 17860041 +2172392 DRC3 chr17 17972813 18016889 +2172648 ATPAF2 chr17 17977409 18039209 +2172779 GID4 chr17 18039408 18068405 +2172835 DRG2 chr17 18087892 18107970 +2173136 MYO15A chr17 18108706 18179802 +2173772 AC087164.1 chr17 18172625 18184753 +2173780 ALKBH5 chr17 18183078 18209954 +2173810 LLGL1 chr17 18225635 18244875 +2173930 FLII chr17 18244815 18258738 +2174421 MIEF2 chr17 18260597 18266552 +2174516 AC127537.1 chr17 18268080 18268828 +2174519 TOP3A chr17 18271428 18315007 +2174859 SMCR8 chr17 18315293 18328056 +2174869 SHMT1 chr17 18327860 18363563 +2175039 EVPLL chr17 18377778 18389647 +2175071 AL353997.2 chr17 18379855 18388984 +2175075 LINC02076 chr17 18411159 18414380 +2175079 LGALS9C chr17 18476737 18494945 +2175300 FAM106A chr17 18511221 18551705 +2175407 TBC1D28 chr17 18635006 18644427 +2175517 FOXO3B chr17 18667629 18682262 +2175548 TRIM16L chr17 18697998 18736118 +2175658 FBXW10 chr17 18744026 18779349 +2175789 TVP23B chr17 18781111 18806714 +2175928 AC107982.3 chr17 18809956 18810940 +2175931 PRPSAP2 chr17 18840085 18931287 +2176446 AC107982.2 chr17 18859354 18861466 +2176450 SLC5A10 chr17 18950345 19022595 +2176625 AC090286.1 chr17 18951625 18954149 +2176629 FAM83G chr17 18968789 19004764 +2176673 GRAP chr17 19020673 19047637 +2176738 AC007952.3 chr17 19077775 19087878 +2176750 AC007952.7 chr17 19091069 19091825 +2176753 AC007952.2 chr17 19092974 19096837 +2176763 AC007952.4 chr17 19112000 19112636 +2176766 GRAPL chr17 19127535 19159187 +2176818 AC007952.6 chr17 19141017 19143689 +2176821 AC007952.9 chr17 19150279 19151286 +2176825 AC007952.1 chr17 19155727 19159111 +2176833 AC007952.5 chr17 19160789 19162274 +2176836 AC007952.8 chr17 19164209 19174436 +2176845 AC106017.1 chr17 19203825 19214045 +2176857 EPN2 chr17 19215615 19336715 +2177181 AC106017.2 chr17 19219143 19222527 +2177189 EPN2-AS1 chr17 19296596 19306261 +2177194 B9D1 chr17 19334308 19378193 +2177510 AC124066.1 chr17 19362760 19370236 +2177515 MAPK7 chr17 19377721 19383544 +2177679 MFAP4 chr17 19383442 19387240 +2177738 AC004448.5 chr17 19403283 19403872 +2177742 RNF112 chr17 19411125 19417276 +2177799 AC004448.3 chr17 19411786 19413118 +2177803 AC004448.2 chr17 19417769 19492991 +2177859 LINC02094 chr17 19419035 19424357 +2177863 AC004448.1 chr17 19457080 19458399 +2177867 SLC47A1 chr17 19495385 19579034 +2178108 AC025627.1 chr17 19560111 19597922 +2178114 ALDH3A2 chr17 19648136 19685760 +2178735 AC115989.1 chr17 19649373 19649935 +2178738 SLC47A2 chr17 19678288 19718979 +2178944 AC005722.3 chr17 19719059 19722428 +2178947 AC005722.4 chr17 19737682 19738542 +2178951 ALDH3A1 chr17 19737984 19748943 +2179196 ULK2 chr17 19770829 19867936 +2179395 AC015726.2 chr17 19868568 19868689 +2179398 AC015726.1 chr17 19896590 19897287 +2179404 AKAP10 chr17 19904302 19978343 +2179571 AC005730.3 chr17 19929372 19929737 +2179574 AC005730.2 chr17 20008051 20009234 +2179577 SPECC1 chr17 20009344 20319026 +2179899 AC004702.1 chr17 20185082 20322973 +2179903 AC008088.1 chr17 20323058 20323337 +2179906 LGALS9B chr17 20449395 20467539 +2180002 AC015818.7 chr17 20507413 20508931 +2180005 AC015818.2 chr17 20530042 20530881 +2180008 AC015818.8 chr17 20545371 20549952 +2180011 AC015818.4 chr17 20576667 20578748 +2180015 CDRT15L2 chr17 20579724 20580911 +2180036 LINC02088 chr17 20612912 20633234 +2180042 AC126365.1 chr17 20788071 20789584 +2180045 CCDC144NL chr17 20836447 20896140 +2180081 AC090774.2 chr17 20855946 20857317 +2180084 CCDC144NL-AS1 chr17 20868433 21002276 +2180187 AC107926.1 chr17 20963722 20980238 +2180191 USP22 chr17 20999596 21043760 +2180338 AC087393.2 chr17 20999747 21000323 +2180342 LINC01563 chr17 21075362 21092351 +2180374 DHRS7B chr17 21123364 21193265 +2180477 TMEM11 chr17 21197280 21214624 +2180507 AC087294.1 chr17 21214322 21230035 +2180518 NATD1 chr17 21238870 21253410 +2180530 MAP2K3 chr17 21284672 21315232 +2180796 KCNJ12 chr17 21376357 21419870 +2180819 LINC02693 chr17 21428263 21574517 +2180954 AC068418.3 chr17 21442805 21451525 +2180963 AC068418.2 chr17 21456513 21460215 +2180966 AC068418.1 chr17 21457434 21458989 +2180970 AC233702.5 chr17 21519514 21521269 +2180974 AC233702.7 chr17 21532974 21542786 +2180979 KCNJ18 chr17 21692523 21704612 +2180991 LINC02002 chr17 22233926 22266392 +2181047 AC138761.1 chr17 22266395 22288301 +2181066 FAM27E5 chr17 22298691 22299893 +2181073 AC209154.1 chr17 22406019 22413744 +2181077 AC132825.3 chr17 22420022 22424731 +2181080 MTRNR2L1 chr17 22523111 22524663 +2181088 AC132825.2 chr17 22524563 22525330 +2181092 AC131274.1 chr17 22676695 22692618 +2181096 AC069061.2 chr17 26989189 26999941 +2181104 AC129926.2 chr17 27089545 27170310 +2181110 AC129926.1 chr17 27237859 27241661 +2181114 WSB1 chr17 27294076 27315926 +2181292 AC026254.2 chr17 27333241 27352828 +2181306 KSR1 chr17 27456470 27626438 +2181677 AC069366.2 chr17 27465112 27465541 +2181680 AC015688.6 chr17 27625484 27626438 +2181684 LGALS9 chr17 27629798 27649560 +2181901 NOS2 chr17 27756766 27800529 +2182076 AC005697.2 chr17 27874645 27881237 +2182080 LYRM9 chr17 27878314 27894752 +2182155 LINC01992 chr17 27928924 27991787 +2182187 AC005697.3 chr17 27930177 27930920 +2182191 NLK chr17 28041737 28196381 +2182268 AC061975.8 chr17 28204616 28223735 +2182274 AC061975.7 chr17 28219285 28220005 +2182277 ERVE-1 chr17 28232590 28235281 +2182280 AC061975.6 chr17 28246454 28248006 +2182283 AC061975.4 chr17 28256438 28265551 +2182287 AC061975.1 chr17 28263634 28266369 +2182290 TMEM97 chr17 28319200 28328685 +2182344 IFT20 chr17 28328325 28335489 +2182517 TNFAIP1 chr17 28335602 28347009 +2182589 POLDIP2 chr17 28346633 28357527 +2182644 TMEM199 chr17 28357642 28363683 +2182732 AC002094.2 chr17 28361601 28362859 +2182736 SEBOX chr17 28364268 28365244 +2182748 SARM1 chr17 28364356 28404049 +2182835 VTN chr17 28367284 28373091 +2182871 AC002094.4 chr17 28373256 28373562 +2182874 SLC46A1 chr17 28394642 28407197 +2182945 AC015917.2 chr17 28405240 28406796 +2182949 AC005726.1 chr17 28455752 28614197 +2183022 SLC13A2 chr17 28473293 28497781 +2183198 FOXN1 chr17 28506243 28538896 +2183252 UNC119 chr17 28546707 28552668 +2183331 PIGS chr17 28553383 28571794 +2183490 ALDOC chr17 28573115 28576948 +2183627 AC005726.4 chr17 28573117 28574243 +2183631 SPAG5 chr17 28577565 28599025 +2183833 SPAG5-AS1 chr17 28598790 28617377 +2183855 AC005726.3 chr17 28601827 28602284 +2183858 AC005726.5 chr17 28607963 28609730 +2183862 RSKR chr17 28607964 28614200 +2183981 KIAA0100 chr17 28614446 28645454 +2184332 AC005726.2 chr17 28633206 28635950 +2184341 SDF2 chr17 28648346 28662189 +2184398 SUPT6H chr17 28662198 28702679 +2184610 AC010761.3 chr17 28670054 28672804 +2184614 PROCA1 chr17 28703197 28711854 +2184701 RAB34 chr17 28714281 28718429 +2185143 RPL23A chr17 28719985 28724359 +2185245 AC010761.1 chr17 28721487 28722877 +2185249 TLCD1 chr17 28724348 28727935 +2185294 NEK8 chr17 28725897 28743455 +2185403 AC010761.6 chr17 28727258 28727739 +2185407 AC010761.2 chr17 28732963 28743102 +2185414 TRAF4 chr17 28744005 28750956 +2185598 AC010761.4 chr17 28745569 28747652 +2185602 AC010761.5 chr17 28749731 28750079 +2185606 FAM222B chr17 28755978 28855232 +2185782 ERAL1 chr17 28855010 28861061 +2185891 AC024267.1 chr17 28861072 28861966 +2185894 FLOT2 chr17 28879335 28897733 +2186080 AC024267.3 chr17 28892469 28893342 +2186084 AC024267.6 chr17 28897738 28899402 +2186091 DHRS13 chr17 28897781 28903079 +2186137 PHF12 chr17 28905250 28951771 +2186390 AC024267.4 chr17 28926275 28944749 +2186400 AC024267.5 chr17 28944796 28945394 +2186403 PIPOX chr17 28950513 29057216 +2186502 SEZ6 chr17 28954901 29006440 +2186755 AC024619.2 chr17 29009799 29011009 +2186760 AC024619.1 chr17 29012865 29016512 +2186767 MYO18A chr17 29071124 29180412 +2187338 TIAF1 chr17 29073521 29078857 +2187346 AC024619.3 chr17 29140483 29155489 +2187350 CRYBA1 chr17 29246863 29254494 +2187381 NUFIP2 chr17 29255839 29294148 +2187406 AC068025.2 chr17 29352069 29404105 +2187410 AC068025.1 chr17 29369717 29390777 +2187414 TAOK1 chr17 29390464 29551904 +2187530 ABHD15 chr17 29560547 29567037 +2187540 ABHD15-AS1 chr17 29560547 29707090 +2187544 TP53I13 chr17 29566052 29573157 +2187672 AC104564.3 chr17 29569580 29570519 +2187676 GIT1 chr17 29573469 29594054 +2187975 ANKRD13B chr17 29589769 29614761 +2188149 AC104564.4 chr17 29591703 29592241 +2188153 CORO6 chr17 29614756 29622907 +2188333 AC104564.2 chr17 29621617 29622254 +2188336 SSH2 chr17 29625938 29930276 +2188558 AC104564.1 chr17 29639627 29640825 +2188562 AC104564.5 chr17 29644796 29645847 +2188565 AC023389.1 chr17 29761103 29787836 +2188570 AC104982.2 chr17 29863402 29866092 +2188574 EFCAB5 chr17 29929200 30108452 +2188844 AC104996.1 chr17 30059339 30065677 +2188848 AC104984.2 chr17 30090366 30117497 +2188852 NSRP1 chr17 30115521 30186475 +2189070 hsa-mir-423 chr17 30117079 30117172 +2189073 AC104984.3 chr17 30122429 30126118 +2189077 AC104984.5 chr17 30144062 30144790 +2189081 SLC6A4 chr17 30194319 30236002 +2189234 AC104984.1 chr17 30204318 30206468 +2189238 AC104984.4 chr17 30238741 30252237 +2189242 BLMH chr17 30248203 30292056 +2189394 TMIGD1 chr17 30316333 30334059 +2189431 CPD chr17 30378927 30469989 +2189581 GOSR1 chr17 30477362 30527592 +2189754 AC011840.3 chr17 30550493 30551189 +2189758 AC011840.4 chr17 30557732 30558502 +2189761 AC011840.2 chr17 30564057 30565576 +2189764 AC011840.1 chr17 30573471 30577000 +2189776 AC005562.1 chr17 30576464 30672789 +2189827 AC127024.3 chr17 30726305 30727564 +2189831 AC127024.2 chr17 30729469 30731202 +2189838 CRLF3 chr17 30769388 30824692 +2189902 AC127024.4 chr17 30781493 30782221 +2189906 AC127024.5 chr17 30792372 30792833 +2189909 AC127024.6 chr17 30803654 30804077 +2189912 ATAD5 chr17 30831966 30895869 +2190011 AC130324.2 chr17 30834325 30863028 +2190015 AC130324.1 chr17 30863921 30864940 +2190019 TEFM chr17 30897336 30906238 +2190063 AC130324.3 chr17 30899110 30899651 +2190066 ADAP2 chr17 30906344 30959322 +2190231 AC138207.1 chr17 30956280 30956961 +2190235 AC138207.5 chr17 30964935 30965500 +2190239 AC138207.9 chr17 30968785 30970307 +2190243 RNF135 chr17 30970984 30999911 +2190316 AC138207.4 chr17 30971652 30973312 +2190319 AC138207.7 chr17 30978610 30980250 +2190323 AC138207.2 chr17 31090787 31095450 +2190328 NF1 chr17 31094927 31382116 +2191133 AC079915.1 chr17 31133182 31138518 +2191137 OMG chr17 31272013 31297539 +2191156 EVI2B chr17 31303770 31314105 +2191177 EVI2A chr17 31317560 31321884 +2191207 RAB11FIP4 chr17 31391675 31538211 +2191345 AC003101.2 chr17 31560132 31560573 +2191348 AC003101.1 chr17 31571142 31575659 +2191353 AC007923.4 chr17 31583162 31637543 +2191359 AC007923.1 chr17 31762440 31769048 +2191363 AC004253.2 chr17 31830731 31831750 +2191367 COPRS chr17 31851871 31859291 +2191431 UTP6 chr17 31860904 31901708 +2191547 AC004253.1 chr17 31873926 31886666 +2191551 SUZ12 chr17 31937007 32001038 +2191631 LRRC37B chr17 32007872 32053504 +2191888 AC116407.2 chr17 32127595 32128454 +2191891 AC116407.1 chr17 32141226 32143135 +2191895 RHOT1 chr17 32142454 32253374 +2192385 AC026620.2 chr17 32258615 32265404 +2192389 RHBDL3 chr17 32265832 32324659 +2192501 AC026620.1 chr17 32280387 32280953 +2192505 C17orf75 chr17 32324565 32350023 +2192687 AC005899.3 chr17 32328441 32329395 +2192691 ZNF207 chr17 32350117 32381886 +2192948 AC005899.6 chr17 32408013 32408309 +2192951 AC005899.7 chr17 32410159 32410746 +2192954 AC005899.5 chr17 32411217 32412420 +2192958 AC005899.8 chr17 32423971 32446038 +2192967 AC005899.1 chr17 32430967 32432841 +2192971 PSMD11 chr17 32444379 32483319 +2193143 CDK5R1 chr17 32486993 32491253 +2193169 MYO1D chr17 32492522 32877177 +2193417 AC079336.5 chr17 32495536 32500910 +2193424 AC079336.2 chr17 32509954 32523424 +2193428 AC079336.1 chr17 32512869 32519350 +2193432 AC079336.4 chr17 32518953 32531492 +2193436 AC079336.3 chr17 32529008 32530049 +2193440 AC025211.1 chr17 32627739 32686484 +2193445 AC084809.1 chr17 32876759 32881070 +2193450 AC084809.2 chr17 32905662 32906584 +2193454 TMEM98 chr17 32927910 32945106 +2193583 SPACA3 chr17 32970376 32997877 +2193638 ASIC2 chr17 33013087 34174964 +2193703 AC003687.1 chr17 33052107 33052867 +2193707 AC008133.1 chr17 33111858 33131743 +2193712 AC011824.3 chr17 33529787 33533760 +2193717 AC011824.4 chr17 33534110 33541339 +2193721 AC011824.2 chr17 33565764 33624122 +2193735 AC011824.1 chr17 33627027 33635057 +2193739 AC024614.1 chr17 33680577 33680883 +2193742 AC024614.2 chr17 33688803 33689174 +2193745 AC024614.4 chr17 33791838 33816761 +2193750 AC024610.2 chr17 33827699 34079100 +2193777 AC024610.1 chr17 33976531 33980851 +2193781 AC004147.1 chr17 34080882 34082224 +2193785 AC004147.5 chr17 34118347 34118882 +2193788 AC004147.3 chr17 34142947 34147047 +2193792 AC004147.2 chr17 34155566 34165736 +2193802 LINC01989 chr17 34169372 34195937 +2193817 AC005549.1 chr17 34176538 34178166 +2193820 CCL2 chr17 34255218 34257203 +2193845 CCL7 chr17 34270221 34272242 +2193877 CCL11 chr17 34285742 34288334 +2193889 CCL8 chr17 34319435 34321402 +2193901 CCL13 chr17 34356480 34358610 +2193920 CCL1 chr17 34360328 34363233 +2193932 AC011193.1 chr17 34479272 34482148 +2193953 C17orf102 chr17 34574123 34579369 +2193961 TMEM132E chr17 34579487 34639318 +2194013 AC005552.1 chr17 34725509 34726170 +2194016 AC022903.1 chr17 34837871 34859046 +2194020 CCT6B chr17 34927859 34981078 +2194138 AC022903.2 chr17 34937306 34938604 +2194142 ZNF830 chr17 34961540 34963777 +2194157 LIG3 chr17 34980512 35009743 +2194365 RFFL chr17 35005990 35089319 +2194526 AC004223.4 chr17 35018660 35018991 +2194529 AC004223.2 chr17 35073831 35074374 +2194532 RAD51D chr17 35092208 35121522 +2194888 FNDC8 chr17 35121615 35130732 +2194902 NLE1 chr17 35128730 35142304 +2195055 UNC45B chr17 35147817 35189345 +2195183 AC022916.4 chr17 35164243 35167012 +2195187 SLC35G3 chr17 35192520 35194523 +2195195 AC022916.1 chr17 35231450 35242963 +2195202 SLFN5 chr17 35243071 35273655 +2195240 AC022706.1 chr17 35313479 35325449 +2195293 SLFN11 chr17 35350305 35373701 +2195417 AC060766.6 chr17 35400878 35403006 +2195421 AC060766.4 chr17 35403837 35404373 +2195424 SLFN12 chr17 35411060 35433283 +2195499 SLFN13 chr17 35435096 35448837 +2195643 SLFN12L chr17 35464249 35522379 +2195687 AC015911.5 chr17 35477994 35478444 +2195690 AC015911.3 chr17 35499690 35510270 +2195695 AC015911.2 chr17 35540039 35540797 +2195699 SLFN14 chr17 35548125 35558098 +2195713 AC015911.6 chr17 35553205 35554767 +2195717 AC015911.9 chr17 35561539 35562077 +2195721 SNHG30 chr17 35568076 35574900 +2195735 PEX12 chr17 35574795 35578863 +2195776 AP2B1 chr17 35578046 35726413 +2196343 TAF15 chr17 35713791 35864615 +2196588 RASL10B chr17 35731639 35743521 +2196605 GAS2L2 chr17 35744511 35752878 +2196661 MMP28 chr17 35756249 35795707 +2196761 AC006237.1 chr17 35757199 35758325 +2196765 C17orf50 chr17 35760887 35765079 +2196799 AC015849.2 chr17 35808489 35808897 +2196802 AC015849.3 chr17 35816717 35830293 +2196806 AC015849.4 chr17 35818399 35823713 +2196810 HEATR9 chr17 35854946 35868891 +2197023 AC015849.1 chr17 35868967 35885863 +2197032 CCL5 chr17 35871491 35880793 +2197081 RDM1 chr17 35918066 35930773 +2197291 LYZL6 chr17 35934518 35943713 +2197331 CCL16 chr17 35976493 35981497 +2197367 CCL14 chr17 35983288 35987004 +2197411 AC244100.2 chr17 35983656 35990270 +2197418 CCL15 chr17 35996440 36001553 +2197441 AC244100.3 chr17 36001419 36011618 +2197448 AC244100.4 chr17 36012504 36012891 +2197451 CCL23 chr17 36013056 36017972 +2197485 CCL18 chr17 36064272 36072032 +2197500 AC243829.4 chr17 36072866 36090134 +2197518 CCL3 chr17 36088256 36090169 +2197536 CCL4 chr17 36103827 36105621 +2197559 AC243829.2 chr17 36116177 36177510 +2197567 TBC1D3B chr17 36165681 36176636 +2197634 AC243829.1 chr17 36183235 36196471 +2197645 CCL3L1 chr17 36194869 36196758 +2197664 CCL4L2 chr17 36210924 36212878 +2197769 AC243829.5 chr17 36225246 36226807 +2197773 TBC1D3I chr17 36253456 36264553 +2197862 TBC1D3G chr17 36323884 36334759 +2197896 TBC1D3H chr17 36377531 36388423 +2197930 TBC1D3F chr17 36428618 36439566 +2197964 ZNHIT3 chr17 36486629 36499310 +2198081 MYO19 chr17 36495633 36543435 +2198488 PIGW chr17 36534987 36539310 +2198514 GGNBP2 chr17 36544912 36589848 +2198608 DHRS11 chr17 36591879 36600804 +2198695 MRM1 chr17 36601583 36608964 +2198726 AC243830.2 chr17 36634069 36634698 +2198729 AC243830.3 chr17 36684754 36685129 +2198732 AC243830.1 chr17 36722443 36726346 +2198741 LHX1-DT chr17 36861674 36936670 +2198768 LHX1 chr17 36936785 36944612 +2198802 AC243773.1 chr17 36940049 36943456 +2198806 AATF chr17 36948954 37056871 +2198890 AC243773.2 chr17 36980167 36980422 +2198893 AC244093.4 chr17 36998598 37000034 +2198897 AC244093.3 chr17 37034668 37043252 +2198901 AC244093.5 chr17 37045228 37052890 +2198906 ACACA chr17 37084992 37406836 +2199636 C17orf78 chr17 37375985 37392708 +2199671 AC243654.3 chr17 37386886 37387926 +2199675 TADA2A chr17 37406886 37479725 +2199962 AC243654.1 chr17 37407936 37408594 +2199966 DUSP14 chr17 37489891 37513501 +2199998 SYNRG chr17 37514807 37609472 +2200364 AC243585.2 chr17 37609739 37613841 +2200368 DDX52 chr17 37609739 37643446 +2200524 AC243571.2 chr17 37642947 37684252 +2200531 AC243585.1 chr17 37649133 37650894 +2200535 HNF1B chr17 37686431 37745105 +2200663 AC243571.1 chr17 37798894 37802788 +2200668 TBC1D3K chr17 37924415 37935365 +2200702 TBC1D3L chr17 37977972 37989048 +2200766 TBC1D3D chr17 38003976 38014902 +2200800 TBC1D3C chr17 38057693 38068592 +2200834 TBC1D3E chr17 38127951 38138862 +2200868 TBC1D3 chr17 38181659 38192541 +2200902 MRPL45 chr17 38297023 38323217 +2200943 GPR179 chr17 38325530 38343847 +2201004 SOCS7 chr17 38351844 38405593 +2201097 ARHGAP23 chr17 38419280 38512385 +2201300 AC244153.1 chr17 38450394 38452444 +2201324 SRCIN1 chr17 38530031 38605952 +2201536 AC006449.1 chr17 38601049 38602701 +2201540 EPOP chr17 38671703 38674957 +2201548 AC006449.6 chr17 38702452 38704747 +2201551 AC006449.2 chr17 38703480 38706261 +2201555 MLLT6 chr17 38705273 38729795 +2201680 AC006449.3 chr17 38715328 38720272 +2201687 CISD3 chr17 38730341 38735605 +2201708 PCGF2 chr17 38733898 38749817 +2201872 AC006449.5 chr17 38749360 38751457 +2201875 PSMB3 chr17 38752741 38764225 +2201943 PIP4K2B chr17 38765689 38800126 +2201997 CWC25 chr17 38800441 38825355 +2202112 C17orf98 chr17 38835088 38841455 +2202124 RPL23 chr17 38847860 38853764 +2202232 LASP1 chr17 38869859 38921770 +2202360 AC006441.1 chr17 38903704 38904600 +2202364 AC006441.3 chr17 38918801 38921769 +2202368 LINC00672 chr17 38925168 38929384 +2202378 FBXO47 chr17 38936432 38967403 +2202406 AC006441.4 chr17 39003248 39013032 +2202414 LINC02079 chr17 39026715 39027110 +2202418 PLXDC1 chr17 39063313 39154394 +2202695 AC091178.2 chr17 39086976 39091942 +2202699 ARL5C chr17 39156894 39167484 +2202739 AC004408.1 chr17 39173290 39177503 +2202743 CACNB1 chr17 39173453 39197703 +2202918 RPL19 chr17 39200283 39204732 +2202997 STAC2 chr17 39210541 39225945 +2203052 FBXL20 chr17 39252663 39402523 +2203210 AC005288.1 chr17 39401793 39406233 +2203218 MED1 chr17 39404285 39451272 +2203352 CDK12 chr17 39461486 39564907 +2203486 AC009283.1 chr17 39566915 39567559 +2203489 NEUROD2 chr17 39603536 39609777 +2203501 AC087491.1 chr17 39619613 39622770 +2203511 PPP1R1B chr17 39626740 39636626 +2203637 STARD3 chr17 39637090 39664201 +2204031 TCAP chr17 39664187 39666555 +2204052 PNMT chr17 39667981 39670475 +2204084 PGAP3 chr17 39671122 39696797 +2204229 ERBB2 chr17 39687914 39730426 +2204807 MIEN1 chr17 39728496 39730532 +2204845 GRB7 chr17 39737927 39747291 +2205074 IKZF3 chr17 39757718 39864312 +2205376 ZPBP2 chr17 39868164 39877896 +2205449 GSDMB chr17 39904595 39919854 +2205685 ORMDL3 chr17 39921041 39927601 +2205767 AC090844.2 chr17 39927742 39939601 +2205780 LRRC3C chr17 39941474 39944734 +2205790 GSDMA chr17 39953263 39977768 +2205860 PSMD3 chr17 39980807 39997959 +2205940 AC090844.3 chr17 40012226 40014705 +2205948 CSF3 chr17 40015361 40017813 +2206047 MED24 chr17 40019097 40061215 +2206729 THRA chr17 40058290 40093867 +2206898 NR1D1 chr17 40092793 40100589 +2206920 MSL1 chr17 40121971 40136917 +2207048 CASC3 chr17 40140318 40172171 +2207146 RAPGEFL1 chr17 40177010 40195656 +2207358 WIPF2 chr17 40219304 40284136 +2207499 CDC6 chr17 40287879 40304657 +2207591 RARA chr17 40309180 40357643 +2207740 AC080112.4 chr17 40317698 40318676 +2207745 RARA-AS1 chr17 40340867 40343136 +2207750 GJD3 chr17 40360652 40364737 +2207758 AC080112.1 chr17 40360655 40364693 +2207762 TOP2A chr17 40388525 40417896 +2207867 IGFBP4 chr17 40443450 40457725 +2207881 TNS4 chr17 40475828 40501623 +2207929 AC004585.1 chr17 40516892 40527002 +2207943 CCR7 chr17 40553769 40565472 +2207973 SMARCE1 chr17 40624962 40648654 +2208814 AC073508.3 chr17 40648300 40649718 +2208817 KRT222 chr17 40654665 40665181 +2208876 KRT24 chr17 40697991 40703752 +2208898 KRT25 chr17 40748021 40755331 +2208920 KRT26 chr17 40766238 40772162 +2208942 KRT27 chr17 40776808 40782550 +2208969 KRT28 chr17 40792196 40799959 +2208991 AC090283.1 chr17 40803744 40809296 +2208996 KRT10 chr17 40818117 40822614 +2209025 TMEM99 chr17 40819106 40836270 +2209060 AC004231.3 chr17 40850800 40863282 +2209064 KRT12 chr17 40861303 40867223 +2209110 KRT20 chr17 40875889 40885242 +2209135 AC004231.1 chr17 40921430 40975926 +2209141 KRT23 chr17 40922696 40937634 +2209251 KRT39 chr17 40958417 40966948 +2209295 KRT40 chr17 40977716 40987135 +2209361 KRTAP3-3 chr17 40993430 40994164 +2209369 KRTAP3-2 chr17 40999193 40999906 +2209377 KRTAP3-1 chr17 41008521 41019324 +2209389 KRTAP1-5 chr17 41026026 41027208 +2209397 KRTAP1-4 chr17 41029697 41030104 +2209405 KRTAP1-3 chr17 41033884 41034874 +2209413 KRTAP1-1 chr17 41040541 41041450 +2209421 KRTAP2-1 chr17 41046541 41047316 +2209437 KRTAP2-2 chr17 41054498 41055230 +2209453 KRTAP2-3 chr17 41059240 41060114 +2209461 KRTAP2-4 chr17 41065116 41065879 +2209469 KRTAP4-7 chr17 41084150 41085141 +2209485 AC100808.1 chr17 41090338 41093246 +2209489 KRTAP4-8 chr17 41096981 41098142 +2209507 KRTAP4-16 chr17 41101502 41102209 +2209514 KRTAP4-9 chr17 41105332 41106488 +2209532 KRTAP4-11 chr17 41117181 41118373 +2209540 KRTAP4-12 chr17 41123091 41124182 +2209548 KRTAP4-6 chr17 41139433 41140487 +2209555 KRTAP4-5 chr17 41148924 41149825 +2209563 KRTAP4-4 chr17 41159649 41160748 +2209571 KRTAP4-3 chr17 41167231 41168221 +2209579 KRTAP4-2 chr17 41177446 41178221 +2209587 KRTAP4-1 chr17 41184102 41185342 +2209604 KRTAP9-1 chr17 41189887 41190639 +2209634 KRTAP9-2 chr17 41226648 41227652 +2209642 KRTAP9-3 chr17 41232449 41233454 +2209650 KRTAP9-8 chr17 41237999 41239004 +2209658 KRTAP9-4 chr17 41249687 41250653 +2209666 KRTAP9-9 chr17 41255384 41256364 +2209674 KRTAP9-6 chr17 41265339 41266641 +2209682 KRTAP9-7 chr17 41275659 41276697 +2209690 KRTAP29-1 chr17 41301826 41302851 +2209697 KRTAP16-1 chr17 41307700 41309253 +2209704 KRTAP17-1 chr17 41314912 41315710 +2209712 KRT33A chr17 41346092 41350828 +2209732 KRT33B chr17 41363498 41369813 +2209752 KRT34 chr17 41377650 41382403 +2209772 KRT31 chr17 41393721 41397608 +2209792 AC003958.2 chr17 41402416 41425049 +2209802 KRT37 chr17 41420547 41424585 +2209822 KRT38 chr17 41436446 41440921 +2209841 KRT32 chr17 41459811 41467429 +2209861 KRT35 chr17 41476689 41481140 +2209902 KRT36 chr17 41486136 41492546 +2209942 KRT13 chr17 41500981 41505705 +2210056 AC019349.1 chr17 41500983 41502409 +2210060 KRT15 chr17 41513745 41522529 +2210189 KRT19 chr17 41523617 41528308 +2210246 LINC00974 chr17 41549606 41554495 +2210251 KRT9 chr17 41565836 41572059 +2210296 KRT14 chr17 41582279 41586895 +2210326 KRT16 chr17 41609778 41615899 +2210374 KRT17 chr17 41619442 41624842 +2210472 EIF1 chr17 41688885 41692668 +2210524 GAST chr17 41712331 41715969 +2210536 HAP1 chr17 41717742 41734644 +2210666 JUP chr17 41754604 41786931 +2210858 P3H4 chr17 41801947 41812604 +2210943 FKBP10 chr17 41812680 41823217 +2211056 NT5C3B chr17 41825057 41836260 +2211242 KLHL10 chr17 41835685 41848384 +2211279 AC125257.1 chr17 41848518 41851447 +2211282 KLHL11 chr17 41848518 41865423 +2211292 ACLY chr17 41866917 41930542 +2211630 AC125257.2 chr17 41867581 41867736 +2211633 TTC25 chr17 41930617 41966503 +2211716 CNP chr17 41966763 41977740 +2211798 DNAJC7 chr17 41976435 42021376 +2212136 NKIRAS2 chr17 42011382 42025644 +2212295 ZNF385C chr17 42025576 42098479 +2212375 C17orf113 chr17 42038232 42050601 +2212387 DHX58 chr17 42101404 42112714 +2212492 KAT2A chr17 42113111 42121367 +2212592 HSPB9 chr17 42122804 42123352 +2212600 RAB5C chr17 42124976 42155044 +2212703 AC099811.3 chr17 42154600 42155972 +2212708 KCNH4 chr17 42156891 42181142 +2212787 HCRT chr17 42184060 42185452 +2212797 GHDC chr17 42188799 42194532 +2212976 STAT5B chr17 42199168 42276707 +2213062 AC099811.4 chr17 42268587 42269807 +2213066 AC099811.1 chr17 42270517 42272683 +2213070 AC099811.5 chr17 42272069 42275571 +2213074 STAT5A chr17 42287547 42311943 +2213314 STAT3 chr17 42313324 42388568 +2213617 CAVIN1 chr17 42402449 42423256 +2213627 ATP6V0A1 chr17 42458844 42522611 +2214055 AC107993.1 chr17 42495867 42496550 +2214058 AC067852.3 chr17 42509784 42511519 +2214061 NAGLU chr17 42536241 42544449 +2214113 HSD17B1 chr17 42549214 42555213 +2214169 AC067852.2 chr17 42552436 42554748 +2214172 COASY chr17 42561467 42566277 +2214322 MLX chr17 42567068 42573239 +2214435 PSMC3IP chr17 42572315 42577831 +2214592 AC067852.5 chr17 42577825 42578366 +2214595 RETREG3 chr17 42579513 42610623 +2214765 TUBG1 chr17 42609683 42615238 +2214845 TUBG2 chr17 42659284 42667006 +2214886 PLEKHH3 chr17 42667914 42676994 +2215034 CCR10 chr17 42678889 42683917 +2215060 AC100793.2 chr17 42679963 42682020 +2215065 CNTNAP1 chr17 42682531 42699993 +2215178 AC100793.3 chr17 42683187 42699466 +2215182 EZH1 chr17 42700275 42745049 +2215678 AC100793.4 chr17 42751289 42751717 +2215681 RAMP2-AS1 chr17 42753914 42761257 +2215712 RAMP2 chr17 42758447 42763041 +2215777 VPS25 chr17 42773449 42779599 +2215842 WNK4 chr17 42780610 42797066 +2215948 COA3 chr17 42795147 42798704 +2215970 CNTD1 chr17 42798800 42811587 +2216058 BECN1 chr17 42810134 42833350 +2216305 PSME3 chr17 42824385 42843760 +2216640 AOC2 chr17 42844580 42850707 +2216667 AOC3 chr17 42851184 42858130 +2216749 LINC00671 chr17 42874670 42898704 +2216768 G6PC chr17 42900797 42914438 +2216815 AARSD1 chr17 42950526 42964498 +2216987 PTGES3L chr17 42968088 42980433 +2217062 RUNDC1 chr17 42980565 42993690 +2217091 RPL27 chr17 42998273 43002959 +2217181 IFI35 chr17 43006725 43014456 +2217243 VAT1 chr17 43014607 43025123 +2217351 RND2 chr17 43025231 43032041 +2217370 BRCA1 chr17 43044295 43170245 +2218242 NBR2 chr17 43125551 43153671 +2218267 AC060780.1 chr17 43148368 43171037 +2218295 NBR1 chr17 43170481 43211689 +2218498 TMEM106A chr17 43211835 43220041 +2218626 CCDC200 chr17 43216941 43305397 +2218781 LINC00910 chr17 43338741 43389199 +2218902 ARL4D chr17 43398993 43401137 +2218912 MIR2117HG chr17 43444707 43451200 +2218916 DHX8 chr17 43483865 43610338 +2219133 ETV4 chr17 43527844 43579620 +2219357 MEOX1 chr17 43640389 43661922 +2219400 LINC02594 chr17 43679341 43706709 +2219405 SOST chr17 43753738 43758791 +2219415 DUSP3 chr17 43766125 43778977 +2219463 CFAP97D1 chr17 43780435 43787620 +2219492 AC003098.1 chr17 43782804 43784682 +2219497 MPP3 chr17 43800799 43833170 +2219676 CD300LG chr17 43847148 43863639 +2219778 MPP2 chr17 43875357 43909711 +2220219 AC007993.3 chr17 43914433 43923001 +2220228 FAM215A chr17 43917194 43917985 +2220233 AC007993.2 chr17 43927563 43932622 +2220238 LINC01976 chr17 43938363 43938959 +2220242 PPY chr17 43940804 43942468 +2220298 PYY chr17 43952738 44004469 +2220327 NAGS chr17 44004622 44009068 +2220369 TMEM101 chr17 44011188 44023946 +2220455 LSM12 chr17 44034635 44067619 +2220509 G6PC3 chr17 44070735 44076344 +2220607 HDAC5 chr17 44076746 44123702 +2220857 AC023855.1 chr17 44115912 44120595 +2220862 C17orf53 chr17 44141906 44162476 +2220941 ASB16 chr17 44170447 44179084 +2220981 ASB16-AS1 chr17 44175968 44186723 +2221020 TMUB2 chr17 44186970 44191929 +2221200 ATXN7L3 chr17 44191805 44200113 +2221371 AC004596.1 chr17 44198882 44216565 +2221375 UBTF chr17 44205033 44221626 +2221788 AC003102.1 chr17 44221401 44223710 +2221794 SLC4A1 chr17 44248390 44268141 +2221894 AC003043.2 chr17 44276368 44281182 +2221898 RUNDC3A-AS1 chr17 44299574 44315315 +2221919 RUNDC3A chr17 44308413 44318670 +2222032 SLC25A39 chr17 44319625 44324870 +2222309 AC003043.1 chr17 44328613 44331462 +2222313 GRN chr17 44345246 44353106 +2222603 FAM171A2 chr17 44353215 44363853 +2222665 ITGA2B chr17 44372180 44389649 +2222855 GPATCH8 chr17 44395281 44503430 +2223006 AC103703.1 chr17 44486153 44486815 +2223009 FZD2 chr17 44557484 44561262 +2223017 LINC01180 chr17 44646364 44650349 +2223022 MEIOC chr17 44656404 44690308 +2223110 CCDC43 chr17 44673069 44689779 +2223167 AC091152.2 chr17 44673689 44676257 +2223170 DBF4B chr17 44708608 44752264 +2223311 ADAM11 chr17 44758988 44781846 +2223548 AC005180.2 chr17 44793199 44794474 +2223552 AC005180.1 chr17 44794747 44797783 +2223556 GJC1 chr17 44798448 44830816 +2223638 HIGD1B chr17 44846353 44850476 +2223685 EFTUD2 chr17 44849948 44899445 +2224111 CCDC103 chr17 44899142 44905390 +2224171 FAM187A chr17 44899712 44905390 +2224198 GFAP chr17 44903159 44916937 +2224608 KIF18B chr17 44924709 44947773 +2224717 AC015936.1 chr17 44947912 44948939 +2224720 C1QL1 chr17 44959693 44968303 +2224730 AC015936.2 chr17 44982514 44982772 +2224733 DCAKD chr17 45023340 45061109 +2224845 NMT1 chr17 45051610 45109016 +2224982 PLCD3 chr17 45108959 45133354 +2225084 ACBD4 chr17 45132600 45144181 +2225349 AC142472.1 chr17 45146730 45148470 +2225352 HEXIM1 chr17 45148502 45152101 +2225360 AC138150.1 chr17 45150400 45161510 +2225367 HEXIM2 chr17 45160700 45170040 +2225452 AC138150.2 chr17 45168800 45171584 +2225459 AC008105.3 chr17 45190931 45222222 +2225480 FMNL1 chr17 45221444 45247319 +2225695 AC008105.1 chr17 45238028 45241734 +2225702 MAP3K14-AS1 chr17 45247916 45269824 +2225760 SPATA32 chr17 45254393 45262094 +2225810 MAP3K14 chr17 45263119 45317029 +2225911 AC003070.2 chr17 45371402 45372057 +2225915 ARHGAP27 chr17 45393902 45434421 +2226227 AC003070.1 chr17 45396932 45397477 +2226231 PLEKHM1 chr17 45435900 45490749 +2226426 AC091132.2 chr17 45452844 45464065 +2226432 AC091132.1 chr17 45533963 45534710 +2226436 AC091132.4 chr17 45545804 45563230 +2226452 AC126544.2 chr17 45586452 45588379 +2226456 AC217774.1 chr17 45731703 45732977 +2226460 AC217774.2 chr17 45733353 45734669 +2226464 CRHR1 chr17 45784280 45835828 +2226767 MAPT-AS1 chr17 45799390 45895680 +2226792 SPPL2C chr17 45844881 45847067 +2226800 MAPT chr17 45894382 46028334 +2227174 MAPT-IT1 chr17 45895783 45898798 +2227177 CR936218.2 chr17 45907670 45910779 +2227181 STH chr17 45999250 45999694 +2227189 KANSL1 chr17 46029916 46225389 +2227674 CR936218.1 chr17 46035313 46035770 +2227678 KANSL1-AS1 chr17 46193576 46196723 +2227687 ARL17B chr17 46274784 46361797 +2227813 LRRC37A chr17 46292733 46337794 +2227909 LRRC37A2 chr17 46511511 46555650 +2227985 ARL17A chr17 46516702 46579682 +2228071 FAM215B chr17 46558830 46562795 +2228075 NSF chr17 46590669 46757464 +2228246 WNT3 chr17 46762506 46833154 +2228274 WNT9B chr17 46833201 46886730 +2228312 LINC01974 chr17 46909742 46911512 +2228316 AC005670.1 chr17 46916770 46923034 +2228321 GOSR2 chr17 46923075 46975524 +2229040 RPRML chr17 46978156 46979253 +2229048 AC005670.3 chr17 46983287 47100323 +2229242 CDC27 chr17 47117703 47189422 +2229600 AC002558.3 chr17 47160398 47167723 +2229608 AC002558.2 chr17 47169826 47171049 +2229612 MYL4 chr17 47200446 47223679 +2229777 ITGB3 chr17 47253846 47311816 +2229843 AC068234.3 chr17 47279526 47280047 +2229846 AC068234.2 chr17 47303460 47323613 +2229854 EFCAB13 chr17 47323290 47441312 +2230068 AC040934.1 chr17 47409322 47423526 +2230072 NPEPPS chr17 47522942 47623276 +2230452 AC025682.1 chr17 47603860 47649420 +2230470 KPNB1 chr17 47649476 47685505 +2230734 AC015674.1 chr17 47682417 47682683 +2230737 TBKBP1 chr17 47694081 47712050 +2230804 TBX21 chr17 47733236 47746122 +2230825 OSBPL7 chr17 47807372 47821834 +2231072 MRPL10 chr17 47823272 47831541 +2231155 LRRC46 chr17 47831634 47837719 +2231239 SCRN2 chr17 47837692 47841289 +2231400 SP6 chr17 47844908 47855874 +2231419 AC018521.3 chr17 47863342 47865190 +2231423 AC018521.7 chr17 47879472 47882398 +2231426 AC018521.5 chr17 47891229 47895812 +2231436 SP2 chr17 47896150 47928957 +2231513 SP2-AS1 chr17 47897330 47941410 +2231531 AC018521.6 chr17 47929682 47933106 +2231536 PNPO chr17 47941506 47949308 +2231760 AC018521.2 chr17 47946802 47948275 +2231767 PRR15L chr17 47951967 47957883 +2231777 CDK5RAP3 chr17 47967810 47981781 +2232236 AC018521.4 chr17 47980398 47996196 +2232240 COPZ2 chr17 48026167 48038030 +2232359 AC004477.1 chr17 48045141 48048073 +2232365 NFE2L1 chr17 48048329 48061545 +2232597 AC004477.2 chr17 48060383 48060669 +2232601 AC004477.3 chr17 48066704 48067293 +2232604 CBX1 chr17 48070052 48101478 +2232689 SNX11 chr17 48103357 48123074 +2232884 SKAP1 chr17 48133442 48430275 +2233036 SKAP1-AS1 chr17 48185938 48204529 +2233041 THRA1/BTR chr17 48294335 48308762 +2233057 AC036222.2 chr17 48377262 48380370 +2233061 AC036222.1 chr17 48460370 48466040 +2233065 HOXB1 chr17 48528526 48531011 +2233082 HOXB2 chr17 48540894 48544989 +2233098 HOXB-AS1 chr17 48543551 48551250 +2233122 HOXB3 chr17 48548870 48604912 +2233260 HOXB-AS3 chr17 48549630 48606414 +2233322 HOXB-AS2 chr17 48557262 48560333 +2233326 HOXB4 chr17 48575507 48578350 +2233336 AC103702.1 chr17 48579630 48582259 +2233339 HOXB5 chr17 48591257 48593961 +2233349 HOXB6 chr17 48595751 48604992 +2233380 HOXB7 chr17 48607232 48633572 +2233396 HOXB8 chr17 48611377 48615292 +2233421 HOXB9 chr17 48621156 48626358 +2233431 HOXB-AS4 chr17 48628675 48634932 +2233438 AC103702.2 chr17 48635923 48647023 +2233449 LINC02086 chr17 48646923 48707346 +2233483 PRAC1 chr17 48721719 48722518 +2233493 PRAC2 chr17 48723185 48724758 +2233512 HOXB13 chr17 48724763 48729178 +2233522 AC091179.1 chr17 48733091 48733888 +2233526 TTLL6 chr17 48762235 48817214 +2233694 CALCOCO2 chr17 48830988 48866522 +2234032 ATP5MC1 chr17 48892765 48895871 +2234130 UBE2Z chr17 48908407 48929056 +2234218 SNF8 chr17 48929316 48944842 +2234421 AC091133.1 chr17 48931791 48937100 +2234426 GIP chr17 48958554 48968596 +2234444 AC091133.3 chr17 48995266 48997492 +2234449 IGF2BP1 chr17 48997385 49056145 +2234536 AC091133.4 chr17 49004731 49013725 +2234542 B4GALNT2 chr17 49132460 49176840 +2234624 GNGT2 chr17 49202791 49210574 +2234701 ABI3 chr17 49210411 49223225 +2234766 PHOSPHO1 chr17 49223362 49230766 +2234836 AC004797.1 chr17 49230853 49318011 +2234933 ZNF652 chr17 49289206 49362473 +2234992 AC091180.2 chr17 49361150 49369998 +2235005 AC091180.5 chr17 49370740 49476988 +2235010 AC091180.4 chr17 49375380 49380094 +2235014 PHB chr17 49404049 49414905 +2235194 AC091180.3 chr17 49404081 49405197 +2235198 LINC02075 chr17 49457861 49461749 +2235203 NGFR chr17 49495293 49515008 +2235247 AC006487.1 chr17 49505657 49574064 +2235252 AC006487.2 chr17 49544788 49577962 +2235260 NXPH3 chr17 49575858 49583827 +2235283 SPOP chr17 49598884 49678163 +2235728 SLC35B1 chr17 49700934 49709014 +2235960 AC015795.1 chr17 49708334 49720060 +2235964 FAM117A chr17 49710332 49789180 +2236090 KAT7 chr17 49788681 49835026 +2236361 AC027801.4 chr17 49834239 49836454 +2236365 TAC4 chr17 49838309 49848017 +2236442 FLJ45513 chr17 49845910 49848837 +2236447 AC027801.1 chr17 49887598 49900893 +2236454 AC027801.3 chr17 49914403 49932918 +2236459 DLX4 chr17 49968970 49974959 +2236499 DLX3 chr17 49990005 49995224 +2236520 AC009720.1 chr17 49996889 50016844 +2236524 PICART1 chr17 50050349 50055739 +2236529 ITGA3 chr17 50055968 50090481 +2236781 AC002401.4 chr17 50094065 50094647 +2236784 PDK2 chr17 50094737 50112152 +2236985 AC002401.3 chr17 50098460 50098899 +2236988 AC002401.2 chr17 50100704 50101920 +2236992 SAMD14 chr17 50110040 50129882 +2237102 PPP1R9B chr17 50133737 50150677 +2237134 AC002401.1 chr17 50135586 50146176 +2237140 AC015909.2 chr17 50158333 50161276 +2237144 AC015909.3 chr17 50163523 50165316 +2237147 SGCA chr17 50164214 50175928 +2237302 COL1A1 chr17 50183289 50201632 +2237476 AC015909.1 chr17 50199876 50215922 +2237563 AC015909.4 chr17 50212933 50215357 +2237568 TMEM92 chr17 50271406 50281485 +2237606 TMEM92-AS1 chr17 50281577 50287855 +2237612 XYLT2 chr17 50346126 50363138 +2237715 MRPL27 chr17 50367857 50373207 +2237793 EME1 chr17 50373220 50381483 +2237922 LRRC59 chr17 50375059 50397523 +2237958 AC004707.1 chr17 50396438 50397888 +2237962 ACSF2 chr17 50426158 50474845 +2238272 CHAD chr17 50464496 50468906 +2238306 AC021491.4 chr17 50475819 50478391 +2238309 RSAD1 chr17 50478860 50485974 +2238401 AC021491.1 chr17 50503412 50508328 +2238405 MYCBPAP chr17 50508384 50531501 +2238676 AC021491.2 chr17 50525520 50538761 +2238688 EPN3 chr17 50532682 50543750 +2238904 SPATA20 chr17 50543058 50555852 +2239379 CACNA1G-AS1 chr17 50556207 50562108 +2239389 CACNA1G chr17 50560715 50627474 +2241808 AC021491.3 chr17 50563203 50563783 +2241812 AC004590.1 chr17 50627032 50631940 +2241816 ABCC3 chr17 50634777 50692253 +2242156 ANKRD40 chr17 50693198 50707914 +2242182 AC005921.2 chr17 50693448 50695449 +2242186 LUC7L3 chr17 50719565 50756219 +2242506 ANKRD40CL chr17 50761029 50767557 +2242554 AC005921.4 chr17 50781306 50792493 +2242558 WFIKKN2 chr17 50834650 50842353 +2242577 AC091062.1 chr17 50840057 50841626 +2242581 TOB1 chr17 50862223 50867978 +2242605 TOB1-AS1 chr17 50866679 50910774 +2242624 AC005920.4 chr17 50909637 50910232 +2242628 AC005920.1 chr17 50934989 50944713 +2242632 AC005920.3 chr17 50944104 50948750 +2242639 SPAG9 chr17 50962174 51120868 +2243100 AC005920.2 chr17 51042524 51085471 +2243105 NME1 chr17 51153536 51162428 +2243216 NME2 chr17 51165435 51171747 +2243313 MBTD1 chr17 51177425 51260163 +2243474 AC006141.1 chr17 51249579 51251748 +2243477 UTP18 chr17 51260546 51297936 +2243585 LINC02071 chr17 51312609 51335165 +2243596 AC005823.2 chr17 51332679 51334090 +2243600 AC005823.1 chr17 51335261 51336240 +2243604 LINC02073 chr17 51336646 51521401 +2243648 CA10 chr17 51630313 52160017 +2243809 LINC01982 chr17 52390515 52535701 +2243815 LINC02089 chr17 52862121 52899588 +2243820 C17orf112 chr17 52985513 52987652 +2243831 AC034268.2 chr17 53276760 54365634 +2243844 KIF2B chr17 53822927 53825193 +2243852 AC015943.1 chr17 54609249 54670420 +2243856 TOM1L1 chr17 54899387 54961956 +2244318 COX11 chr17 54951902 54968785 +2244406 AC007485.1 chr17 54964474 54964679 +2244409 STXBP4 chr17 54968727 55173632 +2244572 HLF chr17 55264960 55325187 +2244661 AC007638.2 chr17 55271504 55273653 +2244665 AC007638.1 chr17 55325757 55327791 +2244669 MMD chr17 55392622 55421924 +2244726 SMIM36 chr17 55448433 55511444 +2244750 TMEM100 chr17 55719627 55732121 +2244791 PCTP chr17 55751051 55842830 +2244900 AC090618.1 chr17 55842677 55872939 +2244905 ANKFN1 chr17 55882301 56511659 +2245108 NOG chr17 56593699 56595598 +2245116 C17orf67 chr17 56791913 56838773 +2245145 AC106858.1 chr17 56803841 56804269 +2245148 DGKE chr17 56834107 56869567 +2245227 TRIM25 chr17 56836387 56914080 +2245354 AC015912.1 chr17 56888880 56891841 +2245358 AC015912.3 chr17 56914186 56914533 +2245361 COIL chr17 56938199 56961050 +2245390 AC004584.1 chr17 56939932 56941275 +2245394 SCPEP1 chr17 56978105 57006768 +2245615 AC004584.3 chr17 56982749 56985104 +2245618 AC007114.1 chr17 57071814 57085024 +2245630 AKAP1 chr17 57085092 57121346 +2245940 AC007114.2 chr17 57092145 57096425 +2245943 AC003950.1 chr17 57196081 57213300 +2245947 AC091181.2 chr17 57253236 57255855 +2245952 MSI2 chr17 57255851 57684689 +2246179 AC007431.2 chr17 57522248 57523597 +2246184 AC007431.1 chr17 57600856 57608412 +2246189 CCDC182 chr17 57744495 57745299 +2246197 AC015845.2 chr17 57771946 57834749 +2246205 MRPS23 chr17 57834781 57850056 +2246248 CUEDC1 chr17 57861243 57955412 +2246417 AC015845.1 chr17 57912333 57922581 +2246424 AC015813.4 chr17 57955965 57956143 +2246427 VEZF1 chr17 57971547 57988259 +2246484 AC015813.1 chr17 57989039 57994850 +2246493 SRSF1 chr17 58000919 58007346 +2246589 AC015813.8 chr17 58050789 58060739 +2246596 AC015813.3 chr17 58076891 58083204 +2246601 DYNLL2 chr17 58083419 58095542 +2246613 OR4D1 chr17 58148449 58159555 +2246632 OR4D2 chr17 58166982 58171411 +2246649 EPX chr17 58192726 58205174 +2246681 AC005962.1 chr17 58202352 58203003 +2246684 MKS1 chr17 58205437 58219605 +2246968 LPO chr17 58218548 58268518 +2247162 AC005962.2 chr17 58219375 58233479 +2247169 AC004687.3 chr17 58241164 58247385 +2247173 MPO chr17 58269855 58280935 +2247220 TSPOAP1 chr17 58301228 58328795 +2247449 TSPOAP1-AS1 chr17 58324472 58415766 +2247513 AC004687.1 chr17 58330884 58332508 +2247516 SUPT4H1 chr17 58345175 58353093 +2247599 RNF43 chr17 58352500 58417595 +2247744 HSF5 chr17 58420167 58488408 +2247762 MTMR4 chr17 58489529 58517905 +2247933 SEPTIN4-AS1 chr17 58519837 58557799 +2247948 SEPTIN4 chr17 58520250 58544368 +2248467 TEX14 chr17 58556678 58692055 +2248768 AC011195.2 chr17 58660424 58692018 +2248778 RAD51C chr17 58692573 58735611 +2249010 AC025521.1 chr17 58747055 58747340 +2249013 PPM1E chr17 58755854 58985179 +2249033 AC100832.2 chr17 58965952 58966727 +2249036 TRIM37 chr17 58982638 59106921 +2249359 AC099850.1 chr17 59106598 59118267 +2249363 SKA2 chr17 59109857 59155260 +2249472 PRR11 chr17 59155499 59204705 +2249629 AC099850.3 chr17 59202677 59203829 +2249633 SMG8 chr17 59209400 59215247 +2249693 GDPD1 chr17 59220467 59275970 +2249831 YPEL2 chr17 59331655 59401729 +2249885 AC091059.1 chr17 59400488 59403303 +2249889 LINC01476 chr17 59422088 59526946 +2249933 DHX40 chr17 59565558 59608345 +2250097 AC091271.1 chr17 59618553 59619714 +2250100 CLTC chr17 59619689 59696956 +2250419 PTRH2 chr17 59674636 59707626 +2250453 VMP1 chr17 59707192 59842255 +2250643 AC040904.1 chr17 59784813 59785035 +2250646 TUBD1 chr17 59859479 59892945 +2250872 RPS6KB1 chr17 59893046 59950574 +2251100 RNFT1 chr17 59952240 59964761 +2251211 RNFT1-DT chr17 59964832 59996972 +2251221 AC005702.5 chr17 60019149 60020006 +2251225 HEATR6 chr17 60043194 60078931 +2251480 AC025048.4 chr17 60079309 60088695 +2251484 AC025048.2 chr17 60122642 60135743 +2251578 AC025048.7 chr17 60135039 60136271 +2251581 AC025048.1 chr17 60135762 60140081 +2251585 CA4 chr17 60149942 60170899 +2251659 USP32 chr17 60177327 60422470 +2251944 C17orf64 chr17 60392429 60431426 +2251984 APPBP2 chr17 60443158 60526242 +2252082 AC011921.1 chr17 60526293 60550798 +2252095 LINC01999 chr17 60564547 60586623 +2252101 PPM1D chr17 60600183 60666280 +2252164 BCAS3 chr17 60677453 61392838 +2252784 AC005884.1 chr17 61034636 61070122 +2252789 AC005884.2 chr17 61069856 61070356 +2252793 AC005856.1 chr17 61119095 61135969 +2252800 AC005746.3 chr17 61354763 61355155 +2252803 AC005746.2 chr17 61361668 61400243 +2252809 AC005746.1 chr17 61382785 61384680 +2252817 TBX2-AS1 chr17 61393456 61411555 +2252838 TBX2 chr17 61399843 61409466 +2252886 C17orf82 chr17 61411751 61413280 +2252889 TBX4 chr17 61452404 61485110 +2252996 AC005901.1 chr17 61460224 61463384 +2253000 NACA2 chr17 61590421 61591219 +2253008 BRIP1 chr17 61681266 61863521 +2253137 INTS2 chr17 61865367 61928016 +2253453 MED13 chr17 61942605 62065278 +2253541 AC018628.2 chr17 62035944 62040352 +2253545 EFCAB3 chr17 62343941 62416479 +2253655 METTL2A chr17 62423867 62450822 +2253712 TLK2 chr17 62458658 62615481 +2254067 AC008026.3 chr17 62549726 62552121 +2254071 AC080038.2 chr17 62626031 62626453 +2254074 AC080038.1 chr17 62626437 62627590 +2254077 MRC2 chr17 62627670 62693597 +2254220 AC005821.1 chr17 62699244 62754973 +2254246 MARCH10 chr17 62701314 62808344 +2254401 AC005821.2 chr17 62789109 62791765 +2254405 MARCH10-DT chr17 62808500 62836371 +2254409 AC005972.3 chr17 62910021 62968549 +2254426 TANC2 chr17 63009556 63427699 +2254620 AC006270.1 chr17 63117019 63130947 +2254626 AC015923.1 chr17 63193930 63339053 +2254635 AC005828.2 chr17 63305262 63313521 +2254639 AC005828.1 chr17 63381231 63414430 +2254648 AC005828.3 chr17 63391191 63431089 +2254652 AC005828.4 chr17 63430468 63432211 +2254656 CYB561 chr17 63432304 63446354 +2254909 AC005828.5 chr17 63454993 63455817 +2254913 ACE chr17 63477061 63498380 +2255310 KCNH6 chr17 63523334 63548977 +2255491 DCAF7 chr17 63550477 63594279 +2255563 TACO1 chr17 63600882 63608365 +2255584 MAP3K3 chr17 63622415 63696303 +2255854 STRADA chr17 63682336 63741986 +2256879 LIMD2 chr17 63695888 63701172 +2257011 CCDC47 chr17 63745255 63776351 +2257153 DDX42 chr17 63773603 63819317 +2257472 FTSJ3 chr17 63819433 63830012 +2257652 PSMC5 chr17 63827152 63832026 +2257966 SMARCD2 chr17 63832081 63843065 +2258166 CSH2 chr17 63872012 63873766 +2258240 GH2 chr17 63880215 63881944 +2258312 CSH1 chr17 63894909 63896661 +2258371 CSHL1 chr17 63909597 63918838 +2258474 GH1 chr17 63917200 63918839 +2258542 CD79B chr17 63928740 63932354 +2258601 SCN4A chr17 63938554 63972918 +2258662 AC127029.2 chr17 63972920 63989422 +2258667 PRR29-AS1 chr17 63995418 63999899 +2258681 PRR29 chr17 63998351 64004304 +2258798 ICAM2 chr17 64002594 64020634 +2258980 ERN1 chr17 64039142 64130819 +2259063 AC005803.1 chr17 64067619 64070270 +2259067 SNHG25 chr17 64145970 64146476 +2259074 TEX2 chr17 64147227 64263301 +2259252 PECAM1 chr17 64319415 64413776 +2259344 MILR1 chr17 64449037 64468643 +2259468 POLG2 chr17 64477785 64497054 +2259601 DDX5 chr17 64498254 64508199 +2259996 CEP95 chr17 64506865 64542461 +2260261 SMURF2 chr17 64542282 64662307 +2260433 LRRC37A3 chr17 64854312 64919480 +2260632 AC103810.2 chr17 64892729 64910180 +2260642 AC103810.5 chr17 64899766 64900716 +2260646 AC037487.1 chr17 64943262 64951054 +2260650 GNA13 chr17 65009289 65056740 +2260677 AC037487.2 chr17 65051909 65053308 +2260681 RGS9 chr17 65100812 65227703 +2260951 LINC02563 chr17 65457541 65458408 +2260956 AXIN2 chr17 65528563 65561648 +2261075 CEP112 chr17 65635537 66192133 +2261405 APOH chr17 66212033 66256525 +2261466 PRKCA chr17 66302613 66810743 +2261571 PRKCA-AS1 chr17 66398069 66416854 +2261583 AC006947.1 chr17 66676372 66677404 +2261588 CACNG5 chr17 66835117 66885486 +2261621 CACNG4 chr17 66964707 67033398 +2261635 AC005544.1 chr17 67019934 67021743 +2261639 AC005544.2 chr17 67032409 67033290 +2261643 CACNG1 chr17 67044554 67056797 +2261657 HELZ chr17 67070444 67245989 +2261959 AC007448.3 chr17 67224303 67225541 +2261963 AC007448.5 chr17 67244282 67273503 +2261970 AC007448.4 chr17 67244837 67245806 +2261974 PSMD12 chr17 67337916 67366605 +2262094 PITPNC1 chr17 67377281 67697261 +2262207 AC110921.1 chr17 67524481 67525422 +2262211 AC079331.3 chr17 67658015 67659465 +2262215 NOL11 chr17 67717931 67744531 +2262363 BPTF chr17 67825503 67984378 +2262855 AC134407.1 chr17 67950885 67951746 +2262859 C17orf58 chr17 67991101 67996431 +2262898 KPNA2 chr17 68035708 68046854 +2262999 AC145343.1 chr17 68096046 68101496 +2263010 AC005332.6 chr17 68126666 68129586 +2263013 AC005332.3 chr17 68131462 68131907 +2263016 AC005332.5 chr17 68133201 68135935 +2263019 AC005332.7 chr17 68188547 68189165 +2263022 AC005332.2 chr17 68189884 68192802 +2263025 AC005332.4 chr17 68205489 68207493 +2263028 AC005332.1 chr17 68246629 68247938 +2263031 AMZ2 chr17 68247930 68257164 +2263291 ARSG chr17 68259182 68422731 +2263410 SLC16A6 chr17 68267026 68291267 +2263490 AC007780.1 chr17 68413623 68524949 +2263511 WIPI1 chr17 68420948 68457513 +2263672 PRKAR1A chr17 68511780 68551319 +2264030 FAM20A chr17 68535113 68601367 +2264135 AC079210.1 chr17 68557516 68582577 +2264140 LINC01482 chr17 68591796 68763882 +2264160 AC011591.1 chr17 68793549 68797822 +2264164 ABCA8 chr17 68867289 68955392 +2264575 ABCA9-AS1 chr17 68944531 69042784 +2264614 ABCA9 chr17 68974488 69060949 +2264826 ABCA6 chr17 69078702 69141895 +2264966 ABCA10 chr17 69147214 69244846 +2265374 AC005495.2 chr17 69242230 69244097 +2265378 ABCA5 chr17 69244311 69327244 +2265819 MAP2K6 chr17 69414697 69553865 +2265984 AC002546.1 chr17 69477139 69501755 +2265989 LINC01483 chr17 69577251 69903000 +2266023 LINC01497 chr17 69961568 69994845 +2266053 AC005208.1 chr17 70017324 70128859 +2266068 LINC01028 chr17 70051277 70068095 +2266076 KCNJ16 chr17 70053429 70135608 +2266204 KCNJ2-AS1 chr17 70166961 70169402 +2266207 KCNJ2 chr17 70168673 70180048 +2266226 AC011990.1 chr17 70312831 70368916 +2266231 AC007423.1 chr17 70778604 70779230 +2266234 CASC17 chr17 71097774 71202203 +2266312 AC118653.1 chr17 71596338 71597279 +2266319 AC007432.1 chr17 71678899 71743468 +2266323 AC005144.1 chr17 71829870 71871750 +2266330 ROCR chr17 72021851 72034092 +2266339 LINC01152 chr17 72030291 72041310 +2266362 SOX9-AS1 chr17 72034107 72237203 +2266570 LINC02097 chr17 72072333 72103035 +2266589 SOX9 chr17 72121020 72126416 +2266601 LINC00511 chr17 72290091 72640472 +2267120 LINC02003 chr17 72342692 72355136 +2267138 AC007639.1 chr17 72425939 72428852 +2267142 AC080037.2 chr17 72642731 72644490 +2267146 SLC39A11 chr17 72645949 73092712 +2267345 AC011120.1 chr17 72839039 72839718 +2267349 SSTR2 chr17 73165010 73176633 +2267363 COG1 chr17 73192632 73208507 +2267517 AC097641.2 chr17 73202968 73203431 +2267520 FAM104A chr17 73207353 73236753 +2267593 C17orf80 chr17 73232233 73248947 +2267717 AC087301.1 chr17 73243093 73244706 +2267721 CPSF4L chr17 73248449 73262352 +2267758 CDC42EP4 chr17 73283624 73312005 +2267824 SDK2 chr17 73334384 73644445 +2268025 AC124804.1 chr17 73513469 73521407 +2268039 AC032019.1 chr17 73641026 73643106 +2268043 AC032019.2 chr17 73662568 73663848 +2268047 AC125421.1 chr17 73737854 73756932 +2268066 LINC00469 chr17 73749270 73828520 +2268083 LINC02092 chr17 73786675 73800966 +2268132 AC125421.2 chr17 73831572 73836019 +2268140 AC137735.1 chr17 73894749 73911878 +2268144 AC137735.3 chr17 73912190 73931436 +2268149 AC137735.2 chr17 73926421 73949906 +2268156 LINC02074 chr17 74043452 74154212 +2268188 RPL38 chr17 74203582 74210655 +2268276 AC100786.1 chr17 74209980 74213342 +2268292 TTYH2 chr17 74213571 74262020 +2268437 AC100786.2 chr17 74256896 74262020 +2268441 DNAI2 chr17 74274234 74314884 +2268604 AC103809.1 chr17 74307210 74309790 +2268608 KIF19 chr17 74326210 74355820 +2268714 BTBD17 chr17 74356416 74361868 +2268726 GPR142 chr17 74367407 74372622 +2268766 GPRC5C chr17 74424851 74451653 +2268892 CD300A chr17 74466399 74484794 +2269004 CD300LB chr17 74521174 74531475 +2269029 CD300C chr17 74541073 74546115 +2269043 CD300LD chr17 74579365 74592283 +2269057 C17orf77 chr17 74584679 74594209 +2269069 AC064805.1 chr17 74599840 74607229 +2269079 CD300E chr17 74609885 74623738 +2269100 AC064805.2 chr17 74670077 74677624 +2269112 RAB37 chr17 74670578 74747335 +2269373 CD300LF chr17 74694311 74712978 +2269535 AC016888.1 chr17 74747319 74748912 +2269539 SLC9A3R1 chr17 74748628 74769353 +2269595 NAT9 chr17 74770529 74776367 +2269902 TMEM104 chr17 74776483 74839779 +2270025 GRIN2C chr17 74842023 74861504 +2270102 FDXR chr17 74862497 74873031 +2270516 FADS6 chr17 74877302 74893781 +2270573 USH1G chr17 74916083 74923256 +2270596 OTOP2 chr17 74924275 74933912 +2270638 OTOP3 chr17 74935802 74949992 +2270676 HID1 chr17 74950742 74973166 +2270849 HID1-AS1 chr17 74970704 74975728 +2270854 CDR2L chr17 74987632 75005800 +2270870 MRPL58 chr17 75012670 75021261 +2270922 KCTD2 chr17 75032575 75065889 +2271013 ATP5PD chr17 75038863 75046985 +2271069 SLC16A5 chr17 75087727 75106162 +2271195 ARMC7 chr17 75109952 75130272 +2271243 NT5C chr17 75130225 75131757 +2271372 JPT1 chr17 75135248 75168281 +2271518 AC022211.3 chr17 75138416 75141350 +2271522 AC022211.1 chr17 75145261 75146546 +2271526 SUMO2 chr17 75165586 75182959 +2271564 NUP85 chr17 75205659 75235758 +2271952 GGA3 chr17 75236599 75262363 +2272428 MRPS7 chr17 75261674 75266376 +2272512 MIF4GD chr17 75266228 75271227 +2272720 AC022211.2 chr17 75271369 75273895 +2272726 SLC25A19 chr17 75272981 75289510 +2272942 GRB2 chr17 75318076 75405709 +2273085 AC011933.4 chr17 75344405 75373662 +2273089 AC011933.2 chr17 75370947 75373736 +2273092 AC011933.3 chr17 75394123 75394963 +2273096 TMEM94 chr17 75441159 75500452 +2273589 CASKIN2 chr17 75500261 75515537 +2273723 TSEN54 chr17 75516060 75524735 +2273850 LLGL2 chr17 75525080 75575208 +2274281 MYO15B chr17 75588058 75626849 +2275325 RECQL5 chr17 75626845 75667189 +2275602 SMIM5 chr17 75633434 75641404 +2275626 SMIM6 chr17 75646243 75647975 +2275647 SAP30BP chr17 75667251 75708062 +2276000 AC087749.2 chr17 75679474 75679967 +2276004 AC087749.1 chr17 75683543 75684799 +2276011 ITGB4 chr17 75721328 75757818 +2276446 GALK1 chr17 75751594 75765236 +2276545 H3F3B chr17 75776434 75785893 +2276657 UNK chr17 75784806 75825799 +2276762 AC087289.1 chr17 75818815 75820055 +2276766 UNC13D chr17 75827225 75844717 +2277092 WBP2 chr17 75845699 75856507 +2277350 TRIM47 chr17 75874164 75878581 +2277406 AC087289.5 chr17 75876372 75879546 +2277409 TRIM65 chr17 75880335 75896951 +2277480 AC087289.2 chr17 75897060 75900148 +2277485 MRPL38 chr17 75898643 75905413 +2277583 FBF1 chr17 75909574 75941140 +2277912 ACOX1 chr17 75941507 75979177 +2278112 AC087289.4 chr17 75943832 75945142 +2278116 TEN1 chr17 75979240 76000586 +2278168 CDK3 chr17 76000906 76005999 +2278237 EVPL chr17 76004502 76027452 +2278368 SRP68 chr17 76038775 76072517 +2278551 ZACN chr17 76071961 76083666 +2278627 GALR2 chr17 76074781 76077537 +2278637 EXOC7 chr17 76081016 76121576 +2279129 FOXJ1 chr17 76136333 76141245 +2279141 RNF157-AS1 chr17 76138432 76154650 +2279170 RNF157 chr17 76142465 76240493 +2279350 UBALD2 chr17 76265348 76271298 +2279380 QRICH2 chr17 76274049 76307998 +2279549 PRPSAP1 chr17 76309478 76384521 +2279685 SPHK1 chr17 76376584 76387860 +2279821 UBE2O chr17 76389456 76453152 +2279924 AANAT chr17 76453351 76470117 +2279979 RHBDF2 chr17 76470891 76501790 +2280220 CYGB chr17 76527356 76551175 +2280274 PRCD chr17 76527586 76553578 +2280361 AC015802.4 chr17 76545668 76557683 +2280376 AC015802.3 chr17 76549951 76550826 +2280380 AC015802.5 chr17 76551352 76551750 +2280383 SNHG16 chr17 76557764 76565348 +2280445 AC015802.6 chr17 76563710 76570544 +2280455 ST6GALNAC2 chr17 76565377 76586956 +2280551 AC015802.1 chr17 76569792 76571240 +2280554 AC015802.7 chr17 76617959 76619128 +2280558 ST6GALNAC1 chr17 76624761 76643786 +2280688 AC005837.1 chr17 76671942 76673658 +2280691 MXRA7 chr17 76672551 76711016 +2280785 AC005837.4 chr17 76709760 76710045 +2280788 JMJD6 chr17 76712832 76726799 +2280906 METTL23 chr17 76726830 76733936 +2281095 SRSF2 chr17 76734115 76737374 +2281183 MFSD11 chr17 76735865 76781449 +2281564 LINC02080 chr17 76799044 76807102 +2281569 AC016168.4 chr17 76831684 76841099 +2281574 LINC00868 chr17 76849840 76861836 +2281592 MGAT5B chr17 76868456 76950393 +2281778 AC016168.2 chr17 76950317 76969156 +2281790 AC016168.1 chr17 76957023 76958222 +2281794 SNHG20 chr17 77086716 77099902 +2281870 SEC14L1 chr17 77088749 77217101 +2282298 SEPTIN9-DT chr17 77257737 77281897 +2282309 AC068594.1 chr17 77264180 77264776 +2282312 SEPTIN9 chr17 77280569 77500596 +2282997 AC111182.1 chr17 77373818 77377236 +2283000 AC111182.2 chr17 77386901 77388546 +2283004 AC111170.2 chr17 77469068 77471045 +2283008 AC111170.1 chr17 77469162 77472770 +2283013 AC021683.3 chr17 77516887 77536601 +2283113 AC021683.2 chr17 77546940 77563243 +2283124 AC021683.6 chr17 77548129 77550499 +2283128 AC021683.1 chr17 77563368 77568695 +2283132 AC021683.5 chr17 77590532 77680687 +2283143 LINC01987 chr17 77722872 77728559 +2283147 LINC01973 chr17 77877330 77884119 +2283155 TNRC6C chr17 77959240 78108835 +2283435 TNRC6C-AS1 chr17 78107398 78111799 +2283441 TMC6 chr17 78110458 78132407 +2283798 TMC8 chr17 78130770 78142968 +2283909 C17orf99 chr17 78146353 78166177 +2283952 SYNGR2 chr17 78168558 78173527 +2284041 TK1 chr17 78174091 78187233 +2284137 AFMID chr17 78187317 78207701 +2284332 BIRC5 chr17 78214186 78225636 +2284453 TMEM235 chr17 78231310 78240987 +2284541 AC087645.4 chr17 78248193 78251440 +2284545 LINC01993 chr17 78261349 78278492 +2284554 AC087645.2 chr17 78315729 78347798 +2284562 SOCS3 chr17 78356778 78360077 +2284579 AC061992.2 chr17 78360453 78373911 +2284589 PGS1 chr17 78378649 78425114 +2284787 DNAH17 chr17 78423697 78577394 +2285269 DNAH17-AS1 chr17 78484882 78503056 +2285289 SCAT1 chr17 78605233 78632155 +2285488 CYTH1 chr17 78674048 78782297 +2285776 USP36 chr17 78787381 78841441 +2286182 AC022966.2 chr17 78845345 78846686 +2286186 TIMP2 chr17 78852977 78925387 +2286254 AC022966.1 chr17 78855478 78855844 +2286257 CEP295NL chr17 78870910 78903217 +2286298 AC100788.1 chr17 78903263 78905024 +2286302 LGALS3BP chr17 78971238 78979947 +2286539 CANT1 chr17 78991716 79009867 +2286705 C1QTNF1-AS1 chr17 79018131 79027673 +2286714 C1QTNF1 chr17 79022814 79049788 +2286851 ENGASE chr17 79074939 79088599 +2286965 RBFOX3 chr17 79089345 79516148 +2287176 AC021534.1 chr17 79132722 79136402 +2287181 AC233701.1 chr17 79598032 79603921 +2287187 LINC02078 chr17 79707266 79712317 +2287191 ENPP7 chr17 79730943 79742219 +2287218 CBX2 chr17 79778148 79787983 +2287251 CBX8 chr17 79792132 79801683 +2287298 AC100791.2 chr17 79800598 79802529 +2287302 LINC01977 chr17 79819083 79827704 +2287313 CBX4 chr17 79833156 79839440 +2287357 AC100791.1 chr17 79848058 79850110 +2287361 LINC01979 chr17 79915252 79926725 +2287369 LINC01978 chr17 79919357 79925999 +2287379 TBC1D16 chr17 79932343 80035872 +2287541 AC100791.3 chr17 79952663 79952992 +2287544 AC116025.2 chr17 79991944 79992841 +2287548 AC116025.1 chr17 80023894 80026107 +2287555 CCDC40 chr17 80036632 80100613 +2287783 GAA chr17 80101556 80119881 +2287930 EIF4A3 chr17 80134369 80147151 +2288039 AC087741.2 chr17 80149627 80149798 +2288042 CARD14 chr17 80169992 80209331 +2288605 AC087741.1 chr17 80200673 80205949 +2288629 SGSH chr17 80206716 80220923 +2288802 SLC26A11 chr17 80219699 80253500 +2289072 RNF213 chr17 80260866 80398786 +2289529 AC124319.1 chr17 80315651 80316633 +2289533 AC124319.2 chr17 80333841 80334366 +2289536 RNF213-AS1 chr17 80351828 80415168 +2289551 ENDOV chr17 80415165 80438086 +2289955 AC120024.1 chr17 80453735 80454729 +2289958 NPTX1 chr17 80466834 80477843 +2289987 RPTOR chr17 80544819 80966371 +2290263 AC016245.1 chr17 80801640 80805632 +2290269 AC016245.2 chr17 80824170 80826900 +2290273 AC127496.3 chr17 80940418 80942033 +2290278 AC127496.4 chr17 80960766 80961713 +2290282 AC127496.1 chr17 80966239 80971213 +2290289 CHMP6 chr17 80991598 81009517 +2290362 AC127496.6 chr17 80999509 81000130 +2290369 AC127496.5 chr17 81017969 81028079 +2290388 AC127496.2 chr17 81023545 81025503 +2290392 BAIAP2-DT chr17 81029130 81034881 +2290399 BAIAP2 chr17 81035122 81117432 +2290910 AATK chr17 81110487 81166221 +2291099 AC115099.1 chr17 81135771 81136256 +2291103 PVALEF chr17 81165507 81183166 +2291135 CEP131 chr17 81189593 81222999 +2291425 AC027601.3 chr17 81197393 81200288 +2291429 TEPSIN chr17 81228277 81239091 +2291579 AC027601.2 chr17 81228707 81233983 +2291590 NDUFAF8 chr17 81239305 81241310 +2291623 SLC38A10 chr17 81244811 81295547 +2291767 AC027601.4 chr17 81251194 81251803 +2291770 LINC00482 chr17 81303771 81309248 +2291780 AC027601.1 chr17 81311270 81330674 +2291798 AC027601.6 chr17 81339183 81345966 +2291801 AC110285.3 chr17 81362272 81374214 +2291806 AC110285.1 chr17 81375144 81385464 +2291874 AC110285.5 chr17 81387415 81387766 +2291877 AC110285.2 chr17 81388126 81390319 +2291887 BAHCC1 chr17 81395475 81466332 +2292029 AC110285.4 chr17 81461013 81461937 +2292033 LINC01971 chr17 81480523 81481570 +2292036 ACTG1 chr17 81509971 81523847 +2292236 AC139149.1 chr17 81514047 81527776 +2292243 FSCN2 chr17 81528396 81537130 +2292276 FAAP100 chr17 81539885 81553961 +2292374 NPLOC4 chr17 81556887 81648465 +2292635 TSPAN10 chr17 81637171 81648749 +2292678 PDE6G chr17 81650459 81663112 +2292726 OXLD1 chr17 81665036 81666635 +2292775 CCDC137 chr17 81666737 81673904 +2292854 ARL16 chr17 81681174 81683924 +2293000 HGS chr17 81683326 81703138 +2293186 AC139530.3 chr17 81697025 81697714 +2293189 AC139530.1 chr17 81701324 81703300 +2293192 MRPL12 chr17 81703367 81707517 +2293208 SLC25A10 chr17 81712236 81721016 +2293358 GCGR chr17 81804132 81814008 +2293443 MCRIP1 chr17 81822361 81833302 +2293610 PPP1R27 chr17 81833492 81835050 +2293634 P4HB chr17 81843161 81860624 +2293884 AC145207.3 chr17 81843165 81843958 +2293888 AC145207.2 chr17 81867721 81868552 +2293895 ARHGDIA chr17 81867721 81871378 +2294083 AC145207.5 chr17 81878425 81881106 +2294086 AC145207.6 chr17 81878667 81879557 +2294090 ALYREF chr17 81887835 81891586 +2294121 ANAPC11 chr17 81890790 81900991 +2294388 NPB chr17 81900745 81902905 +2294405 PCYT2 chr17 81900965 81911464 +2294746 SIRT7 chr17 81911939 81921323 +2294907 MAFG chr17 81918270 81927735 +2294941 AC145207.8 chr17 81922899 81924511 +2294946 MAFG-DT chr17 81927829 81930753 +2294950 PYCR1 chr17 81932384 81942412 +2295224 AC145207.4 chr17 81932398 81933058 +2295228 MYADML2 chr17 81939645 81947233 +2295240 AC145207.1 chr17 81941869 81947601 +2295244 NOTUM chr17 81952507 81961840 +2295314 AC145207.7 chr17 81965632 81966589 +2295317 ASPSCR1 chr17 81976807 82017406 +2295665 CENPX chr17 82018702 82024107 +2295772 LRRC45 chr17 82023305 82031151 +2295866 RAC3 chr17 82031678 82034204 +2295914 DCXR chr17 82035136 82037709 +2296114 DCXR-DT chr17 82037905 82039380 +2296121 RFNG chr17 82047902 82051831 +2296218 GPS1 chr17 82050691 82057470 +2296679 DUS1L chr17 82057506 82065887 +2296904 FASN chr17 82078338 82098294 +2297152 CCDC57 chr17 82101460 82212830 +2297425 AC129510.1 chr17 82153430 82154815 +2297429 AC129510.2 chr17 82160056 82160452 +2297433 AC132872.2 chr17 82214227 82217352 +2297437 SLC16A3 chr17 82228397 82261129 +2297650 CSNK1D chr17 82239023 82273731 +2297907 AC132872.3 chr17 82244770 82245591 +2297911 AC132872.5 chr17 82273748 82279645 +2297936 LINC01970 chr17 82290046 82292814 +2297940 AC132872.1 chr17 82293716 82294910 +2297943 CD7 chr17 82314868 82317608 +2298013 SECTM1 chr17 82321024 82334074 +2298114 TEX19 chr17 82359247 82363775 +2298124 UTS2R chr17 82374230 82375586 +2298132 AC132938.1 chr17 82381110 82382690 +2298136 OGFOD3 chr17 82389210 82418637 +2298288 AC132938.2 chr17 82400703 82401382 +2298291 HEXD chr17 82418318 82442645 +2298599 HEXD-IT1 chr17 82425498 82427310 +2298602 CYBC1 chr17 82442586 82450829 +2299082 AC132938.6 chr17 82450911 82452213 +2299085 AC132938.3 chr17 82454140 82458521 +2299097 NARF chr17 82458180 82490537 +2299498 NARF-AS1 chr17 82476597 82477924 +2299502 NARF-IT1 chr17 82482098 82483388 +2299506 FOXK2 chr17 82519713 82644662 +2299617 AC124283.3 chr17 82578023 82578616 +2299620 AC124283.2 chr17 82587313 82588411 +2299624 AC124283.1 chr17 82602989 82604178 +2299627 WDR45B chr17 82614562 82648553 +2299763 RAB40B chr17 82654973 82698698 +2299852 AC024361.2 chr17 82713908 82716255 +2299856 FN3KRP chr17 82716706 82730328 +2299970 AC024361.3 chr17 82729164 82734143 +2299974 FN3K chr17 82735615 82751196 +2300010 AC024361.1 chr17 82745068 82745709 +2300013 TBCD chr17 82752065 82945914 +2300538 AC068014.1 chr17 82795486 82796095 +2300542 ZNF750 chr17 82829434 82840022 +2300565 AC087222.1 chr17 82918282 82918785 +2300568 B3GNTL1 chr17 82942155 83051810 +2300708 AC130371.1 chr17 82978525 82981738 +2300722 METRNL chr17 83079609 83095122 +2300771 AC130371.2 chr17 83098377 83098987 +2300774 AC144831.1 chr17 83104255 83106910 +2300777 AC139099.2 chr17 83135734 83221442 +2300803 AC139099.1 chr17 83220527 83227721 +2300815 LINC02564 chr18 11103 16352 +2300823 AP005530.1 chr18 14195 16898 +2300830 TUBB8P12 chr18 47390 49557 +2300846 AP001005.3 chr18 49815 73545 +2300854 USP14 chr18 158383 214629 +2301054 THOC1 chr18 214520 268050 +2301435 AP000845.1 chr18 268148 270278 +2301438 AP000915.1 chr18 316737 319165 +2301442 COLEC12 chr18 316737 500722 +2301481 AP000915.2 chr18 423744 424416 +2301485 LINC01925 chr18 508568 515294 +2301490 CETN1 chr18 580380 582114 +2301498 CLUL1 chr18 596988 650334 +2301684 TYMSOS chr18 623743 658340 +2301698 AP001178.3 chr18 650229 652843 +2301702 AP001178.1 chr18 653985 657259 +2301706 TYMS chr18 657653 673578 +2301770 ENOSF1 chr18 670318 712662 +2302118 AP001178.2 chr18 706523 707648 +2302122 YES1 chr18 721588 812546 +2302219 AP001020.3 chr18 735746 737459 +2302222 AP001020.1 chr18 738058 739444 +2302226 AP001020.2 chr18 738058 739662 +2302229 AP000894.4 chr18 813274 813756 +2302232 AP000894.3 chr18 894435 907680 +2302236 AP000894.2 chr18 902766 906667 +2302252 ADCYAP1 chr18 904871 912172 +2302288 LINC01904 chr18 926083 927993 +2302292 AP005328.1 chr18 962592 976883 +2302297 AP000829.1 chr18 976589 1310018 +2302339 LINC00470 chr18 1254383 1408344 +2302667 AP005262.2 chr18 1509022 2049510 +2302807 AC019183.1 chr18 1655177 1779955 +2302812 AP005057.1 chr18 1780329 1782064 +2302817 AP005230.1 chr18 1883524 2489426 +2302861 AP005136.4 chr18 2506628 2511580 +2302865 METTL4 chr18 2537525 2571509 +2302954 AP005136.3 chr18 2561172 2562220 +2302957 NDC80 chr18 2571557 2616635 +2303031 SMCHD1 chr18 2655738 2805017 +2303390 AP001011.1 chr18 2688564 2833065 +2303399 EMILIN2 chr18 2847006 2916003 +2303432 LPIN2 chr18 2916994 3013315 +2303504 AP000919.4 chr18 2920966 2921685 +2303507 AP000919.2 chr18 2948238 2960756 +2303519 AP000919.3 chr18 2967018 2985410 +2303525 MYOM1 chr18 3066807 3220108 +2303795 AP005329.2 chr18 3190397 3247277 +2303802 AP005329.3 chr18 3246401 3247086 +2303805 MYL12A chr18 3247481 3256236 +2303907 AP005329.1 chr18 3255436 3261850 +2303916 MYL12B chr18 3261479 3278431 +2303982 AP001025.1 chr18 3284120 3330984 +2303987 LINC01895 chr18 3347696 3383532 +2304071 IGLJCOR18 chr18 3394889 3395312 +2304074 TGIF1 chr18 3411608 3459978 +2304304 GAPLINC chr18 3466250 3478978 +2304323 DLGAP1 chr18 3496032 4455307 +2304675 DLGAP1-AS1 chr18 3593732 3598363 +2304703 DLGAP1-AS2 chr18 3603000 3608336 +2304709 AP002478.1 chr18 3653030 3656282 +2304722 AP002478.2 chr18 3770017 3771430 +2304726 DLGAP1-AS3 chr18 3878058 3897069 +2304747 DLGAP1-AS4 chr18 3962353 4024150 +2304793 DLGAP1-AS5 chr18 4264602 4295405 +2304808 AP005203.1 chr18 4775054 5004537 +2304821 LINC01892 chr18 5081171 5098780 +2304848 AKAIN1 chr18 5142911 5197503 +2304867 AP005380.1 chr18 5159332 5171026 +2304872 AP001496.4 chr18 5197165 5215497 +2304876 AP001496.2 chr18 5232876 5238526 +2304884 LINC00526 chr18 5236724 5238598 +2304887 LINC00667 chr18 5237826 5290608 +2305052 ZBTB14 chr18 5289019 5297053 +2305152 AP001496.1 chr18 5310396 5317664 +2305156 AP005671.1 chr18 5381641 5385330 +2305160 EPB41L3 chr18 5392381 5630700 +2305759 AP005059.2 chr18 5463627 5480975 +2305765 AP005059.1 chr18 5567130 5570942 +2305770 MIR3976HG chr18 5721812 5876328 +2306005 TMEM200C chr18 5882072 5895955 +2306024 AP001021.1 chr18 5887487 5989369 +2306044 AP001021.3 chr18 5895745 6108382 +2306059 L3MBTL4 chr18 5954706 6415237 +2306248 AP001021.2 chr18 5956101 5960785 +2306252 L3MBTL4-AS1 chr18 6256747 6260934 +2306257 AP005202.2 chr18 6493420 6495668 +2306261 LINC01387 chr18 6511416 6590653 +2306269 AP005202.1 chr18 6557822 6558654 +2306273 AP005205.1 chr18 6641971 6642478 +2306276 AP005205.2 chr18 6728821 6729862 +2306280 ARHGAP28 chr18 6729718 6915716 +2306605 AP005210.2 chr18 6784614 6796503 +2306610 AP005210.1 chr18 6873399 6875024 +2306614 LINC00668 chr18 6919496 6929966 +2306656 LAMA1 chr18 6941742 7117797 +2306912 AP002409.1 chr18 6954677 6957419 +2306916 AP005062.1 chr18 7076817 7080123 +2306921 LRRC30 chr18 7231125 7232047 +2306929 AP001095.1 chr18 7455844 7461135 +2306933 PTPRM chr18 7566782 8406861 +2307306 AP000897.2 chr18 7741310 7754831 +2307315 AP000897.1 chr18 7814118 7815730 +2307318 AP005900.1 chr18 8012257 8016565 +2307322 AC006566.2 chr18 8133203 8136032 +2307326 AC006566.1 chr18 8154558 8155070 +2307329 AP001094.3 chr18 8360820 8367034 +2307335 AP001094.2 chr18 8402847 8405161 +2307338 AP001094.1 chr18 8406761 8406953 +2307341 RAB12 chr18 8609437 8639382 +2307379 AP001793.1 chr18 8635179 8636347 +2307383 GACAT2 chr18 8695856 8707621 +2307387 MTCL1 chr18 8705661 8832778 +2307615 AP000864.1 chr18 8801656 8802305 +2307618 AP001531.1 chr18 8913999 8919414 +2307622 AP005899.2 chr18 8971624 8974580 +2307626 NDUFV2 chr18 9102630 9134345 +2307711 AP005899.1 chr18 9112404 9115877 +2307715 NDUFV2-AS1 chr18 9121265 9136645 +2307727 ANKRD12 chr18 9136228 9285985 +2307861 AP001033.2 chr18 9259388 9260390 +2307864 AP001033.1 chr18 9310522 9334445 +2307869 TWSG1 chr18 9334767 9402420 +2307917 AP001033.3 chr18 9335269 9336242 +2307920 AP005432.2 chr18 9473421 9474006 +2307923 RALBP1 chr18 9475009 9538114 +2308014 AP005432.1 chr18 9506242 9509726 +2308017 PPP4R1 chr18 9546791 9615240 +2308362 AP001381.1 chr18 9587386 9590182 +2308366 PPP4R1-AS1 chr18 9615264 9619363 +2308371 LINC02856 chr18 9646110 9648502 +2308375 RAB31 chr18 9708275 9862551 +2308474 AC006238.2 chr18 9840340 9841559 +2308478 TXNDC2 chr18 9885726 9889275 +2308533 AC006238.1 chr18 9912316 9912849 +2308536 VAPA chr18 9914002 9960021 +2308612 AP005271.1 chr18 10124588 10144406 +2308620 AP005209.2 chr18 10297299 10323565 +2308625 AP005209.1 chr18 10321380 10372387 +2308649 AP006219.1 chr18 10375103 10378114 +2308653 AP006219.2 chr18 10380423 10390344 +2308658 LINC01254 chr18 10405133 10414515 +2308665 AP006219.3 chr18 10406558 10422360 +2308669 APCDD1 chr18 10454635 10489949 +2308739 NAPG chr18 10525905 10552764 +2308856 AP001099.1 chr18 10594590 10604798 +2308863 LINC01887 chr18 10612304 10626353 +2308871 AP001180.2 chr18 10627646 10628846 +2308875 AP001180.1 chr18 10661933 10666887 +2308880 PIEZO2 chr18 10666483 11148762 +2309512 AP001180.4 chr18 10704297 10709599 +2309517 AP005120.1 chr18 10893617 10908783 +2309524 AP005229.1 chr18 11366913 11378409 +2309529 AP005229.2 chr18 11390033 11390729 +2309532 AP001109.1 chr18 11447756 11489369 +2309536 LINC01928 chr18 11454478 11465996 +2309542 LINC01255 chr18 11486205 11523087 +2309727 SLC35G4 chr18 11609596 11610612 +2309734 AP001120.2 chr18 11620717 11621158 +2309738 AP001120.1 chr18 11666456 11670165 +2309741 GNAL chr18 11689264 11885685 +2309935 AP001120.5 chr18 11758977 11786181 +2309940 AP005137.1 chr18 11810406 11811484 +2309944 CHMP1B chr18 11851413 11854444 +2309955 CHMP1B-AS1 chr18 11851414 11852751 +2309959 AP005137.2 chr18 11857155 11857554 +2309962 MPPE1 chr18 11882622 11908366 +2310353 AP001269.4 chr18 11908712 11909223 +2310356 AP001269.2 chr18 11910634 11914344 +2310360 IMPA2 chr18 11981025 12030877 +2310527 AP001269.1 chr18 11993988 11994938 +2310531 AP001542.3 chr18 12031178 12032181 +2310535 AP002414.5 chr18 12081540 12085267 +2310540 ANKRD62 chr18 12093843 12129764 +2310584 AP005264.4 chr18 12200779 12201979 +2310588 AP005264.3 chr18 12230411 12231573 +2310592 CIDEA chr18 12254361 12277595 +2310636 AP005264.1 chr18 12288308 12291488 +2310640 TUBB6 chr18 12307669 12344320 +2310797 AFG3L2 chr18 12328944 12377314 +2310854 PRELID3A chr18 12407896 12432238 +2311002 AP001029.1 chr18 12432897 12437635 +2311006 AP001029.2 chr18 12438890 12448205 +2311016 SPIRE1 chr18 12446512 12658134 +2311289 PSMG2 chr18 12658043 12725740 +2311392 CEP76 chr18 12661833 12702777 +2311568 AP005482.3 chr18 12670426 12671145 +2311571 AP005482.2 chr18 12738965 12750068 +2311575 AP005482.1 chr18 12739490 12776140 +2311591 PTPN2 chr18 12785478 12929643 +2311910 SEH1L chr18 12947133 12987536 +2312028 AP002449.1 chr18 12984694 12991173 +2312033 CEP192 chr18 12991362 13125052 +2312663 AP001198.2 chr18 13183402 13185617 +2312667 AP001198.1 chr18 13203774 13216367 +2312674 LDLRAD4 chr18 13217498 13652755 +2312824 AP002505.1 chr18 13234945 13236470 +2312828 AP002505.3 chr18 13276427 13277155 +2312832 AP002439.1 chr18 13362203 13366243 +2312836 LDLRAD4-AS1 chr18 13419421 13427480 +2312842 AP005131.5 chr18 13461020 13470823 +2312848 AP005131.4 chr18 13471012 13472709 +2312854 AP005131.6 chr18 13486462 13490676 +2312857 AP005131.2 chr18 13500641 13501289 +2312861 AP005131.1 chr18 13514520 13522888 +2312865 AP005131.7 chr18 13526078 13526688 +2312868 AP005131.3 chr18 13561399 13565035 +2312873 AP001010.1 chr18 13644815 13645685 +2312877 FAM210A chr18 13663347 13726663 +2312957 RNMT chr18 13726660 13764558 +2313148 MC5R chr18 13824149 13827323 +2313165 MC2R chr18 13882044 13915707 +2313182 ZNF519 chr18 14057457 14132490 +2313267 AC006557.1 chr18 14089935 14091019 +2313270 AC006557.3 chr18 14104542 14105226 +2313274 AP006261.1 chr18 14404551 14430923 +2313279 POTEC chr18 14507339 14543585 +2313360 ANKRD30B chr18 14728272 14854038 +2313597 AP006565.1 chr18 14816151 14825249 +2313601 LINC01906 chr18 14877611 14884052 +2313607 AP005121.1 chr18 14903580 14915628 +2313618 LINC01443 chr18 14946267 14974215 +2313630 LINC01444 chr18 14969001 14970468 +2313637 AP005121.2 chr18 14978739 14979839 +2313640 AP005242.3 chr18 15056845 15066598 +2313644 AP005242.1 chr18 15075445 15122767 +2313649 AP005242.5 chr18 15139255 15150980 +2313655 AP005901.2 chr18 15159724 15164467 +2313659 AP005901.6 chr18 15165338 15172007 +2313666 AP005901.5 chr18 15184016 15189760 +2313670 ROCK1 chr18 20946906 21111813 +2313835 AC022809.1 chr18 21240675 21241371 +2313839 GREB1L chr18 21242242 21525417 +2314137 AC015878.2 chr18 21316878 21317795 +2314141 AC015878.1 chr18 21380286 21451017 +2314147 ESCO1 chr18 21529284 21600884 +2314229 SNRPD1 chr18 21612314 21633524 +2314270 ABHD3 chr18 21650901 21704780 +2314388 AC106037.2 chr18 21661787 21662395 +2314392 AC106037.3 chr18 21673628 21682561 +2314396 MIB1 chr18 21704957 21870957 +2314477 MIR133A1HG chr18 21825487 21831539 +2314492 AC103987.2 chr18 21871446 21893996 +2314496 LINC01900 chr18 21981121 22051159 +2314508 AC091043.1 chr18 22088060 22098780 +2314512 GATA6-AS1 chr18 22164886 22169878 +2314545 GATA6 chr18 22169392 22202528 +2314582 AC091588.1 chr18 22175465 22176662 +2314586 AC091588.3 chr18 22200619 22205229 +2314590 AC091588.2 chr18 22213778 22228029 +2314594 AC027449.1 chr18 22347846 22348252 +2314597 CTAGE1 chr18 22413599 22417915 +2314612 AC090912.1 chr18 22699481 22933764 +2314618 AC090912.2 chr18 22723491 22907721 +2314635 RBBP8 chr18 22798261 23026488 +2314973 AC090912.3 chr18 22882825 22883357 +2314976 CABLES1 chr18 23134564 23260467 +2315108 TMEM241 chr18 23197144 23437961 +2315478 AC011731.1 chr18 23257164 23260354 +2315482 RIOK3 chr18 23453287 23486603 +2315634 RMC1 chr18 23503470 23531822 +2315922 NPC1 chr18 23506184 23586506 +2316094 ANKRD29 chr18 23598926 23662911 +2316195 LAMA3 chr18 23689443 23956222 +2316921 AC010754.1 chr18 23957754 23982556 +2316929 TTC39C chr18 23992773 24135610 +2317066 TTC39C-AS1 chr18 23994213 24015339 +2317074 AC090772.2 chr18 24076794 24099320 +2317078 AC090772.1 chr18 24113637 24121003 +2317082 CABYR chr18 24138956 24161603 +2317329 AC090772.3 chr18 24159509 24162211 +2317334 OSBPL1A chr18 24162045 24397880 +2317651 AC023983.1 chr18 24364787 24367984 +2317655 AC023983.2 chr18 24402153 24402714 +2317658 IMPACT chr18 24426634 24453531 +2317780 AC007922.2 chr18 24435364 24439638 +2317784 HRH4 chr18 24460637 24479961 +2317804 AC007922.1 chr18 24489375 24491080 +2317808 AC007922.4 chr18 24500399 24508133 +2317817 AC007922.3 chr18 24516699 24544154 +2317829 LINC01915 chr18 24534551 24708542 +2317911 AC018697.1 chr18 24725762 24986980 +2317975 LINC01894 chr18 24932771 24987919 +2317994 AC104961.1 chr18 25055600 25056760 +2317998 ZNF521 chr18 25061924 25352190 +2318145 AC105114.2 chr18 25196663 25218241 +2318152 AC110603.1 chr18 25302126 25302960 +2318156 SS18 chr18 26016253 26091217 +2318545 PSMA8 chr18 26133852 26193355 +2318642 TAF4B chr18 26225936 26391685 +2318750 AC121320.1 chr18 26266009 26267409 +2318754 LINC01543 chr18 26421139 26438041 +2318768 KCTD1 chr18 26454910 26657401 +2318891 AC007996.1 chr18 26542971 26545791 +2318894 AC090206.1 chr18 26565723 26575626 +2318898 AQP4-AS1 chr18 26655737 27190698 +2319002 AC012588.1 chr18 26685954 26689668 +2319016 PCAT18 chr18 26687621 26703638 +2319020 AC018371.1 chr18 26822341 26825171 +2319029 AQP4 chr18 26852043 26865771 +2319134 CHST9 chr18 26906481 27185308 +2319182 LINC01908 chr18 27225742 27247188 +2319189 AC090403.1 chr18 27335968 27595164 +2319215 AC021382.1 chr18 27343252 27346110 +2319220 AC068408.1 chr18 27375310 27401910 +2319238 AC068408.2 chr18 27454466 27469673 +2319243 AC090936.1 chr18 27785821 27795637 +2319249 CDH2 chr18 27950966 28177130 +2319357 AC110015.1 chr18 27954519 27963687 +2319362 AC006249.1 chr18 28146233 28146703 +2319365 AC090365.1 chr18 28638714 28789580 +2319373 AC074237.1 chr18 29278509 29361963 +2319378 AC117569.1 chr18 29518259 29548241 +2319392 AC117569.2 chr18 29629842 29650440 +2319397 AC115100.1 chr18 30290161 30414073 +2319403 AC090506.1 chr18 30713275 30714286 +2319407 AC016382.1 chr18 30954820 30980917 +2319412 DSC3 chr18 30989365 31042815 +2319504 DSC2 chr18 31058840 31102522 +2319620 DSCAS chr18 31101583 31162789 +2319630 DSC1 chr18 31129236 31162856 +2319707 AC012417.1 chr18 31131456 31132494 +2319710 DSG1 chr18 31318160 31359246 +2319751 DSG1-AS1 chr18 31343368 31426988 +2319771 DSG4 chr18 31376777 31414912 +2319844 DSG3 chr18 31447741 31478702 +2319882 AC021549.1 chr18 31496645 31497195 +2319886 DSG2 chr18 31498177 31549008 +2319939 DSG2-AS1 chr18 31542146 31556948 +2319961 TTR chr18 31557010 31599021 +2320035 B4GALT6 chr18 31622247 31685836 +2320116 AC017100.1 chr18 31685655 31686823 +2320119 SLC25A52 chr18 31759562 31760880 +2320134 TRAPPC8 chr18 31829180 31953136 +2320404 AC022960.1 chr18 31844388 31845178 +2320408 AC022960.2 chr18 31895745 31896410 +2320411 AC009831.1 chr18 31942575 31944156 +2320414 RNF125 chr18 32018825 32073219 +2320456 AC009831.3 chr18 32031035 32031359 +2320459 AC011825.4 chr18 32091295 32092119 +2320463 RNF138 chr18 32091874 32131561 +2320552 AC011825.2 chr18 32122400 32124478 +2320556 GAREM1 chr18 32124877 32470882 +2320604 MEP1B chr18 32185069 32220404 +2320699 AC015563.1 chr18 32245946 32249032 +2320703 AC015563.2 chr18 32287437 32290340 +2320707 AC025887.2 chr18 32470288 32745567 +2320724 AC009835.1 chr18 32554033 32566634 +2320728 AC025887.1 chr18 32581528 32582828 +2320732 KLHL14 chr18 32672673 32773023 +2320776 AC012123.1 chr18 32769795 32774413 +2320782 AC090371.2 chr18 32833454 32938316 +2320802 CCDC178 chr18 32937402 33441101 +2321198 AC090371.1 chr18 32954075 32957998 +2321204 AC091198.1 chr18 33552123 33578187 +2321208 ASXL3 chr18 33578219 33751195 +2321430 NOL4 chr18 33851100 34224952 +2321641 AC104985.1 chr18 34222965 34224761 +2321645 AC104985.2 chr18 34225930 34226429 +2321648 DTNA chr18 34493290 34891844 +2322509 AC022601.1 chr18 34737795 34767663 +2322516 AC068506.1 chr18 34892013 34903504 +2322526 MAPRE2 chr18 34976928 35143470 +2322705 AC015967.1 chr18 35144942 35145417 +2322708 ZNF397 chr18 35241030 35267133 +2322815 ZSCAN30 chr18 35251058 35290245 +2322935 AC011815.2 chr18 35268218 35270238 +2322938 AC011815.1 chr18 35280867 35290201 +2322942 AC116447.1 chr18 35317396 35317848 +2322945 ZNF24 chr18 35332227 35345482 +2323006 ZNF396 chr18 35366694 35377337 +2323066 AC007998.4 chr18 35403996 35406528 +2323069 AC007998.3 chr18 35443869 35467088 +2323082 INO80C chr18 35452230 35497991 +2323209 GALNT1 chr18 35581117 35711834 +2323315 AC090220.1 chr18 35595901 35597599 +2323318 AC090229.1 chr18 35716370 35717978 +2323321 AC118757.1 chr18 35951803 35966118 +2323329 C18orf21 chr18 35972625 35979286 +2323412 RPRD1A chr18 35984387 36067576 +2323567 SLC39A6 chr18 36108531 36129385 +2323652 ELP2 chr18 36129444 36180557 +2324166 AC023043.1 chr18 36179996 36187448 +2324170 MOCOS chr18 36187497 36272157 +2324210 AC023043.4 chr18 36189824 36190272 +2324213 FHOD3 chr18 36297714 36780055 +2324522 AC055840.1 chr18 36417055 36424185 +2324528 TPGS2 chr18 36777647 36829216 +2324825 KIAA1328 chr18 36829106 37232172 +2325018 AC016493.1 chr18 36901946 36923814 +2325024 AC015961.1 chr18 37234119 37236242 +2325027 CELF4 chr18 37243040 37565827 +2325444 AC015961.2 chr18 37243776 37247506 +2325448 AC090386.1 chr18 37273706 37276572 +2325459 AC009899.1 chr18 37565281 37762131 +2325477 AC108452.1 chr18 37960220 37992413 +2325484 AC100781.1 chr18 38655209 38688033 +2325503 MIR924HG chr18 39206917 39800322 +2325815 AC011139.1 chr18 39314240 39328008 +2325825 AC099845.1 chr18 39655645 39665494 +2325831 LINC01901 chr18 39841174 39924840 +2325838 LINC01902 chr18 39841709 39896298 +2325898 LINC01477 chr18 40066286 40099233 +2325904 AC068688.1 chr18 40245879 40247367 +2325908 AC079052.1 chr18 41341319 41507550 +2325914 AC021504.1 chr18 41465783 41632185 +2325957 PIK3C3 chr18 41955234 42087830 +2326248 AC087683.2 chr18 42052705 42053030 +2326251 AC087683.3 chr18 42105729 42115538 +2326255 LINC00907 chr18 42159283 42691422 +2326341 AC084335.1 chr18 42649520 42657893 +2326345 RIT2 chr18 42743227 43115691 +2326417 AC100779.1 chr18 43115747 43129039 +2326424 SYT4 chr18 43267892 43277535 +2326485 AC110014.1 chr18 44214971 44342315 +2326491 LINC01478 chr18 44280768 44579953 +2326697 AC120049.1 chr18 44676927 44679717 +2326701 SETBP1 chr18 44680173 45068510 +2326748 AC090376.1 chr18 45104361 45181382 +2326791 SLC14A2 chr18 45212995 45683686 +2326911 SLC14A2-AS1 chr18 45423764 45483218 +2326929 AC021517.1 chr18 45483343 45529855 +2326949 AC021517.2 chr18 45491581 45503824 +2326954 AC091151.1 chr18 45507202 45550183 +2326960 AC091151.5 chr18 45571406 45611540 +2326964 AC023421.2 chr18 45573084 45747215 +2326977 AC023421.1 chr18 45646153 45647937 +2326980 SLC14A1 chr18 45687025 45752520 +2327323 SIGLEC15 chr18 45825675 45844094 +2327379 EPG5 chr18 45847609 45967329 +2327715 PSTPIP2 chr18 45983536 46072272 +2327809 ATP5F1A chr18 46080248 46104334 +2328124 HAUS1 chr18 46104378 46128333 +2328298 C18orf25 chr18 46173553 46266992 +2328359 RNF165 chr18 46326809 46463140 +2328460 AC018931.1 chr18 46409197 46410645 +2328464 LOXHD1 chr18 46476972 46657220 +2328998 ST8SIA5 chr18 46667821 46759257 +2329103 AC090241.2 chr18 46756487 46802449 +2329132 AC090241.3 chr18 46786699 46789297 +2329135 PIAS2 chr18 46803218 46920160 +2329369 KATNAL2 chr18 46917492 47102243 +2329526 ELOA3 chr18 46962768 46964644 +2329536 ELOA3B chr18 47022287 47023927 +2329545 ELOA3D chr18 47028202 47029842 +2329554 ELOA2 chr18 47032572 47035621 +2329572 AC012254.1 chr18 47077361 47091280 +2329576 AC012254.3 chr18 47105946 47108062 +2329579 HDHD2 chr18 47107408 47150500 +2329735 IER3IP1 chr18 47152834 47176364 +2329756 SKOR2 chr18 47206322 47251603 +2329808 AC051635.1 chr18 47263935 47282939 +2329812 MIR4527HG chr18 47285725 47594550 +2329826 AC102797.1 chr18 47501172 47558383 +2329832 SMAD2 chr18 47808957 47931146 +2330032 AC120349.1 chr18 47878295 47882444 +2330036 ZBTB7C chr18 48026672 48410752 +2330407 AC105101.2 chr18 48162039 48184725 +2330415 CTIF chr18 48539031 48863217 +2330553 AC048380.1 chr18 48673575 48688419 +2330558 AC093567.1 chr18 48826051 48834770 +2330562 SMAD7 chr18 48919853 48952052 +2330623 AC114684.1 chr18 48962951 48963941 +2330627 AC016866.1 chr18 49023703 49048474 +2330634 DYM chr18 49041474 49461347 +2330888 AC016866.2 chr18 49116301 49126479 +2330892 AC044840.1 chr18 49205912 49208781 +2330897 AC100778.1 chr18 49431744 49447420 +2330901 AC100778.4 chr18 49447464 49451827 +2330905 C18orf32 chr18 49477250 49487252 +2330939 AC100778.2 chr18 49484536 49486149 +2330943 AC100778.3 chr18 49487339 49491878 +2330947 RPL17 chr18 49488453 49492523 +2331236 LINC02837 chr18 49499390 49501860 +2331240 LIPG chr18 49560699 49599185 +2331341 AC090227.3 chr18 49739823 49742063 +2331345 ACAA2 chr18 49782164 49813953 +2331459 SNHG22 chr18 49814023 49851059 +2331469 MYO5B chr18 49822789 50195147 +2331635 AC091044.1 chr18 49969721 49970957 +2331639 CFAP53 chr18 50227193 50266495 +2331661 AC090246.1 chr18 50256036 50256461 +2331664 MBD1 chr18 50266882 50281774 +2332363 CXXC1 chr18 50282343 50288304 +2332573 AC105227.1 chr18 50302190 50313595 +2332577 SKA1 chr18 50375040 50394168 +2332663 MAPK4 chr18 50560087 50731826 +2332726 AC012433.2 chr18 50647315 50651212 +2332730 MRO chr18 50795120 50825402 +2332924 ME2 chr18 50879080 50954257 +2333454 ELAC1 chr18 50967991 50988121 +2333495 SMAD4 chr18 51028394 51085045 +2333696 MEX3C chr18 51174550 51218304 +2333724 LINC01630 chr18 51346249 51643939 +2333840 AC016383.3 chr18 52223078 52223688 +2333844 AC016383.2 chr18 52283909 52309224 +2333849 AC016383.1 chr18 52336361 52339025 +2333853 DCC chr18 52340197 53535903 +2334162 LINC01917 chr18 53480825 53581107 +2334195 LINC01919 chr18 53568439 53629990 +2334261 MBD2 chr18 54151606 54224669 +2334322 AC093462.1 chr18 54268346 54270028 +2334325 POLI chr18 54269404 54321266 +2334520 STARD6 chr18 54324358 54357964 +2334588 C18orf54 chr18 54357906 54385218 +2334711 DYNAP chr18 54587757 54599493 +2334745 RAB27B chr18 54717860 54895516 +2334792 AC007673.1 chr18 54879457 54880809 +2334796 AC098848.1 chr18 54885866 54898083 +2334802 CCDC68 chr18 54901509 54959461 +2334915 LINC01929 chr18 55105904 55124306 +2334929 TCF4 chr18 55222185 55664787 +2337073 TCF4-AS1 chr18 55452533 55482940 +2337077 TCF4-AS2 chr18 55492175 55496392 +2337081 AC022031.2 chr18 55589904 55839184 +2337106 LINC01415 chr18 55776727 55781722 +2337128 AC022031.1 chr18 55817167 55819759 +2337131 AC027584.1 chr18 55863960 55866550 +2337135 LINC01416 chr18 55881688 55998219 +2337150 AC009271.1 chr18 55893038 56026082 +2337161 AC006305.1 chr18 56003613 56191262 +2337182 AC009271.2 chr18 56026388 56029186 +2337186 LINC01905 chr18 56031830 56135295 +2337460 AC006305.2 chr18 56061109 56063078 +2337464 LINC01539 chr18 56083356 56137536 +2337726 AC006305.3 chr18 56137573 56150102 +2337750 TXNL1 chr18 56597209 56651600 +2337887 WDR7 chr18 56651343 57036606 +2338116 AC012301.1 chr18 56872668 56873970 +2338120 WDR7-OT1 chr18 57027832 57038845 +2338125 AC012301.2 chr18 57046406 57047692 +2338129 LINC-ROR chr18 57054558 57072119 +2338169 AC100775.1 chr18 57136322 57146998 +2338174 BOD1L2 chr18 57147087 57150410 +2338182 LINC02565 chr18 57169615 57171194 +2338186 ST8SIA3 chr18 57352557 57371731 +2338212 AC090340.1 chr18 57427133 57432112 +2338215 ONECUT2 chr18 57435374 57491298 +2338229 FECH chr18 57544389 57586702 +2338405 AC100847.1 chr18 57588611 57589091 +2338408 NARS chr18 57600656 57622213 +2338593 AC027097.1 chr18 57630302 57669296 +2338605 AC027097.2 chr18 57639455 57738603 +2338627 ATP8B1 chr18 57646426 57803315 +2338884 LINC01897 chr18 57961231 57964434 +2338897 NEDD4L chr18 58044226 58401540 +2339851 AC107896.1 chr18 58189834 58195696 +2339860 AC090236.2 chr18 58371566 58372666 +2339863 AC090236.1 chr18 58398663 58400082 +2339867 AC105105.2 chr18 58416765 58417628 +2339871 MIR122HG chr18 58445788 58453766 +2339887 AC105105.4 chr18 58476191 58477484 +2339890 ALPK2 chr18 58481247 58629091 +2339938 AC105105.3 chr18 58511598 58512310 +2339941 AC105105.1 chr18 58535415 58538552 +2339945 AC104971.2 chr18 58557070 58566677 +2339949 AC104971.3 chr18 58659858 58660524 +2339953 AC104971.1 chr18 58670009 58671877 +2339957 MALT1 chr18 58671465 58754477 +2340176 AC104365.1 chr18 58672613 58752730 +2340186 AC104365.3 chr18 58752179 58753898 +2340190 AC104365.2 chr18 58754859 58757842 +2340194 LINC01926 chr18 58808468 58834364 +2340205 ZNF532 chr18 58862600 58986480 +2340496 AC040963.1 chr18 59081911 59085920 +2340546 SEC11C chr18 59139866 59158832 +2340623 GRP chr18 59220158 59230774 +2340670 RAX chr18 59267035 59274086 +2340700 CPLX4 chr18 59275156 59318649 +2340723 LMAN1 chr18 59327823 59359265 +2340772 AC016229.2 chr18 59360700 59386749 +2340776 CCBE1 chr18 59430939 59697662 +2340895 AC016229.1 chr18 59459072 59465682 +2340902 AC090213.1 chr18 59563709 59568615 +2340907 AC010776.1 chr18 59685820 59688400 +2340911 AC010776.2 chr18 59696459 59698111 +2340915 AC010776.3 chr18 59700523 59700946 +2340918 PMAIP1 chr18 59899948 59904306 +2340943 AC090377.1 chr18 60010281 60014258 +2340948 AC090771.2 chr18 60125033 60161195 +2340957 AC090621.1 chr18 60294136 60301317 +2340966 AC091576.1 chr18 60329190 60540205 +2340980 MC4R chr18 60371062 60372775 +2340988 AC113137.1 chr18 60628963 60902726 +2341006 CDH20 chr18 61333430 61555779 +2341095 AC090409.2 chr18 61571342 61579456 +2341106 AC090409.1 chr18 61585746 61607006 +2341119 AC105094.2 chr18 61592375 61748832 +2341133 AC105094.1 chr18 61681653 61682695 +2341137 LINC01544 chr18 61748082 61758464 +2341147 RNF152 chr18 61808067 61894247 +2341177 PIGN chr18 61905255 62187118 +2343241 RELCH chr18 62187255 62310217 +2343537 AC027514.1 chr18 62245810 62247412 +2343540 AC027514.2 chr18 62300036 62300998 +2343544 TNFRSF11A chr18 62325287 62391288 +2343660 AC100843.1 chr18 62372894 62378130 +2343665 ZCCHC2 chr18 62523025 62587709 +2343824 AC064801.1 chr18 62525919 62526325 +2343827 PHLPP1 chr18 62715541 62980433 +2343903 BCL2 chr18 63123346 63320128 +2343934 AC022726.1 chr18 63151114 63151320 +2343937 AC022726.2 chr18 63207622 63208168 +2343940 KDSR chr18 63327726 63367228 +2344113 AC036176.1 chr18 63367328 63381629 +2344117 VPS4B chr18 63389190 63422483 +2344208 SERPINB5 chr18 63476958 63505085 +2344267 AC036176.3 chr18 63485601 63486018 +2344270 SERPINB12 chr18 63556160 63567011 +2344307 SERPINB13 chr18 63586989 63604639 +2344403 SERPINB4 chr18 63637259 63644256 +2344461 SERPINB11 chr18 63647579 63726432 +2344585 SERPINB3 chr18 63655197 63661893 +2344626 SERPINB7 chr18 63752935 63805376 +2344750 SERPINB2 chr18 63871692 63903888 +2344841 SERPINB10 chr18 63897174 63936111 +2344913 HMSD chr18 63949301 63981774 +2344945 AC009802.1 chr18 63966406 63970181 +2344950 SERPINB8 chr18 63970029 64019779 +2345090 LINC01924 chr18 64041555 64423601 +2345131 LINC00305 chr18 64079989 64149088 +2345211 LINC01538 chr18 64181314 64260055 +2345221 AC090348.1 chr18 64872264 64992828 +2345228 AC007948.1 chr18 65105873 65125710 +2345232 AC007631.1 chr18 65186159 65187018 +2345236 LINC01916 chr18 65423958 65448167 +2345241 AC090358.1 chr18 65606079 65652053 +2345251 CDH7 chr18 65750252 65890337 +2345340 AC023394.2 chr18 65865262 65866397 +2345344 AC023394.1 chr18 65917782 65920942 +2345348 CDH19 chr18 66501083 66604138 +2345461 AC110597.1 chr18 67481791 67484966 +2345464 DSEL chr18 67506587 67516720 +2345474 AC110597.3 chr18 67506589 67514030 +2345481 AC114689.3 chr18 67516546 67899619 +2345488 AC022655.1 chr18 67672221 67767051 +2345503 LINC01903 chr18 67808505 67814822 +2345507 AC100844.1 chr18 67940949 67956426 +2345512 AC068112.1 chr18 68102087 68114878 +2345518 AC005909.2 chr18 68237100 68495133 +2345523 LINC01912 chr18 68258080 68264827 +2345535 AC005909.1 chr18 68427030 68436918 +2345541 TMX3 chr18 68673688 68715108 +2345763 CCDC102B chr18 68715209 69055189 +2345869 AC040896.1 chr18 68721082 68721560 +2345872 AC022035.1 chr18 68753179 68754583 +2345876 AC096708.2 chr18 68899781 68902255 +2345883 AC096708.3 chr18 68908048 68908599 +2345886 AC090337.1 chr18 69212277 69214350 +2345889 AC090337.2 chr18 69240448 69250781 +2345900 AC026585.1 chr18 69398726 69399249 +2345903 DOK6 chr18 69400888 69849087 +2345949 AC119868.2 chr18 69483627 69618694 +2345954 AC068254.1 chr18 69704978 69724975 +2345959 CD226 chr18 69831158 69961803 +2346074 RTTN chr18 70003031 70205726 +2346852 AC021701.1 chr18 70205774 70208781 +2346859 SOCS6 chr18 70289045 70330199 +2346885 LINC01909 chr18 70335439 70352459 +2346896 LIVAR chr18 70335929 70337310 +2346900 LINC01910 chr18 70380140 70384591 +2346905 AC091646.1 chr18 70497923 70554100 +2346912 GTSCR1 chr18 70630534 70650744 +2346917 AC090415.2 chr18 71000477 71011490 +2346922 AC091691.3 chr18 71137829 71208366 +2346929 AC091691.2 chr18 71215618 71237158 +2346935 LINC01541 chr18 71519962 71578956 +2346950 LINC01899 chr18 71732615 71788128 +2346964 AC027458.1 chr18 71837039 71870788 +2346968 AC069114.1 chr18 71890409 71944577 +2346973 CBLN2 chr18 72536680 72638521 +2347042 NETO1 chr18 72742314 72868146 +2347138 AC023301.1 chr18 72743756 72745961 +2347141 AC091138.1 chr18 72868388 72881399 +2347152 AC079062.1 chr18 73151241 73264480 +2347204 LINC02582 chr18 73324941 73349879 +2347238 AC079070.1 chr18 73711329 73715490 +2347243 AC090125.1 chr18 73914405 74034161 +2347248 AC090125.2 chr18 73947880 73957974 +2347252 FBXO15 chr18 74073353 74147843 +2347442 TIMM21 chr18 74148523 74160531 +2347497 AC090398.1 chr18 74211391 74240555 +2347503 CYB5A chr18 74250846 74291973 +2347578 AC090398.2 chr18 74293217 74298662 +2347582 C18orf63 chr18 74315839 74359189 +2347616 LINC01922 chr18 74409415 74413209 +2347622 DIPK1C chr18 74434099 74457944 +2347647 AC009704.3 chr18 74464410 74468707 +2347651 CNDP2 chr18 74495816 74523454 +2347978 AC009704.2 chr18 74504766 74505248 +2347981 CNDP1 chr18 74534500 74587212 +2348072 AC009704.1 chr18 74561381 74562100 +2348076 LINC00909 chr18 74590317 74598885 +2348107 ZNF407 chr18 74597870 75065671 +2348201 AC015819.2 chr18 75070197 75071091 +2348206 AC015819.1 chr18 75073543 75074205 +2348209 AC015819.5 chr18 75112137 75125565 +2348213 ZADH2 chr18 75195113 75209139 +2348246 TSHZ1 chr18 75210755 75289950 +2348283 AC116003.3 chr18 75387056 75387596 +2348286 AC116003.1 chr18 75407012 75426607 +2348305 SMIM21 chr18 75409476 75427703 +2348337 AC116003.2 chr18 75432703 75436957 +2348341 AC012101.2 chr18 75455787 75468835 +2348346 AC012101.1 chr18 75472794 75474772 +2348351 AC090812.1 chr18 75506227 75508114 +2348355 AC090338.1 chr18 75642494 75656016 +2348362 LINC01898 chr18 75696044 75712851 +2348373 AC021506.1 chr18 75844925 75868252 +2348377 AC090457.1 chr18 76008118 76015861 +2348381 AC011095.1 chr18 76122968 76145259 +2348400 AC103808.6 chr18 76173304 76177738 +2348404 LINC01893 chr18 76209422 76221718 +2348431 AC103808.2 chr18 76227990 76233387 +2348436 AC103808.4 chr18 76232927 76252044 +2348456 AC103808.3 chr18 76254292 76255214 +2348460 AC103808.1 chr18 76256891 76258337 +2348464 AC103808.5 chr18 76259166 76260114 +2348468 ZNF516 chr18 76357682 76495242 +2348514 AC009716.1 chr18 76372717 76378275 +2348518 AC018413.1 chr18 76491629 76493918 +2348528 C18orf65 chr18 76495521 76498088 +2348532 LINC00683 chr18 76528652 76670111 +2348652 AC034110.1 chr18 76615160 76617645 +2348657 LINC01927 chr18 76622136 76639030 +2348681 LINC01879 chr18 76686058 76693636 +2348691 ZNF236-DT chr18 76794732 76822295 +2348696 AC027575.2 chr18 76805151 76805736 +2348699 ZNF236 chr18 76822607 76970727 +2348940 AC093330.1 chr18 76974690 76984162 +2348962 MBP chr18 76978827 77133683 +2349514 AC093330.3 chr18 77042864 77044739 +2349518 AC018529.1 chr18 77093086 77093446 +2349521 AC018529.2 chr18 77112602 77115726 +2349527 AC100863.1 chr18 77180106 77235430 +2349534 GALR1 chr18 77250549 77277896 +2349548 AC124254.2 chr18 77421619 77561044 +2349553 AC123786.1 chr18 77622552 77624515 +2349557 AC123786.3 chr18 77647014 77650973 +2349561 LINC01029 chr18 77970637 77993731 +2349616 AC134978.1 chr18 77983020 77986610 +2349620 AC107892.1 chr18 78137223 78140887 +2349624 AC087399.1 chr18 78480549 78484867 +2349629 AC012572.1 chr18 78505165 78506410 +2349633 AC044873.1 chr18 78795612 78796672 +2349637 AC091027.2 chr18 78908629 78918993 +2349641 AC091027.1 chr18 78925064 78927441 +2349645 AC091027.3 chr18 78926053 78928494 +2349650 LINC01896 chr18 78976555 78979074 +2349663 SALL3 chr18 78980275 79002677 +2349722 ATP9B chr18 79069285 79378287 +2350121 AC125437.1 chr18 79117207 79117920 +2350124 AC125437.3 chr18 79185801 79191559 +2350128 AC104423.1 chr18 79253577 79254856 +2350132 AC023090.1 chr18 79340258 79343972 +2350136 NFATC1 chr18 79395856 79529325 +2350428 AC018445.5 chr18 79460378 79465843 +2350433 AC018445.1 chr18 79470120 79470940 +2350437 AC018445.6 chr18 79539574 79540840 +2350441 AC068473.3 chr18 79576460 79589010 +2350449 AC068473.4 chr18 79610747 79612303 +2350453 AC068473.1 chr18 79638928 79679745 +2350460 AC068473.5 chr18 79677287 79679358 +2350463 CTDP1 chr18 79679801 79756623 +2350605 AC068473.2 chr18 79702721 79703651 +2350609 AC021594.1 chr18 79787121 79791432 +2350613 AC021594.2 chr18 79792726 79816529 +2350617 KCNG2 chr18 79863668 79900184 +2350629 AC114341.1 chr18 79900555 79900903 +2350632 SLC66A2 chr18 79902420 79951657 +2350795 AC114341.2 chr18 79959579 79963178 +2350799 HSBP1L1 chr18 79964582 79970822 +2350834 TXNL4A chr18 79970813 80033949 +2350955 AC090360.1 chr18 80034346 80097088 +2351000 RBFA chr18 80034389 80050651 +2351047 RBFADN chr18 80046900 80095482 +2351068 ADNP2 chr18 80109262 80147523 +2351122 PARD6G-AS1 chr18 80147924 80179839 +2351146 PARD6G chr18 80157232 80247514 +2351177 AC139100.2 chr18 80161752 80162413 +2351180 AC139100.1 chr18 80183680 80202992 +2351189 AC008993.3 chr19 71778 72718 +2351193 FAM138F chr19 76163 77686 +2351201 OR4F17 chr19 107104 117102 +2351234 AC092192.1 chr19 176896 177913 +2351237 LINC01002 chr19 198264 246544 +2351421 AC016588.2 chr19 248551 251571 +2351424 PLPP2 chr19 281040 291403 +2351518 MIER2 chr19 301444 344815 +2351597 AC016588.1 chr19 305573 306467 +2351601 THEG chr19 361747 376026 +2351658 AC010641.2 chr19 382725 387533 +2351664 AC010641.1 chr19 397589 399173 +2351668 C2CD4C chr19 405445 409147 +2351678 SHC2 chr19 416583 460996 +2351762 ODF3L2 chr19 463346 474983 +2351791 MADCAM1 chr19 489176 505343 +2351940 AC005775.1 chr19 490046 507833 +2351945 TPGS1 chr19 507497 519654 +2351957 CDC34 chr19 531760 542092 +2352018 GZMM chr19 544034 549924 +2352049 AC009005.1 chr19 567210 572228 +2352065 BSG chr19 571277 583493 +2352270 HCN2 chr19 589881 617159 +2352292 POLRMT chr19 617221 633537 +2352395 AC004449.1 chr19 637105 637537 +2352398 FGF22 chr19 639879 644371 +2352423 RNF126 chr19 647526 663233 +2352514 AC004156.1 chr19 663482 669500 +2352518 FSTL3 chr19 676392 683392 +2352586 PRSS57 chr19 685546 695498 +2352617 PALM chr19 708935 748329 +2352730 MISP chr19 751112 764318 +2352750 AC006273.1 chr19 781002 781862 +2352753 LINC01836 chr19 782755 786092 +2352772 PTBP1 chr19 797075 812327 +2353115 PLPPR3 chr19 812488 821977 +2353174 AZU1 chr19 825097 832018 +2353203 PRTN3 chr19 840999 848175 +2353232 ELANE chr19 851014 856247 +2353265 CFD chr19 859664 863641 +2353296 MED16 chr19 867630 893218 +2353595 R3HDM4 chr19 896503 913245 +2353698 KISS1R chr19 917287 921005 +2353733 ARID3A chr19 925781 975939 +2353793 AC005379.1 chr19 928259 928817 +2353797 AC005391.1 chr19 956485 958149 +2353801 WDR18 chr19 984271 998438 +2353970 AC004528.1 chr19 999796 1002757 +2353975 GRIN3B chr19 1000419 1009732 +2354002 TMEM259 chr19 1009648 1021179 +2354162 AC004528.2 chr19 1010221 1010907 +2354166 CNN2 chr19 1026586 1039068 +2354339 ABCA7 chr19 1040101 1065572 +2354770 ARHGAP45 chr19 1065923 1086628 +2355154 POLR2E chr19 1086574 1095380 +2355362 GPX4 chr19 1103926 1106791 +2355562 SBNO2 chr19 1107637 1174268 +2355835 STK11 chr19 1177558 1228435 +2355981 CBARP chr19 1228287 1238027 +2356111 AC004221.1 chr19 1238179 1239522 +2356116 ATP5F1D chr19 1241746 1244825 +2356189 MIDN chr19 1248553 1259140 +2356259 CIRBP chr19 1259384 1274880 +2356882 CIRBP-AS1 chr19 1267471 1270260 +2356886 FAM174C chr19 1275530 1279244 +2356921 EFNA2 chr19 1285873 1301431 +2356935 AC005330.1 chr19 1321225 1322846 +2356939 PWWP3A chr19 1354711 1378431 +2357196 AC005329.2 chr19 1376773 1377520 +2357203 NDUFS7 chr19 1383527 1395589 +2357469 AC005329.3 chr19 1385473 1389665 +2357474 AC005329.1 chr19 1392170 1396467 +2357491 GAMT chr19 1397026 1401570 +2357559 DAZAP1 chr19 1407569 1435687 +2357739 RPS15 chr19 1438358 1440494 +2357895 AC027307.3 chr19 1440839 1441938 +2357898 APC2 chr19 1446302 1473244 +2358085 AC027307.2 chr19 1457670 1458580 +2358088 C19orf25 chr19 1461143 1479556 +2358213 PCSK4 chr19 1481428 1490752 +2358366 REEP6 chr19 1491166 1497927 +2358415 ADAMTSL5 chr19 1505022 1513604 +2358568 AC027307.1 chr19 1508375 1508963 +2358572 PLK5 chr19 1524077 1536046 +2358710 MEX3D chr19 1554669 1568058 +2358728 MBD3 chr19 1573596 1592865 +2358858 UQCR11 chr19 1597169 1605473 +2358899 TCF3 chr19 1609290 1652615 +2359331 AC005256.1 chr19 1748056 1748745 +2359338 ONECUT3 chr19 1753506 1780988 +2359348 ATP8B3 chr19 1782075 1812276 +2359617 REXO1 chr19 1815248 1848483 +2359737 AC012615.2 chr19 1815249 1815873 +2359741 AC012615.6 chr19 1822089 1824542 +2359755 AC012615.3 chr19 1852382 1853622 +2359759 KLF16 chr19 1852399 1863579 +2359798 AC012615.4 chr19 1860250 1862019 +2359803 AC012615.1 chr19 1874871 1876169 +2359806 AC012615.5 chr19 1875016 1875992 +2359810 ABHD17A chr19 1876810 1885547 +2359876 SCAMP4 chr19 1905372 1926013 +2360019 ADAT3 chr19 1905399 1913447 +2360036 CSNK1G2 chr19 1941172 1981338 +2360156 CSNK1G2-AS1 chr19 1952531 1954586 +2360166 BTBD2 chr19 1985438 2034881 +2360278 AC005306.1 chr19 1989401 1990370 +2360284 MKNK2 chr19 2037465 2051244 +2360497 MOB3A chr19 2071036 2096673 +2360581 IZUMO4 chr19 2096429 2099593 +2360753 AP3D1 chr19 2100988 2164468 +2361080 DOT1L chr19 2163933 2232578 +2361222 AC004490.1 chr19 2212029 2215565 +2361226 PLEKHJ1 chr19 2230084 2237704 +2361355 SF3A2 chr19 2236824 2248655 +2361420 AMH chr19 2249309 2252073 +2361443 JSRP1 chr19 2252252 2269759 +2361472 OAZ1 chr19 2269509 2273490 +2361557 PEAK3 chr19 2274631 2282175 +2361571 LINGO3 chr19 2289784 2292024 +2361579 AC104530.1 chr19 2293173 2295781 +2361582 AC005258.2 chr19 2315162 2316875 +2361586 LSM7 chr19 2321520 2328611 +2361645 SPPL2B chr19 2328615 2355095 +2361842 TMPRSS9 chr19 2360238 2426239 +2362017 TIMM13 chr19 2425625 2427586 +2362040 LMNB2 chr19 2427638 2456959 +2362092 LINC01775 chr19 2458935 2462185 +2362096 GADD45B chr19 2476122 2478259 +2362155 GNG7 chr19 2511219 2702694 +2362188 AC092068.2 chr19 2610155 2611862 +2362191 AC092068.1 chr19 2631954 2632849 +2362195 AC092068.3 chr19 2641838 2643853 +2362198 AC006538.3 chr19 2700689 2701266 +2362201 DIRAS1 chr19 2714567 2721372 +2362227 AC006538.4 chr19 2721710 2724517 +2362231 AC006538.1 chr19 2727743 2729327 +2362234 SLC39A3 chr19 2732204 2740028 +2362289 SGTA chr19 2754715 2783282 +2362353 THOP1 chr19 2785503 2815807 +2362520 ZNF554 chr19 2819868 2836735 +2362573 ZNF555 chr19 2841437 2860471 +2362611 AC006130.1 chr19 2847227 2858716 +2362615 AC006130.3 chr19 2862270 2864428 +2362619 ZNF556 chr19 2867335 2883445 +2362659 ZNF57 chr19 2900898 2918473 +2362727 AC119403.1 chr19 2908371 2926817 +2362741 ZNF77 chr19 2933218 2944971 +2362758 TLE6 chr19 2977538 2995179 +2362905 TLE2 chr19 2997639 3047635 +2363320 AC005944.1 chr19 3052910 3053724 +2363324 TLE5 chr19 3052910 3063107 +2363440 GNA11 chr19 3094362 3123999 +2363497 AC005262.2 chr19 3118665 3119304 +2363501 KF456478.1 chr19 3121116 3122128 +2363506 GNA15 chr19 3136033 3163749 +2363545 AC005264.1 chr19 3141576 3155175 +2363551 S1PR4 chr19 3172346 3180332 +2363562 NCLN chr19 3185563 3209575 +2363734 CELF5 chr19 3224661 3297076 +2363880 AC010649.1 chr19 3296765 3306887 +2363891 NFIC chr19 3314403 3469217 +2364082 SMIM24 chr19 3473986 3480525 +2364119 AC005551.1 chr19 3482804 3483446 +2364129 DOHH chr19 3490821 3500940 +2364186 FZR1 chr19 3506273 3538330 +2364363 MFSD12 chr19 3538261 3574290 +2364560 C19orf71 chr19 3539154 3544030 +2364574 AC005786.3 chr19 3544199 3557569 +2364578 AC005786.2 chr19 3558015 3558486 +2364582 HMG20B chr19 3572777 3579088 +2364739 GIPC3 chr19 3585478 3593541 +2364773 TBXA2R chr19 3594506 3606840 +2364810 CACTIN-AS1 chr19 3607247 3613930 +2364816 CACTIN chr19 3610645 3626815 +2364980 PIP5K1C chr19 3630183 3700479 +2365159 AC004637.1 chr19 3672582 3674295 +2365164 TJP3 chr19 3708362 3750813 +2365389 APBA3 chr19 3750772 3761692 +2365450 AC005954.2 chr19 3753840 3756517 +2365455 AC005954.1 chr19 3754620 3756659 +2365459 MRPL54 chr19 3762682 3768575 +2365478 RAX2 chr19 3769089 3772221 +2365501 MATK chr19 3777970 3802129 +2365765 ZFR2 chr19 3804024 3869038 +2365895 ATCAY chr19 3879864 3928082 +2366010 NMRK2 chr19 3933103 3942416 +2366104 DAPK3 chr19 3958453 3971123 +2366189 EEF2 chr19 3976056 3985463 +2366252 PIAS4 chr19 4007736 4039386 +2366303 ZBTB7A chr19 4043303 4066899 +2366326 AC016586.1 chr19 4061615 4062749 +2366330 MAP2K2 chr19 4090321 4124129 +2366449 CREB3L3 chr19 4153631 4173054 +2366555 SIRT6 chr19 4174109 4182566 +2366743 ANKRD24 chr19 4183354 4224814 +2366947 EBI3 chr19 4229523 4237528 +2366966 YJU2 chr19 4247080 4269088 +2367001 SHD chr19 4278601 4290724 +2367052 TMIGD2 chr19 4292232 4302431 +2367103 FSD1 chr19 4304598 4323843 +2367240 STAP2 chr19 4324043 4342786 +2367409 AC104521.1 chr19 4339577 4343491 +2367413 MPND chr19 4343527 4360086 +2367602 AC007292.3 chr19 4347244 4354057 +2367606 AC007292.2 chr19 4356637 4358448 +2367609 SH3GL1 chr19 4360370 4400547 +2367722 AC007292.1 chr19 4363789 4364640 +2367726 CHAF1A chr19 4402640 4445018 +2367809 AC011498.3 chr19 4429689 4430934 +2367813 UBXN6 chr19 4444999 4457794 +2367928 AC011498.2 chr19 4447304 4448217 +2367932 AC011498.6 chr19 4454014 4455286 +2367936 AC011498.1 chr19 4457962 4471493 +2367946 HDGFL2 chr19 4472297 4502208 +2368138 PLIN4 chr19 4502180 4518465 +2368176 PLIN5 chr19 4522531 4535224 +2368229 LRG1 chr19 4536402 4540036 +2368243 SEMA6B chr19 4542593 4559684 +2368324 TNFAIP8L1 chr19 4639516 4655568 +2368345 MYDGF chr19 4641374 4670370 +2368393 AC005339.1 chr19 4654964 4655524 +2368397 DPP9 chr19 4675224 4724673 +2368811 DPP9-AS1 chr19 4679282 4685948 +2368816 AC005594.1 chr19 4692021 4694340 +2368820 MIR7-3HG chr19 4769031 4785077 +2369122 AC005523.1 chr19 4785120 4791207 +2369126 FEM1A chr19 4791734 4801273 +2369134 AC005523.2 chr19 4791745 4795559 +2369141 TICAM1 chr19 4815932 4831704 +2369170 AC027319.1 chr19 4838332 4838907 +2369174 PLIN3 chr19 4838341 4867694 +2369286 ARRDC5 chr19 4890437 4902896 +2369308 UHRF1 chr19 4903080 4962154 +2369607 KDM4B chr19 4969113 5153598 +2369870 PTPRS chr19 5158495 5340803 +2370273 AC022517.1 chr19 5178119 5178464 +2370276 AC005790.1 chr19 5294247 5294696 +2370279 ZNRF4 chr19 5455417 5456856 +2370287 TINCR chr19 5558167 5578349 +2370324 SAFB2 chr19 5586999 5624046 +2370457 SAFB chr19 5623035 5668478 +2370733 RPL36 chr19 5674947 5691875 +2370816 MICOS13 chr19 5678421 5680896 +2370877 HSD11B1L chr19 5680604 5688523 +2371232 LONP1 chr19 5691834 5720572 +2371558 CATSPERD chr19 5720637 5778734 +2371624 PRR22 chr19 5782960 5784746 +2371641 DUS3L chr19 5784832 5791225 +2371812 NRTN chr19 5823802 5828324 +2371822 FUT6 chr19 5830610 5839731 +2371931 FUT3 chr19 5842888 5851474 +2372017 AC024592.2 chr19 5847467 5858239 +2372023 FUT5 chr19 5865826 5870540 +2372040 NDUFA11 chr19 5891276 5904006 +2372096 AC024592.1 chr19 5899895 5901511 +2372103 VMAC chr19 5904872 5910853 +2372113 AC104532.2 chr19 5911578 5913899 +2372117 CAPS chr19 5912339 5916211 +2372194 RANBP3 chr19 5916139 5978142 +2372692 AC011444.1 chr19 5978403 6020363 +2372698 RFX2 chr19 5993164 6199572 +2372990 AC011444.2 chr19 6067953 6077119 +2372994 AC011444.3 chr19 6109322 6125797 +2372998 ACSBG2 chr19 6135247 6193094 +2373250 MLLT1 chr19 6210381 6279975 +2373290 AC011471.2 chr19 6259157 6259799 +2373294 ACER1 chr19 6306142 6333612 +2373312 AC011491.3 chr19 6343761 6362149 +2373318 CLPP chr19 6361531 6370242 +2373395 ALKBH7 chr19 6372794 6375250 +2373435 PSPN chr19 6375148 6379058 +2373451 GTF2F1 chr19 6379572 6393981 +2373558 AC011491.2 chr19 6386762 6390400 +2373562 KHSRP chr19 6413348 6424794 +2373789 SLC25A41 chr19 6426037 6433779 +2373851 SLC25A23 chr19 6436079 6465203 +2374031 CRB3 chr19 6463777 6467221 +2374084 DENND1C chr19 6467207 6482557 +2374368 AC010503.4 chr19 6469465 6470152 +2374371 TUBB4A chr19 6494319 6502848 +2374529 AC010503.2 chr19 6494320 6494805 +2374533 AC010503.1 chr19 6494320 6495025 +2374537 TNFSF9 chr19 6531026 6535924 +2374549 CD70 chr19 6583183 6604103 +2374585 TNFSF14 chr19 6661253 6670588 +2374614 C3 chr19 6677704 6730562 +2374807 AC008760.2 chr19 6716386 6717742 +2374810 GPR108 chr19 6729914 6737603 +2375107 TRIP10 chr19 6737925 6751530 +2375338 AC008760.1 chr19 6748293 6751467 +2375342 SH2D3A chr19 6752160 6767463 +2375430 VAV1 chr19 6772708 6857366 +2375750 ADGRE1 chr19 6887566 6940459 +2375997 AC025278.1 chr19 6953211 6954904 +2376001 MBD3L2B chr19 7018969 7021450 +2376022 MBD3L5 chr19 7030578 7033011 +2376032 MBD3L4 chr19 7037748 7040179 +2376042 MBD3L2 chr19 7049321 7051735 +2376052 MBD3L3 chr19 7056209 7058640 +2376062 ZNF557 chr19 7069703 7087968 +2376105 INSR chr19 7112255 7294414 +2376235 AC119396.1 chr19 7348943 7383385 +2376286 AC119396.2 chr19 7390522 7395039 +2376291 ARHGEF18 chr19 7395113 7472484 +2376476 PEX11G chr19 7476875 7497449 +2376529 TEX45 chr19 7492976 7508450 +2376593 ZNF358 chr19 7515292 7521025 +2376610 AC008878.4 chr19 7519916 7520460 +2376614 MCOLN1 chr19 7522624 7534009 +2376712 PNPLA6 chr19 7534004 7561764 +2377268 CAMSAP3 chr19 7595902 7618304 +2377361 XAB2 chr19 7619525 7629545 +2377424 PET100 chr19 7629793 7631956 +2377481 PCP2 chr19 7631611 7633719 +2377508 AC008763.1 chr19 7633766 7636990 +2377512 STXBP2 chr19 7636881 7647873 +2377863 RETN chr19 7669049 7670455 +2377896 MCEMP1 chr19 7676628 7679826 +2377938 TRAPPC5 chr19 7680833 7687703 +2377975 FCER2 chr19 7688758 7702146 +2378105 CLEC4G chr19 7728957 7733906 +2378150 CD209 chr19 7739993 7747564 +2378328 CLEC4M chr19 7763149 7769605 +2378522 EVI5L chr19 7830233 7864976 +2378649 PRR36 chr19 7868719 7874390 +2378682 AC010336.3 chr19 7870561 7871296 +2378686 LRRC8E chr19 7888505 7902021 +2378745 AC010336.1 chr19 7898804 7903542 +2378748 MAP2K7 chr19 7903843 7914478 +2378857 AC010336.4 chr19 7912648 7913518 +2378861 TGFBR3L chr19 7916145 7919097 +2378889 AC010336.2 chr19 7918652 7919157 +2378892 SNAPC2 chr19 7920338 7923250 +2378947 CTXN1 chr19 7924491 7926135 +2378957 AC010336.5 chr19 7926001 7926810 +2378963 TIMM44 chr19 7926718 7943667 +2379111 AC010336.8 chr19 7944241 7945400 +2379115 ELAVL1 chr19 7958573 8005659 +2379179 AC010336.6 chr19 7959123 7960012 +2379183 AC008946.1 chr19 8008729 8016025 +2379187 CCL25 chr19 8052767 8062650 +2379242 FBN3 chr19 8065402 8149592 +2379807 CERS4 chr19 8206736 8262421 +2380031 AC022146.2 chr19 8222153 8239648 +2380035 CD320 chr19 8302127 8308358 +2380098 NDUFA7 chr19 8308768 8321375 +2380163 RPS28 chr19 8321158 8323340 +2380188 KANK3 chr19 8322584 8343262 +2380274 ANGPTL4 chr19 8363289 8374370 +2380404 RAB11B-AS1 chr19 8374373 8390685 +2380417 RAB11B chr19 8389981 8404434 +2380471 MARCH2 chr19 8413270 8439017 +2380563 AC136469.1 chr19 8423355 8427827 +2380567 HNRNPM chr19 8444767 8489114 +2380876 PRAM1 chr19 8490056 8502640 +2380922 ZNF414 chr19 8509678 8514167 +2381012 MYO1F chr19 8520778 8577577 +2381262 AC092316.1 chr19 8549506 8550139 +2381266 ADAMTS10 chr19 8580240 8610735 +2381572 AC130469.1 chr19 8581160 8582715 +2381576 LINC01862 chr19 8630635 8677708 +2381636 ACTL9 chr19 8697400 8698795 +2381649 OR2Z1 chr19 8721634 8732160 +2381668 ZNF558 chr19 8806170 8832314 +2381741 AC008734.1 chr19 8821501 8824110 +2381745 MBD3L1 chr19 8832398 8843340 +2381764 AC008734.2 chr19 8833065 8833541 +2381767 MUC16 chr19 8848844 8981342 +2382171 OR1M1 chr19 9087061 9095669 +2382188 OR7G2 chr19 9100407 9107475 +2382204 OR7G1 chr19 9114828 9115763 +2382211 OR7G3 chr19 9126012 9126950 +2382218 ZNF317 chr19 9140397 9163424 +2382293 OR7D2 chr19 9178979 9188818 +2382321 OR7D4 chr19 9210276 9219589 +2382347 OR7E24 chr19 9247344 9252625 +2382364 ZNF699 chr19 9291140 9309838 +2382399 AC011451.1 chr19 9291515 9294482 +2382403 ZNF559 chr19 9323772 9351162 +2382618 ZNF177 chr19 9363020 9382617 +2382717 AC011451.3 chr19 9383581 9407055 +2382725 ZNF266 chr19 9412461 9435571 +2382889 AC011451.4 chr19 9458119 9462388 +2382893 ZNF560 chr19 9466355 9498616 +2382923 AC008567.2 chr19 9498678 9510079 +2382927 AC008567.3 chr19 9507820 9514539 +2382931 ZNF426 chr19 9523223 9538645 +2383023 ZNF426-DT chr19 9538693 9539734 +2383033 ZNF121 chr19 9560353 9584533 +2383071 ZNF561 chr19 9604680 9621236 +2383281 ZNF561-AS1 chr19 9621249 9647203 +2383334 ZNF562 chr19 9641807 9675100 +2383447 AC008759.3 chr19 9721903 9722410 +2383450 AC008759.2 chr19 9730853 9731943 +2383454 ZNF846 chr19 9751993 9793180 +2383595 AC008752.1 chr19 9793621 9802301 +2383599 FBXL12 chr19 9810267 9827816 +2383734 UBL5 chr19 9827892 9830115 +2383809 AC008752.2 chr19 9834079 9835013 +2383813 PIN1 chr19 9835257 9849682 +2383911 OLFM2 chr19 9853718 9936552 +2383979 COL5A3 chr19 9959561 10010504 +2384123 AC008742.1 chr19 9995997 9997163 +2384126 RDH8 chr19 10013249 10022279 +2384173 SHFL chr19 10086122 10093252 +2384318 AC020931.1 chr19 10089032 10090377 +2384321 ANGPTL6 chr19 10092338 10102796 +2384374 PPAN chr19 10106362 10112012 +2384488 P2RY11 chr19 10111693 10115372 +2384501 EIF3G chr19 10115014 10119918 +2384699 DNMT1 chr19 10133345 10231286 +2385196 S1PR2 chr19 10221433 10231331 +2385206 MRPL4 chr19 10251901 10260055 +2385394 AC011511.2 chr19 10252268 10285108 +2385399 AC011511.3 chr19 10259109 10260045 +2385403 ICAM1 chr19 10271093 10286615 +2385455 AC011511.5 chr19 10285801 10289019 +2385458 ICAM4 chr19 10286955 10288522 +2385490 ICAM5 chr19 10289952 10296778 +2385541 ZGLP1 chr19 10304803 10309880 +2385575 FDX2 chr19 10310045 10316015 +2385637 RAVER1 chr19 10316212 10333638 +2385770 AC114271.1 chr19 10333436 10336248 +2385773 ICAM3 chr19 10333776 10339661 +2385884 TYK2 chr19 10350529 10380572 +2386196 CDC37 chr19 10391133 10420121 +2386308 PDE4A chr19 10416773 10469630 +2386521 KEAP1 chr19 10486125 10503558 +2386613 AC011461.1 chr19 10490339 10491000 +2386617 S1PR5 chr19 10512742 10517931 +2386652 ATG4D chr19 10543895 10553418 +2386836 KRI1 chr19 10553085 10566031 +2387095 CDKN2D chr19 10566460 10569059 +2387116 AP1M2 chr19 10572671 10587315 +2387267 SLC44A2 chr19 10602457 10644557 +2387581 ILF3-DT chr19 10651862 10653844 +2387584 ILF3 chr19 10654261 10692417 +2388090 QTRT1 chr19 10701430 10713437 +2388224 DNM2 chr19 10718079 10833488 +2388559 TMED1 chr19 10832067 10836318 +2388639 C19orf38 chr19 10836575 10869790 +2388686 CARM1 chr19 10871513 10923070 +2388896 YIPF2 chr19 10922185 10928681 +2389077 TIMM29 chr19 10928811 10933535 +2389097 SMARCA4 chr19 10960825 11079426 +2391608 AC011442.1 chr19 11010917 11016011 +2391612 LDLR chr19 11089362 11133816 +2391931 SPC24 chr19 11131520 11155808 +2392021 KANK2 chr19 11164267 11197791 +2392177 DOCK6 chr19 11199295 11262524 +2392432 AC011472.1 chr19 11203628 11216168 +2392437 AC011472.4 chr19 11221083 11221573 +2392440 ANGPTL8 chr19 11237450 11241943 +2392492 TSPAN16 chr19 11296139 11326996 +2392591 AC011472.2 chr19 11300777 11324441 +2392600 RAB3D chr19 11322068 11346270 +2392631 AC011472.3 chr19 11322156 11324195 +2392635 TMEM205 chr19 11342776 11346518 +2392804 CCDC159 chr19 11344684 11354944 +2393029 PLPPR2 chr19 11355386 11365698 +2393121 AC024575.1 chr19 11368123 11374935 +2393126 SWSAP1 chr19 11374666 11376951 +2393136 EPOR chr19 11377207 11384342 +2393265 RGL3 chr19 11384341 11419342 +2393536 CCDC151 chr19 11420604 11435782 +2393663 PRKCSH chr19 11435288 11450968 +2393956 ELAVL3 chr19 11451326 11481046 +2394007 ZNF653 chr19 11483427 11505839 +2394088 ECSIT chr19 11505929 11529172 +2394276 CNN1 chr19 11538767 11550323 +2394404 ELOF1 chr19 11551147 11559236 +2394518 ZNF627 chr19 11559374 11619161 +2394583 ACP5 chr19 11574660 11579008 +2394708 AC008543.1 chr19 11639754 11686569 +2394726 ZNF823 chr19 11721265 11739009 +2394767 AC008543.3 chr19 11725961 11730783 +2394771 ZNF441 chr19 11767000 11784078 +2394803 AC008543.5 chr19 11796084 11798598 +2394806 ZNF491 chr19 11797667 11809622 +2394833 ZNF440 chr19 11814273 11835216 +2394891 AC008543.4 chr19 11841241 11842439 +2394895 ZNF439 chr19 11848726 11883750 +2394933 ZNF69 chr19 11887782 11914329 +2394974 ZNF700 chr19 11925068 11950773 +2395012 AC008770.3 chr19 11939959 11953381 +2395016 ZNF763 chr19 11965037 11980617 +2395070 ZNF433-AS1 chr19 11987617 12046275 +2395106 ZNF433 chr19 12014732 12035741 +2395230 ZNF878 chr19 12043805 12052961 +2395244 ZNF844 chr19 12064731 12081565 +2395276 ZNF20 chr19 12092843 12140355 +2395346 ZNF625 chr19 12142090 12156734 +2395384 ZNF136 chr19 12163064 12189871 +2395455 ZNF44 chr19 12224686 12294887 +2395579 ZNF563 chr19 12317477 12333720 +2395634 ZNF442 chr19 12345944 12365905 +2395688 ZNF799 chr19 12390016 12401271 +2395734 ZNF443 chr19 12429706 12441021 +2395761 AC008758.2 chr19 12450935 12460705 +2395766 ZNF709 chr19 12461184 12513854 +2395792 ZNF564 chr19 12525373 12551542 +2395846 AC010422.4 chr19 12529768 12532973 +2395850 AC010422.1 chr19 12552597 12553644 +2395854 ZNF490 chr19 12576100 12640098 +2395905 ZNF791 chr19 12610918 12633840 +2395971 MAN2B1 chr19 12646511 12666742 +2396193 WDR83 chr19 12666802 12675832 +2396359 WDR83OS chr19 12668073 12669415 +2396394 AC010422.7 chr19 12670079 12671023 +2396398 DHPS chr19 12675717 12681880 +2396701 AC010422.2 chr19 12682693 12687279 +2396705 GNG14 chr19 12687998 12688422 +2396721 FBXW9 chr19 12688053 12696631 +2396794 AC018761.4 chr19 12688922 12689238 +2396798 TNPO2 chr19 12699194 12724011 +2397251 AC018761.1 chr19 12725517 12725886 +2397255 TRIR chr19 12730640 12734684 +2397300 GET3 chr19 12737139 12748323 +2397376 BEST2 chr19 12751702 12758458 +2397456 HOOK2 chr19 12763003 12872740 +2397762 AC018761.3 chr19 12784539 12785101 +2397766 JUNB chr19 12791486 12793315 +2397774 PRDX2 chr19 12796820 12801800 +2397823 AC018761.2 chr19 12796823 12801849 +2397827 THSD8 chr19 12802031 12813581 +2397864 RNASEH2A chr19 12806556 12815201 +2397934 RTBDN chr19 12825478 12835428 +2398130 AC020934.1 chr19 12825711 12832983 +2398135 MAST1 chr19 12833951 12874952 +2398283 DNASE2 chr19 12875209 12881466 +2398320 AC020934.2 chr19 12880969 12884088 +2398324 KLF1 chr19 12884422 12887199 +2398336 GCDH chr19 12891160 12914207 +2398555 SYCE2 chr19 12898786 12919293 +2398585 FARSA chr19 12922479 12934037 +2398779 FARSA-AS1 chr19 12930522 12933296 +2398784 CALR chr19 12938578 12944489 +2398857 AC092069.1 chr19 12944118 12944487 +2398861 RAD23A chr19 12945855 12953642 +2399039 GADD45GIP1 chr19 12953119 12957223 +2399049 DAND5 chr19 12965159 12974762 +2399072 NFIX chr19 12995608 13098796 +2399347 AC138474.1 chr19 13013662 13014511 +2399351 AC007787.1 chr19 13069792 13071374 +2399354 LYL1 chr19 13099033 13103161 +2399379 TRMT1 chr19 13104902 13117567 +2399705 NACC1 chr19 13116862 13141147 +2399739 AC005546.1 chr19 13131571 13132410 +2399743 AC011446.1 chr19 13139617 13141147 +2399747 STX10 chr19 13144058 13150383 +2399929 IER2 chr19 13150411 13154911 +2399955 AC011446.3 chr19 13152252 13152913 +2399958 AC011446.2 chr19 13153071 13154193 +2399965 CACNA1A chr19 13206442 13633025 +2402005 CCDC130 chr19 13731760 13763296 +2402144 MRI1 chr19 13764522 13774282 +2402198 AC008686.1 chr19 13772118 13774118 +2402208 C19orf53 chr19 13774456 13778773 +2402265 ZSWIM4 chr19 13795460 13832230 +2402335 AC020916.2 chr19 13796574 13796933 +2402338 AC020916.1 chr19 13823880 13842928 +2402341 NANOS3 chr19 13862063 13880757 +2402368 C19orf57 chr19 13882348 13906452 +2402470 CC2D1A chr19 13906201 13930879 +2402728 PODNL1 chr19 13931187 13953392 +2402894 DCAF15 chr19 13952492 13961449 +2402966 RFX1 chr19 13961530 14007039 +2403053 AC022098.4 chr19 14006422 14006773 +2403056 RLN3 chr19 14028148 14031551 +2403076 AC022098.2 chr19 14030855 14031557 +2403080 IL27RA chr19 14031762 14053218 +2403114 PALM3 chr19 14053363 14062076 +2403178 MISP3 chr19 14072536 14075062 +2403213 C19orf67 chr19 14081624 14085875 +2403249 SAMD1 chr19 14087851 14091036 +2403281 PRKACA chr19 14091688 14118084 +2403414 AC022098.3 chr19 14119106 14119537 +2403418 ASF1B chr19 14119512 14136613 +2403478 AC022098.1 chr19 14137146 14171267 +2403489 ADGRL1 chr19 14147743 14206187 +2403637 AC011509.3 chr19 14217493 14219605 +2403642 AC011509.2 chr19 14254189 14293205 +2403649 AC011509.1 chr19 14267807 14269377 +2403653 LINC01841 chr19 14305458 14370196 +2403664 LINC01842 chr19 14333743 14343916 +2403668 ADGRE5 chr19 14380501 14408725 +2403880 AC008569.1 chr19 14402717 14408723 +2403884 DDX39A chr19 14408798 14419383 +2404120 PKN1 chr19 14433053 14471867 +2404346 AC008569.2 chr19 14458401 14459366 +2404350 PTGER1 chr19 14472466 14475354 +2404362 GIPC1 chr19 14477760 14496149 +2404532 DNAJB1 chr19 14514769 14529770 +2404632 TECR chr19 14517085 14565980 +2404930 NDUFB7 chr19 14566078 14572066 +2404953 CLEC17A chr19 14583084 14611157 +2405082 ADGRE3 chr19 14619117 14690027 +2405230 ZNF333 chr19 14689801 14733746 +2405395 ADGRE2 chr19 14732392 14778560 +2405787 OR7C1 chr19 14789260 14835376 +2405847 OR7A5 chr19 14824251 14835285 +2405864 OR7A10 chr19 14840466 14848922 +2405880 OR7A17 chr19 14878203 14886132 +2405910 OR7C2 chr19 14941489 14942448 +2405917 SLC1A6 chr19 14950034 15022990 +2406079 CCDC105 chr19 15010726 15023276 +2406099 CASP14 chr19 15049480 15058293 +2406123 OR1I1 chr19 15082211 15092970 +2406140 SYDE1 chr19 15107401 15114985 +2406214 ILVBL chr19 15114984 15125786 +2406418 AC003956.1 chr19 15124160 15126174 +2406423 NOTCH3 chr19 15159038 15200995 +2406571 AC004257.1 chr19 15221015 15222297 +2406575 EPHX3 chr19 15226919 15233435 +2406650 BRD4 chr19 15235519 15332545 +2406835 AC005776.2 chr19 15346068 15348417 +2406839 AKAP8 chr19 15353385 15379798 +2406931 AC005785.1 chr19 15379076 15381194 +2406937 AKAP8L chr19 15380050 15419141 +2407208 WIZ chr19 15419980 15449951 +2407381 RASAL3 chr19 15451624 15464544 +2407478 PGLYRP2 chr19 15468645 15498956 +2407527 CYP4F22 chr19 15508525 15552317 +2407590 AC093072.1 chr19 15613247 15614553 +2407594 CYP4F8 chr19 15615218 15630639 +2407725 CYP4F3 chr19 15640897 15662825 +2407891 CYP4F12 chr19 15673018 15697174 +2408105 OR10H2 chr19 15728020 15729060 +2408113 OR10H3 chr19 15737985 15742343 +2408129 AC004597.1 chr19 15760375 15770828 +2408133 OR10H5 chr19 15787661 15801025 +2408150 OR10H1 chr19 15804549 15815664 +2408171 LINC01764 chr19 15827040 15835853 +2408184 UCA1 chr19 15828206 15836328 +2408394 CYP4F2 chr19 15878023 15898077 +2408519 CYP4F11 chr19 15912367 15934867 +2408659 OR10H4 chr19 15944299 15950350 +2408677 LINC00661 chr19 16015287 16027462 +2408720 LINC00905 chr19 16031170 16042142 +2408918 LINC01855 chr19 16065737 16066312 +2408923 TPM4 chr19 16067021 16103002 +2409423 AC008894.1 chr19 16103761 16104254 +2409427 RAB8A chr19 16111889 16134234 +2409492 AC008894.2 chr19 16123661 16139892 +2409499 HSH2D chr19 16134028 16158575 +2409619 CIB3 chr19 16161368 16173525 +2409670 FAM32A chr19 16185380 16192046 +2409730 AC020911.1 chr19 16186276 16189458 +2409734 AC020911.3 chr19 16197080 16197738 +2409737 AP1M1 chr19 16197578 16245907 +2409944 AC020911.2 chr19 16283359 16324514 +2409952 KLF2 chr19 16324817 16327874 +2409973 AC020917.3 chr19 16352462 16353182 +2409976 EPS15L1 chr19 16355239 16472085 +2410433 AC020917.2 chr19 16440946 16443584 +2410437 CALR3 chr19 16479057 16496192 +2410474 C19orf44 chr19 16496394 16521352 +2410591 CHERP chr19 16517894 16542437 +2410695 AC008764.6 chr19 16542746 16544814 +2410698 SLC35E1 chr19 16549831 16572415 +2410777 AC008764.3 chr19 16551773 16552328 +2410781 AC008764.5 chr19 16565551 16566330 +2410785 AC008764.8 chr19 16572624 16575340 +2410788 MED26 chr19 16574907 16629062 +2410848 AC008764.7 chr19 16586905 16587985 +2410851 AC008764.2 chr19 16610411 16636531 +2410855 AC024075.3 chr19 16630743 16643942 +2410862 SMIM7 chr19 16630751 16660442 +2411152 AC024075.2 chr19 16633797 16635269 +2411155 AC024075.1 chr19 16639967 16640668 +2411159 TMEM38A chr19 16661139 16690023 +2411192 NWD1 chr19 16719976 16817963 +2411489 AC008737.3 chr19 16801426 16801714 +2411493 SIN3B chr19 16829400 16880353 +2411675 AC008737.1 chr19 16844025 16846473 +2411679 F2RL3 chr19 16888999 16892606 +2411697 CPAMD8 chr19 16892947 17026815 +2412087 AC020908.2 chr19 17009189 17013460 +2412091 HAUS8 chr19 17049729 17075625 +2412231 AC020908.1 chr19 17051994 17055087 +2412235 MYO9B chr19 17075781 17214537 +2412686 AC020908.3 chr19 17095418 17099307 +2412690 AC020913.1 chr19 17152588 17168051 +2412700 AC020913.3 chr19 17177511 17178476 +2412704 AC020913.2 chr19 17207138 17208010 +2412708 USE1 chr19 17215346 17219829 +2412861 OCEL1 chr19 17226213 17229219 +2413005 NR2F6 chr19 17231883 17245940 +2413028 USHBP1 chr19 17249171 17282786 +2413190 BABAM1 chr19 17267376 17281249 +2413463 ANKLE1 chr19 17281645 17287646 +2413626 ABHD8 chr19 17292131 17310236 +2413658 MRPL34 chr19 17292609 17306843 +2413715 AC010463.3 chr19 17296196 17296695 +2413718 DDA1 chr19 17309518 17323298 +2413775 ANO8 chr19 17323223 17334855 +2413892 GTPBP3 chr19 17334920 17342731 +2414155 PLVAP chr19 17351450 17377342 +2414193 AC010463.2 chr19 17360932 17362753 +2414197 CCDC194 chr19 17390509 17394158 +2414212 BST2 chr19 17402939 17405630 +2414237 BISPR chr19 17405686 17419324 +2414326 MVB12A chr19 17405722 17433724 +2414509 AC010319.4 chr19 17414257 17422324 +2414513 AC010319.3 chr19 17419305 17419774 +2414516 TMEM221 chr19 17435509 17448668 +2414531 AC010319.5 chr19 17452211 17452969 +2414534 NXNL1 chr19 17455425 17460954 +2414544 SLC27A1 chr19 17468769 17506168 +2414681 AC010618.3 chr19 17488990 17511889 +2414698 PGLS chr19 17511636 17521288 +2414762 AC010618.2 chr19 17518330 17520565 +2414766 NIBAN3 chr19 17523301 17553839 +2415104 COLGALT1 chr19 17555649 17583162 +2415174 UNC13A chr19 17601328 17688365 +2415550 AC008761.2 chr19 17613722 17614430 +2415554 MAP1S chr19 17719242 17734513 +2415760 AC008761.1 chr19 17727840 17734513 +2415765 FCHO1 chr19 17747718 17788568 +2416561 B3GNT3 chr19 17794828 17813576 +2416600 INSL3 chr19 17816512 17821574 +2416628 JAK3 chr19 17824780 17848071 +2416823 RPL18A chr19 17859910 17864153 +2416903 SLC5A5 chr19 17871945 17895174 +2416944 CCDC124 chr19 17933015 17943991 +2416987 KCNN1 chr19 17951293 18000080 +2417048 ARRDC2 chr19 18001132 18014102 +2417137 IL12RB1 chr19 18058995 18098944 +2417285 MAST3 chr19 18097793 18151692 +2417378 AC007192.2 chr19 18144522 18151691 +2417382 PIK3R2 chr19 18153163 18170532 +2417554 IFI30 chr19 18173162 18178117 +2417589 MPV17L2 chr19 18193218 18196948 +2417617 RAB3A chr19 18196784 18204042 +2417657 AC005759.1 chr19 18204730 18220480 +2417672 PDE4C chr19 18208652 18248200 +2417965 AC008397.1 chr19 18249950 18255419 +2417987 IQCN chr19 18257097 18274509 +2418084 JUND chr19 18279694 18281622 +2418097 LSM4 chr19 18306230 18323274 +2418162 PGPEP1 chr19 18340598 18369950 +2418282 GDF15 chr19 18374731 18389176 +2418315 LRRC25 chr19 18391137 18397622 +2418336 SSBP4 chr19 18418864 18434562 +2418598 ISYNA1 chr19 18434388 18438167 +2418810 AC010335.1 chr19 18441419 18443597 +2418814 ELL chr19 18442663 18522116 +2418914 AC005387.1 chr19 18531613 18532632 +2418918 FKBP8 chr19 18531751 18544077 +2419126 AC005387.2 chr19 18532908 18536188 +2419130 KXD1 chr19 18557762 18569387 +2419353 AC005253.1 chr19 18557775 18561560 +2419357 AC005253.2 chr19 18568506 18569375 +2419361 UBA52 chr19 18571730 18577550 +2419546 CRLF1 chr19 18572220 18607741 +2419589 REX1BD chr19 18588685 18592336 +2419657 TMEM59L chr19 18607430 18621039 +2419725 KLHL26 chr19 18637025 18671721 +2419785 CRTC1 chr19 18683678 18782333 +2419912 COMP chr19 18782773 18791305 +2420042 UPF1 chr19 18831938 18868236 +2420209 GDF1 chr19 18868545 18896158 +2420231 CERS1 chr19 18868545 18896727 +2420321 AC005197.1 chr19 18881680 18883376 +2420325 COPE chr19 18899514 18919387 +2420470 DDX49 chr19 18919705 18929189 +2420688 HOMER3 chr19 18929201 18941261 +2420902 HOMER3-AS1 chr19 18940235 18947452 +2420907 SUGP2 chr19 18990888 19034023 +2421173 ARMC6 chr19 19033575 19060311 +2421454 SLC25A42 chr19 19063994 19113030 +2421499 TMEM161A chr19 19119169 19138513 +2421733 MEF2B chr19 19145567 19192131 +2421847 BORCS8 chr19 19176903 19192591 +2421935 RFXANK chr19 19192229 19201869 +2422124 NR2C2AP chr19 19201416 19203424 +2422199 NCAN chr19 19211958 19252233 +2422257 HAPLN4 chr19 19254756 19262804 +2422277 TM6SF2 chr19 19264364 19273391 +2422327 SUGP1 chr19 19276018 19320509 +2422555 MAU2 chr19 19320829 19358754 +2422711 GATAD2A chr19 19385826 19508931 +2422909 AC092067.1 chr19 19401979 19402603 +2422913 TSSK6 chr19 19512418 19515548 +2422937 NDUFA13 chr19 19515736 19529054 +2423016 YJEFN3 chr19 19528861 19537581 +2423070 CILP2 chr19 19538248 19546659 +2423117 PBX4 chr19 19561707 19618693 +2423183 AC002306.1 chr19 19606350 19608660 +2423187 LPAR2 chr19 19623655 19628930 +2423263 GMIP chr19 19629476 19643657 +2423445 ATP13A1 chr19 19645198 19663676 +2423657 ZNF101 chr19 19668796 19683509 +2423737 ZNF14 chr19 19710472 19733112 +2423751 AC011477.8 chr19 19749637 19754986 +2423757 LINC00663 chr19 19757366 19776423 +2423788 AC011477.9 chr19 19757951 19774809 +2423793 ZNF506 chr19 19785839 19821751 +2423933 AC011477.2 chr19 19788755 19790531 +2423937 ZNF253 chr19 19865882 19894674 +2423983 AC011477.3 chr19 19892433 19895847 +2423987 ZNF93 chr19 19900913 19963464 +2424071 ZNF682 chr19 19997058 20039505 +2424213 ZNF90 chr19 20077994 20127076 +2424270 AC011447.3 chr19 20122569 20321305 +2424301 ZNF486 chr19 20167214 20200488 +2424328 AC008554.1 chr19 20432552 20571095 +2424338 ZNF737 chr19 20535825 20565809 +2424396 AC010636.1 chr19 20611559 20615389 +2424400 ZNF626 chr19 20619939 20661596 +2424449 AC010329.1 chr19 20746923 20755250 +2424452 ZNF66 chr19 20776304 20809995 +2424490 ZNF85 chr19 20923222 20950697 +2424638 AC008739.1 chr19 20972262 20983210 +2424642 ZNF430 chr19 21020634 21060050 +2424710 ZNF714 chr19 21082159 21125270 +2424839 ZNF431 chr19 21142024 21196053 +2424921 ZNF708 chr19 21291160 21329425 +2424968 ZNF738 chr19 21358930 21379302 +2425040 ZNF493 chr19 21397119 21427573 +2425127 AC010615.2 chr19 21444241 21463908 +2425164 LINC00664 chr19 21483374 21503238 +2425195 ZNF429 chr19 21496682 21556270 +2425280 AC123912.1 chr19 21554640 21569237 +2425284 AC123912.4 chr19 21569738 21587322 +2425294 AC123912.2 chr19 21587432 21594628 +2425301 ZNF100 chr19 21722771 21767579 +2425380 AC092364.1 chr19 21768772 21793860 +2425387 ZNF43 chr19 21804949 21852125 +2425524 ZNF208 chr19 21932958 22010949 +2425616 AC003973.1 chr19 22017898 22052370 +2425707 ZNF257 chr19 22052430 22091480 +2425803 ZNF676 chr19 22179089 22215801 +2425831 AC073539.1 chr19 22243254 22245347 +2425834 AC073539.3 chr19 22259693 22261335 +2425838 ZNF729 chr19 22286441 22317176 +2425852 ZNF98 chr19 22391019 22532485 +2425902 AC011516.1 chr19 22422513 22426045 +2425906 AC025811.1 chr19 22455988 22456459 +2425909 AC011467.7 chr19 22518414 22520580 +2425913 AC011467.1 chr19 22520995 22527949 +2425920 LINC01233 chr19 22532626 22533494 +2425931 LINC01785 chr19 22615552 22623971 +2425949 ZNF492 chr19 22634324 22667671 +2425963 AC024563.1 chr19 22665552 22716991 +2425973 ZNF99 chr19 22752183 22784151 +2426007 ZNF723 chr19 22832291 22858667 +2426021 AC022145.1 chr19 22902538 22914340 +2426030 ZNF728 chr19 22974883 23003176 +2426053 LINC01859 chr19 23015059 23031818 +2426145 LINC01858 chr19 23046958 23063705 +2426174 AC074135.2 chr19 23068473 23071476 +2426184 AC074135.1 chr19 23075201 23100361 +2426194 ZNF730 chr19 23075210 23147221 +2426228 ZNF724 chr19 23221599 23250390 +2426266 AC092329.4 chr19 23259906 23274251 +2426312 ZNF91 chr19 23304991 23395471 +2426387 AC010300.1 chr19 23323968 23329101 +2426390 LINC01224 chr19 23399233 23416075 +2426443 ZNF675 chr19 23525631 23687220 +2426550 ZNF681 chr19 23739195 23758891 +2426582 AC139769.2 chr19 23817599 23874701 +2426588 AC011503.4 chr19 23897321 23899495 +2426592 ZNF726 chr19 23914876 23945159 +2426677 AC011503.1 chr19 23919081 23958035 +2426686 AC011503.2 chr19 23927788 23929287 +2426689 AC092279.1 chr19 24033401 24077377 +2426926 ZNF254 chr19 24033405 24129961 +2427022 AC073534.2 chr19 24146701 24147081 +2427025 ERVK-28 chr19 27638483 27646483 +2427035 LINC00662 chr19 27681072 27794005 +2427455 AC006504.1 chr19 27757184 27760849 +2427458 AC006504.5 chr19 27793431 27984984 +2427581 AC006504.7 chr19 27802838 27803472 +2427584 AC006504.2 chr19 27849635 27889222 +2427592 AC010511.1 chr19 28065267 28125430 +2427603 AC020905.1 chr19 28294093 28313500 +2427608 AC005580.1 chr19 28316705 28386204 +2427627 AC093074.1 chr19 28394851 28396428 +2427631 AC005307.1 chr19 28418483 28429490 +2427635 AC005381.1 chr19 28437060 28535277 +2427654 AC005394.1 chr19 28491864 28632728 +2427658 AC005616.1 chr19 28509238 28518728 +2427662 AC079466.2 chr19 28602379 28648303 +2427666 AC079466.1 chr19 28606688 28615229 +2427684 AC007795.1 chr19 28869507 28879176 +2427697 LINC00906 chr19 28883430 28970874 +2427810 AC008991.1 chr19 28892931 28895949 +2427814 AC011524.1 chr19 28949437 28950200 +2427818 AC011524.2 chr19 28960506 28964943 +2427823 LINC01532 chr19 29002319 29015160 +2427874 AC011505.1 chr19 29083094 29093031 +2427878 UQCRFS1 chr19 29205320 29213151 +2427888 AC007786.1 chr19 29213235 29216604 +2427896 AC007786.2 chr19 29220864 29221666 +2427899 AC007786.3 chr19 29222542 29223137 +2427902 AC007786.4 chr19 29268976 29298576 +2427912 AC011474.1 chr19 29287011 29525752 +2427939 AC011474.3 chr19 29448038 29448380 +2427943 AC011474.2 chr19 29489775 29526948 +2427947 VSTM2B chr19 29526499 29564479 +2427963 POP4 chr19 29606283 29617237 +2428101 PLEKHF1 chr19 29665459 29675477 +2428134 C19orf12 chr19 29698886 29715789 +2428222 AC008798.3 chr19 29775504 29781216 +2428226 CCNE1 chr19 29811991 29824312 +2428348 AC008798.2 chr19 29838532 29841818 +2428352 URI1 chr19 29923644 30016612 +2428536 AC008507.2 chr19 30028741 30029916 +2428539 AC008507.4 chr19 30058229 30060797 +2428546 AC008507.5 chr19 30078133 30085893 +2428551 AC005597.1 chr19 30219666 30228715 +2428555 ZNF536 chr19 30228290 30713538 +2428607 AC011478.1 chr19 30665274 30668647 +2428611 AC011507.1 chr19 30850975 30872507 +2428615 LINC01834 chr19 30907199 30909155 +2428619 AC020897.1 chr19 30946582 30957192 +2428623 AC020912.1 chr19 31100304 31147981 +2428631 TSHZ3 chr19 31149979 31349436 +2428661 LINC01791 chr19 31167457 31225143 +2428741 AC025809.1 chr19 31348881 31417794 +2428747 AC008992.1 chr19 31421997 31427302 +2428751 AC008794.1 chr19 31465653 31466431 +2428755 LINC02841 chr19 31520155 31554803 +2428764 AC011525.1 chr19 31588040 31595720 +2428768 AC011525.2 chr19 31588159 31593786 +2428953 LINC01837 chr19 31797666 32072113 +2429188 LINC01533 chr19 32025808 32073809 +2429287 LINC01782 chr19 32102088 32105916 +2429293 AC011518.1 chr19 32103154 32106544 +2429313 AC074139.1 chr19 32127334 32184504 +2429319 ZNF507 chr19 32345594 32387667 +2429385 AC007773.1 chr19 32390050 32405560 +2429390 DPY19L3 chr19 32405543 32485895 +2429628 PDCD5 chr19 32581190 32587453 +2429727 ANKRD27 chr19 32597006 32676597 +2429909 AC008474.1 chr19 32666298 32673210 +2429913 RGS9BP chr19 32675848 32678300 +2429921 AC008736.1 chr19 32687089 32691750 +2429925 NUDT19 chr19 32691961 32713796 +2429936 AC008736.2 chr19 32718298 32719595 +2429940 TDRD12 chr19 32719753 32829580 +2430155 SLC7A9 chr19 32830509 32869767 +2430300 AC008805.2 chr19 32831295 32833168 +2430304 CEP89 chr19 32875925 32971991 +2430484 FAAP24 chr19 32972209 32978229 +2430557 RHPN2 chr19 32978592 33064888 +2430652 GPATCH1 chr19 33080899 33130542 +2430735 WDR88 chr19 33132090 33175799 +2430809 LRP3 chr19 33177603 33208864 +2430850 AC008738.1 chr19 33178056 33178651 +2430854 AC008738.7 chr19 33207129 33207639 +2430857 SLC7A10 chr19 33208664 33225850 +2430943 AC008738.4 chr19 33217817 33222355 +2430957 AC008738.6 chr19 33283978 33285739 +2430961 AC008738.3 chr19 33299934 33301168 +2430965 CEBPA chr19 33299934 33302534 +2430973 AC008738.5 chr19 33301279 33301940 +2430977 CEBPA-DT chr19 33302857 33305054 +2430980 AC008738.2 chr19 33305036 33309387 +2430984 CEBPG chr19 33373685 33382686 +2431014 PEPD chr19 33386950 33521791 +2431272 AC010485.1 chr19 33555568 33557470 +2431276 CHST8 chr19 33621953 33773509 +2431350 KCTD15 chr19 33795933 33815763 +2431508 AC008556.1 chr19 33906352 33908391 +2431511 AC016587.1 chr19 33997289 34066283 +2431519 LSM14A chr19 34172504 34229515 +2431642 KIAA0355 chr19 34254552 34355571 +2431713 AC010504.1 chr19 34348356 34359412 +2431718 GPI chr19 34359480 34402413 +2432098 PDCD2L chr19 34404399 34426168 +2432143 AC008747.1 chr19 34426112 34428273 +2432147 UBA2 chr19 34428352 34471251 +2432332 WTIP chr19 34481758 34512304 +2432372 SCGB1B2P chr19 34576733 34577701 +2432380 SCGB2B2 chr19 34593329 34675699 +2432410 AC020910.2 chr19 34638122 34640689 +2432414 ZNF302 chr19 34677639 34686397 +2432603 AC020910.5 chr19 34733298 34733837 +2432606 ZNF181 chr19 34734155 34745378 +2432691 ZNF599 chr19 34758073 34773229 +2432733 LINC01801 chr19 34788527 34832869 +2432759 AC008555.1 chr19 34811589 34814345 +2432762 AC008555.2 chr19 34837889 34872479 +2432841 AC008555.4 chr19 34849046 34860747 +2432873 AC008555.5 chr19 34891605 34905139 +2432955 LINC01838 chr19 34905315 34908188 +2432959 ZNF30-AS1 chr19 34923299 34926812 +2432963 ZNF30 chr19 34926903 34945170 +2433040 ZNF792 chr19 34956354 34964229 +2433063 GRAMD1A chr19 34994784 35026471 +2433299 AC020907.3 chr19 34998233 35000170 +2433304 AC020907.4 chr19 35014961 35025335 +2433308 SCN1B chr19 35030470 35040449 +2433403 HPN chr19 35040506 35066571 +2433598 HPN-AS1 chr19 35042902 35106307 +2433619 AC020907.1 chr19 35090930 35113664 +2433633 FXYD3 chr19 35115879 35124324 +2433896 LGI4 chr19 35124513 35142451 +2434012 FXYD1 chr19 35138808 35143109 +2434188 FXYD7 chr19 35143250 35154301 +2434241 FXYD5 chr19 35154730 35169881 +2434476 FAM187B chr19 35224800 35228729 +2434486 LSR chr19 35248330 35267964 +2434712 AC002128.2 chr19 35251440 35253639 +2434716 AC002128.1 chr19 35262846 35264804 +2434720 USF2 chr19 35268962 35279821 +2434929 HAMP chr19 35280716 35285143 +2434956 MAG chr19 35292125 35313807 +2435088 CD22 chr19 35319261 35347361 +2435491 U62631.1 chr19 35330843 35331920 +2435495 FFAR1 chr19 35351552 35353862 +2435502 FFAR3 chr19 35358460 35360489 +2435519 GPR42 chr19 35370929 35372962 +2435536 LINC01531 chr19 35399511 35419385 +2435580 AC002511.2 chr19 35424062 35424652 +2435584 AC002511.1 chr19 35432957 35434642 +2435590 FFAR2 chr19 35443907 35451767 +2435609 KRTDAP chr19 35487324 35495558 +2435649 DMKN chr19 35497220 35513658 +2436940 SBSN chr19 35523367 35528351 +2436980 GAPDHS chr19 35533455 35545319 +2437040 TMEM147-AS1 chr19 35540738 35546029 +2437082 TMEM147 chr19 35545600 35547526 +2437173 ATP4A chr19 35550031 35563658 +2437251 AD000090.1 chr19 35557956 35581954 +2437256 PMIS2 chr19 35586161 35587296 +2437275 LINC01766 chr19 35596581 35601596 +2437328 AC002115.1 chr19 35608285 35612666 +2437332 HAUS5 chr19 35612735 35625355 +2437531 RBM42 chr19 35629030 35637686 +2437665 ETV2 chr19 35641745 35644871 +2437800 COX6B1 chr19 35648323 35658782 +2437854 UPK1A chr19 35666516 35678483 +2437937 UPK1A-AS1 chr19 35667948 35673291 +2437941 ZBTB32 chr19 35704558 35717038 +2438013 KMT2B chr19 35718019 35738878 +2438113 IGFLR1 chr19 35738801 35742453 +2438221 U2AF1L4 chr19 35742464 35745445 +2438457 PSENEN chr19 35745600 35747519 +2438495 AD000671.3 chr19 35747057 35753415 +2438502 LIN37 chr19 35748361 35754519 +2438590 AC002398.2 chr19 35754566 35755490 +2438594 HSPB6 chr19 35754566 35758079 +2438626 PROSER3 chr19 35758143 35771028 +2438822 AC002398.1 chr19 35769144 35771028 +2438826 ARHGAP33 chr19 35774532 35788822 +2439065 PRODH2 chr19 35799988 35813299 +2439152 NPHS1 chr19 35825964 35869287 +2439290 KIRREL2 chr19 35855861 35867109 +2439448 APLP1 chr19 35867899 35879791 +2439721 NFKBID chr19 35887653 35902303 +2439873 HCST chr19 35902529 35904377 +2439900 TYROBP chr19 35904401 35908295 +2440011 LRFN3 chr19 35935358 35945767 +2440042 AF038458.3 chr19 35947115 35959192 +2440048 AF038458.2 chr19 35960512 35964063 +2440052 SDHAF1 chr19 35995199 35996315 +2440060 SYNE4 chr19 36003307 36008813 +2440146 ALKBH6 chr19 36009120 36014239 +2440353 AC002116.2 chr19 36014508 36045972 +2440359 CLIP3 chr19 36014660 36033343 +2440454 THAP8 chr19 36034984 36054739 +2440493 WDR62 chr19 36054881 36105108 +2440761 OVOL3 chr19 36111151 36113711 +2440785 POLR2I chr19 36113709 36115213 +2440867 TBCB chr19 36114289 36125947 +2441018 CAPNS1 chr19 36139953 36150353 +2441355 AD001527.1 chr19 36144081 36148348 +2441359 COX7A1 chr19 36150922 36152449 +2441401 ZNF565 chr19 36182060 36246257 +2441480 ZNF146 chr19 36214602 36238774 +2441516 AC092296.2 chr19 36304564 36321274 +2441552 LINC00665 chr19 36313067 36331770 +2441679 ZFP14 chr19 36334453 36379201 +2441706 AC092296.1 chr19 36378028 36378832 +2441710 AC092296.4 chr19 36379351 36380912 +2441714 ZFP82 chr19 36383120 36418644 +2441739 ZNF566 chr19 36445119 36489902 +2441844 AC092295.2 chr19 36489649 36491040 +2441847 ZNF260 chr19 36510687 36528271 +2441895 AC092295.1 chr19 36528318 36535235 +2441900 ZNF529 chr19 36534774 36605276 +2441997 ZNF529-AS1 chr19 36573070 36594708 +2442029 ZNF382 chr19 36604817 36634114 +2442120 ZNF461 chr19 36636618 36666853 +2442262 AC074138.1 chr19 36668102 36669404 +2442265 LINC01534 chr19 36682636 36687449 +2442282 ZNF567 chr19 36687612 36727701 +2442366 ZNF850 chr19 36714383 36772825 +2442410 AC020928.1 chr19 36773112 36777078 +2442423 AC020928.2 chr19 36773712 36775908 +2442426 ZNF790-AS1 chr19 36797502 36831596 +2442470 ZNF790 chr19 36817428 36850787 +2442581 ZNF345 chr19 36850361 36913029 +2442726 ZNF829 chr19 36888124 36916291 +2442767 ZNF568 chr19 36916329 36998700 +2443006 ZNF420 chr19 37007857 37130368 +2443114 AC010632.1 chr19 37075113 37078605 +2443118 AC010632.2 chr19 37091341 37092564 +2443121 ZNF585A chr19 37106734 37172741 +2443213 AC012309.2 chr19 37128679 37141640 +2443218 ZNF585B chr19 37181579 37218153 +2443334 ZNF383 chr19 37217926 37248738 +2443427 AC016590.1 chr19 37235507 37304395 +2443470 LINC01535 chr19 37251885 37265535 +2443529 AC016590.4 chr19 37304451 37309641 +2443534 ZNF875 chr19 37312837 37369365 +2443871 AC016590.3 chr19 37314868 37315620 +2443874 AC016590.2 chr19 37337236 37337743 +2443878 ZNF527 chr19 37371061 37393066 +2443974 ZNF569 chr19 37411155 37469275 +2444084 ZNF570 chr19 37467585 37488652 +2444172 ZNF793-AS1 chr19 37497159 37507122 +2444193 AC022148.2 chr19 37503906 37504465 +2444196 ZNF793 chr19 37506939 37548762 +2444359 AC022148.1 chr19 37545470 37549171 +2444363 ZNF571-AS1 chr19 37548914 37587348 +2444422 ZNF540 chr19 37551406 37614179 +2444532 ZNF571 chr19 37554782 37594792 +2444611 ZFP30 chr19 37613749 37692337 +2444732 ZNF781 chr19 37667751 37692315 +2444771 ZNF607 chr19 37696371 37719761 +2444837 AC093227.1 chr19 37728586 37730643 +2444841 AC093227.3 chr19 37728596 37730733 +2444845 ZNF573 chr19 37735833 37817300 +2445051 WDR87 chr19 37884823 37906677 +2445090 SIPA1L3 chr19 37907208 38208369 +2445191 AC008395.1 chr19 37963853 37964790 +2445195 AC011465.1 chr19 38108500 38109533 +2445199 AC011479.3 chr19 38184376 38186265 +2445202 AC011479.2 chr19 38199836 38200934 +2445206 DPF1 chr19 38211006 38229714 +2445528 SPINT2 chr19 38244035 38292615 +2445644 PPP1R14A chr19 38251237 38256532 +2445702 AC011479.4 chr19 38290117 38292423 +2445706 YIF1B chr19 38303558 38317273 +2445933 C19orf33 chr19 38304164 38305006 +2445968 KCNK6 chr19 38319845 38332076 +2445983 CATSPERG chr19 38335775 38370943 +2446387 AC005625.1 chr19 38361795 38362484 +2446391 PSMD8 chr19 38374536 38383824 +2446524 GGN chr19 38384267 38388082 +2446572 AC005789.1 chr19 38385522 38386759 +2446576 SPRED3 chr19 38388421 38399587 +2446660 FAM98C chr19 38403135 38409088 +2446753 RASGRP4 chr19 38409051 38426305 +2447354 RYR1 chr19 38433699 38587564 +2447994 AC067969.2 chr19 38526954 38528555 +2447999 AC067969.1 chr19 38535517 38537128 +2448003 MAP4K1 chr19 38587641 38618882 +2448367 AC008649.1 chr19 38596346 38601694 +2448372 EIF3K chr19 38619082 38636955 +2448549 ACTN4 chr19 38647649 38731589 +2448726 AC008649.2 chr19 38683873 38693606 +2448730 CAPN12 chr19 38730187 38769904 +2448918 AC022144.1 chr19 38738284 38739863 +2448921 LGALS7 chr19 38770971 38773492 +2448941 LGALS7B chr19 38789200 38791754 +2448958 LGALS4 chr19 38801671 38812945 +2449048 ECH1 chr19 38815422 38831841 +2449195 AC104534.1 chr19 38820166 38823223 +2449199 HNRNPL chr19 38836388 38852347 +2449418 AC008982.2 chr19 38844729 38845499 +2449422 RINL chr19 38867830 38878275 +2449526 AC011455.1 chr19 38870159 38873763 +2449531 SIRT2 chr19 38878555 38899862 +2449902 NFKBIB chr19 38899700 38908893 +2449991 CCER2 chr19 38908980 38912158 +2450015 SARS2 chr19 38915266 38930896 +2450264 MRPS12 chr19 38930548 38933162 +2450299 ERVK9-11 chr19 38935297 38938632 +2450302 FBXO17 chr19 38941401 38975742 +2450381 AC011455.6 chr19 38975161 39014527 +2450385 FBXO27 chr19 38990714 39032785 +2450465 AC010605.1 chr19 39030436 39031323 +2450469 ACP7 chr19 39083913 39111493 +2450572 PAK4 chr19 39125770 39182816 +2450766 AC011443.1 chr19 39134882 39136463 +2450770 NCCRP1 chr19 39196964 39201884 +2450788 SYCN chr19 39202831 39204266 +2450798 IFNL3 chr19 39243553 39245129 +2450831 IFNL2 chr19 39268514 39270092 +2450849 IFNL1 chr19 39296407 39298673 +2450865 LRFN1 chr19 39306568 39315336 +2450874 AC011445.1 chr19 39314651 39320858 +2450880 GMFG chr19 39328353 39342372 +2451058 AC011445.2 chr19 39341773 39341945 +2451061 SAMD4B chr19 39342396 39385710 +2451254 PAF1 chr19 39385629 39391154 +2451371 MED29 chr19 39391303 39400641 +2451446 ZFP36 chr19 39406847 39409412 +2451480 PLEKHG2 chr19 39412669 39428415 +2451739 RPS16 chr19 39433137 39435949 +2451824 SUPT5H chr19 39436156 39476670 +2452261 TIMM50 chr19 39480412 39493785 +2452513 DLL3 chr19 39498895 39508481 +2452579 SELENOV chr19 39515113 39520686 +2452650 EID2B chr19 39530987 39532852 +2452661 AC011500.3 chr19 39532412 39534422 +2452666 EID2 chr19 39538707 39540161 +2452674 LGALS13 chr19 39602501 39607474 +2452715 LGALS16 chr19 39655913 39660647 +2452742 LGALS14 chr19 39704481 39709444 +2452780 CLC chr19 39731255 39738029 +2452794 LEUTX chr19 39776595 39786167 +2452817 AC005393.1 chr19 39812972 39813555 +2452820 DYRK1B chr19 39825350 39834201 +2452986 FBL chr19 39834458 39846379 +2453150 FCGBP chr19 39863323 39934626 +2453238 PSMC4 chr19 39971165 39981764 +2453326 ZNF546 chr19 39984134 40021038 +2453461 ZNF780B chr19 40028260 40056231 +2453555 ZNF780A chr19 40069152 40090938 +2453731 AC005614.1 chr19 40090754 40094406 +2453734 MAP3K10 chr19 40191426 40215575 +2453818 TTC9B chr19 40216058 40218399 +2453832 CNTD2 chr19 40222208 40226697 +2453895 AKT2 chr19 40230317 40285536 +2454480 AC118344.1 chr19 40273489 40275479 +2454484 C19orf47 chr19 40319536 40348527 +2454621 PLD3 chr19 40348456 40380439 +2454945 HIPK4 chr19 40379271 40390181 +2454959 PRX chr19 40393768 40413366 +2455000 SERTAD1 chr19 40421589 40425992 +2455009 AC010271.2 chr19 40426115 40426702 +2455012 SERTAD3 chr19 40440844 40444335 +2455050 AC010271.1 chr19 40443436 40444087 +2455054 BLVRB chr19 40447765 40465764 +2455130 SPTBN4 chr19 40466241 40576464 +2455612 SHKBP1 chr19 40576853 40591399 +2456007 LTBP4 chr19 40592883 40629818 +2456544 NUMBL chr19 40665905 40690972 +2456693 COQ8B chr19 40691530 40718207 +2456959 ITPKC chr19 40717112 40740860 +2456991 C19orf54 chr19 40740856 40751553 +2457141 SNRPA chr19 40750637 40765389 +2457252 MIA chr19 40771648 40777490 +2457328 RAB4B chr19 40778216 40796942 +2457428 AC008537.4 chr19 40779780 40796943 +2457433 EGLN2 chr19 40798996 40808434 +2457593 AC008537.2 chr19 40831221 40837210 +2457597 CYP2A6 chr19 40843541 40850447 +2457648 CYP2A7 chr19 40875439 40882752 +2457715 AC092071.1 chr19 40946347 40947450 +2457719 CYP2B6 chr19 40991282 41018398 +2457788 CYP2A13 chr19 41088451 41096195 +2457812 CYP2F1 chr19 41114432 41128381 +2457893 CYP2S1 chr19 41193210 41207539 +2457982 AXL chr19 41219223 41261766 +2458128 AC011510.1 chr19 41221426 41222051 +2458132 HNRNPUL1 chr19 41262496 41307787 +2458570 TGFB1 chr19 41301587 41353922 +2458609 AC011462.5 chr19 41307397 41310412 +2458613 CCDC97 chr19 41310172 41324873 +2458643 TMEM91 chr19 41350911 41384083 +2458804 B9D2 chr19 41354417 41364165 +2458837 AC011462.4 chr19 41373971 41374419 +2458840 EXOSC5 chr19 41386374 41397359 +2458897 BCKDHA chr19 41397808 41425002 +2458996 AC011462.3 chr19 41399372 41400365 +2459000 AC011462.2 chr19 41425359 41426237 +2459004 B3GNT8 chr19 41425359 41428730 +2459022 DMAC2 chr19 41431318 41440717 +2459213 ERICH4 chr19 41443156 41444765 +2459223 PCAT19 chr19 41449520 41501223 +2459386 AC243960.3 chr19 41531206 41532174 +2459393 LINC01480 chr19 41535183 41536904 +2459407 AC243960.1 chr19 41545192 41555462 +2459425 CEACAM21 chr19 41549518 41586844 +2459530 CEACAM4 chr19 41618971 41627074 +2459570 CEACAM7 chr19 41673303 41706976 +2459617 CEACAM5 chr19 41708585 41729798 +2459771 CEACAM6 chr19 41750977 41772211 +2459800 AC243967.2 chr19 41757898 41786893 +2459804 CEACAM3 chr19 41796587 41811554 +2459897 AC243967.3 chr19 41833686 41835950 +2459900 LYPD4 chr19 41837074 41844697 +2459948 DMRTC2 chr19 41844743 41852333 +2460060 RPS19 chr19 41860255 41872925 +2460165 CD79A chr19 41877120 41881372 +2460204 ARHGEF1 chr19 41883161 41930150 +2460727 ERFL chr19 41907705 41928516 +2460745 RABAC1 chr19 41956681 41959321 +2460827 ATP1A3 chr19 41966582 41997497 +2461128 GRIK5 chr19 41998321 42069498 +2461308 ZNF574 chr19 42068477 42081552 +2461345 POU2F2 chr19 42086110 42196585 +2461780 AC010247.1 chr19 42132555 42137099 +2461788 AC010247.2 chr19 42152569 42157523 +2461792 DEDD2 chr19 42198598 42220140 +2461907 ZNF526 chr19 42220312 42228201 +2461928 GSK3A chr19 42230190 42242625 +2462014 ERF chr19 42247569 42255128 +2462071 CIC chr19 42268537 42295797 +2462259 PAFAH1B3 chr19 42297033 42303546 +2462363 PRR19 chr19 42302098 42310821 +2462402 TMEM145 chr19 42313309 42325064 +2462558 MEGF8 chr19 42325609 42378769 +2462848 CNFN chr19 42387019 42390297 +2462877 LIPE-AS1 chr19 42397128 42652355 +2462912 LIPE chr19 42401514 42427388 +2463003 AC011497.1 chr19 42424384 42425071 +2463007 CXCL17 chr19 42428278 42442946 +2463034 CEACAM1 chr19 42507304 42561234 +2463209 CEACAM8 chr19 42580243 42595055 +2463236 PSG3 chr19 42721638 42740481 +2463319 PSG8 chr19 42752686 42855691 +2463411 PSG8-AS1 chr19 42821863 42826878 +2463417 PSG1 chr19 42866464 42879822 +2463540 PSG6 chr19 42902079 42919563 +2463630 PSG7 chr19 42924132 42937207 +2463687 AC004784.1 chr19 42977463 43171515 +2463695 PSG11 chr19 43007656 43026474 +2463802 PSG2 chr19 43064209 43083045 +2463838 AC005392.1 chr19 43153279 43160862 +2463843 PSG5 chr19 43166256 43186536 +2463957 PSG4 chr19 43192702 43207299 +2464111 PSG9 chr19 43211791 43269530 +2464232 AC005392.2 chr19 43329295 43331430 +2464236 CD177 chr19 43353686 43363172 +2464293 AC005392.3 chr19 43360685 43368970 +2464298 TEX101 chr19 43401496 43418597 +2464344 LYPD3 chr19 43460787 43465608 +2464372 PHLDB3 chr19 43474954 43504935 +2464488 ETHE1 chr19 43506719 43527230 +2464573 ZNF575 chr19 43525497 43536130 +2464627 XRCC1 chr19 43543040 43580473 +2464788 L34079.2 chr19 43553445 43555494 +2464792 L34079.3 chr19 43574638 43575618 +2464796 PINLYP chr19 43575801 43583964 +2464876 IRGQ chr19 43584369 43596135 +2464909 ZNF576 chr19 43596392 43601157 +2464977 SRRM5 chr19 43596617 43614498 +2464996 ZNF428 chr19 43607224 43619629 +2465022 CADM4 chr19 43622368 43639850 +2465050 PLAUR chr19 43646095 43670547 +2465228 IRGC chr19 43716076 43720021 +2465245 SMG9 chr19 43727983 43754962 +2465407 KCNN4 chr19 43766533 43781257 +2465529 LYPD5 chr19 43785874 43827206 +2465622 AC115522.1 chr19 43794309 43795658 +2465626 ZNF283 chr19 43827321 43852017 +2465749 ZNF404 chr19 43872365 43901385 +2465772 AC006213.2 chr19 43891804 43901805 +2465780 AC006213.7 chr19 43897211 43898533 +2465784 AC006213.3 chr19 43901909 43927767 +2465789 ZNF45 chr19 43912624 43935282 +2465861 ZNF221 chr19 43951223 43967709 +2465937 ZNF155 chr19 43967862 43998326 +2466045 AC006213.4 chr19 43976815 43977448 +2466048 AC006213.5 chr19 43978376 43978663 +2466051 AC006213.1 chr19 43996896 44003298 +2466068 ZNF230 chr19 44002957 44013924 +2466123 AC067968.2 chr19 44023118 44025262 +2466132 ZNF222 chr19 44025342 44033110 +2466178 ZNF223 chr19 44051367 44067999 +2466237 ZNF284 chr19 44072159 44089613 +2466253 ZNF224 chr19 44094339 44109886 +2466319 AC021092.1 chr19 44103007 44113183 +2466329 ZNF225 chr19 44112181 44134822 +2466403 ZNF234 chr19 44141554 44160313 +2466458 AC138470.2 chr19 44162527 44164955 +2466462 ZNF226 chr19 44165073 44178381 +2466754 ZNF227 chr19 44207547 44237268 +2466899 ZNF235 chr19 44228729 44305046 +2466990 ZNF233 chr19 44259880 44275317 +2467059 ZNF112 chr19 44326555 44367217 +2467136 ZNF285 chr19 44382298 44401608 +2467205 ZNF229 chr19 44417519 44448578 +2467276 ZNF180 chr19 44474428 44500524 +2467410 CEACAM20 chr19 44501677 44529788 +2467577 AC245748.3 chr19 44536263 44536613 +2467581 IGSF23 chr19 44613563 44636781 +2467628 AC243964.3 chr19 44631573 44725217 +2467647 PVR chr19 44643798 44666162 +2467757 CEACAM19 chr19 44662278 44684359 +2467871 CEACAM16 chr19 44699151 44710718 +2467908 BCL3 chr19 44747705 44760044 +2467980 CBLC chr19 44777869 44800652 +2468048 AC092306.1 chr19 44803701 44804010 +2468051 BCAM chr19 44809059 44821421 +2468166 NECTIN2 chr19 44846175 44889223 +2468235 AC011481.2 chr19 44882027 44890876 +2468239 TOMM40 chr19 44890569 44903689 +2468373 APOE chr19 44905791 44909393 +2468421 APOC1 chr19 44914247 44919349 +2468529 APOC4 chr19 44942237 44945496 +2468550 APOC2 chr19 44945971 44949566 +2468612 AC011481.1 chr19 44950044 44954007 +2468617 CLPTM1 chr19 44954585 44993341 +2468790 RELB chr19 45001449 45038198 +2468906 CLASRP chr19 45039045 45070956 +2469191 ZNF296 chr19 45071500 45076587 +2469216 GEMIN7-AS1 chr19 45076510 45092635 +2469229 GEMIN7 chr19 45079195 45091518 +2469274 MARK4 chr19 45079288 45305284 +2469468 PPP1R37 chr19 45091396 45148077 +2469539 AC005757.1 chr19 45135993 45136977 +2469543 NKPD1 chr19 45149750 45158737 +2469562 TRAPPC6A chr19 45162928 45178237 +2469631 BLOC1S3 chr19 45178745 45216933 +2469670 EXOC3L2 chr19 45212621 45245431 +2469722 CKM chr19 45306413 45322875 +2469744 KLC3 chr19 45333434 45351520 +2469889 ERCC2 chr19 45349837 45370918 +2470196 PPP1R13L chr19 45379638 45406349 +2470316 CD3EAP chr19 45406209 45410766 +2470353 ERCC1 chr19 45407333 45478828 +2470615 FOSB chr19 45467995 45475179 +2470750 RTN2 chr19 45485294 45497055 +2470933 PPM1N chr19 45488777 45502510 +2471043 VASP chr19 45506579 45526983 +2471170 OPA3 chr19 45527427 45602212 +2471198 GPR4 chr19 45589764 45602212 +2471211 EML2 chr19 45606994 45645629 +2471753 EML2-AS1 chr19 45641494 45642840 +2471764 GIPR chr19 45668221 45683722 +2471942 SNRPD2 chr19 45687454 45692569 +2472032 QPCTL chr19 45692666 45703989 +2472087 FBXO46 chr19 45710629 45730896 +2472111 BHMG1 chr19 45733251 45764534 +2472146 SIX5 chr19 45764785 45769252 +2472185 AC074212.1 chr19 45764785 45769806 +2472191 DM1-AS chr19 45767796 45772504 +2472207 DMPK chr19 45769717 45782552 +2472562 DMWD chr19 45782947 45792845 +2472623 RSPH6A chr19 45795713 45815308 +2472673 SYMPK chr19 45815410 45863194 +2473034 AC092301.1 chr19 45830164 45831108 +2473038 FOXA3 chr19 45863989 45873797 +2473055 IRF2BP1 chr19 45883608 45886141 +2473063 MYPOP chr19 45890023 45902613 +2473075 NANOS2 chr19 45913214 45914778 +2473083 NOVA2 chr19 45933734 45973865 +2473111 CCDC61 chr19 45995461 46021318 +2473234 PGLYRP1 chr19 46019153 46023053 +2473246 AC007785.3 chr19 46027648 46031667 +2473257 IGFL4 chr19 46039748 46077118 +2473297 AC007785.1 chr19 46101122 46196218 +2473303 IGFL3 chr19 46120067 46124688 +2473317 IGFL2 chr19 46143106 46161299 +2473362 AC006262.2 chr19 46163893 46180647 +2473372 IGFL2-AS1 chr19 46189029 46203160 +2473429 AC006262.1 chr19 46201552 46214838 +2473468 AC006262.3 chr19 46228964 46230388 +2473472 IGFL1 chr19 46229742 46231243 +2473486 HIF3A chr19 46297046 46343433 +2473806 AC007193.2 chr19 46320197 46340004 +2473810 PPP5C chr19 46347087 46392981 +2473967 AC007193.1 chr19 46382492 46383169 +2473971 AC007193.3 chr19 46390515 46390852 +2473975 CCDC8 chr19 46410329 46413564 +2473983 PNMA8C chr19 46424697 46428951 +2473991 PNMA8A chr19 46466491 46471563 +2474025 PPP5D1 chr19 46480796 46601200 +2474064 PNMA8B chr19 46486906 46495879 +2474075 AC011484.1 chr19 46494508 46496502 +2474078 AC093503.1 chr19 46547056 46600861 +2474089 CALM3 chr19 46601074 46610782 +2474256 AC093503.2 chr19 46609277 46610779 +2474260 PTGIR chr19 46620468 46625089 +2474316 GNG8 chr19 46634076 46634685 +2474326 DACT3 chr19 46647551 46661182 +2474364 DACT3-AS1 chr19 46660364 46677447 +2474376 PRKD2 chr19 46674275 46717127 +2474702 STRN4 chr19 46719511 46746994 +2475059 AC008635.1 chr19 46728603 46732700 +2475064 FKRP chr19 46746046 46776988 +2475320 SLC1A5 chr19 46774883 46788594 +2475425 AC008622.2 chr19 46787815 46789043 +2475430 AP2S1 chr19 46838136 46850992 +2475539 ARHGAP35 chr19 46860997 47005077 +2475607 NPAS1 chr19 47019837 47045775 +2475749 TMEM160 chr19 47045909 47048624 +2475761 ZC3H4 chr19 47064187 47113776 +2475833 SAE1 chr19 47113274 47210636 +2476105 BBC3 chr19 47220822 47232766 +2476157 AC008532.1 chr19 47255850 47256477 +2476160 CCDC9 chr19 47255980 47273701 +2476263 INAFM1 chr19 47274885 47275723 +2476271 C5AR1 chr19 47290023 47322066 +2476297 C5AR2 chr19 47332175 47347329 +2476316 DHX34 chr19 47349315 47382704 +2476394 MEIS3 chr19 47403124 47419527 +2476660 SLC8A2 chr19 47428017 47471893 +2476744 AC073548.2 chr19 47469910 47478550 +2476748 KPTN chr19 47475150 47484265 +2476883 NAPA-AS1 chr19 47484282 47501597 +2476893 NAPA chr19 47487637 47515091 +2477154 ZNF541 chr19 47520685 47555856 +2477273 AC010519.1 chr19 47607524 47733098 +2477278 AC010331.1 chr19 47607873 47608454 +2477281 BICRA chr19 47608196 47703277 +2477361 BICRA-AS1 chr19 47615699 47626395 +2477365 EHD2 chr19 47713422 47743134 +2477414 NOP53 chr19 47745546 47757058 +2477568 NOP53-AS1 chr19 47757036 47768840 +2477573 SELENOW chr19 47778585 47784686 +2477726 TPRX1 chr19 47801243 47819051 +2477759 CRX chr19 47819779 47843330 +2477816 LINC01595 chr19 47863409 47865459 +2477826 SULT2A1 chr19 47870467 47886315 +2477844 BSPH1 chr19 47968046 47992170 +2477862 ELSPBP1 chr19 47994632 48025154 +2477947 CABP5 chr19 48029383 48044079 +2477968 PLA2G4C chr19 48047843 48110817 +2478254 PLA2G4C-AS1 chr19 48061371 48064945 +2478269 LIG1 chr19 48115445 48170603 +2478788 AC011466.3 chr19 48118432 48127706 +2478798 AC011466.2 chr19 48145908 48147413 +2478802 ZSWIM9 chr19 48170680 48197620 +2478834 CARD8 chr19 48180770 48255946 +2479408 AC011466.1 chr19 48204071 48214751 +2479413 CARD8-AS1 chr19 48255675 48258199 +2479417 ZNF114-AS1 chr19 48262900 48271283 +2479422 ZNF114 chr19 48270081 48287608 +2479514 CCDC114 chr19 48296457 48321894 +2479585 EMP3 chr19 48321509 48330553 +2479686 TMEM143 chr19 48332356 48364059 +2479822 SYNGR4 chr19 48364367 48376377 +2479871 KDELR1 chr19 48382575 48391551 +2479920 GRIN2D chr19 48394875 48444931 +2479952 GRWD1 chr19 48445841 48457022 +2479990 KCNJ14 chr19 48455509 48466980 +2480011 AC008403.2 chr19 48465348 48469693 +2480030 CYTH2 chr19 48469208 48482314 +2480240 LMTK3 chr19 48485271 48513935 +2480446 AC008403.3 chr19 48547637 48597238 +2480451 SULT2B1 chr19 48552075 48599425 +2480497 FAM83E chr19 48600810 48614854 +2480529 SPACA4 chr19 48606742 48607714 +2480537 RPL18 chr19 48615328 48619184 +2480715 AC022154.1 chr19 48619272 48624132 +2480727 SPHK2 chr19 48619291 48630717 +2480901 DBP chr19 48630030 48637379 +2480951 CA11 chr19 48637946 48646187 +2480992 NTN5 chr19 48661407 48673081 +2481033 FUT2 chr19 48695971 48705951 +2481066 MAMSTR chr19 48712725 48719725 +2481156 RASIP1 chr19 48720585 48740610 +2481202 IZUMO1 chr19 48740852 48746909 +2481288 FUT1 chr19 48748011 48755390 +2481338 FGF21 chr19 48755524 48758333 +2481363 BCAT2 chr19 48795062 48811029 +2481574 AC026803.3 chr19 48807321 48810717 +2481579 HSD17B14 chr19 48813018 48836510 +2481652 PLEKHA4 chr19 48837097 48868617 +2481822 PPP1R15A chr19 48872421 48876058 +2481839 TULP2 chr19 48880967 48898744 +2481930 NUCB1 chr19 48900312 48923372 +2482091 NUCB1-AS1 chr19 48910930 48918891 +2482095 AC026803.1 chr19 48926171 48926444 +2482098 DHDH chr19 48933699 48944969 +2482161 BAX chr19 48954815 48961798 +2482308 AC026803.2 chr19 48963975 48965158 +2482315 FTL chr19 48965309 48966879 +2482329 GYS1 chr19 48968130 48993310 +2482427 RUVBL2 chr19 48993562 49015970 +2482687 LHB chr19 49015980 49017090 +2482702 AC008687.4 chr19 49017496 49020523 +2482722 CGB3 chr19 49022869 49024333 +2482734 CGB2 chr19 49031912 49033238 +2482755 CGB1 chr19 49035610 49036895 +2482776 CGB5 chr19 49043848 49045311 +2482788 CGB8 chr19 49047638 49049106 +2482800 CGB7 chr19 49054275 49058860 +2482842 AC008687.2 chr19 49060613 49061132 +2482845 NTF4 chr19 49061066 49065054 +2482866 AC008687.3 chr19 49064259 49064856 +2482869 KCNA7 chr19 49067418 49072941 +2482879 SNRNP70 chr19 49085419 49108605 +2483057 LIN7B chr19 49114324 49118460 +2483127 C19orf73 chr19 49118402 49119143 +2483135 PPFIA3 chr19 49119544 49151026 +2483428 HRC chr19 49151198 49155396 +2483475 TRPM4 chr19 49157741 49211836 +2483818 SLC6A16 chr19 49289638 49325215 +2483922 AC011450.1 chr19 49331525 49340303 +2483931 CD37 chr19 49335171 49343335 +2484126 TEAD2 chr19 49340595 49362457 +2484347 AC010524.1 chr19 49356152 49357769 +2484351 DKKL1 chr19 49361783 49375116 +2484420 AC010643.1 chr19 49368558 49388091 +2484433 CCDC155 chr19 49388219 49417990 +2484646 PTH2 chr19 49422419 49423441 +2484656 GFY chr19 49423749 49428818 +2484682 SLC17A7 chr19 49429401 49442360 +2484772 PIH1D1 chr19 49446298 49453497 +2485064 ALDH16A1 chr19 49453225 49471050 +2485248 FLT3LG chr19 49474207 49486231 +2485462 RPL13A chr19 49487554 49492308 +2485611 RPS11 chr19 49496365 49499708 +2485701 FCGRT chr19 49506816 49526428 +2485879 RCN3 chr19 49528003 49546962 +2485931 NOSIP chr19 49555468 49590262 +2486119 PRRG2 chr19 49580646 49591004 +2486182 PRR12 chr19 49591182 49626439 +2486247 AC011495.2 chr19 49625994 49626439 +2486251 RRAS chr19 49635292 49640143 +2486274 SCAF1 chr19 49642209 49658642 +2486341 IRF3 chr19 49659569 49665875 +2486762 BCL2L12 chr19 49665142 49673916 +2486948 PRMT1 chr19 49675786 49689029 +2487218 ADM5 chr19 49688664 49690575 +2487228 AC011495.3 chr19 49688853 49690573 +2487232 CPT1C chr19 49690898 49713731 +2487663 TSKS chr19 49739753 49763306 +2487712 AP2A1 chr19 49766968 49807113 +2487889 FUZ chr19 49806866 49817376 +2488174 AC006942.1 chr19 49808933 49809738 +2488178 MED25 chr19 49818279 49840383 +2488468 PTOV1-AS1 chr19 49838639 49851676 +2488478 PTOV1 chr19 49850735 49860744 +2488784 AC018766.1 chr19 49852887 49854967 +2488789 PTOV1-AS2 chr19 49856970 49859289 +2488802 PNKP chr19 49859882 49878351 +2489269 AKT1S1 chr19 49869033 49878459 +2489375 TBC1D17 chr19 49877425 49888750 +2489598 IL4I1 chr19 49889654 49929539 +2489751 NUP62 chr19 49906825 49929763 +2489931 ATF5 chr19 49928702 49933935 +2489985 SIGLEC11 chr19 49948985 49961172 +2490046 VRK3 chr19 49976468 50025946 +2490516 ZNF473 chr19 50025714 50053414 +2490635 AC010624.3 chr19 50043196 50051062 +2490648 AC010624.1 chr19 50050589 50066793 +2490653 AC010624.2 chr19 50075123 50075902 +2490657 AC010624.5 chr19 50136859 50148230 +2490662 IZUMO2 chr19 50152548 50163195 +2490729 MYH14 chr19 50188186 50310542 +2491384 AC008655.1 chr19 50310022 50310539 +2491388 KCNC3 chr19 50311937 50333515 +2491445 NR1H2 chr19 50329653 50383388 +2491690 NAPSA chr19 50358477 50365830 +2491759 AC008655.2 chr19 50365880 50369331 +2491763 POLD1 chr19 50384204 50418018 +2492271 SPIB chr19 50418938 50431314 +2492373 MYBPC2 chr19 50432892 50466321 +2492438 FAM71E1 chr19 50466785 50476848 +2492507 EMC10 chr19 50476400 50490870 +2492629 AC020909.3 chr19 50480119 50483351 +2492633 AC020909.2 chr19 50486810 50487638 +2492637 JOSD2 chr19 50505998 50511353 +2492700 ASPDH chr19 50511600 50514690 +2492771 LRRC4B chr19 50516892 50568435 +2492814 AC008743.1 chr19 50555370 50557969 +2492818 SYT3 chr19 50621307 50639881 +2492918 C19orf81 chr19 50649445 50659310 +2492949 SHANK1 chr19 50661827 50719450 +2493145 CLEC11A chr19 50723364 50725718 +2493187 GPR32 chr19 50770464 50771732 +2493195 AC010325.1 chr19 50776141 50793142 +2493235 ACP4 chr19 50790415 50795219 +2493262 AC010325.2 chr19 50792685 50793584 +2493266 C19orf48 chr19 50797704 50804929 +2493358 KLK1 chr19 50819146 50823787 +2493400 KLK15 chr19 50825289 50837213 +2493476 AC011523.1 chr19 50830530 50851089 +2493481 KLK3 chr19 50854915 50860764 +2493674 KLK2 chr19 50861568 50880567 +2493871 KLK4 chr19 50906352 50910738 +2493948 KLK5 chr19 50943303 50953093 +2494020 AC011483.2 chr19 50950185 50963649 +2494031 KLK6 chr19 50958631 50969673 +2494145 AC011483.1 chr19 50968193 51012129 +2494155 KLK7 chr19 50976468 50984099 +2494234 KLK8 chr19 50996007 51002711 +2494351 KLK9 chr19 51002508 51009634 +2494380 KLK10 chr19 51012739 51020175 +2494461 AC011473.2 chr19 51014374 51014734 +2494465 KLK11 chr19 51022216 51028039 +2494608 KLK12 chr19 51029092 51035230 +2494726 AC011473.3 chr19 51030076 51034335 +2494730 AC011473.1 chr19 51043806 51052077 +2494734 KLK13 chr19 51055626 51065114 +2494863 KLK14 chr19 51077495 51084245 +2494921 CTU1 chr19 51097606 51108409 +2494933 SIGLEC9 chr19 51124908 51136651 +2494981 SIGLEC7 chr19 51142299 51153526 +2495048 AC063977.6 chr19 51152923 51181966 +2495055 CD33 chr19 51225064 51243860 +2495143 SIGLECL1 chr19 51246348 51269330 +2495230 AC063977.3 chr19 51251231 51271179 +2495235 LINC01872 chr19 51271266 51281234 +2495248 IGLON5 chr19 51311848 51330354 +2495269 VSIG10L chr19 51331536 51342124 +2495302 AC008750.3 chr19 51340695 51344117 +2495314 AC008750.4 chr19 51345169 51353293 +2495318 ETFB chr19 51345169 51366418 +2495371 AC008750.5 chr19 51361712 51365544 +2495375 CLDND2 chr19 51367098 51369003 +2495413 NKG7 chr19 51371606 51372701 +2495469 LIM2 chr19 51379909 51387960 +2495500 C19orf84 chr19 51388289 51390591 +2495519 AC008750.7 chr19 51394488 51403650 +2495523 SIGLEC10 chr19 51410020 51417803 +2495731 AC008750.1 chr19 51414298 51414965 +2495735 AC008750.2 chr19 51415724 51417425 +2495743 SIGLEC8 chr19 51450847 51458456 +2495801 CEACAM18 chr19 51478622 51490952 +2495819 SIGLEC12 chr19 51491227 51501800 +2495880 SIGLEC6 chr19 51517819 51531856 +2496010 AC020914.1 chr19 51519731 51520260 +2496014 ZNF175 chr19 51571283 51592510 +2496067 AC018755.1 chr19 51599289 51600470 +2496070 SIGLEC5 chr19 51611927 51645545 +2496096 AC018755.4 chr19 51639478 51639931 +2496099 SIGLEC14 chr19 51642553 51646801 +2496125 SPACA6P-AS chr19 51685363 51693456 +2496129 SPACA6 chr19 51689128 51712387 +2496224 HAS1 chr19 51713112 51723994 +2496289 FPR1 chr19 51745172 51804110 +2496326 FPR2 chr19 51752026 51770531 +2496383 AC018755.5 chr19 51771311 51773169 +2496387 FPR3 chr19 51795157 51826190 +2496406 ZNF577 chr19 51804816 51890950 +2496602 AC006272.1 chr19 51839771 51840945 +2496606 ZNF649-AS1 chr19 51888025 51900463 +2496611 ZNF649 chr19 51889235 51905040 +2496682 ZNF613 chr19 51927147 51948759 +2496760 ZNF350-AS1 chr19 51949134 51981367 +2496775 ZNF350 chr19 51964340 51986856 +2496856 ZNF615 chr19 51991332 52008230 +2497069 ZNF614 chr19 52012765 52030240 +2497128 ZNF432 chr19 52031378 52095738 +2497208 AC011468.5 chr19 52049007 52049754 +2497211 AC011468.1 chr19 52058490 52063703 +2497215 ZNF841 chr19 52064466 52095765 +2497291 ZNF616 chr19 52113091 52139938 +2497357 AC011468.3 chr19 52142626 52144156 +2497361 ZNF836 chr19 52153864 52171643 +2497423 AC010320.1 chr19 52171158 52177002 +2497427 PPP2R1A chr19 52190048 52229518 +2497585 AC010320.2 chr19 52222225 52231294 +2497596 ZNF766 chr19 52269587 52296046 +2497702 AC010320.3 chr19 52284780 52297920 +2497706 ZNF480 chr19 52297169 52325922 +2497789 AC010320.4 chr19 52300693 52345229 +2497798 ZNF610 chr19 52336243 52367778 +2497909 ZNF880 chr19 52369917 52385795 +2497978 ZNF528-AS1 chr19 52388842 52397783 +2498006 ZNF528 chr19 52397849 52418412 +2498151 ZNF534 chr19 52429187 52452315 +2498217 ZNF578 chr19 52453553 52516882 +2498246 AC010332.3 chr19 52453580 52458836 +2498262 AC022150.3 chr19 52511282 52512342 +2498266 ZNF808 chr19 52527652 52564464 +2498354 ZNF701 chr19 52555457 52587174 +2498439 AC022150.1 chr19 52575883 52585561 +2498443 ZNF83 chr19 52594060 52690496 +2498663 AC022150.2 chr19 52597699 52598887 +2498667 AC022150.4 chr19 52650437 52653284 +2498670 ZNF611 chr19 52702813 52735073 +2498943 ZNF600 chr19 52749942 52786807 +2499023 ZNF28 chr19 52797408 52857600 +2499101 ZNF468 chr19 52838010 52890375 +2499203 ZNF320 chr19 52863790 52897693 +2499320 ZNF888 chr19 52904417 52923481 +2499342 AC010487.2 chr19 52923382 52924075 +2499346 ZNF816 chr19 52949379 52962911 +2499447 AC010328.1 chr19 53007512 53013180 +2499451 ERVV-1 chr19 53013921 53016122 +2499459 ERVV-2 chr19 53044740 53051680 +2499469 ZNF160 chr19 53066606 53103436 +2499629 ZNF415 chr19 53107879 53133077 +2499934 ZNF347 chr19 53124072 53159075 +2500026 ZNF665 chr19 53159213 53193386 +2500081 AC092070.1 chr19 53162428 53163563 +2500085 ZNF677 chr19 53235381 53254898 +2500205 AC092070.3 chr19 53240675 53241913 +2500209 VN1R2 chr19 53258292 53261837 +2500220 VN1R4 chr19 53266676 53267723 +2500228 AC092070.4 chr19 53267870 53270932 +2500233 ZNF845 chr19 53333749 53356906 +2500262 ZNF525 chr19 53365693 53392217 +2500338 ZNF765 chr19 53389793 53430413 +2500429 AC022137.4 chr19 53434661 53473936 +2500433 ZNF761 chr19 53445001 53458261 +2500480 ZNF813 chr19 53467733 53496255 +2500516 ZNF331 chr19 53519527 53580269 +2500885 DPRX chr19 53632056 53637009 +2500897 AC011453.1 chr19 53761961 53764199 +2500900 AC008753.3 chr19 53787597 53788169 +2500904 AC008753.2 chr19 53788782 53789168 +2500907 NLRP12 chr19 53793603 53824394 +2501031 AC008440.1 chr19 53854581 53869107 +2501037 MYADM chr19 53864763 53876435 +2501138 AC008440.2 chr19 53874626 53876049 +2501142 PRKCG chr19 53879190 53907652 +2501231 CACNG7 chr19 53909335 53943941 +2501281 CACNG8 chr19 53963040 53990215 +2501306 CACNG6 chr19 53992288 54012669 +2501339 VSTM1 chr19 54040825 54063953 +2501465 TARM1 chr19 54069895 54081365 +2501496 OSCAR chr19 54094668 54102692 +2501659 NDUFA3 chr19 54102728 54109257 +2501818 TFPT chr19 54107013 54115675 +2501885 PRPF31 chr19 54115410 54131719 +2502062 AC245052.4 chr19 54119511 54125343 +2502068 CNOT3 chr19 54137749 54155681 +2502385 LENG1 chr19 54155161 54159721 +2502399 TMC4 chr19 54160108 54173250 +2502524 MBOAT7 chr19 54173412 54189882 +2502691 TSEN34 chr19 54189938 54194536 +2502817 AC245052.1 chr19 54199454 54199971 +2502821 RPS9 chr19 54200809 54249003 +2502982 LILRB3 chr19 54216278 54223506 +2503144 AC245052.7 chr19 54224523 54224881 +2503147 LILRA6 chr19 54236592 54242791 +2503217 LILRB5 chr19 54249431 54257301 +2503326 LILRB2 chr19 54273821 54281184 +2503522 LILRA5 chr19 54307070 54313166 +2503573 LILRA4 chr19 54333185 54339162 +2503604 LAIR1 chr19 54351384 54370558 +2503897 TTYH1 chr19 54415219 54436904 +2504125 AC245884.1 chr19 54430654 54434698 +2504129 AC245884.9 chr19 54434183 54434665 +2504132 AC245884.10 chr19 54438010 54438346 +2504135 AC245884.8 chr19 54438665 54439544 +2504138 LENG8-AS1 chr19 54444807 54449045 +2504154 LENG8 chr19 54448887 54462037 +2504345 LENG9 chr19 54461732 54463778 +2504353 CDC42EP5 chr19 54465026 54473296 +2504367 LAIR2 chr19 54497879 54510687 +2504412 LILRA2 chr19 54572920 54590287 +2504538 AC245036.5 chr19 54589441 54590287 +2504541 LILRA1 chr19 54593582 54602381 +2504614 LILRB1 chr19 54617158 54637528 +2504910 LILRB1-AS1 chr19 54635722 54638892 +2504914 LILRB4 chr19 54643889 54670359 +2505110 KIR3DL3 chr19 54724479 54736536 +2505132 KIR2DL3 chr19 54738513 54753052 +2505154 KIR2DL1 chr19 54769793 54784322 +2505199 KIR2DL4 chr19 54803535 54814517 +2505341 KIR3DL1 chr19 54816468 54830778 +2505407 KIR3DL2 chr19 54850443 54867207 +2505451 FCAR chr19 54874235 54891420 +2505596 AC245128.3 chr19 54890673 54891420 +2505599 NCR1 chr19 54906148 54916140 +2505712 NLRP7 chr19 54923509 54966312 +2505900 NLRP2 chr19 54953130 55001142 +2506248 AC011476.3 chr19 55006193 55048086 +2506263 GP6 chr19 55013705 55038264 +2506338 RDH13 chr19 55039108 55071291 +2506543 EPS8L1 chr19 55072020 55087923 +2506830 PPP1R12C chr19 55090914 55117637 +2507018 AC010327.8 chr19 55116420 55123169 +2507025 TNNT1 chr19 55132698 55149206 +2507414 TNNI3 chr19 55151767 55157773 +2507511 DNAAF3 chr19 55158661 55166722 +2507756 AC010327.4 chr19 55158939 55177540 +2507763 SYT5 chr19 55171196 55180289 +2507897 PTPRH chr19 55181247 55209506 +2508014 AC010327.7 chr19 55214287 55217281 +2508018 AC010327.5 chr19 55216660 55221616 +2508024 TMEM86B chr19 55226639 55229264 +2508041 PPP6R1 chr19 55229779 55259017 +2508183 HSPBP1 chr19 55262223 55280381 +2508309 BRSK1 chr19 55282072 55312562 +2508491 AC020922.2 chr19 55312029 55312495 +2508495 TMEM150B chr19 55312801 55334048 +2508605 AC020922.4 chr19 55338945 55339283 +2508608 KMT5C chr19 55339853 55348121 +2508727 COX6B2 chr19 55349306 55354719 +2508827 FAM71E2 chr19 55354908 55363260 +2508878 IL11 chr19 55364382 55370463 +2508931 TMEM190 chr19 55376826 55378246 +2508947 AC020922.3 chr19 55377579 55378125 +2508950 TMEM238 chr19 55379244 55384292 +2508960 RPL28 chr19 55385345 55403250 +2509088 UBE2S chr19 55399745 55407788 +2509130 SHISA7 chr19 55428740 55442863 +2509156 ISOC2 chr19 55452985 55462343 +2509244 C19orf85 chr19 55463002 55464707 +2509254 AC008735.3 chr19 55475983 55476482 +2509257 ZNF628 chr19 55476617 55484487 +2509281 NAT14 chr19 55485188 55487568 +2509324 SSC5D chr19 55488404 55519099 +2509411 SBK2 chr19 55529733 55537089 +2509436 SBK3 chr19 55540656 55545543 +2509456 ZNF579 chr19 55576774 55580848 +2509473 FIZ1 chr19 55591376 55601970 +2509519 ZNF524 chr19 55600022 55603138 +2509543 ZNF865 chr19 55605405 55617269 +2509558 AC008735.4 chr19 55612490 55613097 +2509561 ZNF784 chr19 55620742 55624601 +2509580 ZNF580 chr19 55635016 55643470 +2509627 ZNF581 chr19 55635459 55645623 +2509662 CCDC106 chr19 55641062 55653161 +2509775 U2AF2 chr19 55654146 55674715 +2509898 AC008735.2 chr19 55661901 55674715 +2509905 AC008735.1 chr19 55670632 55672069 +2509909 EPN1 chr19 55675226 55709858 +2510010 AC010525.1 chr19 55694118 55694558 +2510013 NLRP9 chr19 55708438 55738402 +2510057 RFPL4A chr19 55759014 55763175 +2510069 RFPL4AL1 chr19 55769141 55773179 +2510081 NLRP11 chr19 55785397 55836800 +2510218 NLRP4 chr19 55836540 55881855 +2510291 NLRP13 chr19 55891699 55932336 +2510347 NLRP8 chr19 55947832 55988629 +2510397 NLRP5 chr19 55999726 56061810 +2510477 LINC01864 chr19 56066684 56078801 +2510483 ZNF787 chr19 56087366 56121295 +2510511 ZNF444 chr19 56132599 56160893 +2510612 GALP chr19 56176008 56185775 +2510653 ZSCAN5B chr19 56189570 56197920 +2510701 ZSCAN5C chr19 56202301 56209452 +2510729 ZSCAN5A chr19 56219670 56368383 +2510869 EDDM13 chr19 56272748 56310454 +2510959 AC006116.5 chr19 56311928 56312486 +2510962 AC006116.8 chr19 56314703 56365316 +2510979 AC006116.6 chr19 56347081 56348183 +2510982 AC006116.9 chr19 56354493 56368053 +2510995 ZNF582 chr19 56375846 56393545 +2511092 AC006116.10 chr19 56376704 56377284 +2511095 AC006116.11 chr19 56380230 56383924 +2511099 AC006116.4 chr19 56387412 56388424 +2511103 ZNF582-AS1 chr19 56393656 56399172 +2511127 ZNF583 chr19 56397966 56436035 +2511200 ZNF667 chr19 56439325 56478065 +2511306 ZNF667-AS1 chr19 56477250 56504362 +2511368 ZNF471 chr19 56507850 56530221 +2511413 AC005498.1 chr19 56535299 56535763 +2511416 AC005498.2 chr19 56536156 56538575 +2511435 ZFP28 chr19 56538948 56556808 +2511497 AC005498.3 chr19 56545566 56567411 +2511505 ZNF470 chr19 56567468 56588911 +2511569 ZNF71 chr19 56595264 56626481 +2511598 SMIM17 chr19 56643159 56657247 +2511623 ZNF835 chr19 56661980 56671783 +2511640 AC006115.2 chr19 56669941 56823395 +2511748 ZIM2 chr19 56774547 56840729 +2511965 PEG3 chr19 56810077 56840728 +2512348 MIMT1 chr19 56840866 56848556 +2512357 USP29 chr19 57119138 57131926 +2512400 ZIM3 chr19 57134096 57145202 +2512416 DUXA chr19 57154021 57167443 +2512433 ZNF264 chr19 57191500 57222846 +2512500 AURKC chr19 57230802 57235548 +2512642 ZNF805 chr19 57240632 57262728 +2512667 AC005261.3 chr19 57261354 57262738 +2512670 ZNF460-AS1 chr19 57267211 57280334 +2512687 ZNF460 chr19 57280051 57294069 +2512719 AC005261.1 chr19 57304305 57308562 +2512722 ZNF543 chr19 57320472 57330770 +2512736 AC005261.2 chr19 57350848 57352012 +2512740 ZNF304 chr19 57351307 57359898 +2512791 ZNF547 chr19 57363477 57379565 +2512834 TRAPPC2B chr19 57363551 57365405 +2512851 ZNF548 chr19 57389850 57402992 +2512996 ZNF17 chr19 57411163 57421939 +2513048 ZNF749 chr19 57435325 57447101 +2513073 AC004076.2 chr19 57449689 57453011 +2513076 VN1R1 chr19 57454790 57457142 +2513084 ZNF772 chr19 57466663 57477570 +2513196 AC003005.2 chr19 57477649 57482996 +2513203 ZNF419 chr19 57487711 57496097 +2513387 ZNF773 chr19 57499915 57518404 +2513462 ZNF549 chr19 57527325 57557542 +2513509 ZNF550 chr19 57535257 57559863 +2513608 ZNF416 chr19 57571566 57578911 +2513622 ZIK1 chr19 57578456 57593890 +2513699 ZNF530 chr19 57599885 57612722 +2513750 ZNF134 chr19 57614233 57624724 +2513785 AC003682.1 chr19 57625032 57626950 +2513789 ZNF211 chr19 57630395 57644041 +2513919 ZSCAN4 chr19 57668935 57679152 +2513948 ZNF551 chr19 57681969 57717301 +2513983 ZNF154 chr19 57697367 57709194 +2514012 ZNF671 chr19 57719751 57727624 +2514067 ZNF776 chr19 57746815 57758148 +2514104 ZNF586 chr19 57769655 57819939 +2514182 ZNF552 chr19 57803841 57814913 +2514215 ZNF587B chr19 57819721 57846238 +2514262 ZNF814 chr19 57848731 57889074 +2514414 ZNF587 chr19 57849859 57865117 +2514452 AC010326.3 chr19 57867038 57868172 +2514456 ZNF417 chr19 57900296 57916610 +2514532 ZNF418 chr19 57921884 57935393 +2514670 ZNF256 chr19 57940833 57947706 +2514691 C19orf18 chr19 57958437 57974534 +2514709 ZNF606 chr19 57977053 58003349 +2514817 AC008969.1 chr19 58002061 58011232 +2514854 AC008969.2 chr19 58016695 58025589 +2514858 ZSCAN1 chr19 58034025 58054631 +2514900 ZNF135 chr19 58059239 58086310 +2514987 ZSCAN18 chr19 58083838 58118427 +2515152 ZNF329 chr19 58126248 58155110 +2515212 AC008751.3 chr19 58155864 58177576 +2515216 ZNF274 chr19 58183029 58213562 +2515362 ZNF544 chr19 58228594 58277495 +2515635 AC020915.2 chr19 58257270 58278808 +2515639 AC020915.1 chr19 58266635 58267685 +2515643 ZNF8 chr19 58278955 58302791 +2515657 ERVK3-1 chr19 58305319 58315663 +2515732 AC010642.2 chr19 58309727 58327248 +2515778 ZSCAN22 chr19 58326994 58342332 +2515790 A1BG chr19 58345178 58353492 +2515837 A1BG-AS1 chr19 58347718 58355455 +2515874 ZNF497 chr19 58354357 58362848 +2515906 AC012313.2 chr19 58357999 58359603 +2515910 AC012313.6 chr19 58362583 58367593 +2515919 ZNF837 chr19 58367618 58381030 +2515942 RPS5 chr19 58386400 58394806 +2516053 RNF225 chr19 58396090 58397079 +2516060 LINC02560 chr19 58400221 58400679 +2516063 ZNF584 chr19 58401504 58418327 +2516147 AC012313.1 chr19 58404238 58408484 +2516159 AC012313.5 chr19 58428632 58431148 +2516162 ZNF132 chr19 58432814 58440153 +2516195 AC012313.8 chr19 58440448 58445849 +2516198 ZNF324B chr19 58451611 58457833 +2516271 ZNF324 chr19 58467045 58475436 +2516320 ZNF446 chr19 58474017 58481230 +2516435 AC012313.7 chr19 58475355 58475763 +2516438 SLC27A5 chr19 58479512 58512413 +2516529 AC012313.9 chr19 58500505 58501137 +2516532 ZBTB45 chr19 58513530 58538911 +2516575 TRIM28 chr19 58544064 58550722 +2516758 CHMP2A chr19 58551566 58555105 +2516844 UBE2M chr19 58555712 58558954 +2516897 MZF1-AS1 chr19 58559129 58574797 +2516922 MZF1 chr19 58561931 58573575 +2517008 AC016629.2 chr19 58593134 58599355 +2517016 DEFB125 chr20 87250 97094 +2517029 DEFB126 chr20 142590 145751 +2517043 DEFB127 chr20 157454 159163 +2517053 DEFB128 chr20 187853 189711 +2517063 DEFB129 chr20 227258 229886 +2517073 DEFB132 chr20 257724 261096 +2517083 AL034548.1 chr20 267186 268857 +2517086 C20orf96 chr20 270863 290778 +2517164 ZCCHC3 chr20 297570 300321 +2517172 AL034548.2 chr20 311731 313237 +2517176 NRSN2-AS1 chr20 316860 348490 +2517192 SOX12 chr20 325595 330224 +2517200 NRSN2 chr20 346782 359660 +2517316 TRIB3 chr20 362835 397559 +2517366 RBCK1 chr20 407498 430966 +2517603 TBC1D20 chr20 435480 462543 +2517662 CSNK2A1 chr20 472498 543835 +2518639 TCF15 chr20 603797 610398 +2518649 SRXN1 chr20 646615 653370 +2518659 SCRT2 chr20 661596 675802 +2518669 SLC52A3 chr20 760080 776015 +2518734 FAM110A chr20 833715 857463 +2518789 ANGPT4 chr20 869900 916334 +2518813 RSPO4 chr20 958452 1002311 +2518842 AL110114.1 chr20 1023874 1118467 +2518861 PSMF1 chr20 1113240 1189415 +2518999 TMEM74B chr20 1180561 1185415 +2519021 C20orf202 chr20 1203454 1208279 +2519031 RAD21L1 chr20 1226056 1296421 +2519111 SNPH chr20 1266280 1309328 +2519178 SDCBP2 chr20 1309909 1329139 +2519272 SDCBP2-AS1 chr20 1325405 1378735 +2519310 AL136531.1 chr20 1361622 1362585 +2519314 FKBP1A chr20 1368978 1393172 +2519433 NSFL1C chr20 1442162 1473842 +2519626 SIRPB2 chr20 1470741 1491587 +2519722 SIRPD chr20 1534251 1557705 +2519758 SIRPB1 chr20 1563521 1620061 +2519918 SIRPG chr20 1629152 1657779 +2520001 SIRPG-AS1 chr20 1633508 1648472 +2520011 AL109809.5 chr20 1729038 1817765 +2520051 AL117335.1 chr20 1888128 1894374 +2520062 SIRPA chr20 1894167 1940592 +2520153 PDYN-AS1 chr20 1947246 2030028 +2520162 PDYN chr20 1978757 1994285 +2520274 STK35 chr20 2101827 2177038 +2520299 AL359916.1 chr20 2107900 2109991 +2520303 AL121899.3 chr20 2194074 2201329 +2520308 AL121899.4 chr20 2206683 2207397 +2520311 AL121899.1 chr20 2207217 2213151 +2520318 TGM3 chr20 2296001 2341079 +2520355 TGM6 chr20 2380901 2432753 +2520421 SNRPB chr20 2461634 2470853 +2520481 ZNF343 chr20 2481817 2524702 +2520602 TMC2 chr20 2536607 2641784 +2520679 NOP56 chr20 2652593 2658393 +2520866 IDH3B chr20 2658395 2664219 +2521050 AL049712.1 chr20 2664352 2665874 +2521054 EBF4 chr20 2692878 2760108 +2521274 CPXM1 chr20 2794074 2800627 +2521308 C20orf141 chr20 2814987 2815833 +2521329 TMEM239 chr20 2816302 2820284 +2521348 PCED1A chr20 2835314 2841190 +2521433 VPS16 chr20 2840703 2866732 +2521610 PTPRA chr20 2864184 3039076 +2521925 GNRH2 chr20 3043622 3045747 +2521974 MRPS26 chr20 3046052 3048250 +2521988 OXT chr20 3071620 3072517 +2522000 AVP chr20 3082556 3084724 +2522012 UBOX5-AS1 chr20 3106913 3150867 +2522025 UBOX5 chr20 3107573 3160196 +2522065 FASTKD5 chr20 3146519 3159865 +2522075 LZTS3 chr20 3162617 3173592 +2522136 DDRGK1 chr20 3190350 3204685 +2522187 ITPA chr20 3208868 3223870 +2522292 SLC4A11 chr20 3227417 3239559 +2522645 AL109976.1 chr20 3239705 3245382 +2522648 C20orf194 chr20 3249305 3407625 +2522734 ATRN chr20 3471018 3651118 +2522852 GFRA4 chr20 3659292 3663399 +2522895 ADAM33 chr20 3667965 3682246 +2523126 SIGLEC1 chr20 3686970 3707128 +2523186 HSPA12B chr20 3732685 3753111 +2523247 C20orf27 chr20 3753508 3768387 +2523308 SPEF1 chr20 3777504 3781448 +2523341 CENPB chr20 3783851 3786740 +2523349 CDC25B chr20 3786772 3806121 +2523569 LINC01730 chr20 3808357 3812434 +2523575 AP5S1 chr20 3820524 3828838 +2523629 MAVS chr20 3846799 3876123 +2523666 AL353194.1 chr20 3888239 3888868 +2523670 PANK2 chr20 3888839 3929882 +2523837 AL031670.1 chr20 3921279 3923400 +2523841 RNF24 chr20 3927309 4015558 +2523911 AL356414.1 chr20 4070152 4075165 +2523916 SMOX chr20 4120980 4187747 +2524069 LINC01433 chr20 4192932 4195953 +2524078 ADRA1D chr20 4220630 4249287 +2524091 AL139350.1 chr20 4422186 4431732 +2524104 AL121781.1 chr20 4475638 4525200 +2524108 PRNP chr20 4686350 4701590 +2524141 PRND chr20 4721909 4728460 +2524151 PRNT chr20 4731279 4740668 +2524164 AL133396.2 chr20 4761300 4761696 +2524167 RASSF2 chr20 4780023 4823608 +2524234 SLC23A2 chr20 4852356 5010293 +2524349 AL121890.3 chr20 5045761 5046276 +2524352 AL121890.2 chr20 5049857 5050321 +2524355 AL121890.5 chr20 5061037 5061340 +2524358 AL121890.4 chr20 5066082 5068154 +2524363 TMEM230 chr20 5068232 5113103 +2524507 PCNA chr20 5114953 5126626 +2524544 CDS2 chr20 5126879 5197887 +2524631 PROKR2 chr20 5302040 5314369 +2524640 AL121757.2 chr20 5318268 5503189 +2524661 AL121757.3 chr20 5407564 5407876 +2524664 LINC00658 chr20 5426892 5471094 +2525024 AL121757.1 chr20 5445838 5475483 +2525043 LINC00654 chr20 5482736 5526709 +2525079 LINC01729 chr20 5507875 5510002 +2525084 AL109935.1 chr20 5533628 5535889 +2525089 GPCPD1 chr20 5544399 5611006 +2525217 SHLD1 chr20 5750393 5864395 +2525261 CHGB chr20 5911510 5925353 +2525293 TRMT6 chr20 5937228 5950558 +2525375 MCM8 chr20 5950652 5998977 +2525589 MCM8-AS1 chr20 5990943 6005821 +2525596 AL035461.2 chr20 6000418 6000941 +2525599 CRLS1 chr20 6006093 6040053 +2525678 LRRN4 chr20 6040546 6054060 +2525694 AL118505.1 chr20 6065966 6067897 +2525697 FERMT1 chr20 6074845 6123544 +2525785 CASC20 chr20 6446723 6528459 +2525790 LINC01713 chr20 6731080 6736326 +2525803 BMP2 chr20 6767686 6780246 +2525815 AL096799.1 chr20 7069614 7146656 +2525819 LINC01428 chr20 7146467 7254202 +2525829 AL080248.1 chr20 7255053 7258323 +2525843 LINC01751 chr20 7302056 7307432 +2525847 LINC01706 chr20 7347451 7367933 +2525867 HAO1 chr20 7882985 7940458 +2525889 TMX4 chr20 7977346 8019805 +2525952 AL021396.1 chr20 8019180 8043512 +2525983 PLCB1 chr20 8077251 8968360 +2526867 PLCB1-IT1 chr20 8248704 8256918 +2526874 PLCB4 chr20 9068763 9481242 +2527449 LAMP5-AS1 chr20 9505180 9514998 +2527456 LAMP5 chr20 9514358 9530524 +2527489 PAK5 chr20 9537389 9839041 +2527569 AL353612.2 chr20 9562941 9571257 +2527573 AL353612.1 chr20 9575608 9577689 +2527577 AL034427.1 chr20 9835556 9873900 +2527582 PARAL1 chr20 9986088 10007116 +2527586 ANKEF1 chr20 9986126 10058303 +2527654 SNAP25-AS1 chr20 10006381 10368776 +2527781 AL354824.1 chr20 10172522 10200824 +2527790 AL354824.2 chr20 10172701 10186740 +2527799 SNAP25 chr20 10218830 10307418 +2527862 AL023913.1 chr20 10317889 10318753 +2527866 MKKS chr20 10401009 10434222 +2527928 AL034430.1 chr20 10413520 10431922 +2527940 AL034430.2 chr20 10420546 10420737 +2527947 SLX4IP chr20 10435305 10636829 +2527980 JAG1 chr20 10637684 10673999 +2528122 AL050403.2 chr20 10672695 10994924 +2528147 LINC01752 chr20 10696949 10754033 +2528157 AL135937.1 chr20 10753278 10765286 +2528162 AL050403.1 chr20 10875333 10909279 +2528313 C20orf187 chr20 10996293 11029455 +2528332 AL158042.1 chr20 11001304 11001763 +2528335 AL049649.1 chr20 11234170 11301525 +2528357 AL109837.2 chr20 11536406 11541647 +2528362 AL109837.3 chr20 11566484 11581335 +2528367 AL161938.1 chr20 11685144 11687323 +2528370 LINC00687 chr20 11800463 11878429 +2528402 BTBD3 chr20 11890723 11926609 +2528562 AL035448.1 chr20 11909404 11918677 +2528567 AL109838.1 chr20 12243308 12318221 +2528575 AL136460.1 chr20 12305613 12316485 +2528579 LINC01722 chr20 12865202 12952519 +2528593 AL078623.1 chr20 12934877 12937097 +2528600 AL133331.1 chr20 12936262 12940902 +2528607 LINC01723 chr20 12950288 13008417 +2528685 SPTLC3 chr20 13008972 13169103 +2528754 ISM1 chr20 13221274 13300651 +2528772 ISM1-AS1 chr20 13237801 13239674 +2528777 AL050320.1 chr20 13244064 13245369 +2528781 AL121782.1 chr20 13368291 13368703 +2528784 TASP1 chr20 13389392 13638932 +2528893 ESF1 chr20 13714322 13784886 +2528954 NDUFAF5 chr20 13785007 13821580 +2529123 SEL1L2 chr20 13849247 13996443 +2529385 MACROD2 chr20 13995369 16053197 +2529593 FLRT3 chr20 14322985 14337614 +2529617 AL121582.1 chr20 14522081 14523314 +2529621 MACROD2-IT1 chr20 14554384 14636524 +2529633 MACROD2-AS1 chr20 14884250 14929528 +2529648 AL138808.1 chr20 14933843 14935363 +2529653 AL121584.1 chr20 15552157 15552885 +2529657 AL079338.1 chr20 15892355 15985876 +2529661 AL161941.1 chr20 16177933 16259603 +2529672 KIF16B chr20 16272104 16573434 +2529867 AL049794.1 chr20 16576068 16579615 +2529871 AL049794.2 chr20 16580258 16580622 +2529874 AL034428.1 chr20 16714844 16730948 +2529884 SNRPB2 chr20 16729961 16742564 +2529927 OTOR chr20 16748358 16770062 +2529949 AL121892.1 chr20 16857962 16864148 +2529954 AL359511.2 chr20 17216779 17221913 +2529959 AL359511.3 chr20 17222851 17226146 +2529963 PCSK2 chr20 17226107 17484578 +2530061 BFSP1 chr20 17493905 17569220 +2530141 AL132765.2 chr20 17565501 17565851 +2530144 DSTN chr20 17570075 17609919 +2530188 RRBP1 chr20 17613678 17682295 +2530572 BANF2 chr20 17693672 17735871 +2530620 AL035045.1 chr20 17887363 17888160 +2530624 SNX5 chr20 17941597 17968980 +2530854 OVOL2 chr20 17956979 18059188 +2530885 MGME1 chr20 17969018 17991122 +2530934 AL160411.1 chr20 18059493 18071008 +2530938 PET117 chr20 18137863 18143169 +2530948 KAT14 chr20 18138118 18188387 +2531038 AL049646.3 chr20 18270630 18271069 +2531042 ZNF133 chr20 18288283 18316996 +2531234 AL049646.1 chr20 18289343 18359300 +2531254 AL049646.2 chr20 18313765 18315111 +2531258 LINC00851 chr20 18379049 18381484 +2531264 DZANK1 chr20 18383367 18467281 +2531638 POLR3F chr20 18467389 18484646 +2531692 RBBP9 chr20 18486540 18497225 +2531717 SEC23B chr20 18507520 18561415 +2532008 SMIM26 chr20 18567347 18569563 +2532036 DTD1 chr20 18587893 18766644 +2532088 AL121900.1 chr20 18674395 18698709 +2532094 LINC00652 chr20 18786065 18794579 +2532135 LINC00653 chr20 18794529 18796067 +2532138 C20orf78 chr20 18809728 18830153 +2532146 SCP2D1 chr20 18813783 18814378 +2532154 AL135936.1 chr20 19000709 19056796 +2532162 AL136090.2 chr20 19208652 19212164 +2532166 SLC24A3 chr20 19212642 19722926 +2532246 AL136090.1 chr20 19212852 19213477 +2532250 AL049647.1 chr20 19242302 19284596 +2532260 AL121830.1 chr20 19693209 19697576 +2532288 AL121761.1 chr20 19756390 19758037 +2532291 RIN2 chr20 19757606 20002459 +2532424 NAA20 chr20 20017310 20033655 +2532498 CRNKL1 chr20 20034368 20056046 +2532680 CFAP61 chr20 20052514 20360698 +2533010 AL035454.1 chr20 20094401 20095684 +2533014 AL049648.1 chr20 20214299 20215262 +2533018 AL121721.1 chr20 20258407 20267809 +2533023 INSM1 chr20 20368104 20370949 +2533031 RALGAPA2 chr20 20389530 20712644 +2533240 AL133465.1 chr20 20970448 20972562 +2533244 LINC00237 chr20 21085576 21106514 +2533274 AL121759.2 chr20 21089696 21092539 +2533287 KIZ chr20 21125983 21246622 +2533528 AL121759.1 chr20 21148741 21162890 +2533541 KIZ-AS1 chr20 21154023 21218289 +2533566 AL117332.1 chr20 21302731 21303704 +2533569 XRN2 chr20 21303331 21389825 +2533635 NKX2-4 chr20 21395365 21397526 +2533645 AL158013.1 chr20 21397740 21400391 +2533656 AL133325.3 chr20 21499261 21502934 +2533659 NKX2-2 chr20 21511017 21514064 +2533669 NKX2-2-AS1 chr20 21511447 21512309 +2533673 AL133325.2 chr20 21530122 21535665 +2533682 LINC01727 chr20 21569976 21666621 +2533782 LINC01726 chr20 21610787 21703585 +2533789 PAX1 chr20 21705659 21718486 +2533841 AL109807.1 chr20 21947647 21970783 +2533845 LINC01432 chr20 22054074 22074654 +2533851 AL035258.1 chr20 22220554 22223283 +2533856 LINC01427 chr20 22263065 22284029 +2533877 AL133464.1 chr20 22371216 22471557 +2533919 LINC00261 chr20 22547671 22578642 +2533938 FOXA2 chr20 22581005 22585455 +2533959 LNCNEF chr20 22587522 22607517 +2533964 LINC01747 chr20 22668480 22685344 +2533988 AL158175.1 chr20 22684958 22746991 +2534014 AL049651.1 chr20 23010209 23030785 +2534020 AL049651.2 chr20 23030863 23039241 +2534029 SSTR4 chr20 23035386 23036812 +2534037 THBD chr20 23045633 23049741 +2534045 CD93 chr20 23079360 23086324 +2534055 LINC00656 chr20 23125068 23132635 +2534070 AL118508.1 chr20 23179272 23190419 +2534374 AL390037.1 chr20 23320958 23325352 +2534380 AL096677.1 chr20 23346941 23351486 +2534384 NXT1 chr20 23350791 23354771 +2534394 LINC01431 chr20 23356594 23358116 +2534406 GZF1 chr20 23362182 23373062 +2534453 NAPB chr20 23374519 23421519 +2534580 CSTL1 chr20 23439685 23444930 +2534622 CST11 chr20 23450403 23452876 +2534643 AL096677.2 chr20 23452623 23461207 +2534653 AL109954.1 chr20 23481645 23519054 +2534659 AL109954.2 chr20 23489416 23489973 +2534662 CST8 chr20 23491101 23496010 +2534687 CST9L chr20 23564732 23568484 +2534699 CST9 chr20 23602410 23605876 +2534709 CST3 chr20 23626706 23638473 +2534747 AL121894.2 chr20 23631826 23632316 +2534750 AL121894.1 chr20 23655225 23656390 +2534754 AL121894.3 chr20 23656151 23674888 +2534780 CST4 chr20 23685640 23689040 +2534792 AL591074.2 chr20 23722589 23745524 +2534803 CST1 chr20 23747553 23751268 +2534828 AL591074.1 chr20 23798092 23805983 +2534847 CST2 chr20 23823769 23826729 +2534859 CST5 chr20 23875934 23879748 +2534871 GGTLC1 chr20 23985050 23988779 +2534921 LINC01721 chr20 24063255 24226013 +2534948 AL110503.1 chr20 24142590 24144386 +2534952 AL158090.1 chr20 24297585 24318086 +2534959 SYNDIG1 chr20 24469629 24666616 +2534976 AL157413.1 chr20 24491472 24502345 +2534981 AL049594.1 chr20 24679547 24680991 +2534985 AL035661.1 chr20 24931840 24932983 +2534988 CST7 chr20 24949269 24959928 +2535002 APMAP chr20 24962925 24992751 +2535049 AL035661.2 chr20 24992312 24993322 +2535052 ACSS1 chr20 25006230 25058980 +2535160 AL080312.2 chr20 25062962 25063591 +2535163 VSX1 chr20 25070885 25082365 +2535253 AL035252.2 chr20 25139652 25149372 +2535298 AL035252.5 chr20 25184658 25187849 +2535303 ENTPD6 chr20 25195693 25228075 +2535637 AL035252.3 chr20 25229150 25231933 +2535640 AL121772.1 chr20 25239007 25245229 +2535644 PYGB chr20 25248085 25298012 +2535707 AL121772.2 chr20 25251008 25251304 +2535710 AL121772.3 chr20 25284915 25285588 +2535713 ABHD12 chr20 25294742 25390835 +2536222 GINS1 chr20 25407673 25452628 +2536255 NINL chr20 25452697 25585531 +2536387 NANP chr20 25612935 25624014 +2536397 ZNF337-AS1 chr20 25624045 25689032 +2536446 ZNF337 chr20 25673195 25696853 +2536481 AL031673.1 chr20 25680781 25681246 +2536484 AL390198.1 chr20 25697003 25752776 +2536498 FAM182B chr20 25762384 25868225 +2536600 LINC01733 chr20 25955795 25969288 +2536606 FAM182A chr20 25985210 26086917 +2536714 AL078587.1 chr20 26008791 26010531 +2536718 AL078587.2 chr20 26009792 26011243 +2536721 AL391119.1 chr20 26132887 26134198 +2536725 AL121904.2 chr20 26135983 26188191 +2536729 MIR663AHG chr20 26167817 26251546 +2537584 AL121904.1 chr20 26188408 26196891 +2537593 FAM242B chr20 29548661 29559705 +2537598 LINC01597 chr20 30278906 30289956 +2537618 AL121762.1 chr20 30281837 30282954 +2537622 AL121762.2 chr20 30294550 30312480 +2537626 FAM242A chr20 30323367 30362276 +2537667 DEFB115 chr20 31257664 31259632 +2537676 DEFB116 chr20 31303212 31308585 +2537685 DEFB118 chr20 31368601 31373923 +2537695 DEFB119 chr20 31377164 31390590 +2537729 DEFB121 chr20 31404845 31412838 +2537742 DEFB123 chr20 31440632 31450257 +2537752 DEFB124 chr20 31465506 31476757 +2537764 REM1 chr20 31475288 31484895 +2537780 LINC00028 chr20 31485778 31487574 +2537786 HM13 chr20 31514410 31577923 +2538172 AL110115.1 chr20 31535263 31535626 +2538175 MCTS2P chr20 31547412 31548081 +2538183 HM13-IT1 chr20 31563166 31564076 +2538187 HM13-AS1 chr20 31567707 31573263 +2538192 AL110115.2 chr20 31580890 31581214 +2538195 ID1 chr20 31605283 31606515 +2538212 COX4I2 chr20 31637912 31645006 +2538232 BCL2L1 chr20 31664452 31723989 +2538308 AL117381.1 chr20 31686216 31716825 +2538312 ABALON chr20 31721507 31723409 +2538315 TPX2 chr20 31739271 31801805 +2538400 MYLK2 chr20 31819308 31834689 +2538468 FOXS1 chr20 31844303 31845604 +2538476 DUSP15 chr20 31847637 31870747 +2538629 TTLL9 chr20 31870702 31944963 +2539038 PDRG1 chr20 31944337 31952046 +2539054 XKR7 chr20 31968151 32003387 +2539066 AL031658.2 chr20 31970181 31970831 +2539069 AL031658.1 chr20 32005671 32031591 +2539087 CCM2L chr20 32010438 32032180 +2539136 HCK chr20 32052188 32101856 +2539453 TM9SF4 chr20 32109714 32167258 +2539590 AL049539.1 chr20 32116171 32116629 +2539593 PLAGL2 chr20 32192504 32207743 +2539605 POFUT1 chr20 32207880 32238658 +2539654 AL121897.1 chr20 32275117 32277510 +2539658 KIF3B chr20 32277651 32335011 +2539682 AL121583.1 chr20 32355053 32355734 +2539685 ASXL1 chr20 32358330 32439319 +2540103 NOL4L chr20 32443059 32585074 +2540262 AL034550.1 chr20 32449755 32453607 +2540268 AL034550.3 chr20 32485149 32487019 +2540272 AL034550.2 chr20 32509959 32520285 +2540277 AL133343.2 chr20 32561093 32573888 +2540282 NOL4L-DT chr20 32564992 32608893 +2540291 AL133343.1 chr20 32581963 32593900 +2540295 C20orf203 chr20 32631625 32673941 +2540324 COMMD7 chr20 32702691 32743997 +2540411 DNMT3B chr20 32762385 32809356 +2540690 MAPRE1 chr20 32819954 32850405 +2540710 AL035071.2 chr20 32843128 32854257 +2540714 AL035071.1 chr20 32856621 32858751 +2540717 EFCAB8 chr20 32858923 32961609 +2540796 SUN5 chr20 32983773 33004433 +2540883 BPIFB2 chr20 33007704 33023703 +2540921 BPIFB6 chr20 33031648 33044047 +2540992 BPIFB3 chr20 33055424 33073628 +2541027 BPIFB4 chr20 33079644 33111751 +2541087 BPIFA2 chr20 33161768 33181412 +2541134 AL121901.1 chr20 33214920 33217067 +2541138 BPIFA3 chr20 33217310 33227806 +2541191 BPIFA1 chr20 33235995 33243311 +2541283 BPIFB1 chr20 33273480 33309871 +2541348 CDK5RAP1 chr20 33358839 33401561 +2541569 SNTA1 chr20 33407955 33443892 +2541591 CBFA2T2 chr20 33490075 33650036 +2541803 AL121906.2 chr20 33655701 33656423 +2541806 NECAB3 chr20 33657087 33674463 +2542134 C20orf144 chr20 33662327 33665619 +2542146 ACTL10 chr20 33666943 33668525 +2542154 AL121906.1 chr20 33674517 33675380 +2542158 E2F1 chr20 33675477 33686385 +2542178 PXMP4 chr20 33702758 33720319 +2542216 AL050349.1 chr20 33728931 33731828 +2542220 ZNF341 chr20 33731657 33792269 +2542361 ZNF341-AS1 chr20 33787373 33811109 +2542375 CHMP4B chr20 33811348 33854366 +2542391 RALY-AS1 chr20 33980679 33994357 +2542417 RALY chr20 33993646 34108308 +2542547 AL031668.1 chr20 34014969 34017749 +2542552 EIF2S2 chr20 34088309 34112243 +2542576 AL031668.2 chr20 34132270 34136485 +2542580 ASIP chr20 34194569 34269344 +2542605 AL035458.2 chr20 34234840 34281173 +2542610 AHCY chr20 34280268 34311802 +2542684 AL356299.2 chr20 34281632 34286466 +2542688 ITCH chr20 34363241 34540748 +2543233 ITCH-AS1 chr20 34441592 34442025 +2543237 ITCH-IT1 chr20 34450930 34454552 +2543241 AL109923.1 chr20 34476205 34476787 +2543244 DYNLRB1 chr20 34516409 34540958 +2543288 MAP1LC3A chr20 34546854 34560345 +2543336 PIGU chr20 34560542 34698790 +2543422 NCOA6 chr20 34689097 34825651 +2543584 TP53INP2 chr20 34704339 34713439 +2543633 AL109824.1 chr20 34741401 34807447 +2543638 GGT7 chr20 34844720 34872856 +2543709 ACSS2 chr20 34872146 34927962 +2544025 GSS chr20 34928432 34956027 +2544497 MYH7B chr20 34975403 35002437 +2544736 TRPC4AP chr20 35002404 35092807 +2544823 EDEM2 chr20 35115364 35147336 +2544876 PROCR chr20 35172072 35216240 +2544908 AL356652.1 chr20 35174355 35174919 +2544911 MMP24OS chr20 35201745 35278131 +2544979 MMP24 chr20 35226690 35276998 +2545003 EIF6 chr20 35278911 35284985 +2545115 FAM83C-AS1 chr20 35285251 35285756 +2545119 FAM83C chr20 35285731 35292425 +2545133 UQCC1 chr20 35302566 35412031 +2545485 GDF5OS chr20 35433029 35435450 +2545498 GDF5 chr20 35433347 35454746 +2545521 CEP250 chr20 35455164 35519280 +2545779 FO393401.1 chr20 35476203 35490982 +2545791 C20orf173 chr20 35523186 35529652 +2545850 ERGIC3 chr20 35542021 35557634 +2546109 SPAG4 chr20 35615829 35621094 +2546195 CPNE1 chr20 35626031 35664956 +2546712 RBM12 chr20 35648925 35664956 +2546771 NFS1 chr20 35668052 35699355 +2547014 ROMO1 chr20 35699272 35700984 +2547064 RBM39 chr20 35701347 35742312 +2547828 PHF20 chr20 35771974 35950370 +2548008 SCAND1 chr20 35953617 35959472 +2548040 CNBD2 chr20 35954564 36030700 +2548175 NORAD chr20 36045618 36051018 +2548178 AL035420.1 chr20 36051491 36085703 +2548211 AL035420.3 chr20 36064243 36064563 +2548214 AL035420.2 chr20 36086252 36088192 +2548218 EPB41L1 chr20 36091504 36232799 +2548753 AL121895.1 chr20 36147334 36155760 +2548770 AL121895.2 chr20 36233851 36234297 +2548773 AAR2 chr20 36236459 36270918 +2548813 DLGAP4 chr20 36306336 36528637 +2549052 DLGAP4-AS1 chr20 36507702 36573391 +2549081 MYL9 chr20 36541497 36551447 +2549106 TGIF2 chr20 36573488 36593950 +2549194 RAB5IF chr20 36605779 36612557 +2549286 SLA2 chr20 36612318 36646196 +2549329 NDRG3 chr20 36651766 36746090 +2549489 DSN1 chr20 36751791 36773818 +2549688 SOGA1 chr20 36777447 36863538 +2549789 TLDC2 chr20 36876121 36894235 +2549833 SAMHD1 chr20 36889773 36951901 +2550432 RBL1 chr20 36996349 37095997 +2550557 AL136172.1 chr20 37095785 37097178 +2550560 MROH8 chr20 37101226 37179588 +2550791 RPN2 chr20 37178410 37241619 +2550952 GHRH chr20 37251082 37261835 +2550993 MANBAL chr20 37289638 37317260 +2551059 AL034422.1 chr20 37338886 37344109 +2551063 SRC chr20 37344685 37406050 +2551215 BLCAP chr20 37492472 37527931 +2551318 NNAT chr20 37521206 37523690 +2551370 AL109614.1 chr20 37526642 37527060 +2551373 LINC01746 chr20 37571103 37591493 +2551385 LINC00489 chr20 37619298 37623119 +2551390 AL162293.1 chr20 37676889 37683234 +2551401 CTNNBL1 chr20 37693955 37872129 +2551654 VSTM2L chr20 37903111 37945350 +2551686 TTI1 chr20 37983007 38033461 +2551764 RPRD1B chr20 38033725 38127780 +2551850 AL031651.1 chr20 38103524 38104961 +2551853 TGM2 chr20 38127385 38166578 +2551937 KIAA1755 chr20 38210503 38260772 +2552025 AL031651.2 chr20 38233251 38233799 +2552028 AL359555.4 chr20 38260175 38293892 +2552036 AL359555.2 chr20 38270778 38274020 +2552039 AL359555.1 chr20 38288331 38326536 +2552044 BPI chr20 38304123 38337505 +2552173 LBP chr20 38346482 38377013 +2552209 AL391095.2 chr20 38378825 38383179 +2552213 AL391095.1 chr20 38404893 38416797 +2552218 AL391095.3 chr20 38418483 38419202 +2552221 SNHG17 chr20 38419638 38435409 +2552836 SNHG11 chr20 38446343 38450940 +2553041 RALGAPB chr20 38472816 38578859 +2553364 ADIG chr20 38581195 38588463 +2553407 ARHGAP40 chr20 38601934 38651035 +2553498 SLC32A1 chr20 38724486 38729372 +2553508 ACTR5 chr20 38748460 38772520 +2553532 PPP1R16B chr20 38805697 38923024 +2553594 FAM83D chr20 38926312 38953106 +2553621 AL023803.2 chr20 38955910 38956547 +2553624 AL023803.1 chr20 38961925 38962111 +2553627 DHX35 chr20 38962299 39039723 +2553894 AL023803.3 chr20 38962472 38962993 +2553897 LINC01734 chr20 39213777 39224748 +2553903 AL035251.1 chr20 39231115 39233836 +2553907 AL132981.1 chr20 39655325 39663552 +2553912 AL118523.1 chr20 39757202 39815097 +2553927 LINC01370 chr20 40004216 40011323 +2553973 AL133419.1 chr20 40031585 40043889 +2553978 AL009050.1 chr20 40121041 40126357 +2553983 MAFB chr20 40685848 40689236 +2553991 AL035665.1 chr20 40696499 40698616 +2553995 AL035665.2 chr20 40717257 40758636 +2553999 TOP1 chr20 41028822 41124487 +2554047 PLCG1-AS1 chr20 41098019 41138003 +2554084 PLCG1 chr20 41136960 41196801 +2554386 ZHX3 chr20 41178448 41317672 +2554588 LPIN3 chr20 41340920 41360582 +2554709 EMILIN3 chr20 41359962 41366818 +2554723 CHD6 chr20 41402083 41618384 +2554916 AL031667.3 chr20 41485571 41486225 +2554919 AL049812.2 chr20 41991140 42063969 +2554923 AL049812.3 chr20 42014034 42015478 +2554928 PTPRT chr20 42072752 43189970 +2555582 AL031656.1 chr20 42685404 42688562 +2555592 AL031676.1 chr20 42968743 42971492 +2555596 AL021395.1 chr20 43189998 43202599 +2555611 SRSF6 chr20 43457893 43466046 +2555708 L3MBTL1 chr20 43489442 43550950 +2556550 Z98752.1 chr20 43549389 43550949 +2556554 SGK2 chr20 43558968 43588237 +2556853 Z98752.4 chr20 43590009 43590596 +2556856 IFT52 chr20 43590937 43647299 +2556954 MYBL2 chr20 43667019 43716495 +2557019 GTSF1L chr20 43726164 43727002 +2557036 LINC01728 chr20 43894720 43895468 +2557040 TOX2 chr20 43914852 44069616 +2557150 JPH2 chr20 44111695 44187578 +2557177 AL035447.1 chr20 44181111 44182712 +2557181 OSER1 chr20 44195939 44210771 +2557212 OSER1-DT chr20 44210907 44226027 +2557262 GDAP1L1 chr20 44247099 44280917 +2557375 FITM2 chr20 44302840 44311202 +2557385 R3HDML chr20 44336986 44351242 +2557401 AL117382.1 chr20 44347552 44355185 +2557410 HNF4A chr20 44355700 44434596 +2557618 HNF4A-AS1 chr20 44372746 44395706 +2557627 AL117382.2 chr20 44389624 44391537 +2557631 LINC01620 chr20 44436172 44465349 +2557652 TTPAL chr20 44475874 44494603 +2557712 SERINC3 chr20 44496221 44522085 +2557782 PKIG chr20 44531785 44624247 +2557886 ADA chr20 44619522 44652233 +2558026 LINC01260 chr20 44656451 44663498 +2558032 KCNK15-AS1 chr20 44694892 44746021 +2558051 CCN5 chr20 44714844 44728509 +2558101 KCNK15 chr20 44745865 44752313 +2558111 AL118522.1 chr20 44746642 44747201 +2558114 RIMS4 chr20 44751808 44810338 +2558148 AL008725.1 chr20 44864435 44885604 +2558152 YWHAB chr20 44885702 44908532 +2558247 PABPC1L chr20 44910062 44959035 +2558506 TOMM34 chr20 44942130 44960397 +2558526 STK4-AS1 chr20 44963794 44966402 +2558535 STK4 chr20 44966479 45080021 +2558653 KCNS1 chr20 45091214 45101127 +2558682 WFDC5 chr20 45109452 45115172 +2558709 WFDC12 chr20 45123425 45124465 +2558721 PI3 chr20 45174902 45176544 +2558733 SEMG1 chr20 45207033 45209768 +2558745 SEMG2 chr20 45221373 45224458 +2558757 SLPI chr20 45252239 45254564 +2558771 MATN4 chr20 45293445 45308529 +2558891 RBPJL chr20 45306840 45317824 +2558996 SDC4 chr20 45325288 45348424 +2559012 AL021578.1 chr20 45345115 45345823 +2559015 SYS1 chr20 45361937 45376798 +2559102 TP53TG5 chr20 45372557 45407889 +2559134 DBNDD2 chr20 45406057 45410610 +2559246 PIGT chr20 45416084 45456934 +2560670 AL031663.3 chr20 45435272 45448325 +2560674 WFDC2 chr20 45469753 45481532 +2560742 AL031663.2 chr20 45487613 45490248 +2560746 SPINT3 chr20 45512461 45515622 +2560756 WFDC6 chr20 45534196 45539495 +2560776 EPPIN chr20 45540626 45547752 +2560817 WFDC8 chr20 45551153 45579326 +2560854 WFDC9 chr20 45607939 45631284 +2560870 WFDC10A chr20 45629739 45631196 +2560880 WFDC11 chr20 45648563 45670270 +2560924 WFDC10B chr20 45684653 45705019 +2560949 WFDC13 chr20 45702038 45708817 +2560963 SPINT4 chr20 45722347 45725830 +2560975 WFDC3 chr20 45747944 45791932 +2561082 DNTTIP1 chr20 45791954 45811427 +2561196 UBE2C chr20 45812576 45816957 +2561311 TNNC2 chr20 45823214 45833745 +2561348 SNX21 chr20 45833799 45843276 +2561461 ACOT8 chr20 45841721 45857405 +2561610 ZSWIM3 chr20 45857614 45879122 +2561620 ZSWIM1 chr20 45881227 45885266 +2561641 SPATA25 chr20 45886489 45887635 +2561651 NEURL2 chr20 45888625 45891287 +2561668 CTSA chr20 45890144 45898820 +2561963 AL008726.1 chr20 45892694 45893419 +2561967 PLTP chr20 45898621 45912155 +2562141 AL162458.1 chr20 45926518 45935055 +2562144 PCIF1 chr20 45934683 45948023 +2562202 ZNF335 chr20 45948660 45972203 +2562276 MMP9 chr20 46008908 46016561 +2562308 SLC12A5-AS1 chr20 46013500 46022073 +2562316 SLC12A5 chr20 46021690 46060152 +2562703 NCOA5 chr20 46060991 46089962 +2562736 CD40 chr20 46118278 46129863 +2562843 AL031687.1 chr20 46168404 46171237 +2562847 CDH22 chr20 46173739 46308498 +2562883 SLC35C2 chr20 46345980 46364458 +2563073 AL133227.1 chr20 46364551 46397994 +2563084 ELMO2 chr20 46366050 46432985 +2563446 ZNF334 chr20 46499630 46513559 +2563530 OCSTAMP chr20 46540946 46550654 +2563542 SLC13A3 chr20 46557823 46684467 +2563786 AL133520.1 chr20 46681676 46682375 +2563789 TP53RK chr20 46684365 46689444 +2563808 AL031055.1 chr20 46689659 46690289 +2563811 SLC2A10 chr20 46709649 46736347 +2563839 EYA2 chr20 46894624 47188844 +2564040 AL354766.2 chr20 46901143 46901726 +2564044 ZMYND8 chr20 47209214 47356889 +2564920 AL031666.2 chr20 47318502 47320754 +2564923 AL031666.3 chr20 47348137 47349142 +2564926 AL031666.1 chr20 47352561 47354633 +2564930 LINC01754 chr20 47391925 47412327 +2564940 NCOA3 chr20 47501887 47656877 +2565102 SULF2 chr20 47656348 47786616 +2565299 AL354813.1 chr20 47677901 47686297 +2565305 AL357558.2 chr20 47950797 47954808 +2565321 AL357558.1 chr20 47958022 47958603 +2565325 AL357558.3 chr20 47974137 47977584 +2565329 LINC01522 chr20 47979102 47990127 +2565344 LINC01523 chr20 47983404 47984313 +2565348 AL139351.2 chr20 48007875 48022237 +2565355 AL139351.3 chr20 48025245 48060271 +2565359 AL139351.1 chr20 48073869 48074188 +2565362 AL136102.1 chr20 48120269 48136844 +2565368 AL121888.2 chr20 48264969 48275392 +2565372 AL121888.1 chr20 48324812 48367976 +2565377 LINC00494 chr20 48359884 48370636 +2565442 AL137078.1 chr20 48383323 48384895 +2565446 AL137078.2 chr20 48406777 48410716 +2565459 AL049541.1 chr20 48471308 48472414 +2565463 AL049541.2 chr20 48476999 48477553 +2565466 PREX1 chr20 48624252 48827999 +2565607 AL035106.1 chr20 48657073 48659119 +2565611 AL133342.1 chr20 48821688 48849458 +2565615 ARFGEF2 chr20 48921711 49036693 +2565702 CSE1L-AS1 chr20 49040463 49046168 +2565714 CSE1L chr20 49046246 49096960 +2565830 STAU1 chr20 49113339 49188367 +2566111 DDX27 chr20 49219295 49244077 +2566317 ZNFX1 chr20 49237946 49278426 +2566459 ZFAS1 chr20 49278178 49299600 +2566525 KCNB1 chr20 49293394 49484297 +2566577 PTGIS chr20 49503874 49568137 +2566613 B4GALT5 chr20 49632945 49713878 +2566637 SLC9A8 chr20 49812713 49892242 +2566718 SPATA2 chr20 49903391 49915529 +2566741 RNF114 chr20 49936336 49953885 +2566842 SNAI1 chr20 49982980 49988886 +2566854 TRERNA1 chr20 50040716 50041504 +2566858 UBE2V1 chr20 50081124 50115959 +2567057 TMEM189 chr20 50118254 50153734 +2567141 LINC01275 chr20 50162765 50166216 +2567161 AL161937.1 chr20 50166362 50171742 +2567168 LINC01273 chr20 50171809 50176676 +2567201 CEBPB-AS1 chr20 50184598 50191498 +2567209 CEBPB chr20 50190830 50192668 +2567217 SMIM25 chr20 50247643 50283250 +2567265 LINC01270 chr20 50292709 50315488 +2567339 LINC01271 chr20 50310711 50321342 +2567344 PTPN1 chr20 50510321 50585241 +2567393 AL133230.1 chr20 50570975 50578041 +2567397 RIPOR3 chr20 50586108 50691542 +2567527 AL353653.1 chr20 50645471 50662275 +2567537 PARD6B chr20 50731580 50756795 +2567560 BCAS4 chr20 50794894 50882676 +2567642 ADNP chr20 50888916 50931437 +2567743 ADNP-AS1 chr20 50930984 50945148 +2567762 DPM1 chr20 50934867 50958555 +2567871 MOCS3 chr20 50958818 50963929 +2567879 AL050404.1 chr20 50999370 51010019 +2567884 KCNG1 chr20 51003656 51023107 +2567937 NFATC2 chr20 51386957 51562831 +2568098 ATP9A chr20 51596514 51768390 +2568215 SALL4 chr20 51782331 51802521 +2568261 LINC01429 chr20 51831797 51862912 +2568266 ZFP64 chr20 52051663 52204308 +2568432 AL109984.1 chr20 52072685 52096480 +2568437 LINC01524 chr20 52192159 52670578 +2568671 AL109610.1 chr20 52451464 52455619 +2568676 AL049765.1 chr20 52487922 52500591 +2568680 AL031674.1 chr20 52671735 52699472 +2568884 AL161945.1 chr20 52840936 52843775 +2568888 AL121902.1 chr20 52858338 52862855 +2568892 TSHZ2 chr20 52972358 53495330 +2568937 AL391097.3 chr20 53137293 53141169 +2568941 AL391097.1 chr20 53168643 53179550 +2568945 AL391097.2 chr20 53196229 53208705 +2568952 AL109930.1 chr20 53255979 53487274 +2568957 AL354993.1 chr20 53397661 53412910 +2568962 AL354993.2 chr20 53453058 53504314 +2568968 AL157838.1 chr20 53552770 53575863 +2568976 ZNF217 chr20 53567065 53609907 +2569030 AC005808.1 chr20 53608354 53634590 +2569035 AC005914.1 chr20 53738728 53741797 +2569039 AC006076.1 chr20 53799823 53827297 +2569047 BCAS1 chr20 53936777 54070594 +2569140 AC005220.1 chr20 53940160 53942508 +2569145 CYP24A1 chr20 54153446 54173986 +2569236 AL133335.2 chr20 54178414 54183129 +2569240 PFDN4 chr20 54208087 54228052 +2569285 AL133335.1 chr20 54232758 54269542 +2569290 DOK5 chr20 54475593 54651169 +2569339 LINC01440 chr20 55408898 55684915 +2569430 LINC01441 chr20 55420336 55427197 +2569435 AL160413.1 chr20 55504906 55505215 +2569438 AL109829.1 chr20 55607852 55744938 +2569445 AL109828.1 chr20 55775176 55781231 +2569455 CBLN4 chr20 55997357 56005519 +2569467 MC3R chr20 56248732 56249815 +2569475 AL139824.1 chr20 56295967 56299160 +2569479 FAM210B chr20 56358974 56368663 +2569498 AURKA chr20 56369389 56392337 +2569766 CSTF1 chr20 56392371 56406362 +2569857 CASS4 chr20 56412112 56460387 +2569898 RTF2 chr20 56468585 56519449 +2570017 GCNT7 chr20 56491492 56525925 +2570049 FAM209A chr20 56517187 56526152 +2570064 FAM209B chr20 56533246 56536520 +2570074 AL109806.2 chr20 56550605 56555579 +2570078 LINC01716 chr20 56577563 56598621 +2570089 TFAP2C chr20 56629306 56639283 +2570116 AL133232.1 chr20 56730397 56731460 +2570120 AL157414.2 chr20 57105741 57107128 +2570125 AL157414.1 chr20 57110640 57122745 +2570134 AL157414.4 chr20 57116566 57119543 +2570138 BMP7 chr20 57168753 57266641 +2570228 BMP7-AS1 chr20 57214872 57215866 +2570232 AL122058.1 chr20 57266797 57282998 +2570240 SPO11 chr20 57329803 57343994 +2570368 RAE1 chr20 57351223 57379211 +2570557 MTRNR2L3 chr20 57358447 57359498 +2570565 AL109955.1 chr20 57377140 57393062 +2570573 RBM38 chr20 57391396 57409333 +2570641 AL109955.2 chr20 57442742 57458298 +2570646 CTCFL chr20 57495966 57525652 +2571103 PCK1 chr20 57561080 57568121 +2571147 AL035541.1 chr20 57599695 57601200 +2571151 ZBP1 chr20 57603846 57620576 +2571239 PMEPA1 chr20 57648392 57711536 +2571332 NKILA chr20 57710156 57712780 +2571338 AL354984.1 chr20 57957126 57960176 +2571346 LINC01742 chr20 58003904 58004648 +2571350 AL354984.2 chr20 58069054 58072070 +2571357 C20orf85 chr20 58150902 58161150 +2571371 ANKRD60 chr20 58218495 58228653 +2571384 RAB22A chr20 58309715 58367507 +2571409 VAPB chr20 58389122 58451101 +2571468 APCDD1L chr20 58459101 58515399 +2571496 APCDD1L-DT chr20 58515379 58619888 +2571544 AL050327.1 chr20 58594417 58603973 +2571548 LINC01711 chr20 58634772 58635738 +2571551 STX16 chr20 58651253 58679526 +2571896 NPEPL1 chr20 58689131 58719238 +2572038 AL139349.1 chr20 58710795 58711633 +2572042 AL132655.3 chr20 58754351 58756838 +2572047 AL132655.2 chr20 58817132 58817725 +2572050 GNAS-AS1 chr20 58818919 58850903 +2572069 AL132655.1 chr20 58833809 58836529 +2572073 GNAS chr20 58839718 58911192 +2573161 AL121917.1 chr20 58863528 58888809 +2573179 AL121917.2 chr20 58876592 58876981 +2573182 AL109840.2 chr20 58916000 58981169 +2573189 NELFCD chr20 58981208 58995133 +2573364 CTSZ chr20 58995185 59007254 +2573395 TUBB1 chr20 59019254 59026654 +2573409 ATP5F1E chr20 59025475 59032345 +2573441 PRELID3B chr20 59033145 59042809 +2573494 ZNF831 chr20 59123381 59259113 +2573533 EDN3 chr20 59300443 59325992 +2573640 AL035250.1 chr20 59352195 59357774 +2573644 AL035250.2 chr20 59360927 59364773 +2573648 AL160410.1 chr20 59395496 59397109 +2573652 AL389889.2 chr20 59467755 59469853 +2573656 AL389889.1 chr20 59515191 59516039 +2573660 PHACTR3 chr20 59577509 59847711 +2573873 AL121908.1 chr20 59624904 59628295 +2573886 SYCP2 chr20 59863564 59933655 +2574199 FAM217B chr20 59933764 59948680 +2574242 PPP1R3D chr20 59936663 59940305 +2574250 CDH26 chr20 59958423 60034011 +2574368 C20orf197 chr20 60055853 60072956 +2574381 AL132822.1 chr20 60083360 60083872 +2574384 MIR646HG chr20 60087826 60653784 +2574842 AL117372.1 chr20 60755001 60767279 +2574858 AL139348.1 chr20 60812004 60814211 +2574861 AL121910.1 chr20 61077224 61077816 +2574865 LINC01718 chr20 61079049 61083750 +2574873 CDH4 chr20 61252261 61940617 +2574981 AL365229.1 chr20 61267525 61271827 +2574985 BX640515.1 chr20 61369879 61370855 +2574988 AL160412.1 chr20 61432868 61437630 +2575025 AL162457.1 chr20 61717506 61719748 +2575029 AL162457.2 chr20 61738219 61755056 +2575037 TAF4 chr20 61953469 62065810 +2575122 AL137077.2 chr20 62066830 62068437 +2575125 LSM14B chr20 62122461 62135374 +2575209 PSMA7 chr20 62136733 62143440 +2575285 SS18L1 chr20 62143769 62182514 +2575369 MTG2 chr20 62183029 62203568 +2575454 HRH3 chr20 62214960 62220278 +2575494 OSBPL2 chr20 62231922 62296213 +2576141 ADRM1 chr20 62302093 62308862 +2576230 AL354836.1 chr20 62305432 62306325 +2576234 LAMA5 chr20 62307955 62367312 +2576497 LAMA5-AS1 chr20 62352995 62356480 +2576512 AL121832.2 chr20 62386303 62386970 +2576515 RPS21 chr20 62387103 62388520 +2576572 CABLES2 chr20 62388632 62407285 +2576613 AL121832.3 chr20 62402236 62405935 +2576616 RBBP8NL chr20 62410237 62427539 +2576650 AL121832.1 chr20 62427827 62447677 +2576666 GATA5 chr20 62463497 62475995 +2576686 AL499627.2 chr20 62477870 62478594 +2576689 AL499627.1 chr20 62513909 62516096 +2576692 MIR1-1HG-AS1 chr20 62544343 62551526 +2576718 MIR1-1HG chr20 62550453 62570764 +2576727 BX640514.1 chr20 62575590 62577507 +2576730 BX640514.2 chr20 62596732 62603355 +2576740 AL450469.2 chr20 62633681 62635504 +2576746 AL450469.1 chr20 62633772 62635862 +2576750 AL357033.1 chr20 62640719 62643304 +2576754 SLCO4A1 chr20 62642503 62685785 +2576875 AL357033.4 chr20 62648961 62650767 +2576878 AL357033.3 chr20 62651272 62652186 +2576882 SLCO4A1-AS1 chr20 62663019 62666724 +2576894 LINC00686 chr20 62695024 62700480 +2576898 NTSR1 chr20 62708836 62762771 +2576916 AL357033.2 chr20 62732566 62735347 +2576920 LINC00659 chr20 62774121 62776996 +2576952 MRGBP chr20 62796473 62801729 +2576968 OGFR-AS1 chr20 62800627 62805587 +2576973 OGFR chr20 62804835 62814000 +2577050 COL9A3 chr20 62816244 62841159 +2577234 TCFL5 chr20 62841005 62861822 +2577269 DIDO1 chr20 62877738 62937952 +2577447 AL117379.1 chr20 62928621 62929297 +2577450 GID8 chr20 62938147 62948475 +2577469 SLC17A9 chr20 62952707 62969585 +2577575 BHLHE23 chr20 63005927 63007035 +2577590 LINC01749 chr20 63009383 63085071 +2577599 LINC00029 chr20 63034217 63037028 +2577612 LINC01056 chr20 63038011 63053863 +2577620 HAR1B chr20 63090806 63102631 +2577649 HAR1A chr20 63102205 63104386 +2577653 AL096828.6 chr20 63116218 63117205 +2577657 AL096828.2 chr20 63127495 63129459 +2577660 AL096828.5 chr20 63144311 63152087 +2577665 AL096828.1 chr20 63166797 63180903 +2577669 YTHDF1 chr20 63195429 63216139 +2577698 AL096828.3 chr20 63218041 63218502 +2577701 BIRC7 chr20 63235883 63240495 +2577753 NKAIN4 chr20 63240784 63272694 +2577848 AL121827.2 chr20 63253978 63261615 +2577851 ARFGAP1 chr20 63272785 63289790 +2578242 COL20A1 chr20 63293186 63334851 +2578500 CHRNA4 chr20 63343223 63378401 +2578626 AL121827.1 chr20 63359988 63371177 +2578637 KCNQ2 chr20 63400210 63472677 +2579195 AL353658.2 chr20 63422269 63424555 +2579200 AL353658.1 chr20 63448051 63449329 +2579204 EEF1A2 chr20 63488014 63499185 +2579286 AL121829.1 chr20 63502287 63505111 +2579290 PPDPF chr20 63520765 63522206 +2579322 PTK6 chr20 63528001 63537376 +2579363 SRMS chr20 63540810 63547504 +2579385 AL121829.2 chr20 63543411 63543738 +2579388 FNDC11 chr20 63547891 63556695 +2579421 HELZ2 chr20 63558086 63574239 +2579517 GMEB2 chr20 63587602 63627101 +2579587 MHENCR chr20 63627227 63628824 +2579594 STMN3 chr20 63639705 63657682 +2579656 RTEL1 chr20 63657810 63696253 +2580141 TNFRSF6B chr20 63696652 63698684 +2580153 ARFRP1 chr20 63698642 63708025 +2580333 ZGPAT chr20 63707465 63736142 +2580460 AL121845.4 chr20 63730072 63730377 +2580463 LIME1 chr20 63736283 63739103 +2580566 SLC2A4RG chr20 63739776 63744050 +2580620 ZBTB46 chr20 63743666 63832038 +2580691 AL121845.1 chr20 63744689 63745958 +2580698 ZBTB46-AS1 chr20 63808076 63816521 +2580703 AL118506.1 chr20 63861212 63864293 +2580706 ABHD16B chr20 63861498 63862988 +2580714 TPD52L2 chr20 63865228 63891545 +2580887 DNAJC5 chr20 63895126 63936031 +2580920 UCKL1 chr20 63939829 63956416 +2581058 UCKL1-AS1 chr20 63953384 63956985 +2581061 ZNF512B chr20 63956704 63969930 +2581101 SAMD10 chr20 63974116 63980008 +2581139 PRPF6 chr20 63981132 64033100 +2581187 C20orf204 chr20 64034344 64039962 +2581220 SOX18 chr20 64047582 64049639 +2581230 TCEA2 chr20 64049836 64072347 +2581428 AL355803.1 chr20 64056803 64057084 +2581432 RGS19 chr20 64073181 64079988 +2581475 OPRL1 chr20 64080082 64100643 +2581534 LKAAEAR1 chr20 64083380 64084359 +2581555 AL121581.2 chr20 64097208 64101162 +2581559 MYT1 chr20 64102394 64242253 +2581837 NPBWR2 chr20 64105820 64107171 +2581845 PCMTD2 chr20 64255695 64287821 +2581957 LINC00266-1 chr20 64290385 64313132 +2581970 FP565260.4 chr21 5011799 5017145 +2581982 FP565260.3 chr21 5022493 5040666 +2582074 FP565260.5 chr21 5073458 5087867 +2582078 GATD3B chr21 5079294 5128413 +2582204 FP565260.1 chr21 5130871 5154658 +2582311 FP565260.6 chr21 5155499 5165472 +2582325 AC079801.1 chr21 5232668 5243833 +2582329 LINC01670 chr21 5499151 5502542 +2582341 CU633967.1 chr21 5553637 5614880 +2582395 FP236315.3 chr21 5705345 5707160 +2582399 FP236315.1 chr21 5707004 5709456 +2582403 CU639417.1 chr21 5972924 5973383 +2582411 LINC01669 chr21 6060340 6076305 +2582432 CU639417.4 chr21 6081193 6082585 +2582436 CU639417.5 chr21 6084364 6091407 +2582446 SIK1B chr21 6111131 6123778 +2582484 CU633906.5 chr21 6215291 6217681 +2582487 CU633906.1 chr21 6228966 6267317 +2582516 CU633906.2 chr21 6318434 6360415 +2582540 CBSL chr21 6444869 6468040 +2582778 U2AF1L5 chr21 6484623 6499261 +2582934 FP236240.1 chr21 6550749 6553955 +2582939 CRYAA2 chr21 6560714 6564489 +2582976 CU638689.4 chr21 6630182 6670695 +2583010 CU638689.1 chr21 6667304 6670667 +2583018 CU638689.5 chr21 6721812 6725209 +2583023 FP475955.3 chr21 6789592 6812297 +2583028 FP475955.1 chr21 6858539 6897263 +2583033 FP475955.2 chr21 6904884 6906692 +2583037 CU634019.5 chr21 6986450 6997765 +2583056 CU634019.2 chr21 7020599 7025166 +2583060 CU634019.1 chr21 7048891 7087229 +2583086 CU633904.1 chr21 7430659 7469007 +2583117 FP236241.1 chr21 7669397 7681742 +2583147 SMIM11B chr21 7744962 7777853 +2583231 FAM243B chr21 7768884 7770591 +2583239 SMIM34B chr21 7784482 7793954 +2583263 KCNE1B chr21 7816675 7829926 +2583304 FP671120.4 chr21 8197620 8227646 +2583313 FP671120.6 chr21 8210384 8211306 +2583316 FP671120.7 chr21 8254592 8255514 +2583319 FP236383.3 chr21 8380643 8454792 +2583346 FP236383.4 chr21 8393419 8394341 +2583349 FP236383.5 chr21 8437629 8438551 +2583352 LINC01666 chr21 8759077 8761335 +2583359 CR381670.2 chr21 8762386 8836565 +2583364 CR392039.4 chr21 8996496 9018670 +2583368 CR381653.1 chr21 9325013 9368775 +2583398 AC124864.3 chr21 9634244 9679906 +2583404 AC018692.1 chr21 9913117 9914846 +2583412 CR382287.2 chr21 10122273 10129029 +2583416 AP003900.1 chr21 10328411 10342737 +2583429 TPTE chr21 10521553 10606140 +2583649 IGHV1OR21-1 chr21 10649400 10649835 +2583656 AP001464.1 chr21 12999676 13016692 +2583660 AJ239318.1 chr21 13305152 13314944 +2583664 LINC01674 chr21 13516107 13574999 +2583689 POTED chr21 13609858 13641585 +2583738 AL050303.1 chr21 13769932 13771740 +2583742 AP001347.1 chr21 14027419 14144468 +2583759 LIPI chr21 14108813 14210891 +2583842 RBM11 chr21 14216130 14228372 +2583882 HSPA13 chr21 14371115 14383484 +2583902 SAMSN1 chr21 14485228 14658821 +2584061 SAMSN1-AS1 chr21 14582202 14598303 +2584068 AF127936.2 chr21 14728396 14753925 +2584110 AF127936.1 chr21 14761710 14763090 +2584114 LINC02246 chr21 14819699 14918552 +2584145 AF127577.3 chr21 14918534 14947096 +2584149 NRIP1 chr21 14961235 15065936 +2584211 AF127577.1 chr21 14961309 14964233 +2584215 AF127577.2 chr21 14971470 14992854 +2584220 AF127577.5 chr21 15067070 15067837 +2584224 AJ009632.2 chr21 15368966 15627342 +2584392 AJ009632.1 chr21 15493932 15496124 +2584396 USP25 chr21 15730025 15880069 +2584637 MIR99AHG chr21 15928296 16645467 +2585553 AP001172.1 chr21 16291079 16310382 +2585562 AP001172.2 chr21 16417139 16419080 +2585567 AP000962.3 chr21 16505555 16507916 +2585571 AP000962.1 chr21 16574718 16582637 +2585575 AF130359.1 chr21 16754519 16815688 +2585580 AF212831.1 chr21 16862875 16873691 +2585586 LINC01549 chr21 17438821 17450104 +2585596 CXADR chr21 17513043 17593579 +2585673 BTG3 chr21 17593653 17612947 +2585724 BTG3-AS1 chr21 17611744 17633199 +2585731 AP000432.1 chr21 17659276 17660384 +2585735 C21orf91-OT1 chr21 17763315 17792523 +2585751 C21orf91 chr21 17788974 17819386 +2585816 AL109761.1 chr21 17793488 17810845 +2585823 CHODL-AS1 chr21 17835016 17885608 +2585828 CHODL chr21 17901263 18267373 +2585946 AF130417.1 chr21 18022370 18114904 +2585953 TMPRSS15 chr21 18269116 18485879 +2586039 AL109763.1 chr21 18477358 18486599 +2586043 MIR548XHG chr21 18561265 18760320 +2586073 AF240627.1 chr21 18614431 18650360 +2586078 AL157359.2 chr21 18917934 18935859 +2586082 AL157359.1 chr21 18953264 18967058 +2586086 AP000431.2 chr21 19046310 19047684 +2586090 AP000431.1 chr21 19130523 19134423 +2586094 AP000855.1 chr21 19301613 19303739 +2586098 LINC01683 chr21 19893113 19900043 +2586107 LINC02573 chr21 20256752 20258820 +2586111 LINC00320 chr21 20651450 20803816 +2586761 NCAM2 chr21 20998409 21543329 +2586857 AP001136.1 chr21 21223295 21226829 +2586861 AP001117.1 chr21 21566763 21615437 +2586865 AF241725.1 chr21 21655038 21686329 +2586872 LINC00317 chr21 21723293 21737319 +2586877 LINC01425 chr21 21746973 21797415 +2586889 AP000472.1 chr21 21933315 21975681 +2586894 LINC01687 chr21 22008756 22098518 +2586941 LINC00308 chr21 22098616 22116605 +2586954 AP000561.1 chr21 22209920 22420819 +2586973 AP000959.1 chr21 22500604 22520058 +2586978 AP001116.1 chr21 23065491 23131206 +2586985 AP001255.1 chr21 23106928 23119903 +2586990 AP000459.2 chr21 23352929 23423778 +2587042 AP000459.1 chr21 23477641 23490724 +2587046 AP000961.1 chr21 23704260 23709345 +2587051 AP000474.2 chr21 23857081 23889150 +2587057 AP000474.1 chr21 23888798 23890541 +2587062 AP000477.2 chr21 23960569 23968747 +2587067 AP000477.3 chr21 23982645 24114352 +2587072 AP000477.1 chr21 24043257 24050286 +2587079 AP000470.1 chr21 24154871 24192924 +2587093 LINC01689 chr21 24304546 24321377 +2587105 LINC01684 chr21 24306939 24547942 +2587274 LINC01692 chr21 24840550 25057746 +2587284 AP000402.1 chr21 24886676 24902756 +2587288 AP000146.1 chr21 24938431 24992817 +2587298 AP000235.1 chr21 25055535 25069906 +2587304 AP000233.2 chr21 25095022 25103670 +2587313 AP000233.1 chr21 25127469 25135247 +2587319 AP001341.1 chr21 25169431 25361868 +2587337 LINC00158 chr21 25385388 25431701 +2587474 AP000221.1 chr21 25515349 25518865 +2587487 MIR155HG chr21 25561909 25575168 +2587497 AP000223.1 chr21 25582770 25583326 +2587500 MRPL39 chr21 25585656 25607517 +2587572 JAM2 chr21 25639258 25717562 +2587678 AP000224.1 chr21 25646113 25654671 +2587682 ATP5PF chr21 25716503 25735673 +2587782 GABPA chr21 25734570 25772460 +2587838 APP chr21 25880550 26171128 +2588214 AP001442.1 chr21 25928754 25952614 +2588241 AP001439.1 chr21 26158091 26175824 +2588245 AP000229.1 chr21 26170871 26217381 +2588258 AP001595.2 chr21 26317390 26320773 +2588262 AP001595.1 chr21 26349780 26350634 +2588266 AP001596.1 chr21 26378552 26471698 +2588285 CYYR1-AS1 chr21 26393635 26569252 +2588296 AP001596.2 chr21 26459903 26460214 +2588299 CYYR1 chr21 26466209 26573286 +2588339 ADAMTS1 chr21 26835755 26845409 +2588402 AP001599.1 chr21 26889376 26939742 +2588407 ADAMTS5 chr21 26917922 26967088 +2588450 AP001605.1 chr21 27358885 27448579 +2588456 AP001604.1 chr21 27361121 27395787 +2588473 LINC01673 chr21 27638613 27675024 +2588499 LINC00113 chr21 27722379 27751233 +2588515 AJ006995.1 chr21 27954922 27985295 +2588520 LINC00314 chr21 28013363 28023233 +2588524 LINC01697 chr21 28048404 28137611 +2588556 LINC01695 chr21 28116094 28228667 +2588579 AF165147.1 chr21 28328738 28674848 +2588610 LINC00161 chr21 28539318 28540355 +2588617 N6AMT1 chr21 28872191 28885371 +2588669 LTN1 chr21 28928144 28992956 +2588925 RWDD2B chr21 29004384 29019360 +2588971 AF129075.2 chr21 29024255 29024890 +2588974 USP16 chr21 29024629 29054488 +2589134 CCT8 chr21 29055805 29073797 +2589322 AF129075.1 chr21 29058073 29060095 +2589326 AF129075.3 chr21 29063446 29064368 +2589330 MAP3K7CL chr21 29077471 29175889 +2589568 AF124730.1 chr21 29182027 29187795 +2589572 LINC00189 chr21 29193480 29288205 +2589584 BACH1 chr21 29194071 29630751 +2589713 BACH1-IT1 chr21 29351634 29361894 +2589719 AP000240.1 chr21 29359002 29359453 +2589722 BACH1-AS1 chr21 29370019 29376339 +2589729 BACH1-IT2 chr21 29370497 29373709 +2589741 BACH1-IT3 chr21 29496047 29500386 +2589745 GRIK1 chr21 29536933 29940033 +2590026 AP000238.1 chr21 29657406 29657831 +2590029 GRIK1-AS1 chr21 29748175 29764002 +2590059 AF096876.1 chr21 30089717 30097836 +2590063 CLDN17 chr21 30165565 30166805 +2590071 LINC00307 chr21 30209151 30211783 +2590076 CLDN8 chr21 30214006 30216097 +2590084 KRTAP24-1 chr21 30281309 30282950 +2590092 KRTAP25-1 chr21 30289145 30289514 +2590100 KRTAP26-1 chr21 30319124 30320315 +2590108 KRTAP27-1 chr21 30337013 30337694 +2590116 KRTAP23-1 chr21 30348399 30348609 +2590124 KRTAP13-2 chr21 30371390 30372271 +2590132 KRTAP13-1 chr21 30396031 30396822 +2590140 KRTAP13-3 chr21 30425265 30425968 +2590148 KRTAP13-4 chr21 30430230 30431026 +2590156 KRTAP15-1 chr21 30440275 30440945 +2590164 KRTAP19-1 chr21 30479706 30480367 +2590172 KRTAP19-2 chr21 30487043 30487436 +2590180 KRTAP19-3 chr21 30491462 30492013 +2590188 KRTAP19-4 chr21 30496824 30497165 +2590196 KRTAP19-5 chr21 30501657 30502141 +2590204 KRTAP19-6 chr21 30541535 30541864 +2590212 KRTAP19-7 chr21 30560875 30561314 +2590220 KRTAP22-2 chr21 30590105 30590397 +2590228 KRTAP6-3 chr21 30592440 30593075 +2590236 KRTAP6-2 chr21 30598590 30598902 +2590244 KRTAP22-1 chr21 30601087 30601382 +2590252 KRTAP6-1 chr21 30613431 30613930 +2590260 KRTAP20-1 chr21 30616425 30616699 +2590268 KRTAP20-4 chr21 30620627 30620850 +2590276 KRTAP20-2 chr21 30635206 30635619 +2590284 KRTAP20-3 chr21 30642864 30643136 +2590292 KRTAP21-3 chr21 30718525 30718777 +2590300 KRTAP21-2 chr21 30746794 30747259 +2590308 KRTAP21-1 chr21 30755015 30755428 +2590316 KRTAP8-1 chr21 30812697 30813274 +2590324 KRTAP7-1 chr21 30829039 30829759 +2590332 KRTAP11-1 chr21 30880644 30881580 +2590340 KRTAP19-8 chr21 31038159 31038476 +2590348 TIAM1 chr21 31118416 31559977 +2590538 AP000248.1 chr21 31347736 31359157 +2590543 AP000251.1 chr21 31559245 31560487 +2590547 AP000253.1 chr21 31653593 31659500 +2590552 SOD1 chr21 31659622 31668931 +2590595 AP000254.2 chr21 31666728 31667247 +2590598 SCAF4 chr21 31671000 31732118 +2590759 AP000255.1 chr21 31735732 31736407 +2590762 HUNK chr21 31873020 32044633 +2590817 HUNK-AS1 chr21 32020966 32021782 +2590821 LINC00159 chr21 32080316 32197813 +2590835 AP000265.1 chr21 32259804 32261585 +2590838 MIS18A chr21 32268228 32279049 +2590857 MIS18A-AS1 chr21 32277863 32280988 +2590862 MRAP chr21 32291813 32314784 +2590904 AP000266.1 chr21 32306464 32308737 +2590908 URB1 chr21 32311018 32393012 +2590998 URB1-AS1 chr21 32393130 32393960 +2591001 EVA1C chr21 32412006 32515397 +2591161 TCP10L chr21 32572238 32587373 +2591232 CFAP298 chr21 32592079 32612603 +2591333 SYNJ1 chr21 32628759 32728048 +2591752 PAXBP1-AS1 chr21 32728097 32747065 +2591814 PAXBP1 chr21 32733899 32771792 +2591992 C21orf62-AS1 chr21 32772100 32955437 +2592062 C21orf62 chr21 32790673 32813743 +2592105 AP000281.2 chr21 32844367 32849934 +2592109 AP000282.1 chr21 32913649 33071104 +2592113 LINC01690 chr21 32958888 32960566 +2592117 OLIG2 chr21 33025935 33029196 +2592141 LINC00945 chr21 33057829 33064983 +2592148 OLIG1 chr21 33070141 33072413 +2592166 AP000289.1 chr21 33110867 33123725 +2592183 AP000290.1 chr21 33152614 33159110 +2592192 LINC01548 chr21 33164809 33170649 +2592204 IFNAR2 chr21 33229901 33265675 +2592387 IL10RB-DT chr21 33263873 33266260 +2592391 IL10RB chr21 33266367 33310187 +2592469 IFNAR1 chr21 33324429 33359864 +2592603 IFNGR2 chr21 33402896 33479348 +2592710 TMEM50B chr21 33432485 33479974 +2592821 AP000302.1 chr21 33482499 33484258 +2592826 DNAJC28 chr21 33485530 33491720 +2592865 GART chr21 33503931 33543491 +2593198 SON chr21 33543038 33577514 +2593445 DONSON chr21 33559542 33588706 +2593673 CRYZL1 chr21 33589341 33643926 +2594067 ITSN1 chr21 33642400 33899861 +2594930 ATP5PO chr21 33903453 33915814 +2595044 LINC00649 chr21 33915534 33977691 +2595121 AP000569.1 chr21 33967101 33968573 +2595125 MRPS6 chr21 34073224 34143034 +2595156 SLC5A3 chr21 34073578 34106260 +2595166 LINC00310 chr21 34157724 34190244 +2595201 AP000317.1 chr21 34205055 34325034 +2595208 AP000320.1 chr21 34353099 34375364 +2595213 KCNE2 chr21 34364024 34371389 +2595223 SMIM11A chr21 34375480 34416961 +2595315 FAM243A chr21 34400112 34401072 +2595322 AP000322.2 chr21 34412200 34412587 +2595325 SMIM34A chr21 34418715 34423966 +2595335 AP000322.1 chr21 34425508 34426017 +2595338 KCNE1 chr21 34446688 34512210 +2595428 RCAN1 chr21 34513142 34615113 +2595571 CLIC6 chr21 34669389 34718227 +2595606 LINC00160 chr21 34723807 34737204 +2595622 LINC01426 chr21 34745757 34784886 +2595633 RUNX1 chr21 34787801 36004667 +2595831 AP000331.1 chr21 34836286 34884882 +2595835 AF015262.1 chr21 35136638 35139222 +2595839 AF015720.1 chr21 35713139 35732942 +2595843 LINC01436 chr21 36005338 36007838 +2595847 SETD4 chr21 36034541 36079389 +2596121 AP000688.4 chr21 36060432 36064408 +2596126 AP000688.1 chr21 36069642 36126640 +2596135 CBR1 chr21 36069941 36073166 +2596182 AP000688.3 chr21 36082859 36090414 +2596186 AP000688.2 chr21 36104881 36109690 +2596190 CBR3-AS1 chr21 36131767 36175815 +2596288 CBR3 chr21 36135079 36146562 +2596300 DOP1B chr21 36156782 36294274 +2596403 AP000692.2 chr21 36319792 36320670 +2596406 MORC3 chr21 36320189 36386148 +2596562 AP000692.1 chr21 36360630 36362040 +2596566 CHAF1B chr21 36385392 36419015 +2596612 AP000695.1 chr21 36430360 36481070 +2596616 AP000695.2 chr21 36445731 36532408 +2596623 CLDN14 chr21 36460621 36576569 +2596675 AP000696.2 chr21 36526280 36542855 +2596679 AP000696.3 chr21 36580172 36581229 +2596683 AP000696.1 chr21 36632681 36637033 +2596687 AP000697.1 chr21 36698773 36701564 +2596691 SIM2 chr21 36699115 36749917 +2596763 HLCS chr21 36750888 36990236 +2596889 HLCS-IT1 chr21 36803984 36806284 +2596893 AP000704.1 chr21 36966461 36975164 +2596907 RIPPLY3 chr21 37006150 37019662 +2596930 PIGP chr21 37059170 37073170 +2597022 TTC3 chr21 37073226 37203112 +2597828 AP001429.1 chr21 37100814 37101343 +2597831 TTC3-AS1 chr21 37187666 37193926 +2597835 DSCR9 chr21 37208503 37221736 +2597862 AP001432.1 chr21 37221419 37237744 +2597866 VPS26C chr21 37223420 37267919 +2597988 AP001412.1 chr21 37267784 37268497 +2597991 AP001437.2 chr21 37337382 37366858 +2597995 AP001437.1 chr21 37365477 37365932 +2597998 DYRK1A chr21 37365573 37526358 +2598478 AP001407.1 chr21 37593977 37661496 +2598483 KCNJ6 chr21 37607373 38121345 +2598512 KCNJ6-AS1 chr21 37717102 37719569 +2598516 DSCR4 chr21 37951425 38121360 +2598533 DSCR4-IT1 chr21 38006544 38010618 +2598537 DSCR8 chr21 38121451 38156511 +2598570 KCNJ15 chr21 38155549 38307357 +2598834 DSCR10 chr21 38206156 38208644 +2598839 AP001434.1 chr21 38237217 38238201 +2598843 LINC01423 chr21 38323635 38333421 +2598855 ERG chr21 38380027 38661780 +2599169 AP001037.1 chr21 38503562 38543336 +2599174 LINC00114 chr21 38733890 38747460 +2599198 ETS2 chr21 38805183 38824955 +2599389 AP001042.1 chr21 38812878 38956467 +2599501 AP001042.2 chr21 38846247 38848644 +2599505 AP001042.3 chr21 38857539 38858861 +2599510 AP001043.1 chr21 38888772 38903905 +2599514 LINC01700 chr21 38974429 38977774 +2599519 AF064858.1 chr21 38988569 39062894 +2599546 AF064858.2 chr21 39028536 39029128 +2599550 PSMG1 chr21 39174769 39183488 +2599624 BRWD1 chr21 39184176 39321559 +2600168 AF129408.1 chr21 39184469 39184899 +2600171 BRWD1-IT1 chr21 39217093 39219805 +2600175 BRWD1-AS2 chr21 39313935 39314962 +2600178 BRWD1-AS1 chr21 39315707 39323218 +2600183 HMGN1 chr21 39342315 39349647 +2600433 GET1 chr21 39377698 39428528 +2600706 LCA5L chr21 39405844 39445805 +2600959 SH3BGR chr21 39445855 39515506 +2601101 B3GALT5 chr21 39556442 39673137 +2601157 B3GALT5-AS1 chr21 39597147 39612910 +2601190 AF064860.1 chr21 39630271 39726085 +2601195 AF064860.2 chr21 39727755 39730680 +2601203 IGSF5 chr21 39745407 39802096 +2601237 PCP4 chr21 39867438 39929397 +2601271 DSCAM chr21 40010999 40847158 +2601468 DSCAM-AS1 chr21 40383083 40385358 +2601483 DSCAM-IT1 chr21 40615378 40630767 +2601494 AF064866.1 chr21 40736318 40754888 +2601498 AL773573.1 chr21 41007244 41037362 +2601502 LINC00323 chr21 41141493 41148198 +2601521 BACE2 chr21 41167801 41282530 +2601634 PLAC4 chr21 41175231 41186788 +2601652 BACE2-IT1 chr21 41180097 41180626 +2601656 FAM3B chr21 41304212 41357727 +2601756 MX2 chr21 41361999 41409393 +2601873 MX1 chr21 41420304 41459214 +2602168 AP001610.2 chr21 41441056 41445708 +2602173 TMPRSS2 chr21 41464305 41531116 +2602346 AP001610.3 chr21 41559125 41562958 +2602351 AP006748.1 chr21 41576135 41581319 +2602355 AP006748.2 chr21 41580475 41582887 +2602362 LINC00111 chr21 41679181 41697336 +2602367 LINC00479 chr21 41711520 41715775 +2602392 LINC00112 chr21 41715806 41717975 +2602425 RIPK4 chr21 41739369 41767089 +2602470 AP001615.1 chr21 41739373 41741308 +2602474 PRDM15 chr21 41798225 41879482 +2602988 AP001619.2 chr21 41870633 41872054 +2602992 AP001619.1 chr21 41874756 41877613 +2602997 C2CD2 chr21 41885112 41954018 +2603112 ZBTB21 chr21 41986831 42010387 +2603192 ZNF295-AS1 chr21 42009194 42055130 +2603212 UMODL1 chr21 42062959 42143453 +2603535 UMODL1-AS1 chr21 42102134 42108534 +2603539 ABCG1 chr21 42199689 42297244 +2603811 TFF3 chr21 42311667 42315651 +2603847 TFF2 chr21 42346357 42350997 +2603872 TFF1 chr21 42362282 42366535 +2603884 TMPRSS3 chr21 42371837 42396091 +2604062 UBASH3A chr21 42403447 42447684 +2604271 RSPH1 chr21 42472486 42496246 +2604324 SLC37A1 chr21 42496008 42581440 +2604456 AP001625.3 chr21 42496539 42497443 +2604461 AP001625.1 chr21 42508624 42509661 +2604468 AP001625.2 chr21 42560374 42561934 +2604472 LINC01671 chr21 42599280 42615058 +2604476 AP001626.1 chr21 42648271 42651244 +2604480 PDE9A chr21 42653621 42775509 +2605214 AP001627.1 chr21 42733594 42741758 +2605218 LINC01668 chr21 42777819 42779994 +2605223 AP001628.2 chr21 42781074 42782229 +2605227 AP001628.1 chr21 42831040 42836477 +2605232 WDR4 chr21 42843094 42879568 +2605336 NDUFV3 chr21 42879644 42913304 +2605371 ERVH48-1 chr21 42916803 42925646 +2605377 AP001630.1 chr21 42964639 42965363 +2605381 PKNOX1 chr21 42974510 43033931 +2605493 CBS chr21 43053191 43076943 +2605766 U2AF1 chr21 43092956 43107587 +2605922 AP001631.2 chr21 43107942 43168646 +2605927 FRGCA chr21 43140523 43141092 +2605931 AP001631.1 chr21 43159066 43162277 +2605936 CRYAA chr21 43169008 43172805 +2605978 LINC00322 chr21 43322417 43332039 +2605983 LINC01679 chr21 43358147 43362349 +2605987 AP001046.1 chr21 43363332 43366566 +2605991 SIK1 chr21 43414483 43427131 +2606055 LINC00319 chr21 43446601 43453902 +2606068 LINC00313 chr21 43461960 43479534 +2606108 AP001048.1 chr21 43465309 43467298 +2606112 HSF2BP chr21 43529186 43659488 +2606153 H2BFS chr21 43565182 43565648 +2606161 RRP1B chr21 43659560 43696079 +2606205 PDXK chr21 43719094 43762307 +2606411 AP001053.1 chr21 43768320 43771666 +2606416 CSTB chr21 43772511 43776445 +2606446 RRP1 chr21 43789513 43805293 +2606535 AATBC chr21 43805758 43812567 +2606547 AGPAT3 chr21 43865223 43987592 +2606794 TRAPPC10 chr21 44012309 44106552 +2606964 PWP2 chr21 44107373 44131181 +2607050 GATD3A chr21 44133610 44210114 +2607220 LINC01678 chr21 44158740 44160076 +2607228 AP001056.2 chr21 44172169 44194338 +2607236 AP001056.1 chr21 44175489 44176453 +2607240 AP001057.1 chr21 44200602 44207399 +2607252 ICOSLG chr21 44217014 44240966 +2607332 AP001059.3 chr21 44241847 44242081 +2607335 AP001059.2 chr21 44244545 44244993 +2607338 DNMT3L chr21 44246339 44262216 +2607423 AP001059.1 chr21 44250813 44251520 +2607427 AIRE chr21 44285838 44298648 +2607506 PFKL chr21 44300051 44327376 +2607716 AP001062.3 chr21 44328944 44330221 +2607724 CFAP410 chr21 44328944 44339402 +2607805 AP001062.1 chr21 44331234 44335851 +2607809 AP001062.2 chr21 44339376 44340470 +2607813 AP001063.1 chr21 44347767 44348295 +2607816 TRPM2 chr21 44350163 44443081 +2608172 TRPM2-AS chr21 44414588 44425272 +2608180 LRRC3-DT chr21 44450986 44455284 +2608186 LRRC3 chr21 44455510 44462196 +2608196 AP001065.3 chr21 44477850 44478493 +2608199 LINC02575 chr21 44485577 44490288 +2608203 AP001065.4 chr21 44494874 44495519 +2608206 TSPEAR chr21 44497893 44711572 +2608279 TSPEAR-AS1 chr21 44506807 44516575 +2608291 TSPEAR-AS2 chr21 44517216 44525952 +2608302 AP001066.1 chr21 44530172 44533145 +2608306 KRTAP10-1 chr21 44538981 44540195 +2608314 KRTAP10-2 chr21 44550357 44551505 +2608325 KRTAP10-3 chr21 44557790 44558795 +2608333 KRTAP10-4 chr21 44573724 44638284 +2608366 KRTAP10-5 chr21 44579455 44580604 +2608374 KRTAP10-6 chr21 44591268 44592505 +2608382 KRTAP10-7 chr21 44600597 44602174 +2608390 KRTAP10-8 chr21 44612079 44612954 +2608398 KRTAP10-9 chr21 44627093 44628378 +2608420 KRTAP10-10 chr21 44637356 44638455 +2608428 KRTAP10-11 chr21 44646414 44647650 +2608436 KRTAP12-4 chr21 44654213 44654659 +2608444 KRTAP12-3 chr21 44657932 44658341 +2608452 KRTAP12-2 chr21 44666189 44666927 +2608460 KRTAP12-1 chr21 44681576 44682163 +2608468 KRTAP10-12 chr21 44697172 44698044 +2608483 UBE2G2 chr21 44768580 44801826 +2608598 LINC01424 chr21 44802577 44804717 +2608602 SUMO3 chr21 44805617 44818779 +2608662 PTTG1IP chr21 44849585 44873903 +2608736 ITGB2 chr21 44885953 44931989 +2609207 ITGB2-AS1 chr21 44921051 44929678 +2609236 AL844908.2 chr21 44929653 44930112 +2609239 LINC01547 chr21 44932814 44939937 +2609282 AL844908.1 chr21 44936303 44936954 +2609285 FAM207A chr21 44940012 44976989 +2609342 AP001505.1 chr21 44978832 44979274 +2609345 LINC00163 chr21 44989864 44994086 +2609352 LINC00165 chr21 44994362 44995185 +2609355 PICSAR chr21 44999208 45004727 +2609359 ADARB1 chr21 45073853 45226560 +2609621 AL133499.1 chr21 45100487 45101094 +2609624 LINC00334 chr21 45234308 45264548 +2609654 POFUT2 chr21 45263928 45287898 +2609824 LINC00205 chr21 45288050 45297806 +2609841 BX322557.2 chr21 45299929 45302964 +2609846 LINC00315 chr21 45300245 45305257 +2609851 BX322557.1 chr21 45336707 45338665 +2609855 LINC00316 chr21 45338590 45341990 +2609859 BX322559.1 chr21 45378201 45379635 +2609866 BX322562.1 chr21 45403809 45404369 +2609869 COL18A1 chr21 45405165 45513720 +2610209 COL18A1-AS2 chr21 45407386 45410065 +2610215 COL18A1-AS1 chr21 45419716 45425070 +2610224 SLC19A1 chr21 45493572 45573365 +2610365 LINC01694 chr21 45593654 45603088 +2610379 AL133493.1 chr21 45596364 45625675 +2610385 AL133493.2 chr21 45607386 45609194 +2610389 PCBP3 chr21 45643694 45942454 +2610687 AL133492.1 chr21 45759804 45763758 +2610690 AL592528.1 chr21 45827961 45837987 +2610695 AJ011931.2 chr21 45861830 45888638 +2610699 AJ011931.1 chr21 45870854 45873345 +2610702 AJ239328.1 chr21 45914296 45919483 +2610707 AJ011932.1 chr21 45974489 45974953 +2610710 COL6A1 chr21 45981737 46005050 +2610884 AP001476.1 chr21 46037052 46039807 +2610888 AP001476.3 chr21 46052596 46053105 +2610892 AP001476.2 chr21 46056516 46057567 +2610896 AP001471.1 chr21 46093264 46097530 +2610900 COL6A2 chr21 46098097 46132849 +2611183 FTCD chr21 46136262 46155579 +2611369 FTCD-AS1 chr21 46151614 46152647 +2611373 SPATC1L chr21 46161148 46184476 +2611402 AP001468.1 chr21 46185079 46188941 +2611406 LSS chr21 46188141 46228824 +2611651 AP001469.1 chr21 46220269 46225364 +2611660 MCM3AP-AS1 chr21 46229196 46259390 +2611720 MCM3AP chr21 46235133 46286297 +2611918 AP001469.2 chr21 46246890 46247682 +2611922 AP001469.3 chr21 46251549 46254133 +2611929 YBEY chr21 46286342 46297751 +2612024 C21orf58 chr21 46300181 46323875 +2612194 PCNT chr21 46324141 46445769 +2612385 AP000471.1 chr21 46326288 46326491 +2612392 DIP2A chr21 46458891 46570015 +2612838 DIP2A-IT1 chr21 46462471 46469306 +2612844 S100B chr21 46598604 46605208 +2612878 PRMT2 chr21 46635595 46665124 +2613134 CU104787.1 chr22 11066418 11068174 +2613138 AP000542.3 chr22 15282557 15288670 +2613141 AP000542.2 chr22 15298378 15304556 +2613144 OR11H1 chr22 15528159 15529139 +2613157 AP000534.1 chr22 15557577 15560694 +2613162 AP000532.2 chr22 15600908 15604882 +2613167 POTEH chr22 15690026 15721631 +2613250 POTEH-AS1 chr22 15699361 15703403 +2613254 AP000527.1 chr22 15746630 15778297 +2613263 DUXAP8 chr22 15784959 15829984 +2613319 AP000525.1 chr22 15823197 15823890 +2613322 AC145543.1 chr22 15914721 15915800 +2613326 AP000547.2 chr22 16521059 16527237 +2613331 CCT8L2 chr22 16590751 16592810 +2613339 AP000547.4 chr22 16592895 16600110 +2613343 AP000547.3 chr22 16601911 16615111 +2613359 AP000365.1 chr22 16616170 16617114 +2613363 ANKRD62P1-PARP4P3 chr22 16654066 16675540 +2613379 AC005301.2 chr22 16725072 16747761 +2613384 LINC01665 chr22 16746628 16748645 +2613391 XKR3 chr22 16783412 16821699 +2613405 AC007064.2 chr22 16869478 16871126 +2613409 IGKV1OR22-5 chr22 16904219 16904696 +2613413 IGKV2OR22-4 chr22 16914235 16914981 +2613417 IGKV2OR22-3 chr22 16921443 16922173 +2613421 IGKV3OR22-2 chr22 16925952 16926444 +2613425 IGKV1OR22-1 chr22 16933521 16934003 +2613429 GAB4 chr22 16961936 17008222 +2613529 AC006946.2 chr22 17067821 17070675 +2613532 AC006946.3 chr22 17080701 17081456 +2613535 IL17RA chr22 17084954 17115694 +2613604 TMEM121B chr22 17116297 17121367 +2613621 LINC01664 chr22 17121560 17132104 +2613645 HDHD5 chr22 17137511 17165287 +2613717 HDHD5-AS1 chr22 17159384 17165445 +2613724 ADA2 chr22 17178790 17258235 +2613988 CECR3 chr22 17256859 17266733 +2613993 CECR2 chr22 17359949 17558149 +2614184 AC007666.2 chr22 17521514 17570078 +2614192 SLC25A18 chr22 17563450 17590995 +2614263 AC007666.1 chr22 17580157 17589192 +2614274 ATP6V1E1 chr22 17592136 17628749 +2614385 BCL2L13 chr22 17628855 17730855 +2614606 BID chr22 17734138 17774770 +2614796 LINC00528 chr22 17777322 17779481 +2614799 MICAL3 chr22 17787649 18024561 +2615285 AC016026.2 chr22 17800722 17802035 +2615289 AC016027.3 chr22 17983205 17983619 +2615293 AC016027.2 chr22 18004270 18007308 +2615297 LINC01634 chr22 18029385 18037968 +2615301 AC016027.1 chr22 18076527 18078884 +2615309 PEX26 chr22 18077920 18131138 +2615386 TUBA8 chr22 18110331 18146554 +2615446 AC008079.1 chr22 18110759 18131154 +2615449 USP18 chr22 18150170 18177397 +2615477 FAM230D chr22 18178038 18205915 +2615488 FAM230J chr22 18361820 18391105 +2615531 AC011718.1 chr22 18374106 18375689 +2615535 FAM230A chr22 18422244 18500594 +2615560 AC023490.2 chr22 18486999 18491247 +2615567 AC023490.4 chr22 18501794 18512187 +2615571 GGTLC3 chr22 18516344 18518161 +2615589 TMEM191B chr22 18527802 18530573 +2615660 RIMBP3 chr22 18605815 18611919 +2615668 AC023490.5 chr22 18633984 18634682 +2615675 FAM230E chr22 18733914 18757906 +2615688 FAM230F chr22 18873543 18894407 +2615698 AC008103.1 chr22 18883502 18884682 +2615701 DGCR6 chr22 18906028 18914238 +2615796 PRODH chr22 18912777 18936553 +2616028 AC007326.5 chr22 18936411 18947741 +2616040 AC007326.2 chr22 18951934 18959512 +2616043 DGCR9 chr22 18970525 19031242 +2616065 DGCR10 chr22 19023056 19023550 +2616068 DGCR2 chr22 19036282 19122454 +2616185 DGCR11 chr22 19046162 19048375 +2616188 AC004461.2 chr22 19061041 19061843 +2616191 AC004471.1 chr22 19121529 19124503 +2616195 AC004471.2 chr22 19124309 19128449 +2616200 ESS2 chr22 19130279 19144684 +2616265 TSSK2 chr22 19131308 19132622 +2616273 GSC2 chr22 19148576 19150283 +2616284 LINC01311 chr22 19171395 19172839 +2616287 SLC25A1 chr22 19175581 19178739 +2616353 CLTCL1 chr22 19179473 19291719 +2616692 AC000072.1 chr22 19196402 19200083 +2616696 AC000085.1 chr22 19291969 19328901 +2616700 HIRA chr22 19330698 19447450 +2616825 C22orf39 chr22 19351368 19448232 +2616934 MRPL40 chr22 19431902 19436075 +2616957 AC000068.1 chr22 19447893 19450105 +2616961 UFD1 chr22 19449911 19479202 +2617110 AC000068.3 chr22 19454179 19454605 +2617113 AC000068.2 chr22 19456503 19456962 +2617116 CDC45 chr22 19479457 19520612 +2617460 AC000082.1 chr22 19520572 19522769 +2617464 CLDN5 chr22 19523024 19527545 +2617497 LINC00895 chr22 19565203 19566839 +2617500 AC000067.1 chr22 19667023 19667555 +2617504 SEPTIN5 chr22 19714503 19724224 +2617726 GP1BB chr22 19722945 19724771 +2617736 TBX1 chr22 19756703 19783593 +2617834 GNB1L chr22 19783223 19854939 +2617917 RTL10 chr22 19846138 19854896 +2617962 TXNRD2 chr22 19875517 19941820 +2618424 COMT chr22 19941607 19969975 +2618566 ARVCF chr22 19969896 20016823 +2618760 TANGO2 chr22 20017014 20067164 +2619129 AC006547.1 chr22 20058030 20070569 +2619179 AC006547.3 chr22 20064552 20065705 +2619183 DGCR8 chr22 20080232 20111877 +2619324 AC006547.2 chr22 20110821 20111875 +2619328 TRMT2A chr22 20111875 20117392 +2619538 RANBP1 chr22 20115938 20127355 +2619692 ZDHHC8 chr22 20129456 20148007 +2619796 CCDC188 chr22 20148416 20151055 +2619827 AC007663.2 chr22 20198729 20204918 +2619833 LINC00896 chr22 20206397 20208524 +2619838 RTN4R chr22 20241415 20283246 +2619872 DGCR6L chr22 20314238 20320080 +2619914 AC007663.4 chr22 20318119 20318749 +2619917 AC007663.3 chr22 20320739 20321203 +2619920 FAM230G chr22 20338805 20354372 +2619945 AC007731.2 chr22 20343203 20344365 +2619949 AC007731.5 chr22 20348758 20354387 +2619953 USP41 chr22 20350578 20390758 +2620015 ZNF74 chr22 20394115 20408461 +2620120 SCARF2 chr22 20424815 20437826 +2620181 KLHL22 chr22 20441519 20495844 +2620290 MED15 chr22 20495913 20587632 +2620747 AC007731.3 chr22 20522070 20523870 +2620752 PI4KA chr22 20707691 20859417 +2621027 SERPIND1 chr22 20774113 20787720 +2621056 SNAP29 chr22 20859007 20891214 +2621088 AC007308.1 chr22 20889206 20891214 +2621092 CRKL chr22 20917407 20953747 +2621117 LINC01637 chr22 20957092 20964679 +2621121 AIFM3 chr22 20965108 20981360 +2621437 AC002470.1 chr22 20981361 20981755 +2621440 LZTR1 chr22 20982269 20999032 +2621765 THAP7 chr22 20999104 21002196 +2621816 THAP7-AS1 chr22 21001886 21010342 +2621828 P2RX6 chr22 21009808 21028830 +2621993 SLC7A4 chr22 21028718 21032840 +2622031 AC002472.1 chr22 21031354 21044117 +2622036 LRRC74B chr22 21045960 21064168 +2622084 AP000550.1 chr22 21114607 21124451 +2622092 FAM230B chr22 21167758 21192156 +2622153 AP000550.2 chr22 21177892 21179875 +2622157 GGT2 chr22 21207973 21227637 +2622221 FAM230H chr22 21300990 21325042 +2622286 AP000552.2 chr22 21312920 21314904 +2622290 LINC01651 chr22 21354563 21358067 +2622299 AP000552.4 chr22 21360601 21361299 +2622306 RIMBP3B chr22 21383374 21389478 +2622314 HIC2 chr22 21417371 21451463 +2622346 TMEM191C chr22 21466423 21471269 +2622512 RIMBP3C chr22 21545357 21551461 +2622527 UBE2L3 chr22 21549447 21624034 +2622570 YDJC chr22 21628089 21630064 +2622631 CCDC116 chr22 21632716 21637329 +2622669 AP000553.3 chr22 21640844 21641284 +2622672 SDF2L1 chr22 21642302 21644299 +2622687 AP000553.2 chr22 21661934 21662363 +2622690 PPIL2 chr22 21666009 21700015 +2622984 YPEL1 chr22 21697536 21735794 +2623029 AP000553.9 chr22 21712761 21714013 +2623033 AP000553.8 chr22 21737448 21744108 +2623037 MAPK1 chr22 21754500 21867680 +2623103 PPM1F chr22 21919425 21952848 +2623199 AC245452.1 chr22 21938269 21977632 +2623207 TOP3B chr22 21957025 21982816 +2623524 IGLVI-70 chr22 22026076 22026593 +2623528 IGLV4-69 chr22 22030934 22031472 +2623536 IGLVI-68 chr22 22032745 22033194 +2623540 AC245452.5 chr22 22036344 22040065 +2623544 IGLV10-54 chr22 22038643 22215270 +2623562 IGLV10-67 chr22 22043618 22043942 +2623565 IGLVIV-66-1 chr22 22058433 22058892 +2623568 IGLVV-66 chr22 22061077 22061538 +2623572 IGLVIV-65 chr22 22070225 22070707 +2623576 IGLVIV-64 chr22 22075366 22075666 +2623579 IGLVI-63 chr22 22079770 22080263 +2623583 IGLV1-62 chr22 22086561 22087110 +2623587 IGLV8-61 chr22 22098700 22099212 +2623595 IGLV4-60 chr22 22162199 22162681 +2623602 IGLVIV-59 chr22 22179228 22179477 +2623605 IGLVV-58 chr22 22182582 22182885 +2623608 IGLV6-57 chr22 22195799 22196276 +2623615 IGLVI-56 chr22 22198560 22199011 +2623619 IGLV11-55 chr22 22201663 22202161 +2623627 IGLVIV-53 chr22 22219647 22220133 +2623631 VPREB1 chr22 22244780 22245515 +2623650 AC245060.6 chr22 22264601 22273020 +2623653 AC245060.5 chr22 22283928 22287220 +2623656 AC245060.2 chr22 22293733 22294794 +2623660 IGLV5-52 chr22 22318727 22319226 +2623668 IGLV1-51 chr22 22322472 22322969 +2623676 IGLV1-50 chr22 22327300 22327814 +2623684 IGLV9-49 chr22 22343187 22343732 +2623694 IGLV5-48 chr22 22352940 22353433 +2623703 IGLV1-47 chr22 22357739 22358260 +2623711 IGLV7-46 chr22 22369614 22370087 +2623719 IGLV5-45 chr22 22375986 22376505 +2623727 IGLV1-44 chr22 22380766 22381347 +2623735 IGLV7-43 chr22 22395018 22395489 +2623743 IGLVI-42 chr22 22397032 22397524 +2623747 IGLVVII-41-1 chr22 22398849 22398999 +2623750 IGLV1-41 chr22 22404207 22404721 +2623754 IGLV1-40 chr22 22409766 22410282 +2623762 IGLVI-38 chr22 22425821 22426314 +2623766 IGLV5-37 chr22 22427540 22428035 +2623774 IGLV1-36 chr22 22431958 22432465 +2623782 IGLV7-35 chr22 22450202 22450652 +2623786 ZNF280B chr22 22484421 22508742 +2623824 ZNF280A chr22 22513736 22520270 +2623834 PRAME chr22 22547701 22559361 +2624000 AC246793.1 chr22 22559343 22566602 +2624005 IGLV2-34 chr22 22580014 22580296 +2624008 IGLV2-33 chr22 22588155 22588688 +2624016 IGLV3-32 chr22 22594528 22595056 +2624024 IGLV3-31 chr22 22604445 22605165 +2624028 IGLV3-30 chr22 22618572 22619163 +2624032 AC244250.4 chr22 22630546 22633849 +2624036 GGTLC2 chr22 22644475 22647903 +2624158 IGLV3-29 chr22 22661299 22661542 +2624161 IGLV2-28 chr22 22664473 22664907 +2624165 IGLV3-27 chr22 22668288 22668806 +2624173 IGLV3-26 chr22 22673152 22673602 +2624177 IGLVVI-25-1 chr22 22679097 22679345 +2624180 IGLV3-25 chr22 22686726 22687271 +2624188 AC244250.1 chr22 22692778 22693312 +2624192 IGLV3-24 chr22 22694439 22694952 +2624196 IGLV2-23 chr22 22697789 22698407 +2624204 IGLVVI-22-1 chr22 22700760 22700970 +2624207 IGLV3-22 chr22 22704265 22704822 +2624215 IGLV3-21 chr22 22711689 22713203 +2624225 IGLVI-20 chr22 22715290 22715419 +2624228 IGLV3-19 chr22 22720623 22721145 +2624236 IGLV2-18 chr22 22734607 22735089 +2624244 IGLV3-17 chr22 22738944 22739187 +2624247 IGLV3-16 chr22 22747383 22747921 +2624255 IGLV3-15 chr22 22755554 22755797 +2624258 IGLV2-14 chr22 22758700 22759218 +2624266 IGLV3-13 chr22 22762294 22762516 +2624269 IGLV3-12 chr22 22771824 22772582 +2624277 IGLV2-11 chr22 22792491 22793007 +2624285 IGLV3-10 chr22 22811747 22812281 +2624293 IGLV3-9 chr22 22819010 22819756 +2624301 IGLV2-8 chr22 22822658 22823289 +2624309 IGLV3-7 chr22 22838602 22838872 +2624312 IGLV3-6 chr22 22850375 22850624 +2624315 IGLV2-5 chr22 22856762 22857038 +2624318 IGLV3-4 chr22 22858025 22858268 +2624321 IGLV4-3 chr22 22871507 22872035 +2624331 IGLV3-2 chr22 22873212 22873440 +2624334 IGLV3-1 chr22 22880706 22881396 +2624342 IGLJ1 chr22 22893692 22893818 +2624346 IGLC1 chr22 22895375 22895834 +2624352 IGLJ2 chr22 22899481 22899655 +2624358 IGLC2 chr22 22900976 22901437 +2624364 IGLJ3 chr22 22904850 22905025 +2624370 IGLC3 chr22 22906342 22906803 +2624376 IGLJ4 chr22 22910574 22910606 +2624380 IGLC4 chr22 22910828 22911075 +2624383 IGLJ5 chr22 22914237 22914308 +2624387 IGLC5 chr22 22915635 22915927 +2624390 IGLJ6 chr22 22918132 22918201 +2624394 IGLC6 chr22 22919535 22919851 +2624397 IGLJ7 chr22 22921390 22921435 +2624401 IGLC7 chr22 22922594 22923034 +2624407 RSPH14 chr22 23059415 23145021 +2624465 GNAZ chr22 23070519 23125032 +2624483 RAB36 chr22 23145326 23164350 +2624546 BCR chr22 23179704 23318037 +2624723 LINC02556 chr22 23326616 23328493 +2624727 LINC01659 chr22 23433564 23435071 +2624735 FAM230I chr22 23462086 23486980 +2624749 AP000345.3 chr22 23510154 23512662 +2624753 LINC02557 chr22 23512494 23513602 +2624757 PCAT14 chr22 23536881 23547797 +2624768 AP000345.1 chr22 23567064 23573507 +2624780 IGLL1 chr22 23573125 23580302 +2624810 AP000345.2 chr22 23580880 23583859 +2624815 DRICH1 chr22 23608452 23632321 +2624869 RGL4 chr22 23688136 23699176 +2625081 ZNF70 chr22 23738682 23751112 +2625091 VPREB3 chr22 23752743 23754425 +2625110 C22orf15 chr22 23763021 23765861 +2625169 CHCHD10 chr22 23765834 23768443 +2625223 MMP11 chr22 23768226 23784316 +2625330 SMARCB1 chr22 23786931 23838008 +2625574 DERL3 chr22 23834503 23839128 +2625671 AP000350.5 chr22 23856427 23857039 +2625674 SLC2A11 chr22 23856703 23886309 +2625994 AP000350.7 chr22 23865248 23873277 +2625997 MIF chr22 23894383 23895227 +2626015 MIF-AS1 chr22 23894426 23898930 +2626020 AP000350.6 chr22 23901432 23907068 +2626023 GSTT2B chr22 23957414 23961186 +2626054 DDTL chr22 23966888 23972556 +2626066 AC253536.6 chr22 23969211 23969873 +2626069 DDT chr22 23971365 23979828 +2626126 GSTT4 chr22 23998401 24005453 +2626173 CABIN1 chr22 24011192 24178628 +2626575 AC253536.3 chr22 24101689 24103354 +2626580 SUSD2 chr22 24181487 24189106 +2626628 GGT5 chr22 24219654 24245142 +2626738 SPECC1L chr22 24270817 24417739 +2626928 ADORA2A chr22 24417879 24442357 +2627049 ADORA2A-AS1 chr22 24429206 24495074 +2627080 UPB1 chr22 24494107 24528390 +2627151 AP000355.1 chr22 24516508 24518386 +2627155 GUCD1 chr22 24540423 24555935 +2627302 SNRPD3 chr22 24555958 24582052 +2627334 GGT1 chr22 24556007 24629005 +2627472 LRRC75B chr22 24585620 24593208 +2627538 GGT1 chr22 24594811 24629005 +2627982 AP000356.1 chr22 24598054 24599398 +2627986 AP000356.2 chr22 24645171 24651657 +2627992 AP000357.2 chr22 24691122 24696003 +2627996 PIWIL3 chr22 24719034 24774720 +2628209 SGSM1 chr22 24806169 24927578 +2628429 TMEM211 chr22 24934954 24946695 +2628466 KIAA1671 chr22 24952730 25197448 +2628579 AL022323.3 chr22 25009685 25015072 +2628582 AL022323.5 chr22 25022594 25024652 +2628585 AL022323.2 chr22 25048967 25051966 +2628588 AL022323.4 chr22 25052122 25065241 +2628591 AL022323.1 chr22 25102433 25112692 +2628598 CRYBB3 chr22 25199858 25207359 +2628631 Z99916.1 chr22 25212085 25213826 +2628639 CRYBB2 chr22 25212564 25231870 +2628674 Z99916.3 chr22 25251523 25252602 +2628677 AL022332.1 chr22 25279529 25282674 +2628685 LRP5L chr22 25351418 25405377 +2628765 AL022324.3 chr22 25434324 25435070 +2628768 AL008721.1 chr22 25436312 25436915 +2628771 IGLVIVOR22-1 chr22 25437306 25437823 +2628775 AL008721.2 chr22 25476218 25479971 +2628778 AL022329.1 chr22 25561117 25564719 +2628798 GRK3 chr22 25564675 25729294 +2628918 AL022329.2 chr22 25580241 25581382 +2628922 MYO18B chr22 25742144 26031041 +2629363 AL022329.3 chr22 25756318 25756669 +2629366 Z98949.1 chr22 25876854 25903247 +2629484 Z98949.3 chr22 25959074 25983526 +2629488 LINC02559 chr22 26161834 26164303 +2629492 AL022337.1 chr22 26161905 26169341 +2629512 SEZ6L chr22 26169462 26383597 +2629813 AL080273.1 chr22 26241331 26254092 +2629820 ASPHD2 chr22 26429260 26445015 +2629834 HPS4 chr22 26443423 26483837 +2630119 SRRD chr22 26483877 26494658 +2630147 TFIP11 chr22 26491225 26512505 +2630411 Z95115.1 chr22 26512537 26514568 +2630417 TPST2 chr22 26521996 26596717 +2630529 Z95115.2 chr22 26597028 26611453 +2630534 CRYBB1 chr22 26599278 26618027 +2630556 CRYBA4 chr22 26621963 26630669 +2630580 MIAT chr22 26646411 26676475 +2630705 Z99774.1 chr22 26667693 26672654 +2630710 MIATNB chr22 26672747 26780893 +2630786 LINC01422 chr22 26858634 26968763 +2630820 Z97353.2 chr22 26903292 26920935 +2630829 AL008638.3 chr22 27019369 27024550 +2630832 AL008638.5 chr22 27040197 27041494 +2630835 AL008638.4 chr22 27044001 27045315 +2630838 AL008638.2 chr22 27048144 27061247 +2630846 AL008638.6 chr22 27102766 27107019 +2630849 AL008638.1 chr22 27143478 27159878 +2630853 AL021153.1 chr22 27204211 27205126 +2630857 LINC01638 chr22 27221349 27225134 +2630877 AL020994.3 chr22 27276240 27286349 +2630882 AL020994.1 chr22 27307483 27318538 +2630887 LINC02554 chr22 27307777 27318501 +2630903 AL020994.2 chr22 27331634 27379265 +2630920 AL049536.1 chr22 27414462 27419713 +2630926 AL050402.2 chr22 27436292 27441774 +2630931 AL050402.1 chr22 27457247 27460060 +2630935 AL133456.1 chr22 27563839 27573573 +2630940 AL121885.2 chr22 27676559 27714970 +2630947 AL121885.3 chr22 27707580 27709931 +2630951 AL121885.1 chr22 27716480 27721677 +2630955 MN1 chr22 27748277 27801756 +2630977 PITPNB chr22 27851669 27920134 +2631155 TTC28-AS1 chr22 27919376 28008581 +2631334 TTC28 chr22 27978014 28679865 +2631470 CHEK2 chr22 28687743 28742422 +2632093 HSCB chr22 28742039 28757515 +2632191 CCDC117 chr22 28772674 28789301 +2632268 XBP1 chr22 28794555 28800597 +2632353 Z93930.2 chr22 28800683 28848559 +2632370 Z93930.3 chr22 28814914 28815662 +2632373 ZNRF3 chr22 28883572 29057488 +2632440 ZNRF3-IT1 chr22 28992721 29018620 +2632444 ZNRF3-AS1 chr22 29024999 29031476 +2632449 C22orf31 chr22 29058672 29061844 +2632461 KREMEN1 chr22 29073078 29168333 +2632550 AL021393.1 chr22 29099041 29111683 +2632554 EMID1 chr22 29205896 29259597 +2632750 RHBDD3 chr22 29259872 29268209 +2632823 AL031186.1 chr22 29260889 29262037 +2632827 EWSR1 chr22 29268009 29300525 +2633288 GAS2L1 chr22 29306582 29312785 +2633410 RASL10A chr22 29312933 29319679 +2633438 AC002059.1 chr22 29316744 29317220 +2633441 AP1B1 chr22 29327680 29423179 +2633780 RFPL1S chr22 29436534 29478868 +2633813 RFPL1 chr22 29438583 29442455 +2633823 NEFH chr22 29480218 29491390 +2633837 AC000035.1 chr22 29480220 29481113 +2633841 THOC5 chr22 29505879 29555216 +2634249 AC005529.1 chr22 29513889 29535390 +2634253 NIPSNAP1 chr22 29554808 29581327 +2634341 NF2 chr22 29603556 29698598 +2634853 AC004882.1 chr22 29705256 29719859 +2634861 AC004882.2 chr22 29711820 29719714 +2634865 CABP7 chr22 29720003 29731833 +2634881 ZMAT5 chr22 29730956 29767011 +2634902 AC004882.3 chr22 29767091 29768096 +2634907 UQCR10 chr22 29767369 29770413 +2634926 ASCC2 chr22 29788609 29838304 +2635254 MTMR3 chr22 29883155 30030866 +2635513 AC003681.1 chr22 29978950 30028236 +2635516 HORMAD2-AS1 chr22 30008742 30080480 +2635531 HORMAD2 chr22 30080174 30177075 +2635614 AC002378.1 chr22 30182818 30207195 +2635619 LIF-AS1 chr22 30239194 30240538 +2635624 LIF chr22 30240453 30246759 +2635645 AC004264.1 chr22 30246205 30246998 +2635648 OSM chr22 30262829 30266851 +2635680 CASTOR1 chr22 30285117 30289627 +2635836 TBC1D10A chr22 30291990 30327046 +2635986 SF3A1 chr22 30331988 30356919 +2636081 CCDC157 chr22 30356635 30378658 +2636190 RNF215 chr22 30368811 30421771 +2636297 SEC14L2 chr22 30396941 30425303 +2636537 AC004832.5 chr22 30420512 30420912 +2636540 AC004832.4 chr22 30421206 30421536 +2636543 MTFP1 chr22 30425623 30429054 +2636608 AC004832.6 chr22 30435544 30436247 +2636614 SEC14L3 chr22 30447959 30472049 +2636816 AC004832.1 chr22 30475364 30492804 +2636840 SEC14L4 chr22 30488902 30505711 +2636960 SEC14L6 chr22 30522799 30546682 +2637000 GAL3ST1 chr22 30554635 30574665 +2637241 PES1 chr22 30576625 30607083 +2637482 AC005006.1 chr22 30598309 30606687 +2637487 TCN2 chr22 30607003 30627271 +2637592 SLC35E4 chr22 30635781 30669016 +2637622 DUSP18 chr22 30652051 30667890 +2637712 OSBP2 chr22 30693782 30907824 +2638098 MORC2-AS1 chr22 30922308 30932449 +2638120 MORC2 chr22 30925130 30968774 +2638272 TUG1 chr22 30969245 30979395 +2638352 AC004542.2 chr22 30976515 30978848 +2638356 AC004542.1 chr22 30977516 30977858 +2638360 AC005005.4 chr22 31051630 31068327 +2638363 SMTN chr22 31064105 31104757 +2638830 AC005005.3 chr22 31082156 31083565 +2638833 SELENOM chr22 31104772 31120069 +2638921 INPP5J chr22 31122731 31134697 +2639202 PLA2G3 chr22 31134807 31140508 +2639222 RNF185 chr22 31160182 31207019 +2639316 RNF185-AS1 chr22 31205264 31205616 +2639319 LIMK2 chr22 31212239 31280080 +2639489 PIK3IP1 chr22 31281594 31292534 +2639557 PIK3IP1-AS1 chr22 31292499 31338021 +2639564 PATZ1 chr22 31325804 31346346 +2639625 LINC01521 chr22 31346777 31348719 +2639630 DRG1 chr22 31399604 31530634 +2639708 EIF4ENIF1 chr22 31436977 31496108 +2639962 AL096701.3 chr22 31452881 31464304 +2639972 SFI1 chr22 31488688 31618588 +2640587 AL096701.4 chr22 31490150 31491022 +2640590 PISD chr22 31618491 31662432 +2640802 PRR14L chr22 31676256 31750140 +2640883 DEPDC5 chr22 31753867 31908033 +2643866 C22orf24 chr22 31926214 31945518 +2643891 YWHAH chr22 31944522 31957603 +2643937 AL008719.1 chr22 31963357 31970400 +2643941 LINC02558 chr22 31970823 32037995 +2643959 SLC5A1 chr22 32043261 32113029 +2644039 Z83839.2 chr22 32141267 32143272 +2644043 C22orf42 chr22 32149006 32159322 +2644079 AL008723.1 chr22 32159454 32160392 +2644083 RFPL2 chr22 32190435 32205001 +2644153 IGLCOR22-1 chr22 32199919 32200234 +2644156 SLC5A4-AS1 chr22 32205115 32278382 +2644169 SLC5A4 chr22 32218476 32255341 +2644205 AL008723.2 chr22 32284683 32285131 +2644208 AL021937.3 chr22 32327064 32343105 +2644219 RFPL3 chr22 32354885 32361161 +2644240 IGLCOR22-2 chr22 32356676 32356988 +2644243 RFPL3S chr22 32359886 32382106 +2644295 IGLVIVOR22-2 chr22 32376682 32377135 +2644299 AL021937.4 chr22 32383786 32385631 +2644303 RTCB chr22 32387582 32412248 +2644358 BPIFC chr22 32413847 32464484 +2644474 FBXO7 chr22 32474676 32498829 +2644611 SYN3 chr22 32512552 33058372 +2644725 Z82246.1 chr22 32583300 32584204 +2644729 Z73495.1 chr22 32783177 32784982 +2644733 TIMP3 chr22 32801701 32863043 +2644749 LINC01640 chr22 33104330 33145861 +2644771 Z82198.1 chr22 33105383 33106059 +2644775 LARGE1 chr22 33162226 33922841 +2645005 Z82198.2 chr22 33164063 33166439 +2645009 Z82173.1 chr22 33320865 33322813 +2645013 LARGE-IT1 chr22 33723832 33724912 +2645017 LARGE-AS1 chr22 33725007 33750843 +2645099 Z73429.1 chr22 33922422 33922766 +2645102 LINC01643 chr22 34017422 34218796 +2645415 Z68323.1 chr22 34191194 34210564 +2645426 AL021877.2 chr22 34641179 34651862 +2645429 Z82196.1 chr22 34703126 34704885 +2645434 Z82196.2 chr22 34711908 34724919 +2645440 AL024495.1 chr22 34756676 35002862 +2645450 ISX chr22 35066136 35087387 +2645479 Z99755.2 chr22 35122661 35127419 +2645483 HMGXB4 chr22 35257452 35295807 +2645580 AL008635.1 chr22 35298838 35299541 +2645584 TOM1 chr22 35299275 35347992 +2645957 Z82244.2 chr22 35372174 35372621 +2645960 Z82244.1 chr22 35376422 35377261 +2645963 HMOX1 chr22 35380361 35394207 +2645997 MCM5 chr22 35400134 35425431 +2646146 AL022334.2 chr22 35526932 35527415 +2646149 RASD2 chr22 35540831 35553999 +2646161 MB chr22 35606764 35637951 +2646274 AL049747.1 chr22 35626988 35635134 +2646278 APOL6 chr22 35648446 35668404 +2646290 AL049748.1 chr22 35685940 35689373 +2646294 APOL5 chr22 35717872 35729483 +2646309 RBFOX2 chr22 35738736 36028824 +2646634 Z82217.1 chr22 35992321 36000469 +2646637 Z95114.4 chr22 36066533 36070110 +2646640 Z95114.1 chr22 36071000 36085573 +2646643 Z95114.2 chr22 36091148 36093352 +2646646 APOL3 chr22 36140330 36166177 +2646851 APOL4 chr22 36189124 36204840 +2646998 APOL2 chr22 36226209 36239954 +2647089 APOL1 chr22 36253010 36267530 +2647277 MYH9 chr22 36281277 36388067 +2647427 Z82215.1 chr22 36335421 36343530 +2647431 FO393418.1 chr22 36388626 36396517 +2647435 AL022313.2 chr22 36445395 36454944 +2647439 TXN2 chr22 36467046 36481640 +2647496 FOXRED2 chr22 36487190 36507101 +2647576 EIF3D chr22 36510855 36529184 +2647747 AL022313.3 chr22 36552165 36552700 +2647751 AL022313.4 chr22 36560870 36562915 +2647754 CACNG2 chr22 36563921 36703558 +2647771 AL049749.1 chr22 36703918 36721472 +2647775 Z80897.2 chr22 36754086 36755731 +2647779 IFT27 chr22 36758202 36776256 +2647903 Z80897.1 chr22 36766478 36769022 +2647907 PVALB chr22 36800684 36819479 +2647977 Z82185.1 chr22 36816326 36819736 +2647982 NCF4-AS1 chr22 36847372 36870441 +2647989 NCF4 chr22 36860988 36878017 +2648122 CSF2RB chr22 36913628 36940439 +2648239 Z82180.1 chr22 36965248 36968172 +2648245 TEX33 chr22 36991120 37007851 +2648310 TST chr22 37010859 37020183 +2648349 MPST chr22 37019635 37029822 +2648435 Z73420.1 chr22 37033124 37035513 +2648439 KCTD17 chr22 37051736 37063390 +2648555 TMPRSS6 chr22 37065436 37109713 +2648769 AL022314.1 chr22 37080068 37082847 +2648774 IL2RB chr22 37125843 37175054 +2648865 Z82188.2 chr22 37166757 37182850 +2648869 C1QTNF6 chr22 37180166 37199385 +2648933 SSTR3 chr22 37204237 37212477 +2648952 RAC2 chr22 37225270 37244448 +2649044 CYTH4 chr22 37282027 37315341 +2649183 FP325335.1 chr22 37339583 37427445 +2649192 Z94160.1 chr22 37352190 37355002 +2649200 ELFN2 chr22 37367960 37427479 +2649243 Z94160.2 chr22 37371684 37372858 +2649247 MFNG chr22 37469063 37486393 +2649369 CARD10 chr22 37490362 37519542 +2649574 AL022315.1 chr22 37550026 37551735 +2649578 CDC42EP1 chr22 37560480 37569405 +2649613 LGALS2 chr22 37570248 37582616 +2649638 GGA1 chr22 37608725 37633564 +2649994 SH3BP1 chr22 37634654 37656119 +2650179 Z83844.2 chr22 37641832 37658377 +2650187 PDXP chr22 37658723 37666932 +2650206 LGALS1 chr22 37675636 37679802 +2650264 NOL12 chr22 37681673 37693476 +2650343 TRIOBP chr22 37697048 37776556 +2650579 H1F0 chr22 37805093 37807436 +2650587 GCAT chr22 37807905 37817176 +2650677 GALR3 chr22 37823382 37825485 +2650687 ANKRD54 chr22 37830855 37849327 +2650858 EIF3L chr22 37848868 37889407 +2651122 AL022311.1 chr22 37876148 37895563 +2651125 MICALL1 chr22 37905657 37942822 +2651224 C22orf23 chr22 37943050 37953669 +2651325 AL031587.3 chr22 37950965 37951778 +2651328 POLR2F chr22 37952607 38041915 +2651517 SOX10 chr22 37970686 37987422 +2651579 AL031587.1 chr22 38032165 38034228 +2651583 AL031587.4 chr22 38043230 38043920 +2651586 PICK1 chr22 38056311 38075701 +2651788 AL031587.2 chr22 38057180 38073940 +2651792 SLC16A8 chr22 38078134 38084093 +2651822 BAIAP2L2 chr22 38084900 38110684 +2651902 AL022322.1 chr22 38090127 38091559 +2651905 PLA2G6 chr22 38111495 38214778 +2652624 AL022322.2 chr22 38130216 38150612 +2652627 MAFF chr22 38200767 38216507 +2652699 TMEM184B chr22 38219291 38273010 +2652847 AL020993.1 chr22 38231320 38232248 +2652851 CSNK1E chr22 38290691 38318084 +2653069 Z98749.1 chr22 38387918 38388857 +2653073 Z97056.2 chr22 38416565 38423933 +2653079 Z97056.1 chr22 38424288 38427336 +2653084 KCNJ4 chr22 38426327 38455199 +2653094 Z97056.3 chr22 38434307 38436686 +2653099 KDELR3 chr22 38468078 38483447 +2653134 DDX17 chr22 38483438 38507660 +2653309 DMC1 chr22 38518948 38570204 +2653441 FAM227A chr22 38578120 38656629 +2653624 CBY1 chr22 38656636 38673854 +2653725 AL021707.4 chr22 38666508 38668750 +2653729 AL021707.2 chr22 38667585 38681847 +2653751 AL021707.9 chr22 38675876 38677800 +2653755 TOMM22 chr22 38681957 38685421 +2653773 JOSD1 chr22 38685543 38701556 +2653842 GTPBP1 chr22 38705742 38738299 +2653976 AL021707.5 chr22 38734725 38738765 +2653980 SUN2 chr22 38734725 38794143 +2654262 AL021707.3 chr22 38734730 38738990 +2654267 AL021707.8 chr22 38736610 38736792 +2654270 AL021707.1 chr22 38739003 38749041 +2654274 AL021707.6 chr22 38742625 38743115 +2654277 AL021707.7 chr22 38743495 38743910 +2654280 DNAL4 chr22 38778508 38794198 +2654311 NPTXR chr22 38818452 38844028 +2654340 CBX6 chr22 38861422 38872249 +2654376 AL022318.5 chr22 38886837 38903794 +2654380 AL022318.1 chr22 38921227 38924708 +2654384 APOBEC3A chr22 38952741 38992778 +2654438 APOBEC3B chr22 38982347 38992804 +2654519 APOBEC3B-AS1 chr22 38991559 38998209 +2654526 APOBEC3C chr22 39014257 39020352 +2654551 APOBEC3D chr22 39021113 39033277 +2654597 APOBEC3F chr22 39040604 39055972 +2654636 APOBEC3G chr22 39077067 39087743 +2654681 APOBEC3H chr22 39097224 39104067 +2654770 CBX7 chr22 39120167 39152680 +2654828 AL031846.2 chr22 39133090 39136760 +2654831 PDGFB chr22 39223359 39244982 +2654896 AL031590.1 chr22 39242188 39279897 +2654908 AL022326.1 chr22 39292988 39295589 +2654916 RPL3 chr22 39312882 39320389 +2655072 SYNGR1 chr22 39349925 39385575 +2655152 TAB1 chr22 39399778 39437060 +2655226 MGAT3 chr22 39457012 39492194 +2655251 MGAT3-AS1 chr22 39475807 39476822 +2655255 MIEF1 chr22 39499432 39518132 +2655390 AL022312.1 chr22 39504231 39504443 +2655397 ATF4 chr22 39519695 39522685 +2655431 RPS19BP1 chr22 39529093 39532761 +2655474 CACNA1I chr22 39570753 39689735 +2655782 ENTHD1 chr22 39743044 39893864 +2655805 GRAP2 chr22 39901084 39973721 +2655871 Z82206.1 chr22 39960397 39964718 +2655881 FAM83F chr22 39994954 40043534 +2655916 Z83847.1 chr22 40043068 40044530 +2655919 TNRC6B chr22 40044817 40335808 +2656185 ADSL chr22 40346500 40390463 +2656571 SGSM3 chr22 40370591 40410289 +2656742 AL022238.2 chr22 40372664 40388290 +2656756 MRTFA chr22 40410281 40636719 +2657107 AL022238.3 chr22 40415003 40415445 +2657110 MRTFA-AS1 chr22 40521800 40526707 +2657116 MCHR1 chr22 40678750 40682814 +2657143 SLC25A17 chr22 40769630 40819399 +2657436 ST13 chr22 40824535 40856639 +2657558 XPNPEP3 chr22 40857077 40932815 +2657632 DNAJB7 chr22 40859549 40862113 +2657640 RBX1 chr22 40951347 40973309 +2657663 EP300 chr22 41092592 41180077 +2657779 AL035658.1 chr22 41169190 41183144 +2657784 EP300-AS1 chr22 41174591 41197456 +2657789 L3MBTL2 chr22 41205282 41231271 +2657966 AL035681.1 chr22 41207592 41228500 +2657983 CHADL chr22 41229510 41240931 +2658023 RANGAP1 chr22 41245611 41286251 +2658183 ZC3H7B chr22 41301525 41360147 +2658243 TEF chr22 41367333 41399326 +2658277 AL008582.1 chr22 41430934 41431375 +2658280 TOB2 chr22 41433494 41446801 +2658297 PHF5A chr22 41459717 41468692 +2658321 ACO2 chr22 41469117 41528989 +2658426 POLR3H chr22 41525799 41544606 +2658555 AL023553.1 chr22 41551710 41560905 +2658559 CSDC2 chr22 41561010 41577741 +2658582 PMM1 chr22 41576900 41589871 +2658662 DESI1 chr22 41598028 41621043 +2658690 XRCC6 chr22 41621119 41664048 +2658877 SNU13 chr22 41673933 41690504 +2659007 MEI1 chr22 41699503 41799456 +2659232 CCDC134 chr22 41800679 41826299 +2659265 SREBF2-AS1 chr22 41831215 41834665 +2659269 SREBF2 chr22 41833079 41907307 +2659446 SHISA8 chr22 41909554 41914667 +2659464 TNFRSF13C chr22 41922023 41926818 +2659476 CENPM chr22 41938737 41947152 +2659569 LINC00634 chr22 41952174 41958933 +2659586 SEPTIN3 chr22 41969475 41998221 +2659735 Z99716.1 chr22 41981304 41982217 +2659740 WBP2NL chr22 41998725 42058456 +2659878 NAGA chr22 42058334 42070842 +2659952 Z99716.2 chr22 42070949 42071488 +2659955 PHETA2 chr22 42074248 42079438 +2659976 SMDT1 chr22 42079691 42084284 +2660002 NDUFA6 chr22 42085526 42090884 +2660034 AL021878.2 chr22 42089630 42090028 +2660037 NDUFA6-DT chr22 42090931 42137742 +2660133 CYP2D6 chr22 42126499 42130881 +2660229 AC254562.2 chr22 42136433 42139927 +2660234 AC254562.3 chr22 42138060 42139726 +2660238 TCF20 chr22 42160013 42343616 +2660288 OGFRP1 chr22 42269703 42279534 +2660307 LINC01315 chr22 42364390 42369284 +2660323 NFAM1 chr22 42380410 42432395 +2660352 AL022316.1 chr22 42438023 42446195 +2660358 RRP7A chr22 42508344 42519796 +2660400 SERHL2 chr22 42553617 42574382 +2660595 POLDIP3 chr22 42583721 42614962 +2660738 Z93241.1 chr22 42615244 42615907 +2660741 CYB5R3 chr22 42617840 42649392 +2660882 ATP5MGL chr22 42639803 42640601 +2660890 A4GALT chr22 42692121 42721298 +2660941 ARFGAP3 chr22 42796502 42858106 +2661060 PACSIN2 chr22 42835412 43015149 +2661275 AL022476.1 chr22 43038585 43052366 +2661280 TTLL1 chr22 43039516 43089419 +2661386 BIK chr22 43110750 43129712 +2661402 MCAT chr22 43132209 43143398 +2661437 TSPO chr22 43151547 43163242 +2661500 TTLL12 chr22 43166622 43187134 +2661555 SCUBE1 chr22 43197280 43343372 +2661675 Z82214.2 chr22 43212674 43213661 +2661679 Z82214.1 chr22 43232141 43239010 +2661684 Z99756.1 chr22 43275955 43283830 +2661688 LINC01639 chr22 43400331 43409681 +2661694 MPPED1 chr22 43411196 43507848 +2661757 BX546033.1 chr22 43507824 43513727 +2661761 EFCAB6-AS1 chr22 43516107 43560063 +2661770 EFCAB6 chr22 43528744 43812337 +2661979 Z97055.2 chr22 43812456 43817394 +2661985 SULT4A1 chr22 43824509 43862513 +2662047 PNPLA5 chr22 43879678 43892013 +2662145 PNPLA3 chr22 43923792 43964488 +2662227 SAMM50 chr22 43955442 44010531 +2662291 PARVB chr22 43999211 44172949 +2662455 AL033543.1 chr22 44102779 44116232 +2662458 AL031595.3 chr22 44139365 44153626 +2662461 PARVG chr22 44172956 44219533 +2662648 AL031595.2 chr22 44210442 44229512 +2662651 SHISAL1 chr22 44243665 44312951 +2662668 Z85994.1 chr22 44365551 44366284 +2662672 LINC01656 chr22 44443327 44444788 +2662677 RTL6 chr22 44492583 44498233 +2662687 LINC00207 chr22 44569295 44572453 +2662715 LINC00229 chr22 44606939 44625419 +2662721 PRR5 chr22 44668547 44737681 +2662998 ARHGAP8 chr22 44752558 44862788 +2663192 PHF21B chr22 44881162 45010005 +2663375 AL079301.1 chr22 45000565 45003619 +2663380 NUP50-DT chr22 45133020 45163781 +2663395 Z82243.1 chr22 45155539 45156011 +2663398 NUP50 chr22 45163925 45188017 +2663596 AL008718.3 chr22 45178990 45179310 +2663599 KIAA0930 chr22 45190338 45240769 +2663803 AL008718.2 chr22 45262273 45263585 +2663806 UPK3A chr22 45284949 45295874 +2663837 FAM118A chr22 45308968 45341955 +2663976 SMC1B chr22 45344063 45413619 +2664083 RIBC2 chr22 45413693 45432509 +2664112 AL021391.1 chr22 45435864 45448743 +2664116 FBLN1 chr22 45502238 45601135 +2664414 LINC01589 chr22 45604432 45605621 +2664418 Z95331.1 chr22 45657019 45680130 +2664421 ATXN10 chr22 45671798 45845307 +2664560 BX324167.2 chr22 45875932 45879247 +2664563 BX324167.1 chr22 45875999 45891438 +2664573 WNT7B chr22 45920366 45977162 +2664635 BX537318.1 chr22 46013606 46015498 +2664639 LINC00899 chr22 46039907 46044853 +2664651 PRR34 chr22 46049478 46054144 +2664655 AL121672.3 chr22 46053093 46053560 +2664658 PRR34-AS1 chr22 46053705 46057210 +2664672 MIRLET7BHG chr22 46053869 46113928 +2664696 AL121672.1 chr22 46055740 46058160 +2664700 AL121672.2 chr22 46067356 46069891 +2664705 PPARA chr22 46150521 46243756 +2664824 FP325332.1 chr22 46163303 46165347 +2664827 CDPF1 chr22 46244011 46250311 +2664885 PKDREJ chr22 46255663 46263343 +2664893 TTC38 chr22 46267961 46294008 +2665004 GTSE1-DT chr22 46295143 46296660 +2665009 GTSE1 chr22 46296870 46330810 +2665051 TRMU chr22 46330875 46357340 +2665402 CELSR1 chr22 46360834 46537170 +2665497 AL021392.1 chr22 46541495 46548196 +2665501 GRAMD4 chr22 46576012 46679790 +2665637 CERK chr22 46684410 46738252 +2665706 AL118516.1 chr22 46761894 46762563 +2665709 TBC1D22A chr22 46762617 47175699 +2665952 TBC1D22A-AS1 chr22 46914092 46916042 +2665957 Z82186.1 chr22 47345569 47373541 +2665963 LINC01644 chr22 47461299 47487111 +2665971 LINC00898 chr22 47612231 47631569 +2665995 AL117329.1 chr22 47630827 48023004 +2666534 FP325330.3 chr22 47916728 47926264 +2666537 FP325330.1 chr22 48044710 48048549 +2666541 FP325330.2 chr22 48052646 48058275 +2666544 BX284656.2 chr22 48139461 48141001 +2666548 BX284656.1 chr22 48141542 48143229 +2666554 AL008720.1 chr22 48254903 48259116 +2666559 Z72006.1 chr22 48403462 48415571 +2666566 Z82249.1 chr22 48448890 48451217 +2666570 Z84468.2 chr22 48474135 48489324 +2666592 TAFA5 chr22 48489460 48850912 +2666645 Z84468.1 chr22 48538900 48547387 +2666659 LINC01310 chr22 48866770 48898386 +2666672 AL078622.1 chr22 49047484 49052549 +2666688 Z82202.2 chr22 49166421 49188062 +2666693 Z82202.1 chr22 49264201 49266080 +2666696 AC207130.1 chr22 49372924 49377119 +2666700 C22orf34 chr22 49414524 49657542 +2666738 AL008636.1 chr22 49500568 49501585 +2666741 AL031593.1 chr22 49534062 49534926 +2666744 Z97192.1 chr22 49548681 49556473 +2666748 Z97192.2 chr22 49572264 49575426 +2666752 Z97192.3 chr22 49612657 49615716 +2666756 Z97192.4 chr22 49662312 49664968 +2666760 AL023802.1 chr22 49718053 49724506 +2666764 BRD1 chr22 49773283 49827512 +2666921 Z98885.3 chr22 49805452 49807208 +2666924 Z98885.2 chr22 49832449 49838901 +2666938 AL117328.2 chr22 49851425 49853364 +2666941 ZBED4 chr22 49853844 49890080 +2666951 ALG12 chr22 49900229 49918438 +2667003 AL671710.1 chr22 49902228 49904576 +2667006 CRELD2 chr22 49918167 49927540 +2667158 BX539320.1 chr22 49933198 49934074 +2667161 PIM3 chr22 49960768 49964072 +2667183 IL17REL chr22 49994513 50012659 +2667250 TTLL8 chr22 50015123 50056935 +2667317 MLC1 chr22 50059391 50085902 +2667405 MOV10L1 chr22 50089879 50161690 +2667722 AL034546.1 chr22 50092745 50096437 +2667725 PANX2 chr22 50170731 50180295 +2667761 TRABD chr22 50185915 50199598 +2667875 AL022328.3 chr22 50191724 50192402 +2667878 AL022328.4 chr22 50199090 50200837 +2667882 SELENOO chr22 50200979 50217616 +2667941 AL022328.1 chr22 50205585 50206062 +2667944 AL022328.2 chr22 50208461 50209542 +2667948 TUBGCP6 chr22 50217689 50245023 +2668149 HDAC10 chr22 50245183 50251405 +2668547 MAPK12 chr22 50245450 50261716 +2668717 MAPK11 chr22 50263713 50270767 +2668812 PLXNB2 chr22 50274979 50307646 +2669167 DENND6B chr22 50309030 50327012 +2669273 CR559946.1 chr22 50314631 50316008 +2669277 CR559946.2 chr22 50316035 50317025 +2669280 PPP6R2 chr22 50343304 50445090 +2669616 SBF1 chr22 50445000 50475035 +2669838 ADM2 chr22 50481543 50486440 +2669859 MIOX chr22 50486784 50490648 +2669952 LMF2 chr22 50502949 50507702 +2670042 NCAPH2 chr22 50508224 50524780 +2670289 SCO2 chr22 50523568 50526461 +2670333 U62317.2 chr22 50523926 50524780 +2670336 TYMP chr22 50525752 50530032 +2670576 ODF3B chr22 50529710 50532580 +2670682 U62317.4 chr22 50541108 50543011 +2670686 U62317.1 chr22 50542305 50542906 +2670689 KLHDC7B chr22 50545899 50551023 +2670707 SYCE3 chr22 50551112 50562919 +2670727 CPT1B chr22 50568861 50578465 +2670989 CHKB chr22 50578949 50601455 +2671100 CHKB-DT chr22 50583026 50595634 +2671135 U62317.3 chr22 50597152 50597599 +2671138 MAPK8IP2 chr22 50600793 50613981 +2671179 ARSA chr22 50622754 50628173 +2671307 AC000050.1 chr22 50672714 50674174 +2671311 SHANK3 chr22 50674415 50733298 +2671468 AC000036.1 chr22 50735825 50738139 +2671472 ACR chr22 50738196 50745339 +2671508 AC002056.2 chr22 50740593 50743520 +2671512 RABL2B chr22 50767501 50783663 +2671751 PLCXD1 chrX 276322 303356 +2671898 GTPBP6 chrX 304529 318819 +2671929 LINC00685 chrX 320990 321851 +2671933 PPP2R3B chrX 333933 386955 +2672022 AL732314.6 chrX 386980 405579 +2672026 AL732314.4 chrX 419157 421980 +2672030 SHOX chrX 624344 659411 +2672080 AL672277.1 chrX 990221 994365 +2672084 CRLF2 chrX 1187549 1212723 +2672169 CSF2RA chrX 1268800 1310381 +2672532 IL3RA chrX 1336616 1382689 +2672600 SLC25A6 chrX 1386152 1392113 +2672624 LINC00106 chrX 1396427 1399402 +2672632 ASMTL-AS1 chrX 1401769 1414028 +2672653 ASMTL chrX 1403139 1453762 +2672756 P2RY8 chrX 1462581 1537185 +2672773 AKAP17A chrX 1591604 1602520 +2672819 ASMT chrX 1615059 1643081 +2672893 AL683807.1 chrX 1732584 1763212 +2672902 AL683807.2 chrX 1767347 1768776 +2672906 DHRSX chrX 2219506 2502805 +2672980 DHRSX-IT1 chrX 2334295 2336410 +2672984 ZBED1 chrX 2486414 2500976 +2673031 LINC00102 chrX 2612988 2615347 +2673035 CD99 chrX 2691187 2741309 +2673265 XG chrX 2752048 2816500 +2673370 GYG2 chrX 2828822 2882820 +2673516 GYG2-AS1 chrX 2852740 2853760 +2673520 ARSD chrX 2903972 2929349 +2673592 ARSD-AS1 chrX 2904904 2906081 +2673596 ARSE chrX 2934521 2968475 +2673819 ARSH chrX 3006613 3033571 +2673842 ARSF chrX 3041471 3112727 +2673897 LINC01546 chrX 3271544 3286138 +2673915 MXRA5 chrX 3308565 3346652 +2673935 PRKX chrX 3604340 3713649 +2673974 PRKX-AS1 chrX 3659487 3668192 +2673979 BX890604.2 chrX 3817528 3937855 +2674127 BX842570.1 chrX 3819924 3823898 +2674131 AC074035.1 chrX 4627200 4633572 +2674136 AC110995.1 chrX 5653418 5726326 +2674153 NLGN4X chrX 5840637 6228867 +2674258 VCX3A chrX 6533618 6535118 +2674298 PUDP chrX 6667865 7148190 +2674372 STS chrX 7147237 7804358 +2674494 VCX chrX 7842262 7844143 +2674534 PNPLA4 chrX 7898247 7927739 +2674605 AC079142.1 chrX 7928443 8374386 +2674623 VCX2 chrX 8169944 8171267 +2674635 VCX3B chrX 8464830 8466510 +2674688 AC006062.1 chrX 8487165 8504564 +2674695 ANOS1 chrX 8528874 8732137 +2674736 FAM9A chrX 8790795 8801383 +2674787 AC003685.1 chrX 8863861 8867601 +2674792 AC074281.2 chrX 8897642 8927153 +2674798 FAM9B chrX 9024232 9295682 +2674933 AC003684.1 chrX 9249920 9275206 +2674937 TBL1X chrX 9463295 9741037 +2675288 GPR143 chrX 9725346 9786297 +2675353 SHROOM2 chrX 9786429 9949443 +2675415 CLDN34 chrX 9967358 9968352 +2675422 WWC3 chrX 10015562 10144478 +2675477 WWC3-AS1 chrX 10024842 10038654 +2675481 CLCN4 chrX 10156945 10237660 +2675584 AC003666.1 chrX 10242339 10365323 +2675591 MID1 chrX 10445310 10833654 +2675831 AC073529.1 chrX 10847578 11111220 +2675866 HCCS chrX 11111301 11123086 +2675924 ARHGAP6 chrX 11117651 11665920 +2676158 AMELX chrX 11293413 11300761 +2676210 AC004554.2 chrX 11668401 11757718 +2676216 MSL3 chrX 11758159 11775772 +2677123 FRMPD4 chrX 11822423 12724523 +2677453 FRMPD4-AS1 chrX 12373167 12375133 +2677457 PRPS2 chrX 12791355 12824222 +2677533 TLR7 chrX 12867072 12890361 +2677548 TLR8-AS1 chrX 12902817 12908333 +2677553 TLR8 chrX 12906620 12923169 +2677574 TMSB4X chrX 12975110 12977227 +2677617 FAM9C chrX 13035617 13044682 +2677696 AC079171.1 chrX 13093660 13094573 +2677699 LINC02154 chrX 13266048 13303452 +2677710 AC004674.1 chrX 13310652 13319933 +2677729 ATXN3L chrX 13318236 13320399 +2677747 LINC01203 chrX 13333952 13403035 +2677948 EGFL6 chrX 13569601 13633575 +2678011 TCEANC chrX 13653189 13681964 +2678050 RAB9A chrX 13689128 13710504 +2678080 TRAPPC2 chrX 13712244 13734635 +2678168 OFD1 chrX 13734745 13769357 +2678419 GPM6B chrX 13770939 13938638 +2678587 AC003035.2 chrX 13955393 13963904 +2678591 AC003035.1 chrX 13980066 13988820 +2678595 GEMIN8 chrX 14008279 14029893 +2678645 GLRA2 chrX 14529298 14731812 +2678734 FANCB chrX 14835961 14873069 +2678886 MOSPD2 chrX 14873421 14922327 +2678997 ASB9 chrX 15235288 15270467 +2679114 ASB11 chrX 15281697 15315640 +2679192 PIGA chrX 15319451 15335580 +2679398 VEGFD chrX 15345596 15384413 +2679421 PIR chrX 15384799 15493564 +2679492 BMX chrX 15464246 15556529 +2679636 ACE2 chrX 15561033 15602148 +2679734 AC097625.1 chrX 15602881 15621484 +2679738 CLTRN chrX 15627318 15675012 +2679775 CA5B chrX 15688830 15788411 +2679867 INE2 chrX 15785716 15787589 +2679870 ZRSR2 chrX 15790472 15823260 +2679916 AP1S2 chrX 15825806 15854931 +2680089 GRPR chrX 16123565 16153518 +2680101 AC078993.1 chrX 16152941 16170869 +2680120 MAGEB17 chrX 16167481 16171464 +2680141 CTPS2 chrX 16587999 16712936 +2680287 S100G chrX 16650158 16654670 +2680299 SYAP1 chrX 16719612 16765340 +2680327 TXLNG chrX 16786432 16844519 +2680377 RBBP7 chrX 16839283 16870414 +2680543 REPS2 chrX 16946658 17153272 +2680639 NHS chrX 17375420 17735994 +2680738 Z93022.1 chrX 17528435 17587160 +2680742 NHS-AS1 chrX 17552349 17557387 +2680746 SCML1 chrX 17737449 17754988 +2680845 RAI2 chrX 17800049 17861337 +2680908 LINC01456 chrX 17970197 18104644 +2680915 BEND2 chrX 18162931 18220886 +2680975 SCML2 chrX 18239313 18354688 +2681057 CDKL5 chrX 18425583 18653629 +2681346 RS1 chrX 18639910 18672109 +2681370 PPEF1 chrX 18675909 18827921 +2681527 PPEF1-AS1 chrX 18688643 18691604 +2681531 PHKA2-AS1 chrX 18890296 18894974 +2681543 PHKA2 chrX 18892298 18984114 +2681651 AL732509.1 chrX 18984291 19060329 +2681667 ADGRG2 chrX 18989307 19122637 +2682270 PDHA1 chrX 19343893 19361718 +2682466 MAP3K15 chrX 19360056 19515261 +2682624 SH3KBP1 chrX 19533977 19887600 +2682849 BCLAF3 chrX 19912860 19970298 +2682963 MAP7D2 chrX 20006713 20116907 +2683116 EIF1AX chrX 20124525 20141838 +2683153 EIF1AX-AS1 chrX 20139968 20140444 +2683157 RPS6KA3 chrX 20149911 20267519 +2683847 AL928596.1 chrX 20311838 20317783 +2683851 AL807740.1 chrX 20443326 20492349 +2683857 AL807742.1 chrX 20769718 21374265 +2683893 BX088723.1 chrX 21131496 21163726 +2683898 CNKSR2 chrX 21372801 21654695 +2684882 KLHL34 chrX 21654690 21658330 +2684890 SMPX chrX 21705978 21758116 +2684938 MBTPS2 chrX 21839617 21885423 +2684992 YY2 chrX 21855987 21858740 +2685000 SMS chrX 21940709 21994837 +2685070 PHEX chrX 22032325 22251310 +2685125 PHEX-AS1 chrX 22162733 22172983 +2685132 PTCHD1-AS chrX 22191895 23293146 +2685150 CBLL2 chrX 22272943 22274461 +2685158 AC092832.2 chrX 22428132 22494713 +2685163 AC004470.1 chrX 22698457 22768966 +2685167 DDX53 chrX 22999960 23003589 +2685175 PTCHD1 chrX 23334849 23404374 +2685194 PRDX4 chrX 23664262 23686397 +2685257 ACOT9 chrX 23701055 23766475 +2685456 AC131011.1 chrX 23772992 23782956 +2685461 SAT1 chrX 23783173 23786226 +2685539 APOO chrX 23833353 23907938 +2685659 CXorf58 chrX 23907801 23939509 +2685719 KLHL15 chrX 23983720 24027186 +2685733 EIF2S3 chrX 24054946 24078810 +2685786 ZFX-AS1 chrX 24146225 24149654 +2685791 ZFX chrX 24149173 24216255 +2685939 PDK3 chrX 24465221 24550466 +2686028 PCYT1B chrX 24558087 24672677 +2686113 PCYT1B-AS1 chrX 24650073 24658237 +2686117 POLA1 chrX 24693909 24996986 +2686446 ARX chrX 25003694 25016420 +2686476 AC121342.1 chrX 25878339 25893544 +2686482 MAGEB18 chrX 26138343 26140736 +2686494 MAGEB6B chrX 26160601 26161824 +2686501 MAGEB6 chrX 26192440 26195646 +2686511 MAGEB5 chrX 26216169 26218270 +2686521 VENTXP1 chrX 26558337 26561052 +2686524 AC112493.1 chrX 27042907 27176298 +2686535 AC107419.1 chrX 27174920 27399006 +2686588 PPP4R3C chrX 27460207 27463341 +2686596 DCAF8L2 chrX 27590382 27748821 +2686652 MAGEB10 chrX 27807990 27823014 +2686671 DCAF8L1 chrX 27977992 27981449 +2686679 AC112495.1 chrX 28571532 28586395 +2686684 IL1RAPL1 chrX 28587446 29956718 +2686725 AC003659.1 chrX 28942050 28942568 +2686729 MAGEB2 chrX 30215563 30220089 +2686739 MAGEB3 chrX 30230436 30237492 +2686762 MAGEB4 chrX 30242000 30244187 +2686770 MAGEB1 chrX 30243730 30252040 +2686804 NR0B1 chrX 30304206 30309390 +2686823 CXorf21 chrX 30558809 30577766 +2686835 GK chrX 30653359 30731456 +2687163 GK-IT1 chrX 30671635 30672166 +2687167 AC112496.1 chrX 30698207 30721932 +2687171 GK-AS1 chrX 30699998 30724174 +2687175 TAB3 chrX 30827442 30975084 +2687292 TAB3-AS1 chrX 30834623 30835300 +2687296 TAB3-AS2 chrX 30854321 30854707 +2687300 FTHL17 chrX 31071233 31072041 +2687308 DMD chrX 31097677 33339441 +2688681 AC079177.1 chrX 31411033 31413701 +2688685 DMD-AS3 chrX 32754940 32756400 +2688689 AL591378.1 chrX 33718958 33726013 +2688694 AL591501.1 chrX 33726337 34346527 +2688769 FAM47A chrX 34129756 34132314 +2688786 AL592043.1 chrX 34206725 34415537 +2688791 TMEM47 chrX 34627075 34657285 +2688803 FAM47B chrX 34942796 34944915 +2688811 MAGEB16 chrX 35798342 35803735 +2688861 CFAP47 chrX 35919734 36385317 +2689117 AL606516.1 chrX 36365626 36440292 +2689127 AL592156.2 chrX 36678678 36866689 +2689132 FAM47C chrX 37008397 37011666 +2689140 PRRG1 chrX 37349275 37457295 +2689241 LANCL3 chrX 37571569 37684463 +2689289 XK chrX 37685791 37732130 +2689301 CYBB chrX 37780011 37813461 +2689338 DYNLT3 chrX 37836757 37847571 +2689386 AL121578.3 chrX 37906147 37949405 +2689391 HYPM chrX 37990779 37991314 +2689399 AL121578.2 chrX 37994252 37994918 +2689407 SYTL5 chrX 38006553 38128819 +2689486 SRPX chrX 38149336 38220924 +2689589 AL606748.1 chrX 38221391 38223667 +2689593 RPGR chrX 38269170 38327544 +2690129 OTC chrX 38352586 38421446 +2690189 TSPAN7 chrX 38561370 38688920 +2690315 AF241728.1 chrX 38770331 38799658 +2690322 AF241728.2 chrX 38779584 38800678 +2690326 MID1IP1 chrX 38801432 38806537 +2690367 MID1IP1-AS1 chrX 38801568 38803883 +2690371 AC108879.1 chrX 39226103 39299786 +2690376 LINC01281 chrX 39304956 39327362 +2690389 LINC01282 chrX 39367285 39391807 +2690408 LINC01283 chrX 39401252 39434824 +2690414 AL592164.1 chrX 39837536 39848358 +2690418 AL592164.2 chrX 39908309 39914419 +2690422 AC092198.1 chrX 40009276 40012182 +2690426 BCOR chrX 40049815 40177329 +2690734 AC091806.1 chrX 40262917 40299061 +2690745 ATP6AP2 chrX 40579372 40606848 +2691248 AC092473.2 chrX 40620701 40622109 +2691252 MPC1L chrX 40623566 40624136 +2691259 CXorf38 chrX 40626921 40647561 +2691313 MED14 chrX 40648305 40735858 +2691432 MED14OS chrX 40735400 40738701 +2691436 AC092268.2 chrX 41008427 41029306 +2691440 USP9X chrX 41085445 41236579 +2691652 LINC02601 chrX 41275739 41276778 +2691656 DDX3X chrX 41333284 41364472 +2693267 NYX chrX 41447434 41475710 +2693291 CASK chrX 41514934 41923645 +2694226 CASK-AS1 chrX 41520036 41522336 +2694230 GPR34 chrX 41688973 41697275 +2694277 GPR82 chrX 41724181 41730130 +2694292 AL133329.1 chrX 42047883 42054836 +2694296 Z93403.1 chrX 42252459 42699385 +2694311 Z94277.1 chrX 42723209 42755892 +2694316 PPP1R2C chrX 42777366 42778163 +2694324 PINCR chrX 43176994 43226598 +2694332 AL023574.1 chrX 43279560 43438657 +2694342 MAOA chrX 43654907 43746824 +2694428 MAOB chrX 43766610 43882450 +2694476 NDP chrX 43948776 43973395 +2694505 NDP-AS1 chrX 43949732 43971582 +2694517 EFHC2 chrX 44147872 44343672 +2694559 FUNDC1 chrX 44523639 44542859 +2694580 DUSP21 chrX 44844021 44844888 +2694588 KDM6A chrX 44873177 45112602 +2695060 DIPK2B chrX 45148373 45200901 +2695094 AC136489.1 chrX 45183251 45333917 +2695112 LINC01204 chrX 45505388 45632121 +2695140 MIR222HG chrX 45745211 45770274 +2695147 AC234772.2 chrX 45764772 45765299 +2695150 LINC02595 chrX 45847042 45851541 +2695162 AL031584.3 chrX 45913267 45917040 +2695166 LINC01186 chrX 46256759 46327680 +2695189 AL139811.3 chrX 46400686 46402957 +2695193 KRBOX4 chrX 46447292 46497422 +2695297 ZNF674 chrX 46497727 46545457 +2695365 ZNF674-AS1 chrX 46545438 46548841 +2695376 CHST7 chrX 46573765 46598496 +2695386 SLC9A7 chrX 46599251 46759118 +2695481 RP2 chrX 46837043 46882358 +2695497 LINC01545 chrX 46887417 46899703 +2695507 JADE3 chrX 46912276 47061242 +2695590 RGN chrX 47078355 47093314 +2695677 NDUFB11 chrX 47142216 47145504 +2695700 RBM10 chrX 47145221 47186813 +2695922 UBA1 chrX 47190861 47215128 +2696151 INE1 chrX 47204921 47205865 +2696154 CDK16 chrX 47217860 47229997 +2696529 USP11 chrX 47232690 47248328 +2696714 AL591503.1 chrX 47297852 47298721 +2696718 ZNF157 chrX 47370583 47414305 +2696732 ZNF41 chrX 47445879 47482946 +2696779 LINC01560 chrX 47483571 47484823 +2696784 ARAF chrX 47561100 47571920 +2696889 SYN1 chrX 47571901 47619857 +2696978 TIMP1 chrX 47582408 47586789 +2697042 CFP chrX 47623172 47630305 +2697152 ELK1 chrX 47635521 47650604 +2697210 UXT chrX 47651796 47659180 +2697270 UXT-AS1 chrX 47658833 47692326 +2697290 ZNF81 chrX 47836902 48002561 +2697352 ZNF182 chrX 47974851 48003978 +2697389 ZNF630 chrX 47983356 48071658 +2697511 SPACA5 chrX 48004336 48009729 +2697540 ZNF630-AS1 chrX 48056310 48066583 +2697544 AC244636.3 chrX 48071226 48078721 +2697548 SPACA5B chrX 48130657 48132613 +2697562 SSX5 chrX 48186220 48196763 +2697636 SSX1 chrX 48255317 48267444 +2697658 AL606490.3 chrX 48333675 48334439 +2697662 SSX3 chrX 48346427 48356707 +2697725 SSX4 chrX 48383516 48393347 +2697766 SSX4B chrX 48402078 48411910 +2697807 SLC38A5 chrX 48458537 48470260 +2698108 FTSJ1 chrX 48476021 48486364 +2698261 AF196972.1 chrX 48506523 48508838 +2698265 PORCN chrX 48508962 48520814 +2698572 EBP chrX 48521799 48528716 +2698631 TBC1D25 chrX 48539714 48562609 +2698686 AC115618.1 chrX 48568014 48574860 +2698690 RBM3 chrX 48574449 48581162 +2698782 AC115618.2 chrX 48579774 48581157 +2698786 WDR13 chrX 48590042 48608869 +2698911 WAS chrX 48676596 48691427 +2698989 SUV39H1 chrX 48695554 48709012 +2699032 AC231533.1 chrX 48698963 48737163 +2699037 GLOD5 chrX 48761747 48773648 +2699068 GATA1 chrX 48786554 48794311 +2699118 HDAC6 chrX 48801377 48824982 +2699926 ERAS chrX 48826513 48830138 +2699943 PCSK1N chrX 48831096 48835610 +2699958 PQBP1 chrX 48890197 48903143 +2700174 TIMM17B chrX 48893447 48898143 +2700295 SLC35A2 chrX 48903180 48911958 +2700518 PIM2 chrX 48913182 48919024 +2700546 OTUD5 chrX 48922028 48958386 +2700703 KCND1 chrX 48961378 48971844 +2700741 GRIPAP1 chrX 48973720 49002264 +2701054 TFE3 chrX 49028726 49043410 +2701120 CCDC120 chrX 49053572 49069857 +2701280 PRAF2 chrX 49071161 49074002 +2701304 WDR45 chrX 49074433 49101170 +2701944 GPKOW chrX 49113407 49123735 +2701972 MAGIX chrX 49162564 49168483 +2702084 PLP2 chrX 49171898 49175235 +2702111 PRICKLE3 chrX 49174802 49186528 +2702218 SYP chrX 49187804 49200259 +2702318 SYP-AS1 chrX 49198966 49202454 +2702322 CACNA1F chrX 49205063 49233371 +2702642 CCDC22 chrX 49235470 49250520 +2702695 FOXP3 chrX 49250436 49270477 +2702901 AC232271.3 chrX 49262866 49270521 +2702909 PPP1R3F chrX 49269793 49301461 +2702988 AC232271.1 chrX 49273054 49275768 +2702991 AC232271.2 chrX 49279677 49281440 +2702995 GAGE10 chrX 49303669 49319844 +2703011 GAGE12J chrX 49322057 49329384 +2703027 GAGE13 chrX 49331616 49338952 +2703043 GAGE2E chrX 49341192 49345922 +2703055 GAGE12B chrX 49529869 49529985 +2703061 GAGE12C chrX 49532211 49539538 +2703077 GAGE12D chrX 49541767 49549094 +2703093 GAGE12F chrX 49551278 49568218 +2703124 GAGE12E chrX 49551333 49558649 +2703140 GAGE12G chrX 49570434 49577754 +2703156 GAGE12H chrX 49579983 49587301 +2703172 GAGE1 chrX 49589496 49608536 +2703232 GAGE2A chrX 49589529 49596827 +2703248 PAGE1 chrX 49687447 49695984 +2703266 PAGE4 chrX 49829260 49834264 +2703305 USP27X-AS1 chrX 49876724 49879241 +2703309 USP27X chrX 49879484 49882558 +2703317 CLCN5 chrX 49922596 50099235 +2703567 AKAP4 chrX 50190777 50201007 +2703640 CCNB3 chrX 50202713 50351910 +2703790 DGKK chrX 50365409 50470825 +2703852 SHROOM4 chrX 50591647 50814302 +2703929 BMP15 chrX 50910784 50916607 +2703938 LINC01284 chrX 51095836 51224432 +2703990 AC233976.1 chrX 51190598 51396462 +2704001 AC233976.2 chrX 51325790 51330662 +2704005 NUDT10 chrX 51332231 51337525 +2704028 AL158055.1 chrX 51395959 51465661 +2704038 EZHIP chrX 51406948 51408843 +2704046 NUDT11 chrX 51490011 51496592 +2704057 LINC01496 chrX 51498490 51511005 +2704067 CENPVL3 chrX 51617024 51618968 +2704075 CENPVL2 chrX 51681212 51682831 +2704082 CENPVL1 chrX 51710512 51712131 +2704089 GSPT2 chrX 51743442 51746232 +2704097 MAGED1 chrX 51803007 51902357 +2704258 AC239585.1 chrX 52050860 52054255 +2704262 AC239585.2 chrX 52053176 52055684 +2704273 MAGED4B chrX 52061827 52069248 +2704470 MAGED4 chrX 52184823 52192268 +2704616 AC231759.2 chrX 52195836 52265919 +2704631 AC245177.1 chrX 52199840 52203235 +2704635 XAGE2 chrX 52369021 52375680 +2704651 XAGE1A chrX 52495808 52500812 +2704686 XAGE1B chrX 52512077 52520803 +2704737 SSX7 chrX 52644061 52654900 +2704759 SSX2 chrX 52696896 52707189 +2704809 SSX2B chrX 52751132 52790305 +2704880 SPANXN5 chrX 52796144 52797427 +2704890 XAGE5 chrX 52812204 52818301 +2704936 XAGE3 chrX 52862525 52868083 +2704967 FAM156B chrX 52891306 52908560 +2705058 AC234031.1 chrX 52925956 52929574 +2705062 FAM156A chrX 52926402 52995472 +2705296 GPR173 chrX 53049091 53080615 +2705315 TSPYL2 chrX 53082367 53088540 +2705372 AL591212.1 chrX 53093710 53094858 +2705376 KANTR chrX 53094145 53170914 +2705405 KDM5C chrX 53191321 53225422 +2705752 KDM5C-IT1 chrX 53212408 53214679 +2705756 IQSEC2 chrX 53225828 53321350 +2706024 SMC1A chrX 53374149 53422728 +2706179 RIBC1 chrX 53422690 53431120 +2706245 HSD17B10 chrX 53431258 53434373 +2706305 AC233728.1 chrX 53432722 53433032 +2706309 HUWE1 chrX 53532096 53686728 +2706972 PHF8 chrX 53936676 54048958 +2707364 FAM120C chrX 54068324 54183281 +2707447 WNK3 chrX 54192823 54358642 +2707659 TSR2 chrX 54440404 54448032 +2707675 FGD1 chrX 54445454 54496234 +2707717 GNL3L chrX 54530211 54567289 +2707802 ITIH6 chrX 54748918 54798255 +2707837 MAGED2 chrX 54807599 54816015 +2708110 TRO chrX 54920462 54931431 +2708488 PFKFB1 chrX 54932961 54998534 +2708609 APEX2 chrX 55000363 55009057 +2708633 ALAS2 chrX 55009055 55030977 +2708788 PAGE2B chrX 55075030 55078909 +2708819 PAGE2 chrX 55089018 55092842 +2708859 FAM104B chrX 55143102 55161310 +2708934 MTRNR2L10 chrX 55181392 55182442 +2708942 PAGE5 chrX 55220355 55224108 +2708988 PAGE3 chrX 55258412 55264846 +2709019 MAGEH1 chrX 55452127 55453566 +2709027 USP51 chrX 55484616 55489202 +2709044 FOXR2 chrX 55623400 55626192 +2709052 RRAGB chrX 55717739 55758774 +2709133 AL050309.1 chrX 55908123 56209271 +2709162 KLF8 chrX 56232356 56291531 +2709238 UBQLN2 chrX 56563639 56567868 +2709246 AL354793.1 chrX 56618391 56624458 +2709250 NBDY chrX 56729241 56819179 +2709292 SPIN3 chrX 56818298 56995827 +2709917 AL139397.1 chrX 56973510 56974796 +2709921 SPIN2B chrX 57118551 57121546 +2709965 AL022157.1 chrX 57121662 57127243 +2709969 SPIN2A chrX 57134530 57137625 +2709997 Z83745.1 chrX 57222706 57224791 +2710001 FAAH2 chrX 57286706 57489196 +2710038 ZXDB chrX 57591652 57597545 +2710046 NLRP2B chrX 57677067 57680260 +2710053 ZXDA chrX 57906708 57910820 +2710061 LINC01278 chrX 63222993 63561095 +2710295 SPIN4 chrX 63347228 63351332 +2710303 SPIN4-AS1 chrX 63349646 63352178 +2710307 ARHGEF9 chrX 63634967 63809274 +2711189 ARHGEF9-IT1 chrX 63670196 63671502 +2711193 AMER1 chrX 64185117 64205708 +2711203 AL356317.2 chrX 64205974 64233855 +2711208 ASB12 chrX 64224194 64230607 +2711220 MTMR8 chrX 64268081 64395452 +2711270 ZC4H2 chrX 64915802 65034713 +2711341 ZC3H12B chrX 65366638 65507887 +2711364 LAS1L chrX 65512582 65534775 +2711496 MSN chrX 65588377 65741931 +2711555 AL034397.2 chrX 65925836 66001436 +2711572 AL034397.3 chrX 66015461 66020422 +2711583 VSIG4 chrX 66021738 66040125 +2711683 HEPH chrX 66162549 66268867 +2711969 EDA2R chrX 66595637 66639298 +2712043 AR chrX 67544021 67730619 +2712185 AL157700.1 chrX 68013470 68014901 +2712188 OPHN1 chrX 68042344 68433913 +2712264 YIPF6 chrX 68498562 68537282 +2712336 STARD8 chrX 68647666 68725842 +2712474 EFNB1 chrX 68829021 68842160 +2712490 PJA1 chrX 69160851 69165793 +2712544 LINC00269 chrX 69179557 69209924 +2712557 FAM155B chrX 69505241 69532508 +2712569 AL158069.1 chrX 69569635 69576337 +2712578 EDA chrX 69616067 70039472 +2712730 AL158141.1 chrX 70037840 70039325 +2712734 AWAT2 chrX 70040542 70049938 +2712773 OTUD6A chrX 70062457 70064179 +2712781 IGBP1 chrX 70133447 70166324 +2712818 IGBP1-AS2 chrX 70148582 70149654 +2712822 IGBP1-AS1 chrX 70163842 70165206 +2712826 DGAT2L6 chrX 70177483 70205704 +2712846 AWAT1 chrX 70234655 70240659 +2712871 P2RY4 chrX 70258170 70259764 +2712879 ARR3 chrX 70268305 70281840 +2713016 RAB41 chrX 70282093 70285002 +2713068 PDZD11 chrX 70286595 70290514 +2713121 KIF4A chrX 70290104 70420886 +2713194 GDPD2 chrX 70423031 70433390 +2713351 AL139398.1 chrX 70427450 70435350 +2713356 DLG3 chrX 70444835 70505490 +2713563 DLG3-AS1 chrX 70452958 70455994 +2713570 TEX11 chrX 70528940 70908731 +2713808 SLC7A3 chrX 70925579 70931125 +2713867 SNX12 chrX 71056332 71073426 +2713939 FOXO4 chrX 71095851 71103532 +2713970 CXorf65 chrX 71103889 71106788 +2714011 IL2RG chrX 71107404 71112108 +2714120 MED12 chrX 71118556 71142454 +2714445 NLGN3 chrX 71144831 71171201 +2714543 AL590764.1 chrX 71183384 71198208 +2714553 GJB1 chrX 71215194 71225516 +2714610 ZMYM3 chrX 71239624 71255146 +2714912 NONO chrX 71283192 71301168 +2715132 ITGB1BP2 chrX 71301750 71305371 +2715199 TAF1 chrX 71366239 71532374 +2715625 OGT chrX 71533104 71575892 +2715788 GCNA chrX 71578411 71613583 +2715853 CXCR3 chrX 71615916 71618511 +2715872 BX276092.9 chrX 71667542 71671524 +2715908 LINC00891 chrX 71697196 71706455 +2715913 CXorf49 chrX 71714371 71718151 +2715936 CXorf49B chrX 71763424 71767204 +2715959 NHSL2 chrX 71910818 72161750 +2716041 RTL5 chrX 72127110 72131901 +2716058 PIN4 chrX 72181353 72302926 +2716174 ERCC6L chrX 72204657 72239027 +2716195 RPS4X chrX 72255679 72277248 +2716234 CITED1 chrX 72301638 72307187 +2716356 HDAC8 chrX 72329516 72573101 +2717508 PHKA1 chrX 72578814 72714319 +2717850 PHKA1-AS1 chrX 72688950 72712348 +2717857 DMRTC1B chrX 72777009 72848802 +2717961 FAM226B chrX 72777608 72779097 +2717964 FAM236B chrX 72781865 72782660 +2717976 FAM236D chrX 72807425 72808210 +2717999 DMRTC1 chrX 72872025 72943814 +2718064 FAM236C chrX 72912615 72913401 +2718087 FAM236A chrX 72938163 72938958 +2718110 PABPC1L2B-AS1 chrX 72998388 73002856 +2718116 PABPC1L2B chrX 73003517 73005713 +2718124 PABPC1L2A chrX 73077276 73079512 +2718132 AL662864.1 chrX 73080167 73084635 +2718138 NAP1L2 chrX 73212299 73214851 +2718146 CDX4 chrX 73447254 73455245 +2718157 CHIC1 chrX 73563200 73687102 +2718226 TSIX chrX 73792205 73829231 +2718229 XIST chrX 73820649 73852723 +2718418 FTX chrX 73940435 74293574 +2718875 JPX chrX 73944182 74070408 +2719356 AL353804.1 chrX 73948973 73949558 +2719360 AL353804.2 chrX 73958059 73969485 +2719364 Z83843.1 chrX 74209976 74213660 +2719367 ZCCHC13 chrX 74304180 74305034 +2719375 SLC16A2 chrX 74421493 74533917 +2719421 RLIM chrX 74582976 74614624 +2719450 NEXMIF chrX 74732856 74925485 +2719499 ABCB7 chrX 75051048 75156732 +2719900 UPRT chrX 75156388 75304885 +2720043 ZDHHC15 chrX 75368427 75523502 +2720103 MAGEE2 chrX 75782987 75785254 +2720111 AL451105.2 chrX 75903105 75904858 +2720115 PBDC1 chrX 76173040 76178314 +2720148 MAGEE1 chrX 76427710 76431342 +2720156 AC233296.1 chrX 76656866 77014532 +2720203 FGF16 chrX 77447389 77457278 +2720215 ATRX chrX 77504878 77786233 +2720659 MAGT1 chrX 77826364 77895593 +2720754 COX7B chrX 77899440 77907376 +2720799 ATP7A chrX 77910656 78050395 +2720982 PGK1 chrX 77910739 78129295 +2721056 PGAM4 chrX 77967949 77969638 +2721063 TAF9B chrX 78129748 78139650 +2721090 CYSLTR1 chrX 78271468 78327691 +2721114 RTL3 chrX 78656068 78659328 +2721124 LPAR4 chrX 78747709 78757094 +2721172 P2RY10 chrX 78945332 78963727 +2721202 GPR174 chrX 79144663 79175315 +2721221 ITM2A chrX 79360384 79367667 +2721271 TBX22 chrX 80014753 80031774 +2721350 TENT5D chrX 80335504 80445311 +2721377 BRWD3 chrX 80669503 80809877 +2721506 AL391294.1 chrX 81000150 81004217 +2721509 HMGN5 chrX 81113699 81201913 +2721613 SH3BGRL chrX 81202102 81298547 +2721643 AL445213.2 chrX 81475532 81498083 +2721649 POU3F4 chrX 83508290 83512127 +2721657 CYLC1 chrX 83861126 83886699 +2721686 RPS6KA6 chrX 84058346 84188199 +2721798 HDX chrX 84317874 84502479 +2721888 APOOL chrX 85003877 85093316 +2721960 SATL1 chrX 85092287 85243961 +2722078 AC003001.1 chrX 85210684 85220021 +2722100 ZNF711 chrX 85244032 85273362 +2722174 POF1B chrX 85277396 85379717 +2722251 CHM chrX 85861180 86047561 +2722312 DACH2 chrX 86148451 86832604 +2722528 KLHL4 chrX 87517409 87670050 +2722612 Z83818.2 chrX 87707579 87750883 +2722617 CPXCR1 chrX 88747225 88754785 +2722649 AL121872.1 chrX 89423738 89446983 +2722657 TGIF2LX chrX 89921908 89922883 +2722674 AL121823.1 chrX 91307781 91308878 +2722678 PABPC5-AS1 chrX 91414878 91434999 +2722684 PABPC5 chrX 91434595 91438584 +2722703 PCDH11X chrX 91779261 92623230 +2722812 NAP1L3 chrX 93670930 93673578 +2722829 FAM133A chrX 93674013 93712274 +2722854 AL022151.1 chrX 96127747 96372889 +2722878 DIAPH2 chrX 96684663 97604997 +2723176 RPA4 chrX 96883908 96885467 +2723184 DIAPH2-AS1 chrX 97431286 97642589 +2723204 AL157778.1 chrX 98450688 98892061 +2723228 PCDH19 chrX 100291644 100410273 +2723288 TNMD chrX 100584936 100599885 +2723312 TSPAN6 chrX 100627108 100639991 +2723384 SRPX2 chrX 100644195 100675788 +2723483 SYTL4 chrX 100674491 100732123 +2723636 CSTF2 chrX 100820359 100840932 +2723752 NOX1 chrX 100843324 100874359 +2723870 XKRX chrX 100913445 100929433 +2723891 ARL13A chrX 100969708 100990831 +2723958 TRMT2B chrX 101009346 101052116 +2724100 TRMT2B-AS1 chrX 101043564 101094476 +2724104 TMEM35A chrX 101078879 101096367 +2724117 CENPI chrX 101098218 101163681 +2724267 DRP2 chrX 101219769 101264497 +2724509 TAF7L chrX 101268253 101293057 +2724599 TIMM8A chrX 101345661 101348742 +2724632 BTK chrX 101349447 101390796 +2724820 RPL36A chrX 101390824 101396154 +2724926 GLA chrX 101397803 101408012 +2725022 HNRNPH2 chrX 101408222 101414133 +2725032 ARMCX4 chrX 101418287 101533459 +2725234 ARMCX1 chrX 101550547 101554700 +2725248 ARMCX6 chrX 101615118 101618001 +2725304 ARMCX3 chrX 101622797 101627843 +2725384 ARMCX3-AS1 chrX 101622983 101624164 +2725388 AC234775.3 chrX 101627868 101628523 +2725391 AC234775.4 chrX 101640421 101644352 +2725395 ARMCX2 chrX 101655281 101659850 +2725525 NXF5 chrX 101832112 101857577 +2725675 ZMAT1 chrX 101882288 101932079 +2725755 TCEAL2 chrX 102125679 102140426 +2725786 TCEAL6 chrX 102140476 102142970 +2725809 Z70719.1 chrX 102142588 102143971 +2725814 BEX5 chrX 102153708 102155977 +2725840 TCP11X1 chrX 102215301 102229532 +2725915 NXF2 chrX 102247161 102326719 +2726014 NXF2B chrX 102360396 102439932 +2726119 TCP11X2 chrX 102456862 102471842 +2726250 TMSB15A chrX 102513682 102516739 +2726262 ARMCX5 chrX 102599168 102604159 +2726325 ARMCX5-GPRASP2 chrX 102599512 102714671 +2726384 AL035427.1 chrX 102599657 102659712 +2726389 GPRASP1 chrX 102651092 102659083 +2726466 AL035427.2 chrX 102659983 102663455 +2726470 GPRASP2 chrX 102712176 102717733 +2726524 ARMCX5-GPRASP2 chrX 102712495 102753530 +2726546 BHLHB9 chrX 102720688 102753540 +2726614 LINC00630 chrX 102769158 102885406 +2726697 Z68871.1 chrX 102884414 102906158 +2726710 RAB40AL chrX 102937272 102938300 +2726718 Z95624.1 chrX 102937770 102940561 +2726722 Z93943.1 chrX 102945971 102952039 +2726726 BEX1 chrX 103062651 103064171 +2726738 NXF3 chrX 103075810 103093143 +2726853 BEX4 chrX 103215108 103217246 +2726874 TCEAL8 chrX 103252995 103255192 +2726906 TCEAL5 chrX 103273691 103276750 +2726918 BEX2 chrX 103309346 103311046 +2726961 TCEAL7 chrX 103330229 103332326 +2726984 TCEAL9 chrX 103356489 103358462 +2727012 BEX3 chrX 103376340 103378077 +2727053 AL117327.1 chrX 103404777 103452754 +2727064 Z69733.1 chrX 103486461 103517919 +2727076 RAB40A chrX 103499130 103519489 +2727095 AL021308.1 chrX 103563917 103573278 +2727100 TCEAL4 chrX 103576231 103587736 +2727228 TCEAL3 chrX 103607451 103629690 +2727270 TCEAL3-AS1 chrX 103626076 103626492 +2727274 TCEAL1 chrX 103628704 103630953 +2727311 MORF4L2 chrX 103675496 103688158 +2727457 MORF4L2-AS1 chrX 103687284 103691772 +2727462 GLRA4 chrX 103707224 103728655 +2727518 TMEM31 chrX 103710909 103714032 +2727530 PLP1 chrX 103773718 103792619 +2727720 RAB9B chrX 103822327 103832257 +2727732 TMSB15B-AS1 chrX 103880668 103919548 +2727746 TMSB15B chrX 103918896 103966712 +2727809 H2BFWT chrX 104011147 104013687 +2727829 H2BFM chrX 104039949 104042454 +2727858 TMSB15B chrX 104063871 104076212 +2727881 SLC25A53 chrX 104099214 104157009 +2727894 ZCCHC18 chrX 104112131 104115846 +2727941 FAM199X chrX 104166453 104195902 +2727964 ESX1 chrX 104250038 104254933 +2727978 IL1RAPL2 chrX 104566199 105767829 +2728024 TEX13A chrX 105218929 105220674 +2728047 NRK chrX 105822539 105958610 +2728194 SERPINA7 chrX 106032435 106038727 +2728227 PWWP3B chrX 106168305 106208956 +2728267 RADX chrX 106611930 106679439 +2728392 RNF128 chrX 106693794 106797016 +2728446 TBC1D8B chrX 106802673 106876150 +2728612 MORC4 chrX 106813871 107000212 +2728701 RIPPLY1 chrX 106900063 106903341 +2728724 CLDN2 chrX 106900164 106930861 +2728752 RBM41 chrX 107064420 107118823 +2728845 NUP62CL chrX 107123427 107206433 +2728918 PIH1D3 chrX 107206632 107244243 +2728978 FRMPD3-AS1 chrX 107512983 107545821 +2728982 FRMPD3 chrX 107522450 107605251 +2729055 PRPS1 chrX 107628424 107651026 +2729178 TSC22D3 chrX 107713221 107777342 +2729348 NCBP2L chrX 107774899 107795829 +2729367 MID2 chrX 107825755 107927193 +2729429 AL109946.1 chrX 107857364 107936230 +2729449 TEX13B chrX 107980864 107982370 +2729461 VSIG1 chrX 108044970 108079184 +2729521 PSMD10 chrX 108084207 108091549 +2729605 ATG4A chrX 108091668 108154671 +2729775 COL4A6 chrX 108155607 108439497 +2730364 COL4A5 chrX 108439844 108697545 +2730704 AL035425.3 chrX 108719949 108724944 +2730707 IRS4 chrX 108732482 108736409 +2730715 AL035425.1 chrX 108736011 108739223 +2730735 GUCY2F chrX 109372906 109482086 +2730781 NXT2 chrX 109535781 109544690 +2730838 KCNE5 chrX 109623700 109625172 +2730846 ACSL4 chrX 109624244 109733403 +2731199 TMEM164 chrX 110002631 110182734 +2731288 AMMECR1 chrX 110194186 110440233 +2731349 AMMECR1-IT1 chrX 110305420 110307221 +2731353 RTL9 chrX 110358816 110456334 +2731385 AC000113.1 chrX 110472692 110524320 +2731389 CHRDL1 chrX 110673856 110795819 +2731531 PAK3 chrX 110944285 111227361 +2731942 CAPN6 chrX 111245099 111270483 +2731974 DCX chrX 111293779 111412429 +2732162 SERTM2 chrX 111511662 111522399 +2732177 ALG13 chrX 111665811 111760649 +2733086 ALG13-AS1 chrX 111706649 111711101 +2733090 TRPC5 chrX 111774315 112082776 +2733118 TRPC5OS chrX 111876051 111903990 +2733158 RTL4 chrX 112454500 112457112 +2733166 LHFPL1 chrX 112630648 112680054 +2733184 AMOT chrX 112774503 112840815 +2733324 AC002072.1 chrX 112880563 113212186 +2733332 AL023877.1 chrX 113157873 113188018 +2733336 XACT chrX 113616300 114059289 +2733347 HTR2C chrX 114584078 114910061 +2733401 IL13RA2 chrX 115003975 115019977 +2733460 LRCH2 chrX 115110616 115234096 +2733553 RBMXL3 chrX 115189427 115192868 +2733561 LUZP4 chrX 115289715 115307563 +2733586 PLS3-AS1 chrX 115518182 115562731 +2733596 PLS3 chrX 115561174 115650861 +2733846 DANT2 chrX 115694880 115969130 +2733865 DANT1 chrX 115840964 115843050 +2733873 AGTR2 chrX 116170744 116174974 +2733885 SLC6A14 chrX 116436606 116461458 +2733923 CT83 chrX 116461686 116462976 +2733933 BX119904.2 chrX 116692910 116694188 +2733937 KLHL13 chrX 117897813 118117340 +2734105 WDR44 chrX 118346073 118449961 +2734280 DOCK11 chrX 118495898 118686163 +2734613 IL13RA1 chrX 118727133 118794535 +2734693 ZCCHC12 chrX 118823824 118826968 +2734707 LINC01285 chrX 118839539 118919669 +2734801 LONRF3 chrX 118974614 119018355 +2734946 AL772284.2 chrX 119073226 119076373 +2734957 KIAA1210 chrX 119078635 119150579 +2734990 PGRMC1 chrX 119236245 119244466 +2735011 AC004835.1 chrX 119291529 119335610 +2735017 AC004973.1 chrX 119356301 119393595 +2735022 SLC25A43 chrX 119399336 119454478 +2735054 AC004000.1 chrX 119422917 119423547 +2735058 SLC25A5-AS1 chrX 119465986 119469128 +2735079 SLC25A5 chrX 119468422 119471396 +2735104 CXorf56 chrX 119538149 119565408 +2735164 UBE2A chrX 119574536 119591083 +2735294 NKRF chrX 119588337 119606443 +2735334 SEPTIN6 chrX 119615724 119693370 +2735524 SOWAHD chrX 119758588 119760202 +2735532 RPL39 chrX 119786504 119791630 +2735550 AC005052.2 chrX 119791971 119810949 +2735554 UPF3B chrX 119805311 119852998 +2735654 RNF113A chrX 119870475 119871733 +2735662 NDUFA1 chrX 119871832 119876662 +2735674 AKAP14 chrX 119895837 119920716 +2735740 NKAP chrX 119920672 119943751 +2735800 RHOXF1-AS1 chrX 120036236 120146854 +2735818 RHOXF2B chrX 120070672 120077705 +2735832 RHOXF1 chrX 120109051 120115913 +2735844 LINC01402 chrX 120117642 120119700 +2735849 RHOXF2 chrX 120158613 120165630 +2735863 ZBTB33 chrX 120250752 120258398 +2735884 TMEM255A chrX 120258650 120311556 +2735985 ATP1B4 chrX 120362085 120383249 +2736047 LAMP2 chrX 120427827 120469365 +2736134 CUL4B chrX 120524609 120575794 +2736309 MCTS1 chrX 120594010 120621159 +2736365 C1GALT1C1 chrX 120625674 120630054 +2736386 CT47B1 chrX 120872603 120875929 +2736398 AC008162.2 chrX 120877496 120878924 +2736406 CT47A12 chrX 120930250 120932301 +2736416 CT47A11 chrX 120933840 120937158 +2736428 CT47A10 chrX 120938701 120942023 +2736440 CT47A9 chrX 120943561 120946883 +2736452 CT47A8 chrX 120948422 120951744 +2736464 CT47A7 chrX 120953282 120956600 +2736476 CT47A6 chrX 120958165 120961487 +2736488 CT47A5 chrX 120963026 120966348 +2736500 CT47A4 chrX 120967886 120971208 +2736512 CT47A3 chrX 120972746 120976068 +2736524 CT47A2 chrX 120977606 120980928 +2736536 CT47A1 chrX 120982476 120985788 +2736548 GLUD2 chrX 121047610 121050094 +2736556 AC006144.2 chrX 121065882 121078538 +2736560 AC002377.1 chrX 121093392 121298035 +2736568 AL359851.1 chrX 121871869 121876865 +2736571 AL513487.1 chrX 122422006 122478043 +2736576 GRIA3 chrX 123184153 123490915 +2736765 THOC2 chrX 123600561 123733056 +2737213 XIAP chrX 123859724 123913979 +2737321 XIAP-AS1 chrX 123872626 123873932 +2737325 AL121601.1 chrX 123959233 123961341 +2737329 STAG2 chrX 123960212 124422664 +2737877 SH2D1A chrX 124227868 124373197 +2737947 TEX13D chrX 124246249 124336863 +2737958 TENM1 chrX 124375903 124963817 +2738100 TEX13C chrX 125320120 125325214 +2738107 AL445072.1 chrX 126109762 126115562 +2738112 DCAF12L2 chrX 126163499 126166289 +2738120 DCAF12L1 chrX 126549383 126552814 +2738130 PRR32 chrX 126819729 126821786 +2738140 AL591643.1 chrX 127660631 127662530 +2738143 AL008633.1 chrX 128027322 129326707 +2738178 ACTRT1 chrX 128050962 128052398 +2738186 SMARCA1 chrX 129446501 129523500 +2738381 OCRL chrX 129539849 129592561 +2738629 APLN chrX 129645259 129654956 +2738641 AL022162.1 chrX 129675888 129678348 +2738645 XPNPEP2 chrX 129738974 129769536 +2738710 SASH3 chrX 129779949 129795201 +2738735 AL023653.1 chrX 129794994 129796963 +2738740 ZDHHC9 chrX 129803288 129843909 +2738822 AL034405.1 chrX 129869064 129957528 +2738836 UTP14A chrX 129906121 129929761 +2738925 BCORL1 chrX 129981107 130058083 +2739046 ELF4 chrX 130064874 130110716 +2739131 AIFM1 chrX 130129362 130165887 +2739387 AL139234.1 chrX 130165954 130166905 +2739390 RAB33A chrX 130171962 130184870 +2739400 ZNF280C chrX 130202707 130268899 +2739475 SLC25A14 chrX 130339888 130373361 +2739703 GPR119 chrX 130384345 130385660 +2739711 RBMX2 chrX 130401987 130413656 +2739767 Z82195.3 chrX 130497785 130520309 +2739772 ENOX2 chrX 130623369 130903317 +2739963 LINC01201 chrX 130981590 131058146 +2739971 ARHGAP36 chrX 131058346 131089885 +2740127 IGSF1 chrX 131273506 131578899 +2740499 AL135784.1 chrX 131385453 131407083 +2740504 OR13H1 chrX 131543976 131545056 +2740512 AL365256.1 chrX 131578681 131611684 +2740517 FIRRE chrX 131688779 131830862 +2740672 STK26 chrX 132023302 132075943 +2740812 FRMD7 chrX 132076993 132128020 +2740891 RAP2C chrX 132203024 132219480 +2740948 RAP2C-AS1 chrX 132217053 132432862 +2740963 MBNL3 chrX 132369317 132489968 +2741167 HS6ST2 chrX 132626016 132961395 +2741239 HS6ST2-AS1 chrX 132667642 132669888 +2741244 USP26 chrX 133024631 133097109 +2741276 TFDP3 chrX 133216662 133218354 +2741284 GPC4 chrX 133300103 133415489 +2741308 GPC3 chrX 133535745 133985895 +2741411 AC002407.1 chrX 134168911 134174089 +2741415 CCDC160 chrX 134237047 134246207 +2741436 PHF6 chrX 134373253 134428791 +2741560 HPRT1 chrX 134460165 134520513 +2741602 MIR503HG chrX 134543119 134546642 +2741635 LINC00629 chrX 134549770 134560399 +2741665 PLAC1 chrX 134565838 134764322 +2741689 AL672032.1 chrX 134599457 134606254 +2741695 FAM122B chrX 134769566 134797232 +2741863 FAM122C chrX 134796395 134854835 +2742181 MOSPD1 chrX 134887632 134915257 +2742248 LINC02243 chrX 134949549 134953382 +2742253 SMIM10 chrX 134990991 134992473 +2742261 RTL8B chrX 135020513 135022542 +2742269 RTL8C chrX 135032355 135033546 +2742283 AL136169.1 chrX 135037281 135040355 +2742287 RTL8A chrX 135050932 135052196 +2742304 SMIM10L2B-AS1 chrX 135059685 135123952 +2742319 SMIM10L2B chrX 135094985 135098712 +2742329 ETDB chrX 135118955 135120526 +2742350 AC234771.1 chrX 135123239 135123604 +2742354 CT55 chrX 135156536 135171398 +2742387 ZNF75D chrX 135248920 135344109 +2742428 ETDA chrX 135252061 135253583 +2742449 ETDC chrX 135309480 135309659 +2742456 AL590282.2 chrX 135327758 135330743 +2742460 ZNF449 chrX 135344796 135363413 +2742485 SMIM10L2A chrX 135421944 135428075 +2742495 INTS6L-AS1 chrX 135520083 135520674 +2742499 INTS6L chrX 135520643 135582510 +2742624 CT45A1 chrX 135713453 135723539 +2742653 CT45A3 chrX 135759846 135768191 +2742681 CT45A5 chrX 135777130 135785298 +2742709 CT45A6 chrX 135794706 135802656 +2742738 CT45A2 chrX 135811668 135820012 +2742766 CT45A7 chrX 135829247 135837268 +2742795 CT45A8 chrX 135846497 135854538 +2742824 CT45A9 chrX 135863418 135871812 +2742853 CT45A10 chrX 135881063 135889086 +2742882 SAGE1 chrX 135889205 135913061 +2742999 MMGT1 chrX 135962070 135974063 +2743013 SLC9A6 chrX 135973841 136047269 +2743465 FHL1 chrX 136146702 136211359 +2743979 MAP7D3 chrX 136213220 136256482 +2744164 ADGRG4 chrX 136300963 136416890 +2744326 BRS3 chrX 136487947 136493780 +2744338 HTATSF1 chrX 136497079 136512346 +2744417 VGLL1 chrX 136532215 136556807 +2744454 LINC00892 chrX 136639539 136642429 +2744469 CD40LG chrX 136648193 136660390 +2744498 ARHGEF6 chrX 136665547 136780932 +2744642 AL683813.1 chrX 136840931 136847797 +2744646 RBMX chrX 136848004 136880764 +2744822 GPR101 chrX 137027447 137033847 +2744838 AL035443.1 chrX 137556191 137564387 +2744846 ZIC3 chrX 137566127 137577691 +2744872 Z96074.1 chrX 137573752 137981780 +2744894 FGF13 chrX 138614727 139222777 +2745015 AL031386.1 chrX 138627077 138627343 +2745019 FGF13-AS1 chrX 138711452 138716617 +2745029 F9 chrX 139530758 139563458 +2745082 MCF2 chrX 139581770 139708227 +2745547 ATP11C chrX 139726346 139945276 +2745820 CXorf66 chrX 139955728 139965521 +2745832 AL589987.2 chrX 140017268 140018037 +2745836 FO393408.1 chrX 140216035 140216804 +2745840 SOX3 chrX 140502985 140505116 +2745848 AL844175.1 chrX 140681106 140689819 +2745858 LINC00632 chrX 140709562 140793215 +2746001 CDR1 chrX 140783578 140784366 +2746008 AL451048.1 chrX 140931738 140997448 +2746013 SPANXB1 chrX 141002594 141003706 +2746023 LDOC1 chrX 141111605 141177129 +2746038 SPANXA2-OT1 chrX 141177284 141649927 +2746069 SPANXC chrX 141241463 141242517 +2746079 SPANXA1 chrX 141583674 141585011 +2746089 SPANXA2 chrX 141589708 141590762 +2746099 AC235097.1 chrX 141625864 141626733 +2746103 SPANXD chrX 141697411 141698739 +2746113 MAGEC3 chrX 141838316 141897832 +2746175 MAGEC1 chrX 141903894 141909374 +2746202 AL031073.2 chrX 141934496 142740581 +2746214 MAGEC2 chrX 142202342 142205290 +2746226 SPANXN4 chrX 143025918 143034702 +2746247 AC239727.1 chrX 143284977 143516803 +2746255 SPANXN3 chrX 143508735 143517475 +2746265 SLITRK4 chrX 143622790 143636101 +2746293 SPANXN2 chrX 143711955 143721423 +2746303 AL500522.1 chrX 143757737 143828133 +2746308 AL713923.1 chrX 145232929 145233619 +2746312 SPANXN1 chrX 145247503 145256208 +2746322 AL109653.3 chrX 145699056 145820632 +2746327 SLITRK2 chrX 145817832 145829856 +2746350 CXorf51B chrX 146809771 146810411 +2746360 CXorf51A chrX 146814106 146814726 +2746370 AL589669.1 chrX 147181064 147271894 +2746377 AL591022.1 chrX 147279481 147286481 +2746385 AC016925.3 chrX 147879361 147885249 +2746390 L29074.1 chrX 147900178 147901459 +2746394 FMR1-AS1 chrX 147909431 147911817 +2746407 FMR1 chrX 147911951 147951125 +2746906 FMR1-IT1 chrX 147946941 147947583 +2746910 FMR1NB chrX 147981337 148026665 +2746941 AC002368.1 chrX 148498113 148500615 +2746945 AFF2 chrX 148500617 149000663 +2747175 AFF2-IT1 chrX 148546878 148547397 +2747179 AC231656.1 chrX 149414886 149415495 +2747189 IDS chrX 149476988 149521096 +2747314 AC244197.2 chrX 149511509 149526264 +2747318 LINC00893 chrX 149527591 149540959 +2747405 CXorf40A chrX 149540355 149550510 +2747566 HSFX3 chrX 149548210 149549932 +2747576 MAGEA9B chrX 149581653 149587453 +2747621 HSFX2 chrX 149592512 149595314 +2747631 TMEM185A chrX 149596556 149631912 +2747756 MAGEA11 chrX 149688228 149717268 +2747806 HSFX1 chrX 149774068 149776867 +2747816 MAGEA9 chrX 149781930 149787737 +2747830 LINC00850 chrX 149825708 149879799 +2747835 MAGEA8-AS1 chrX 149878836 149881070 +2747842 MAGEA8 chrX 149881141 149885835 +2747887 CXorf40B chrX 149929527 149938700 +2747979 HSFX4 chrX 149929645 149931287 +2747988 LINC00894 chrX 149938613 150224580 +2748101 MAMLD1 chrX 150361422 150514178 +2748192 MTM1 chrX 150568619 150673322 +2748269 MTMR1 chrX 150692971 150765108 +2748572 CD99L2 chrX 150766336 150898816 +2748767 AF274573.1 chrX 150915813 150920938 +2748777 HMGB3 chrX 150980509 150990771 +2748843 GPR50-AS1 chrX 151175192 151177836 +2748848 GPR50 chrX 151176584 151181465 +2748858 KC877982.1 chrX 151182386 151182855 +2748861 AF274853.1 chrX 151303384 151397142 +2748876 VMA21 chrX 151396515 151409364 +2748905 BX546450.2 chrX 151497726 151498354 +2748909 BX546450.1 chrX 151515551 151516245 +2748913 PASD1 chrX 151563675 151676739 +2748967 PRRG3 chrX 151694658 151705924 +2749034 FATE1 chrX 151716035 151723194 +2749061 CNGA2 chrX 151738451 151745304 +2749079 MAGEA4-AS1 chrX 151904431 151913968 +2749093 MAGEA4 chrX 151912509 151925170 +2749232 GABRE chrX 151953124 151974680 +2749321 MAGEA10 chrX 152133310 152138578 +2749400 AC116666.1 chrX 152138883 152186857 +2749406 GABRA3 chrX 152166234 152451315 +2749463 AC244102.4 chrX 152574677 152698700 +2749470 GABRQ chrX 152637895 152657542 +2749494 MAGEA3 chrX 152698767 152702347 +2749526 CSAG2 chrX 152708261 152714549 +2749561 MAGEA2B chrX 152714586 152718607 +2749675 CSAG1 chrX 152727484 152733735 +2749730 MAGEA12 chrX 152733757 152737669 +2749762 AC244102.1 chrX 152746817 152747762 +2749766 MAGEA2 chrX 152749863 152753884 +2749892 CSAG3 chrX 152753921 152760222 +2749917 MAGEA6 chrX 152766136 152769747 +2749960 AC244102.3 chrX 152769764 152792268 +2749966 CETN2 chrX 152826979 152830757 +2749986 NSDHL chrX 152830967 152869729 +2750050 ZNF185 chrX 152914442 152973480 +2750539 U82671.1 chrX 152925356 152927043 +2750543 PNMA5 chrX 152988824 152994116 +2750586 PNMA3 chrX 153056409 153060467 +2750616 PNMA6A chrX 153072482 153075018 +2750626 MAGEA1 chrX 153179284 153183880 +2750638 AC236972.3 chrX 153225649 153230357 +2750649 AC236972.4 chrX 153271618 153277803 +2750656 PNMA6F chrX 153317680 153321767 +2750666 ZNF275 chrX 153334147 153360110 +2750713 PNMA6E chrX 153395639 153401392 +2750734 ZFP92 chrX 153418322 153426481 +2750748 TREX2 chrX 153444720 153470587 +2750892 HAUS7 chrX 153447666 153495516 +2751007 BGN chrX 153494980 153509546 +2751064 ATP2B3 chrX 153517676 153582939 +2751305 CCNQ chrX 153587925 153600045 +2751419 DUSP9 chrX 153642492 153651326 +2751450 PNCK chrX 153669730 153689010 +2751844 SLC6A8 chrX 153687926 153696588 +2751961 BCAP31 chrX 153700492 153724565 +2752158 ABCD1 chrX 153724856 153744755 +2752200 U52111.1 chrX 153735626 153766478 +2752209 PLXNB3 chrX 153764196 153779346 +2752411 SRPK3 chrX 153776412 153785732 +2752659 IDH3G chrX 153785766 153794523 +2752884 SSR4 chrX 153793516 153798499 +2753001 PDZD4 chrX 153802166 153830565 +2753112 L1CAM chrX 153861514 153886173 +2753444 U52112.1 chrX 153880672 153888990 +2753453 AVPR2 chrX 153902531 153907166 +2753509 ARHGAP4 chrX 153907367 153934999 +2753994 NAA10 chrX 153929225 153935080 +2754163 RENBP chrX 153935269 153944687 +2754305 HCFC1 chrX 153947557 153971818 +2754447 HCFC1-AS1 chrX 153969325 153970087 +2754451 TMEM187 chrX 153972754 153983194 +2754475 IRAK1 chrX 154010506 154019902 +2754708 MECP2 chrX 154021573 154137103 +2754890 OPN1LW chrX 154144243 154159032 +2754924 OPN1MW chrX 154182596 154196861 +2754958 OPN1MW2 chrX 154219756 154233286 +2754992 OPN1MW3 chrX 154257538 154271805 +2755010 TEX28 chrX 154271265 154295853 +2755058 TKTL1 chrX 154295795 154330350 +2755171 AC245140.1 chrX 154333960 154335037 +2755175 FLNA chrX 154348524 154374638 +2755855 AC245140.3 chrX 154374595 154376934 +2755859 EMD chrX 154379197 154381523 +2755937 RPL10 chrX 154389955 154409168 +2756133 AC245140.2 chrX 154396878 154398816 +2756136 DNASE1L1 chrX 154401236 154412112 +2756332 TAZ chrX 154411524 154421726 +2756835 AC244090.1 chrX 154424380 154428479 +2756839 ATP6AP1 chrX 154428645 154436516 +2756998 GDI1 chrX 154436913 154443467 +2757133 FAM50A chrX 154444141 154450654 +2757222 PLXNA3 chrX 154458281 154477779 +2757324 LAGE3 chrX 154477769 154479257 +2757336 UBL4A chrX 154483717 154486615 +2757396 SLC10A3 chrX 154487306 154490690 +2757457 FAM3A chrX 154506159 154516242 +2757843 AC244090.3 chrX 154517840 154518631 +2757846 G6PD chrX 154531391 154547572 +2758018 IKBKG chrX 154541199 154565046 +2758292 FAM223A chrX 154571248 154571960 +2758297 CTAG1A chrX 154585133 154586821 +2758324 CTAG1B chrX 154617609 154619282 +2758345 FAM223B chrX 154632470 154633182 +2758350 CTAG2 chrX 154651972 154653579 +2758371 GAB3 chrX 154675249 154751583 +2758464 DKC1 chrX 154762742 154777689 +2758650 MPP1 chrX 154778684 154821007 +2758887 SMIM9 chrX 154823348 154834662 +2758908 F8 chrX 154835788 155026940 +2759062 H2AFB1 chrX 154884972 154885558 +2759070 F8A1 chrX 154886349 154888061 +2759078 FUNDC2 chrX 155025980 155060304 +2759130 CMC4 chrX 155061622 155071136 +2759153 MTCP1 chrX 155064034 155147937 +2759194 BRCC3 chrX 155071420 155123074 +2759426 VBP1 chrX 155197007 155239841 +2759484 RAB39B chrX 155258235 155264491 +2759494 CLIC2 chrX 155276211 155334657 +2759538 AC234781.1 chrX 155334858 155351957 +2759545 H2AFB2 chrX 155380787 155381134 +2759552 F8A2 chrX 155382115 155383230 +2759559 F8A3 chrX 155456914 155458672 +2759567 H2AFB3 chrX 155459415 155460005 +2759575 TMLHE-AS1 chrX 155466540 155611616 +2759584 BX571846.1 chrX 155468286 155487046 +2759588 TMLHE chrX 155489011 155669944 +2759641 SPRY3 chrX 155767812 155782459 +2759651 VAMP7 chrX 155881345 155943769 +2759747 IL9R chrX 155997581 156010817 +2759802 WASIR1 chrX 156014623 156016837 +2759806 SRY chrY 2786855 2787682 +2759814 AC006040.1 chrY 2828192 2840851 +2759819 RPS4Y1 chrY 2841602 2932000 +2759864 AC006157.1 chrY 2934406 2934771 +2759867 ZFY chrY 2935281 2982506 +2759963 ZFY-AS1 chrY 2966844 3002626 +2759972 LINC00278 chrY 3002887 3200509 +2760013 TGIF2LY chrY 3579041 3580041 +2760030 AC012078.2 chrY 3786282 3864893 +2760038 AC010737.1 chrY 4036497 4100320 +2760042 AC010722.1 chrY 4993858 4999650 +2760050 PCDH11Y chrY 5000226 5742224 +2760137 TSPY2 chrY 6246223 6249019 +2760199 LINC00280 chrY 6357219 6369921 +2760209 TTTY1B chrY 6390431 6411564 +2760216 TTTY2B chrY 6406244 6462091 +2760237 TTTY21B chrY 6443434 6450685 +2760242 TTTY7 chrY 6449468 6457906 +2760262 TTTY8B chrY 6470773 6473630 +2760271 AMELY chrY 6865918 6911774 +2760324 TBL1Y chrY 6910686 7101970 +2760463 AC011297.1 chrY 6918682 6920791 +2760466 PRKY chrY 7273972 7381548 +2760501 TTTY12 chrY 7803996 7810683 +2760518 AC064829.1 chrY 8550518 8713825 +2760584 TTTY18 chrY 8682594 8700977 +2760593 TTTY19 chrY 8704472 8705283 +2760597 TTTY20 chrY 9329880 9334832 +2760601 TSPY4 chrY 9337464 9340284 +2760658 TSPY8 chrY 9357797 9360599 +2760713 FAM197Y7 chrY 9367803 9375681 +2760724 FAM197Y6 chrY 9388122 9396027 +2760735 TSPY3 chrY 9398421 9401223 +2760788 TSPY1 chrY 9466955 9469749 +2760823 TSPY9P chrY 9487313 9489893 +2760840 TSPY10 chrY 9527880 9530682 +2760883 TTTY8 chrY 9691100 9693957 +2760892 TTTY7B chrY 9706824 9715262 +2760912 TTTY21 chrY 9717653 9721296 +2760916 TTTY2 chrY 9740584 9758476 +2760925 TTTY1 chrY 9753156 9774289 +2760932 TTTY22 chrY 9784372 9833895 +2760952 AC010891.1 chrY 9813315 9817513 +2760957 TTTY23 chrY 9910798 9911962 +2760962 USP9Y chrY 12537650 12860839 +2761246 AC244213.1 chrY 12661309 12663478 +2761263 DDX3Y chrY 12904108 12920478 +2761402 UTY chrY 13248379 13480673 +2762157 TMSB4Y chrY 13703899 13706024 +2762167 VCY chrY 13985772 13986513 +2762177 VCY1B chrY 14056227 14056958 +2762187 AC010723.1 chrY 14276212 14277489 +2762191 NLGN4Y chrY 14522573 14845650 +2762317 NLGN4Y-AS1 chrY 14793642 14804033 +2762323 AC011751.1 chrY 16599730 16644539 +2762328 FAM41AY1 chrY 17500958 17515018 +2762337 FAM224B chrY 17552800 17579754 +2762344 CDY2B chrY 17877410 17880220 +2762363 CDY2A chrY 18025787 18028597 +2762382 FAM224A chrY 18326253 18353210 +2762389 FAM41AY2 chrY 18390994 18405046 +2762398 AC022486.1 chrY 18491740 18547698 +2762405 HSFY1 chrY 18546671 18588963 +2762452 TTTY9B chrY 18581206 18590521 +2762464 HSFY2 chrY 18731440 18773735 +2762501 TTTY14 chrY 18772706 19077563 +2762739 AC007244.1 chrY 19076946 19077416 +2762747 AC010889.1 chrY 19691941 19694606 +2762750 KDM5D chrY 19703865 19744939 +2763053 AC010889.2 chrY 19744756 19759978 +2763062 TTTY10 chrY 20464916 20575519 +2763159 EIF1AY chrY 20575776 20593154 +2763209 AC009494.2 chrY 20725331 20734526 +2763213 RPS4Y2 chrY 20756108 20781032 +2763233 AC007876.1 chrY 21038289 21044724 +2763238 PRORY chrY 21382954 21386360 +2763244 AC010086.3 chrY 21424028 21456216 +2763250 RBMY1B chrY 21511338 21549094 +2763334 RBMY1A1 chrY 21511372 21549326 +2763447 TTTY13 chrY 21565092 21605081 +2763463 AC024236.1 chrY 21825441 21846721 +2763472 RBMY1D chrY 21880076 21894526 +2763556 RBMY1E chrY 21903618 21918067 +2763640 PRY2 chrY 22071756 22096007 +2763673 AC007359.1 chrY 22100814 22147484 +2763693 TTTY6B chrY 22144966 22146831 +2763698 RBMY1F chrY 22168542 22182982 +2763767 TTTY5 chrY 22296798 22298876 +2763771 RBMY1J chrY 22403461 22417881 +2763813 AC008175.1 chrY 22438940 22485592 +2763833 TTTY6 chrY 22439593 22441458 +2763838 PRY chrY 22490397 22514637 +2763871 TTTY17A chrY 22851584 22852715 +2763875 TTTY4 chrY 22936455 22973284 +2763881 BPY2 chrY 22973819 23005465 +2763939 DAZ1 chrY 23129355 23199094 +2764177 DAZ2 chrY 23219434 23291356 +2764613 PRYP3 chrY 23681440 23694579 +2764625 TTTY3B chrY 23936727 23941622 +2764630 CDY1B chrY 24045229 24048019 +2764647 TTTY17B chrY 24485332 24486463 +2764651 TTTY4B chrY 24570202 24607025 +2764657 BPY2B chrY 24607560 24639207 +2764715 DAZ3 chrY 24763069 24813492 +2764835 DAZ4 chrY 24833843 24907040 +2765171 BPY2C chrY 25030901 25062548 +2765229 TTTY4C chrY 25063083 25099892 +2765235 TTTY17C chrY 25182277 25213389 +2765242 LINC00266-4P chrY 25378300 25394719 +2765252 CDY1 chrY 25622162 25624902 +2765269 TTTY3 chrY 25728490 25733388 +2765274 MT-ND1 chrM 3307 4262 +2765278 MT-ND2 chrM 4470 5511 +2765282 MT-CO1 chrM 5904 7445 +2765287 MT-CO2 chrM 7586 8269 +2765294 MT-ATP8 chrM 8366 8572 +2765301 MT-ATP6 chrM 8527 9207 +2765308 MT-CO3 chrM 9207 9990 +2765313 MT-ND3 chrM 10059 10404 +2765317 MT-ND4L chrM 10470 10766 +2765324 MT-ND4 chrM 10760 12137 +2765329 MT-ND5 chrM 12337 14148 +2765335 MT-ND6 chrM 14149 14673 +2765340 MT-CYB chrM 14747 15887 +2765345 BX004987.1 GL000009.2 56140 58376 +2765353 AC145212.1 GL000194.1 53590 115018 +2765365 MAFIP GL000194.1 53594 115055 +2765379 AC011043.1 GL000195.1 42939 49164 +2765389 AC011043.2 GL000195.1 173872 179372 +2765403 AC011841.1 GL000205.2 99351 104855 +2765417 BX072566.1 GL000213.1 108007 139659 +2765466 AL354822.1 GL000218.1 51867 54893 +2765474 AL592183.1 GL000219.1 54224 83311 +2765487 AC240274.1 KI270711.1 4612 29626 +2765638 AC213203.2 KI270713.1 31698 32528 +2765646 AC213203.1 KI270713.1 35407 35916 +2765653 AC004556.3 KI270721.1 2585 11802 +2765669 AC233755.2 KI270726.1 26241 26534 +2765673 AC233755.1 KI270726.1 41444 41876 +2765680 AC136352.3 KI270727.1 100123 101141 +2765691 AC136352.2 KI270727.1 136160 167571 +2765740 AC171558.3 KI270727.1 372322 373405 +2765748 AC171558.1 KI270727.1 386278 387620 +2765755 AC133551.1 KI270728.1 17234 19833 +2765765 AC136612.1 KI270728.1 933862 936467 +2765775 AC136616.1 KI270728.1 1139577 1147868 +2765842 AC136616.3 KI270728.1 1157687 1240349 +2765850 AC136616.2 KI270728.1 1167457 1257196 +2765865 AC141272.1 KI270728.1 1270984 1271271 +2765869 AC023491.2 KI270731.1 10598 13001 +2765876 AC007325.1 KI270734.1 72411 74814 +2765883 AC007325.4 KI270734.1 131494 137392 +2765899 AC007325.2 KI270734.1 138082 161852 diff --git a/GRCh38_resources/ig_gene_list.txt b/GRCh38_resources/ig_gene_list.txt new file mode 100644 index 0000000..a629e0d --- /dev/null +++ b/GRCh38_resources/ig_gene_list.txt @@ -0,0 +1,213 @@ +IGKV3OR2-268 +IGKC +IGKJ5 +IGKJ4 +IGKJ3 +IGKJ2 +IGKJ1 +IGKV4-1 +IGKV5-2 +IGKV1-5 +IGKV1-6 +IGKV3-7 +IGKV1-8 +IGKV1-9 +IGKV3-11 +IGKV1-12 +IGKV3-15 +IGKV1-16 +IGKV1-17 +IGKV3-20 +IGKV6-21 +IGKV2-24 +IGKV1-27 +IGKV2-28 +IGKV2-30 +IGKV1-33 +IGKV1-37 +IGKV1-39 +IGKV2-40 +IGKV2D-40 +IGKV1D-39 +IGKV1D-37 +IGKV1D-33 +IGKV2D-30 +IGKV2D-29 +IGKV2D-28 +IGKV2D-26 +IGKV2D-24 +IGKV6D-21 +IGKV3D-20 +IGKV6D-41 +IGKV1D-17 +IGKV1D-16 +IGKV3D-15 +IGKV1D-13 +IGKV1D-12 +IGKV3D-11 +IGKV1D-42 +IGKV1D-43 +IGKV1D-8 +IGKV3D-7 +IGKV1OR2-108 +IGHA2 +IGHE +IGHG4 +IGHG2 +IGHA1 +IGHG1 +IGHG3 +IGHD +IGHM +IGHJ6 +IGHJ5 +IGHJ4 +IGHJ3 +IGHJ2 +IGHJ1 +IGHD7-27 +IGHD1-26 +IGHD6-25 +IGHD5-24 +IGHD4-23 +IGHD3-22 +IGHD2-21 +IGHD1-20 +IGHD6-19 +IGHD5-18 +IGHD4-17 +IGHD3-16 +IGHD2-15 +IGHD1-14 +IGHD6-13 +IGHD5-12 +IGHD4-11 +IGHD3-10 +IGHD3-9 +IGHD2-8 +IGHD1-7 +IGHD6-6 +IGHD5-5 +IGHD4-4 +IGHD3-3 +IGHD2-2 +IGHD1-1 +IGHV6-1 +IGHV1-2 +IGHV1-3 +IGHV4-4 +IGHV7-4-1 +IGHV2-5 +IGHV3-7 +IGHV3-64D +IGHV5-10-1 +IGHV3-11 +IGHV3-13 +IGHV3-15 +IGHV3-16 +IGHV1-18 +IGHV3-20 +IGHV3-21 +IGHV3-23 +IGHV1-24 +IGHV2-26 +IGHV4-28 +IGHV3-30 +IGHV4-31 +IGHV3-33 +IGHV4-34 +IGHV3-35 +IGHV3-38 +IGHV4-39 +IGHV3-43 +IGHV1-45 +IGHV1-46 +IGHV3-48 +IGHV3-49 +IGHV5-51 +IGHV3-53 +IGHV1-58 +IGHV4-59 +IGHV4-61 +IGHV3-64 +IGHV3-66 +IGHV1-69 +IGHV2-70D +IGHV1-69-2 +IGHV1-69D +IGHV2-70 +IGHV3-72 +IGHV3-73 +IGHV3-74 +IGHV7-81 +IGHV1OR15-9 +IGHV3OR15-7 +IGHD5OR15-5A +IGHD4OR15-4A +IGHD3OR15-3A +IGHD2OR15-2A +IGHD1OR15-1A +IGHD5OR15-5B +IGHD4OR15-4B +IGHD3OR15-3B +IGHD2OR15-2B +IGHD1OR15-1B +AC135068.8 +AC135068.2 +IGHV1OR15-1 +IGHV4OR15-8 +IGHV3OR16-9 +IGHV2OR16-5 +IGHV3OR16-10 +IGHV3OR16-8 +IGHV3OR16-12 +IGHV3OR16-13 +IGHV1OR21-1 +IGLV4-69 +IGLV10-54 +IGLV8-61 +IGLV4-60 +IGLV6-57 +IGLV11-55 +IGLV5-52 +IGLV1-51 +IGLV1-50 +IGLV9-49 +IGLV5-48 +IGLV1-47 +IGLV7-46 +IGLV5-45 +IGLV1-44 +IGLV7-43 +IGLV1-40 +IGLV5-37 +IGLV1-36 +IGLV2-33 +IGLV3-32 +IGLV3-27 +IGLV3-25 +IGLV2-23 +IGLV3-22 +IGLV3-21 +IGLV3-19 +IGLV2-18 +IGLV3-16 +IGLV2-14 +IGLV3-12 +IGLV2-11 +IGLV3-10 +IGLV3-9 +IGLV2-8 +IGLV4-3 +IGLV3-1 +IGLJ1 +IGLC1 +IGLJ2 +IGLC2 +IGLJ3 +IGLC3 +IGLJ4 +IGLJ5 +IGLJ6 +IGLJ7 +IGLC7 \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..b1e56ee --- /dev/null +++ b/LICENSE @@ -0,0 +1,28 @@ +BSD 3-Clause License + +Copyright (c) 2023, Princeton University + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/README.md b/README.md index b2f50d6..d29666a 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,232 @@ -# Locality clustering for CNV inference -A repo for the locality clustering (HMM) module in CNV calling across various data modalities. +# CalicoST + +

+ +

+ +CalicoST is a probabilistic model that infers allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics.CalicoST has the following key features: +1. Identifies allele-specific integer copy numbers for each transcribed region, revealing events such as copy neutral loss of heterozygosity (CNLOH) and mirrored subclonal CNAs that are invisible to total copy number analysis. +2. Assigns each spot a clone label indicating whether the spot is primarily normal cells or a cancer clone with aberration copy number profile. +3. Infers a phylogeny relating the identified cancer clones as well as a phylogeography that combines genetic evolution and spatial dissemination of clones. +4. Handles normal cell admixture in SRT technologies hat are not single-cell resolution (e.g. 10x Genomics Visium) to infer more accurate allele-specific copy numbers and cancer clones. +5. Simultaneously analyzes multiple regions or aligned SRT slices from the same tumor. + +# System requirements +The package has tested on the following Linux operating systems: SpringdaleOpenEnterprise 9.2 (Parma) and CentOS Linux 7 (Core). + +# Installation +## Minimum installation +First setup a conda environment from the `environment.yml` file: +``` +git clone https://github.com/raphael-group/CalicoST.git +cd CalicoST +conda env create -f environment.yml --name calicost_env +``` + + +Then, install CalicoST using pip by +``` +conda activate calicost_env +pip install -e . +``` + +Setting up the conda environments takes around 15 minutes on an HPC head node. + +## Additional installation for SNP parsing +CalicoST requires allele count matrices for reference-phased A and B alleles for inferring allele-specific CNAs, and provides a snakemake pipeline for obtaining the required matrices from a BAM file. Run the following commands in CalicoST directory for installing additional package, [Eagle2](https://alkesgroup.broadinstitute.org/Eagle/), for snakemake preprocessing pipeline. + +``` +mkdir external +wget --directory-prefix=external https://storage.googleapis.com/broad-alkesgroup-public/Eagle/downloads/Eagle_v2.4.1.tar.gz +tar -xzf external/Eagle_v2.4.1.tar.gz -C external +``` + +## Additional installation for reconstructing phylogeny +Based on the inferred cancer clones and allele-specific CNAs by CalicoST, we apply Startle to reconstruct a phylogenetic tree along the clones. Install Startle by +``` +git clone --recurse-submodules https://github.com/raphael-group/startle.git +cd startle +mkdir build; cd build +cmake -DLIBLEMON_ROOT=\ + -DCPLEX_INC_DIR=\ + -DCPLEX_LIB_DIR=\ + -DCONCERT_INC_DIR=\ + -DCONCERT_LIB_DIR=\ + .. +make +``` + + +# Getting started +### Preprocessing: genotyping and reference-based phasing +To infer allele-specific CNAs, we generate allele count matrices in this preprocessing step. We followed the recommended pipeline by [Numbat](https://kharchenkolab.github.io/numbat/), which is designed for scRNA-seq data to infer clones and CNAs: first genotyping using the BAM file by cellsnp-lite (included in the conda environment) and reference-based phasing by Eagle2. Download the following panels for genotyping and reference-based phasing. +* [SNP panel](https://sourceforge.net/projects/cellsnp/files/SNPlist/genome1K.phase3.SNP_AF5e4.chr1toX.hg38.vcf.gz) - 0.5GB in size. You can also choose other SNP panels from [cellsnp-lite webpage](https://cellsnp-lite.readthedocs.io/en/latest/main/data.html#data-list-of-common-snps). +* [Phasing panel](http://pklab.med.harvard.edu/teng/data/1000G_hg38.zip)- 9.0GB in size. Unzip the panel after downloading. + +Replace the following paths `config.yaml`: +* `region_vcf`: Replace with the path of downloaded SNP panel. +* `phasing_panel`: Replace with the unzipped directory of the downloaded phasing panel. +* `spaceranger_dir`: Replace with the spaceranger directory of your Visium data, which should contain the BAM file `possorted_genome_bam.bam`. +* `output_snpinfo`: Replace with the desired output directory. +* Replace `calicost_dir` and `eagledir` with the path to the cloned CalicoST directory and downloaded Eagle2 directory. + +Then you can run preprocessing pipeline by +``` +snakemake --cores --configfile config.yaml --snakefile calicost.smk all +``` + +### Inferring tumor purity per spot (optional) +Replace the paths in the parameter configuration file `configuration_purity` with the corresponding data/reference file paths and run +``` +OMP_NUM_THREADS=1 /src/calicost/estimate_tumor_proportion.py -c configuration_purity +``` + +### Inferring clones and allele-specific CNAs +Replace the paths in parameter configuration file `configuration_cna` with the corresponding data/reference file paths and run +``` +OMP_NUM_THREADS=1 python /src/calicost/calicost_main.py -c configuration_cna +``` + +When jointly inferring clones and CNAs across multiple SRT slices, prepare a table with the following columns (See [`examples/example_input_filelist`](https://github.com/raphael-group/CalicoST/blob/main/examples/example_input_filelist) as an example). +Path to BAM file | sample ID | Path to Spaceranger outs +Modify `configuration_cna_multi` with paths to the table and run +``` +OMP_NUM_THREADS=1 python /src/calicost/calicost_main.py -c configuration_cna_multi +``` + +### Reconstruct phylogeography + +``` +python /src/calicost/phylogeny_startle.py -c -s -o +``` + + +# Tutorials +Check out our [readthedocs](https://calicost.readthedocs.io/en/latest/) for the following tutorials: +1. [Inferring clones and allele-specific CNAs on simulated data](https://calicost.readthedocs.io/en/latest/notebooks/tutorials/simulated_data_tutorial.html) +The simulated count matrices and parameter configuration file are available from [`examples/simulated_example.tar.gz`](https://github.com/raphael-group/CalicoST/blob/main/examples/simulated_example.tar.gz). CalicoST takes about 2h to finish on this example. + +2. [Inferring tumor purity, clones, allele-specific CNAs, and phylogeography on prostate cancer data](https://calicost.readthedocs.io/en/latest/notebooks/tutorials/prostate_tutorial.html) +The transcript count, allele count matrices, and running configuration fies are available from [`examples/prostate_example.tar.gz`](https://github.com/raphael-group/CalicoST/blob/main/examples/prostate_example.tar.gz). This sample contains five slices and over 10000 spots, CalicoST takes about 9h to finish on this example. + + + + + +### Understanding the output +The above snakemake run will create a folder `calicost` in the directory of downloaded example data. Within this folder, each random initialization of CalicoST generates a subdirectory of `calicost/clone*`. + +CalicoST generates the following key files of each random initialization: +* clone_labels.tsv: The inferred clone labels for each spot. +* cnv_seglevel.tsv: Allele-specific copy numbers for each clone for each genome segment. +* cnv_genelevel.tsv: The projected allele-specific copy numbers from genome segments to the covered genes. +* cnv_diploid_seglevel.tsv, cnv_triploid_seglevel.tsv, cnv_tetraploid_seglevel.tsv, cnv_diploid_genelevel.tsv, cnv_triploid_genelevel.tsv, cnv_tetraploid_genelevel.tsv: Allele-specific copy numbers when enforcing a ploidy for each genome segment or each gene. + +See the following examples of the key files. +``` +head -10 calicost/clone3_rectangle0_w1.0/clone_labels.tsv +BARCODES clone_label +spot_0 2 +spot_1 2 +spot_2 2 +spot_3 2 +spot_4 2 +spot_5 2 +spot_6 2 +spot_7 2 +spot_8 0 +``` + +``` +head -10 calicost/clone3_rectangle0_w1.0/cnv_seglevel.tsv +CHR START END clone0 A clone0 B clone1 A clone1 B clone2 A clone2 B +1 1001138 1616548 1 1 1 1 1 1 +1 1635227 2384877 1 1 1 1 1 1 +1 2391775 6101016 1 1 1 1 1 1 +1 6185020 6653223 1 1 1 1 1 1 +1 6785454 7780639 1 1 1 1 1 1 +1 7784320 8020748 1 1 1 1 1 1 +1 8026738 9271273 1 1 1 1 1 1 +1 9292894 10375267 1 1 1 1 1 1 +1 10398592 11922488 1 1 1 1 1 1 +``` + +``` +head -10 calicost/clone3_rectangle0_w1.0/cnv_genelevel.tsv +gene clone0 A clone0 B clone1 A clone1 B clone2 A clone2 B +A1BG 1 1 1 1 1 1 +A1CF 1 1 1 1 1 1 +A2M 1 1 1 1 1 1 +A2ML1-AS1 1 1 1 1 1 1 +AACS 1 1 1 1 1 1 +AADAC 1 1 1 1 1 1 +AADACL2-AS1 1 1 1 1 1 1 +AAK1 1 1 1 1 1 1 +AAMP 1 1 1 1 1 1 +``` + +CalicoST graphs the following plots for visualizing the inferred cancer clones in space and allele-specific copy number profiles for each random initialization. +* plots/clone_spatial.pdf: The spatial distribution of inferred cancer clones and normal regions (grey color, clone 0 by default) +* plots/rdr_baf_defaultcolor.pdf: The read depth ratio (RDR) and B allele frequency (BAF) along the genome for each clone. Higher RDR indicates higher total copy numbers, and a deviation-from-0.5 BAF indicates allele imbalance due to allele-specific CNAs. +* plots/acn_genome.pdf: The default allele-specific copy numbers along the genome. +* plots/acn_genome_diploid.pdf, plots/acn_genome_triploid.pdf, plots/acn_genome_tetraploid.pdf: Allele-specific copy numbers when enforcing a ploidy. + +The allele-specific copy number plots have the following color legend. +

+ +

+ + +# Software dependencies +CalicoST uses the following command-line packages and python for extracting the BAF information +* samtools +* cellsnp-lite +* Eagle2 +* pysam +* snakemake + +CalicoST uses the following packages for the remaining steps to infer allele-specific copy numbers and cancer clones: +* numpy +* scipy +* pandas +* scikit-learn +* scanpy +* anndata +* numba +* tqdm +* statsmodels +* networkx +* matplotlib +* seaborn +* snakemake + + +# Citations +The CalicoST manuscript is available on bioRxiv. If you use CalicoST for your work, please cite our paper. +``` +@article{ma2024inferring, + title={Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics}, + author={Ma, Cong and Balaban, Metin and Liu, Jingxian and Chen, Siqi and Ding, Li and Raphael, Benjamin}, + journal={bioRxiv}, + pages={2024--03}, + year={2024}, + publisher={Cold Spring Harbor Laboratory} +} +``` \ No newline at end of file diff --git a/calicost.smk b/calicost.smk new file mode 100644 index 0000000..0444ec2 --- /dev/null +++ b/calicost.smk @@ -0,0 +1,132 @@ +import numpy as np +import pandas as pd +import scipy +import calicost.arg_parse +import calicost.parse_input + + +rule all: + input: + f"{config['output_snpinfo']}/cell_snp_Aallele.npz", + + +rule link_or_merge_bam: + output: + bam="{outputdir}/possorted_genome_bam.bam", + bai="{outputdir}/possorted_genome_bam.bam.bai", + barcodefile="{outputdir}/barcodes.txt", + params: + outputdir = "{outputdir}", + samtools_sorting_mem=config['samtools_sorting_mem'] + threads: 1 + log: + "{outputdir}/logs/link_or_merge_bam.log" + run: + if "bamlist" in config: + # merged BAM file + shell(f"python {config['calicost_dir']}/utils/merge_bamfile.py -b {config['bamlist']} -o {params.outputdir}/ >> {log} 2>&1") + shell(f"samtools sort -m {params.samtools_sorting_mem} -o {output.bam} {params.outputdir}/unsorted_possorted_genome_bam.bam >> {log} 2>&1") + shell(f"samtools index {output.bam}") + shell(f"rm -fr {params.outputdir}/unsorted_possorted_genome_bam.bam") + + # merged barcodes + df_entries = pd.read_csv(config["bamlist"], sep='\t', index_col=None, header=None) + df_barcodes = [] + for i in range(df_entries.shape[0]): + tmpdf = pd.read_csv(f"{df_entries.iloc[i,2]}/filtered_feature_bc_matrix/barcodes.tsv.gz", header=None, index_col=None) + tmpdf.iloc[:,0] = [f"{x}_{df_entries.iloc[i,1]}" for x in tmpdf.iloc[:,0]] + df_barcodes.append( tmpdf ) + df_barcodes = pd.concat(df_barcodes, ignore_index=True) + df_barcodes.to_csv(f"{output.barcodefile}", sep='\t', index=False, header=False) + else: + # BAM file + assert "spaceranger_dir" in config + print("softlink of possorted_genome_bam.bam") + shell(f"ln -sf -T {config['spaceranger_dir']}/possorted_genome_bam.bam {output.bam}") + shell(f"ln -sf -T {config['spaceranger_dir']}/possorted_genome_bam.bam.bai {output.bai}") + # barcodes + shell(f"gunzip -c {config['spaceranger_dir']}/filtered_feature_bc_matrix/barcodes.tsv.gz > {output.barcodefile}") + + + +rule genotype: + input: + barcodefile="{outputdir}/barcodes.txt", + bam="{outputdir}/possorted_genome_bam.bam", + bai="{outputdir}/possorted_genome_bam.bam.bai" + output: + vcf="{outputdir}/genotyping/cellSNP.base.vcf.gz" + params: + outputdir="{outputdir}", + region_vcf=config['region_vcf'] + threads: config['nthreads_cellsnplite'] + log: + "{outputdir}/logs/genotyping.log" + run: + shell(f"mkdir -p {params.outputdir}/genotyping") + command = f"cellsnp-lite -s {input.bam} " + \ + f"-b {input.barcodefile} " + \ + f"-O {params.outputdir}/genotyping/ " + \ + f"-R {params.region_vcf} " + \ + f"-p {threads} " + \ + f"--minMAF 0 --minCOUNT 2 --UMItag {config['UMItag']} --cellTAG {config['cellTAG']} --gzip >> {log} 2>&1" + print(command) + shell(command) + + + +rule pre_phasing: + input: + vcf="{outputdir}/genotyping/cellSNP.base.vcf.gz" + output: + expand("{{outputdir}}/phasing/chr{chrname}.vcf.gz", chrname=config["chromosomes"]) + params: + outputdir="{outputdir}", + threads: 1 + run: + shell(f"mkdir -p {params.outputdir}/phasing") + print(f"python {config['calicost_dir']}/utils/filter_snps_forphasing.py -c {params.outputdir}/genotyping -o {params.outputdir}/phasing") + shell(f"python {config['calicost_dir']}/utils/filter_snps_forphasing.py -c {params.outputdir}/genotyping -o {params.outputdir}/phasing") + for chrname in config["chromosomes"]: + shell(f"bgzip -f {params.outputdir}/phasing/chr{chrname}.vcf") + shell(f"tabix -f {params.outputdir}/phasing/chr{chrname}.vcf.gz") + + +rule phasing: + input: + vcf="{outputdir}/phasing/chr{chrname}.vcf.gz" + output: + "{outputdir}/phasing/chr{chrname}.phased.vcf.gz" + params: + outputdir="{outputdir}", + chrname="{chrname}", + threads: 2 + log: + "{outputdir}/logs/phasing_chr{chrname}.log", + run: + command = f"{config['eagledir']}/eagle --numThreads {threads} --vcfTarget {input.vcf} " + \ + f"--vcfRef {config['phasing_panel']}/chr{params.chrname}.genotypes.bcf " + \ + f"--geneticMapFile={config['eagledir']}/tables/genetic_map_hg38_withX.txt.gz "+ \ + f"--outPrefix {params.outputdir}/phasing/chr{params.chrname}.phased >> {log} 2>&1" + shell(command) + + + +rule parse_final_snp: + input: + "{outputdir}/genotyping/cellSNP.base.vcf.gz", + expand("{{outputdir}}/phasing/chr{chrname}.phased.vcf.gz", chrname=config["chromosomes"]), + output: + "{outputdir}/cell_snp_Aallele.npz", + "{outputdir}/cell_snp_Ballele.npz", + "{outputdir}/unique_snp_ids.npy" + params: + outputdir="{outputdir}", + threads: 1 + log: + "{outputdir}/logs/parse_final_snp.log" + run: + command = f"python {config['calicost_dir']}/utils/get_snp_matrix.py " + \ + f"-c {params.outputdir}/genotyping -e {params.outputdir}/phasing -b {params.outputdir}/barcodes.txt -o {params.outputdir}/ >> {log} 2>&1" + shell( command ) + diff --git a/config.yaml b/config.yaml new file mode 100644 index 0000000..a7c65d9 --- /dev/null +++ b/config.yaml @@ -0,0 +1,21 @@ +# path to executables or their parent directories +calicost_dir: +eagledir: + +# running parameters +# samtools sort (only used when joingly calling from multiple slices) +samtools_sorting_mem: "4G" +# cellsnp-lite +UMItag: "Auto" +cellTAG: "CB" +nthreads_cellsnplite: 20 +region_vcf: +# Eagle phasing +phasing_panel: +chromosomes: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22] + +# input +spaceranger_dir: + +# output +output_snpinfo: diff --git a/configuration_cna b/configuration_cna new file mode 100644 index 0000000..b0c2929 --- /dev/null +++ b/configuration_cna @@ -0,0 +1,56 @@ + +spaceranger_dir : +snp_dir : +output_dir : + +# supporting files and preprocessing arguments +geneticmap_file : /GRCh38_resources/genetic_map_GRCh38_merged.tab.gz +hgtable_file : /GRCh38_resources/hgTables_hg38_gencode.txt +normalidx_file : None +tumorprop_file : None +supervision_clone_file : None +filtergenelist_file : /GRCh38_resources/ig_gene_list.txt +filterregion_file : /GRCh38_resources/HLA_regions.bed +secondary_min_umi : 300 +bafonly : False + +# phase switch probability +nu : 1.0 +logphase_shift : -2.0 +npart_phasing : 3 + +# HMRF configurations +n_clones : 3 +n_clones_rdr : 2 +min_spots_per_clone : 100 +min_avgumi_per_clone : 10 +maxspots_pooling : 7 +tumorprop_threshold : 0.5 +max_iter_outer : 20 +nodepotential : weighted_sum +initialization_method : rectangle +num_hmrf_initialization_start : 0 +num_hmrf_initialization_end : 1 +spatial_weight : 1.0 +construct_adjacency_method : hexagon +construct_adjacency_w : 1.0 + +# HMM configurations +n_states : 7 +params : smp +t : 1-1e-5 +t_phaseing : 0.9999 +fix_NB_dispersion : False +shared_NB_dispersion : True +fix_BB_dispersion : False +shared_BB_dispersion : True +max_iter : 30 +tol : 0.0001 +gmm_random_state : 0 +np_threshold : 1.0 +np_eventminlen : 10 + +# integer copy number +nonbalance_bafdist : 1.0 +nondiploid_rdrdist : 10.0 + diff --git a/configuration_cna_multi b/configuration_cna_multi new file mode 100644 index 0000000..72ecc33 --- /dev/null +++ b/configuration_cna_multi @@ -0,0 +1,57 @@ + +input_filelist: +snp_dir : +output_dir : + +# supporting files and preprocessing arguments +geneticmap_file : /GRCh38_resources/genetic_map_GRCh38_merged.tab.gz +hgtable_file : /GRCh38_resources/hgTables_hg38_gencode.txt +normalidx_file : None +tumorprop_file : None +alignment_files : +supervision_clone_file : None +filtergenelist_file : /GRCh38_resources/ig_gene_list.txt +filterregion_file : /GRCh38_resources/HLA_regions.bed +secondary_min_umi : 300 +bafonly : False + +# phase switch probability +nu : 1.0 +logphase_shift : -2.0 +npart_phasing : 3 + +# HMRF configurations +n_clones : 3 +n_clones_rdr : 2 +min_spots_per_clone : 100 +min_avgumi_per_clone : 10 +maxspots_pooling : 7 +tumorprop_threshold : 0.5 +max_iter_outer : 20 +nodepotential : weighted_sum +initialization_method : rectangle +num_hmrf_initialization_start : 0 +num_hmrf_initialization_end : 1 +spatial_weight : 1.0 +construct_adjacency_method : hexagon +construct_adjacency_w : 1.0 + +# HMM configurations +n_states : 7 +params : smp +t : 1-1e-5 +t_phaseing : 0.9999 +fix_NB_dispersion : False +shared_NB_dispersion : True +fix_BB_dispersion : False +shared_BB_dispersion : True +max_iter : 30 +tol : 0.0001 +gmm_random_state : 0 +np_threshold : 1.0 +np_eventminlen : 10 + +# integer copy number +nonbalance_bafdist : 1.0 +nondiploid_rdrdist : 10.0 + diff --git a/configuration_purity b/configuration_purity new file mode 100644 index 0000000..d0d174f --- /dev/null +++ b/configuration_purity @@ -0,0 +1,57 @@ + +spaceranger_dir : +snp_dir : +output_dir : + +# supporting files and preprocessing arguments +geneticmap_file : /GRCh38_resources/genetic_map_GRCh38_merged.tab.gz +hgtable_file : /GRCh38_resources/hgTables_hg38_gencode.txt +normalidx_file : None +tumorprop_file : None +alignment_files : +supervision_clone_file : None +filtergenelist_file : /GRCh38_resources/ig_gene_list.txt +filterregion_file : /GRCh38_resources/HLA_regions.bed +secondary_min_umi : 400 +bafonly : False + +# phase switch probability +nu : 1.0 +logphase_shift : -2.0 +npart_phasing : 3 + +# HMRF configurations +n_clones : 5 +n_clones_rdr : 2 +min_spots_per_clone : 100 +min_avgumi_per_clone : 10 +maxspots_pooling : 19 +tumorprop_threshold : 0.5 +max_iter_outer : 20 +nodepotential : weighted_sum +initialization_method : rectangle +num_hmrf_initialization_start : 0 +num_hmrf_initialization_end : 1 +spatial_weight : 1.0 +construct_adjacency_method : hexagon +construct_adjacency_w : 1.0 + +# HMM configurations +n_states : 7 +params : smp +t : 1-1e-4 +t_phaseing : 0.9999 +fix_NB_dispersion : False +shared_NB_dispersion : True +fix_BB_dispersion : False +shared_BB_dispersion : True +max_iter : 30 +tol : 0.0001 +gmm_random_state : 0 +np_threshold : 1.0 +np_eventminlen : 10 + +# integer copy number +nonbalance_bafdist : 1.0 +nondiploid_rdrdist : 10.0 + diff --git a/docs/_ext/typed_returns.py b/docs/_ext/typed_returns.py new file mode 100644 index 0000000..9b14312 --- /dev/null +++ b/docs/_ext/typed_returns.py @@ -0,0 +1,27 @@ +import re +from typing import Iterable, Iterator, List + +from sphinx.application import Sphinx +from sphinx.ext.napoleon import NumpyDocstring + + +def _process_return(lines: Iterable[str]) -> Iterator[str]: + for line in lines: + m = re.fullmatch(r"(?P\w+)\s+:\s+(?P[\w.]+)", line) + if m: + # Once this is in scanpydoc, we can use the fancy hover stuff + yield f'**{m["param"]}** : :class:`~{m["type"]}`' + else: + yield line + + +def _parse_returns_section(self: NumpyDocstring, section: str) -> list[str]: + lines_raw = list(_process_return(self._dedent(self._consume_to_next_section()))) + lines: list[str] = self._format_block(":returns: ", lines_raw) + if lines and lines[-1]: + lines.append("") + return lines + + +def setup(app: Sphinx) -> None: + NumpyDocstring._parse_returns_section = _parse_returns_section diff --git a/docs/_static/css/custom.css b/docs/_static/css/custom.css new file mode 100644 index 0000000..70f5d13 --- /dev/null +++ b/docs/_static/css/custom.css @@ -0,0 +1,112 @@ +.small { + font-size: 55%; +} + +div.version { + color: #FFD92C!important; +} + +.wy-nav-side { + background: #242335; +} + +.wy-side-nav-search { + background-color: #242335; +} + +.wy-side-nav-search input[type="text"] { + border-radius: 6px!important; +} + +.wy-nav-content { + max-width: 950px; +} + +.wy-menu-vertical a { + color: #eceef4; +} + +.wy-menu-vertical li.current { + background: #f1f5fb; +} + +.wy-menu-vertical li.toctree-l2.current > a { + background: #34377d2e; +} + +.wy-menu-vertical li.toctree-l2.current li.toctree-l3 > a { + background: #34377d4a; +} + +.wy-menu-vertical li.toctree-l3.current li.toctree-l4 > a { + background: #34377d7d; +} + +.wy-menu-vertical a:hover { + background-color: #6b86b0; +} + +.wy-menu-vertical li.current a:hover { + background: #bdcde6a3; +} + +a { + color: #5B64B1; +} + +.rst-content .viewcode-link { + color: #7013e1d9; +} + +.highlight { + background: #f1f5fb!important; +} + +.rst-content div[class^="highlight"] { + border: 1px solid #e4eaf2; +} + +.wy-menu-vertical p.caption { + color: #FFD92C; +} + +div.output_subarea.output_html.rendered_html.output_result{ + overflow: auto; +} + +/* function/class top bar */ +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple) > dt { + color: #404040; + border-top: solid 4px #7013e1d9; + background: #FFD833A8; +} + +/* class params */ +html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(.simple) dl:not(.field-list) > dt { + color: #404040; + border-left: solid 4px #7013e1d9; + background: #FFD8338F; +} + +/* the other elements, but more specific - leave them be */ +code.docutils.literal.notranslate > span[class="pre"] { + font-weight: bold; + color: #404040; +} + +/* odd rows in API */ +.rst-content table.docutils:not(.field-list) tr:nth-child(2n-1) td { + background-color: #f6f6f3; +} + +.rst-content div[class^="highlight"] pre { + padding: 8px; +} + +.rst-content .seealso { + background: #fafae2!important; +} + +.rst-content .seealso .admonition-title { + background: #7013e1d9!important; +} diff --git a/docs/_static/css/dataframe.css b/docs/_static/css/dataframe.css new file mode 100644 index 0000000..748df9d --- /dev/null +++ b/docs/_static/css/dataframe.css @@ -0,0 +1,43 @@ +/* Pandas dataframe css */ +/* Taken from: https://github.com/spatialaudio/nbsphinx/blob/fb3ba670fc1ba5f54d4c487573dbc1b4ecf7e9ff/src/nbsphinx.py#L587-L619 */ +/* modified margin-left */ + +table.dataframe { + border: none !important; + border-collapse: collapse; + border-spacing: 0; + border-color: transparent; + color: black; + font-size: 12px; + table-layout: fixed; + margin-left: 0!important; +} + +table.dataframe thead { + border-bottom: 1px solid black; + vertical-align: bottom; +} + +table.dataframe tr, +table.dataframe th, +table.dataframe td { + text-align: right; + vertical-align: middle; + padding: 0.5em 0.5em; + line-height: normal; + white-space: normal; + max-width: none; + border: none; +} + +table.dataframe th { + font-weight: bold; +} + +table.dataframe tbody tr:nth-child(odd) { + background: #f5f5f5; +} + +table.dataframe tbody tr:hover { + background: rgba(66, 165, 245, 0.2); +} diff --git a/docs/_static/css/nbsphinx.css b/docs/_static/css/nbsphinx.css new file mode 100644 index 0000000..6d1867f --- /dev/null +++ b/docs/_static/css/nbsphinx.css @@ -0,0 +1,24 @@ +div.nbinput.container div.prompt, +div.nboutput.container div.prompt { + display: none; +} + +div.nbinput.container div.prompt > div.highlight, +div.nboutput.container div.prompt > div.highlight { + display: none; +} + +div.nbinput.container div.input_area div[class*="highlight"] > pre, +div.nboutput.container div.output_area div[class*="highlight"] > pre { + padding: 8px!important; +} + +div.nboutput.container div.output_area > div[class^="highlight"] { + background-color: #fafae2!important; +} + +.rst-content .output_area img { + max-width: unset; + width: 100% !important; + height: auto !important; +} diff --git a/docs/_static/css/sphinx_gallery.css b/docs/_static/css/sphinx_gallery.css new file mode 100644 index 0000000..c5d499b --- /dev/null +++ b/docs/_static/css/sphinx_gallery.css @@ -0,0 +1,104 @@ +#graph, #image, #core-tutorials, #external-tutorials, #gallery { + margin-bottom: 1em; +} + +div.sphx-glr-download a { + background-color: #FFD92C9E!important; + background-image: none!important; + border-radius: 2px!important; + border: 1px solid #f4c200!important; + color: #404040!important; + font-weight bold !important; + padding: 0.1cm!important; + text-align: center!important; +} + + +div.sphx-glr-download a[href$=".py"] { + display: none!important; +} + +div.sphx-glr-example-title div[class="highlight"] { + background-color: #F5F5F5; + border: none; +} + +/ * notebook output cell */ +.sphx-glr-script-out .highlight pre { + background: #FDFFD9!important; +} + +p.sphx-glr-script-out { + display: none !important; +} + +div.sphx-glr-download p { + margin: 0!important; + width: auto!important; +} + +.sphx-glr-script-out { + color: #404040 !important; + margin: -24px 0px 0px 0px !important; +} + +p.sphx-glr-signature { + display: none!important; +} + +div.sphx-glr-download-link-note { + display: none!important; +} + +/* this gets rid of uneven vertical padding */ +div.sphx-glr-download code.download { + display: block !important; +} + +.sphx-glr-thumbcontainer { + background: none !important; + border: 1px solid #7013e1d9!important; + text-align: center !important; + min-height: 220px !important; +} + +.sphx-glr-thumbcontainer a.internal:hover { + color: #7013e1d9!important; +} + +.sphx-glr-thumbcontainer .headerlink { + display: none !important; +} + +div.sphx-glr-thumbcontainer span { + font-style: normal !important; +} + +p.sphx-glr-timing { + margin: 0 !important; + padding-top: 24px; + border-top: 1px solid #000; +} + +.sphx-glr-thumbcontainer:hover { + box-shadow: 0 0 10px #7013e1d9!important +} + +/* sphinx-gallery inserts 2
after_repr_html_, ignore the 1st one */ +div[class="rendered_html"] + br { + display: none!important; +} + +/* remove `Jupyter notebook: ` from `Download Jupyter notebook: `*/ +div.sphx-glr-download-jupyter code.xref.download.docutils.literal.notranslate > span:nth-child(2), +div.sphx-glr-download-jupyter code.xref.download.docutils.literal.notranslate > span:nth-child(3) { + display: none!important; +} + +.sphx-glr-thumbcontainer a.internal { + padding: 140px 10px 0!important; +} + +div.binder-badge img { + width: 120px; +} diff --git a/docs/_static/img/acn_color_palette.png b/docs/_static/img/acn_color_palette.png new file mode 100644 index 0000000..d11058e Binary files /dev/null and b/docs/_static/img/acn_color_palette.png differ diff --git a/docs/_static/img/overview4_combine.pdf b/docs/_static/img/overview4_combine.pdf new file mode 100644 index 0000000..20957ac Binary files /dev/null and b/docs/_static/img/overview4_combine.pdf differ diff --git a/docs/_static/img/overview4_combine.png b/docs/_static/img/overview4_combine.png new file mode 100644 index 0000000..3efeba8 Binary files /dev/null and b/docs/_static/img/overview4_combine.png differ diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..f3814ca --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,152 @@ +# Configuration file for the Sphinx documentation builder. +# +# This file only contains a selection of the most common options. For a full +# list see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Path setup -------------------------------------------------------------- +import os +import sys +from datetime import datetime + +# from importlib.metadata import metadata +from pathlib import Path + +from sphinx.application import Sphinx + +HERE = Path(__file__).parent +# sys.path.insert(0, str(HERE.parent.parent)) # this way, we don't have to install squidpy +# sys.path.insert(0, os.path.abspath("_ext")) + +sys.path.insert(0, str(HERE / "_ext")) + +# -- Project information ----------------------------------------------------- + +project = 'CalicoST' +author = 'Ma et al.' +version = '1.0.0' +copyright = f"{datetime.now():%Y}, raphael-lab" + +# -- General configuration --------------------------------------------------- + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + "sphinx.ext.autodoc", + "sphinx.ext.napoleon", + "sphinx.ext.viewcode", + "sphinx_autodoc_typehints", + "sphinx.ext.intersphinx", + "sphinx.ext.autosummary", + "sphinx.ext.mathjax", + "sphinxcontrib.bibtex", + "sphinx_copybutton", + "myst_nb", + "nbsphinx", + "typed_returns", + "IPython.sphinxext.ipython_console_highlighting", +] +intersphinx_mapping = dict( # noqa: C408 + python=("https://docs.python.org/3", None), + numpy=("https://numpy.org/doc/stable/", None), + statsmodels=("https://www.statsmodels.org/stable/", None), + scipy=("https://docs.scipy.org/doc/scipy/", None), + pandas=("https://pandas.pydata.org/pandas-docs/stable/", None), + anndata=("https://anndata.readthedocs.io/en/stable/", None), + scanpy=("https://scanpy.readthedocs.io/en/stable/", None), + matplotlib=("https://matplotlib.org/stable/", None), + seaborn=("https://seaborn.pydata.org/", None), + networkx=("https://networkx.org/documentation/stable/", None), + sklearn=("https://scikit-learn.org/stable/", None), + numba=("https://numba.readthedocs.io/en/stable/", None), + ete3=("http://etetoolkit.org/docs/latest/", None), +) + +# Add any paths that contain templates here, relative to this directory. +templates_path = ["_templates"] +source_suffix = {".rst": "restructuredtext", ".ipynb": "myst-nb"} +master_doc = "index" +pygments_style = "sphinx" + +# myst +nb_execution_mode = "off" +myst_enable_extensions = [ + "colon_fence", + "dollarmath", + "amsmath", +] +myst_heading_anchors = 2 + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = [ + "notebooks/README.rst", + "notebooks/CONTRIBUTING.rst", + "release/changelog/*", + "**.ipynb_checkpoints", + "build", +] +suppress_warnings = ["download.not_readable", "git.too_shallow"] + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +autosummary_generate = True +autodoc_member_order = "groupwise" +autodoc_typehints = "signature" +autodoc_docstring_signature = True +napoleon_google_docstring = False +napoleon_numpy_docstring = True +napoleon_include_init_with_doc = False +napoleon_use_rtype = True +napoleon_use_param = True +todo_include_todos = False + +# bibliography +bibtex_bibfiles = ["references.bib"] +bibtex_reference_style = "author_year" +bibtex_default_style = "alpha" + +# spelling +spelling_lang = "en_US" +spelling_warning = True +spelling_word_list_filename = "spelling_wordlist.txt" +spelling_add_pypi_package_names = True +spelling_show_suggestions = True +spelling_exclude_patterns = ["references.rst"] +# see: https://pyenchant.github.io/pyenchant/api/enchant.tokenize.html +spelling_filters = [ + "enchant.tokenize.URLFilter", + "enchant.tokenize.EmailFilter", + "docs.source.utils.ModnameFilter", + "docs.source.utils.SignatureFilter", + "enchant.tokenize.MentionFilter", +] +# see the solution from: https://github.com/sphinx-doc/sphinx/issues/7369 +linkcheck_ignore = [ + # 403 Client Error + "https://doi.org/10.1126/science.aar7042", + "https://doi.org/10.1126/science.aau5324", + "https://doi.org/10.1093/bioinformatics/btab164", + "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2716260/", + "https://raw.githubusercontent.com/scverse/squidpy/main/docs/_static/img/figure1.png", +] + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_theme = "sphinx_rtd_theme" +html_static_path = ["_static"] +# html_logo = "_static/img/gaston_logo_v2.png" +html_theme_options = {"navigation_depth": 4, "logo_only": True} +html_show_sphinx = False + + +def setup(app: Sphinx) -> None: + app.add_css_file("css/custom.css") + app.add_css_file("css/sphinx_gallery.css") + app.add_css_file("css/nbsphinx.css") + app.add_css_file("css/dataframe.css") # had to add this manually \ No newline at end of file diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..4db020e --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,33 @@ +CalicoST - Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics +============================================================================================================================= + +.. image:: https://raw.githubusercontent.com/raphael-group/CalicoST/main/docs/_static/img/overview4_combine.png + :alt: CalicoST overview + :width: 800px + :align: center + +CalicoST is a probabilistic model that infers allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics.CalicoST has the following key features: +1. Identifies allele-specific integer copy numbers for each transcribed region, revealing events such as copy neutral loss of heterozygosity (CNLOH) and mirrored subclonal CNAs that are invisible to total copy number analysis. +2. Assigns each spot a clone label indicating whether the spot is primarily normal cells or a cancer clone with aberration copy number profile. +3. Infers a phylogeny relating the identified cancer clones as well as a phylogeography that combines genetic evolution and spatial dissemination of clones. +4. Handles normal cell admixture in SRT technologies hat are not single-cell resolution (e.g. 10x Genomics Visium) to infer more accurate allele-specific copy numbers and cancer clones. +5. Simultaneously analyzes multiple regional or aligned SRT slices from the same tumor. + + +Installation +------------ +Find the details of installation `here `_. + +Getting started with CalicoST +----------------------------- +Browse the Tutorials to get started with CalicoST `here `_. + +.. toctree:: + :maxdepth: 1 + + installation + tutorials + parameters + references + +.. _github: https://github.com/raphael-group/CalicoST \ No newline at end of file diff --git a/docs/installation.rst b/docs/installation.rst new file mode 100644 index 0000000..67cec6f --- /dev/null +++ b/docs/installation.rst @@ -0,0 +1,58 @@ +Installation +============ +Minimum installation +-------------------- +First setup a conda environment from the `environment.yml` file: + +.. code-block:: bash + + git clone https://github.com/raphael-group/CalicoST.git + cd CalicoST + conda env create -f environment.yml --name calicost_env + + +Then, install CalicoST using pip by + +.. code-block:: bash + + conda activate calicost_env + pip install -e . + + +Setting up the conda environments takes around 15 minutes on an HPC head node. + +Additional installation for SNP parsing +--------------------------------------- +CalicoST requires allele count matrices for reference-phased A and B alleles for inferring allele-specific CNAs, and provides a snakemake pipeline for obtaining the required matrices from a BAM file. Run the following commands in CalicoST directory for installing additional package, [Eagle2](https://alkesgroup.broadinstitute.org/Eagle/), for snakemake preprocessing pipeline. + +.. code-block:: bash + + mkdir external + wget --directory-prefix=external https://storage.googleapis.com/broad-alkesgroup-public/Eagle/downloads/Eagle_v2.4.1.tar.gz + tar -xzf external/Eagle_v2.4.1.tar.gz -C external + + +Additional installation for reconstructing phylogeny +---------------------------------------------------- +Based on the inferred cancer clones and allele-specific CNAs by CalicoST, we apply Startle to reconstruct a phylogenetic tree along the clones. Install Startle by + +.. code-block:: bash + + git clone --recurse-submodules https://github.com/raphael-group/startle.git + cd startle + mkdir build; cd build + cmake -DLIBLEMON_ROOT=\ + -DCPLEX_INC_DIR=\ + -DCPLEX_LIB_DIR=\ + -DCONCERT_INC_DIR=\ + -DCONCERT_LIB_DIR=\ + .. + make + + +Prepare reference files for SNP parsing +-------------------- +We followed the recommended pipeline by `Numbat `_` for parsing SNP information from BAM file(s): first genotyping using the BAM file by cellsnp-lite (included in the conda environment) and reference-based phasing by Eagle2. Download the following panels for genotyping and reference-based phasing. + +* `SNP panel `_ - 0.5GB in size. You can also choose other SNP panels from `cellsnp-lite webpage `_. +* `Phasing panel `_ - 9.0GB in size. Unzip the panel after downloading. diff --git a/docs/notebooks/tutorials/prostate_tutorial.ipynb b/docs/notebooks/tutorials/prostate_tutorial.ipynb new file mode 100644 index 0000000..54df063 --- /dev/null +++ b/docs/notebooks/tutorials/prostate_tutorial.ipynb @@ -0,0 +1,1970 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5a234ce5-cbe3-4431-87be-7a1d7490c6fd", + "metadata": {}, + "source": [ + "# Run CalicoST on prostate cancer dataset" + ] + }, + { + "cell_type": "markdown", + "id": "297f7e52-56c0-4e8d-92fa-40b961acdfbd", + "metadata": {}, + "source": [ + "## Download the data" + ] + }, + { + "cell_type": "markdown", + "id": "28f5b861-7bf8-4e99-8cae-d00c06db7d14", + "metadata": {}, + "source": [ + "We applied CalicoST on five slices in a prostate cross section from [Erickon et al.](https://www.nature.com/articles/s41586-022-05023-2) to study the cancer clones and spatial tumor evolution.\n", + "\n", + "We provided the transcript count matrices from spaceranger output and the allele count matrices in [examples/prostate_example.tar.gz](https://github.com/raphael-group/CalicoST/blob/main/examples/prostate_example.tar.gz), so that users can download and start running from there.\n", + "\n", + "After downloading and untarring file, you will see the following files/directories\n", + "* prostate_example\n", + " * bamfile_list.tsv: A table of SRT slices with the paths to jointly identify clones and CNAs.\n", + " * data: Spacerange directories of the SRT slices.\n", + " * snpinfo: Allele count matrices from preprocessing Snakemake pipeline.\n", + " * configuration_purity: Parameter configuration of CalicoST for inferring tumor proportion per spot.\n", + " * configuration_cna_multi: Parameter configuration of CalicoST for inferring clones and CNAs.\n", + " * estimate_tumor_prop: An empty directory to store future results for estimating tumor proportion.\n", + " * calicost: An empty directory to store future results for inferred clones and CNAs.\n", + "\n", + "Download and untar the data by\n", + "```\n", + "tar -xzvf /examples/prostate_example.tar.gz\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "06d471bc-f461-4f77-8e1f-8093b572a01e", + "metadata": {}, + "source": [ + "## Estimate tumor proportion per spot" + ] + }, + { + "cell_type": "markdown", + "id": "1612bea0-9fbe-40a1-af67-49ad3060b3fe", + "metadata": {}, + "source": [ + "CalicoST can estimate tumor proportions based on the BAF signals. To use CalicoST for inferring tumor proportion, first replace \"\\\" in the `configuration_purity` file with the cloned CalicoST directory.\n", + "\n", + "Then, run the following command in terminal\n", + "\n", + "```\n", + "cd prostate_example\n", + "OMP_NUM_THREADS=1 python /src/calicost/estimate_tumor_proportion.py -c configuration_purity\n", + "```\n", + "\n", + "This command takes about 1.5 hours to run and will generate an output file of `estimate_tumor_prop/loh_estimator_tumor_prop.tsv`." + ] + }, + { + "cell_type": "markdown", + "id": "93640398", + "metadata": {}, + "source": [ + "### Load and visualize inferred tumor proportions\n", + "\n", + "We load and visualize the estimated tumor proportions as follows." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "194a04dc-6a5d-4e05-9b60-da3731218157", + "metadata": {}, + "outputs": [], + "source": [ + "import scanpy as sc\n", + "import numpy as np\n", + "import pandas as pd\n", + "from matplotlib import pyplot as plt\n", + "import seaborn as sns\n", + "import copy" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "8651d4c7-18f9-47e8-80ee-8c060fb84f53", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Tumor
BARCODES
AAACAAGTATCTCCCA-1_H120.050000
AAACAGGGTCTATATT-1_H12NaN
AAACATTTCCCGGATT-1_H120.050000
AAACCGGGTAGGTACC-1_H120.825997
AAACCGTTCGTCCAGG-1_H120.940555
......
TTGTTCAGTGTGCTAC-1_H250.050000
TTGTTGTGTGTCAAGA-1_H250.188937
TTGTTTCACATCCAGG-1_H250.956014
TTGTTTCATTAGTCTA-1_H250.838851
TTGTTTCCATACAACT-1_H250.364009
\n", + "

13344 rows × 1 columns

\n", + "
" + ], + "text/plain": [ + " Tumor\n", + "BARCODES \n", + "AAACAAGTATCTCCCA-1_H12 0.050000\n", + "AAACAGGGTCTATATT-1_H12 NaN\n", + "AAACATTTCCCGGATT-1_H12 0.050000\n", + "AAACCGGGTAGGTACC-1_H12 0.825997\n", + "AAACCGTTCGTCCAGG-1_H12 0.940555\n", + "... ...\n", + "TTGTTCAGTGTGCTAC-1_H25 0.050000\n", + "TTGTTGTGTGTCAAGA-1_H25 0.188937\n", + "TTGTTTCACATCCAGG-1_H25 0.956014\n", + "TTGTTTCATTAGTCTA-1_H25 0.838851\n", + "TTGTTTCCATACAACT-1_H25 0.364009\n", + "\n", + "[13344 rows x 1 columns]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Modify the example_directory to be the path of the downloaded and untarred data.\n", + "example_directory = \"./\"\n", + "\n", + "tumor_proportions = pd.read_csv(f'{example_directory}/estimate_tumor_prop/loh_estimator_tumor_prop.tsv', header=0, index_col=0, sep='\\t')\n", + "tumor_proportions" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d03c6dd9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "ACGCCTGACACGCGCT-1 0 0 0 1466 \n", + "TACCGATCCAACACTT-1 0 1 1 1592 \n", + "ATTAAAGCGGACGAGC-1 0 0 2 1466 \n", + "GATAAGGGACGATTAG-1 0 1 3 1592 \n", + "GTGCAAATCACCAATA-1 0 0 4 1466 \n", + "\n", + " pxl_col_in_fullres \n", + "barcode \n", + "ACGCCTGACACGCGCT-1 1298 \n", + "TACCGATCCAACACTT-1 1370 \n", + "ATTAAAGCGGACGAGC-1 1443 \n", + "GATAAGGGACGATTAG-1 1515 \n", + "GTGCAAATCACCAATA-1 1588 \n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "ACGCCTGACACGCGCT-1 0 0 0 1831 \n", + "TACCGATCCAACACTT-1 0 1 1 1983 \n", + "ATTAAAGCGGACGAGC-1 0 0 2 1831 \n", + "GATAAGGGACGATTAG-1 0 1 3 1983 \n", + "GTGCAAATCACCAATA-1 0 0 4 1831 \n", + "\n", + " pxl_col_in_fullres \n", + "barcode \n", + "ACGCCTGACACGCGCT-1 1544 \n", + "TACCGATCCAACACTT-1 1631 \n", + "ATTAAAGCGGACGAGC-1 1718 \n", + "GATAAGGGACGATTAG-1 1805 \n", + "GTGCAAATCACCAATA-1 1892 \n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "ACGCCTGACACGCGCT-1 0 0 0 1593 \n", + "TACCGATCCAACACTT-1 0 1 1 1720 \n", + "ATTAAAGCGGACGAGC-1 0 0 2 1593 \n", + "GATAAGGGACGATTAG-1 0 1 3 1719 \n", + "GTGCAAATCACCAATA-1 0 0 4 1593 \n", + "\n", + " pxl_col_in_fullres \n", + "barcode \n", + "ACGCCTGACACGCGCT-1 1172 \n", + "TACCGATCCAACACTT-1 1245 \n", + "ATTAAAGCGGACGAGC-1 1317 \n", + "GATAAGGGACGATTAG-1 1390 \n", + "GTGCAAATCACCAATA-1 1462 \n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "ACGCCTGACACGCGCT-1 0 0 0 1830 \n", + "TACCGATCCAACACTT-1 0 1 1 1982 \n", + "ATTAAAGCGGACGAGC-1 0 0 2 1831 \n", + "GATAAGGGACGATTAG-1 0 1 3 1982 \n", + "GTGCAAATCACCAATA-1 0 0 4 1831 \n", + "\n", + " pxl_col_in_fullres \n", + "barcode \n", + "ACGCCTGACACGCGCT-1 1523 \n", + "TACCGATCCAACACTT-1 1610 \n", + "ATTAAAGCGGACGAGC-1 1697 \n", + "GATAAGGGACGATTAG-1 1784 \n", + "GTGCAAATCACCAATA-1 1871 \n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "ACGCCTGACACGCGCT-1 0 0 0 1948 \n", + "TACCGATCCAACACTT-1 0 1 1 2100 \n", + "ATTAAAGCGGACGAGC-1 0 0 2 1948 \n", + "GATAAGGGACGATTAG-1 0 1 3 2100 \n", + "GTGCAAATCACCAATA-1 0 0 4 1947 \n", + "\n", + " pxl_col_in_fullres \n", + "barcode \n", + "ACGCCTGACACGCGCT-1 1441 \n", + "TACCGATCCAACACTT-1 1529 \n", + "ATTAAAGCGGACGAGC-1 1616 \n", + "GATAAGGGACGATTAG-1 1705 \n", + "GTGCAAATCACCAATA-1 1791 \n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "slice_ids = ['H12', 'H14', 'H15', 'H21', 'H25']\n", + "directory_name = ['P1_H1_2_visium', 'P1_H1_4_visium', 'P1_H1_5_visium', 'P1_H2_1_visium', 'P1_H2_5_visium']\n", + "\n", + "for i,s in enumerate(slice_ids):\n", + " # load spatial locations\n", + " # note that scanpy is incompatible with the latest tissue_positions.csv file, we directly load the positions as pandas data frame\n", + " df = pd.read_csv(f'{example_directory}/data/{directory_name[i]}/spatial/tissue_positions.csv', header=0, index_col=0, sep=',')\n", + " print(df.head())\n", + " # combine the position data frame with the tumor proportion dataframe\n", + " slice_tumor_proportions = tumor_proportions[tumor_proportions.index.str.endswith(s)]\n", + " df = df.join( slice_tumor_proportions.rename(index=lambda x:x.split(\"_\")[0]) )\n", + "\n", + " # plot\n", + " fig, axes = plt.subplots(1, 1, facecolor='white')\n", + " sns.scatterplot(x=df.array_row, y=df.array_col, hue=df.Tumor, palette='magma_r', linewidth=0, s=10, legend=False, ax=axes)\n", + " norm = plt.Normalize(np.nanmin(df.Tumor.values), np.nanmax(df.Tumor.values))\n", + " axes.figure.colorbar( plt.cm.ScalarMappable(cmap='magma_r', norm=norm), ax=axes )\n", + " axes.set_title(s)\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "a26ff025-5a1c-4c71-8689-47308d9ba2a8", + "metadata": {}, + "source": [ + "## Run CalicoST to infer CNAs and cancer clones based on estimated tumor proportions" + ] + }, + { + "cell_type": "markdown", + "id": "b65b83f2-89d4-4284-b914-6289ce673a50", + "metadata": {}, + "source": [ + "To infer cancer clones and CNAs by CalicoST, first replace \"\\\" in the `configuration_cna_multi` file with the cloned CalicoST directory. Note that the parameter configuration takes in the estimated tumor proportion in the previous section by specifying\n", + "\"tumorprop_file : estimate_tumor_prop/loh_estimator_tumor_prop.tsv\".\n", + "\n", + "Then, run the following command in terminal:\n", + "\n", + "```\n", + "OMP_NUM_THREADS=1 python /src/calicost/calicost_main.py -c configuration_cna_multi\n", + "```\n", + "\n", + "This command takes about 8h to finish." + ] + }, + { + "cell_type": "markdown", + "id": "74de80d8-63ad-4550-a628-5d741de3f60e", + "metadata": {}, + "source": [ + "### Load CalicoST-generated result tables" + ] + }, + { + "cell_type": "markdown", + "id": "a607883c-587b-4b7b-adba-7ebb93f1bd59", + "metadata": {}, + "source": [ + "`/clone5_rectangle0_w1.0/clone_labels.tsv` stores the inferred cancer clones for each spot. Note that spots with a low tumor purity will also be assigned to a cancer clone, despite that the inferred cancer clone label is not very meaningful for those nearly normal spots." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ee26403d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
clone_labeltumor_proportion
BARCODES
AAACAAGTATCTCCCA-1_H1230.050000
AAACAGGGTCTATATT-1_H123NaN
AAACATTTCCCGGATT-1_H1230.050000
AAACCGGGTAGGTACC-1_H1230.825997
AAACCGTTCGTCCAGG-1_H1230.940555
.........
TTGTTCAGTGTGCTAC-1_H2520.050000
TTGTTGTGTGTCAAGA-1_H2520.188937
TTGTTTCACATCCAGG-1_H2510.956014
TTGTTTCATTAGTCTA-1_H2510.838851
TTGTTTCCATACAACT-1_H2520.364009
\n", + "

13344 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " clone_label tumor_proportion\n", + "BARCODES \n", + "AAACAAGTATCTCCCA-1_H12 3 0.050000\n", + "AAACAGGGTCTATATT-1_H12 3 NaN\n", + "AAACATTTCCCGGATT-1_H12 3 0.050000\n", + "AAACCGGGTAGGTACC-1_H12 3 0.825997\n", + "AAACCGTTCGTCCAGG-1_H12 3 0.940555\n", + "... ... ...\n", + "TTGTTCAGTGTGCTAC-1_H25 2 0.050000\n", + "TTGTTGTGTGTCAAGA-1_H25 2 0.188937\n", + "TTGTTTCACATCCAGG-1_H25 1 0.956014\n", + "TTGTTTCATTAGTCTA-1_H25 1 0.838851\n", + "TTGTTTCCATACAACT-1_H25 2 0.364009\n", + "\n", + "[13344 rows x 2 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv(f\"{example_directory}/calicost/clone5_rectangle0_w1.0/clone_labels.tsv\", header=0, index_col=0, sep='\\t')\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "afe38fc3-ec59-455f-876d-10478ea09b84", + "metadata": {}, + "source": [ + "`/clone5_rectangle0_w1.0/cnv_seglevel.tsv` stores the allele-specific copy numbers of each genome bin within each clone. Each row is a genome bin, the columns containing the chromosome, start, and end position of the genome bin, and the inferred the A and B allele copy number within each cancer clone." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "73a50a49-5bf3-4331-a77b-8158de518c32", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
CHRSTARTENDclone1 Aclone1 Bclone2 Aclone2 Bclone3 Aclone3 Bclone4 Aclone4 Bclone5 Aclone5 B
018929514191361111111111
11143486114405681111111111
21144968914961231111111111
31151216217210781111111111
41172483823085681111111111
..........................................
22552246360834488983611111111111
22562249773283499639781111111111
22572250089879501802131111111111
22582250185915502920301111111111
22592250309030507836251111111111
\n", + "

2260 rows × 13 columns

\n", + "
" + ], + "text/plain": [ + " CHR START END clone1 A clone1 B clone2 A clone2 B \\\n", + "0 1 89295 1419136 1 1 1 1 \n", + "1 1 1434861 1440568 1 1 1 1 \n", + "2 1 1449689 1496123 1 1 1 1 \n", + "3 1 1512162 1721078 1 1 1 1 \n", + "4 1 1724838 2308568 1 1 1 1 \n", + "... ... ... ... ... ... ... ... \n", + "2255 22 46360834 48898361 1 1 1 1 \n", + "2256 22 49773283 49963978 1 1 1 1 \n", + "2257 22 50089879 50180213 1 1 1 1 \n", + "2258 22 50185915 50292030 1 1 1 1 \n", + "2259 22 50309030 50783625 1 1 1 1 \n", + "\n", + " clone3 A clone3 B clone4 A clone4 B clone5 A clone5 B \n", + "0 1 1 1 1 1 1 \n", + "1 1 1 1 1 1 1 \n", + "2 1 1 1 1 1 1 \n", + "3 1 1 1 1 1 1 \n", + "4 1 1 1 1 1 1 \n", + "... ... ... ... ... ... ... \n", + "2255 1 1 1 1 1 1 \n", + "2256 1 1 1 1 1 1 \n", + "2257 1 1 1 1 1 1 \n", + "2258 1 1 1 1 1 1 \n", + "2259 1 1 1 1 1 1 \n", + "\n", + "[2260 rows x 13 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv(f\"{example_directory}/calicost/clone5_rectangle0_w1.0/cnv_seglevel.tsv\", header=0, index_col=None, sep='\\t')\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "7a369b3e-78bd-4376-bee8-e473511a5287", + "metadata": {}, + "source": [ + "`/clone5_rectangle0_w1.0/cnv_genelevel.tsv` stores the allele-specific copy number for each gene. The copy number per gene is derived from projecting the allele-specific copy numbers of each genome bin to the spanned genes that have enough expression to be retained after CalicoST gene filtering step." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "efd47ed2-3fe9-4c9e-98da-9810786154ca", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
geneclone1 Aclone1 Bclone2 Aclone2 Bclone3 Aclone3 Bclone4 Aclone4 Bclone5 Aclone5 B
0AL627309.11111111111
1AL627309.51111111111
2LINC014091111111111
3LINC011281111111111
4LINC001151111111111
....................................
15035CHKB-DT1111111111
15036MAPK8IP21111111111
15037ARSA1111111111
15038SHANK31111111111
15039RABL2B1111111111
\n", + "

15040 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " gene clone1 A clone1 B clone2 A clone2 B clone3 A clone3 B \\\n", + "0 AL627309.1 1 1 1 1 1 1 \n", + "1 AL627309.5 1 1 1 1 1 1 \n", + "2 LINC01409 1 1 1 1 1 1 \n", + "3 LINC01128 1 1 1 1 1 1 \n", + "4 LINC00115 1 1 1 1 1 1 \n", + "... ... ... ... ... ... ... ... \n", + "15035 CHKB-DT 1 1 1 1 1 1 \n", + "15036 MAPK8IP2 1 1 1 1 1 1 \n", + "15037 ARSA 1 1 1 1 1 1 \n", + "15038 SHANK3 1 1 1 1 1 1 \n", + "15039 RABL2B 1 1 1 1 1 1 \n", + "\n", + " clone4 A clone4 B clone5 A clone5 B \n", + "0 1 1 1 1 \n", + "1 1 1 1 1 \n", + "2 1 1 1 1 \n", + "3 1 1 1 1 \n", + "4 1 1 1 1 \n", + "... ... ... ... ... \n", + "15035 1 1 1 1 \n", + "15036 1 1 1 1 \n", + "15037 1 1 1 1 \n", + "15038 1 1 1 1 \n", + "15039 1 1 1 1 \n", + "\n", + "[15040 rows x 11 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv(f\"{example_directory}/calicost/clone5_rectangle0_w1.0/cnv_genelevel.tsv\", header=0, index_col=None, sep='\\t')\n", + "df" + ] + }, + { + "cell_type": "markdown", + "id": "ed5513b9-d7fe-4cb2-bb4e-6165e1e0226e", + "metadata": {}, + "source": [ + "### Visualize CalicoST-generated plots\n", + "\n", + "Once CalicoST is finished running, it generates the plots of spatial organization of clones and allele-specific copy numbers. The plots are in PDF format and can be directly viewed. Below, we load the PDF plots in this notebook for easy visualization." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "dea9d0d3-6ac9-47f9-b277-ac0db051400a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from wand.image import Image as WImage\n", + "img = WImage(filename=f\"{example_directory}/calicost/clone5_rectangle0_w1.0/plots/clone_spatial.pdf\", resolution=100)\n", + "img" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f385b59e-f16d-4654-b363-c5fdce571ba9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# allele-specific copy numbers of each clone (the color scheme is the same as Fig2c\n", + "img = WImage(filename=f\"{example_directory}/calicost/clone5_rectangle0_w1.0/plots/acn_genome.pdf\", resolution=120)\n", + "img" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "564b3852-5b29-4454-b1ee-8a78177aad83", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# RDR-BAF plot along the genome for each clone\n", + "img = WImage(filename=f\"{example_directory}/calicost/clone5_rectangle0_w1.0/plots/rdr_baf_defaultcolor.pdf\", resolution=120)\n", + "img\n" + ] + }, + { + "cell_type": "markdown", + "id": "0948de8d-9114-44f0-8351-b4ec7be603fa", + "metadata": {}, + "source": [ + "## Reconstruct tumor phylogeny and phylogeography" + ] + }, + { + "cell_type": "markdown", + "id": "a16f1292-0fc7-49af-a1e1-ebb0bb78f369", + "metadata": {}, + "source": [ + "We use an existing phylogeny reconstruction method, [Startle](https://github.com/raphael-group/startle) by [Sashittal et al](https://linkinghub.elsevier.com/retrieve/pii/S2405471223003289), to infer a phylogeny of CalicoST-inferred cancer clones. To reconstruct a phylogeny based CalicoST results of the first random initialization, run the following command in shell:\n", + "```\n", + "mkdir calicost/phylogeny_clone5_rectangle0_w1.0\n", + "python /src/calicost/phylogeny_startle.py -c calicost/clone5_rectangle0_w1.0 -s -o calicost/phylogeny_clone5_rectangle0_w1.0/\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "358f5846-34a6-4234-92dd-4ac38fe8d2ac", + "metadata": {}, + "source": [ + "The above run of Startle will produce a plain-text file `calicost/phylogeny_clone5_rectangle0_w1.0/loh_tree.newick` that encodes phylogeny tree with leaf nodes as CalicoST-inferred clones. We load the tree file as follows." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "c5114cc8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['((clone1:0,clone2:3):4,(clone3:1,(clone4:3,clone5:3):9):2);']\n" + ] + } + ], + "source": [ + "with open(f\"{example_directory}/calicost/phylogeny_clone5_rectangle0_w1.0/loh_tree.newick\", 'r') as fp:\n", + " print( fp.readlines() )" + ] + }, + { + "cell_type": "markdown", + "id": "6e172836-f627-4fb7-abc1-3c53534aadb3", + "metadata": {}, + "source": [ + "Now we project the phylogenetic tree in space to get a phylogeography. Before getting the phylogeography, we note that we currently don't have the relative positioning among the five slices yet. We manually place the five slices according to Fig 1b in the original publication by [Erickon et al.](https://www.nature.com/articles/s41586-022-05023-2), and transform the x/y coordinate in the `tissue_positions.csv` file according to the new positioning." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "72a0eb26-d971-4d91-9687-ac4e5b65e050", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
in_tissuearray_rowarray_colpxl_row_in_fullrespxl_col_in_fullresslice_idclone_labeltumor_proportion
barcode
TCCTTCAGTGGTCGAA-1_H121156933666308H12clone30.050000
GCGTCGAAATGTCGGT-1_H121176536186018H12clone30.132391
AACTGATATTAGGCCT-1_H121166634926090H12clone30.050000
CGAGCTGGGCTTTAGG-1_H121176736186163H12clone30.050000
GGGTGTTTCAGCTATG-1_H121166834926236H12clone30.050000
...........................
ATGGCCCGAAAGGTTA-1_H251761201348012001H25clone21.000000
CGTAATATGGCCCTTG-1_H251771211363212089H25clone21.000000
AGAGTCTTAATGAAAG-1_H251761221348012176H25clone21.000000
ATTGAATTCCCTGTAG-1_H251761241347912351H25clone21.000000
TTGAAGTGCATCTACA-1_H251771271363012615H25clone2NaN
\n", + "

13344 rows × 8 columns

\n", + "
" + ], + "text/plain": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 1 15 69 3366 \n", + "GCGTCGAAATGTCGGT-1_H12 1 17 65 3618 \n", + "AACTGATATTAGGCCT-1_H12 1 16 66 3492 \n", + "CGAGCTGGGCTTTAGG-1_H12 1 17 67 3618 \n", + "GGGTGTTTCAGCTATG-1_H12 1 16 68 3492 \n", + "... ... ... ... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 1 76 120 13480 \n", + "CGTAATATGGCCCTTG-1_H25 1 77 121 13632 \n", + "AGAGTCTTAATGAAAG-1_H25 1 76 122 13480 \n", + "ATTGAATTCCCTGTAG-1_H25 1 76 124 13479 \n", + "TTGAAGTGCATCTACA-1_H25 1 77 127 13630 \n", + "\n", + " pxl_col_in_fullres slice_id clone_label \\\n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 6308 H12 clone3 \n", + "GCGTCGAAATGTCGGT-1_H12 6018 H12 clone3 \n", + "AACTGATATTAGGCCT-1_H12 6090 H12 clone3 \n", + "CGAGCTGGGCTTTAGG-1_H12 6163 H12 clone3 \n", + "GGGTGTTTCAGCTATG-1_H12 6236 H12 clone3 \n", + "... ... ... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 12001 H25 clone2 \n", + "CGTAATATGGCCCTTG-1_H25 12089 H25 clone2 \n", + "AGAGTCTTAATGAAAG-1_H25 12176 H25 clone2 \n", + "ATTGAATTCCCTGTAG-1_H25 12351 H25 clone2 \n", + "TTGAAGTGCATCTACA-1_H25 12615 H25 clone2 \n", + "\n", + " tumor_proportion \n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 0.050000 \n", + "GCGTCGAAATGTCGGT-1_H12 0.132391 \n", + "AACTGATATTAGGCCT-1_H12 0.050000 \n", + "CGAGCTGGGCTTTAGG-1_H12 0.050000 \n", + "GGGTGTTTCAGCTATG-1_H12 0.050000 \n", + "... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 1.000000 \n", + "CGTAATATGGCCCTTG-1_H25 1.000000 \n", + "AGAGTCTTAATGAAAG-1_H25 1.000000 \n", + "ATTGAATTCCCTGTAG-1_H25 1.000000 \n", + "TTGAAGTGCATCTACA-1_H25 NaN \n", + "\n", + "[13344 rows x 8 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# load coordinates and inferred cancer clones\n", + "coords = []\n", + "for i,s in enumerate(slice_ids):\n", + " # load spatial locations\n", + " # note that scanpy is incompatible with the latest tissue_positions.csv file, we directly load the positions as pandas data frame\n", + " df = pd.read_csv(f'{example_directory}/data/{directory_name[i]}/spatial/tissue_positions.csv', header=0, index_col=0, sep=',')\n", + " df.index = df.index + \"_\" + s\n", + " df['slice_id'] = s\n", + " coords.append( df )\n", + "\n", + "coords = pd.concat(coords)\n", + "\n", + "# combine with the cancer clone table\n", + "df = pd.read_csv(f\"{example_directory}/calicost/clone5_rectangle0_w1.0/clone_labels.tsv\", header=0, index_col=0, sep='\\t')\n", + "df.clone_label = 'clone' + df.clone_label.astype(str)\n", + "coords = coords.join(df)\n", + "\n", + "# remove spots that are not assigned to clones by CalicoST (filtered out due to low UMI count or SNP-covering UMI count)\n", + "coords = coords[coords.clone_label.notnull()]\n", + "coords" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b160c077-6ba4-4e76-938f-f53bcf89b88a", + "metadata": {}, + "outputs": [], + "source": [ + "def flip_axis(coords, axis):\n", + " max_x = np.max(coords[:,axis])\n", + " min_x = np.min(coords[:,axis])\n", + " tmp_coords = copy.copy(coords)\n", + " tmp_coords[:,axis] = min_x + max_x - coords[:,axis]\n", + " return tmp_coords\n", + "\n", + "\n", + "def rotate_by_angle(coords, angle):\n", + " theta = angle / 180 * np.pi\n", + " R = np.array([ [np.cos(theta), -np.sin(theta)], [np.sin(theta), np.cos(theta)]] )\n", + " mean_coords = np.mean(coords, axis=0)\n", + " return (coords - mean_coords.reshape(1,-1)) @ R + mean_coords.reshape(1,-1)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "3e74eac1-7b54-458b-a928-c88a0334990b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
in_tissuearray_rowarray_colpxl_row_in_fullrespxl_col_in_fullresslice_idclone_labeltumor_proportionfinal_xfinal_y
barcode
TCCTTCAGTGGTCGAA-1_H121156933666308H12clone30.050000238.41765274.069483
GCGTCGAAATGTCGGT-1_H121176536186018H12clone30.132391241.24607969.170504
AACTGATATTAGGCCT-1_H121166634926090H12clone30.050000239.57304770.654068
CGAGCTGGGCTTTAGG-1_H121176736186163H12clone30.050000241.76371771.102355
GGGTGTTTCAGCTATG-1_H121166834926236H12clone30.050000240.09068572.585919
.................................
ATGGCCCGAAAGGTTA-1_H251761201348012001H25clone21.000000700.743520183.090182
CGTAATATGGCCCTTG-1_H251771211363212089H25clone21.000000701.914026181.184948
AGAGTCTTAATGAAAG-1_H251761221348012176H25clone21.000000702.735909183.264493
ATTGAATTCCCTGTAG-1_H251761241347912351H25clone21.000000704.728299183.438805
TTGAAGTGCATCTACA-1_H251771271363012615H25clone2NaN707.891194181.707882
\n", + "

13344 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " in_tissue array_row array_col pxl_row_in_fullres \\\n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 1 15 69 3366 \n", + "GCGTCGAAATGTCGGT-1_H12 1 17 65 3618 \n", + "AACTGATATTAGGCCT-1_H12 1 16 66 3492 \n", + "CGAGCTGGGCTTTAGG-1_H12 1 17 67 3618 \n", + "GGGTGTTTCAGCTATG-1_H12 1 16 68 3492 \n", + "... ... ... ... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 1 76 120 13480 \n", + "CGTAATATGGCCCTTG-1_H25 1 77 121 13632 \n", + "AGAGTCTTAATGAAAG-1_H25 1 76 122 13480 \n", + "ATTGAATTCCCTGTAG-1_H25 1 76 124 13479 \n", + "TTGAAGTGCATCTACA-1_H25 1 77 127 13630 \n", + "\n", + " pxl_col_in_fullres slice_id clone_label \\\n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 6308 H12 clone3 \n", + "GCGTCGAAATGTCGGT-1_H12 6018 H12 clone3 \n", + "AACTGATATTAGGCCT-1_H12 6090 H12 clone3 \n", + "CGAGCTGGGCTTTAGG-1_H12 6163 H12 clone3 \n", + "GGGTGTTTCAGCTATG-1_H12 6236 H12 clone3 \n", + "... ... ... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 12001 H25 clone2 \n", + "CGTAATATGGCCCTTG-1_H25 12089 H25 clone2 \n", + "AGAGTCTTAATGAAAG-1_H25 12176 H25 clone2 \n", + "ATTGAATTCCCTGTAG-1_H25 12351 H25 clone2 \n", + "TTGAAGTGCATCTACA-1_H25 12615 H25 clone2 \n", + "\n", + " tumor_proportion final_x final_y \n", + "barcode \n", + "TCCTTCAGTGGTCGAA-1_H12 0.050000 238.417652 74.069483 \n", + "GCGTCGAAATGTCGGT-1_H12 0.132391 241.246079 69.170504 \n", + "AACTGATATTAGGCCT-1_H12 0.050000 239.573047 70.654068 \n", + "CGAGCTGGGCTTTAGG-1_H12 0.050000 241.763717 71.102355 \n", + "GGGTGTTTCAGCTATG-1_H12 0.050000 240.090685 72.585919 \n", + "... ... ... ... \n", + "ATGGCCCGAAAGGTTA-1_H25 1.000000 700.743520 183.090182 \n", + "CGTAATATGGCCCTTG-1_H25 1.000000 701.914026 181.184948 \n", + "AGAGTCTTAATGAAAG-1_H25 1.000000 702.735909 183.264493 \n", + "ATTGAATTCCCTGTAG-1_H25 1.000000 704.728299 183.438805 \n", + "TTGAAGTGCATCTACA-1_H25 NaN 707.891194 181.707882 \n", + "\n", + "[13344 rows x 10 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "adjusted_coords = copy.copy(coords[['array_row', 'array_col']].values)\n", + "# scale y coordinate so that the hexagon is not squeezed on one direction\n", + "adjusted_coords[:,0] = adjusted_coords[:,0] * np.sqrt(3)\n", + "# shift x and y coordinate to start from 0 for each slice\n", + "for s,sname in enumerate(slice_ids):\n", + " index = np.where(coords.slice_id.values == sname)[0]\n", + " adjusted_coords[index,0] -= np.min(adjusted_coords[index,0])\n", + " adjusted_coords[index,1] -= np.min(adjusted_coords[index,1])\n", + " \n", + "\n", + "# position in number of cubes\n", + "cube_length = min( np.max(adjusted_coords[:,0]), np.max(adjusted_coords[:,1]) )\n", + "sample_cube_pos = np.array([ [2,0], #H12\n", + " [4, 0.2], #H14\n", + " [5,0.5], #H15\n", + " [0,1], #H21\n", + " [5,1.5] ]) #H25\n", + "\n", + "swap_x_y = [False, True, True, False, True]\n", + "rotation_angle = [15,-5,-5,0,-5] # H12, H14, H15, H21, H25\n", + "\n", + "full_adj_coords = np.zeros(adjusted_coords.shape)\n", + "for s,sname in enumerate(slice_ids):\n", + " index = np.where(coords.slice_id.values == sname)[0]\n", + " if swap_x_y[s]:\n", + " tmp_coords = np.vstack([adjusted_coords[index,1],adjusted_coords[index,0]]).T\n", + " if sname != \"H25\":\n", + " tmp_coords = flip_axis(tmp_coords, axis=0 )\n", + " tmp_coords = flip_axis(tmp_coords, axis=1)\n", + " full_adj_coords[index,:] = tmp_coords + cube_length * sample_cube_pos[s]\n", + " else:\n", + " full_adj_coords[index,:] = adjusted_coords[index,:] + cube_length * sample_cube_pos[s]\n", + " \n", + " full_adj_coords[index,:] = rotate_by_angle(full_adj_coords[index,:], rotation_angle[s])\n", + "\n", + "coords['final_x'] = full_adj_coords[:,0]\n", + "coords['final_y'] = full_adj_coords[:,1]\n", + "coords" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "c17a5b64-f13a-42d1-8cab-3b292a34f213", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import calicost.utils_plotting\n", + "\n", + "fig = calicost.utils_plotting.plot_individual_spots_in_space(full_adj_coords, coords.clone_label, coords.tumor_proportion, base_width=10, base_height=5)\n", + "plt.gca().invert_yaxis()\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "932b0667-cba8-414d-a40d-37b986fa47cb", + "metadata": {}, + "source": [ + "Now we project the phylogeny to the space of coords[['final_x', 'final_y']] and infer ancestor locations using a Gaussian diffusion model." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "5038e208-62b5-4a55-9fa5-7e6e21d8345b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "root node is ancestor1_2_3_4_5\n", + "a list of leaf nodes: ['clone1', 'clone2', 'clone3', 'clone4', 'clone5']\n", + "a list of internal nodes: ['ancestor1_2_3_4_5', 'ancestor1_2', 'ancestor3_4_5', 'ancestor4_5']\n", + "\n", + " /-clone1\n", + " /-|\n", + " | \\-clone2\n", + "--|\n", + " | /-clone3\n", + " \\-|\n", + " | /-clone4\n", + " \\-|\n", + " \\-clone5\n" + ] + } + ], + "source": [ + "import calicost.phylogeography\n", + "\n", + "newick_file = f\"{example_directory}/calicost/phylogeny_clone5_rectangle0_w1.0/loh_tree.newick\"\n", + "t = calicost.phylogeography.project_phylogeneny_space(newick_file, coords[['final_x', 'final_y']].values, coords.clone_label.values, \n", + " single_tumor_prop=coords.tumor_proportion.values, sample_list=slice_ids, sample_ids=coords.slice_id.values)\n", + "\n", + "print( t )" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "c4cd8da6-976d-40ef-b94d-4844337c81be", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1404: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1]))\n", + "/n/fs/ragr-data/users/congma/temp/CalicoST/src/calicost/utils_plotting.py:1407: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes)\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAB7sAAAPUCAYAAADc4V37AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAB7CAAAewgFu0HU+AAEAAElEQVR4nOzdebAlZZkn/u/75nK2u9etvUoKoVhFoXBabLpZXEawoRvHGBdcgNB2otWeMSa64zdjMA7dON3TS4QTIdDtMoHSMihrN6CIiKKAuLBKCQXFcoFa7q26+1lzed/390fmyZN5zrlr3aIWvp9o2nvOyXzPm3mv/OE3n+cRxhgDIiIiIiIiIiIiIiIiIiKiI4g81BsgIiIiIiIiIiIiIiIiIiJaKobdRERERERERERERERERER0xGHYTURERERERERERERERERERxyG3UREREREREREREREREREdMRh2E1EREREREREREREREREREccht1ERERERERERERERERERHTEYdhNRERERERERERERERERERHHIbdRERERERERERERERERER0xGHYTURERERERERERERERERERxyG3UREREREREREREREREREdMRh2E1EREREREREREREREREREccht1ERERERERERERERERERHTEYdhNRERERERERERERERERERHHIbdRERERERERERERERERER0xGHYTURERERERERERERERERERxyG3UREREREREREREREREREdMRh2E1EREREREREREREREREREccht1ERERERERERERERERERHTEYdhNRERERERERERERERERERHHIbdRERERERERERERERERER0xGHYTURERERERERERERERERERxyG3UREREREREREREREREREdMRh2E1EREREREREREREREREREccht1ERERERERERERERERERHTEYdhNRERERERERERERERERERHHIbdRERERERERERERERERER0xGHYTURERERERERERERERERERxyG3UREREREREREREREREREdMRh2E1EREREREREREREREREREccht1ERERERERERERERERERHTEYdhNRERERERERERERERERERHHIbdRERERERERERERERERER0xLEP9QaIiIiIiIiIiIiIiIiI6MhnjEG1WsXs7CwajQaUUod6S3SISSnhui5KpRJ6enrguu6Kri+MMWZFVyQiIiIiIiIiIiIiIiKiNxStNV599VXU6/VDvRU6jK1evRqrVq2CEGJF1mPYTURERERERERERERERETLZozBK6+8kgm6hRCwLOsQ7ooOB0optMfR/f392LBhw4qszzbmRERERERERERERERERLRs1Wo1Cboty8K6devQ09MDKeUh3hkdasYYeJ6H2dlZTExMAABmZmawatUq5HK5A16ff2FEREREREREREREREREtGyzs7PJz+vWrUNfXx+DbgIQVfjn83msWbMGa9asSd6fmppakfX5V0ZEREREREREREREREREy9ZoNABEwWZPT88h3g0drgYGBpKfa7XaiqzJsJuIiIiIiIiIiIiIiIiIlk0pBSBqYc6KbpqLZVnJHPfm38yB4l8bEREREREREREREREREREddEKIFV2PYTcRERERERERERERERERER1xGHYTEREREREREREREREREdERh2E3EREREREREREREREREREdcRh2ExERERERERERERERERHREcc+1BsgIiIiIiIiIiIiIiIioqOXMhq/ndiN303twSuVSYzWZhFoBUdaWFfswzE9Qzh1cAPeumojLHF41OqOjIzg2GOPBQBcf/31uPzyyw/thqgrht1EREREREREREREREREdMBc18281kbjx7ufw/27d2Dar3cc72uFVytTeLUyhQdHX8SAW8B7Np6Ed288EfIwCb3fKMIwxNNPP41f//rX+M1vfoNf//rXeOaZZ6CUAgC8/PLL2LJly6HdZBcMu4mIiIiIiIiIiIiIiIjogDiOg40bNyavR2szuP65X2KkMrHoNab9Om59+Qk8Ov4qrjjhLKwr9h+MrVIX/+t//S9cddVVh3obS8ZHIoiIiIiIiIiIiIiIiIjogGzcuBG2HdXZvjQ7jv/95I+WFHSnjZQn8HdP/QgvzY6v5BZpHsaY5Od8Po+zzjoLxx133CHc0eIw7CYiIiIiIiIiIiIiIiKiZRscHEShUAAQVXR/9Xc/RV0FB7RmLQzw1d/9FKO1mZXYIi3gne98J/75n/8Zjz/+OMrlMh555BH8wR/8waHe1oLYxpyIiIiIiIiIiIiIiIiIlm1oaAhANKP7+ud+iVp4YEF3Uy0McP3zv8T/97b3cob3Qfa+973vUG9hWfhXQURERERERERERERERETLJmUUOf5493PLbl0+l5HyBO7f/dyKrPXwww/j05/+NE488UT09fXBdV1s2rQJF110Ea699lpMT08veU3f93Hdddfh/PPPx+rVq+G6LtatW4f3v//9+M53vgOt9ZznXn755RBCYMuWLQCA6elpfOlLX8Kpp56KUqmEgYEBnHPOObjxxhsXtZeZmRn87d/+Lc4+++xkL+vXr8fFF1+MW2+9NdOq/GjBym4iIiIiIiIiIiIiIiIiOiDKaNy/e8dBWfvHu3fgXRtPhLXM6u56vY5PfepTuOmmmzo+2717N3bv3o3vf//72L9/P6666qpFrzsyMoILL7wQO3Zkr3tsbAz33HMP7rnnHnzta1/Dv/3bvyXV73N57rnncMEFF2BkZCTz/oMPPogHH3wQjzzyCK655po5z7///vvx4Q9/GBMT2YcNRkdHcffdd+Puu+/G+9//fnzve99DT0/Poq/xcMfKbiIiIiIiIiIiIiIiIiI6IL+d2I1pv35Q1p726/jtxO5lnau1xp/8yZ8kQffWrVvxla98BQ8++CAee+wx3H333fjiF7+I448/fknrVioVvPvd706C7ksuuQR33nknHn30Udxyyy0499xzAQAPPfQQLr74Yiil5lyrVqvh4osvxsTEBK688ko88MADePTRR/GNb3wDmzZtAgBce+21uPfee7ue//DDD+PCCy/ExMQE1q5diy9/+cu466678Nhjj+Guu+7Cxz/+cQDAD37wA1x22WVLus7DHSu7iYiIiIiIiIiIiIiIiOiA/G5qz0Fefy/OGN685POuueYa3HfffQCAD3zgA7jpppuQy+Uyx/zRH/0Rrr76auzdu3fR6/7VX/0VXnrpJQDAlVdeiauvvjr57Mwzz8QHP/hBfOITn8CNN96IX/ziF/j617+OP/uzP+u61v79++H7Ph555BGceuqpmXXOO+88nHbaaWg0Grjuuus6ZmsHQYCPf/zjCIIAF1xwAW677TYUi8Xk823btuGiiy7COeecg8985jO4/fbbcd999+G9733voq/1cMbKbiIiIiIiIiIiIiIiIiI6IK9UJg/q+q8uY32tNf7hH/4BALBp0ybccMMNHUF3k5QSGzduXNS6nufhm9/8JgDg1FNP7dr6XAiB6667DqtWrQKAeVuQA8DVV1+dCbqbjj/+eFxyySUAoirxdt/97ncxMjKCfD6PG264IRN0p/3pn/4pfu/3fg8A8K1vfWvevRxJGHYTERERERERERERERER0QEZrc0e1PX31maWfM6TTz6JXbt2AYjC3pWaVf3YY49henoaAHD55ZfDsqyux/X19eFDH/oQAOCZZ56Zs3JcCIFLL710zu8788wzAQCTk5PJ9zbdeeedAIBzzz0Xq1evnnff55xzDgDgkUcemfe4IwnDbiIiIiIiIiIiIiIiIiI6IIGeeyb1yqyvl3zOE088kfz8h3/4hyu2l+3btyc/v+Md75j32PTn6fPShoeHkwrwboaGhpKfy+Vy5rNHH30UAHDvvfdCCDHvP//4j/8IABgdHZ13z0cSzuwmIiIiIiIiIiIiIiKirowxCHwfUkrYjoNatYqZqUkopZAvFDAwNATbdg71Nukw4EgL/kEMvB259Bre8fHx5Of169ev2F4mJ1st1desWTPvsevWret6XtpcrcebZOralcre43379s17bjf1en3J5xyuGHYTERERERERERERERG9ARmjoXwfwrJh2TZq1Spmp6eSIFuFIaYnJxCGIQDAsm2o+GcAmJ2ewv6xUWw6Zgt6+/oP1WXQYWJdsQ+vVqYO2vrri4fn35gQ4pB+fzP8vvDCC/H3f//3h3QvhwLDbiIiIiIiIiIiIiIioqOMMQZKhZDSylSFRp9pTO16BTOju6ACHwYAeocQpLpEz3TJLNNBd7KW1tg18jK2nnwqbIcV3m9kx/QMHdSw+009Qwsf1GZ4eDj5ee/evTjppJNWZC/ptuJjY2M44YQT5jw23TI8fd5KWbVqFfbs2QPf9/GWt7xlxdc/3HFmNxERERERERERERER0REkCrIVjDEAgHqtirE9uzG6exdmpiaxb3Qvdj6zHc//bjue2/5b7HplBL7nJeePPf87TL72ElTgAwC0k88E3cvZz9TkxAFdEx35Th3ccJDXX3ob8m3btiU///znP1+xvaRD5V/96lfzHvvrX/+663kr5YwzzgAQze72fX/F1z/cMewmIiIiIiIiIiIiIiI6AmitsT8Osp/b/ls8+/RT2PnMdry883lM7N+HyfH92P3qKxgfG01ajxtjMDs9hZdfeB6+56E+O4XKRGvGrwGg7PwB761Rrx3wGnRke+uqjRhwCwdl7QG3gLeu2rjk8972trdh8+bNAIBvfvObqFQqK7KfM888EwMDAwCAb3/729C6+9Mi5XIZN998MwDglFNOWdG54U1//Md/DACYmZnB9ddfv+LrH+4YdhMRERERERERERERER3mjDF4beQl7E8F2TAGQRAs6nwVhtg/Nory/rHsB0IC8sDjIktaB7wGHdksIfHujSvTJrzdezaeBEss/e9USom//Mu/BADs2rULn/zkJ+esftZaY8+ePYtaN5fL4dOf/jQAYPv27bj66qs7jjHG4POf/zzGx8cBAJ///OeXvP/FuOyyy5JA/y/+4i8WrGB/6KGH8LOf/eyg7OVQ4MxuIiIiIiIiIiIiIiKiw1x5ZhrVcvmA1pidnsJgri0aMib6R4jOE+I26V0/a9M3uPKziOnIobWGlBLv2XgiHtv/KkYqK9fWfkvvKrx744nLPv9zn/sc7rrrLtx333244447cNppp+Gzn/0s3v72t6NYLGJ0dBS//OUvcdNNN+HSSy/FVVddtah1v/SlL+H222/HSy+9hKuuugpPP/00rrjiCqxfvx4vv/wyrrnmGjzwwAMAgHe+8534zGc+s+xrmE8ul8PNN9+M8847D5VKBe9617vwkY98BJdccgmOPfZYaK2xd+9ePPbYY7jjjjvw9NNP46tf/SrOPffczDqVSgW33npr5r0XXngh+fnWW2/NzEA//fTTcfrppx+Ua1oKht1ERERERERERERERESHuZmpqQNewxgDt9QDTLSquwUMROhBGg2hNbRlA8bA9mqQKqqADQp9UG5xztC7t68fpZ6eA94fHbkmJycxPDwMKSSuOPEs/N1TP0ItXFzXgfkUbQdXnHAW5DKqupuklPjXf/1XXHbZZbj11lvx/PPP4wtf+MIB7623txf3338/LrzwQuzYsQO33XYbbrvtto7jzj77bNx5552wrIPX/eCss87CAw88gA996EN47bXXcOONN+LGG2+c8/i+vr6O98bHx3HFFVfMeU6zQr7pf/7P/8mwm4iIiIiIiIiIiIiIiBamlDrgNWzbhislnHoZQkVBpHILECpEEmMbDdGs6AagbHfeoHtw1TDWbdwEsYjqbzp6TU1NoVQqoVAoYF2xH39+6vn46u9+ekCBd9F28Oenno91xf4D3l+xWMQtt9yCn/70p7j++uvx0EMPYXR0FEoprF27FqeffjouuugifPSjH13Sulu2bMFTTz2Fb3zjG7jllluwfft2zM7OYmhoCGeccQY+9rGP4dJLL4VcgVEBCznrrLOwc+dOfOtb38Jdd92FJ554AuPj45BSYvXq1Tj55JNx7rnn4oMf/CBOPHH5lfKHG2FM6t9YREREREREREREREREdNjZu+s1TE2MZ94TKoRbnYTUIUK3hKDQN2/Lcac2jXy5tYaWNlSu2DrAmCjsTp3jlQahnfycaw6uGsb6TZuXfD10dNm5cyeEENiyZQtsO6q1Ha3N4PrnfrmsluZbelfhihPOWpGgmw4vO3fuRBiGsG0bW7duPeD1WNlNRERERERERERERER0mNG+h8bYa9AqhNu/CkUo1Kf3wgo9GCEhQx+56kSmCjt0CphddwK0W+hYT2iFXDkblmvbbTvKoD0q11b7MVn1WnUpl0VHsSAIsHv3bhxzzDEAgHXFfvx/p78X9+9+Dj/evQPTfn3BNQbcAt6z8SS8e+OJB9S6nN44GHYTERERERERERERERG9jlQYolyehdEahVIJvudhcnw/vEYDlmWhpz4NPTYC6Kh1uZYOtO0moY7lVeA2ZjvWtYM6+vfugNj2HszOzCJMtZC2G+WOINvIxcwQnr9BsGAgSSm+72deSyHx3k0n410bT8RvJ3bjd1N78WplEntrMwi0hiMl1hf78aaeIZw6uB5vXbURFv+maAkYdhMREREREREREREREa0QFYaolGdhjEGx1INGo46p8XF4XgO2ZcNybNQqFcw1Zdaa2Qc9vSd5bSCgLSdzjO3PXU1thR5KQRWTbbOShV7MzG+B9nDbChpQudKcZ2itUKtWUSzNfQyRJSTOGN6MM4bZ8p5WFsNuIiIiIiIiIiIiIiKiZQhe3QH/+SegypMQhRIqm9+KaSXnDLLDIAAa8yxoDHLl/Zm3tGVn53BrDblAcB2M7wHcobZ1nI7jhApgUq3Mm03Mm99mhIBUPpQpAHNU23qNBkZeeB4b37QF/YOD8+6LiGilMewmIiIiIiIiIiIiIiJqMzszjemJCfi+B8dxMTC0Cn0DAxBx8Fz/1Q/hP/9Y6/jCKsyGnZXRSyGVD0sFbe+KeV92XUdK9PT2oVJutToP8z3Q5XFIowEAys7B61kFp1GBgIERIprhbTSsIErkte1CAHAaZYRuEUa2Be8pe3e9ht6+PkhrMa3RiYhWBsNuIiIiIiIiIiIiIiKilD2vvYrpyYnkte95qFbKKM8MYOMxWxDufTkTdBshUV597Ap8c2eQLIzJxudCQllOJhRXtguvZxhh3G7cz/WjUZmJcvdmOC0kGgPrUJjeCyMs1AY2AFLClxacRgVGyuhYYUG5RQgdJucKo2H5NYSF/jl3rrXC7Mw0BoZWHehNICJaNIbdREREREREREREREREsdmZ6UzQ3f5Zz9Qk3BeezLzvF/oz7cCXS9sulJ2DFXqt96SMMuv4dejk4Q9vQe/YTggAQa6E6qotgIzajBsAlYYHCAEhRFyNHX2m3CKqq46BUEHreMtBUOiD7ddaGxECRsps9D5HG/O0MGivSiciOrgW/jcTERERERERERERERHRG8T0RPegu2lqYhy6Mr0yX6Y10Dbfu9G3JvnZz/didt1JaPSvhQGgLBeN/rXwe1ahvO4EhHYOtaHNSXANRFXmrYpsE1VopxjLhnby2X3Erc3nIxZxjJPLLXgMEdFKYmU3ERERERERERERERFRzPe9BT73IUr9wMTe5D23PgMZ+tHM66YwAGxnznWECmEFdWjLyYTPQaEf1QGN/Oy+pGI7KPRD2XlIFSQV1n5pCEG+F1boty3c3gp94SHfpmvVtoARAkZYADSgVfSP7D6T27Jt9PXN3eaciOhgYNhNREREREREREREREQUcxwXvjd34G3bNsQxpwCv7kje83pWZSq0La+C/Ow++MVBBKXBzkWMgRXUIQBYKoDQGsrNJ0F2UBqEXxqCsVoxjnZyna3Fs0Xhc1jEQdKCst245TmiUFvI+LVI9twZpEeElNj4pi0Qkg2Fiej1xX/rEBERERERERERERHRG5YxBl6tikalDK0VSn298x7v1+t4ZaqC6uAmAECjZxiTx5wBYztRIKxC5Gf3QwDI1aaQn94bhccpUgWZ0FoYhY4K7DmC5QWPMSb6RyvAaJjm67nOj9fQTh7GsmGkDWPnYCwnu/48+znmzcejp3f++0ZEdDCwspuIiIiIiIiIiIiIiN4QPK+BqYkJ+F4Dtu3AtSTK42MIGnUAgLFdKGvu1uMwBsYoCAAzG0+B1zOEMN+XVGQLGNiNMkSqmtoKGp2tvxcx/7p7RbbIvG+kBSXtaH0RtUaXgQcBEx8poPM9nUH1Qq87tjJ3VTcA7Hn1FWzacizyhcL86xARrTCG3UREREREREREREREdNSbmhjH3l2vJa+FCiFDL6mnNhBRcDwvk6m/bvSvS4LuJqmC7CndQuK2cwQAoVWmbXmzOlvEVdnN/2+QqgEXAsbJJcfbYS0TtIducc4Z24uiFQZ2/w7Tm98672G+72HkheexZesJyOcZeBPR64dtzImIiIiIiIiIiIiI6KjWqNczQTeMgQz9THCtLXtxFc4LMG3hsjAaMsjOANfSgtEKUCGgQxgThdjp9QUAaXRcpW0g46B9rh3K0IdIVYwbIbLh+TL0792BwswooBeuRNdaY3x09IC+j4hoqVjZTURERERERERERERER7WpifHsG3GInCGWWR/YDKjjVt9BvgcwGtopADCQQSP7TVrBaZSTYNoYgTBfOrAKbLRVlBsTReOLmfs9B6ECFKd2QWqFwuwo6gMbFjxndmYaWmtIyVpLInp9MOwmIiIiIiIiIiIiIqKjWiOeyT2/hau2ISSM0a0QWStYoQdhNAQALSSUW4Tfu7p1Tr43s4TtVTIV2MrJzx90Gx0F6c1jjIb0G9C54tz7N6ozzF8i26tCagUA6Nu7A35xEMpduEW5MRpsLExErxf+24aIiIiIiIiIiIiIiI5qdns7byHjtuEa0CoKk1UIIwS0sKCbn7cTIgqdhQQMYAde3Go8ipqVU5i3mlqoIAmQgWgCuG7O3O7GaLjVqUw4HoXQYeehzXnjxkRt2rWCaJ8fvgTpFuh20MDqFx6GW5mY9xzXzUEeYIU6EdFSsLKbiIiIiIiIiIiIiIiOOlopQCsI20FfXx/qY6/BCj0YIaFtF25tGpZfhwAQuEX4q96Uqp42URA+D0v5meppIy0g3b67eX6qPbpoC7rDQu+87dMtvw6pQ0gVQFlOdD3NAFurTEW4snOQoRfP+I7YjQqCYv/SWrTH7djDXA/qPcNQ+R5oy4FTL6MwtRd+aWjOQH9oeDXEAbROJyJaKobdRERERERERERERER0RDHGwBgDKSWMClHfM4KgPAXp5GAPDKOyZwT1/XsBY2DlCjBhgIIKmyfHM7vjlxCoDW3KBMfCKMwb2RqTrZo2GkIh89qpzURBc1oqCFZOvlWNPQcraET/6degnAKkCltBtldFmO9trSklwlwJdqOSHCN1CKc2jaDQByzwXTL0IINGHMgLhLkSJo/9d4ue+z24ahiDw8OLOpaIaKUw7CYiIiIiIiIiIiIioiNCo17D/rFRlGdmAAAFEyI39iIQ+gAAIwSUnc+Gyl49G1yngm4ACAp9MJaT+jxqAz4nY2AF9exrvx7N3o5ZXj1uIx7C2G7yvrZcGNQgYKBT78+l2b5cagWnPoMw9R1Sh7AbswhzPUlQbywHQaEfTm0KxnZhICB1AMtvQOVKcwbXll9LgnUAULaT2fdC8oUC1m/avOjj6Y3HaAW8+CTMyHaYsVeAyb1AGAC2Awyth1h7DMSWtwDHnQ5xmLTCHxkZwbHHHgsAuP7663H55Zcf2g1RVwy7iYiIiIiIiIiIiIjosFerVvHKSy/A6CgAFiqEO/pcpt24ttyOQDf9SgsJCZU63ka9b03Hd81XyyxDHyIVhgutIIyGFTQQxC3ArTAKjm2/jiAdGgsB5RZg+7VFtRbX0oaloiDfCj2I0Ie2HRjLjb87hO3VovnaRgMQUE4OQarVuJpr8eRLFGQq6AYAnQrVF6NRr8P3fbju4gNyOjq1/w0YrWEevw/m8R8BlenOE0If2PcKzL5XYJ7+OdAzALHt30Nsey+EXEL7fTpgMzMzuPvuu/HjH/8Yjz/+OEZGRlCr1TAwMIC3vOUtuOiii/CpT30KAwMDh3qrGQy7iYiIiIiIiIiIiIjosDe2Z3cSdAOAW5tKKp+BKMjW0kqCam3Z0JYLx68lr6sDG9G3/yUAUfvy6uCmaNZ2mogmcXcNvI2B0GHzwGiVeA63MBp2o4ww35uE4VIFsBqVTFW1dvIIhASMAsT8MU2YKyFEKWp3bjSE0VEVeryWDDxIHSb3QVtWph37Ylihl7lWA7Fge/VuVBgCDLvf0BzHwcaNG5PXZnIv9A//LzD68uIXqUzD/PxmmOd/A3nBpyCG1h+EnVK7e+65Bx/4wAfgeV7HZ+Pj43jggQfwwAMP4B//8R/x//7f/8P5559/CHbZHcNuIiIiIiIiIiIiIiI67Hiz0wgaVVhuHtrOoV6rJp8JFc2ibtLCgl/shx1XKBshUB/YADd1TL13DbSTh5Y2pA4R5HtgbDcKkJENiI2QmSA9LQmGhYhmh6c+c7wKhFaZ8+2gAanCaH53HFIby4FTn4Vbm4JUAZRlo9G/HtrOZSrTs63EZea7oBVkErwDBoBOt2NfrI6W7XEb90XO6m5ynGV8Nx1VNm7cCNuOokez50XoO74CePUFzprD6MvQN/0N5H/4AsT641Zwl9TNxMQEPM+DlBLvfe97ccEFF+Btb3sbBgYGsGvXLtx444343ve+h9HRUVx00UV4+OGHcfrppx/qbQNg2E1ERERERERERERERK+zetz22nEcOI6DqfH9qMzOwsCg4DrQ43sQ1MoAolbeXu9wq+230XDqs0jXXoeFXkDaSUV2mOuFsRyEuR649VloIRHmewEh4JWGUCjvg8oVgfh4ozWQbpksomC5W+BtICCasbOQ0JYDqfxof8ZABnVot4DA7YURMp4RngqOjUFhZg/c+mzyll8aXHLrcKnC7BtCLKo1esf1tLWKFgCECrJBuwqjivF5AvCXdj6HjW86BqWe3iXvgY58g4ODKBQKAOKK7jv+z/KD7iavBn37/4H86BdZ4X2QOY6D//Sf/hO++MUv4k1velPmszPOOAMXX3wxzj77bPzn//yfUavV8F//63/FT37yk0O02yyG3URERERERERERERE9Lqo1+vYvXs3Go14RrQxkFoBzfBYK4ix/ZmQOaqIbgWyVtCAMBrKycMO6jBCJrO6jeVAqAChG4Vuyi0gcItRBXQc1Hq9w9FM7VRBszAK0CYKp4WIW5kLDA4NY3piPHMNRlrJfGwYDWkMjHSS9udhrgTt5FJn2DCpkNhulDNBtxESXnFwGXezvSJ78Wdl2pYLK/OetpxMG3MR+nAaZRjLRpDvmzPwDoMAr778Et58wonI5ZYW3NORb2hoCED04Ij+4f8FvNrKLOzVoH/4fyE/8kXO8D6IPvzhD+PDH/7wvMf8+Z//OW644QY8+uij+NnPfobx8XEMDw+/TjucG/8qiIiIiIiIiIiIiIjooPN9HyMjI62gG4jnX7dCW9uvZedwSztq7Z0iwyD6zM5BWW4UPjfnYds56LaZ1Y3+dQjcUhxQAxACtaHNCOLKbiCuZtYKlleFW5lArrwfea+M0GvtFcZAqjAKheNQXKogE6Rr220Luju59enM69ApLHnOdvM6Mi+NAXT31utNBgJGtNqhyzjIFiZqXa6lhTDX06pyNyZqzY6oktytTUG0V5Sn19cak/v3L/1a6Ign478Z8/h9S5vRvRijL0frroCHH34Yn/70p3HiiSeir68Pruti06ZNuOiii3Dttddienp6yWv6vo/rrrsO559/PlavXg3XdbFu3Tq8//3vx3e+8x3oef57efnll0MIgS1btgAApqen8aUvfQmnnnoqSqUSBgYGcM455+DGG29c1F5mZmbwt3/7tzj77LOTvaxfvx4XX3wxbr31VpiOsQVLc9555wEAtNZ4+eUV/j0vEyu7iYiIiIiIiIiIiIjooJucnIRSqvWG0WivEbaCRua1mS8EFgJ+aRB2o9KaMS0EtFOAVCFM0IBbnYKxbHg9qwCtIdAMnQyM5SKKfwEYA7tRhqWCZPkAFvxKpfV1WmfbmhsNkToeAFS3oLstlO5oP75YbXO0ZdAARCvod2rTyAejqKzpPt/YQCQPBhgjABXCblSS34EBoO189jtUEAXhzUsxJlOl3k21Ul7e9dERz2gF8/iPDs7aj98Hs+09EMt5MARRV4lPfepTuOmmmzo+2717N3bv3o3vf//72L9/P6666qpFrzsyMoILL7wQO3bsyLw/NjaGe+65B/fccw++9rWv4d/+7d+S6ve5PPfcc7jgggswMjKSef/BBx/Egw8+iEceeQTXXHPNnOfff//9+PCHP4yJiYnM+6Ojo7j77rtx99134/3vfz++973voaenZ9HXmOZ5XvKzZS3vd7HSWNlNREREREREREREREQHXbm89BBUaNXxnrYdGABGCBhhwS/0QVk2lJ1D6OSgLQsDu57C5ifuxLrnfoZ1z/4UufI4ZBT3xv8g+U8gCtnTQbcREjo9sxpxq/P0a6U6wnqziJnZ2nIyr22/BrRfZ9uscBk0YHvV5HVhahfWPvdz9O7bGa3RKKM08QoKs2PoHdsJEXpoZ6RsBdlCQuqwNXscUXW7tp22k+avFO9u/jCcjmIvPglUpg/O2pWpaP1l0FrjT/7kT5Kge+vWrfjKV76CBx98EI899hjuvvtufPGLX8Txxx+/tC1VKnj3u9+dBN2XXHIJ7rzzTjz66KO45ZZbcO655wIAHnroIVx88cXZh33a1Go1XHzxxZiYmMCVV16JBx54AI8++ii+8Y1vYNOmTQCAa6+9Fvfee2/X8x9++GFceOGFmJiYwNq1a/HlL38Zd911Fx577DHcdddd+PjHPw4A+MEPfoDLLrtsSdeZ9rOf/QxANON7qffrYGFlNxERERERERERERERHXSLaZ+r7ByEDqGlA2E0hA4hQh9GNCsITfR/VmtGdrOiu2no5UeRL7daac+sPxle35p5v1e2VZQr2+2cTb2I/QujYdBW7dhWka3sPByvVTEe5Huzx2sFoVVUhS0tyNCD05iNI2QDLW0MvfokBAxKk6/Bqc0gzJWSiDlf3g8jZJcK77a25wu0PI8O6gzvrdCHlhakCmCkBe1k53P39vUtvC4dlczI9oO8/u8gtp655POuueYa3Hdf1Ab9Ax/4AG666SbkctkuDH/0R3+Eq6++Gnv37l30un/1V3+Fl156CQBw5ZVX4uqrr04+O/PMM/HBD34Qn/jEJ3DjjTfiF7/4Bb7+9a/jz/7sz7qutX//fvi+j0ceeQSnnnpqZp3zzjsPp512GhqNBq677jq8733vy5wbBAE+/vGPIwgCXHDBBbjttttQLLbGNGzbtg0XXXQRzjnnHHzmM5/B7bffjvvuuw/vfe97F32tAPD9738fv/3tbwEA73vf+9B3mPx3nZXdRERERERERERERER00PX09ADGRNXaWgOZuuJImO9Bo28d/N5heL2r4fWsBoSMqrCNhhU0MjOy24NutzqVCboBoLy2e1vvNLGoCuZsWGwsq2P/zXnic8lP70Hf6LOQfh1AFHTXBza0ZnbH90cAkFpBqAC2V02+2Q7q6Bt7PrNfpzGbqUoH5min3qZbi/j2/WvLQegU4Bf6ogp620WuvA89k6+iOLMXpaldKE68AsuvAYjaGg8Nr17wu+noZMZeObjr7xtZ8jlaa/zDP/wDAGDTpk244YYbOoLuJiklNm7cuKh1Pc/DN7/5TQDAqaee2rX1uRAC1113HVatWgUA87YgB4Crr746E3Q3HX/88bjkkksARFXi7b773e9iZGQE+XweN9xwQyboTvvTP/1T/N7v/R4A4Fvf+ta8e2k3OTmJz33ucwCi/57/9V//9ZLOP5gYdhMRERERERERERER0YoyWmN2Yj/2vrADu3c+g4k9r0JXZmA3yrC9KmyvAqn8zobXItVq2+hMkC2MhkyFvN3qrPMzo5nXWlhQbvfgp+N7U6TqDK2NzB6jpQ1tt0Kz0MlD5dq+K3U9ll9H774XIAA4XgV2fQaN0qpsBXnbHHOhVRTup7TPNe/GCjrbmAMmmluuQkCruO17AX4+CrIDp9gZgAsBlSvCWA6MsJCrTHQE65YKUJjei7wEjjnueDhutv07vYFMLr4qelkmlr7+k08+iV27dgGIwt7lzqpu99hjj2F6ehoAcPnll885v7qvrw8f+tCHAADPPPPMnJXjQghceumlc37fmWdGFe2Tk5PJ9zbdeeedAIBzzz0Xq1fP/7DJOeecAwB45JFH5j0uTSmFj33sY3jllehhhiuvvBJnnHHGos8/2NjGnIiIiIiIiIiIiIiIVowKA+zasR1eLZoxbQBUpqYAIZIgN2pDPk89njEdbcO7ze9ubzUu2s8xCjL0O+Zvd+zZycGOq60BwPaq0JYDlSu1tiQtGKMhjIEWEsZ2EFo20ACgw+hYIeZsd56f2ZsN94WEdgvz7r+bjlniAIQKoOwcICWE1siV90PZLtz6DADAK62CXxxIaukNBHRbOG/aZom3cxqzmeDdAFBuEWGuBAOBgvbh5vJzL0BHvwU6GxywLg+hLOSJJ55Ifv7DP/zDFdvK9u2tlu3veMc75j32He94B/7pn/4pOW/9+vUdxwwPDycV4N0MDQ0lP5fLZQwMDCSvH330UQDAvffeC9E+fmEOo6OjCx8U++xnP4sf/vCHAICLLroI/+N//I9Fn/t6YNhNRERERERERERERPQGppVCGIawbRtyjurEpdg38mISdCdSAYxB9xba7Tojmy5BcNs8bK9nFXr3v5RZozC1G9XVxybv2V4FynJhUqGxcgqQoQ+pFWTQgO3XYAV1NPrWIWyG2EJAW07Ugr1Z5S0EwkJvtgp9jrApHaZHV7OIUEpIaCEhABghIbSC1zMM6Teg8j2AASy/gtAtQcfBtQgDuLVJ9ExEVZha2qgObso0jdfdZpIvwPZav1MjJGoDGzLzussAXnzuWRzz5uPhztEmmo5ytgOE/sFbf4EHMroZHx9Pfu4WMi/X5ORk8vOaNWvmPXbdunVdz0ubq/V4k0x1llAq++DPvn375j23m3q9vvBBAP77f//v+PrXvw4geljg5ptvnrOK/VBh2E1ERERERERERERE9AYUBgHG9u7B7PQUjDEQQqB/cBBr1m+EbS8vPgh9H+WpibZ320LVtjnbczFtZxphAWiFPAKd8XejZxhBrgeOVwEAzK49Hn5pENAKkBbsRhlufQZGSHiloVZYKwSCQj8sv45CdSp6yxgUZvai3r8eYb6ntfduQc98Veqx9opsK6hDBo1MYGyETAX4BsYAfmEgmuktBETgoRB4aAzGc4WNQZgrZO6TU5/JVIg3eldngn0tRGtGeLxGcm2L1Ohdndl3U+D7eG3kJRx34smLXouOIkPrgX0HcW73qpULq1fSYqupD5Zm+H3hhRfi7//+71ds3b/7u7/D//7f/xsAsG3bNtx9990oFAoLnPX6Y9hNRERERERERERERPQGo8IQIy/shO+3ZjsbYzA9OYlatYZjt56wrOo9v1Gbs41364sWsZAQaI+zjbRglGi14m4PzbWGhMHEljMx9OoT0HYOlTXHQcDAaZShbBdOfTZa3mjkK+No9AxnAu+o3jq7QW2tTJRS710DGTSgnHwURqswqghPLtBE1xtXcBqI6OdkhrlBvjIBkTpHGJWd8R36mVbj2nLQ6GtVnRoAxkpVXRsDoUIYy0K3Wvo05RZgB3VoaSHMzT332Gs0UK2UUerpnXc9OvqItcfAHMSwW6zZsuRzhoeHk5/37t2Lk046aUX2km4rPjY2hhNOOGHOY9Mtw9PnrZRVq1Zhz5498H0fb3nLW1Zkzeuuuw7/7b/9NwDAySefjHvvvRd9fX0rsvZKW/hRIyIiIiIiIiIiIiIiOqpMToxngu4032tgamK862cLsexubYbb5mjDRK3Ak49NVHndHpJL2TozrqhWbgFGiCgIFhJJQGtMEgJrt4Dx438fU5tOy3yn41U7guz2durdZmZ3nRXe5Zjc7D6UxkdQnHgVllfLfh4GsEIPXu8ahPk+eKUhlDecBO0WW/fA6LaZ3tkw3/Lr2ZnZbdXkRggY2QrmtbQx+aYzMrO4dTzXu3WSju7JImaFB4U+GCGjNRaoZG3UavN+TkcnsWVlgta51z91yeds27Yt+fnnP//5iu0lHSr/6le/mvfYX//6113PWylnnHEGgGh2t+8feBv5f/mXf8HnP/95AMCb3/xm/PjHP848NHC4YdhNRERERERERERERPQGMzM1Ne/ns9Pzf55mjIFSIYzWyBVLcPKtNrfN+dwm9VpLK/opDliFVpBaQagwG7rG7bajcDsmJZRbbAupBWA665JNR/DeJchOV1YDUE4eprnv+B+7UZ73+u1GBf27t6M0tQu56iRsrwrlZKun3dp0JkiP5oBnI5rM/tsDdmMgUrOQjRDwSoOZQ0K3BJ265trQJqhcKblXpr19OQARP3Qguj1s0MZIG7WBDYuaNb4Ss9/pCHTc6UDPwMFZu2cwWn+J3va2t2Hz5s0AgG9+85uoVCorsp0zzzwTAwMDAIBvf/vb0Fp3Pa5cLuPmm28GAJxyyikrOje86Y//+I8BADMzM7j++usPaK3bb78dV1xxBYwx2LRpE+6//35s2LBhJbZ50DDsJiIiIiIiIiIiIiJ6g9ELVCtr1QputNYwcRAalKcx+/xTmHn2MdT2jGB8bAwv7HgGz21/Gs8+/RR2Pvs7NJRJYmVtu9BOHtp2o/eEBKQVxaVGxxXdceAKA6GCzsBbyOxMXNFtWvfClcnRzO9mo/JoPcurQQYNWH4Nll+HCH1oy0n2GbpFeL2r57tR6Nn/ImTqftYH1mdCZRk0MqG6BjrnXaevWSvkyuNIV61HM8dbkU6YK8FYNpQdhepaWjCWjTDXEz9MADT61gIAlJ2Lgvuuc8XjBw4ACB0uGHhrJ49G/7ps+/U2Qgj09g/Muw4dnYS0ILb9+4Oz9rb3QsilP0QhpcRf/uVfAgB27dqFT37yk3NWP2utsWfPnkWtm8vl8OlPfxoAsH37dlx99dUdxxhj8PnPfx7j41GnjGa19Eq77LLLkkD/L/7iLxasYH/ooYfws5/9rOP9H/3oR/joRz8KpRTWrFmDH//4x9iyZcvB2PKK4sxuIiIiIiIiIiIiIqI3mEKhiHIwk3lPaAUR+hAA7JyD8X1jmJoYR+D7EEKgv7oPmBpLjq8ObETQVl0c+D4grWgutQpbLbSlBW3nsvOmgc7W3cCCLbK7ElF1dzOqjdZutQY3iOdXu0MwlgsIEYXcoQc7qEfnqBB2oxydKwSMkGj0r8+2/W6Tq0xkgm5lOQgK/ZljpEq1HgcAaXdeYyq/dxplSKMgQy8OxaNoPqo6j2aWh3FYHuR7YQX1VvtyIdDoW4vC9J4otAei34dbhAy7tK0XolVhbwyMCqLfv1eFMAahm2+1Wk+fM0919/DadbBtxk9vNFprSCkhtr0X5vnfAKMvr9zi646F2PbeZZ/+uc99DnfddRfuu+8+3HHHHTjttNPw2c9+Fm9/+9tRLBYxOjqKX/7yl7jppptw6aWX4qqrrlrUul/60pdw++2346WXXsJVV12Fp59+GldccQXWr1+Pl19+Gddccw0eeOABAMA73/lOfOYzn1n2Ncwnl8vh5ptvxnnnnYdKpYJ3vetd+MhHPoJLLrkExx57LLTW2Lt3Lx577DHccccdePrpp/HVr34V5557brLGL3/5S3zgAx+A7/twHAdf+cpXEAQBtm/fPuf3btq0KaluP5T4bxsiIiIiIiIiIiIioqOc16ijPDMDA6BQLGXDSGNgeTVYKqp2NAAaVQs1L0gOyc2MAuX9yevQKXQE3RnS6piH3TUkbSskFoiqIbsG3s2q4ziItrxqFJ4LidAtIsjlo9BXCFh+DbZXSb7NSBvKLbXWNRpS+W0zsWuZ3fn53nmDbmgFpzHbemnZqA1u7ti7yVSlWxBCxA8CpCMaAQMDYQwsPwrfnUYZnpNPXbeEX+hDrj6TtEDXTg5+aQiWV01WCgt9qEkbll9HWIgCb2M5UMICdNiqjtUaQuuomj5uK59vVGD71dZ9s9Zg7hruTus2bsbQYTzblw6eyclJDA8PQ0gJecGnoG/6G8BbgdntuSLkBZ+CmO+/iwuQUuJf//Vfcdlll+HWW2/F888/jy984QsHvLXe3l7cf//9uPDCC7Fjxw7cdtttuO222zqOO/vss3HnnXfCOojt/c866yw88MAD+NCHPoTXXnsNN954I2688cY5j+/r68u8/uEPf4haLfp9BUGAj33sYwt+5/XXX4/LL7/8gPa9Ehh2ExEREREREREREREdpbTW2PPaK5idnp7zGCuoJ0E3EAXD2nZbBxgNtzqZOccvDixrPwZtcXe3juTNGd5GwwgJoRXc2jSsuAJb2W4U0saHh04eyi0kIbPQKhN0A9E863QILeMK9tYlqs4K7fmu0RjYXjVzNV7PahjLArTOhOTaycM0w+h4D1bQQGj1pO5D/CCA0WhOKLeCBpzaFIJ8K5RSuRIa0oLQKgnLw1wJoZ2DFXpx1TqgIeHWZ5CfHYMV+lCWjdrQm6K9xNXcVpj9vdteBY6fCs2dfEeV+kIOZphHh7epqSmUSiUUCgWIofWQH/gC9B3/58AC71wR8j98AWLowOdcF4tF3HLLLfjpT3+K66+/Hg899BBGR0ehlMLatWtx+umn46KLLsJHP/rRJa27ZcsWPPXUU/jGN76BW265Bdu3b8fs7CyGhoZwxhln4GMf+xguvfRSyAMI6xfrrLPOws6dO/Gtb30Ld911F5544gmMj49DSonVq1fj5JNPxrnnnosPfvCDOPHEEw/6fl4vwpgFBjAQEREREREREREREdERae+u1zA1MT73AcbAqU23BcNFaCeXvJZBA337XsicVh3cNH8YPBetkA6IhQogdYhkdrTWUTv15neHfrZCG/Hs7Tg0NgDqgxta7dIB2I0K7KAVsClpI0yFtgaA7dfi723O8AbycaBvhERtaFOrNXgXMvRgBQ3IwENpaheMkKisfjMgBJTldMzktutlWH4NSO0zdAtQTj5bCW408tOjkCYbvHulVa0AvRnrSInkaQGDeL55FGQXpvfAaZSTNer96zKzx0Xow/Eqqe81yJf3QaQio0bvGgTFpYXdg6uGsX7T5iWdQ0eHnTt3QgiBLVu2JJ0jzORe6B/+3+W1NF93bFTRvQJBNx1edu7ciTAMYds2tm7desDrsbKbiIiIiIiIiIiIiOgopMIQ05MT8x6TDpabTMc86c6KRCtoIGh/02hYgQcY3aoO77ZWswJbBZA6aH2/Mdn9GJNpqR3tTWbWDN1iJugGAKlbO9PSRlDoz4TlEDJzjTqukG7Oww7yvfMG3UB034CojXg0N7uR7EuqABAyUx0fFnqj1utBAyI+zvbrECpEWOhNr4yg0Bc1NRcyuZewUnO+O9q8i0y5vN2oZIJuIyS80lD2HoV+5rVQYSboBtDZhn4RDqTVNB35giDA7t27ccwxxwBAVOH9kS/CPH4fzOP3AZWphRfpGYTY9t7oH/490SIw7CYiIiIiIiIiIiIiOgrV6zUsp7mr0DrTWVzbLgK3AGO5MNKGDBsQoZcJXS2/DrtRSVpwKyefbYWeLN4KbGXoZYLs9uC9PYBVlgMDAWmiKdLKduH3rOr4CpNaJcj3RuG2abY9j6qfteXCUkF0bBzmK7cA269BOYVF3qlIo3c1nNo0EM8PFwCs0AO0hnZbFd4qV4QwClI1K8qje5vcR2OioNyyk/uvrVxn8N5tnnmKU5/OvA7dAtAWXAvTNom7y5JS+Z1vzjVPvfldvo/A9+G4XX739Ibg+20PUkgJ8fb3wWx7D/DikzAjv4PZNwJM7AVUEHU7WLUeYs0WiC2nAsed3porT7QIDLuJiIiIiIiIiIiIiI5CYoFQFIiqd7WQURWvEFHgrMOOULM6/Oa2dtutz2Xow26UU9XTAkG+Z95QtD3YNhAQqYTdCJEJaLW04JcG4dRmo2pnAF7PcGY2dnKsnYOlfGhpt6q+Tdzuu9n+3HKgpQ2Rahce5Huja+8YIt5JSxtCh1FLdUQzzG2vBsuvQxgNbTlQ/WszQbbdKEet0+MLV7kStN1qFy/iOeWte4Jk/aVIzx4H0FGxDcRV23Eb9+i1DS2tzLkyaGR+z3ajAsuvRe3Q5/jdzs5Mo1qtYMtxxyOXX9pDA3R0E9ICtp4JsfXMQ70VOsqw/p+IiIiIiIiIiIiI6ChULJZgWRIy9CCDBoQKOw8SAmGhDyrfA5UrJT93th+f+7XlZVuNh04+0/rcrs92+W6T+klE1cui9Ym2XOjMfOti1BrciSqGtZ2DsbPty5uUk4+C7nQQLkQ2whYCYa4H2nJbM7CFgF8c7Iy6jYHdqCA/M4bC9F645QkYYSHM9ULlSlBuAW5tBm59BpbyIXUIv2comtudPBDQSGaEA1FrcW1lq5/TwXvzmIWquLvRbW3dLb8OobJN54VWresGoG0HXqpKPsj3odG/PlO5n6uMw/FryJf3AWGXqu+YCkPs3bVryfsmIloOVnYTERERERERERERER2BlFKoVqvQWqNYLML3GpgcH4fXqMOyLOSgYJfHAR1VC4dOAcrqEgssI1BtkkEDVugnayjLjcLymOVV0Tf2PKY2vXXO72yGukbaUSjbfG07UJYDSwXQTlQBrZw8LL+RzNnuSoik0jr7fbLjOOUUYNdnomuAgZY2wkJfqiJbIz+7L/484hUHAKtVce1WJmEH9eS1snMI8+k53Ihmmadoy+m878toOd+NXxzIzOyO7lkdYSEKwXPl/ShOvoag0Ae/NAQtLWg7D+0UUIeAW51Coy9bve3UZ5IHGmy/jpyw4PUOz7mHWrUC3/Pg5nJzHkNEtBIYdhMRERERERERERERHeaq05OYGdsDv16D5ThAsQ/lugcdB9nQKpllDQAqaMB4leS1ERLKLc7/JW2ty0Xowdhzh5Uy8JArjyetwg2AoNiXWaMwvRfCGLi1aXh9a1pfJW0YIaIW23EVuLZsCBVGLcxjfnEQueoEkrJvIeEX+zsqlZN1o4MAIRHme7LX1BEua+QqE9Gc7PhcVRxotT4H4NRmMkG3sl1oN9ue261NZ16HuVKXjenO99rF7c6Tl0ZHM9fT+1YhMF/Qj6g9uldahVx1AsrJIyz2ww49oFGGkg6Kk69BAHDrs7CCBirDxybfERb6oqC+rWW9FTQy3zHvwwaxIPAZdhPRQcewm4iIiIiIiIiIiIjoMDbx2suY3P1q8roRaoSmVUkMYzJBN4yB5aeqmhFVdWeC7MCDcVJBpNaIZlpHFcsi9GHXZxH0DM9Z+e00ZiEAGKMBYUG1tS8HALc+DQAozIzCLw3BpEJSZeezIaqQUE4eQrXCZWPZaPSuhlQhDES0F0tASyvac9yq3CCeQ908xhhAh/POLXfqs0nQDUSt0dMztGEMHK+aOUc5bXOojcm0J5+TkJnAW6oAqi3INtLKtHs3Mjuv2/JrsP0aglxP1CJ9Hl7faoS5Yqai3A4ayNfHMi3nhQph7Gw79cVU+ss5HjZIc1wG3UR08DHsJiIiIiIiIiIiIiI6TDXKs5mg2wAI2yqLRXvYanS2yttyM+GoDDzYjVn4zur4eBOtIWQyr9r2a5AAhAo6w9D4HBkHqUJrGCE7wlkYk1QqW6GHvtEdKK8+HtqN9yItKLeYqtIWgJQwIhe3NY/X0xrKzgHSagWxqaA4CrrtbJhvFOaNbI2B5dczbykn13GMaK/Ibl9URMG71K1527ZXhdd2mHLysFMPIMjQhwzq0KlqeyMsGKEhjIaWVqbCXKgwOd/xKghDH6q9ArvjOwuw2kJpqdQcR89DiOghBK1gpAWpQtiNKrSQsON7GOaKCAt90e8BQKm3F67b5e+GiGiFMewmIiIiIiIiIiIiIjpMTY3uyrzWlhuFvjG7UQaM6Wit3WSERJjrybxne1VIYyDCAMZ2AKNbFdrGADBJ5a7tVxF0my8d1VkDAAQMoEII3RakCoEg3wfbr0JbDmToo3/vM5jafHpSkQ0hWqFuuo13+vvaQ/T2z4XoaLu90PzrKAxvP6btGoVotVqPWX4DQaE/c1hQHECuMpG8DnOlqIq72Z5dSOhcD4QKYSkfQoWQOoRbm0ZgTNRePr4GbTmZc5PvDbNtxKVRUMuYta6t7L2URsPya9kW91rDChuQYQAIQFk5NHpWJ78zGXooTO9FLtW+3Qo9uLUZ1Ac2QBZ7sH7T5iXvjYhoORh2ExEREREREREREREdhqYmxjE7NYlm7KktO2oVHhOhj1xlHEGhH5n6Y2lBCysKRO1cphpaGJ203Y6C7P4kzBUAoFUqxkZUxVufjeY4y1QAKySU5UDqEEZYEFrBblSy856NQW1oUxTcChFl0JadXQfoDK6XyLQFw8m1LHCOaTvOCj2o9LxtIRC6JTip2efasjvCaK80BNurwgoa8HpWwetd3foeiCSsD4oD0H4tCcajudkz8IRsPawgRNJKPnM97Q8SLIaUMELG50ZXG7olwADaycV/Dypz/4QK4dRnkwcBjJDQOSdzvbnZ/R0V7wbRgwHF2iQ2nP522DbjJyJ6ffDfNkREREREREREREREh5l6rYa9u16DJSQABYNoxnVcgg0IAadRhkBUqR3mezPnK7cA6VWSttIJ3QoprdAH6rMIU1W9wugoDBUy+lkISOXDrk0hLA1lwmivd1UUzCYV2SYTdMvQz1Rla9vpXqV9ELQH2R3i+eB2PDPcAFDSzrRHBwC/2B9VOasQfr4XYaG3NXu7GQBLC9WhN8GpTSMoDmT3kXlAQEThc3tF+SLuSXugL7QCtMqeqxVsvw6pfAACynKiinuj4muMgvew2J+sGbQ9nGA3ypn9tc9hl0EDVmqmuhYWgtIgwlwxmUs++vILWH/s8bAYeBPR64D/piEiIiIiIiIiIiIiOsxMTYwDQNT+WwXR/GopowDXaBhhxaEmIHUIpz6Taa+tnTwCdLbzNtKKgtM41JWhB1sFCIsDMHHoKbSKW2unKrLt7Ezs6ItTEYMQSMfLQmfbhKcrnFeaMAYmvbX2fRoD6DCe+S2TNudhrgdW6EMYjTDfB5XPtnsHAEgL9b51sBtlqFz0UEDyOwBSgbdE0DPUbXfzvIrNVbWtVXRt0kLo5KNqdCsK5EXb7G0Z+nCrU62KbETz1tNzzTMzzxHPKE/POVdBZta7ETLqDJD+ntQMcCMkGgPrMrPFISTKlQr8nc9hywknQVqvz8MNRPTGxbCbiIiIiIiIiIiIiOgw06jXAERtv5XlJtW5QFx9rZGpuHUaZYjQh98znASY2il0zq4WAl5xoBV8ah0lsM21jAGQrRiOgu7OVuHzaW+7bZbRnnzRjAaMTCrMo3ncqb2oAFIrGKWgHTd6DwaQFrzSEKygHs3ZnouUCAu9Ha27F26WDrTXmCvbjYL/5jxwrWAF9czMdaEC2F49aTevLAdhvgcqlwqVUz/CGLi16ezDBe1zzJF9bYSM5r83LzFooDi1O6lMN0LAL/R1PDhgrFasFBT6skF3iteoY3piHENr1s51Y4iIVgTDbiIiIiIiIiIiIiKiw4yVqojVbh5QQSq4jqZqB3GYrS0HwmgIFUDosK3Stksgmwos2+dnRxXZLVFourSguxsBtDfvXjHRrPEwatludDKDHED0Og7eBQxk4EX3p3lfpIUw19v9Pq3E3rSCESYOoqP/3+hd3fodaJW5v9HM7HLyOzAAwnxp3v1Zfj0TxGthwYhWxK6lBeUWWy3bhYRXHIj+ZgDAGPSOvQAIiWbdtnIK0QMP6XspBJRTgJY2pA6j+d/zmJmaZNhNRAcdw24iIiIiIiIiIiIiosOAidtrCynRNzCIaqWSfCYgYNdnYAUNCACh7SLM97UqcYGk7fiBbWI51ctdlhGiI3TOzMM2BpZXhcrNH+QuVjPw7ni/Lbxffuje3HdqXndzbWMAEbWI7/ZgQKs1ePSQQvZhg2ybb9uvZfar7Fx2TaORrtIWoQ+3NpWso4UFrzQYvYfoWv3Sqkz78dAtRseraM6605iFHdSj3cVzwNvbl7dug4DXuxr5mdGOByXa6bnasxMRrSCG3URERERERERERERErwNjDIQQMFqjOj4Kv1aFdBw4fYOYmpzE7MxM1JI6l0MYtMJJoQLkKpOZecwd1cgrEXSvICNtGOUn4bJOV1MbA7c6CTtoIAw9+KXBFase79zIonab7CtaKGrvbgX1qFJeWNCWDTtoJK3FtXSgbBcimYktm1H2wnuacxsaQrUCewPApGdeaw0Z1KGbLdeNQWFmLwARBe0AwnwPYNkwlg2hQmgnH7XClxK2V4FAPKsbgJFRYG83qvFeDXKVcXi9a1q/q7g1fJrKFVEf3JgE49lG7S35QnEpV09EtCwMu4mIiIiIiIiIiIiIDhK/MoPZl3egtn8PoDXsvkH4ykCrZmhqwy8OZMJe3/MyaziNSmYes3LymaralW0P3lb73F6RrRVK46+guubN8y8jJQwcQAVRe/FUBbMMvaSlth00IKdH0RhYtyKBd7so0G1dkQBgjAaE3bpUoyCDMLnHQgWwvGqqlbiI7ncSbAvoVNANANqyV6CqHqnvbP7Q+l1I5UHCRBXT0oLtVaJZ5BAwxsAIEf1tAFBOEVLNtuZyC4kw1wPbq7Tus5AwAtCpvyXHq0LqvQjyvdBxKJ4E3ipMKsS1ZcNY+ej+Chl1JNAKQofJNQytXnNg94OIaBEYdhMRERERERERERERHQTe9AT2PfEgjIraORsINDw/E4oGuZ75Q16tIcNs+G1kl/9pf7lBa1tr8XTQbZrflQTdGut2/BSFmVHM1CYxecy2efdupAXT5XPbr2ffmKP995KuAeh+D4SMWnI3A12to+OSa1aQ6VbnWrUF3cgE3UBblToADbkyQb0QMEK25m8LwAo9aLeQhMkAIFUALS1Y8QMDAgZCBTBOLtmXdnIITSnTll65haSaO3n4QMqoLXl5P4JCPwDArs8iPzsK5RYhtIpmgNtOsi8DQNv9MOl27ELAWDaMlJChj/Wbj0Gh1HPg94SIaAEMu4mIiIiIiIiIiIiIDoKp555Mgm4AUTiYCkmNkDC2O+8awuguLaK71HKnQ+vF0BrF6T0I3SL8nqFohnZQhzAaWkThs7HsTAV5aeIVFGZGAQD9e3cgP70Xe976R/PPbu62p/a54B1zwue4rrZ22kIrSBVAGB23Snc77nEm2AayezUmOj+1pgy97P3u1h4+VaVuhICxnLn3vxRCQDm5zMMAwmjIoBFVkje/XocwoZ9pmy51CBOYqO16/DCEcoswOpoD37zHWjpAHI4n1yAtzGw6LX5h4NamYIU+ZByuC4HM70jbOei4grzzGiQG1m7A4PDqA7sXRESLxLCbiIiIiIiIiIiIiGiFBZVZ+OXpzHsmFZIC6Fr13C6qjhYQqaDXCj0otzUPuRmIqtQsZ8uvQVvOnGF6YWYUtl+D7dcgdQg/35tU7kqjoI0G2s7tGX8581q3tVNfLG05QFyVHH1ftP9mSGuEyFZKm85wX6gQMp4JHr0hO4Pudu0PBOjsgwRGCAidCnWlBW3nYCk//c2Z/bRXeR8o5eQh2qr5bb8GpcPMbGxL+TDSgracpHW59OqQgQ+Va0U/QgoInZ0DPt9uraABK2xdr0Hn36maK+iOzc7OYsOGDfMeQ288Whu8+No0RnbPYGyihsnZBsJQw7YlhvryWLuqiC0b+3Hc5gFIuXL/nToQIyMjOPbYYwEA119/PS6//PJDuyHqimE3EREREREREREREdEKU4G34DFCq0VVZIdOAY5fAxAFskG+txVaGo38zBik8uH1rkGY74Hl16PW3DoKrbXtZsJjEfrR7OaYW5uOgt3mjGago3U3AFht15QOUeeVtOA2MEIidIswlh0FxTCQoQ9hTLKeFhLGmidENyYbdANQC4XO7YG50RAmVXUPEc23TuZyx6GuEDCqGRALAAJCq6hlN9pC+ZUgBMJ8CTKI2pRry45meYcBtJuHau7RGMApICgNts7tWfhvaaEI0WpvMd9eGY+FH9JQqW4G9MbjutmHZLQ2ePzZMTz+zBgqtaDj+DDU2DdZw77JGp7eOY6eooNtp6zFtpPXHjah9xvFo48+ip/97Gf4zW9+g2eeeQb79+/H5OQkXNfFhg0bcNZZZ+Hyyy/H+eeff6i3msGwm4iIiIiIiIiIiIhohdnFnlYoGRMqzM45RhQYJ22wjYbdqEA5BRjbSc4Ncz2QKoSlfPjFAWg7BxgDYwyc+mxSeZwv70PoVZKqbwHACv24+ji1t6DREXqa9grtLp3S/eIActWJ5HWuMgGrUYHKzz2bWagAQoWtGdhCwlhWFMAD0TWmZpAnc8LnkV4PQNR2va1qPnst7UF3FL5nqrqlFbcRL0CqIHodr2mklczLBuKHFLQCVqp9edxmPKoqNzBCdLYKb38oolsGuAIV5mK+lvIxqRU64mxjkvvs5HId59Abg+M42LhxY/J6cqaOHz40gtHx6qLXqNQC/PzRXXh+ZAoX/MEWDPUXDsZWqYsvfOELePjhhzve930fzz//PJ5//nnccMMN+I//8T/ihhtuQD4/f5eH1wvDbiIiIiIiIiIiIiKiFSYsB1bPAFR5CkDUErvevw6OX43CVAj4xcFM+O3Uy5BaQaoywlwxCrUBQAj4xQEIFcCk3oMQcLxsiJRuw916s60yt0tSKlUYVUc3TzGdVefTG09FZfUW+MUhSBVVhyt37iAqajWebaHdHqq379cIa97QNlrTSyqqjZBRRfqSgt74DggRXWJqX8rNw/JrmTBZWy6E8ZJW8gJRlbsypqPVe7R8HPwKtB4aaIbIzRbtqTnkUXjfCuS73oMVbJU+HyMtIF2xn1xL6/tF6AHp37tWmdnyYaOGl3c+j03HbIHjzj+Tno4uGzduhG1H/07bs6+CO368E16wvEr/0fEqbvrBDvyH92zF+tVzP1BDKyeXy+Hcc8/F7//+7+Pkk0/G+vXrMTQ0hP379+Opp57CP//zP+Pll1/GLbfcAiklvvvd7x7qLQMAhDFdhl0QEREREREREREREdGyhIGP1559GkGtCrc2CaEVqquOiSp1tYZbn4aRVnbudhjAbZQz63iF/s6Z2G2hZ2n/y5mgVNk5hPne7H7ituEJrdAzPgLlFmGEgOXXEeZK8HuGohbVxkAYk1Q7L5cMGplZ40aIzD6MAaz0PGkh49bmczAGll+Ng2qZXG97tXy389pfy2YL87iqOtPqXWtYjQpg29lzVABhogcXhDGADqGcQhz0mqgVfLz/pJK97We03VOhwkw1tYGIqvpfL21BtvQbyNWnk9ehW4SyHNhB1N5cOfn470bGwbhu3cs2bi6H4048GeJ1Curp0BofH8fw8DCAqKL7ph/sgOcfeEv7nGvho+8/6ZBUeL/RZnaHYZg8rNBNvV7Hu971Lvzyl78EADz11FN461vfuuTv2blzZ/JdW7duXfZ+m1Z4mAQRERERERERERER0Rvb+K5XEDTqgJTwS6vg9axutaSWEn5xEGEq6AYAqbKzbE187EJ0WzAqlQ9jDLRlQ8dzpdMtuKODLFRWvxn1gfVo9K9DdXgLvL41UftwIQFpRQHyEmZgi9Dv+DwddEfzybOhLoRsFT4D3YPudDCsU+3L47XNfO3L5958dn0hM3uDlFDFPmhpQ9m5+B8XQb4XfrEfYaEXQaEHxnZg6SAKe42GEVY81Tu1fPZisvc0DtozO1vE73zxlzl/raPlVaMq9iatACkRxn+roVNAUOiDdgsI3SK0tKCcKHAURkct6o2CXZ+FW52EUNkZ7r7nYXZ6euWuhw5rQ0NDAKIZ3T98aGRFgm4A8HyFHz40Aq1Zu3uwzRd0A0ChUMB/+S//JXn94IMPHuwtLQrDbiIiIiIiIiIiIiKiFaKVQnlif+sNIRDmSh3HLVTrKqLFOt8PfeSn9yI/vRcy9OEVh1DvX4fq4CbU+tej0bsGYaEPyi1CuUWE+Z6ozXfHQqL7z4sg/XrmnNzsGNzq5NwnGAOhA8h0sCtkFOY325Evooo8O0/aLBjmZmgFEQYQOgQgoIWMKrHjfxBXtGe2bbtRJba0ovncqT1agddWtW4t/HBCl+s7WDXPdqOcDbLbWH4NjleF7VVhNyqAVpDx35tyi/DyvQhSs9i1k0eQ72vdM2GhMD2Kdb/7MdY/cz/W7vgZNvz2Hgy89jSQak1frcwepCukw42M//4ff3ZsSTO6F2N0vIrHnx1bkbUefvhhfPrTn8aJJ56Ivr4+uK6LTZs24aKLLsK1116L6WU8oOH7Pq677jqcf/75WL16NVzXxbp16/D+978f3/nOd6C7jZeIXX755RBCYMuWLQCA6elpfOlLX8Kpp56KUqmEgYEBnHPOObjxxhsXtZeZmRn87d/+Lc4+++xkL+vXr8fFF1+MW2+9FQfa8Lu3t9U5pNFoHNBaK4Uzu4mIiIiIiIiIiIiIVogKA5h5go2mdHtrAFEbbb+eVPoaISF1GAWxAGAM+vfuQGliJAklJze/FbVVx2TW7NAesLa1rY6qeRdfHW35dTi1aTTimc0yaKB37EXUBzfAa/teI2RUAWxUdK0qAOwcjGhVOGvLhgz91t0QohU6i+x7RrSHySYJr4UOYaTd2dJcKziNSlSFjOi++sX+7DUvNXE2BqK9En9ZFeadfwdC6861lvg7shtlOI1ytLYxCHPFVot2ADAGtldL/l4svxZVpksLwmgYIaCkm/lOI0Rc+R/ttjCzB8Mv/jLTQl/qEL37XoDl1zBx3DuaV7TofdORT2uDx59ZmVC63ePPjGHbyWsh5fL+pur1Oj71qU/hpptu6vhs9+7d2L17N77//e9j//79uOqqqxa97sjICC688ELs2LEj8/7Y2Bjuuece3HPPPfja176Gf/u3f0uq3+fy3HPP4YILLsDIyEjm/QcffBAPPvggHnnkEVxzzTVznn///ffjwx/+MCYmJjLvj46O4u6778bdd9+N97///fje976Hnp7lzUFPz+k+6aSTlrXGSmNlNxERERERERERERHRCrEcB6KtwleqoNWy2mjAGLi1GfSMvYC+Pc+itO9FuNVJyLAOS3mQyoNy81Hr8zgY7h/dgd79LyZBd71vbSboBtBZ6dwWuovQzwTdTnUKVrC0yjynPgtpdBxQA/mZMQgY5Gf3dXxf1Ea9tS8BwArq2X0KCW252S9p7tFk240by4GyHCinAOUUYIRErjyOwvQeFGb3IT87lm3ZbjTc2kw0azt+K8z3LCk47sro5UW47b8fIdrmdSMb9iOqore9akeL8Pm+w/aq0MKCERacxiykn3kMATKoAxCAtAFpRyG2MZC6OT9cAKn2+AZx5Xrqb2dg1/ZM0J1WnN4DpzYNAOjp7Vvcvumo8OJr06jUgoUPXIZKLcCLr00v61ytNf7kT/4kCbq3bt2Kr3zlK3jwwQfx2GOP4e6778YXv/hFHH/88UvbU6WCd7/73UnQfckll+DOO+/Eo48+iltuuQXnnnsuAOChhx7CxRdfDKXmbu1eq9Vw8cUXY2JiAldeeSUeeOABPProo/jGN76BTZs2AQCuvfZa3HvvvV3Pf/jhh3HhhRdiYmICa9euxZe//GXcddddeOyxx3DXXXfh4x//OADgBz/4AS677LJFX6PWGmNjY/jJT36CD3zgA/jOd74DIAq63/e+9y16nYOJld1ERERERERERERERCtECIl83yAqlUpUwRyHh8m8aWNQGn8ZuepUco6RFizVmnmtnAJUqvW5CH2U9r+c+Z7y6jdnXsvAy7Qrt+uz0HYOWubizxuwAg+B7Sav8+X9aPSugerS5bzrtakAUkehq90owy8NwQ7q0XoqQO/YTpTXbW1VEUsL2nYhU0Gt1AqOX0WQ62u1/ZYSxgiI0E/Cai1toL1KWwiY5uxzreDWppPwHwC8nlWZquio1XgqTBay+1zwpYpnjWcqso2CaYtcMscYEx0jRHLdbmUCtleDVxqCsZ1o76n9CxXAiivILb8GbTnQTj66RwJRSN1OhdF9aF6nVpmqbhl4cPxGElwbRHPCk+cLAKjmQxbNrQuZeW03ynDjMHsuxandaAytR29//7zH0dFlZPfMwV1/zwy2HjO45POuueYa3HfffQCAD3zgA7jpppuQy2X/xfdHf/RHuPrqq7F3795Fr/tXf/VXeOmllwAAV155Ja6++urkszPPPBMf/OAH8YlPfAI33ngjfvGLX+DrX/86/uzP/qzrWvv374fv+3jkkUdw6qmnZtY577zzcNppp6HRaOC6667rCJmDIMDHP/5xBEGACy64ALfddhuKxWLy+bZt23DRRRfhnHPOwWc+8xncfvvtuO+++/De9753zmvbsmULXnnlla6fvfnNb8btt9++4Izv1wsru4mIiIiIiIiIiIiIVoAxBrteGUG53ojaaTdnPVt2Enq6lYls0C0kVNwSvCnMZ9vL5ivjmXnXs2uOh987nLy2vFpmPrMMPLj1mbjFN6JqX78ehaRx9bVbm4YA4NaXEE6lKo7toAG3OhWF0ql9Drz6JIQKIVQIGXgABEInFwXlgRe9p3TSrh0AoHV0DaEPqRWE1oA1/wxvp1HJBN3asqNK+BQZZiuaFzMXfFGEyLRLN4jCeZN6bYQEpJW8J4yGhIFUPqAVLK8Kx6tCwCBXnYRdL2dbjQOQoQ8jrOgeCwu2X0NhajdKk6+iNPFqVD3dXi1uO62gG8jMGW/+HaSlW8pHG5Wdle9t90wsok2/a1s45s3HQazE/aYjxtjE3HPiV8K+ZayvtcY//MM/AAA2bdqEG264oSPobpJSYuPGjYta1/M8fPOb3wQAnHrqqV1bnwshcN1112HVqlUAMG8LcgC4+uqrM0F30/HHH49LLrkEQFQl3u673/0uRkZGkM/nccMNN2SC7rQ//dM/xe/93u8BAL71rW/Nu5dubNvGl7/8ZTz55JM4+eSTl3z+wcKwm4iIiIiIiIiIiIjekAIVYrpaQaVRhzEGM7MzePnVV/DCyy9h99698Hx/4UVSpsbHUZ6Zzr7ZFkbmy/szr72eVZkwMcj1dLb1Tmn0rsbshlTIYAzsRgUyDJIA2fbK8X9WASAKn41ptREHkjbkVughVx5f1PUZy4ERMqqQlhasoA4tLdQGNmBm/cmYWXcitJNHz74X0Dv2PHr3v4jefTtRKO+HFQZJOB0U+zNV21bQyLTE1rbTEfy2S4f7ALpXbLd32TYLh7SLpex8FBQjqoQ2Tq4Vbjert4WI3xMATGtGtgpgN6rwC33wioMI8yUo2838HQgVwggreWhChg249ZmkA4By8giKA0sK70XSpjz9ZvZ80229tvsY5Hug7GxYaIREdWgzJt90OqY2vxXusW+B7axAFT0dUSZnlzYWYakmZpa+/pNPPoldu3YBiMLe5c6qbvfYY49henoaAHD55ZfDsrqPR+jr68OHPvQhAMAzzzwzZ+W4EAKXXnrpnN935plnAgAmJyeT72268847AQDnnnsuVq9ePe++zznnHADAI488Mu9xP/rRj/D000/jqaeewk9+8hNcffXVWLNmDf76r/8an/vc51CpVOY9//V0eNSXExEREREREREREREdJMYYzJZnMTU9A6UV8vk8Jrwa9kyPQ8VVqmucEuxUqFeuVLB/YhzHbN6Mwf6BOdc1gQchLQjbwcT4vsznQgWZKlvLr2dmZNf718Mv9iNXiyq9lZ3rqOoGAK+0CkZICKNRGd6S+UyGXhIUW14NKt8TzQhHFGTbjTJ0Kpi042prI1rBTK46CRk0UB/cmA1ctUKuvB9OowwjLdR716DROxy1zxYCRhsY206CaRl4yFUnklA7aoldyLT7DnM9ba26OwPYru2527TPi87M6o5p24H0sy3UhQpbVdnGwK3sR1AaWtR3ZkiJMFeCCFO/YyGiEL9t1jhgknsGY6CFgOpbPXdQrXV0D5OKbA2nPps5xC8sfRa2aK8C73aMVtH+U3uTKkja4TfXqQ5uRN/+qH1zkO/F/q2/D+W2qkkrtRDTL72AzVveDClZd/lGEYYr90BJN0otff0nnngi+fkP//APV2wv27dvT35+xzveMe+x73jHO/BP//RPyXnr16/vOGZ4eDipAO9maGgo+blcLmNgYCB5/eijjwIA7r333kV3UxgdHZ338xNOOCHz+vzzz8fnPvc5vO9978O//Mu/4KmnnsLDDz+8Yg8PHAiG3URERERERERERER01NJa48WREVSqrSq0l6f3wzOtcLRXOpmgu8kYg5FXX0XPSSUESmF8ehKhVujJF1Ga2ov6i9uhqjOAEGhsOgWB05qz3aw8VnEQKkMfVuhFFdFKQ0sb9YF1EFons53DXBwWGg2kwmjt5FAd2oyeiVcQFNpmIKdbi3vVKIROVUW7tWmETj4VbgtYQQNaWPAL/VBODkJryKARBcF2tF+7UUb/nmeTGd2hU0B16E1JUGyA6NhUsJKfHcu0FjfS7miJHba1bO9abb2IrEbZeUjV+p3K0M8G2Yiqny0/qho3AMJ8b+bz4tQuOI0y3EYF1cFNMPYcFfVt4W9rnzKq6O54P3Ws0ZnwycTV3vNp3vOm9sp3AJkHGBar2Wo9cyXt1yZk5u8vVx7Hhqfuwr4Tz0N53QkQKkSuMo7GwHo4XhW52THsP/6sTNDdVC2XMbZnN9Zv2rzkvdKRybblQQ28LWvpD06Mj7c6V3QLmZdrcnIy+XnNmjXzHrtu3bqu56XN1Xq8Kf3QiFLZh3v27dvXfviC6vX6wge1GRwcxLe//W2ccsop+O1vf4u/+Zu/wd/8zd8seZ2VxrCbiIiIiIiIiIiIiI5ae8ZGM0G3p1Um6AaAopi73bIxBk89vwNeXC0NAMPjr8DMtMKFRs8wqqmgG1pDhl6mero5Pzos9MGqTMAvDURhqSWhnALsoJ5qxW3iwLEVbkxvegtgDIQKALQCY2M5UYAZtyl3GhUYYxDkSlHFsdGQoY8wV4JutsrWKlp7zspihf69z2ZC19rQ5kxQjPZZz+ic/226hbrt39llD0IrmPZQK30/jEGYK8L2KnGD8OhBARk2oGSptaa0EBR64TTKUE4BOhVMW34NTiNq924FDfTsewHltSdk26v7dVheDVKHMBDwi30wdm7xrcON6ZypvUB79uS8+V4jmgG+YJ12e5AtJbTtwopb2GtpIcj1wAob0TWKqFq9uUehFTY+dRccr4qNv/0BJmdHMbPupKgSXwiU123F7LrjoXJzV3ZOT01izfoNc7Z4pqPLUF8e+yYP3tzuVf35g7b2gTjUs+mb4feFF16Iv//7vz+o33XyySdj69at2LlzJ2699VaG3UREREREREREREREK80YAyEEtNaYSFXRGWNQ0dk53D3ChjVPUBHCIEgF3Y5fx8BMtoqu0b8281oqHwKAMCppZd5ssx0U+mB71UwQ7pcGgSricDKqvDVGR6+bgbGQmH7T24AwyHyX0ApShdE8ZgChk4fXtyaaGd268LbQc/7gMV8eh1StoNtAwOsZyhxj2suvjems0u4S0srQh3ZagZWRNgy8ZDXTPK25Z61RmnwVRlioDW1KrhnSgl8ahFudhnJyMJYTtSn3KgidQhJaG9uFXxqK1mtWnQsBy6+jNrAhmo8eh7fp+2LXy7BTc8GjudxLDdo67tKydJtHbjUq0D2p6u7mtTWvQWuI0IvC+dTfQpgrQRgNoUIE+V5ASihZhAm96OGEVBjfO/YCnObcdxgMjTyO8vCxmfuk3NRDHl0YreE1GiiW5j+Ojg5rVxUPati9ZtX81c/dDA8PJz/v3bsXJ5100orsJd1WfGxsrKPtd1q6ZXj6vJWyatUq7NmzB77v4y1vecuKr99u9erV2LlzJ1555ZWD/l2LwUEJRERERERERERERHTEM8Zg//g4nnn+OTy5/Wn89nfb8ezzz0HrVgBbNQGCVD1sXljISRtmjlnGxhiEyAa4vZVsC1ojZEcLZ9HWWlykwnIIifrA+lbVs4kaS/s90Vxug2Yb8rhmuX1vdiv4lEED+ZkxyDjoNkLC612dDbqBxVciJ3uuZF4bKTsqkjtWFALKybYolyrI7N8gmuudfq0tG8otRiE3AOUWomuM91yYGYXjVeE2ZlEaH4Hl15KW3trJo9G3GsrJQ1kulOV2VjsbE4W7RkEaHf0T+lBuMWoFLgS07ULlWhXhQoWZoBsAVG7pIdvCpddznNb2MIK2o2tL9mLnEBRb7eyFVrC9KmyvlszclqEHiXimuwpbvwchEBT64Bf7W38nQkA7+Y655fnZsc59dTwosfBFymW0nqYj05aN/QsfdCDrb1j6+tu2bUt+/vnPf75ie0mHyr/61a/mPfbXv/511/NWyhlnnAEgmt3t+/4CRx+43bt3A8BhMa8bYNhNREREREREREREREc4YwxGXnsVu/bugedFYarSGn7QCpkDo+EZnfkfxQsiCvfmawjd/km64jn+8o6KZp0KBAUMnLbwGELCSAvFiVfRN7oDfaM7kJvdBzRnXAsZ/6c1b1DtVqcys5yDfE9n0L0M7aGn1AqW3zbftVl5nrw28HpWZV4Lo2AF0XlRkF2EEALSbwDGRNXtQkI7uVab9fS90wp2owKvOAivNAiho9BWSwta2tE/losw3wvtFqDdAlS+N9OKHEZHYXdmX9kAPtOeHUj2nBwjRMcxi9L1d7dwOGyklRxlED1s4PUOQ1s2tLRQ718f/a3EZNCIOgnAwPKqsPx6cr0CyD5skZy0cIv59opyqUPYcev3Jivwov8KCBk/rJGVy+eRz7fNaaej1nGbB9BTnHssxIHoKTo4bvPAks9729vehs2bo7nx3/zmN1GpVBY4Y3HOPPNMDAxE+/n2t7+debAqrVwu4+abbwYAnHLKKSs6N7zpj//4jwEAMzMzuP7661d8/bTf/OY3SUX3aaeddlC/a7EYdhMRERERERERERHREW22Usb0zMy8xzTndMs4BpQQkHG4F8LMWd3dzm+r8BUwcKtTmfeM5SDI9cAvDMAvDCBwS1F1dBwFyqCBXHUCjl+FAKAtF17v8KLmWScfhUEye7lJ27k5jl6aRu9w5rWBgFuZyH4/0Ar5jYHQCmGhD42e4fgqoxbeVujB8ipREBoHrJbyYXnVqAI5aEAGDRghIYyGW51ErrIfTnUSQoUor9uK+uAG1Ac2oLJ2K1S+pzVvXIgo3J/rPsVV3dn32gMp0TlHuz20SnqrL40wqqOyvUtNfJcTo2pzLWRcVR+F7fX+9Wj0rc0+0KA1pG7NoBepb0L63WXMFC6v3YpG72pMvukMTG5+Gxql6GGGRt8a1PvXo967Bl7PKhjbiQJ6acFYDnQqrF+7fuOSv5eOXFIKbDtl7cIHLsO2U9ZCyqX/HUsp8Zd/+ZcAgF27duGTn/zknNXPWmvs2bNnUevmcjl8+tOfBgBs374dV199dccxxhh8/vOfx/j4OADg85///JL3vxiXXXZZEuj/xV/8xYIV7A899BB+9rOfZd779a9/jccff3ze83bv3o3LLrssef3JT35ymTteWZzZTURERERERERERERHtMmpqQWP0XHoKISAYyRUW3tyHxqOEZCp4FMIAWlEXDULaAB7Cz0YkBJuKhAtTO1GUOxvVUQLAZOqijW2i9ByovbgSiFXn81Enn5psDNwXUBHiAssL5CNq7bDfKsdrcqVUO9dg0J5HwwE/GI/rKAGpzaNoDiQHCeNjgq8gaTC3OtbgzBXQnHytag1OBCF3dKKK4wNDASE5cCtT8ehuYHQAWTqmrSbh3YOPLzviMY6+5x3nGMsG0h3noeBCH2YJexHqAC2VwWEROgWotb0Yp5gvmOBKOAWRmXe07abPaxbpXj0C8m+0T63HYjmesfrt8/rBgCvdxiv/N6HkyU7jrHs7nXqQkI6NjZv3oye3t75rpKOIlprSCmx7eS1eH5kCqPj1RVbe91wCdtOXn6I/rnPfQ533XUX7rvvPtxxxx047bTT8NnPfhZvf/vbUSwWMTo6il/+8pe46aabcOmll+Kqq65a1Lpf+tKXcPvtt+Oll17CVVddhaeffhpXXHEF1q9fj5dffhnXXHMNHnjgAQDAO9/5TnzmM59Z9jXMJ5fL4eabb8Z5552HSqWCd73rXfjIRz6CSy65BMceeyy01ti7dy8ee+wx3HHHHXj66afx1a9+Feeee26yxjPPPIMrrrgCv//7v4+LL74Yp59+OlavXg0gCrl/+tOf4vrrr8dM/GDZe97zHlx++eUH5XqWimE3ERERERERERERER3RwlAteIwtBII4mZNCQBiJQCsIIWBg4opvARcCIhUK5iCT1/vCGp4NZ7FvcBjnTu6HG4fLdtBA355nUV79ZqhcqXvtrhAIcj0wfh0lk91v+6zrxdBx0Jj+LtuvQuVLrTeaLda7taxGFHSXxkcgQw/1wY0ICq15uJU1x0G5ebiVySh0BZAv74PlV9EY2JhZQ2gFGbcYN0JAWw7K606MwlVjYDdmYakgCWaNkJl9i3iWdrJtdM7/XjHxKPT0S2idqZZWTgF2o5LsUdm5pbUxNwa2X0uq322vijBX6pjFvYiFFj5CiI6/A2E0tLDi2e8AtIpmwTcfxjAall9L7rkB4pby83yR6JzbPh+lNdzcynQaoCPD5OQkhoeHIaXABX+wBTf9YAc8f+F/Ny8k51q44A+2LKuqu0lKiX/913/FZZddhltvvRXPP/88vvCFLxzw3np7e3H//ffjwgsvxI4dO3Dbbbfhtttu6zju7LPPxp133gnLWuq/AxbvrLPOwgMPPIAPfehDeO2113DjjTfixhtvnPP4vr6+ru//4he/wC9+8Yt5v+vyyy/HtddeC7kCYzNWAsNuIiIiIiIiIiIiIjqi5XM5VKrZOazKaIyrBkJo9AgXPdJBPRUyCyHgQyd5oiskCsLOBN3N45rr7fSnAQDjuTzuWrsBZ3kaQ74HIy3Ue1YhyPXAmSegFEJkK3UTS6/IhrQQ5kpwvKh6UksLfiqsjlqEewBMxyzsJrcyDiuMZpwXp3bDa1TQ6F8HqUIYIVDv3wChFZBMhDbwi4PZ7wi9TJW5kU4mGJahBys1M9oAHaFp+z3RlrOsttvddBY5Z6ucTbdqaykRFPvh1GZgLBtBsX9J+xE6zMwFF83vWbLOIBvGwGnMxnuzUO9dA+UUknbn0Dpu7x79vrtVZFt+PftwgbQXnPW+nP3XajW4rrvwgXRUmJqaQqlUQqFQwFB/AR9491bccf/OAwq8c66F//CerRjqP/CHX4rFIm655ZakQvmhhx7C6OgolFJYu3YtTj/9dFx00UX46Ec/uqR1t2zZgqeeegrf+MY3cMstt2D79u2YnZ3F0NAQzjjjDHzsYx/DpZde+roEw2eddRZ27tyJb33rW7jrrrvwxBNPYHx8HFJKrF69GieffDLOPfdcfPCDH8SJJ56YOffDH/4wBgcH8ZOf/ASPP/449uzZg7GxMQRBgP7+fhx//PE4++yz8YlPfAJvfetbD/q1LIUwix1EQkRERERERERERER0GNBao1KpQCmFQqGAvZVp/GrkOVRMAAsSthCYUA2EqRC5Tzo4wR5AKLIhZPM/B2SuI+hO2xfW8KyfbZd+VmEdcqIVIkuj4SzwP7nr0MPg/pcy73mloWgWc1MzkG2GI8YAWkUBZnqPWiM/OwYZ+qgPrIdJtbgWoZ/Mcm4GnqatBXZ+ZhRBvgdGWrD8BoQOk/sRtRYPIVPX45UGodzWzHKhAshMkC2gnXxmj05tOqr6bh4jZKvCOCZDL9OOW1lupl36AdEaMg7ThQogQw9GWDDShpFW9CDAHL93oRVgdKYl/WLI0IPt1zPvBfneZVR2oxVeA5BBHUOvPoVcLfo7VJaD8ePemWlB33G6kJkHHYQKYfvZ9tLKyS9Yta2lveQHEDZv3oz+/v6FD6Sjws6dOyGEwJYtW2Db0X/HJ2fq+OFDI8tqab5uuIQL/mDLigTddHjZuXMnwjCEbdvYunXrAa/Hym4iIiIiIiIiIiIiOmz4KsSO6TF4OsSxvauQD6P2uI1GA1JKuK6LSqUCHc/M3h1U8WIwk5wfmjCq2G4zqwP8LpjC+9adgNHyNLzATz5zhTVv0A0AfpcZ2caYTNmtae+R3YUWFpS0YcUBsLIc+PlUO1mjUxXZcXCsVbSyVq25z0IAUkaV2KEHSAnLr8MIGVVGA1C2C0BErcy7hJmN/nXJzzLwkT4iai3euhYt7UzQDSAJx5Oty84q6a6zxdvF7c6TvSh/zj0vmZRRXqxDWKEX1agbBaM0Qrtn3gA3CqeXHlAb0XmOiB8KEFrBiLhlfm0KTr0MGI0wV0Kjb01nBX7qgYfhkcfgNMrJR+W1J8wbdEdf2FZF3/Y7i99d6JLQpUa+cw640RBaI/pvgoDfqEP39h42rY7p4AuCALt378YxxxwDABjqL+AjF56Ex58dw+PPjKFSCxZYAegpOth2ylpsO3ntAbUupzcOht1EREREREREREREdFj4ye7ncNerT6MWRkH0GbnV+IPi+swxjUaj9bMOM0E3AIRdgu6muglRz1vwJv3M+4uJUwpdqnInVAObRClu8B3VJmsAc0V7MvQxtP9FCBUCMpqpXB16U7YiOzXbWoaNuApaJPs0RiWBrYhnZDv1Wdh+NY7aBer966Gd9Lzk+cNGoQJYqu2e6Pa54vnOExfRONYImQ28je4ISbWQsFLHKDvfNVtdNikhlG5bziyv0noRjJTR30Hqmiy/DiHiam+tkKtMpCrvBfzS0Jyz1QEgPzuWCboNBGqDG+bfB7C4auz20LoLGfpR1X58fGn8ZRhpobYqCjWFVm0PNhjsH92L8swMthx3PORBnFVMhxffz/67REqBt5+6DttOXosXX5vGyJ4Z7JuoYWKmAaU0LEtiVX8ea1YVsWVDP47bPMCQm5aEYTcRERERERERERERHXIPj76I7730WPJ6QLo4u7BunjOAMZVtFW2MmSfqjrwysx/tTXH1ImZm9wsXDiSC+BtKwsJqYcNNAj4DAyCEgIhrvNsVpvdAqqiy1miFoNSfbS2udRSEx/sRaM1gbrYWRxx2xxeMXH0600rcLw22Bd0Lk2E2nFpMiB1tMFuRLbSOq91bV6+cPKTXmqeu7Ry0tGDF9yEKWmUSiis7h7CQqnRfIYuqMF8MoyFDP/49AdqyYexc65q1gtMod3xfOkt267NJ0A0AQaFvwd9Zrjyeea0te8H26tHDEW0PFlhOMqe9SYYN6Laq/TTbq0AGDQSFfii3iOLEK+iZeAUGgNQK1cFNc3ZGaNRrGN83hjXr5w/m6egnpcDWYwax9ZjBQ70VOsqwdwQRERERERERERERHVLaGPzgtd9l3jslN7Rga3Gvrfp4MYSQWNWXnSMcmDikjflGYX9Qg47fC4zGuG5grV2EBOBA4O3uEHplNmwUAGwYBBBQQBxeB1EbchVAC4Hq4EZUhzbB6xlGo3d162RjYIUNyHRQLiREM+gGojbRqe+Tym+bmQ0EuQXaWi9Gl/tuhY2O90xbi2wr9CCD7HHazsXt1BEF2fleaKcAZbvxPY+bv0sbWtoI3dKB77+L9r0KRC29RejD8qoQ7YF/N1rBblSi6zQqaoduZWd+236tM1jPzFlXHfcozC3imtt+JVKFi9pztqo+utc6VUFuN6rIVSZh+bXu54c+rKABAcCtz8Ct7Edx8jWEbjEJvt3qxLx7mJ6c/3MiogPBym4iIiIiIiIiIiIiOqRGa7MYb1Qy7/VJd46jW3LSAlJ5txAC0iBT3W2MQQidVG+bUAGmNbfYgkCvdJNgPTQaY2EdGgZK1TFk5TCjoingBWnjGKcPBSOQ6zKXGYgySUuHyDXKSUiohUBQ7EdjcGO0BwBBYSATgsrQawtJRXbechwMp8m2Cl0jrXlbYc9Fd6kQ1qm54kAUVKfbXYvQhwyDZH64jENRGTQQwkA5heSzMNcLZXlRMAwAQkA7eQito/ncyf5tGOvgxBbasgEvav0efZlGobYbVvywgLIc1IY2z3v/rKCetJgHAG27rZnaQPJQw3yEbm+nvjhe72r0TLyaescgV5lEY2D+7gdR2/job0kYDWE0jOVCI4Dl15Iqb7cyidCpIygNIvk7ExIy9BA6+bjy3kCGPqY3vw3ajfojCBUu2A4+DEMYYxZ8eIWIaDkYdhMRERERERERERHRIWW6tBEv6/lDQwBYaxXwalBOzi4JG5vtHjwXTAOIKsb9VBpeEDbW+BJGKPRIBzUdoiQdyFQIV9YBDAwsCPhGYW9YQ1HYyMfhtobEmvnaRxuNQnUKMh0U53oAmf6f40W22tcYiNTx0SGdjVk7osK22ya0jsLNLudmz8u2tna8ahRaxkFzVLVbQK48DksFCHI9CIqpanitYMVVxcYYQGvIwEv26NRnYSCSQBRCwHSZ+X0grcWFCiGMjqqUhYxmnWsNiLhyWdqtYF6FcOtTraBba9iNSia4bvSvm/9BAa0yrccBwLRX9puFg2wjZcc4cturIigOpA4y0e8xtZ9G7xr4hT649VkYADMbToVfGoja3Mu5f98i3jugAGMgVQADwNguZG0WysnDCBHtXQCOV0l+L8pyoZ1W038tBFRbFfpiHk6wbYdBNxEdNAy7iYiIiIiIiIiIiOiQWl/sw2CuiCmv1Ur5JX8G2/KtNt+eUWjoEP1WNNtYGwNLSBzr9OGlYBZ5YeGU3BBsIWELiee9KVSQDZCPdfpgCwkDA0dI9KcquoEouLUgsMYqQAgBbTTCtorUorRhzRPSWn49E3QbIaMK4LT24G8RISmAjpBU2w6Qai8uYGD5DahcMXWOSP4/AAitAKNh4jDYrUwgX5mAgUCQL0G5xSTQ9HqHYXnVjoBThq0HEUSy/2zyvlC1L9DZWhxGd4a38YMAQuuoQFlrOI0KrLgiXAsLYb4nuafGCCA9Q9sYOI2ZVtCNuIo+tV9l56C7hPFpiwnmO66n2zHSgnIKsINo3rwBEDr51gMIxsBulCFVgKDQ3wqThcDEsf8Og6/9Fspy0OhfC4Golb02VvZhira/L4GocjtX2Z88pOD1rEKY703ugjEawpjkOnXb360BFn6IYg4Dq1Yt6zwiosVg2E1EREREREREREREr6spr4aHRl/ASHkCrmVjW98GvMUdwoNx2L3WKuL80kY0dIi8tBEYhXFVhwGglUGfdJNW5WvtIorChoaBHYdx6+wiBIA9YRVDVh4GBpOqgY12KdPiXGaKqw186Kg1ekwDmaDbgYQUAhoC0nRWowOA1TaP2Uir6wzsjG6fG5NNtoXIVHIbAGGuB7ZfSyqOvdJQJujWQkbVwcZELbaNaoW2OmotnatMRsvDwG1UUC2kKriFhMr3dm63LfhtD7qBKFTvfodatGXDSs24jsLV1FlaxcF0RCoFp15Ovi+6B8XM/dO2k20Pr4KOimypsg9BdDyM0EW3IFvoMFvZLCS0sCCNSvannAKsOFyP9ltC6JbQMzECqULUBzciSN1zK2gkgbRTm0HoFqIKeSGg7Rwmjv13sOuzcGpTEFpDWw68dFU40FG5n5vdh8LsWPI6dAoI079XY+I2+al7YrXfE7Hw33EXhVIJw2vWLvk8IqLFYthNRERERERERERERK+bZ6b24p+e+Tn8OIBcZeVxkl/AsbIH5dwwnvUmcV5xAxxhwYeG0gFqJkyqmqsmhFIGPdKJwmigoxU5AAxbBay1o+DXwGCzkw1tJQCRSpPbo1ljOpurN8N0BQErVS09r8W06hYynomsm18OoX0YkYuqaY2JQl+tomBWCGjLhbEd1PvXozA7BmXnMqFpphJXCBjLhghaIa9A3L4c7SHnPC3am2sLAZEO3oWVfJ8RAkIrWEEdiH+GEFCWC6SCYRH6cKtTyfdraSMs9LX2HM+HTt/jaAZ664uNtDtaj7dXlIu2oDs+KntMW/jdlbQ6fkdWUI9/H9HvyPJqEPHfjUD0MIKxXWjbhe1VYSwnmVteGX4z7PpM5ncGANKrJ/sTMFHIng6uy/uQq04lrxulVUD77yx1vNAh8uV9mY/DQpcHGNpeL6ZKfU5GR/fDdnDMm4+HnKfNOhHRgWLYTURERERERERERESvi3oY4GvPPpQE3QDw1twq2JCAAd6aH8bJ7iDqRmE6rEFCYEC6sIVEUdgQQkAZA8AgTAWWVpfY2Uq3J++yF9F2jm4Pu7ue0/xBIICEbTTSMZ4G4FsO8qrV5ltqFc1MjkNYA8RVtNnqW2XnYAV1CEQBpdQKJtBQTgFCq6Q1ugx9aMuGcaP/ed9YDmoDGztDddFZidvRirtLdfpiK7IhJIyUcTCvoXpWwcShqwg82EEddlzlroUFOKkQ2hi4talMcB3mSpk22UKrjiBexhXPyTJdW6Vnr9l0qUY20oZI/46CemZm+VyUW4DlVaN23zpq3e7UZxHkeyHDIPodCQEYCSUlTLNiXFoIC30QKoTl1wBjoKWNoDSUWd9qlCFTM+bDXAnGbbVXd+ozmaBbSwt+2xrtnHo508Id6FbJ3uXvAO0Pe5iOivH2lvMi9OE2ZiGDqBpf2A7Ku0ro23wcZ3YT0UHDsJuIiIiIiIiIiIiIDhoTB21CCPxq7CVsFnmsyQ3AMxqjYQMn2r1wEYXPoTbYpTzs0R4AwIXEaqsAJw5BDUyctbWCMxtiwSCtPcrrdvRCAS8QVX/L+GwjBHxIqDjwNgBCAE6uhJxfiydlI5677LTmcgvZffaxtKCcImTQgBM/DCCMhuVXMzsWMJ2t0YUARHvw2+0qm7uKr8fJxdciYSAgjYLTqMBzC/PfCGlDW3M8TGA07Di0T77HzWf2awX1TABrgM6Z2YupiJ8rrE+F1trOxZXordbnQa4nDtujaeZBcQAy9KAWaDlvpJ1pHW8QPczg1KZhLBfKzkW3uFmBn9qn7VdhBV7yVuAWM0G89FsPBwDR70Q52d+Dmwq6ASDM9S7cWtx0qWzXGpmnNNr+LoCo2n2+uetOfQa9e55Def0JCIoDEKGPfHk8W3kfBph6aQf8agWrTz59/n0SES0Tw24iIiIiIiIiIiIiWnENr4HRffswPTMDYwzyrouhRg3vL25KjjHGZCqsbSGwxS4hryy8pGpYaxeToHsusmuou3QSyMzz7mjrbAwqxseAzCXhuhACAhJBfKYNAWm7qJWGUKxOQeWK0bzleEVjdPegO9mE7Mguu1/dIq65SxCshYTrlaNAWEiEbgGVVW9KgmYRBjDW3AFn6+vn/n4ZBpndGcTtxtOnd2sb3nHhc1Rk69a5MvTiIL35MESqcr55vhAIcr1wGrMAAGXnAWnBF4Bbm05ajUutILwqQiefabfeeYH/P3t/Hm1LVpZ5o785o1nt7k+b52RLdpAgTVKCRdGIoiSSih91tcQGqkS0FO91VOmtcf0shWJYjlJH1ahRCQ6Q+kDK/EAgbWjks5AhCQkJSJIgCWR7zsnM0+9+rzaaOef9I2I1sdba3cl9sn1/Y2zYK1bEjDlnxNpnZTzzeV4P64WYsJqJwc7m4vHmQrmXdAtCt9Xe0H3R26dTeG2C4gIBnMNLo8I+bgfx4KOCOYAftUgKYrwtuLSt9rD5QgjI53RofMokTJ/+HtoaZk5/l/bcUUxQnli7HaB17iTTR6+gNDW7bX8FQRB2i4jdgiAIgiAIgiAIgiAIgiAIwp7S6XR44NgxTC+u3Dlst4M/ItJu5sg+5JU5ZyNmdDFueWK0+AXEI2ei6EBod86ROIs3JEQHSuMBkTO50J2QYLHWMa/L/fN6SqGcxjA4Pg0rbPghoRuq6z3RfT2pc5NG2asCnTfVE3x7+242B0Oirxe1KTUHzlvjl3BeWHAXO3/7et3bMV4jezxOfbQetCITUN1Q7WmnfZwZCOeZI7tGqbOebbCWcnMJP+7QmT2MUyoTiCe4kW1QJlY6E5Tz921QoTsV5lObi+WuOM+bMSwEozR4W4jOzuENObZhQoy4s1nc/TATxP9hhzqAHml3EqZUIw0q+LmYrmxKef0sJqxm47ApXtzJ+1XCaR8TVvM49jy6fETIL2+c7/dXOUd19RTt+Uu3XATROndaxG5BEC4KInYLgiAIgiAIgiAIgiAIgiAIe8qps2cGQjeQhWTvjv26hB6tOc244G2dG9tvlFHXtoaC0L1mI2IsofOoKA9fabxc7FbQF7oBWi6lY1pc4tX659VKke093FmNYgdR3CP0XNC9cfaitjMh0svqd0ctKt1GX0SNqnMktbm+2OhQhahzZRJKzcXCNUgq09tHYF8IY226Qs1yyEXVqDkkZKsxsRulcF6QbQesXwaticlrV7dX0SbJ4shNQnv+6EShu98LP8QohVP5vDiLNkkmHqtsCYDzgi3buCCcHauVPir2ky9BGJ65Se73pDRFmDvUe20X6mb3asGjC9ehtXAZ9aUTeEmnX0+7tnScaPoAxg/759VpRFoKCq54N6H2u99tjo9nm3vJDtVIFwRB2Eu2z7gQBEEQBEEQBEEQBEEQBEEQhB2SJAmNZlEM0zspiD2CjyKeVG94BLeDattqKCxdAcPR6RGGOBelYwwNF+MVotU16Yho7aG2FdgvFKdULoZmPU39EnFtnrRcx+TR10HU7Avdxg9HhG7GanoH3UZBSLVeUBSW9xA7EgGuRp3N1uLHraHocUVSmcpEZpsWnO3OC7BemIvQuWu+XCeqzuGcozt1gO7UfpSJAYUXt/GiFjpuZyLwiEu+345SqH4N9Z6wq7esUX3BTLhP9KiQrRTWG3V7m2L/nSOqzWHzeUtKNTrzl40J3QoyEdwNxu/8kMbBazBBdSBsW0OpsVRwiivY0X0xGp+ubJotaNiCsD6zbbuCIAgXgji7BUEQBEEQBEEQBEEQBEEQhD0jNdsL1DshchZrDWFeQ9o5R8eleEr363gH6B2Lzho1URjvjoh0HnosGt2OHLcTgR2lMI6C31vZFJUmfadvJuT6fUFUJxFe3Oofb7WHKdUHgqlzhM2lEYf2zIigOu7E1aO1ni+SUI81BO2NTDXVXh6DbfGSLk572KBM0G1kEdjaw1mF8Qduam0NFgtDMd9OeyiT4EVtcC5bDOD5rF/6ff2obZ100c72hVs7JI5PxLmxuHV7MYRuAKWxnl8UuK0pRMwH7XXKG2eJq7OgNMYPScvTheuOs+AFdOaOEjSXiaYPFt8fSk9Q5JHsw3OgFNrEha6NO8xhYrGA4RroQFTfhx93snQAZwnaa5iwQlybxymNsil+1MKPWtmt4AfUDx7ZxaQJgiDsHBG7BUEQBEEQBEEQBEEQBEEQhD0jDAK0Utghx6hVCm/EpQpsGX181C9jUES5wNlxKSmO1Bmsc5SVh9a7E20V4/vvRMgO0HQZiKMpjtgZwi1qcHdtSuwM+/BQKovp1mnc74FVuiB04xxe3C46sINyYY68uD1W29kG5U37MKAoamqTjgmYY68vgLC1hrZpNoP5deu1GEQtbNRBqcyNDqDSBBNWs3kgrxE93IWekD00ZuuHBfexsil6KCY8c7ZvI330XN0FLnDsO5i3NKwSdDZQZGNPhxYweHGb6uqjKKDUWiUu10lrC2PXpn/f+CHd2cPFuHWlJhe0H+2qGr0PkrH+91z4Oo1AadKwmjnehz6/SXWWtdrcpnPgvICkOov1Q0rdBgee+2L0HtSDFwRBmISI3YIgCIIgCIIgCIIgCIIgCMKeUiuV6LZbE2ts912qwGht4WEUKn+Areg6RzrUUoKlqvbm8bavFMlQJzNB3eIPCYNTOqTsfErKw+JInCXYokpo7Awtlzl5lzBMW0V1SOiGPC56aOzaxHnl5gF2RLRVdkINcDe6zY2Jj2lYwUu7hb2UTfuisbIpfnudtDyF80fitHeITuNsDL3obOew5TomKOVuX5PVgNZFgb9w/UdrtJukIHRntciLczIaCT4a4b5TFBY3ek23EbK9qI1OuyTVuS33c15AUpnGi9qkpVph31JjaShaPM1d76P31uinaIfjG+l/XJtHWUNaqqGswe9sZPXQg1LWpknxOxuE7bXscKUxQZlePoHrnXt0rJuM3YRV5q9+NuXZ+Z31VxAE4QIQsVsQBEEQBEEQBEEQBEEQBEHYE4xJefjBB4m7nb5sOCaDDblUnbOZgrZFhLSHw0ywrU5yae8E5wbebQVUVUBJ+fhoHA7jXKFmN2R1u3vit0YVhPBJdIYE2gRH16bURvsxOma3vTXXThCivahVcHdnCwwcvZn3u03mHr6b7sxBbFjBao+ovm8w584RtNbQzqLba6SlvDb4qIDpbCa2K4VzEHbWCNtrKGtyQdtDOZOfX9GdPpiLqJuMF7YVpceEbG+CkL2DeRs/rx6aoRxrCwZ4v7OBl0ZEU/sn9y3pEnTWssrqrRXiyjRsUe/aeQFpdbxutd+Lre/tt50rPdtrfJNSWXR57wqYlFJrJXOUO0tSnqIze5juzMFsf2sJoo1BzW7nCOJ2P2IfIK7Ojtfw3uVCgo2NdabnROwWBOHiIWK3IAiCIAiCIAiCIAiCIAiCsCcsnjtHt9vZZq+BUNcTRrdCMflBtsHisbs6y8a5Qmy5Jheyh87mP8Zy1s45Uopu6530cpIYrNMYG1b6r60fYvwQL81qLzul0SbJXNpDIqmyBqcVylkWjn0FP+niL7bpzh6iue+qwuICnUYo57DaQzmH122gTEIQt8A5jB9iwhr9K2UtlfUzeEN1wJ32cEPdTyrTBaH7ghl1rU8qJ63UQLDNx76tIztuo9MIG1aBrF73sKjrRU3KzaX8BI6oNjcmZPvdZv/O9dKIIGqRVGd3PLQBo/XV48n7WNOvOq+cw+8288hxh/HLJNXp/nVVaczU0vEsppzsykVT+wvX3Us6xXkzSUHodpDFrW/R152Qpun2OwnPCJx1RA8uEx1fJTnXxKx0cIlFBRpvvkJwsE7pyjlKVy+gdlmi4mJx4sQJrrzySgA+8IEP8Ja3vOWJ7ZAwERG7BUEQBEEQBEEQBEEQBEEQhMeMc471leWL0rY/ITI8tZbQ27nYbUeEbshc2nuNmiCyJhO2DceIQ+bodUr3BUervaKT21mUSYhr85Qai5mjOqyglCZsrZGU61i/BL062TalunoSbQ1JqY62KaWN82wcuAYddzLhVGm0SQdObmcJW6vouJ2dEkjDWiFePWyvFITuTCguSg1peeoCZm4CShcE70lCthvZZ7Qvo3hxm7CzAYBxkAYVnF88phfjDRBETaz2SOoLgx2cwzNFUXqic30HJOUpvKSL9UOUSVFpBCaF3jisxUu7A2HaGoKoOYiLR5GW69lc5VTWz/SFboCkOlNcfOAceqT/oy56lJoQp74zlE3x4g44Rzi9R/eC8JQhDIsJFM462nedovX109jm+GIOl1jScy3Scy06/3QOXQ+pvfgI1RsvedKI3s90zpw5w3Oe8xzW1tYAeOUrX8nnP//5J7RPw4jYLQiCIAiCIAiCIAiCIAiCIDxmnLUYY7bfcfxIsDYXeV2xpjNgcTSxBVm6onwqO4p7zs/gxqPQNWqiML0XhEpngihggEhpDAov74NTGqdGxFGViZZ+twEuF4yHBExl08wJ7/l0Zw7id5toazMR3DmCzjpOeQTdBso50rCCThMaB6/NIq5RpKUqnh2IoMrZwlxnbQ6uofVDnD/kaHaOoNssdHs0dttx4cLvKNYLig7yESFbxx38pIvVHmgPq/1M8N8Cf6j/Xhph/GLtdKzpO+cHJxq/10Zj0JWd7GDWcQdtEpwXYPwSXtLtC9HGD+jMHC6KysNivnN4Sbew2MCPi47sNKwU5kWZlCAX8/v7lEZC9N12eQr5PiOJAWOjdo6gs0HSi2d3jlJziaCz3t/LNBZZaa8y9+wXofbovhCevARBwJEjR/qv0+U26397P8nZ5hZHFbHNmMbnj9O9b5GZm67FX6hejK4Ku+DXf/3X+0L3kxERuwVBEARBEARBEARBEARBEITHjNIaz/cxo7HFzqF6ccpegDYJXhKBs5noqz2Gw8xdvl/PpdxylngoFtxH7Uro3rS/F3icc25LkVw5xzwew4ZEqyAJ/dwxrTBBeWLMttM+SWUmczAP1wW3Fp3GfWezUwptUpSz/Whxv9tAu0yozubQww05w01YnuB6LgqXWSz20GlHa4Q7W4i6njh+AGu2rMO+U5znY22KtgbrBQV3sjIpft5fbQ3WWWxQ2ayp/jHDYn528Pb9HBOylcL6JZQzWa1ya9BJXBCqddKlunamP6dW+8S1uf51dUph/fK4e3rovlAmLQjdWDvWl+F67b2+bntvKzUm1lu/uLAAwOs2SfNo9qwXajBG55h79FuU18+xetnz6c4cotRcIuysj5zM0Tp9Agcs3PDPtuuZ8BTnyJEj+HlSQnx6g9WPfwcXXcgiKEjONFm+9VvM/csbCC+Z3stuCrvgk5/8JLfddhsHDhzg/PnzT3R3JnJhGRSCIAiCIAiCIAiCIAiCIAiCMIRSirn5kajnuE3QXiWImgRRk7C5TNBtok2CtiYXa4suUwVZHeq0S8tZmiP1r0tqbzxcE8o/b0vqLC2X4twmRztH4OzYg3cNeErRKdVIg3ImGqdxJgrniwF0EqGTCKwpummtJehu4KUx2hq0NYTdFtoN3O5+3OoL3ZA7sofacCjsSM3pUZQzE0TSkS1K40ZE+kmOZi8u1m3XSYQajcneCUphgzJpUBoT3vWIMAv6gmK31QTx2/ilbMFALjV7cTsTeYeIa3NEUweI6wtE0weIpg/0hWplEmrLjxQWDySV6cICBuOXtu3v6NwqZ7cVsp0XMOrb9juNkYZVwQHfi6s3+Rz33Pl+1EL3x6Cy8eVjrKydobJ+FoVj7pFvMnfiG/id9cxdr/2xz1f7zMOknfY2vReeyszNzVGpZAtO0uX2YxK6e7jIsPrx75Auy73zRNBsNvm1X/s1AP74j//4Ce7N5ojYLQiCIAiCIAiCIAiCIAiCIOwJ+w4cpFLNIpO9pJNHMOeMRCdvF3etTUrXjQsleo+ixy1uc9F6AsZZGi4hwdJ0KWaCw9nbIh5aAb5JCdtrlDfOUW4uUWos4sWtTNx3BlzuiB6OFo+aBTe1smbc7TtUnxnAeiM1c4dEys1wSo8JlHo0zlsp0nAQKewAE1QK4mpUncOU64M2ki5eGuHFbVSajInG26IUeMFY/5Udmf8d3BZOe1nk+RA6iQp90kkuoms/E76DCp3ZS8bnT23uyC61Votx8Nov1GeHCa75HTDpGo268Z32BrHi9BZ1uLF7xASV/lxYr4TzAqL6PtKwmtVBV1lF+7C5jN9aG+tL2Fpm7ZJns3LZC9k4dB1xZYaovp+ovq//kw477Z2ju3Ju12MWnjrMz88DWY3u9b+9/zEL3T1cZFj/zP04eyFLlITHwm//9m/z6KOP8oM/+IP8/M///BPdnU0RsVsQBEEQBEEQBEEQBEEQBEHYE7TncfmzrubgocNjItyYyKn0lgKsAkqjgiZgdyuWArGztOxAuFWAlztVd9paN3c+axQplnYueKf5j3WOcSlyuOOGSnMZPx0sADBhtSCaZvXKdeEYPeruHXEiT3ZkF1G47UVmpYvub+fwuo3MgZ7jR03QOhNDyeqKp+WpTDhVHmlYJa1MF9roCeYK8JPOprWtd4sbcUUra/px717cyVzzI/RqZfccysYLiOvzA0d2mlBunO8L1Q6IpvbvOpLd7xad1Bdaw3ysHrrWWD24Rg5F6odj17YzczhzjpM5ym1YIWyvFoV9pUhLU6RhFauzavJOaeLaPMpayhvnqKydptxYyuLvRz6r60efR3vhcrozB2nPHSGaOViYp14kfxpIveVnCjr/TLbvOrWrGt07ITnTpH3X6T1p60tf+hJvfetbue6665ieniYMQ44ePcrrX/963v3ud19Qbeo4jnnPe97DD/7gD7J//37CMOTQoUO87nWv48///M+xE/4t6/GWt7wFpRRXXHEFAGtra/zu7/4uN9xwA7VajdnZWV7xildw66237qgv6+vr/MEf/AEve9nL+n05fPgwN998Mx//+Md3vMjra1/7Gu9+97sJw5A/+ZM/2dExTxRSs1sQBEEQBEEQBEEQBEEQBEHYM7TWhHtks+pJ0T6ZWJoCsTOUGIhqbZsSO8OsV5rYRuwMyzavm2xjaiogULpQd3u0fvEkQqWp4qOUwjpLisMMidveNi340UjUuNJjNbRHRdGxiO0J/XSjDmNA2xTDwDmsnANnQWXtZ656H2VtXwgP22t4cTsX3BU6jdE2Qa+foTt9MBtjGoHSpOU6Ko1Jw1p+gixuPK4U6+pmNae37+9OUWmMchbrhXnktsJ6Pso5/KhJbflhvFzQTsIqnblL+osHlEkIW6v9e8pBoYY2QNDdyOYqxwST6pxfQL8npABok2C2attl16V3bzrI576G7mygnCWqz4/V7Ias1nnjwLMoNZezI5UGHGFnjW5tAXrnVSoTz4ec/1Nn7qW2erLf1saBq4sLGCb0cywBYIikVMdL2iilKC8c3Lwd4WmBs47W1/dGlB6l9fVTVG+8BKUvLN2j0+nwi7/4i3z4wx8ee+/UqVOcOnWKT3/60ywuLvKOd7xjx+2eOHGCm266iXvvvbew/dy5c3zmM5/hM5/5DO9973v5m7/5m777fTPuu+8+Xvva13LixInC9i9+8Yt88Ytf5M477+SWW27Z9PjPfe5z/PRP/zTLy8uF7WfPnuVTn/oUn/rUp3jd617HX/zFX1Cv1zdpBdI05Zd+6Zew1vIf/sN/4Lrrrtuy3080InYLgiAIgiAIgiAIgiAIgiAIe8qOnGPOZoJeQXRWOM/PBFHn8LTHfqfx830cDoPG5Md1bMo5k9VytThmdWks5rxhExSgULk7WzGrJwvjWxH0hGLnSEcc3B4KpRTO9WXJMSbFTY+zTVQ2mVhcEE+1h9UB2mYib1Z/uUo24kwsjauzmKCMl3RQgPWz2GqsxUu7BFETP85r4tpsdCpvT1tDde00SXlqUGNaqdyVXuzv+JjG50LlAu5u8KI25cYiXprNYVKqZ+7lMJM4VNKl1FwZCNlK0Zk9PCJkNwvx7yYojzm2+3PQ6/02dc43Iw1reEMCsDJJvtgg648jW+wwev8PTuyyaHuyY5yzA0FaecTVGZRJx4TuXu13hcNon7gyk4n1vXFaM+5SH3LIV9ZOF4Ru44e0Fi7bcqzKji9oGG3f+iWmD1yCXxaX99Od6MFlbHPzxQ+PBduMiR5cpnztvt0fay0/8RM/wWc/+1kArrnmGn71V3+VF7/4xVSrVc6cOcOXv/xlPvrRj+6q3WazyQ/90A9x7NgxAN7whjfwb/7Nv+GSSy7h+PHj3HLLLdx+++3ccccd3HzzzXzhC1/A8yYnPbTbbW6++WaWl5f5nd/5HX74h3+Yer3O3XffzTvf+U5OnjzJu9/9bm6++WZ+9Ed/dOz4L33pS9x0000kScLBgwf59V//dZ7//OdzySWXcPr0af7iL/6CP//zP+dv//ZvefOb38xtt9226bj++I//mH/6p3/i6quv5rd/+7d3NSdPBCJ2C4IgCIIgCIIgCIIgCIIgCHtKZXp2bNuoSKucRdkEl9eXttrLfu8L21CmWGtaofBxaGtJPI81G+VCNqzbGHDs0yW0y+tJA1XlM69LKKUwzqJROynvvCmThFqdt5gqhd60bnfxSDVhQYByBsdwrLlXmDcHxKUapc5GQciOq7PUlk6gnKU7fZC0Mo0yKUG3QRpWMmGarE6zMulAxNUaE1Yprw9qKSs2ETDHalaPj3JUyHbaz1+r3J6c1Y7ejVvai9tUV08OCdmazvTBYo3s5nJByM6E+SFByTl0GhXanbjYYDRpf4KzfvyYPCK+Jxpbg8IOHNlK01q4DOv5BJ0s3jypTG0tpDsLzuZuboVSXt+Nn53Sgj+0YMM5/G6zvxgAwJbq2GBkUcc2ceq1lUcLr7tTByYuuCj2deu3AUrzB5l79ou231F4yhMdX7247Z9YuyCx+5ZbbukL3T/5kz/Jhz/8YUql4ufjx37sx3jXu97FmTNndtzuO9/5zr7Q/Tu/8zu8613v6r9344038sY3vpGf//mf59Zbb+XLX/4y73vf+/i3//bfTmxrcXGROI658847ueGGGwrtvOpVr+J5z3se3W6X97znPWNid5Ik/NzP/RxJkvDa176W2267jWp1sLjkRS96Ea9//et5xStewdve9jb+8i//ks9+9rO85jWvGevHQw89xH/6T/8JgHe/+92Uy+PpEU82pGa3IAiCIAiCIAiCIAiCIAiCsKcE5Qr1fYPIYuOHJNVZTE/gcxblDF4aZ+KnoyB0Z+QC6QQ1TeNQ1rCgfK7VVa71ajxLVzhIQOAcHg4fRwnHVF+KBm8kvvxC2NKXrBSJmly523phcVebZqLm8DaTFusvK0VaqvXbS0t1bLlOVF/AKZ29DiuYsEJz/1V0awv9yGnn+UTVWZLS1FB7GucX+4Fz/ejvLRkR59VQXevej0qKgjJak5ZqpJWstndaqk+M3d6KUmNpRMieHhGy7Zgj246OkfH490nR4mZEHPai9sTa3/02TMrUuQepL5/oJxVU107jx+1soQLQmT6ICSs4LyCpzpCG1dxVb7aso279EjYoY/0Sxg+xeaS683zww8IceEmnKHRrDxtWNm17M/xusc7yTmqNj9ZOh9y57vlYP8B6AdNXXY+asJ/w9CM5t7e1usfav4Ba4NZa/uiP/giAo0eP8qEPfWhM6O6htebIkSM7ajeKIt7//vcDcMMNN0yMPldK8Z73vIeFhQWALSPIAd71rncVhO4eV199NW94wxsAuOOOO8be/8hHPsKJEycol8t86EMfKgjdw/zSL/0S3//93w/ABz/4wYn7/Mqv/AqdToef/umf5kd+5Ee27O+TBfnrIgiCIAiCIAiCIAiCIAiCIOw5B571bGoLB3BKY8JaJnxWpklKtYLQ6KdR5vI2KTqJ0GmcxzZn7w983gxFOSsC55hSfl+8DpQeizAH8MjE74tJwc2sFDEKOyJkDovWWb3o+awm9NA+irz+8dCxzgtIy9MYv9wXqm1QojNzkLQ8qLlqgxLx1IjjUalCTPVElBqvo52/tsrD9gRPZ4jL00TVeeLKDMYPMX6ADcvYsExaqmJLEwSWYcFU68mx3Zt1zab4SaewzUwQ68eE7FGBWqnBQoteV5JuYZ57919/m3N4aURl49ymonR17RR+0iHoNpk69yDljXN4aZRdU62xfoj1Ayprp6msnsLvNgnbK8w++k8sPHI3c4/cjRe1xhvW3mCelNraXe0cXlycI+vvPqYfGHPcB5317Q/SQ/cImUBuwwrOD3FegPMDHnnoQc6fOXVBfRKeWpiVzvY7Pab229vvNMI3v/lNTp7M4vl/6Zd+acta1bvhrrvuYm1tDYC3vOUtm8aTT09P81M/9VMAfPe7393UOa6U4k1vetOm57vxxhsBWFlZ6Z+3xyc+8QkAXvnKV7J///4t+/2KV7wCgDvvvHPsvQ996EP8/d//PdPT0/y3//bftmznyYTEmAuCIAiCIAiCIAiCIAiCIAh7jvY8Dl/3PE49fJz13oN5pXB9cTUTra1zKBx+7ky1ykMNCZqDGOyipLkbh7bnHIZN6iPvEo3C725Qaa+jnKNTmSapzEBe09s4y9ejRWpoXhTO9fvpcnd70F4jqUz3Hc7WV+g07ruXlTOopIMLKoNId8/HjEV/K3aUx75ZXeghouosCof1gqxWtElJKjOYXLxWaZy5kfN2lEnR2uuf3imFHervnrFJ1HsB7WG8EM8M6gT7nQZRfV+hv17S7QvvTmni2tygv9ZQWzqBl0a5I7mc18x2Wa1v8yjd6QMFV3qvPnZn6gCozBXtlKY5fxnOC1Amob50nJmz9w2NpSjMd2YPY0q1xzxHYy71C7wOnakD1NaGRWmVx95vLSXZoIyKO+Bc5qqfcP7lc2cplSvMzM1fUN+EpwYuGU9M2NP20923f/fdd/d/f/nLX75nfbnnnnv6v7/kJS/Zct+XvOQl/Mmf/En/uMOHD4/ts2/fvr4DfBLz84PPTqPRYHZ2tv/661//OgB/93d/t+N/G8+ePVt4vbS0xL//9/8egN///d+f2McnKyJ2C4IgCIIgCIIgCIIgCIIgCBeFZmOD9bWBO1SlCUG32XeqOgDPLwiANijtqD70btjN0co5dC6y2lyc779nDQtn76c05HidWT9LXKqxcvh6rBdwT7TCoumwCESx4bnBLNM6cxUnYZVuUMUfFj21h9O64EZWFM+7Gb260P3XSqEcfZFYKYVyNq8DPrL3UPtxfaE4xyMCeSH6PK9/XbhmOth7oZusRrXVPtqm/W1+p0FcKwpCcW2Wysb5vC8+nfkjRSF78TieiTFBGRNWiWszhZrZYXsVL6/prU2KMk3SUq0vRHtRa8z97pSmceja/IWD6YOF9yvrZwlGXNvFa6WJprZ2YO4INX4fKJOO7zdyTXXcyZzXuZBdWTtNbfmRvvu+O7Wf1aPP275mN2TO+VI1u4e3uA9WFs+L2P00RwX6ogreyt99YPXS0lL/970UcFdWVvq/HzhwYMt9Dx06NPG4YTaLHu+hh1I6jCku+jl//vyWx06i0ym68P/dv/t3LC0t8eIXv5hf/dVf3XV7TyQidguCIAiCIAiCIAiCIAiCIAh7ThxFPHriOMMh337ULArPvVjyHKfUBBfpYxdRJ4VQO+dInSPoCQjOEThbrP3pHNZBojIBcGbxWEHo7hFGLebOPcDpw9dxKh3UlD1julwSGEoqj5VWCjXBiasuJGVdKbAmc4U7i1Mezjl00kE7iwNMUAHt913jvXjtiW1t9XoYZws1tGFntZ0vDEdSrlNqr2WvlMaGFby4gxmqSZ1UZ9EmJWyt0Jk9XIjxLjVX+q5vL+niHNjZIcHLObyoQ1ydywRtZ0mqM0XH9SRReosxK5tSai2PjWUYE5Rxeg8kGqVx2s9qwPfo1YPPhWqVxug0ysakNH63SalxHucFdGYO4cdt5h75FgqHMwarPdYPXbczoXsIp9SWn9Zue0Jku/C0wpuvkJ67eNfZm99aEH6i2E3SyMWgJ37fdNNN/OEf/uGujz99+jT/63/9LwBe/epX89GPfnTL/c+fP89HPvIRAK688sptne0XGxG7BUEQBEEQBEEQBEEQBEEQhD1ndXkJZweirjIpekIt5WHGqy/vDW7kXM45Os5gcZnIrTz8UaE7RwO+s1iTUmmOCpgDSp0N4s46o57GgO3rVPcd2TkKB9ZsKah6cQcvbg9mLI/J7r/Ufha73YtChz1xX6uJ0eJu91XRncsE2c3G6GwualdJTIIftUhKdZz28OMWyqakpVr/+GhqH1F1Nns9XPNcKRoHrsZ6PjqNszjzoT6ErdWCcz2uzmPDQVz5heDFnYnzNDq+HTEkWgPoqIUNK/1tldVTVFceobnvyqx+tufj8hh264Uoa/CSLgpQURvjh4TNpey1SaiuPEq5sTiI0QfSymwhsn2v0NvVjxee8gQH6xdV7A4O7b7e9r59+/q/nzlzhuuvv35P+jIcK37u3DmuvfbaTfcdjgwfPm6vWFhY4PTp08RxzHOf+9xdHx/HgzIQOxHLv/e97/EzP/MzALz5zW9+wsVu+csiCIIgCIIgCIIgCIIgCIIg7DntVrO4YQfinnJ2Qp3mC7E9F49ORxyqCTYTuoHIWbo22fJhuQbCTnNbKX4qao9t27BJsT9KjQnizvMxfgkTVLIfv7Slq1anMf4WQjdkzuG9joMHcFqPXRFlkon7bt5IFoWuTVKIbx9Gp1nNbJQiqc7SndqHCUpZFLlfyt3KMX63id9poKPWxPHFU/uyaHztYcMKSW2u/54Xd9BDfbdKZ/s+VnbgiPaTLjouxgiPXsX6uQc4cN8XsoUPQNBZp7p+hsraGbCWsLXC9Nl7CeI2U4vH8LpNrF/uJwjoNELnQjdkn6+ws44e+iwqIOhsFPph/YALQ/XHMH5HwrREmD/tKV05t/1Oj6X9K2Z3fcyLXvSi/u9f+MIX9qwvw6LyV7/61S33/drXvjbxuL3ihS98IZDV7h4Wrp8piNgtCIIgCIIgCIIgCIIgCIIg7DlqtMax9sZl6zFhWxVFcefQcbcv9u2WrjOcSNtj9a/TEeHdY+uwdAWgtxeKK15IRXn4KAI0GkXXxPjWEOY/vjXj51I6cyT3Yt17v2+Cl3Q2fa/HxYiD77VTiC13DmWSyXWiN2vBpJmzGDLBO00ycVQpHAqXi/fGL2H8MqkXkpRnSGrzpOUp0vIULijjmQSVx6o7LxwXmbcR971RsdkP92RBQBpWMV5RME5KU4X7vzN1ADvkKHdKZzW0889JZfU0Cw9/g8rGOQ7edzuljfOUGpkj20861JdPMHXuwf5V9ZMOYbdR6L+Cscj88c8cY/Pmdxu7HnOhrd4Pqp/W4Hk+CwcObX2s8JSndPUCuh5uv+MFoOshpasXdn3c85//fC699FIA3v/+99NsNrc5YmfceOONzM7OAvBnf/ZnWDt5QVej0ejHgj/nOc/Z07rhPX78x38cgPX1dT7wgQ/s+vgrrrgC59y2Pz1e+cpX9rd98IMf3KthXDAidguCIAiCIAiCIAiCIAiCIAh7ztTMTHGD9griHtZkccpp5kJzKJJyHaf9TBR0Dp100XmctUrjyULdFvgo0gkFsS/EOx6XZzAjNZaj6hzrh69n5fIXsnrp97FUrlFRHmXtU9Ie3xfO8sLSXF9MV2wvrO+EHQnLO3HI73I+e/tbr5TXt85i4DXgxW10Ek1sU5k0qyWeRJAmlBvnqS8eY+r8g5TXz2TR216QXXvtZbHoXpCLpgq8AIbEe51GBRHXKj1B3N9+LGNC8E5TBEbGqNIRZ7tSdGYv6b/sTB+gcfg6WgtX4Mjum/bCZf0I9kzoz+WavAb39Nl7+8eXG4vMnvx2oVa6chY/Kop2dgdzMKm+elyeoltfoLlwOe2ZwyiTUFk9RWXlJNWVRwmaSzuLXZ+UJKAUYbnC5ddcR1jaA9e88KRGaUXtxZdsv+MFUHvxEdQOFh2NorXmt37rtwA4efIkv/ALv7Cp+9lay+nTp3fUbqlU4q1vfSsA99xzD+9617vG9nHO8fa3v52lpSUA3v72t++6/zvhzW9+c1/Q/83f/M1tHex33HEHt99++0XpyxOB1OwWBEEQBEEQBEEQBEEQBEEQ9pQkjthYXsxEwSEBLC3VUXYdbVJK7VW0TfGai8SVWaL6vkH9Zgc40697rAAvjUm93cUr+0oTTvB8qcwLPOgv4HCoTWRoB0QKVuYuYf/yIwC05o7SnR049Jz2mQe+X/t8LV7BV4qrvNqu+rtzFNsJs9rEWF3pv/aSbl7HOxMcg84606e+y9qlz8eUqrs8vcL45Swm2xqs0ll/0igTpnvCqHUE0QZeLyrcGsrNZbTNxHoHdGaPFGpmK5sWRN1Jtcb1iLjs9O6lDm2STEBPB6KXTuKxe3aUoL2Gspa4nkVye90mQdQiDSukpXpf4I3rCzSVotRYojN7BMjqiifl+kDY7g96tK67o9xYLI5x0r2vVEF49yc4/p3SmWNeaZRzKOdI/TLk9bMditZlR/vXQJmEyvrZoWukSCuzO4pm3wzrnAjdzwCstWitqd54hO69SyRn98ZBDRAcrlO98cJF9F/7tV/jk5/8JJ/97Gf5q7/6K573vOfxq7/6q7z4xS+mWq1y9uxZvvKVr/DhD3+YN73pTbzjHe/YUbu/+7u/y1/+5V9y7Ngx3vGOd/Dtb3+bf/2v/zWHDx/m+PHj3HLLLXz+858H4Ad+4Ad429vedsFj2IpSqcRHP/pRXvWqV9FsNnn1q1/Nv/pX/4o3vOENXHnllVhrOXPmDHfddRd/9Vd/xbe//W3+x//4H7zyla+8KP15vBGxWxCeIThraZ9ZJ+3GBLUSlYMzqD2I5BEEQRAEQRAEQRAEQRCEYay1PPzgfSRRlG/J4oyzeG5NUp0lHBI8lXOE7VU6M0MRx0qhRiJhJ4meO6FhEw4aQ2CTXOgLCXNxVuWR2f42wnEMpMqxMXMApxTTrbWC0D1MTftc7ddJsBft+Zv1Q7w0GtriCiKt1T4myIRuRea6njr3INbzaRy8FpRi/uG70SZh4cTX2Th0Ld3pg1vPrzX4cQcv6YJzmKBEGlaxYS6oOwd5pHjvddBdQw9F0IfdRv+6AySVGdLS0IIA58ZreI/2ybmCGN4f/y6pzMxRDfbRePiB/rbtRH+/s0GpvZp1C0tSqhNErey9uINOY+LafL/PcW2euDpXGIMNymPtTvDC4/K62z100h3bKwkroLN6714ao5IuDvIEBQXOgD+Id1cmJYxbfZe8QxHV5weLTICwtVJwvKel2u5d86P9jGPSJCEIL068tfDkYGVlhX379qG0YuZ117J867dw0YWVoBhGlTxmbrr2glzdPbTW/PVf/zVvfvOb+fjHP87999/Pb/zGbzzmvk1NTfG5z32Om266iXvvvZfbbruN2267bWy/l73sZXziE5/A88aTFfaKl770pXz+85/np37qp3j00Ue59dZbufXWWzfdf3p6+qL15fFGxG5BeAbQOrPG0t0nMNHgi6RfCTnw4isp75t6AnsmCIIgCIIgCIIgCIIgPN1orK30hW4FOGdBDT3gVwrPFCNknfYKgtskFGSO4VGHaV7fuacYekkXP2qibIrRHldoxVSU9P3dDkiCEp3yVNYXINhEK3VAiqKjBuJfY3o/6dR+tvKpHvbKnDPj4uSO2MZZDGDCCjqNM9HXWVTunO7FgCfVmWyenMM5S3XlUZSzeGnMzOnvAJkgnpSn0GlE/fxDJOWpvoBuvBBTqg36YQ2l5nJfuHaACecK0eKZCD1Am7ggdOPcWI3suDISdc8OIt7VBCHYGnYQsl2g1WrRAvyggp90SMMqabm++QHOEXbW+i+DbgMddwuOa+Vc3zE93N/tGPPpK0Vr7ih+3CEt1fCjFl7cJarOkZaz57k66dKeOdw/v0NlovTw+VRRAgq6jcK8mbBc+Nwpk2aLGYYwE8T5C0GMV09/VldXqdVqVCoV/IUqc//yBlY//p3HJHirksfcv7wBf2GX6RMTqFarfOxjH+Mf/uEf+MAHPsAdd9zB2bNnMcZw8OBBXvCCF/D617+en/mZn9lVu1dccQXf+ta3+NM//VM+9rGPcc8997CxscH8/DwvfOEL+dmf/Vne9KY3oUf/NlwEXvrSl/LAAw/wwQ9+kE9+8pPcfffdLC0tobVm//79PPvZz+aVr3wlb3zjG7nuuusuen8eL5RzEwpoCILwtCFabXHq9nsn18rxNUdffQNBTSJkBEEQBEEQBEEQBEEQhL3h1IljbKwu9187gJGY6craaUqtlcI+G4euLzpIrcGLO4Maw9bg/BLOz8XFXs1lZ3Mh3OF31vGHxDrrBZPjn4HYL9GpTFEaEWlH6aLoqqKUWnUQbiPLPpQ0eFawjdGk98yuJwTm7ujxWOtxlElzEbTddzo7IClP47SHl0ZYvwTOUl88ju3NW+7mTaqz2UtrCNtr/dE4FHF9vhANHjZXCk7yNKwMjh/q93CP/W6jcIyyKZWN84UxNOcvozvs6Hcuq8c9PEUwthDCi1oF4d36pWI9eNhVCoBKouy+2iKqW6cx1bVThW3GCwvz5JQmmt6/4/P2j7MWbZIsWh0wfikTzYfHPbwIwjmUSQrzZD1/y/4rkxY+c5AtNujF2kNWC72yfrawT7e+gCltsQhgB2itueTSy5ienXtM7QhPbh544AGUUlxxxRX4fva5SJfbrP/t/RcUaR4crjNz07V7InQLTy4eeOAB0jTF932uueaax9yeOLsF4SlMFEU01jdwzlGr16nWxv/orz94bqLQDeBSy8ax8yw879KL3VVBEARBEARBEARBEAThGcJEiXHErZyUpwjba7lr1KHjLl7cJq0Mxapqr+guHmlDOVuIW9ZpVBC6HVvXcg7SiNhWUdvUIp7kN9/ORRw7yynT5Uq/jt5MdO0J2wA933kuGDtns21bCLbO80nDCmD7Qq/faTB1/iHC7kbWT+3RnTrQj+d2StOZOVRYVBBErcI1M0G5OG/WoAuR6bkYO8J20rJTuhcc398WdtaLYne+X/+6OkcQtTBBuS/K+p0NvKSL9QLQXiZ0B6XiM9BduohdsL0ZaOIT1pHnrip32RcWWFiDl3RReXy78ctZfey8j71FC/3FBkpnjvnRMQzf+9aMLAhQ29bUHv6sbIbVWaB/YdFC3CmK3dbixW1MzwVvDbXF40TTB4qf3+F2reXkwyeYazY5fFSeRT+dSZKEU6dOcfnllwPgL1SZ/9nn077rNK2vn8I2421aAF0Pqb34CNUbL3lM0eXCMwcRuwXhKYi1ltMnT7G+uja09RzVWo1Lr7isv2oKoLO4sWVb270vCIIgCIIgCIIgCIIgCLuhNj3D+pCzWzmHTlr4URtlDcYLMKU6zX1XZpHUZCIbk+oCFyKZh34vCMUZXtweOXZrsVgBnkmzmsbbMBoznQClXLqdxGnToaQ9jpkWV3m1ccF7xAnt8rFkTnWHUhrHSPz7KM7htO7HWqs0pr50Ai93BwPEtblCrHYyWn/Zmr6buL9pRPjVI8JqxviWUZHUesW64k5p0lK1X+Pa9Y5J40z8dQ7lTH+uFeBHzaxOeNwhqc7gUP0FDdokWGux+fgLiyIuAs4Lsvs0H0uv9nhSqvdd88okmVido0yC323058UqryB0Z9Hu7eK8Db+/aWdGxrgDPdBpb+wa6TQqXm/tYcIqfv5ZciiSsDpYaGIN8w9/g6DbYOWKG0kqM9niivYapfYarX1XZDXANxHeV5eXmJqeof40qhUsjBPHRUFbaUXtn2XidfTgMtGJNZKzTcxKG5dalK/x5qsEh+qUrpildPWCiNzCrhCxWxCegpw7c3ZE6M5ot1o8euIRrrz6qsHG7b4YSa0UQRAEQRAEQRAEQRAEYQ+Znp1j6VyZuNvN6hy3VgqOaxOU80dS2XMpp73JQvdWTIgeV/ZC6sK6MQHQizuUG+fxoxZOadr1BZL6AnEuvgQOqrCp0L1uE87bCKUUKy6hnW5wjVenMlaTPKs9DQ6MwUsjdC56W6UzV/uWXS+K0JX1swWh23p+FmM+hAmLyZA7mTM3Qbj00ggbFms5a5P2hXQHpGEVL+mgbZrX+K7SLtWpL5/AS2PivP50qb1KXJnFekFWT1opQOPyGHsAhSNsr2GHFjAo2NYBvZcoZ4mqc/3a01ZpbFAunM8NL5xwLqsdP9TG6P7KpoUa2pBF7++aHej7TntYL+jfIw6FyRcZDPcpqs2j0xhtU7pT+7Fhpf9efekEpfYqAAvH/5HO1AG8JCINKihnqS8ewzlH2F1HmxQTVuhMH8zGnbO6sixi9zMUpRXla/dRvnbfE90V4WmGiN2C8BTDpIbV5ZVN32+3WnTabSrV7Itr9dAMjRNLm+5fPTSz530UBEEQBEEQBEEQBEEQnrkorbns6us4feI48dKpYg1t7RWEL2BQk/sx4rQHw+Jt7pIeFvKszqK/nRdk9aGTDn7UJq1ltYTD1gr1xeOFqO2ZqEm1sci5Q9cRaT1Z6HaZT9mi6AAHvTJ15WNxNJ2hpCc4XXvbrMNPuoW62yasbC3aThD7R+sx20kR7mMrBMb7pdOkIJI77WG1V6yRrb3B3DpHffEYftRi4+A1OD/EeQFOe0RT+wibK6DoR6039l1J2FrF5edQzuWC98zAda4UnonHu7v5jOwKlSaE3Q10EuG0zmtXlzefc2vQSbcvdDvGheuxc5hkXMj2i0K2sttHi09uXI24u4dqvW9BWplGt1bBWeLqTFGc76E9OrOH8eJOQeiGrA77+uFnZ6J5t4ENynRnDvU/T9Nn7mXm/AODA1pQWT1N4+DVRFNZLfMk3j7GWhAEYTeI2C0ITzE67TZumyieVrPVF7tnrj5E8+QKLh3/4uSVfKavPHBR+ikIgiAIgiAIgiAIgiA8cwmCkMuvuY6Tiw8z7B22fmmCQHgBEqZSmdY6tGlUNDdhBeuX+1HaaVAmqcz0z+9HTSob51BA7BxJqUZ9qSh0Azil8JIuc6snaSxcXuyttWgT9yPJldIc9EsoPRA19zPBeDs0BzqNCud02oNtFwBMeD44oX70KF4SjQvZykM702+jsnqS5oFn5QKmpbbyKF7UJqlMg9Ik1dlMjM8pb5wjbK8BMH32fjqzh+nMHcnb94mmD+BFrcEYtUdamcZLi6KnG10QsAO3sjbJ2IKG7fC7Tcr5dYfsvthOuNYmGbnXJjjKR7hQ17w2CVZvXUPcaQ+MHcTrK91fcLFlnXft5c7taEzo1kkXP2qDsxg/xPTi4fsHO9Yue8Hg9Uit9fL62b7rexiFY+rcg6SlOiasEITblw0QBEHYDSJ2C8JTjJ3UqlBDX2jCqTKH//m1LN59gqQxWEVbmqux/0VX4JcvIBZHEARBEARBEARBEARBEHaA6ba332ksSHx7tElQ1vSdwKWN81SXjhPXFzClOmlQIa4tZK0rhU7jgtANEDaXQWmsUgSdNUqN83Tr+zFhBWUNYXs1q9PsBdlxOiAYFlatRafdQd1twPmlwrO5HluNTpu0OBtb1enegqQyXXDRqzQGa/sOcofCan8w287lzmYfZ7JI9MraGfy4jZd02Th0HUG3QdBtABB21okr0wWhG6DUWByMxaabiLzbK9fK2YL4a/0QR29+HE77WK0xpSpO+yhns3PtQuxWNqW8cb5wPeLa/PYu+pExuZ2cbzMhe2SxQVb5feDqVzYFt03dbqWye9+k2X4qyxrIar+rrR3eWhcd285Rai7h55HxsEmywDZjrqyf2by7OMob52jtu4K5+YUt2xEEQdgtInYLwlOMSrWK5/uYNN10n/rUFBvnV2mvNVFKUd83w9EfuoFotYXpJPi1EqXZ6qbHC4IgCIIgCIIgCIIgCMJe4IVlTDwQYHU6HmGsrMV5W8cvD6PTGD9uZ1HSOJRJqS0dRwGl5jIm7tC95Ia+OGdKNdJSLXNf9zRXZ0mqs3SDXNQzaSYK5yKhTqPczdsTIRXd6QNFR/aY29fb2lXLZqL3iCN7J5bmfK9hob09ewnlxiLKOZzSNA9eg/FLhK1lALozB7Oa3c7hnMEzSVYjXGusKuF3NvDjbHFCELWYe/gbpNVBCUTl7FgNcKwdd2hPFFr7HuTsMO3hDe/rLCqJcaWBZOF3G5Qai/0a0936PuLZw4+pJnfQaRRd9EqPifeTGMsicG7bq2S1X7zozhK01oh695GzeGkXtMLZgetdkbmsbVDaWrRWGucFqDTGM1F+Ti87bhcEnfWi0O2H29eLH8XZwkKLSfhxm7mFfVKvWxCEPUfEbkF4iqG1Zv/B/Zw9NXml3MzUDKf+6SGSzuBL5trpJSozNY4+9yr0fP3x6qogCIIgCIIgCIIgCILwDKd2+DI2Hr6//9oEpYL+Z7W3u5rdzuEl3b7Q6KUx4cZ5ujOHMEEli7U2yUTBTw/Femd1sYfMIF7xUXnYXi+IommpVowWdw7ciIN5m3rJPbl3VDh12is6h00CbihW27mBe7m3TSlA505eQHmY8hTrh5/N9Nn7ac8dyZzsQFTfjzLJYLxKgdOoYUe50gRx0YWvxiuTT3T7OqULkelBd4NOr9+9fTx/4DrGgdJE1dJgTq0dcd2v9BcwQHbftBcue0xCN5BFzg+xM4f2+BiVScDf3H2t0pipxWP92HDIFhAoZ1GN80T1fYOa3kqDzmpw9/qjnEWP1cwevvaAc/jdBl5+HR1gy/Vt78PiBDiCbrOwKQ0vwCSlNFbpwmesh82vcXlqhoWjl+6+bUEQhG0QsVsQnoIs7NuHQrF47jxp7vDWWjM3P0/nzHpB6O7RWW9x7sGTHL7+8se7u4IgCIIgCIIgCIIgCMIzlJnLr6GzfJakuUFSqhPXF7L4bJMALqsLvRXOoWyaO2kVTinSsDKomWwM8YHpflR375hRdlUl3Bp0WnSpWm+8zvBYGxPOO0rsoDRSV9n6ITp31jrAhtURoTuvzdxrvi9466wXbiAUx/UFlq78Z30BFMD5IaY0KmC68f7bUaFySGTP8aI21PN9VdaHzvT+3GUcotMITJr9v+rFp2cOarVNtPbgtI7K6qlC/7pT+x+z0A3jEfHKGlQaj9WvHsV6Qb/2O9YQRi1Sk5JUZyb2q7byaN/xruwiaVjJYtrJHM569SRRfT8mv/+VNVmkuefn9bft5Ptp6Fx+1C5cZ+sF2G3GMdacNeO13S9wnqP6ApWhSPuoOkd7/ihpXvu75HuE62tMzcxeUPuCIAibIWK3IDxFmd+3wNzCPJ12G+cc5UqF7kab9da5TY/ZOL/G/qsuwQ+lTrcgCIIgCIIgCIIgCIJw8dF+wKEXvZz1Rx7k7EbuHFYqE+W2EYdVLpr2XeDKwwWlohvXm+AKf4yiqHLjQvCYIAiFWstZB7epH21S9p27H1Oeoj0/cLg6L8AEFp1EmKDSr0M+OEveBxzOOUAXHd6jNb61Blvsw9hMKzXmMjelKrRXsdrL5sBZLIp4aj9W++g0RiddwtZq5kgGkrBKd/bIlnO+26vhRS28EQe2CbaPGt8JSblG2Fnvv+7V/t5umYLzfIxzaBMTxG2UswRxC21T4upMYdGGTrp4SUSau7KVSUhLdZLKTJZiYNPszhm6zhPPv1XNbGezBQVD7FbohszZPnofTCo1kC2oGFqQYJLsvssXKZQaSwSdRr+t7tR+GgeuLvQ5Sg2PnjjO4aOXMbcgdbsFQdg7ROwWhKcwSimqtUH9lG6jvcXegHNEzQ7+vIjdgiAIgiAIgiAIgiAIwuOD9gPS+jymldCX1ZzJjMGbHWRtQeh25GLeHrh7t8NpbyyS2YtbJJWhWsO5O70nWDoyB/VW/ZtaPEYYtSBqodOY1txRXB63bv0S1gsYm5Ft3L2TGX9/rMa00rnwavvJ4p36frpT+7N6zc7ldaMHcepe3MWP232h23o+Nixv05fdM2lhQSHmfTNGFhook6JM0o8C10mXqfMP4ZTG+SWs9mjPHRlZXLBF837Qj2JPwwq4rLa7H7Uy17ezmYPdWuLabHYMENUWis5x7W8dnz5xEUhxf2XN9hHzO0F7WL80cK0DQWstE+bzefE7Dfxug+7MwaymeBrjJ12c0qRhFT9uU115BKWy+xhjaC5csWl/zp85xczcHFrvIm5dEARhC0TsFoSnEXrSStYL2EcQBEEQBEEQBEEQBEEQ9or19XXOnV8cOEOdm+ieHkabpPi+0sWo64tMGtYIowaQeaud9tFJlNUCt5Zy4zzKpKRhFRuWM5Fvi9rjOukSDDmKS60VutMHSIdri++m1vJWKIVVqjDfzhUjyVXPvZvPqfVHIrCVKtaLdhZvpKa3CfZe6Iaslvqoaz5sLZPU5gY7WZNFf+d9Viah1FwmqUxjwirKGsLWKjhL6hwmKFNfPJbH54N1lu7suNDtRW38uIVTiqQ0hWcSvKQLzmK1hwkrfSEb5whsip90+sePivImrG4bkX5hTFjQsJMFASaBXgkAIGivZ9dVZWkBOskWNOjFh2juvwptUkrtVQAq6+eIK9P9xQjKWfyoSWXj3KA3ShFPzeP8zc1WxhiajQ2mJc5cEIQ9QsRuQXgaMbV/hvMPndo0Aiooh5SnR+vzCIIgCIIgCIIgCIIgCMLFwVrL6dOnC9uUm+BKHWHU3bulE3YvcQ5lEkxYJTUJftrFBGWc9vDiFsoZdBKj81rJQdwmdQYTbv3MzY9aY2N2eieP53Pb9Ugft3PxOi/YdB9lUrxc9CVv3W5TO12nyVj/7Y76vwNGIrKd5xPVFyg3lwAwXkhamkancSbIW0PQbQIOk/c9bK5k0eLtNXSa5Asqsnso6DYIm8uAIylPZ8J90sWEVXQSAQ5lDZX1M/i5oO9QeLWoEE9ug3JhQYOXdNFuSGCe8Ew2nRS/vhe1xyekDyiTbnlv6DTGS6NMtA8qeHGbUmsl77oFR39Bgx93mDn9XeLqYIGBtilBt5E5/3vnBLy4UzjPTu5ra3YgzAuCIOwQEbsF4WmEHwYsXHqA5Ucm1+3ef9UlqMfrPwwEQRAEQRAEQRAEQRCEZzzNZhMzKmxtU6t7Esra7UVea1HO9AVKZVLC5hJJdTYTKnd0nlyIV4qkOkuadPFsJmwrMoHTi3Yv7rkJrm0vbmPCETF0dG4UOC7A8b3FPOkhoRvy/m/zzFBNuGYKt22t6+3w4jbV5Udpzx8tiKjt+Uuz+tidBtHMQdA+freZucmd7bu+/biNswa0JvVKmcgdt8EPMWGZbAItSvuYylQ2XrJI/GHneHXtVObgzklLtaLQrb0xF/hozeyJ7Fkagcs63rtOzmKCEBV3UYDxQ2xQytzu2hu/nkM1vrU1qKhJ0N7ov63I3P7DR/XqthcSBybcJ6MLUUYTACZRKu9NDXZBEAQQsVsQnnbsu/IwXuizenKRpJvFEZXqFfZdcYj6wswT3DtBEARBEARBEARBEAThmUSaphd0nNU+nomLG4fEbp10qZ9/iNa+KzKR1BrCzgY4R1KZwmmfUmMRbVN0Y4mkOkNaqm/vqh2tFz0xWrwo8U4SgkdJKtOkfogNKzg0OulkruLemJwbaxfUJud/DDg3YYzbm2PshNKIKo1xo2L9brCG2vLDaGuoL5+gO3WAqL7Qj6xvHryGoJ1FvzvtZUJ2EmHDMnFYAVQWZ67UQIh2Fj8OBtek9/9D/c/E/cG8enG7IHQDmBFHtpsQUb+T665MOr4YYltn/qT7YGh/azNHtxdgQjVwvJMtQMCmYwsYtEmLQjagRz5fk2qlZwL70D4TotKTUh3jLCYooU2KnzvplbWAw3oBplTNov6BSrVGpSrpo4Ig7B0idgvC05C5I/uZvWQfSTdGaYUfBnTOrXP2qw9iOgl+rcT0Ffuo7J9+orsqCIIgCIIgCIIgCIIgPI0plUrjG5UeF1yH37YpXtQELxMlHSpz6fZrUFumz96Pl0ZMn72P9vylGL88iK3ubODIYpchEwCD9hppqcakWse7ZqT/WU3nLQRM59BpTHvh8v4+Jij3xb/Nz3MREhontbnFtejv4gVY7aFzsdNqf/v+b0PYXkU5h9UBYPHbq0T1fYV9kvJU0R09Os9aF6RhL43HROjhETvGheuJTuQdLDJw2kPZ4mKOEW2YoLtB1EsVcA4v7WbO8s1i7ycJ6CPXTA1FpzvPx3gTZJ4xZ/f2wvxEQd/EGK86WJBhc4d43p71QtoLl/Xj3ZVJCFtr/fsEyOqet9dJynW8+hxHL79i274IgiDsBhG7BeFpilKKsFLCOcfiXSdoPrrcfy9abdE6ucLMNYdYeO7RJ7CXgiAIgiAIgiAIgiAIwtOZWq1GqVQiivLI50nO4mGcI2hvoJzFWYP1w0wYHBIfw+YK3lAkc23pYVr7rugLfIqsPnGRC3NJO8/H2iSPtFYok2DLdWxQxmoPrEFvIyTqNMpc6nn/rPaKQvFmru6LRCbSjtSa3kEd8KRcJ+w0st8rU9tHn5s0u45KgYNSa4Wgm7nv07CKsiZz25PNSXf64HibozHgW50zr7c+um28Y6NtjLeprCnElmuTYFy5cKzxQ3Scid0OSCvTWT3xqJUdk0QEJsFpn7g2n90H+X1rcBi/Mi7kb3cfOLezO2PkejqtYcSUbf0S2iQ4BcplbvaovpAtMFCKoLORzWdPBM/nsreYwClNUp0ufK6CbrMQD9+bG5TCj1pc9n03EoThTkYgCIKwY0TsFoSnOc1HlgtC9zDrD5ylcmCK6gGJNxcEQRAEQRAEQRAEQRAuDpdeeiknTpwgTRKUTbcU63TS7Tu0M9E6IS0XHadBt1F47bTegQvaoeyESOnRvbSPU72zZ3WSrV8aqpU86iz22NIXnbu6h7HeEyv2WS9E2Q4KsEpn9cx34iLXHnF1BqwhmxibHTeyiEBZg99t9t29vdrpOnckO0B7YUHojWtzYzWxd8/2QrCCsWuYluqUWoPnp7lnufA6DWvZIoHeQg3ncF6I8VI8E5OW6plw7xwoTdBex8uF93JzGb/bJKlM97VrL41xysPqndWS3w0KcM7iJTHKGqznY72Q1C/jPA8ceEkHpxTWz+qSp15IXJ8fXEtrsrGMuL2H59cE5cK1VzYt1IPvu+iHrvPJb3+dQ9c+l8r07B6PWhCEZzJ7XPBDEIQnGxvHFx/T+4IgCIIgCIIgCIIgCILwWCiXy1x99dVM12vbipF6xJm7EyFbWZMLsMPHeVilScMKaVDBKYXfaRC01wlbq/id9YGgV+iAzgS8nog7ev5dRosrZ8acrjtrY/vYaWy6o3jqMbTGBGWM0tigtMsxObQzeGmMZxJ0mhT74CxBZ6MQYx101vpCN+Ri/5AAapUeq5F9YYzN9NjYXN7H4ddpqUZcmem/bs9dSmf2CCZ336elGqZUzRdCeLieu1opTKlGXKrnEfnZtrQ8NRYJrq0ZTxbfUdLA+L3jHHhRC7+zjo47KJvid5sErRWC1ip+e53K2mnKjfOUWsuE7TVQ4PwAlEbl16g3Ww5IqjPFOuZJpzCbzhWF7t5nq4Atzqvz/DFnvkliTn/vm0St5g7GLgiCsDPE2S0IT3OSVrTl+2lz6/cFQRAEQRAEQRAEQRAE4bHi+z7Obl8behRl7ZgTN67NEXbWSUp1lLP4udM7ruSRyrnQ6rygX2vY7zYyp20udFq/MuZavRhM8horZ4sSZq8e8tjBm0eLqzTGj1s47WeO4t3W99Yezi/hxZ3MZUxeR3wrl3fuUi+Inr05zvGSqFAzW5m0H93db2bEwe20vzf1yZXCekHfUT2INVf92t7WC3MhOrsyTvs4z6c9fyluzQdrSGpzACSVadI0xvlhv33n+Whni4K5Xxpzt+uRWt4Tu7uD+0BZg067eW1whTIxlcZif1GI9YLcMd5LHrBZfHyvb5DVQR/qnx8Vo8atF+Yx/UP9TweLTqzyMKUKYf45c0plDv+RMTvtDWqWq80XqThrWT39MIeuuWGL2RGejlhnONX8Omda32Sle4yN+BTGxXgqZDo8wnz5Kg7XXsCR+ovR6uL/fd4JJ06c4MorrwTgAx/4AG95y1ue2A4JExGxWxCe5nglHxtv/uXKKwebvicIgiAIgiAIgiAIgiAIjyfWD3PBNBMTndIok2au1JykMsPqpc8vCHwF4W3UVZtGAwE0b7NQM/tiojROqYIArNM4czf3+t9zpmtvSCBUW4rOftxGkUVHB91M+GdYHNq2nnZC2F4r1l/2t3Z5j0bQu1xEHmZYJM2OGSkUvUm729YM79UVH63hPYL1S5lA7CzKJGhrMpcxHs4LB0K7y4LK+w5spenMHSnWk1cKF0y4T3bgprdeAHQKY3TW5MK4yvpokmJEfrbnoPZ8muDHrf6c6zSmtHGuIGT36msPzmPHosZHFxfoocUHTumBK30T0soUw75uE5Tzz5grbCevRe+lUVanfQtaq0tbvi88tQlH6rJbZ7lv9VPct/ppOunK2P7GRaxGx1iNjvHQ+t9T8ee5fu71XDv3Y+gdJSAIe8U73vEO3vnOd+5o33/4h3/gVa961cXt0A4RsVsQnuZMXbaPle+c3OL9hYveh8R0eXTlnzi38QCpjZgq7+fSueezUL/sop9bEARBEARBEARBEARBeHJQn56m1WxsvoOzBFETL+30KmYTTx0oCN3AuCi6jRjiJd3C61E38mNiRKRVaZQJmv0NCuOX8ZMh4dNZdNLNXNTO9UVk5wwOb6IrVpkUnMVpP3P1KoUtOB/VYIEAAFvEvzuXxVgPibZpWN1WSFajzvwdzOFonHdvLMNOYuUsXtLFjMZiD/VXJx2Utdk+WznylcKEVVwSEdhszrNFAQYTjCwGmOQ+3omwNurAdhPSB6qzWVS8X86udxqTlutDYrsbtDXadv5+b0FDD7+7UXTV+6ViHLz28czA9OSUxoTVSQPo/5aG1YmlBawfouMUq/3+tTK5a974Q0LmyLiTch3VTpnYaOEEFxC/LzwlCIKAI0eO9F9vRKe48+wtrHQf3HEbnXSFuxc/xCONL/PSQ29nunRk+4OEZzQidgvC05zpq/bTOrNKtNIae696aIba0fmLev4obXPXw7fRidf725abD7PcfJirD/xzLl940UU9vyAIgiAIgiAIgiAIgvDEY4yh3Rp/PjVMqbGEnw6E6aQ8nQnCj5ExkXaPCNpraJMQTe0HwO9sUGoukVRniWuDZ27ODzE4dBLl8dEqq3dtDcYP+qKzcg6nVUHMVWlM2NkYxFZrLxNzdfZo36Gwflhw+24VIQ1ZXXQ94ri2QbjJ3lsxLlhazy9EeFvPx+RuX8gisKP6Al4SoV3murbax+82MhF1ojge9/vrxe0sdnuS47p/gEJNCJB324j5O8VqD+V0XnPbFd3gvX16kfA5pjQiOm+zUECbpBg1rrzCog2rfZLyVH+MVntEtQUqa6f7C0VMUC4saBj0rYSOUqz2QHvZIoleskCvv0EFL+kWFiuklWl0axVG/P3ZLZ1v0x5xbQ6/20Q5ky8MGK+mXpmZ23L8wlOXI0eO4PvZ36elzv18/uTvk9j2BbW13H2Q//3I/8mrjv42+yrX7mU3hR3w7W9/e8v3e/HuTwZE7BaEpzna9zj8smtZf+g8jYeXMJ0Yv1Zi+sr9TF95ALVXq1g34aHzdxaE7mEePP9l9k9dRTWcvah9EARBEARBEARBEARBEJ44nHM8evwY7VZz0310EhWEboC0XN+b82tdiNPWJh6PzbZ2W2fzMH5ng+r6GSATqaPKDKXmEgoI22t4cYfOzKG+gGj9UnZKXCYg5vWklRuIslZp0INH9ipNKDVX+kKhg8zZPNRv502od71dhPmEetKTaouP7TMyj1m0eDFC3gTlLIYe14/ZTktV6ovH0NbQWrictDyFMgmlxlImtGqNcjZbKFCawo4Iw3oogl5Bv+1tejs+bmdzgbq3i82u+/B87eRZaV6besAuawuP3nsTXN7D8+yULnwWHJlzPJv3TGhPS3XQGhOW0VEru8eUzmqWjwjZaVjDi9u4oWQAL40wwdC9pTVJdQYdDRIJnPaI6vNZykBxQEXBG4UJKtm1HYrq90zcTx+YvUQSP5+OzM3NUalkCQ0b0Sk+f/I/X7DQ3SOxLT5/8j/zI5f9vji8H2ee+9znPtFd2DEidgvCMwDte8xdd5i56w4/ruc1NuHcxgNb7nNm7Xs868APPE49EgRBEARBEARBEARBEB5vWs3GlkI3gDcU8w2Zdub03jy+NkEmAPZQJsWL25i8VrFOInQaZfWN/Z05nMvNJZzSOCBsLeN1GyTV2cxl7SwqTcZcys4PB7WMrc32670HWVz0kOAZdBsFR2z2flGQd2Ox2zsQrSdEdes0xg7HiE8QYJ32cNb0ncNZ3fGRtrQmqUzhd5vYoITzAxwBjQNXE3QapOWp/li6M4cobZzvj1E51xdDh/sx7k7efozWCwcudwBnUSbF+KX8+PxczqJcb14UW8a/74QR8d/rNjD5mPvvOzeor75JnPmwC90EZVCKpDRF2N3I48uzBRO9qtkmd5En5Wn8qN3vgwKCbpOkMtXf5jyfqLZA0B2UFFDO4cUdTFDq37dO+5jKVFGcV3oQQT8c514Q6tPsmg6PSXsYVca3CQeuvJqqOLuflszPZ4kW1lnuPHsLid06zWOnJLbFV87ewg9f9vtSw1uYiNwVgiBcNBLTxbrxlaLDdNOt/0NHEARBEARBEARBEARBeGrTWJ+c+lekKGgqyBype4D1S5ieQGcN2hmC7gZe1AKTotMIRVbbW8ftYj3mCaioTRpWier7iev7ac9cQmv/lcT1BdLyFEllhnhq34QDB+Kfzut098icuEW3r86jv/ubRoXunQx+AtYvDUR3Mle36omw+bm9qI03OhdKY71gsBBhEye883yS6kxfgIVM6I+nFkb3HIu3HkONB5Irm+au8qEfa1FpnEXFp5lzPy3X+z9xdTYT2rWX9zvziO8m/n27+db5+Xv43Qazp7831IBD5YsFxhsvtt4T67NFBdm9G03tz2Lre3W/c3E+XyqQNeOHdKcP4IakH21TwvZ69nlyLq+Z7hPX5rHKw/ghxg+xWg/mc5hJyQF98VsxmpAwKTq9t284u4/p/Y+vIUt4/ND534T7Vj+1qxrdO2G5+yD3r356T9r60pe+xFvf+lauu+46pqenCcOQo0eP8vrXv553v/vdrK2t7brNOI55z3veww/+4A+yf/9+wjDk0KFDvO51r+PP//zPsVuU03jLW96CUoorrrgCgLW1NX73d3+XG264gVqtxuzsLK94xSu49dZbd9SX9fV1/uAP/oCXvexl/b4cPnyYm2++mY9//OO4bf6Neyoizm5BEPaE7A+kQw196Q68Cp4KMC7Z9LhKMP049E4QBEEQBEEQBEEQBEF4otjJg3Xrl4FGYZuXdPvu68eEUqTlKWzSJeys90XLsLtB6pUxYTkTOvPnW1sJnipNCJIuzssc4E4p0sr07tzAvfjvYsujO00QRScsCBiNxMYVtzk3iLEeEiiT8hRBZwOAtFTDeT7KpjjtZ6K/M9lURC3SoAw9gVV7Wdz6duxoPjIhe1jw1iZmdImD014Wx917rRQ4M5CqbVoQkZUjF65zJzOq6JqfNP/bCt0FWXwcawna66RDEez1pRN4JsbvNrMY8tzJ75wFN2EOCw5qhQmr2eKLfJspVWktXEapuTzUbwUuiyt3XoByBuuX6E7to9Rayeqnu2yhRCU6jZdGKGexyqM9fyk2HCxIoLcg5DEw5swfod3YwKQpni/S1NMV6wz37ZEoPcq9q5/i2rnXodUuSwfkdDodfvEXf5EPf/jDY++dOnWKU6dO8elPf5rFxUXe8Y537LjdEydOcNNNN3HvvfcWtp87d47PfOYzfOYzn+G9730vf/M3f9N3v2/Gfffdx2tf+1pOnDhR2P7FL36RL37xi9x5553ccsstmx7/uc99jp/+6Z9meXm5sP3s2bN86lOf4lOf+hSve93r+Iu/+Avq9b0pFfJkQP6iCILwmGhGK5xY+jqLjYewzjBdPshlCy/g4PQ1eNrn0My1nFr7zsRjFYrDs89+nHssCIIgCIIgCIIgCIIgPJ7U6nXWVpa33McEZYwX4OWiZlyZ2Ruhu4dSmTAdVrM61+SuWb+8K6Haj9sFEdr4pQuKvd72CKWx2s/Eyt6mNIHh8zmHNhFWZ/HjY+7kXl1wHM66zI2dv2eDMrHS6DTqz4dyDtK4ICwrlzl1CxLvY4n5HmlHJxEzZ+/FS7qkpRqrR7+vIPrqJOrfEwBW+7igNJg/Z9FjCQDF/lmv6JpXJilEjTvUNkJ3LrgPu99H8JIOCocXdzOR2iSEnSzRoLp6ko3D1w/i2vN+T4qTHx679cNsn35dcUdaniINqwTdRhZnDuikQ2XjXFYr3Vms0tigNHBYO4cycWFRQTS1f8eR/XuNtXa3Vc6FpxCnml+nk65clLY76Qqnml/n0qmX7PpYay0/8RM/wWc/+1kArrnmGn71V3+VF7/4xVSrVc6cOcOXv/xlPvrRj+6q3WazyQ/90A9x7NgxAN7whjfwb/7Nv+GSSy7h+PHj3HLLLdx+++3ccccd3HzzzXzhC1/A8yZ/AtrtNjfffDPLy8v8zu/8Dj/8wz9MvV7n7rvv5p3vfCcnT57k3e9+NzfffDM/+qM/Onb8l770JW666SaSJOHgwYP8+q//Os9//vO55JJLOH36NH/xF3/Bn//5n/O3f/u3vPnNb+a2227bcmw/8iM/wje/+U3W1taYnZ3lOc95Dq997Wv55V/+ZebmnlylCETsFgThgtnonOcbj/w1xsaDbd1z3HPq72jHa1y575/xrAM/wHrnLM1o/D9orjn4cnF2C4IgCIIgCIIgCIIgPM1Jks1T//ooRTR1gFJzEac8ksrM1vs7l7l7Xe703caZi01Rzg4J3SoTCydFNG/WRWvGhNVee7ulV2u537ZJx6LM01KtL5g6pYnr81nEuEnySOw0D6vuDuo4F6LQ7VA9bIszMXhhfx/nh1ilCrHTyk1wlO9U2+454wGUzmqjJ51M2NU+JqgUos8Xjn2Vfcf/sf96+bIXEk/vL8yJNxTlni1OKAq0yhZLKDqli/HwSg/qYwM66eJ1m6TV2X6b6G1c3fm95dCbOpe1yfqhncGPWtm1zCk3l7CLx2jNXzrot7NZ4kE/Ur13siy+XucCv/ECgjTGi9so57DaI6rPk9Ryoclayo3F4jxprxgl7kxB6Lba69dO32ucUv0a6P1tkNX6VgrP81B6jxZLCE9KzrS+edHbvxCx+5ZbbukL3T/5kz/Jhz/8YUqlUmGfH/uxH+Nd73oXZ86c2XG773znO/tC9+/8zu/wrne9q//ejTfeyBvf+EZ+/ud/nltvvZUvf/nLvO997+Pf/tt/O7GtxcVF4jjmzjvv5IYbbii086pXvYrnPe95dLtd3vOe94yJ3UmS8HM/93MkScJrX/tabrvtNqrVQdLEi170Il7/+tfzile8gre97W385V/+JZ/97Gd5zWtes+nYevPV69vtt9/O7bffzn/5L/+FD37wg/zET/zEjufpYiM1u4VnPNZa0jR9WtYpeKykabplLYkHzt9RELqHOb74NVqdNTwVcuMVb+Sag/+C6fJBquEsB6ev4cWXv5Gjc8/Lz7E39ZcEQRAEQRAEQRAEQRCEJxfnTp/i/JnTO9rXaY/u9CGi2mht5xGsQZkYbQ3KmW2jkzMBMRmpke3vSujutbOjbdugTULQHqpj7lw2DlMUbk2pSlKq44C4NovzApwfZm7yoWBtzyR4cWfsPGrkmZuatCBgtPsTpkDltZ6zms+biL1JRNDdIOysZz/NZUqtZfy4jZ90M/F1SOiuLx4rCN3GC1m+6vuLbabF5452OIqcTLgenjOnPKweLD7I6lsX48v9biNbsNAbx3aLJKAQLT7RjQ2FGuh+3EYnnX5fHFBdO8306e+h0hgvauFF7UzQ7s2/UmANYWuFsL2GH7Xwu01KrVX8qNUXr5PKNAyNMeysjy0IYKSPo5+PiYs89oxiFXandHbfej5oD+Pgge99l8b6+qYtCE9tVrrHLmr7qxfQvrWWP/qjPwLg6NGjfOhDHxoTuntorTly5MiO2o2iiPe///0A3HDDDROjz5VSvOc972FhIft3basIcoB3vetdBaG7x9VXX80b3vAGAO64446x9z/ykY9w4sQJyuUyH/rQhwpC9zC/9Eu/xPd/f/a39oMf/ODEfZ73vOfxH//jf+STn/wkd911F1/5ylf4sz/7M37kR34EyGqKv/GNb+Qzn/nMlmN5PBFnt/CMJY5jzp0/zdr6Ks45fN9nfm4fB/YfQutn9jqQ5ZVFFpfOE8fZF6WpqRkOHjhMtTL4A/no8rdZa2/+HyoOx7ePfYEalzI9PcuhA9dz2fwL+u8vLZ/nvpP3EMVdAKanZjl44BKqlT2MpxIEQRAEQRAEQRAEQRCeMJIkZnnx/O4P3OrZnLMomxYqKE8UrkePGVF1NxMtt8Jpb8yRrdMYG0wWTSah0pjZU/eg04j23FGiqf39Ws6eibHOZu7lfDxpZSqrAz3kFHaeDyP+E7eNOznbaYIwrxQMxZQrpVFJRLm1jLKGNKySlGp4JkHbFAdE9f2YodrUXtzBS7uDNkcc8E4p0pFI+tlHv1V4vXLFi7K62kPHDIu01vOxfmngVDcJQWcjqzdOz/UdAAqX3x9uQnx5r19eEmHCyq5FX6c9nAGFLdwHNihhrMnH4FBpzMbBa0jK0zjPx4tahO11wrxOen9Ohu71sLNeiK2H4r1mtY8NyoX3g26xzv1E8X7kuqstzE2PCeeyU2sPZ022OGBC8oGzlpMPH+dZ1z2bcBPBUXjqshGfuqjtr19A+9/85jc5efIkkIm9e1Wr+q677mJtbQ2At7zlLZvGk09PT/NTP/VT/Mmf/Anf/e53OXPmDIcPHx7bTynFm970pk3Pd+ONN/KRj3yElZWVfrR4j0984hMAvPKVr2T//v2btJDxile8gq997WvceeedY+/9xm/8xkTR/iUveQm/8Au/wHvf+15+5Vd+BWMMb33rW3nooYcol8tj+z/ePLMVPeEZS5LEPHTsPlbXVvqO7jRNOb94lhOPHHtGu7xPnznJqdOP9oVugEZjnYeO3U+73QLgkaVv8dC5r2zbliVzzK+vr/LgsfvoRtmX3lNnHuHUmYf7QjfARmONh47fS7vd3OMRCYIgCIIgCIIgCIIgCE8EjbW9d28qa4rm4504c8fsy5tsG30mOPpaqYKw7ZTOhOhdUF07jZdGKKC2epLa4vGieG7T8b7pcQFlVLxXmwnZeWuu99vIfk572Nwx7rRPbek4s6e/Q2X9LOXGIkG3QZB0+iJsWqoXhG6sRQ8L3YyLqUlYG7tG5cZS//f1w9ezcvmLBn1C4ZTXd0s7spruWZR4hh9ltdP77m+l+/eCy2PLRxc0DIvnXtxCJ10m3xtFxpIDJizGsF5IUpsjLddJy1MktXni+gLOz5zlftItHJeW6gUhWJmkH12+GZmYP7pxB4mZI/Og0y4qnZzWecEUIuxVJnjrzb2WzjlWlhf3tg/CkwLj9vjeGsG6HZTFGOHuu+/u//7yl798z/pyzz339H9/yUu2jlYffn/4uGH27dvXd4BPYn5+vv97o1Fc6PL1r38dgL/7u79DKbXlzx//8R8DcPbs2bFzDAvok/jlX/5lfvEXfxGA06dPb1v3+/FCxG7hGYV1hmZ8jtPnHiFJJ/9RbDTXWVo5RZS0xo+3liiOSNN0wpFPDoxNaMXLJGY8umg7oqjL0vLk1bbOWU6feZRmZ40Ti3cDatvvgh6VQb+M4cyZkzSaGywtn5u4v7WW02dP7rrfgiAIgiAIgiAIgiAIwpOPi1K6brvI8kkoPZ7WPdo3Z4vCobOoNIER4TYNq5k4DCSVqYlC9FaUm0uF15Nrfm/vNu7VhO47sm06NjcDIbuE88KCc3pwKtUXoitrp6munemf3XpBFps9RDJS69mPm4XeGj9k+KFhGlSw4fiCgF7tbesFnLv2FQVBtudSt34pf+2PLWroCcPaJFm986H3nOdnQvfo2gXtD+YLCKImXnf8GXDhGOiL59kGV0gW6LNFJP5wDe4eJqwUXo9Gtk9i0oKG3hwN+mfHFjSY/H7tn8ukVNbOXFAE/5b9K7zY/h7utNp7en7hyYGnwovavlYT/o5tw9LS4O/uJEf1hbKystL//cCBA1vue+jQoYnHDbNZ9HiP4URiY4r/hp0/v/sUlU5n9xoSZIJ3j9tvv/2C2thrJMZceEbgnOPe1U9w/+pnaKfLXJ/8RkGI7dFlka46z+q5u+Ec1Mv7uGL/C1moX8a582dYXlnC5HVg6vUpDh08Uoj2fiJJbcS9i5/hkfV/JLVdFJqD9efwnAOvpx5uHVsBmbP94UePT3zPYbEYGp1Vlo89hFMGhULh4Zj8Hy3K+ZTdvsK2RnODjebalv1otRvEcUQYSoSNIAiCIAiCIAiCIAjCU5lK9XEoV7cTwa7n+u2Jwc6hTYTRXiZWW4sftwGHCas47fVrfDuT4JyXicu5MJxUpsCkuxa6gbG63JPqjStniwLrBNKgDEE5F4ldPrZRwXXI66bU+PvDOEdt5dHCpqRUdGTH5SmcPxCygvYaftzuC7fWCzBhDb/bAlwW1V2emih8bhy8hoWHv0HjwNWFNvPOAmCCEjqNCkI2SuOczWPOsz39qIXD5bXMyYXycGyhgvN8kuoM1gsBhTJJf9HAxClhPCJfObODpQhFJgnZYzH6OxCHdRJl13no2Lg2SxA1+/2N6gtYHVDqrAFZ9LnTHgaFl3bQJkVbQ9jdQC2foDN9CBuOPyffPRdQu94TL+bTkenwCKvRxavbPRPurJ72443aZUmEvaYnft9000384R/+4UU913Oe85z+76dOXdzY+p0iYrfwjODr59/Pg2v/O3vhQDNeQ6DDGTr6TGFbs7vEPY9+lsOllxB1iqvvms0Gx9r386wrr6XyBAve1hm+8uj7WekM/hFxWM4272Glc4KXX/7/phZuHn9hjOHY8fv7MePDOByWpP9d2DH4khi4KQwRRhVXACmnmbbXodj9F34AczFW/QqCIAiCIAiCIAiCIAiPK7WpKUrlMlF3/JnTheKUh3KDZ0fKGpxJYaJDeoD1S1l8s7X9KHQVtzF+CW3Tfiy4F7dxOuhHTisAa8ZF0W3OtxlpqUoQDdzEQWcDN+tyh7cCZ3LhepvnaoX+qLGo6jGcKwiqfqdBWhm4tKfO3Y+XRsVjhtpMwypJbRChq0xKqbmMHXKLGz975mqCMn7SyV5vIgCtXvZCps49SDrB9T18/qQyjZcM3T9KgfIwfhlnYpzno6zFj7uYUr04L5PixoOBsOv0NmabIdd7dsB4DPzOGJ8DZZKCyG/8Ev7QnpnQ7uHlz0n7SQIjbZmwSndqH6XGEnF1lqQ6C0CkFX6n0Z8P54ek2qPUGjhKg26TNGwQ7YnYrRi30ltKzRW8uIsJSkT1hcL1mZ6Z24PzCk825stXXVSxe6581a6P2bdvYMo7c+YM119//Z70ZThW/Ny5c1x77bWb7jscGT583F6xsLDA6dOnieOY5z73uXve/jBPtLA/CVk6Izzt2YhP8eDaZwcbFEQUIx0sCR01Xp8AwHf1MaG7f5y1nDr7CI3uIqnZPGqmmzRpdJZITDT23kZ8mtXucVI7/t52OOdoRsscW76jIHQPE5smDyx/btPjO90O5xbPThS6ARxp4TuUZvAlsMQB6u5ZVO2l+G4a301TtZcyZ19EyMyuxwNZFEcYiKtbEARBEARBEARBEATh6cClV15FEO5NrK0jc+y63sMqa/CjJmFnffvaxUph/TJO6f6jLgX4aVSINB9UiR4//rEPwBFV54gqs3Rr83SrszT2X4UJK1g/xPoBNqhMjhvfpt2tmDrzvUL/54//I9XVQSnB2vLDzJz53lg7euh5Z1wpPusLuo2sZrZJssUADCLZ01INp/SWrmkTVnjkxf8HaWmC+3+4H0pjlUdp/Rz18w9SP/cApY3zpOU68dQ+kuoscX2eaPrABTntt8JNEqkvoB0TlAt3lCOLEh9scPhxp7+4wAE2KGNLtTwWHtJyHVMar30OENfmae67grg6EI9NWM32H+n7aK33yTH6u0enMWFjmcrKKSorp6guPcy+Y19l5vT3qC8dZ+bMvex76KuEea32cqXCzJyI3U9HDtde8KRr/0UvelH/9y984Qt71pdhUfmrX/3qlvt+7Wtfm3jcXvHCF74QyGp3x/HFrZv+3e9+t//7JZdcclHPtVNE7Bae9jyy8WVGv6CueHcVXsesgZr8pTB0W/+j22q1+MdjH+OOB/8v7jv7eYwdCOPN7jLfPPFpvvLAR7jr+F9z5/3/N/eeup3ERJxufoPPnPhNPn38/8P/8/D/l7956Jf51uL/jXU7czWfXb+PO4/9L7567FbuW/zslvs+sv41zqx/p7BtaXmRe++/hwce/B5LS5NraLvc1z2MTx3tQpQL8Cij0ITMUXdXULdXUnVH8djqP2C2/ko4P7sPz9vbL6aCIAiCIAiCIAiCIAjCE0MYlrj6+udQHk1GnFBbeCt6Tle0l4nD2sNLupmA5yxhawWdbOMgV2pM7IMdCpgT+qrSmKC9RtBeA5MMnL+jP/nxlbXT+Ek3ExiVpjt9iLg2VxQwR8XM7eYoTbYU4mdOfYeFE9/ovy41lth/7KsDh69zTJ29P5tHW4xY97stsAar9FjUeG9fReYQxg5dT+1l49pmZk2pztrR52ULFfIfZ13ReBN3mD7/AOXWMl4ao5wlrs2Pu7YfJ6fhtnesc2P3ofP8ftR75tCeyV67QZqAl0ZZRHu+SKC34MEGZeJSbfKigMI5gvE5Ga3hPuE4nezAgGUNOuniRW28qJ3Vsh+6L724Q3n9LH7cRjmLTiOqKyeLgj6gbcrM6e8xF2ouf9bVhfrDwtOHI/UXU/H33rkMUPHnOVJ/8a6Pe/7zn8+ll14KwPvf/36azeae9OfGG29kdnYWgD/7sz/D2vGyFACNRoOPfvSjQBYBvpd1w3v8+I//OADr6+t84AMf2PP2h3nve9/b//2Vr3zlRT3XTpG/JsLTnsR2xratqm+xogdf8kYF3WHUNh+TXu1qYxNOrn6bfzr5aZxztKI17j7xadbag2h06wxn1x/gy8ffzxdO/RfWoof778W2xXdX/oqvnHn3tmM6s/Y9vnP67+jEa3n/t/ma5RzfPP3XnFr7NgDnF89y+syjJMlkx/rIAMfGW+EomgkrTJXD0N2yPypb8znxvZQO5fouV64KgiAIgiAIgiAIgiAIT2ra7TaJtYMnRrl4ptNo54K30gNBU2mcDtCjjuwdCZ7b76OcyYVqC85mMdndBuWN85TXzlDaOE91+RHqi8eorJ+lvH4Wb5JoOBSD7XcbeV3wDKt0Hku9CT2hfIsxqTTGM1s833OWuUe+SRC3KG1kSZczp7+b///3UGmMH7UI4ixW3Uu6heuhcFTWzxWc7/3+D7nPtTWU2mvZ9eydWvukpSpWaaz2s5/RpQb5HA9XE3d+UIhPr62eLFznuDq7Z27k7VC7jSx3jvL6WaorJ/G7RTEtqcyQlOqYoNwXvgGwZhDTrhRoD+uPpF56xTnZcXdGne7aw6qsRj02i8sPOhsErVVK6+cobZxHR+3iPWBSvKSLtia7eip3g/fuS+cIm8uFT1XQ2Shcaas9ulP7ae67gta+y1Fr58bqqQtPH7TyuG7uxy5K29fPvR6tdm+U01rzW7/1WwCcPHmSX/iFX9jU/Wyt5fTp0ztqt1Qq8da3vhWAe+65h3e9611j+zjnePvb387SUpZq8Pa3v33X/d8Jb37zm/uC/m/+5m9u62C/4447uP322wvbvv3tb/Pggw9uedz73vc+3v/+9wNw6NAhfvInf/Ix9HrvELFbeNozX37W+EYFZ7y/45j3Z6yqb+JNqOHdI1XtTd8DMERYBn8Yl1rHeXDl8zxw7osYW/yDqVyA7+ospt/YVGB/uPHFggg+TBxHNBrrPHj+y4XtWzupQeGhUDyweDtpmnB+cXJk+/hxCtz4F2qPMhUunShqO2VIaWOINh3jQPBWGCJi1tlQ99NQD/Dw4rd21DdBEARBEARBEARBEAThyU8URTz88MMkaVb32jmHTuO+I1snne0jyAE3IvqqSemIO9AmrefjlMJ6mQDr+g7sTNh2PTesS1HOoGxK0F0n7DbQJkHnAqEft/sCX1KZHYuMHiXobBS6mVRmCgKmTuPd1YPO5xFnNxUOS83lvpC97/g/grUE3awfXtrlknv+ruDm1s7gx81Ce14aUV9+BG+ozjiACSq4XNJ0ZDWn3dB4HAqn/SxaPL92ajQYPBe6+y+1XxD3ddwpLBAASEv1bSbmAundA0MohrY5l9V23yKRwO82CKIWCiivn6W8dnawr1Kklal+Te0e2qR7FJaeiWrDQnYaVIgr00T1BaL6As5ZvDRC2xRtTbYgoTyFn3TRzmaR8WGlIGTrNCr0xnpB4Rp5caewGMF4QWFxhPFLNA9cTTR9AFOqYUo1Wlbz6N1fIW7vjbtWePLQczZfN/d65stX72nbC+WrufYxiOi/9mu/xmte8xoA/uqv/ornPe95/Pf//t/50pe+xN13381nPvMZfu/3fo/rr7+e973vfTtu93d/93e56qqsjvg73vEO/uW//Jd8+tOf5hvf+Aa33XYbr371q/nQhz4EwA/8wA/wtre97YLHsBWlUomPfvSjlEolms0mr371q/m5n/s5Pv7xj3PXXXfxj//4j3ziE5/g937v9/i+7/s+Xv7yl/Ptb3+70MZdd93F9ddfz2te8xr+63/9r3z2s5/lG9/4Bl/72tf40Ic+xI/+6I/yy7/8ywB4nsf73vc+arWt/+17vHh8lkAJwhPI0anvp7q4QDtdHnuvo09TcUeYcy/Ac2WMGo86ilmhwiVoJq8Y6qgz2Yo2LE11jA5nWVr6MofMD6PyY5TzqbnLCJghZpVEbUxsq8cjjTuZLV0+6EMccfLUIzRbDWLWib3il0ufOolrbBrFrslWC3bTDc6tPLxpnMYkFF5Wt3usTQ/rADWhLeWwLkVvIcJnoVGWVf0t2uokTmWrUBvx/QRnY5578GbUBaxYFARBEARBEARBEARBEJ48LC8vD55FKQ1KF1yfauh/d4PTHm7kSG1irOejbQqoMWEuO87PBFOlslrJkSmIc07rPO48bzONC2Ie1o7FfWeR3b0GHMqmxdhva/M+ZZiwhg0G5htlTV98dHkbw+1Ncncra4b6GGXtbeECr66d4pJ7/h/MkCO7vvwwpbuWiKb3ZQsQnENbi/IN6weuIa7OoZwl6DYKLmGddKmsn+nZ6bFeQGf2kn6Mdj9yfqg/akTYxo1XxHYjzwL1Vq713eAcypqBI9w5/M46plTL4r/za4Zz/Yj5fr+twam8/7nw7ejF06vCGMOhBQ39rdukDUx6mqtGLUb5Qoyt3N3KGpRJ+ue12gMvwPrZ9fa7DaprpwcOehRxdbbQv2SkJvjwPQbkEetDklIeWd7Dao/uzMHs3shpzx+d6MQ3Scy5++/h0he8dNMxCU89VlZW2LdvH1ppfuDQ2/nfj/yfJLa1/YHbEOgaLz30dvRj0Au01vz1X/81b37zm/n4xz/O/fffz2/8xm885r5NTU3xuc99jptuuol7772X2267jdtuu21sv5e97GV84hOfuKglXF/60pfy+c9/np/6qZ/i0Ucf5dZbb+XWW2/ddP/p6emxbcYY/v7v/56///u/3/S4hYUF/uf//J/cfPPNe9LvvUDEbuFpj6cCXnHk/8ftJ3+fjlktvFe3z+KgfRXQE3XtWGy5w+Ri7/gfoa46T0edAmBdfY9YLfcOoh+c4BRT7hp8enVZtv+SNuwIT9OUh47fPxQ5Pi4uaxcy5a6moR8cE7y1K+MxiL4xdly47uFwqKGvMA7LhvoeVS4rtNEbo0eIdTFuVPB2Cp8yCoWhg8UQUB853LCs76Klj48caji+9kUchu879H9s2ldBEARBEARBEARBEAThyU+j0ShucBcWX6ycyyXA7NmXQ2P6grFC2RSdRoS5E9WhSCrT/drHg4aGnMNpVBCyHYwJijqNR94fitwGujOHsEPCduaEdZieCcRl4d3WC9AmwaEwYaUvrqIUKq9trE2CuYCIbm0NJN0s/rpXB9k5TodlDgQlynFm8KmtPIpTiiSs5QKkQyUxpcZyf15as4c5e8NrBvPmHEllevDE0DnKG+cKEd9xZWakXrQaF3nHrvv2Lnbrjxtpgm6z6KJ3FmXSsZrig/cdYWsVZVPi2jzO8wnbq3hphJ92iSuzWO0PxmPSTHTPr0OWQGAK/Ve93o+mDZjNn7tuhvMCLAo8D4fKFj3gMH6IUx7gUNay5YKQEaHb5e0O96+8frbQggkqhXvdATYYef47dI2cUtnnreD6TgqLIJLKdFavvb5AELVIw2phUccocatJt7FOeWpm87EJTylWV1ep1WpUKhWmS0d41dHf5vMn//NjErwDXeNVR3+b6dKRx9y/arXKxz72Mf7hH/6BD3zgA9xxxx2cPXsWYwwHDx7kBS94Aa9//ev5mZ/5mV21e8UVV/Ctb32LP/3TP+VjH/sY99xzDxsbG8zPz/PCF76Qn/3Zn+VNb3rT41Kn/qUvfSkPPPAAH/zgB/nkJz/J3XffzdLSElpr9u/fz7Of/Wxe+cpX8sY3vpHrrruucOzrXvc6/uf//J/ceeed3H333Zw7d47l5WWcc8zPz/P85z+f1772tbzlLW+ZKJQ/kSjndlt4QhCemqQ24pHGl1nq3Eej0aYaP4uay2oYGLos668CoPDz2O/sJ3CzzLjr8y/TFoelw1m6+gypyv5IJzRY1XcXzrdgXkLILKFboO4GLm1Lwv3+LRNd5D3+xSX/nsPVF7LWPk1jvUNjrVs4fll/rSBqe65GyS0Qs05TP4jDkMn3JdTQmhatPH7g0rdx/HhRYO7R5iSRXsJ3dQxtmvoYU/ZaKhwm82L7KKfRhIVFAQ6DxZD9Z4afz2H2xafDGayK0C7EpwYojMqiy1f1N3Bq8pdAheL5h/5f1MODzFUuQ+2o5pIgCIIgCIIgCIIgCILwZOK+++4bMnFkgqAfF4UP6wXjovQIvSdhCnKhrTsQKJ3DS6O+8xYgDauYsLplm0F7ve8yz6K4wyzOmZ472afUXOnvY4IyyiSE7TUgE3m7s4cHTmxn8aMWoEjLuXs8d8d6UYvKxjmMXyKtZCKB8UNMUMaLu/1zWC8o1MMuMPx8zDm8PDK7h45aTC8eI2yt4LTPP4Uez1t8hOkkE+yNN+Rqz/vbi5QHsMrjxEv+VRZl3TulTQvCdm8cw7TmLyu4d51SRQcwFMTYXv/ViAButT/mAp4698AgytxZ/E6D1ctfmImo1lBfOo4yCc39z5ooePvdZn5NsgUQxg8J0k5hn6gym8Wt9/uvx93Io5HrMLYworJyEj8ZPMd1StPcdznaJCiXCdjKGvy4hc5F9aRUL9YpH4o93yk6Kd77VnuFuVBpzOzJbw/EcKWJq7N9Ibon3HenDxRd7SbFy53bxg+Ln1Fr+vXiw8YS2hrac0dwno9OY+ZOfANTqtKZ21qgPHDNDUwdOLzjsQpPbh544AGUUlxxxRX4fvYZ2ohOcefZW1jpbl0LehIL5at56aG374nQLTy5eOCBB0jTFN/3ueaaax5ze+LsFp4x+LrEVTM/yFUzP8h6ZZWHHx0IvpFa7i+Oc6SZk9t5eFQouSyGKBNvcxFcqb7QnR2/NHa+lj5BaF9A6GYL2zUBc/ZFLHlfHjsGoOYdoNtO+OKp92Ncwpx5IQFThePL7gBdNfhS6bvsi3vIDKGb21RIv2TmeUzV5piqL9NojkepV7iEFXUXqW72JoMyB+m9cCQ4lTnJh9YwovDw+s531Re6HQarsi9EVsXExGRrcC2p2thU6O6d7VtnP47Coxbu43kHf4J9tb2t8yEIgiAIgiAIgiAIgiBcXKamplhZWRlscI7pM/dmIqU1tOeOsnz5jaAnx3X3GH5H5eJh//VQxDT0hOvNHaU9V+pwnLoJq9krkzu5lQfaw2mdR1lncd1K6358eiG+nEwc7D0V02lccMqaUo24Mo2XDGKfvZ5rfPCYLYvutgbrl3Kh2eZx7COOQKVwXoDKBcfK6in2P/hldK+WuXP886EYagekIzHVo/WiW/uvKAjdvXaGmRgtPpZHPr4LShfd3b2491wUVyZh5sy9rF/ynIJQ25o7ytTiMbRJKDUW8dKYheP/yNql34cXtfpC+NT5B+hOHyKuLxTO4cUDYVvh8NMJz00vNBp5JGLe+CFhew3lDE5pjF+iunJysJBBezjP709XGpRxo27q7URua4suemuK977SBVFamZSgvT54H7JkgeFroTInvk6iwvXPSgVkxSjHFi8M3RdJdYawNUhUtX7I2mXfR3X5ka3HAnjh5mUwhacmSZJw6tQpLr88MwBOl47wmst+n/tXP829q5+ik65s0wJU/Hmun3s918792GOKLheeOYjYLTwjKduQcNkRz5N/gZhUd9pgXQSM/zGtuqMY26GtTvaWk47t01XnaKgHqPOssfcO2JeTqHXW9XcK2303xYJ9CQ+v3DXoxoSImrq7CutiYrU69l7VXUqLR/oic3/M7iAH/BcBEASTv0QoNAfMqzjvfZ5UNfvbRklp4jM1sW951Zre16AJ51CAZjehEq14ia+d/DP++eW/wmxZVnEJgiAIgiAIgiAIgiA8VVhYWGBtbQ1rLV7U4vKvf5xSKxM7rNKcvf7V44LfVvTqK/deUhTecA4/bhPX923aRFaL2PWFPKt0FpltDfS04lxQNEEFHTX79b+d8jFhFT9uj8VsF1zWuSPWDjmE4/o+vKiV1+f28v1irNaZOK804PC7TcqN833nrFWapDJDXJ0rCJ2983vdJvsfGhK6AWWLTmTrh0VR17mxaPG4sn2c9KjoCeDF3czJ3t9ppMa0NYTNFZLqdFaz3STMnrwHgPUjz8EpzfzD3yDsbBB2Nli5/IWk5cz8Y8MK7cPXstA4g7d6EgA/brPw0Ffozhzqi8N6RPTNOzJx2/igbLa4of/a9et8Z2P2oLA0Yryd0sY5qmun+6+t9nF+OJQcoEB7hWuSloplH7fDi9sok/aTAXoR7sM9yq7z4Cxe1EIphQkq+Eknr0mu8hh9W6iT7sdt4uGocqUwQQkvmbRAYKgUphcQ1ReyRSHaA2cxQZnGoevwu83+faptmrnQ8znxS2UqM/O7mgPhqUEcx4XXWmmun7+Za+dex6nm1znT+iar3WOsx6ewLkGrgJnwCHPlqzhcewFH6i9Gq4tX21p4+iFit/CMIooiOq02ze+cJVx2+OuQTjlcaYbm3Pj+TiVEapGy2z/23pS7hoo7Qks9TEM/NLFsSlMfY83dwwH7ssJ2heao+XH2mZeyrr9DolqU3YGsPXus0Fas1vFdfeR4jxl7AwkN2vpRjIrwXLbqThNQd1eRuiapaqNQlOwCU1zL2cVHSVWLlbV1NiNkhiPmZtrqJJFawhCN1+tWjtRt4DO9heDtSGlSWJra77/K3OpOjdUYLzL05d2lPLT8eW488rNb7C8IgiAIgiAIgiAIgiA8mSiVSlx++eWcOnWK/d/6VF/oBmgcvJp4anNRejJuRMQtZYJmrvN6SRedZu7o4WjqweFFEVPZdCBaaw+rvez9XAQ0YQVtisJNUp3Na20bnK8z4c85rM6zD13WRy/p4lxYEPPTXr3pXt+s7TtrIRMnS63lonDuLKX2KtoktKcPkWDxUaQ4NjzFwsrxQu3xzI09Is1OmIvRp3p+3BnbZ/TZXhpWcEr1FxhYpTPBtOdydhY/7uC0l4u5juraabw0xksjovoCU+ePEUSZ0Wb20X8iDauEnSyFMuysc+jezxPVFkhLVbykS21qCl2boXAVlB5zQU+y3fQWNBS3DZzKymZR3dYLBgsgnEPH7f5xqV/GhqNJAUOCctwuCN0OhurJ59s8r9hfa7eN7i9gDeX189mCgV4PrEEplU09+TUeibrvOfGTyjRe0umL2737Mw0q/QUU2qYE7VWSyszg/tQeJqwMRfVn19mhslrjvfY0aBPhJW0ya5kiLU+RVgaJpZYSBBWC7gaec+x/1rOldOUzDK08Lp16CZdOveSJ7orwNEPEbuEZgUkNpx59lMZGA4DyYpT5i1MIVyGkTiOcoVsbF4E76gxT7ho0418+fKq01SkS1UA5D6fM2D4r+uvssy9BT/i4lTmAtiWsilFOY1U6Jv521Gkq7hCK8S+kPnUMEYY2AdN9F3ZPTA5c9mUiZI6GeghHQufcEhV3cKytYRSamruMmrsMS1yIbB/aCesiPCZHQhm6dNQpFP64WA54hJTcPiK1ieTmKwABAABJREFUuGkvRoX0c817t+y3IAiCIAiCIAiCIAiC8OSjVqtx9SUHsOcf6m9zSrFx+NkX0Jrqx4g7pbOocS+ApJuJe0lWgzroNEhqs5u0kPdB+7jRutF+OXNl98RbpUgqM+ikiyKL28blgrcz0HtmqBTaWZQxQyJpiBt2yg6fvIcupiqOCt3DBFGTxMY8QrE04NHOeLnCsTZGUxaVKojWALWlYyw+66V9oVOZlLAnfioF1hJ0Gxi/jJd0AEV39pKCw71XP1oZi9/ZQFvTj2v30ojKyqOUGoPngX7S7ddAH52HUmsZANNcQl95w8h47FiMeBC1iOsLhO11XH7d0lIVlM4XNpjMdRxW+mP04k7mOM7vA+VMYU6s9iYI3SN9bRRLXFq/VFhokYZVnOf150GnETqeXIZyM4JuI4th7zYzhz9DiQZKZ/fxWNzzYGGIDcpEU/sJhu4VbVOCuJXVDdcapzy0SQibS5hSPY/cd1nqgNb9uuuWzHFPL7XAObzRuuFDc1xAa0xtlkuvvIry1PZJAoIgCDtBxG7hGcEjJ07QbmX1W8a+2OXMpM/BuO+QqOKXw5JdwJJmtbqHnMYOw7L6Ouv6HhSKI+kbWPS/SKTODw52ihnzXDQl+stL+8c7UlpYFYODEvuIGK/9bejSVI9Qc5cWBHNLSkM9QKoa4DQOi3JeUSx3ioBpumpxGwf15mhCPGcxdIrfkp0ioUlKi5D5gjBt6NJWj4KCNiexxEy76wrzZ4hJVZdJzu9M6B7/MjT6Hx+CIAiCIAiCIAiCIAjCUwO1sdQXwxzQXLhizP26s4ZUX7jsuXOtF2K1h07jvtBcaq1gwkqhbnaPnliOUlgvHDya6rmVgzI67hJEjf55dNqltnKyXyO6uXA5yf6r+m3qJMKPWgNxUXuYkRrZ2w4tjQd1vDeh3G1CuThv8eg8qsGCgB5eGmXznffHKU1cmaGUC83GL7FyxT8j6GzkQr6luvIInknQaUxU30cQNbMIdj/EKI3xgmKUu7OFiHntDH7u4O73w6ZjgeDb4hz+viPEx+7JXfdZJHjYWiHoNtAmwQRlHIr9D36p71A/d82/oHH4+k2bVSZFD/W3F18+jPG3jthXJsXL74ls/5C0NIXKI+Wt9jORubsBuTfd7zZR1mQR9v7OalbrnlBuDWFzmbg2FP+tFD3HerFzOvtc5FHnJqiQeiHaGUxYzdzdcZukMk1SGUTMV1dPEzSzhQYub8e5wbNa55cKwroySbFuOPnnahOsg8S6TSxUgiAIu0fEbuFpT7PRoNVq4pRDuWw1pq0ovI7DKUjrYENw9ZA5+0IS1onVGqAouQU8Kjgshm4u1mpW1TdZ1d/EqOyLTMVewgzXMp1eQ0s9nDuaA6bttYTMo/Fw/3/2/izmlixNz8Oeb62IPf7zmXOuysquruqBZHeLVJNiG2IbgmhJhgwbMGReiIZh3tmArmTAhmFRkAcJni58YckXli8MWLAgWRMptUSyKTZFNqua3V1z5Zx58sznn/cQw1qfL1bs2BGx4x/OqayqrOr1AH+esyNiRayIvf+zV653ve9HqLmjeApOcSxrAdoyxpAy0P2NaG/LCCczTvkBKTsYBhQck8mz2kmesIUhQUgY6g08OYIlZYuFPG6dz7GsKxJdF8sIwwCvBSGExgIJc/l+iHrXp6TsAgbPsn4uAGfmfUo541w/YKyvkuiUhDEF53gWCLYaiIU+Bj/3Zp1wgJvTzfrnkUgkEolEIpFIJBKJRCKRnwEmaxdnMd7FDacM5sdk25vlA69C7QD1DWesCMVol3RxXIu8op7J0X0W27dx4+21iCmCF9OOT/audq0C2OUZw9lh/TpZnrfi14vRNue3vrwWsqs64c3ZNpcOX0johk7t8QswqlgE1xA27996i7c/+279WgG1CbZRz1lUscUSV8WQZ1s3qvrNhsHsiKPX/xTlaIs0nwUBWH1dMzzNzrH5HDfcWovlNqnratfX6NQJ77sn3XAfg4oFbYjOIkGILiu38GQHc/SQ0fnztZiuvh3d3uH8xpuXCt3ARjy9F4NtiLbOppdHjXuPKbM6Il6BcrgdFhtU0eLFeLuqfT0OnxFX1v0enj1lsf/qpX2saTy3wfIMcQXF9ACt62sbxHnEL7BlXtfvFvWIlsGRLYZi+0Z9Twro9q3W53R0+rS1AMAng1YEviIbkfjGF63XG3HqPSwXC7Z3965375FIJHIFUeyO/Fwzm53z0acf4G1Vh6f6T37TYo9L8tsCtv3Fm7JLquvBt284sjWEtFQC9FrQneobQBBqt/QttvStel8zWpxKyDWkOFnXwFnFfFtGjPQuS3nYaL+KQlIKQsx6ybwVmb6q161SIGoYsl7ZF+pmr1EpKfU81Mx+AQTTiiMvWaASBjJeitqVHhzw4Zk6suA8B5wsOZf3QWFb30ZI6uWlq2dzFW8f/LdeqM+RSCQSiUQikUgkEolEIpEvBrJ3C159Bz57l3wc5t5GJ4+Y3Xjz2u7W9ckEn45CXe4VxlBMD7DZIjiHRZAqdtsPRnW2oIoBm6xFQu8wjShxUyxbQjeqGzHbs/3XWmKeuHJT1O2LcL4Cn6SomJZLtstZkvKonHMrCfOBM1/wt2WGu/UKf+npg0roTsMzWvWtapsUS2ZimO/dYVxFUBeTXZZbN8i31vOJtsyw3frdPTWyu9N52iNweptgXIFxOSohcl6BdHGKqMebJETAu1B2EtXgcG8I9Rw/xn3z0fpy3mP0YqEb4OSVr7deD0+fku2sF1aYMguO56rP3iSh5npeVq8tbjC5VLQ11QKJYrxLmp2HpIHV+y4G1IdIc4JoXA4mpI3P0uj8GWosy53bLTHbUmWENhZo5KMtxJUhqaBauIB6NBnViwMGy+ftBQDZrNX/YrLfFu8776kpc5Ki/b53Hdpqej4H3TUa11i0YW2UpiKRyOdH/Bcl8nNLnmd8+PF7eN8ZHAq4kcfdNdfRV3vZ1q/g3Jzn5huolFc36JCyjapScrbRh139RfCepTy+sH+WMajiyTaOWfCIMXdImF54/aU8BQ2O8BdxeF8HxUFD8N5A4JyPmejFqxa7zvPghp/hKS5sE4lEIpFIJBKJRCKRSCQS+WJj/tJfwf97/2YtBBvv2Pv0jzh+7Zfx6bi/Uacuc43Iumbw6vz5Ajccr6PEbYpPR41ZJmnXEVbdEJZDbeQ1tlhuHLPhaO6L5b6G4Ldxb2LIxzt1tHiXwiT8v/PHzCj5uu7zht3im8unLLTkP3j1SzwcTfgXHn3K1iqOPRmATeo64iqG//iVN/lzPmHs1qKoG0z6OnfFazCuxJkEU+aotSHuvcgYzI8Q9bhkxOD8GdvPP6rdxi4d1Y5xCKJy8z0RV7aFbl0nQtbHdIVu7zdqnzdjvnc/+w7D08c82flL1TWKED0ua0e2S0egWicD+ORqZ/7qc+EGE4rRNqbIGjtNZbxaf3aK8S5eLIP5cb34Ynz6uK6RjSrGFex+5Zc5Pp9RnB8jKM6klKOtWqwP0eL7rf4N5kebTvfGft+NnGfTZW/KjA06z6AvfUCNhcbnyagLC1EuWfBxfnbKZGuL0fiC3/tIJBJ5AaLYHfm55dnh002he8UL6LvSV+8E2NNfZdv9IjP5MLiUL0DxvbHcA3ZImZLpETlHtTgtWPb0Vyj1bXJ5TsF5ywW+6lPCFGWM8QkJE+pBn3gWPMToAMsYIakE6OYJlKU8QfSQod4gZev6D6TCMkI0rd3d7XsOQUqWCanubNRBVymZ8QljXrkwstzj8SzwODwZiW7x/sM/wO1O2JrssD3de+E+RyKRSCQSiUQikUgkEolEfnrIrdcx/6P/Fcnv/vu4LAhraTbj5vv/kOdv/QbW5eA9Ph3iTUKSL+rY6mK8c6kAKR1Xaohxbtdb1o4giurGNOGG4NfjspaOqOiN3aiRbcoc16pnvXbpQqjxPT66T7Zzh3K0npvLpzcwriTt1Lp2NuVvj1JmLtzjd/Mj3ueEjHX//sGNO/zlpw+hbMzXiUETU89u/pnTI4bTm+376bnHOlpcJDwn70gWpwzPnyPqKYZbTIoFk5MHJPkCL4bF3qut92d49rRzH9ISulf1oJsY155rFF/SdR83nyPeIapVCcnGecoMNxhjypxb7/19yuHaGGTL4CJX9SBBpEeq8pc2xboiiPDXRYTlzl3SxUkQg6tzIZYkW+BdSZLPUWMphtMg+FfCuEfAJHWtdhXh2WefgDG1IO6Gk/ZzWp2/ca/d59bFXxbHXtEXMR9q1jcXiPjwszpWNSwcqKLLw8KB8cb72uX87JT57Jw3336H8aRvsUUkEolcnyh2R35uOT8/+5zOJHhyDJtxSpYB2/o2iF4oaoO/pEa2IZdnlMwY6k0so3pPwoREJzhyTvleK7a87platvTLGAYseNg6xkuOJw9CfXe0XaFVJHv4e38fV0J/d58gDPVmK3K9vd9iGbLjf5Hn9vd7DlBKnV0Yp+7JKZmDwg39c+zoLyCZ4eGTjwEYj6a8/cYvMUiHve0jkUgkEolEIpFIJBKJRCJfPGT/DsWf/ed5/smHlKMtxDsmzz9levhpLeCV6Rg/WDs+XTIMseWXYItl6/Uqyrtz9c7rHve1GGgYR7oxzgCj08cUjRrkGItPBrVgGSKwG45V1YZobgBlcnQf40vGx5+RT2+QTQ+CO1mE5e5d8iIjyc4RVVw6Yj7a5h+ffr/Vj6bQvWJ8SR1rgJF33E8Tvp7lIXZclSSbVfWmp4AgLker90BtCr7k5vu/z/j08fox+bLlaC8b9bwhCLBNoTsI25su4Wb0ebKctfabIkPU1Y5kcQW2zHCrRQyVCN838bn9+D0Ov/QbbD39AOMKBvNjps8+ZnbzTaR2juuGu94NJkg2q4Xmy3AmCS5mMaBKOZgwOf6MdHkO6nHJkIFN6+ekwBipxeoQOT9oXz8dtVzq3qZBjG8/ufZzKnOupDdpoD1p7AZjvBhM9VlVwjOn+l1SwKejsBCCsFBkfPKQwfyYMh2Rbx3g0/GVv6v1vXnPk4cPePPtr1zr+EgkErmIy5fXRCI/w8gVMTPXQXGcy/sUnKGUnX0atoleOfJRiqre9xpPzrm8Tynn9bW6x6wE6Km+hdG2qGs0ZapvBoc1hhG3Ed1ccZjqhJHeQzTZaD/RVzAkeEpyjvGde/Q4Sma9IrinxGBJdAu0K4QnWMKKvBF32fW/hGh79aDRAVTnbzrnFcWxDBHvwJ7+KXb1FzcWEiyWM977+NvodSKhIpFIJBKJRCKRSCQSiUQiXwgeP/iMh0+fU453QAxJNguO7mouT8VsiGXl8Grn58oB3thydWd65g/LTqS32mQtrgLFaJvzG29sthtO8CZBq2PouGGl6pGoJ52fYKr+CjCYPd/ork+H5Fs3yLZvUo62MChFj7jd5dNRT2lD7xFXIGXOqbE8ufEmz770Z3n6zl/k6dt/nsO3fp1s5w5uuIUbTikn+7jxTl3feffhD1pCd7if5nweLXc6QJK1hesQGy6N14tQM7vxOlmerUVZ9ZhyGSLKK1aibu2sr59rczFBYPfBdxjMDrENt//d7/6XjI8f1M861Ah30PzsiFCOtq4UukOnE3w6wicDRD07j99lUNUiDx02nYj7tiO7WzM7pBF0a2Rf7Vfsc2RvdLVYbgje0kxFrSL988levcnbFLVJ+N1SxSeD0D9jQAwmX9T17JNiyej4Ye/ikMuYnZ9RFrF0ZSQS+dGIzu7Izy0727ssFvOXbj/jE07M9xiyz5ADHHNQg2CrH2kMQs2FcdwrlJJVMNKc++RyGIRyYMA+hrRxzGrtYNifMGZH36HUGY4cQ0rCtCVCG1JG3CHTp6isrmRI2MYyItE3cLpAKRFSEhqrY1mgUpJziGiKwaI4PAUD9jr34XHM8VLiKUiYYhnjNQ9x6aIIq3o3YUHAVN9goq+y5BmlnJPLEYKl4AjIccwr57xUgnsYaImaUMP8ApbZnPc//Q6T8ZQbu3cZDmKNl0gkEolEIpFIJBKJRCKRLyrL5YLnT5+sN6gyOD9sHeOTwYYAqNeIYN6gW9cZqvjlpllEWt5WcQWoR0VCHHUlDmZbNxidPQWUw9f/NJr09EcMxXi7qlXcmCfsMWrYsu1CD6Ln5XOLAtwwI5775aXH/e6N23xlflZf25R5XeNaEW699meYbt1by+Y2wdlLZALv2Hr6YWuTcSWYdrR4U5RdOcbr/cWSJF+EutQi4B02XwQXc0WyDG5qcQWaDEK/oRKjPYjUjmPxJWpMq360uBK1Sf0crSt49Y/+U84P1gsTbJnx+h/8hzx+5y+gyYBkeYZLx+STfYaP32N88hhUmR28zukrF89Jri+6fgbTZx/VCxigEqkb72mvr/qiWvQviEtH6OKk/hwrQai2VX+UUAZg41IoeIeKQdSHFIHRFksRksUZ2PC7IupRl+ObtepFGCzbpSsxNrwHL9p/50jSl/gdj3zhMNW/fc45VPVzMSRGfv5QVZwL30vWvkDJiEuIYnfk55aDg5s8e/YE1xfdo5Vr+pJ/bIccAEqqjYGAeBSP4jAMarH5KqG7dWFCRHkuz+utiU47x/SvHUyY1rW9+zCVo9qzbGyrYn6Qqrb3Jp7V6jlBpcCtXisb8e3hXk2rj4LBMkJRvGa1iL++nxBrPuYO6B3OeD+I/Y1jPFl9ttX/YqTstaLd+zg5e8bx2WMePPmAOzfe4PW771x6fCQSiUQikUgkEolEIpFI5KfDyWFb2Bbvgqu7Qa9LtRM13UczRrxu02inSFtQrqPFJcwTek+yPEcI7m5bZMENDaixLHbuUIy2+oXu+oYEesS+jZ5371GD8/oyUX+hnjvJGF96DIJTz6luer3/ePeAv7lc8M88fYB1RS10A5zffIv5jTc7124/W7s8x61c2qrceP8ftupBJ8szMAZvwpyhzeatCPlVHW7fiBpP8gVCiDb3Vb1qIbiNS+9QpBaKrcspbVKL5avjXDqsFyaEc+WtWtIC4MoQsS3BSGTzBbuPvr8hKt96/x/U74k3CdnWjfo9cXbA+Z2vtJ35VyCuYDA/aj/Wbn14uPIzLBCE/UZbU2ZVDeyqrSrJ8pSyE6NfDqekqzj60Q4+HaLZjKRYUIx2cIP+eWFZ1eBu4IZTxPv2ogxj24s4oBEHv7rpF0/gNMaSDl7MDR754jIYDMjzHFUlyzJGo+tF2kf+ZDGfz+vE3sHn9PsfY8wjP7f43GHOYGPEp+A1J5ejjdjuJglb3PR/DuldE+KrethXRwf1MWCfsX+1jhbXC8TtlyFlB6vjhhZ9nXNfPNDq65tlvBFLHs4iGIag5tLLbulbIf78giuuGr/o8338/BOeHN5/oTaRSCQSiUQikUgkEolEIpGfDGXZKRPYI/5Jx7iyEjavwqXjOlXRG4sbbqFi6pkmNbYtNlYR2GGbYMpsHTktBpcM2zNmIpSjTXfsdehOkxXDLVwyIJvskY/38CbFFFlvWwCnyn+xuM8Tt8CKQURY4C6cOfsbd17l//Klr6KdaPejN/50o1NKMj9tPZNb7/49hrP1goT9T/+IvYffq1+LK0iKRSNGXEnyOcaXJIvK5Vudrxhth4UL6utY7ySbtV4LMDg/arnwpTpn22ij2GKJIngx+JVr2vv6dYiQF0QdxpcY70JdcfV1jezVT/N9zce7rcUHs5tv4NN2OcmrMNWiiCu5LEac9UKB5vFpdk6yqn2uytbTD9h+8h7Ds6ettuVoJ4ja6ajuvxtOycZ7FwrddT/omR3uCODSI2S7TrkB4x12eb5x3GXs3Tio3cCRn32m07VR7/T09JIjI39SUVUOGwvfdnZe7nu1S3R2R36uUFXOj884PzljcXKOeEjnFjdexYIHF3JmD/GSk+kzDClgGbC7UZt6wD6JTuu62m08ngzRlIQXX30y5AYD3afQH+0f/SXP8ZIz0XtAEJxTdkjYqqLFr65QZBlQ1sJ/I/BGwGu24a4OLvFpiEWX7v+ACJYhiudQvslIb5Oy3TnGsqNfJeMpKn0LDsL/higFBeekXCSMbwrij59/yq39V2NESiQSiUQikUgkEolEIpHIF4zBsCMiGkuZjkkadZVX4vRqZsfZAf460cjGUo63Mdk81PyunbCVW7wldOuGkG06wrBon5R8PcOKuAJbZihSCYLSEvbdYMLs5pda/bnI9etU+b3sKYuGIOxUyXr7t+q78tuP79P0Jj/+hd8i27lTvx7Mj7D5nHIShIbx4X32PvsO5XCL+Y03EF+y/+kfY9TXEeGr+temyHDpCPGufk6T4884HW6tne3GsNi9x/hobUwx3jGYHbXqOhtfMjp7jq+itKki0K0raLmYxOAHo7UYrCGCu35qqgib7+vmc12/9iZBOzWys62bFz7Xi3DJsI4Cr6/iXMepL5SDEUm1qEFFmO+/RpLNakf2fP9V3GBCujzFlhm2WGJcyfD8WRDuXUm6DBH10+efkMyPmd3+Sn2f5WgLcWW7nrpNXyoaXa2FxrSvrNIHase7kE0PcOkQN5iGGutFhnuBMpPTrW1u333lhfsW+eKytbXF48ePAXj+/DnWWvb29j63qOrIzy6qynw+5/DwkPPzoLeJCFtbF2s/L0IUuyM/N5RFyac/+JDlvBocu6r6tYI4wIaBkKJ4qtWgsorwLnA6bNWxXiGkiCb9oqyCZYRgQ9zRBbKy4i+IOq+c0FUlbEP/P/oXndtTMDMf4SkY6n5LlF5Fi4f2rq6j3YdlTKlLkOYgOVyvZIFhuHH94OIe4FjQx1w+48y8S6bPueF/Y+P+BcNI77CQzy7sUyJjzuSHHOiv9R4ThO72/2Rk+RznSpLLIqUikUgkEolEIpFIJBKJRCI/ccaTtsNUXEE5nGKLEHNdDKcs9l/FuIJ0foIaSzHZvbZYpybBjbbbQnWv4Hmdc5kNE0myPKccbV/UBLxnOHuOLStBE2G5fWtDUN2g0z8pc4bnz0GE3xsYPvHn9dycqnLu2073FKFs5DP+iw8+5NeOn9X7z2+8xekrX2/1M12cBIG4ik/fffh9AHYffJej136F4dmz+j6SfEYx2qkd3YKSZOe4ZD0XmWYzdh7/gLNbXwmiNOAGY85vfZkkm2FdUdVC95VovjYnUbnu67rf3iH4tSVHpLOAoSN0U4mxjdfa81y79EXm9zmYr8RYltu3GJ8Gkc+L4fzWlxgsTkjyOSrC+c0vUw4nTJ99RJrNmO+/TjHZpRjv4M/Ce+WGwRVbjHbw+bx2ywswnB9vuKalu4gj3NWL978HL0mIVK9wVSz96ndLkWqByW7jmOsbwpI05Y0vvx0NSz9nDAYDbt26xdOnIXngyZMnPHnyBGttfK//hLOq475CRHj11Vc/t2SHKHZHfm548MEna6G7QRjYrF9LHczS/uI3F/w6BBfzNk5nQSSvR1mGhAmGFEUpmWNIMaQtYdjjyDkiZbtV51urPYiG9npKwlblNG/2X+v/rvsPBaecmQ/wEtzlJQuEZOM+Mo6YmY/Y9m+T0h8JEWTrPUo9C+J/1X3RhJSdDaE73O85x+YPAWGib9TCuqfkXD7g0PwBALk859B8kx3/tdqhrXgW8hClZKi3yDlsOMRDde9VbfJSzjjnA8b6KpZh45mE2um99xOjbyKRSCQSiUQikUgkEolEvlCcnhxz/+OP6tfiHTZfoMmAfHpAsjhluXuvrvecbd1YO31/DHSFbJcMQH1wwqqGWsmDCWrS4MpWTzG+PG51OHvWqhtejLavFrqbeM/BJ3/A9uN3MZWw/N9NBmzdepVv3AoO2JmWFI15TYNgxeDUoyjTsuAvPn3YOu3JK19rvbbFshZ1B7NDsu3boRY3kC7PuPP9v8PJvXUb6wpYtiPPjSuR8rz1HNNsxu7D74b3c3kOxlAMp6F+d+X4Fl9iinVkvFKJ3A0huxsL7jfcyR0HN2zEbl8H8W7DVT86fcxyd+2ARxXxDl051tVj8wUuHYJZz8PObrxJkp2TZjPO7v4CxWSPfLrP+Pgh3qaUVR302c0vhUUT42rRhBiyndvtiHOR4Jrv9rcrxPcJ85UzvnHQxj2KK0NsvzpAcMko3F91jM3mJMuzRrpCihtN6/113PqP8LtZFgUfvfcur731Fmkaa3b/PHHjxg3yPOfk5KTe5lz/PH7kTyYroXt7+5LFYy9IFLsjPxdkiyWzk07UeKVnqwVM+4s30TGlzOvXRgcbInP7VELCFopHq0FAU1RWSpDgGPeaI9hK+E6C81mUglNQg8EGt3hrMOBAoNRzUvY64rK2/vR4TuS7lOasPmKo+4gIpc42xOmFeYCTOcf2W1gdY3XEtn51w0VusAzYw+NQdQimdwGAp2TGR3iTk3EE4sl4FmLTKTg3H+ClaPRZyeQpT+1TUt1BqmeieLb1nSp2fRevSzwFKn7dfw3Cdy6H5BximZLolDF3L3yvdrduYE2MRYlEIpFIJBKJRCKRSCQS+aLgnePBJ5+0RLggeFb70xHL4dZaUAQwFr0kqfCF6MaEi4A2o8UVN5jghlWcqnrS+SmYtNoLxXi/3b8OpsxaQrcC5XB64fF93PzgH7L99P3WtkGZ888+/BAE/uGNeyy1LRol1VO0CB7lF86OGdRx4KEnl7nR02yG6BPK4QSq6cadJ+8xPnmIF1sJolVdau/Da13bcrpYV9QOZxUTBOWmkN1434GWyBo2+I2zaneu7/MxL4fa3mUWXOPVtXce/oDzm29RjndAPYP5MaKOvHr/k2yG8Q7jSsrBuI4JV5tw/NqvkM6OKCd71QUsi4PX2tK8yFrobnIN4bgblZ4uz8C74IxfHUMngl86c8BVPPoKbyzaTMj0riV0Q3Dod8sANOfbg/g/emHxezGf8fH77/Hld76KiTHXPzeICK+88goHBwccHx8zn8+j2B3BWstgMGBnZ4etra3PzdG9IordkZ8LlrOeKO3VIjaz+SU78DuUEkRouNjVvXlK0xtH3qobLSE23Kmv4s0b8efi8XgE34oGr33bAk4XJLQjndp9EEbc4py12G1X8euiGzW2S9aLAJwscLJg7j9lS9/qPX8QwS8eXBgSUtlmwYN17LmE64S4dQsUvW0LWdUnl0r4lvqeLGMMI0o9r88r2PXzFnDMcMxIdOuCOt7K3Vv99xWJRCKRSCQSiUQikUgkEvnpcHpyjPdtsUM6NbL185r4FkG1GV3e9XBXtK7XMcpkC0xDMFSbXCp0KyF6vPk6m95oiZBXkSzP2OoI3U3+qSf3+W/2bm7cyuqlre7b0HYIo5BkM/LpQb3ZpSNUIc3OgoPYlbh0vHY6Q+XMtuvn6MpQN7p17ctV564ju8+t3I0Sv1aM+GZoZ3AaN2tmEyLfW9Hn6oP4u3I/q2cwPyLbvoWKJcnmGHW88p3f4elX/jzFaKuu5T6YH+GSYf25EJQ0n5OPd1jHZBqK6cGVz+U6uOEEPWtv88kA9TaI3ij5eI/WB8KXdSIAhGfb+tx6j2kI3UBVU36NLZat96i0g5YYbsocVHFVPXJTLBmdPGJ28016f8+uIM8yjo+OOLj54rXSI19sRqMRd+9ebFqLRD5Potgd+bnA2J7BsAiY4CzuftEaUsbuNrk5xpmsERL+svR8kYtS6qL3zIrDk1Wx5u2+e8ko61rg/YP8kd4Gb5jLfbwsW3HejiWKYhlW4nxHcAcW5jPUOyb6Wh0N/iIM9TZOM7Aftm8ZYaS3yTmi4LxeTND3BDybNdCDg36K0yVKQe8yTYEZHzLWewzYr2uRl8xZyhOez/fYnvzGC99TJBKJRCKRSCQSiUQikUjkx0Oe51ceI/7qGOpVfHLtyPYe6Yu0vkTIvhLvMVWt6nBR7btCu19NURgoR9v4wfiFLjs5un/pVbbKgtcW55x06p43Zz4TMXy0tU8pgm3s2Hr8Hi4dYcocFUu6OObgk39Mms3CObzHurxRI9u0hW5VTEfovgqlz5F9jfe4xx0cYsQb72l3yrASrnuXNVTi+aqmt6oLiQEa3lXxjtHpE8rBtL7dJJ9z97v/FY++/k8H5zZB3Dau2HBR01P3+1p4x6Cqm16MdzcWUyTZDDV2fT+urB3kANl4l+XevcZ9+rqmer2p8/xN4z0GcCbZWJDRPIe3KeVkF1b109WTLM9bAvlgfkyo4T6vo9pflLPT4yh2RyKRH4kodkd+LpjubmOsxXfjMOq4nk0sA8b+Nr4okMLhJ7zM4jMguJ09PYN2uXgApzgci9rp3XRje8nwmlXO5rRXkB7pTYZ6A8c8OMtXwrKAZ90+1R0yebrRfmkesdRHbPt3GHH7he5XEKa8wZm+SyEnnX2God4gZY85H1ex5JuDPkeogW4YbLRPmBA88Es85abzXpSFPGChj7A6xTLEMCDRLT579i6v7f0pkuTiWPpIJBKJRCKRSCQSiUQikchPjsFgsyavmgSTzzGuQG2CTwju4UqcVJGW4KpVm6YA2yt0X8bKNXxR3LIq6eKkdc4kO8eb3YtPiYAY3GAC8+OXii+H64n9fceUeESlSlwUvjQ/ZzkYM66OXW7dZLH/GoN5mMMbnD9j77Nvr+9RtSV0A3jTjhbvc2S/FH3PfeW2Xh/UEq0VwGswNVWObFO56FdibtdxvrpWbQDX9eckiLau+QpRj3F5q766t0ktdF94O3X/O3OfXXe6rK8FMH32EVvPPw7iOXB6+yvMbr5V708XJwxnh43z+bZjG8i22uKw+Hb8uxez0a9mvLk3CX6wmS7aFMjL0VZYOOKDocwU4XNii2UlbAs2D6VC0/lxiMJ/CfFfr+Pmj0QikUv4fEPRI5GfEsYYDu72r/4SBdwFX5iqJLklKQfI1QtML0QwGO1fOyJqQfuHg4qiZHhytLuyUUDF1YJv/3UhYULCtKolvtl+oAfIBX2zTBhy49J7u4yRv3OhK77kDC9FuK++QwQc+SU1dkLd8JVTvQ8hZcgBA3ZJGJMwxropf/z+32aZz17qniKRSCQSiUQikUgkEolEIp8v060tpCF0mmLJ9PATtp99yPToPuOjB2AsRn0ldWrbWcyme3qjtrPqpsjYxDvGR/cvrStss1mIrV65gV2B8SVJJej1sXIi+2RImY4BCaL8C7LYvRPOR6gl3r2TzBg+Gk+xCIkYEjEI4AFXFVn8lZPn/JVP36uFbpcMObv9Tuuet5592I4i7wjZCh1nfL31hRA6taMBFds602qhQL1Nw3uvxq4+BahNEWOC0F8J3WGRg4Yo/CuEeOGiuPXL5XvjSsS152Slco97Y0Ota8JnJp0dMTh7Rjo7wrg89Kn66bq/p88+YufJe7XQnU32WkI3qqTztrkoiM1r8sl+u852aLj+mxjo+Qw2I+N9Ouz9XXDpODx3EfxK/K/eI1PNPwuQLk5bv4PW5YxOHgUHeg/a+Oky3bq4pnwkEolchyh2R35uOJuf4ZO2rqwCviohLUVnwOsUs1TEVaLzj2gENgwxOmh1QNRgGKAUKL4WbYPIXeJZAgpqsEwRTdftFUQThJSFPKTgrFEbvD00cCw4k3cpma83axDaDQlDvYnVcWOfYeTvsOd/uY4BfxEcOSfyPZ7Zv0/OcxzraCdPwVKesJTHAKTsMeQWRof19UUTxvoqt91vset/hUTXETeKx1M0otmlet1duWoY6e3eeut5ueS9+3/wwvcViUQikUgkEolEIpFIJBL5fMmWSz58793avSmuYOfh90mX64LE84PX2y5aMW2hWzsB1d6R5AsaB4RaxJcI2aOTx6TL84ujtFWxdT3j0NeVIJkUC2zzehew3LlNMZxeK667S5IvKEbbuOEUN5jiBpPgsK74+/s3WSa2XjSg2rGHqPLPP77fmvBf7NxtPRObL+ro8nW7F+/rdVCk0q617p+oawnZbjAKsdwrwXslnopBTVItcAh3JGgQnzt1uU2ffHrJ56DZw1aTVb1y74JYrZ7x4X1Gx48YH37G4PQJ3qYU4x3K0TblKAi0g+VZ+Hy4vLquNOLgpR0T7h1bzz5qXXe+92rrtc1ntagMUAy31qIzUIy2yXb6UjovWRiyurwd1EL2hQsyjKEY77QzEyQsSvANsdyWOYP5cXDAi+BNgi2ysKCkMQevgBcb3k+boiYJr1eXs5b9g5c3Y0UikQjEGPPIzzhnp6ccHR6RZxnZMgMrqG1En4hAqWGQ56of0SB0N8ZxmvAjL/0QBMsAQ7pe/Ykh56Qaa4QLKkEQbg6oEiYYDDAAJlVckyAYlvIExJPLIbkeIWoZcStcpyIcoyz0Prv8CqKrgZWQ8bwSvG8Ewd17pry+ER9+XRwZ981/gDNZHd2e8xzUoDhKOW/lDKVsIViG3AwCtjdMeJVEJ6Tshjrf/haOJUsec2K/03muliCBF9UWg2WM1SH2kns4XxwxW5wwHV8cMxWJRCKRSCQSiUQikUgkEvnx8tknH1EWRf16dPoE69avy2TYqvXbrfUsrmR88pDZrS9XB3i2n7xPtn0ruFMJscriSrxqv9DpHYPFMaJKujilmOxtHBIczg0XSccpPj55xGLndogrb0Z8r+wt1Xxevn0LccULxX5Pn33EwSd/2OmQwacjtMz4R9s7/Gd3Xm/fUkesfXW54Faetba5bt3wPmG7rwxkJ5o7OLJdc8ovNL3gflZCdvMctYPc2Mq53ojZFtlMxpQgZbc2XTe2fuNzUL9Ldb+1/ls4XlxB0ohzPz94A+uK+rO63H6z9bkx+aLl+FcEl7aft0rbZDQ6fRKSAyq82FbkvZQ5pli/h86mZFs3GZ08rK4By+1bvZ9xNQZxrnbL92LCZ0rKyyNO/WCMG4wwsLYficEnI8zKvQ6U6YRsejN8zkTC56bx7DdKD0AlnAuqQmKE19/6Ekkay1FGIpEfjejsjvxMoqp89sl9PvnwY85OToPQ3aT60oR1KWtYxedsjuHUfH51QaQSqVd1qrUngrzrppbWuhMPjfatWuCiqCnJ5ag1QHOEVacqjqU8rK5fRSix/p8HwWAkoeD0wmjwq7AM2dVfZmMULB4Rad1LqDlu269FcMyxjBvrHMEyYsLrDLS5kk9ax1DdkVK2xP6LWGRnVx4TiUQikUgkEolEIpFIJBL58bCYz1gu2o7owfy4/rsCxXi79To4fRv1jZ9/3HKBD2ZHJMWCZOVQVl+Jy1WsdQ+2zOpa4KOTx3XN5yYqXY+wr0V3rWpFT04eYZdnpIvT0I/lGThXx50bXyINIf9aeMfug+9euDtLR/yHd19HO9Hi3Zm9pEfINp2+uMEYZ9vmEe0RRqVRH5qqnnVb6F7Fj/cHhHubtgVX7RwpBrWbaZNXC9kXlYrs5GCqgvfBpb0SYOv2lWQutjGHrJiGkJ5ND8i31nOU3qYs9l5pXTPplFAM9aob7upOOkHXVa8ieJuu3yNVbJGBSeqeFKMdEKEY7wHg0lGrrnj70ZgNcb0PnwyDKH+Fo3/nxi0G47V4b8qcrWcfMliekhRLjCvIt2/imvctpu1k7zyDdn+FvZu3mExfvL59JBKJdIlid+RnkpPjY46Pjq51bG+5bBGoSmmHlZefZ+86l+r5NQtidEIorA20IrqDmLuK7e6LGXeyZClPapG7GeW9lMecy4ch0vyC65cyI+NpK378RdjTX+bA/UbvPsuojnNvRrc3yeWYjMON7YLhhv8Ntvzb4RwX4Mmu1ffkosFfJBKJRCKRSCQSiUQikUjkx86GQQVabmmfjjDaFkGbIqkpM9LFCUmxDMIya7E8nR8hrkR8o25wkfWKeE2nuPEl06cfYJfnYV/1gzGh7vZgQjHcwqUjymRINtkn27pJtn2TYjhlsDwjXZ6R5PNwbWPaNbC5jmi7ZnT2DHuJ03agyi/Nzze2d6/xcDhmYdrziIOzp63XNl/gbcN0o1rVoV47cUHCwgDvwHtM2XWpS0PcvEB87kZk99ZS7zq5e0+1dthXjuG6pnnj74iEOuPVooS6pvfqpqTzrnSE+O7k8HLrVuv1fO/eRh1z06hNXQ4mlMNGOoFIe9GGKkl2TjmY1M/aV47n0emT0KVVsoAILh2FY5KQXOCGE/LJ3sWO7dV1bRX9vnpeVZ1zvAvpAR99k71P/pA0O7/yXEfPn7UWqkwPPwlR7RXZ1o1WvHpvf664xunp6aX7I5FI5LrEGPPIzyRHzzeF0guxoGXPeKkSvEPtbnBjXmwkeu3Lj2tRunX5yr1tGJOwRVvw1krwBqsjnGy295KxlCcM/D5DvUUu62eSyyG5HCJqsUxI2d5o72SBY4HVCQlTEiYvdF97+suc6Q9ZyIPOfYXQcsMAy7i6r03BfiGfUXBKyk6nvWVHv8pE3+ID+/9kyqskbK7wKzjB01+zG2CQjNid3urdF4lEIpFIJBKJRCKRSCQS+fGTJJvzNuVom6RY1IKgLTNMmeOTwYZ72eaLerpu69lHnNz7GlLVMzbqmT7/mHnDcSvqSZYzysEYGqKuT4aUdkBazEHBekeSzSgmu0H0qwTBcrS9FiiLJbZRFzu4t9eOZxWhGLfntV6Gi9zoTQZeUVUG6km8srCWgff82tETXp/PWFrLD2++xuObb/LWkw/q/llXMJgdkk8PsPmcg0/+8TpGW4MTPkSLG1R9QxgG4x3adWT33wGbCZBXHxIWJZhqR1UTuhbSBVFfOcx13VxMW3SWzkk7/e3ruXZyJMvBOIi/FYvtW63492x6QDHZ3zyPsYgLCwXC50DqqPeuw9qUOaKK2oRsesBo9rwWggezQ4ZnT4OYXRGc19pauLHcvYtdnPVEtLcR9QzmR9h8HhZeFEv2PvsuSbGo7nfC2d2vXti+D5vNGvXsAyu3+Y+C9z+eevGRSORPHlHsjvxMkmc9qx0LD4n0ftmrAen77lRFXBjimKXixz2HoBScMeDywWvJgoTNExiGGB3gZbPPopYB2wiWkgWmRxQ2jBC1qLjNfTqoxGJhoActwRtCrLnTjITpBQ5zi0iC1xxl1HtMwRzwpGxt7Bv6uyzsg43tQCV4J3jKKlS9c26BQ/NH3PK/uSFYK8oz+/dQk5H5QxLd2hy8iuK1rKLSZaP97RtvIJcM/CKRSCQSiUQikUgkEolEIj9eptvbJGnaqtm92LnN8PxpSxAcnj9lsXuPrkradIYm+Zy9z74d4qIJQqYtM6bPPmS5fQdTOWO9sRib4I2t5wnHR/cZZGf12Wf7r7djqVciae3E9RtR56bsRIKn40tFx+uST/ZWcu+FzAT+6sfv8ktnR1jg2CZM8yWjSnzPx7u889Zb+J2Ec1cyff4JLhmCCJPDT7D5nMH8uFUvGjr1r2UlPDc2veQ9ifeo6dTMrlzk1aUxlEHQJlhlfDJsLVCQsuwI7d153x6hu+vq7zi6u07j+d4rqEgtdufjXZZ79+r9XizZ9s3eBQnlYMxgUQQXdl173FT1zjte+Ea/Fnv3EPXYbB5uCdh+9EMWu/fCtarj3HCKeI8psnB9kXZkeA/iCsanjxvP2bN//9vYcp2wcPzqL2/Wcr+CJF9sbLvKtR0O6hHmva8/h+lwED4XcQ43Eon8iESxO/IzSZIklGV7kDF4WoIVyh2LH60GpkAJpCG1RcpKM1UFTxC6NYijfti+hlYyd8EpZ/IuQ24z1nskTNDOGkBPyZn8kJRdRnq7c4xiZYpgq+htDypYxqRsIVg8JTnPsIyxTDAkoU9klCywTPCah/rdoogaErYZ6B6CQVG29B3m+imZPEWlADWkbGOY4JhjSBHSqk+CYYBhWFXFThFMJbinlUjtKDnjufkmC/mMA/9rbOs7WIbkHHNsvsWx+RbrFZirAaapzpFWz7HEUWAYrK+vBsuAmXxIbp+z7/80U30DwTCXzzg032BmPgZgT3+Jod4k4xkFZyBKqjtM9E0W8pACZaA7GEK8j2NJIafcP53x2s1f/Nw+c5FIJBKJRCKRSCQSiUQikRdDRLj36ut8+vGHdZS1H4w5u/0O02cf1cclxZLJ0WfM91/Dp+tJunK0TZmM0CQNM21lhirMVsc5x3B+SJqd1zN15XQf3xDzhmdPGVdR0QAuGVbCeqOf2jaZGNeN7t48Rj8ngc4Npyx27zE5edi7/36S8Ffuv89o5YJV5WA5a/Xv8M0/XUdKP3v7N8mmN9h99IPQb2B09pR0cdK5n8+vrmNTrFeC6IpWLmcN86+1cF3Fhrdka5u2az173xKIg6u787w7QqqKwbB+j3wlxkpjv9oEqeLHnU2ZH7xGulxHaS+3b7buqBxvg5iwkKLMW/Wy3WCKyxetOHA1Fvzmc21Fx4thfvA66dlTxFjKwQRTOfDVmPp98TbFpUOkrGLPxdbx5hcxWJy0ntvw/LAldCswu/Hmpefoo5u4AGCLBaXtpIk23xNVbDHHDad1vLxxeSsdIT875oPv/DGvf+UXGIxeTICPRCKRJlHsjvxMsnewz6MH6wGgLD2mBEpl8DTEf7uR4HcT1FSDTwtqwwDLZGDKZn0gNirYezKcLEJtaYGMJ2TyBFTY0i8z4nZ9bM4RiFJwTCHHoDDWe4y4U8XXSCVkj1EUy6DldC6ZgYBjgSNDVOqRmJDU0eCWYRVZtLfhhhaECa+R6BTF12J86Bt4CqAAhRF3WrXALWGgZkiZy/3VCQGYy6d4yXhqf4+n/B6qgkpWHbJyVUtVm1ta7vawzdfPEzJQw4i7KAVeMjKe8sj+DigoHm/WAzCjI8b6CoJhoq+FBQQ+ZcJdco7xJsTnLOXpWmuv+j3LMo7nD9mbtP/nJRKJRCKRSCQSiUQikUgk8pNje3eXt95+h08//ABXCY3FZJfjV3+J7acfhNrGAL4kWZySmyoyWpWkWLDcubV2u6ajVp1gWywxriFw2pSyEy0+agjdEGoNt4RT7TicoT//upPFbVyxecgVEdMXcfjmn8G+nzGctVMbHwyGuHK5FrqhVaMcQu3n2cHrrXZdV/qq962u9mzr29f9e+2WFgnuooZwrVTCqKzrmEvP8+36s7s1vjeerfqWGC7etQRwrWLQV31tieOVeFwLtpXwmm3fBBGK8S7FcIskO8cNVmUeQ83rZq33dHlOMd4Ownx1nnzrBjZvxHuLhP3ek2TnmLJAjaUYbZGPd/FJCgjiSpZbN+tIdlPmjI2t69cr4NNBy/EcXN2XuKnVY/N5a9Oqzv26f2b9+/YCFKMdlIf1ggUFbDYPsf/VtSdH91GxLPZfDb+7yzNsmVP6kmK8i+mUAajPnWd8+v4P+fLXfzU6vCORyEtzjayJSOSLx97BPsauP77iNiN27FKRpUc3RlOCHwra+PTrZnp4cD2rRekMrkSZy6etOtwbEeUCS3mCY4HS7ZvgKVvblaZL3aOtyO5O7A1CyWzjvGGfCZHljZtWXPcgco5b7VfCuyFhoPv1JRWPl6zdXLQWypvudqle+e7z2uikp+QUTyf+RwARpPFmJExaiwIEASkpOMN1+kU7lQiAZXFKJBKJRCKRSCQSiUQikUjkp8tkOuWVN95Yb1AlzWcU4x3cYIIbTFjsvkIx3a+neGy5xJZZPd3jxbSEblRJslnrOuVw2notrmw5WyGIw102ykn3OFm77US1EntXBzikWLTqLF8XTQY8+epv8eQrf4Gz229zduvLPPnyn+P/++pbfHneESw75/c22RBBNwRNkXXs9MrRXYnDdRtWbuIxfjDBJaM6Znu1H7HhWrLe2p25bPWl1z3e3daOJw/1rRv3uBLLV+eq4sqbwuuqT6t71EYftXlMta8rsJ++8ovhs1Ndo/JSYxp1qgVlsDjF5AtGJ4+ZPv2Q0cljXNqOC7X5gq1nHzI5fsjo/BmD+XE4Wzpc9zNJW7XHB+fPW057b9O2YxzB28Znv4+eRQVNsR5CnHrX4b9qu/67xy7PW/vSxUl9n0pYMKLpEJsvQJXxySMGi1OG8yMmzz8hWZ5jqwUXSb5gePoE4/JwndVPgyLLOD85uvz+IpFI5BKiszvyM8nJ0THeNQY9dnPVlwDJiUMt+K2Omi2C2zKYTJFcV+bjTnshYbuKx26Lpl5yjvk2Y32FITcRTTeEVhXHGe8x0TexdDLSRfGaV65tw2atbF8NFaVTm2Z17pJCT7CMMAxoXtwyCpHpOsdTIGI7YjrBUa3PSNgKbnF8LWAP2MX4lEJOcWS99cbDsbIR5w5BuA+9t6DJqkGLUs7DM+sQzpWCmhB/roveaxRygl7jfxyG6Wad8UgkEolEIpFIJBKJRCKRyE+e7Z1dbt65y7PHj0iy81YdYGdTfDOiWRVbtEXqZoQ0BHev6cwPdUVqFdlwMCcd9+u6rnNDbDQpKlktuoorEV/U53LJsO0QV4+phHktlqgdBKHxBZ2q2c4tsp1b9euvnmSbbjWRll5siwybzUJcdMV871V2H3y3cnhLEE+bfSSIvk0h29tByz1tXN6JOu/UzNZmWcOGq7uxPzy/to/70ifiHcaX1JJzI/J8lSq5rketayf9Sti2Cdp0ta+2d45VY1tCtk+GHL/+p0jmJ9hsjvEl3iSowuj4IbZYhh6IYTg/qp3n+WSPbOfWOnDSFUyOPmuJ9cud2+2I9g7iSpJGX2BTpG7e48UnMnixmEbcfrZ1g+nhp+v7FEM6P6YY74YmvmT/4z8k3zrg/NaXg3B9/IAkX5C5G+TTAwbzY5JiiU/HlNVCAZ+GZE9bZpgiI52fkI9CokKSzygHE/LxDmos4h1SvaeteW6tfpuq+1rMZmzvHVx+j5FIJHIBUeyO/MwwPznn8LOnzE/OKUe0cgn8UPAJIcq8gQDpsSObms0BgUio7T2qBktaboiygjDRV8h40iNmF8zlY5wumOqbLPUhiHaOcSx5yJS3Nm9IgjCsKlgmlHreuUYYzHlKLJsDIhVHyYxEgwu9SaiZXQ1a1LCUxz3tCwqOcKQoBSO9U+9LmJBoiO1Z6tc5kj/s6b6hd5UAlZtc4U33P+S5+Uecy7u91+9DqmUGkLCKjx9xp+fA4AJX2Yy/ARgPdtkbv9K7LxKJRCKRSCQSiUQikUgk8pPn9t17bG1t8/gPf6+13SXtuS1Rt2EA6cqkfTWzTdmZbzKWYrzDYLE2soxOHzM/eL12iSfLcwbnz1nu3gFjUQS1lmK0Tbo8RZzDlMsQsayKJ4iczblGceU6thvAFy8VF92lHE6ZW8ukEdWuYkCL2uEtYrnzg98lzWbYfEEx2kK8Y7CKsO6pkd3Oa6zE1abAqh7x64nWrjgehGbXji+3aUvQFPWdWPd+oVtQ8A6MxTSu2XZZV9HlZr0oITxn1xaGK/f/qi539YCCWK6eEAEaejmYHSKPHOnyDBCK8XYrarscjCkmu6R5lR7gHenipHUPx6/8UsshPpi3a2Y7m+IGl9ei7taC70V9+LksxlyEcrTFoHJuK8Ji9x6zg+dMDz9FxfDsK7/Jcusm4krUJux9+i3GZ08Ynz3BFksW27frRSjD8+cki7OwgGB1P8mQYrQd7kkMqh7jHad3v7p2qndrqVemqH6pfr0UxfSkKUQikch1if+CRH4mOHl6xCfffp/zo1O895sR3iIUB8lmZDmAB3vqLojNqZojJHPpPcYyZqKv97QCqyOm+gaGhIm+tpnCA3jyi6+tQTQ2JFimvYd4Cgr647hF0xC3fsmayJQ9rE569wXB2lDqDEfWe8zUf7kVLd7um+uNU0eFm/4vYBmx63/pwvZ6Ufu6f8KR+WNKFr375/LpZkx71a87e2/GOi+RSCQSiUQikUgkEolEIl8wjCva8d+wGcPdM9cl3ZQ/Y3G2nRwobnMebrF7rxbGTZExmB1x8OE3kLLAFEvGJw9JXM745BEmX9SObLUJ+WS/3RsRfDLYELI3+na5f/lSBufP2Hn4fbYev0e+OOHJcBIEeARVxRaLWpQV7wDP+OwpST4PUdvz47XQ3dOb3mBxaQrdipT5hpDdjidv1w1HTFt0rpzUrfjxS7CuaMVbdwLI623iy9YNCARx2ru1IExwbuNdWITgyhB7XrnGzepPVzKaHWJdgfEFSb6ohW4FFjt3Wvdsi2XrnvPRzkZ9eJu35zC7tcj78CbZ+Lx3a5YLbCQd9FGMdigr13Ux2sInAw7f+DOc3P0qp7ffJtu6GZ6Zy0nnRwzPnpJND8im+yF+PDtjvneP2cHrLHbuVgtCqmh6MeSTPcrxTljYYCysEhmaQnXH/S89dbpbVO95dHVHIpEfhejsjnzh8c7x+P377Y19+urIkN9NsWcOu/CgoKnghkJyHLaV2xY/NIQU7sYXr1eGjxzpAIpdcBNCTe9qteCEV0n8lIU8wjFDsAz1FiPuYAiD6iE3MDok4yklIQ4pYcpAD7CMUHV4XN35IDRLFVTusTJC8ThmrId0noJTMnnKgAOGeoBhhNVhFWG+FrqlihXvEtzpr1PoMbmcoBSo+EaEumBkhGpJQYZhgJCgOErOOTZ/BNXKzbB2VVF8EKqlCIv1qnMZHTLR19j1v8yYuwCcm/ewMsGTV/W8Q1uPw0sBKtXqvvXzWPUboJBTHtv/ki3/DhN9DcGSy3NOzbss5DPm+hkTfY0B+wDkHDKX+3zn5Ae8tf9PYs0V9WwikUgkEolEIpFIJBKJRCI/MfrMCRuCmLF4Ma2YcpvNgvi2iqYWQz7dZ3T6BAHKwYRs++ZGuqMbTjm7/Q7jo/tMz58jwHB+xN3v/21mN96shTrrCgbLs7aAKdJ2G1d9u5JmbHYDmy+wxQIVg7Mp+/e/zc7jH2CLjGx6gE8GpNl5fY7/wUpUrs6TZPNakIXKkd2pkb35dHsmUnsSMOu/+qL13FUsapK10NyJLwfwq2ciBq1c+U1vbytLXjYNR6IeW2atVnXces+WztnbcenqEb8W47X6T/uWpfU5DDWy16/dYNwTm98pE9mp1V13sUFdp/oSQ46gqKwDQ8WVbD37iPnNNykan0Wbz4MwnmyWhlyfTMi2blJUseuriP6Tu18NIn+RhZloMYj3PHvnL6DGVhH0NixqWF1vteCh6rtLR62o/GvR+3ncZOfgJsPx5Q74SCQSuYwodke+0KgqD9+/367PDUihaE+dbk2F8iAJFaqdYjPFzEOkjmTKIAuDknLHUu6vP/525hEFm4F9EkYWxQ5kt9fXGLDHQPeavdi4fsoWqYY60Y4MLxmWUXW0rePIu25kreLALWMc81Y0d0mIN885JJdDAA7cr9fnbT2X3uFsqHk9YJ+B7qMoCz5DZT1As4yr2xGWPGq1X8ij6rwWwVZS9wwVXz8GJdRdsYy543677oenZC6fIRgsoyD648l4itYjOK3bo4akEcmuKIjHseTEfosTvlXtMdUzVJzMOZMfbtz3rFjw/333f8LY7vOl3d/iF2/8c6QmDpoikUgkEolEIpFIJBKJRH6aDLZ3sYMRLl/XKbbFEpeOamHNG0sx3mUwPwqzUvmCdHlKUmYsdu+ixqAmQW1KtnObdHbcrqHdoRxtUUz2keef1NuMKxB1aCP81PcI2RsB4K7cPMZY8CFaXRSkzJiePGJ4/hzxJeVoC5cMg4MZkDLnxsd/UNcPV0ItcXWNetMdoVBc2RK6w8a20M2Gw/w6VOKz0HLirvTplWM7xKd3hezVKaTxZ4i3bpy9KiEpVwre65Dxzj3WtdG70fbVuRr7m0J33YNLxH0a97h+fbVskmTzjW3lcKtVi15UMWXeL4wT3tO9+9/CFnOy6U00GTA9/IQkn5M8+B6zm2+Fmt+VESldnuKSIW60dWnfvE3XQrUqNp/Xnz0ArA2/b6v7FdMSuvEOm83a9zboTw79UZls73DvzS/9WM4diUT+5BBjzCNfWFSVz979mNNnxxv7pATKKyJwbKjj3VdW2p46zLIx6HI98eVnQM/2Rg8vvbxhUMV39/2adbet3N5Cyi7NPHZlcwB9Yr53Yez4VQjCUG+1riFVfwRDwnbj2n6jtrYgmFDofINCTnhq/uv6tScH6SxUwJCy0x9hJL5yf6970M/mCtKLjsvcKd8//E/43U//TUr/cs8sEolEIpFIJBKJRCKRSCTy+SAi7L/5ldY2o44km4FqLbz5wZhiso9HQu1sIM3O2Xr+MeLXblk3GLPcv9eOUu7BlD3zQp35qW589Or83qaU6RiXDBFfks6PGZw/Y3j2lGRxghqLT0doMgQRdh/9gOnRfZIqcly8b4mN208/rIVuCDHhrWh01XY0uupGRHbPzVyx/5L7rgRuWdXhbgrI9Z8mvDdXnU8MSFLP3q33aGubimyK1VTOf5EQPX+J0E1P2+s6iTf73zltz+fA27bT25TZhiCcj3eCSxzwYpgdvH6h0A0wOfyEJJ8hqgzPnzI8eUiSnSNlji0ztp5+wODsGduPfsjOg+8xffYxelVta9X6GYZ+5q3PniIbYn73tW3E2K+PuUaiQZfVe9w6kQ8LN8ocU+ZMp1P0GlH3kUgkchnR2R35QuJLx/nxGWeHJ+uEmgYCmKWiiaKJBO3Y9LiaBwY/9NjFZvv0cYHbMripDZHlHcpdwPZcvH2FaoDmMbS/8EM494Q+tT1EjhvWw7t13w0pQ25Q6hxPjpFBRwAGJ3Oem99noq8y0jtYxrVgfR0sQ8b6KiWnFJzjKTDVPweWEYLFsUQpsDrCybLVPhw7xulsw+B+bP+IpTxhz/8qu/ZLGNKN/lvGpAS3ehcvJaqrmHXbs5wTrjt4bzrdj5Yf8v7x3+KrB3/5Wm0jkUgkEolEIpFIJBKJRCI/HrbvvY4Cxx+/i8uDCJ36gu2tMcfe1imPbjAmWZ63poaMK6pawi+G63GmJtmMbDBGjUXUVwJcFlzMFeVwuo5v9o7h7BBbCecKuMG05bCePvuQpFjPpXnbqfGtntHpOllRgWLY6JsqplgE4bzRT6N9tY+riTPV7pYG7fnN2mndjAxXHwTepnAsJqRRrlzfAMYGsdS1Fw4Y74JgWR2rCCp2fTrtzoFWxp/W9boTgD2O7B8T4l1LRE7yBSZf4AchJVIR8vFu+Hyow9kBz7/0TwR3dDOm3FhmB68xPnkcamZ3hG5xJTafozbBJSO2nnzAYHmKqMfZAUk2I8lmdbHKfHqDnacf1O3Pb38Zf5nDuidivrvIY1WTvt2xDWm7/xl1atVfFdGOhPrpdZkC7zCubH0+Dz/9kPnRM1792q9iuuePRCKRaxL/9Yh8oVg8P+Po3Ycsnp1RbhkYhUFGn94pBIe3OkVTQRPtFbzdtiU5cXXdk2b75NyTnPtqENa+Rrl9vcGUY0HJnCEHG4LzKv67j7CvWmGH4NTVHRAsaeWwFrWcyvc22nvJOZcP8T5nqLcYcuOCHvYL9oaEgR6wMA8pOGVb327sS+ta5Nv6DsfyrZ72KZ4UZXOl49I85HlyzG++/d/HPn3Oh0e/t3FMwphSB3jJN/apeFDHkJsUHOFYbhwjGFoFbXp6KJ1n//HJ70WxOxKJRCKRSCQSiUQikUjkC8DOvdfZvvsq2ekx6j2D7V3EWJ5997ut44zfnHu6wB1xKdnWDU7ufpV8ug8ipLNjNBngKqFZRSjTSR0Z3Ue6PGs5rn06agmA4h2js6etNt62ayyLd6048mK8G2piV69NmWO9o1Qf+uLKzbrh9bk8ahvzkT3x4Iig3Uh0qKLGTf0YjXdVSe7Nytm+6RT2LgiYq0MqgbV+LgrSLJJd92dTgr+IH6fPd6M3qhiX4WxSPT+PzZdsPfuIsztfCa7+wRiMZbl7h+H5c07vvIMbTtfPUcNzsmWGmoT5/quMjh+y/fg9xDvyyS7GFYxOH4f3XpVkeU5arB1aaXnS+myVw7ZYno92WOy9cuXdbcyhXyvavv375JPhxm9YujwlS2/Vr4dnz8CXZLt3Lz+12PB4fIntCN0rludnPPvkQ25/6Z1r9DUSiUQ2iWJ35AvD/MkJD//R+/UAqHZbC6gF3OYgSAFdfYo9QfjsriYzgh8Y7NL3j6IEEMEPweRaa6dqmwf0D7E8BSXB3ey1wLIZS+PxeDISLq4XLRgKOSVhe6Pu9kD3Gft7LMzDjXap7pGyh1JW7ux045jgO+/fN5fPKOQExXPC99nVX+xpXeLIsfStmK0Gy906Nyi3J18nNWNe3fkzfHT0D3rqlCsJE3ItNgVrDTXGBSFhG6ebcegoJEwodd4jeEvve5G58557iEQikUgkEolEIpFIJBKJ/DQQMYx2D+rX3m8Kc934aIB0eU4x3nnRizG/+Wb4uwYprxmy7JLR5VHozrVcsuJKpGPiEFcgG5HMnTrTJsHbFOMKnE2DS33lyFWto9SNK/HJoDdafX0yD961nOXNK9YzdtKuo91q30wgr1qv2tX9q+b+xJVth/kFQvbljuxrRo2/pKt7cxnEuo8KUEV2q/rqvQrzwTaf49JRiJ1HSYoluw++z9ntL1MOJth8jrcpi917iHpufPj7iPcst26gNmF4/hyjHlUlXZzWtbsVGM6et2LAk2zWErrxviVKKyFRoMly985LPQ/E0KzlLj0JAabIahc7wPD8GenynLKqDZ7OjxmdPOTk1V8m27nN4PwZOw+DOetcPYvduxufwfUFBbUJxrtL3/ezZ4+5+eaXMS8Tlx6JRP7EE8XuyE8d7xxlVvL0O5+2Vh6Ka9R1SSpRu6ROBVdDiC9f1f6w9A6CpNDg3l61kVW71QGCCvipwY/BZB4pNLjG69+QteCthFrUjgxPFhJ11GA6YrDiURRPhpMFXnMswzqeuylql8xYykMSnTPR11B85ftOUDxT3iD1uyzlKZ4lgmWg+yRsVTW0Bwi2atceWKz6uRa8lVxOyOQxhZwCkPGcuf0jZv5jdvUXSXSLkjnn5gPO5L2q/QDDqD5/ENgzEN2IPgLl/vk3eDL7Hh8+/31Qs1oHCigqDo9DcSRM8FpUtckNljEJ0zoW3lOSsIXXHKWorhXkbEPKgAFOl/hqnxGDkG4sGgDYGd7b2BaJRCKRSCQSiUQikUgkEvliYIxhMpkwn6/rWWeTPZJ8jkuDGCdlhnuJGPPWdSpBc4VHLq9JvHJsr1Il1bPz6Iec3mk7Ub1NUTEt4dK6At80wYgw37vH1vNP8Kuo8tp9rXW/xJeIv1z4k6pvKn5TbOyI7rqKBV/Nn3rHBRW4w/FiWkJ3EOL7HebtTv3o0ePBMX1FRDa0VX1titramPqV9ayuSRrnNKi69fNWR5LPWxH2xhWMTh6y8+gHGO/wCPnWQSuM3bgcn47qNunirBa6ITzH1mdLlaRo19zcEKBFoPN5vLJW9/pBtLa4ZNCJ1U/RxkKPdH7M4Owp85tfohxtMTp5xO6D7wDCYu8eLhkzPnmIAHuffZvF7B7p4qx+BttP3gfvWRy8dnnPrnCYe+co85zB6GLDWCQSiVxEFLsjPzVcUfLsvQecPTxCS4fJ21/EdunxIwmDyGoQoitzcrf8SOXO7sOerVeNrczBqqDp+nhNqmtY8JMwkDBlkKvbFwn/9ZR4Wa/kDCJwn+/c1/WqVUpKwoAw0SmW9SAol1C7upQTVO+SsK69UhIG9wN2GeguQFVPez0IMo1zaTVcWeEpqpj2Elddfy6f4ht1uHM5AmAhn5HLYad9EPQ9OZ4cNNTcDg+j+Xw2V63+nU//d0z0jTrOPQjyiteiejNCX4NrfEAIV9+qrx/EcV8dMwSG1QKCJWH17WpJQBU3hduoD97k7b3fvnBfJBKJRCKRSCQSiUQikUjkx0+2XFKWJYPhkDTdTCK8ffs2H330UXjhHUmxJJ8G97cCfrL7owmq3mOL5Xq+EULt5UvOOZwdBVFTgvg7mB2R5HNGZ0/aIp+xLHduMz5Z1+QWVyCuQBtx5rObX2IwP1nXMg5H1lL3qvihadQGXx8VIte9SevYcuOLVvz4pi2FtmtdFbPhQO88Jpu0n4muhfgfjbYYvTp32NWMPldCzLqs9yk0Fe5ayNZV/9bHaTNKHeqa4lLF4isSBFhpSsSNWVFVUMdodlSfww0nrX67waQldIcI9LaQ3a1zLbWj/BJUgxu7IbwPz484v315s+DU18ZnW3DpGOMKjHe4ZBjc2lWCgM0XDM+eIIRa89n0gO1nH9Yzs5PjB2HxxqrvwPj4YeuzDGzUJu/t2lW/syLYpC+1NBKJRK7mOsuBIpHPHe8897/5HqefPUd9Oy5nhTiw50EQ3dx5xevmrr5FYx5wGxk97Xalp9RZ7zkTJhhdf/n2uYjX9vHN/pfM8axXQjaF65l8FETlSwgu8mb1nPbwVblMhIaJvo6sbev41fUliNur9mFQ2GkswS2u1xrcmo1nE5zoowuS4T2eZePcmwcFibt/4CNYRPtXvI7kBrfHX7tGnyORSCQSiUQikUgkEolEIp83i/mcD9/9Ae//4Ht8/P67vPvdb/Pphx9QFG3jwtbWFq+99hqJtSTFsj3rZeyGAPtCqGc4O2zX3U6GQQi+6FzeYfN5EKCrdoNKAB0fPyJZnLUOP7/5FuVgbWQRgttXysacm7F88uaf4ft76xrIKzevS4aUgzHFcBpEeFUQG1zJJsElQ9xggiZpEFKDwtt6ThtCd0dovE4dZ70olvrKhle9J91yhtr+u65k5/ZrVs70aimASkN695WArL4R2d2QaCsh3PiyEps9Rl0wutcXl85zUrqvaid+RTdqXPzaKX7h3cvmEd1nLbAhmo8PPyGdH1984lUt+Erwrt93YyjGuxSD8fpzKYJPBiTL08ZTUsanj7CNqH643mflwqj91funircpzqaU6ZgyHeFN0noOW/s3sEn0ZkYikZcj/usR+alw+uA5+XnjC9v01VMBmymcecr9nsGVAVbjnUvGEH7QE20OIRLdKWr7V5Zlo3NycxrqrLDVaS+k7OI1xJlfJMoGN3NCt141ohR6gmEQosXV1jfvJeOE7zHkgFR3WMnD7XOHuO8QJV7icXQr86yixQWzcX3LkG19h1yPWcoTjCSrdHhUPE6XGBLCG2M2VwyIx+sSUXPpQgPwKA6hLUCHiPIxXrON9sFBXm4I+u32STXc3HzuhhRVW19XSEh0gmHIR0f/gF+4Fd3dkUgkEolEIpFIJBKJRCI/SbLlko/ff3ejJvfZ6QnZ+0u+/M5XMXY9f7S3t0dqhPs/PKm3iStbTldxJcnilGLrgOti8wXGl3gJseVaxZf3zzIFQuT5+prNmHJBufnBP+TojT9Fth2Ea7Upx/d+kU9PPuHW7JihVx6kCb8/HXBkhXsecuAja5Ctt/hffPADbhSrZEjBDddCuc3mwYG9cuqKaTuFVcNzuYru3Oe1Fgl0jhHpnb/daCEdd3TPOS/e37kkGhzZWFa1Les49tWJvCJVSchWr7sC/8bJG67vviO6MfDdhRY91+hbICDe0/LmVPHwtlybncSVLUc2qiSLU3w6RE2Czeek2Yx73/kdHn3tt8m7n3nVOiUgLBLwqDT6K4JvLMBY0RW2r714pFpYIOpRkzA6eYSKIV2cosaw3LoVPsfVIgMPYNNWXXCXDBBfYrM5STrgxhtfvt61I5FIpIcodkd+4szPZjz78GF7owgYretxNzFLhVIh6bNfE0Rve/Ewy20Z9HlwinebouBGhnLXYnJtpXLngxAfXnBGwqRHcA7R2iFeu59wTL+ou4oGLzgOkeLN0aJ4Mp6RyTOMjpjoa8jGAG3lcA5idje+PKAYBjgWdAnh4QccyjfqqPT1Tq3jwINY3vPGCFU80mW2eqHUc1J2N3YZUoQU7Y0d9/i6z2ZDLF/1X+kfzAsGowMGnes+OP3jKHZHIpFIJBKJRCKRSCQSifyEefbk8YbQvSLPMo6PDjm4eau1vcjWJfjwjvHxZ8xuvlmLmcOzZ+G4F+iHrWoXiyvApqhtCphazc9dLGCGaPGccjBhsDgN5ywzbn7w+xTDLYrxDsYVPM/O+A9ffZVytLfRhxOzPhcY/p3X3+Z/fP9DbudZx7XuW7WfAXy3rrj6y2bmLuEyeT9gXIlrxlX3OXyrGHVWZ5MQO66Vu7ivb6srX9nv+tyC1EJ3tb3RWPqewcu4/zfMUP1CfRNTZLimiGws3iQY35izVNcWsoFiuIVxR4gqplhiyyw4x6vnLShWHcPTJ5TDbWwZPrdpNuO1P/yP+OxX/jLZ7p3WPV76DC6gW6debXBbSx2HHtxmSTavIvVNqAGez+u0gyIdo/uvsP3kPSCI2Ivde3VUuwLYtLc/ahLM9gGvf+Ud0uFoY38kEolclxhjHvmJsjif88n3PsCXbmNfOTX4tOdL2ABew08HXe2/DCO4UX+AjBsKxV4Y1JZjgzbHQSs3s3gKZteM7d5EKUON657mngxPjqhhrK8GF3UHq2MMw972QYRWVErO5f1eUbpkzoxPetoqh/JNMnlebejGnzev0XtjCFKtrtwkuKqFkllvHW3FU8jZBedvntNf2AdhSN8HQNRuuPEBSp9tbItEIpFIJBKJRCKRSCQSifx4OTs5vmL/yca2JB3Ufx/MjzGVCxSCyGjLDFNmQbi+JisBTgBbLJCGAL+qU7zh6E0GFOmYfLxLNt2nHEwQ3ZxFS7NzJscPGJ095e/u7lBecy7x2WDIv/Wlr/JwNG5tt2V+pYB5Ze3n+iY699Q1MbM59SjerZ+tdyT5IriHV0Jot0/SdFxXMZ51tHhwaKtYvElRO8BL0v+EWueRzi3LhpC9Oet7QcrnC9NuZbzbcNEPzp9Bo+76+OgzxicP6oUBKoIYE2K+G89MbUI22Uf37tR12QXFuLwVG27Uk2ZnGxH1rhOfftXChYvIR7uYMsfmC2y+JMnmDM8PmRx+xvToAeOjB0wO7zM8f066PCddnjI6f0ZSCd0KLPfuQkM0X+y90q7pLXKp8J6XZat9JBKJvAzR2R35ifL0/uMwsLGCNMRrBdy2xe2CWSh2Eep4+1EQqs1CQ41tq6gRNJF1SewrVqlJ7rFLDYnc1SX9UCi3LX4kdQQPA6EcVA7vQrF+QGmWQbQVpdTzyo0corEvdTQDJUsccwTDgD0sQ5xmKCWFzFAytLKbWx0z5Cap7pLrEU4WwXmt+6RsV88owWuB4lGKtRgP5BwxN59S+hk7+guV69njyTkzP2Ru7rPQh4z1HkYH5PKcM3mfUs7X74BQOcQrERut48+Du7sa9mrwqxsSHEuQ1eA+RKYHB/y6VreVcagDrmUd6V7IKQUnWEYoZeVJN6z86pv4Opa9eUxw1Q9RCjwlolJFww96z7M7evXS9ywSiUQikUgkEolEIpFIJPL5c5FZYoXvcQ1Pd3axaYorCpIszGENZ4cUkyDQQZgpGp4/Z7lzuxVxfuF1bIrxlQytSpKdhzjlVT9FQCrhrTHnmO+sXee7zz5ifPq49/wO+Ft7B/zjrU0TRpfW3JUI+53a5f36ZdsTrcagriPLdlzEGx7uyi2tjSKBtcNXfWdBQIb3DvEN97RWthRj0KrOpOLBpKH2OYA6rCtrIVpRsINWTLf48oXdyBulKF+0ZvulJ9eN63cd6Ek+oxjtgAg2m5EUS8yT9zm/9WXS+THjk0cAjM6eko92caPg+l4J2Vo531GwuwcMv/RL6MMf1ue/2m8fMC5vb5CQ/Fk7so0F78Fe/DuRLE7ZffzDut62KTMmRw/WYrsqRi+PyC+HW21hG8imNzpHXb3UIFsuSNP0yuMikUjkIqLYHfmJ4ZxjdnIGgE8FKdbxKppQR5H7ieAnjXigvDGYciBOUa/4yfVWfNnZyqFN/d2qieDHjS97Sz2Y8UOBISTsUrJEVr8monjCQMLoAMtV0SoeLxkD3a8ub0mYVHtyCllHh1sN2w0pI+4g3eWVBMF5FZledtzOuRxVfx6ScxSc5BVLeRrayDln8m44jqP6XlZ9XV3Dk3cGVVL9d/0ATeOZrNGqTnZjIYBKqEkOqLg6br3gmJU43mwb6C4kaFbc0foY0zhOKoE7/N1euBDhSwd/vnd7JBKJRCKRSCQSiUQikUjkx8dkusXs/OzC/dPppjgsxnDnjS/x4IN3awHOlhmTw0/JJ/v1cbbIGB8/Yrlzu13PGpAyJ8lmCEqZjCiGU8rhNBznXXCHN5y5YlPUXCYQnrH1fDNBccX94Yi/tb/Pyzhtl9YyKtfzfd5uTt2Lc2jS6F9X7NWVWYVLo7xDucRgbtGG81bFBnEbqSOsjSuDWahaTKAIPkk3Fxc0hOzgSm8YnUxyDUf2j4+maK2NjZXuXN3bap4R8K63f8aVpItTymRYR+KnyzP27n+rJcQbX2J9jpO1A1tYxYNXlz9+ih4/vUbntf2nCFuP36eYPiddnODSEdn0BtuP32Vy/ABBObv5JZ5/6Z+48JTiSvY++04rbn14fthylV8Hl7bnx+so+xfE9nzWI5FI5EWI/4pEfmJoM4bcCn4kmGUleF+jhkgTcSBLjw4vj0EJF97cZBcef+Zw26uVmpvHJEwY6AGO+cZ+Tx7qQjPYbNhor1r2nnygN/AUuErwbtcDX3mYL74vywTV89oZXgvfAud8yJa+XQvjfRHgKTvkHG/UvA7yc9qKHd/oh4DXgr462gCeonLA9/dfEIbcJOOod38QvS8WrFfHaN8/X0KoCdRwlq92fP3OX+bm9O0LzxmJRCKRSCQSiUQikUgkEvnxcOPW7QvFbmMM+zdu9u7b3j/gja9+ncOzx7AI7dNshs1muHRSi3OiHpvPKUfbrGo9D8+ekmbn9bn89m28XUdnh7YNl7TIhljeZXL82aX738yWbJUFJ8mLT7v/8dYOv3X8vH4t6tvOYvWIL4ML2xjwDtOMOq+E7uAO1vWcqFSzZFWUeBC6V47rldrr69eaDNd1ylUxrK+hgG86tFlfo/6rd6149X4B9MVE1QsRCYbs5rWaT20l/rcbVf1dp1XSuF9VxVwixBtfMsg7c6rq254gaNV6vwjdvbk5A+odiKm891XGZb5AtJoHNgl7n32rkUZg8Mn6PXHJkMM3f+3SaPDR6ZN2XXHvsPm8c9TVixFWfapfAzaft2PW6/rfF8/1Hh8+Jx0MSF7i9yYSiUQgit2RnyA2sQxGA/JlcBRranA2RIaHDf1femr7A1xMoWipoc53Wg1Ser4z/bD/izQ9ddi5w00txU7/l/+AXQosnmV7h4BjidO8is3uF3dTdnrFZkEY6z2cLihl1lspWxsDs+65BSFhC9WSkhlG1jEvXnJO+R4pe6S6hWVE2amZLVgGHODJwn2EIPlqXxDxQ78vGHiK4rXYzPIJPcCTVQ5rW7m928/XMGDIDRyznpNrFW0eVo/2R8YHl/1K0O/2TdWhGF7Z/lW2h7d5be/XmKT7m8dGIpFIJBKJRCKRSCQSiUR+7Gzt7HD31dd4/OCzVqS5TRJee/Mt0sHFhpLRdAv7xlc5PjrC2wHiCsbHD7BV/LIC2c49ytHaHT6YHbaE7jIdtfajulF/Wc3VU+XdNn1MvHJy5VFUMeJhzutXj5/yW5+9j4y3UWMxRcZgflxddB0xbgApFuE5eNeaMVuJyiqhlqPig3BdCfhSlthyWQvR9bTeytUNaNIWsk0naryO4b6ErgBK4xo/CiF63jeeh/Y4kTeNUZvPSOo9iraFeJEXdjdfxEbUOATXez7HuBJNUmTrAAYjyNdzz4LWz3A1K74W8wVv09Y9eZu27vn81pfD+3gJ6bK98ERUe2a2ryZdnpNt3Wx9hobnz5ivxG71DOYn+HREMdm98DxHz58xPz/nrXfeiS7vSCTyUsR/OSI/MUSEg7u3ePRRYwWkkeDOhqC19n0iraAGpGecIQrGhVjynuRvAPzE4BMwPWNRU4bLSiJhoN0z8EqYkGvGxvI8CJ3SMDBtDlBbh3DxKj7LGKvjdT3sDZqDz03BGxIyeU7joNVOCo4p5BjwvaJ0cHEPUTyCUOp5fUyoim0Bi8fRJ3qLCKoXV5JRHIjgdEHCZhSVIcGTbLjL1+1LVEqMKtLroPd4LTHS7/C+u/U1fv21f6n33JFIJBKJRCKRSCQSiUQikZ8sBzdvsbu3z8nxEWVZMhwO2d7dw1wSG66qfPrhB5yfzSEJpofB/LgWugHcYNoRsv2GmFcOt7tnfilxrxjvXLp/YQxHHXeqEDIMy84c2mrW7+5izl/94Dukquj8mDKdkOSztcCprp4bXE3Fictpi9CCT4e1cKsQnL2taPFsY3axOReqYulGjdMVfvvcyhvzqZti88a866rGdOtZ9PqYOvvXc7jSqC9eH7MR3d7j6u6+3uj/y8Wrh9rnVVy7eky+ZHB+WNfE9saQFMtWn/n//V83znPZ0/S2HQevyLpOesVyqz8lodXXThs1Fm9sK9J/LbWvDqo+D2a92MAWS4azQ7KtG8FKNZyQFAsG58/Jt26QLk6xLse6HPEl+XgXLhCzs2zJ4dOn3Lp778r+RyKRSJcodkd+oqSTAWoJtbcb28NghH6nsIIfGEzWEwdjQAdSH9c7IvJQ7iSkJyXSWVhYTg3lfviCticOP7Vo2jmJBsG7ZN4WvDU4lFfu4pxDUnbqGtVrLhaE10dIPcDtovjKxTxuCd6KZy4PKGVGWPPnEE02+jjRNziXD4M7vTneQyvHuq/bd+O/g7/c1e7sluCuQsI2Xpd42VypuHJkl4QIHMu0c25XX7Mrpiu+FsFXdb43FxIIKXuo5hvXNzpkJ3lzo0+RSCQSiUQikUgkEolEIpGfHjZJOLh569rHnx4fc352ut7gHenitHVMMW4L2abMN9y5l9XhXh90tchZpkO0MZPX5RvbOzhrSTTkFgarikFESFUp8a2WCvzFp/dJq2uLKkk2Q42lTIP5Q3yJqK5rQquGbY1z+GTUFm1NW7g2rlNDu6/zPc/oWgsCOkK2N7YWeOtrebcWOVWrZ92NEr94erfZG1FFve+5iz4T0otz2ft7Ed7Y9ntQRc7blbtblSTvLjZ4CTbqpG8e0has+1lu32J88mi9QT3eJOu2qhiXo2JCbH71OiQGKGqSsNgAZXz6GOMK5nuv1OkIo/OnJItTytEW5WAMCjZfMF2cMDl+iM0XlIMJsxtvsNh/tX5uJ0dHUeyORCIvRRS7Iz8Rlosly8WCp0+eBjHZakid0SBYh7GNBKM00BqtaeUiHprQpqr9rVbAriNSNr7cS8UUGhzhqVDcSJAsbPMJuG2LDkx9rF0odlGiQ8EPwo/aMLgRa+vY8CDQShVdHto7MkqZUeoMyxjDkJStqqa3Vm0uRzaGnKt7K1EpKLWoa4RnHJHLUV2z2zFHpcTqmIl/AydzjA4YcouZfIQRi1Q1xD0OxwyVtaPasQzx39UwfOVUpxadq+gjDKKWhEkt6humeB3hySs3t2flDQdQcRSc1s9mJW57MhK2q2v5WvwO9cK1XiMgpDRj3UPM+hCjKQP2EASny3APVG55hnx2/F0mg32mw332J69V9YgikUgkEolEIpFIJBKJRCI/KxwfPW+9tkW2IURqtzZxzxyQKfN2HWExqEjbZasONOltDzA+vM/+p3/YmIJsH/eD8YTf2T+ouiAk1YTlak5KRDAqVTnBwFAsX52t49ZVpFV/uRbguzWxW/ffdftuPgNxLxct3hWfRR3aLFe4ck83osWNK1hL2az/pj6ItZVIuqq3XU3+Nq65bnURcsX+6xJc5+3a7VSfsI3zd13jq+huMR2hu70YATbfs8+N1cKBRt8mh58wu9kwAXmHcQU+HVVtPGosxWg7JCB4x/TwU0yZh/dHJCyOUE9dbxutf1fElahz1eKIsG1w/pxiMGVydD/8rg3GPHn7z5Pt3q2c7srBR99gcvyw7laSzxmdP2N++jjUGBfBXaNMQCQSifQRxe7Ij5WiKLj/8afMZ53azEbANNbf6dqQLNXrDUTAViL3xj42RyBdw7AIOhLcaOUIX6+EM/k6ukgyxWRBEC/3Ld746hJSCa9d5zY4FnU/HAscC7zmTHilEm+vx9q93FgNuWov4MmrbVktdDevX8oZVoeM9W69L+NZq/+GFM+yFR+uNJ3R6xWmm/HqHhWPdDLjDRZDiGN3unbAN9urOErOq74kGF3X4hYMgkGx4R7r0wvtGHitXOaGhEnd3jLCMmr1SdXxw8d/F4BRusPX7/02+9NXiUQikUgkEolEIpFIJBKJ/Gzgyo74dZGQPZjUr70dVC7Vddskm1FM9toOZJsGFzhBsMTYKrZ7sy61uJK9z77dmX5cz5k9twn/7t17JBLsMQBOtOXj9qotoTtBuGsnuIZY362/vCGSqm6I/b4r9l+Xjkgq3m0uHGgmVtbCqquelWLKDFGPT0eh1niZbTqLJczgqa9KJcp6+0oI7fJ5CcObovVqS1u4rh/DSti9aiFAy8medj4vPRH5n1MdcPFl6z2Sqva8JmG+2otFvAuu6vEOeMf4+AHGlSx37+IGY5LsHOMdsxuvMzp5ws6jH2DLlQPdo94jfl0zXHyxmUgqBqrPZojMT5ger0uXHr71T5DtrR3ak8P7LaG7yeToMxY7d1gcvMZwNP6Rn1EkEvmTyTXyWyKRl0NV+fiDDzeF7s/1IpfsM4If9ofOiAfJfe9gqm5egj297kBk8zxO5ix5es32L8aAfRKd9O47lm+Rc3xp31J2MLpZB1uuuS4y54S+Wtuh0veICwuo1z3qVilatTdYJle2L5nXqzyvw7I45Y8+/U+YZYfXbhOJRCKRSCQSiUQikUgkEvnpMhi2zQ0uHW2Iu8Ozp605vmR5ijSEbm8sWEu6OG7PBRqLTwZ4kSAgVqLs2s26ZnTyqCWed7nhSt7KCxIxmJW4y9rYolWEeZMdM8SI8O5BEAVVZDOmemPu8przYZ12vq9OckufVfAleF+/Nq7cENYFMK4IIrwrMerDtmKJyRe1SNp3kTDr+HK10vsIQeaCSqM8ZO1G3ow5VyQ40Cv38moaVBqO7F6h+go2IvJ755tf/K57K45713mPCpJ8HgRvINu9jaZDdh9+j9HJYwazQ6wrEJTRyUOGp4+xxZJkcUqSzVnu3CJZnuGNCT+E9xf1VU308BxN9VxWtqXWDLKYVgR+MZxyevedVr+nzz++9F6nzz8B4ODm1fXGI5FIpI/o7I587ri8ZPbkmNliTrbMrt3u8posl7Rr5uJ0T5AIHsVulpTGlKCloomim2ZtAGym6KlS7F18fUdOIWe9+wo5AVUGXHKCKzAktaN7hSCMuIXXgoU8xEujDo4UHMk3SXWXAfsICXTc5YJhwD5eCwpO2qs4G8NYqYegnaGVKLkeM+Cg47wGwWKZoOpQShwlG8XWqdzpDXd2836lioz3FBfU6/bkPGfIrZ59/Tgt+OTwj/javX/6WsdHIpFIJBKJRCKRSCQSiUR+uuzfuMnp8dF6gwj59AajsydAcGynyzNAOL/9NjafMTpfR58roDZM/CXFElM+Jdu6gfEl4j0uGVSx4Ta4u1HEr2TUNfl0H5cM1g7YHradY1UF2W0IrZtMqvrGf3z7TX71ycfsZYtrPJEeZ7t3rQUAohqiuRvR4qHW8noKtXYH6+o+FQNIuQzPQ5th3toScAWQShBtbfuc3MvQ87y0Lf2qmOo9q56Hd1UN6UvOJ5uO/S6fixAv0qNS9zvYL6LuLyFmvZkFassl3obSmatZ3CQ7J5vso2JJlmeosWw9fR8VYXT2DPEl5XCLYrRFks1DO1UGs0OMuvq5WJdjOu9j27Pe09eO2D/ff21j0YbN55feb5LPObh5i529/UuPi0QikYuIYnfkc+X5ew84/vAx6pVix8LkmuEBdXZ5f0S56iWDDSFkFOgF7a2gpqrd3dNURdBU8APF5Jtf2XYBxQ4X5iDM5WMynjHkdl3HuknBOQnbGF4uUsgwxGnWG58jGGbyEQVnpOy0hOdCTig4qRzQplcUFgyFnG0YqZvHChbVcvPRCjhdkDClS2hvqybDup52+yDFa7YRP95uvxrIbvbdS0GhJy+0kOD5+eWrCCORSCQSiUQikUgkEolEIl8cpltb3Lp7j6eP1hHIxWQXgOHpE5JlMKBMTh4yWJyQTQ9wNgUxGJfj7IByvBPiwVVJlqeMTx5iXTCGFIMpi71X1iKohpjt7jyaG0559uV/ktvv/r0LRd3n6TpFsXvEZQmFeZLy//n6X+Cfe+8PeHVx3t7ZFUlFKlvIOlja23Q9e6aKLTNAKQdTMCZEtasPtb29qxzk6/tT1XpGMYipOSq2cUyd8X3hPbwQXdG3I2TX12u+J61eSIhRb7S/TOiuz9mJGv+8EO9Q25w47tT8Vn0hoTucotlfsyF4G5d3zEtBMN69/22k+rS5wWQjtj/N1q+T5RlJ0Vhg4d1mBP1FfWtvuLKJG4xJivb8cFiIkgBCsnPAwauvXX3tSCQSuYAYYx753Dj++AlH7z9C/cVf3pJ5zLm7YFAT0qt7w3nMZrK1VsfXn2IH+J7Bg1Rx5t1EGcAnoGk4cblj8IPNKi5ubDDebnRMcczkIzIJNbGHegujw84xikpBziG+J/b7OpSc89j8LiXtOHhHxqH5JoWcouJY8gRPe0CiKCUz5ny6cX1PwUIeoFK2ju+2F7UYRpv37+F7v/+Mb/ydj1jM8412VH0xDDC62d7oAMHiyHqu6+v+GsZY+uq1CAseUXD6QpHmkUgkEolEIpFIJBKJRCKRnx1u3bnLW1/5BUwzKnmyixuMmd18i+NXf4mTu19lsXWL+f6rLA5eZ7H/KrMbb7Lce4VyuIVPhoCSZrNa6FYxLHbvtUVDf7FoWo53wvE9fDCecDjYLBlYn7fnrItGLPpsMOLf/+qfZZY0zlGJuO25TkFtUttD3HCKJgMwCYqEiHH1iCpJNgvR4itxXgS1tu26lWbGY3XZavvnwxVzdlUN8nYsdkPore69JVN364pfKXTzud1PX7R4iP1e1TX32GKx3qaK+PKFLq+r/3gXfi5YXNEtRpkUy/q97NZ+d3aATxuGI1WSrL2w4lpC98U9rpkcf7bR52yrHU/u0iH51gHFdJ9iukdWFpz/0X9d1XWPRCKRFyc6uyOfC6rK8UePW9tM5vEdZ7ede8QFMVPH1b7V96FlMxmn863dWujX3Kca4nXcShyvrOBmvRLQjwRc5fAWUEt7oGOEcs8ipSJ5aO8HArbyGXsT+i3KufmYpTxEJXwBp+wyYAfYwWmGJw8iNEuEFMST63MMQeBN2NqI/76IY/NtluYh9/U/Zsw9Et0CUZY8ruPBPQVecpb6mBG31w8SJZdjSjnnTN8lYQtDiuJwzBvP1tcPUztrTw0pgg3ttETxnB3m/J/+53+X730zvOcHd6b8K//H3+Zrv36HvkGsZYhhgGpBkL93MQyYcx9Ecbqsr9NdDZgyraPRPRmeEqUMz09gwQNEUxKmJGyRsnXhs7yx9ea1nnkkEolEIpFIJBKJRCKRSOSLw3K5wPv2nNVi/9XLRcxOlPJgftyadSpG261aw5sO400We/eCmNfgMEn5j2+1RXBD1929ed5Tn7NlUowIo7LgX/zoOwyNDa5gVUxZ1C7dEHu5iuEW1A6qOPJqel+C27lZq1zQUOO5Kw5fIbwKYa73aoW2p/Thqi/1OS6Z/9R1DDf1mbrXbMfJ9wnxXbH+omu1T73Z9+aUc+8pWD1vDbHpjevbcomzA4zL1/3xJSDIdV3dDRf/Vfe0mQDacOpDHd2/wg26yZq6EVf+wu7z1ZW9bznb0/kp24/f5ezuVwHYefA9Dj76Bm4wQW2KS4eU4532Sbxn8f638NmCnT/7z7xUPyKRyJ9sorM78rlQzJaUy3ZdaJMpUjS+JL1SacPYTBGnyGqcIawHKiu3tqE3Ort3X2O8IhAEbcfml7QNkeWadKNrGqdKBD8x+LEB2x08GYxaBn6nFroBUt1dX4IhKdsM9aBqY+uOeclxsqCkE0l0CXOpBtCiLOQBZ+aHzORjmnWwtXJRq5Q4FoThdNgfXof2pZyRyyGlnHWe7Wog1WOfr/6ZEARDyvmh56//1d+phW6Aw8cz/o2/9p/xvW8+ZBNptB9UNbmDo7u+B9HwbFi0xHapjg1/N1jG1UKB9jodlYJCjlnyGCP9cfFWUt44+NO9+yKRSCQSiUQikUgkEolEIl9Mzk6OeXT/080dL2KX9W4jRtknm07sq854vHXA39u/yUejEe+PxvynN27yf3vtdY6T9VyVquJD3mPj9ea5CzyP3ZxCPb/18ANuZnPUWMrBBG04rnv7JIImnXKKqlf2vw8VUzuW13L/VcKnVrq7bP6sWl8mdF90jZdwYF/vrjtpoKqVa3p9t2oSvEkuvHM1VbS7GLRy0q/d246kXLYi7mXlzL+KTqz8j+5B75v33nzdfW4bjnku+BS05tsVUQerhSjeY9Rx5we/y/ajHzA4e8aNj76BIcSsm3we4tUvILv/HuXJ8wv3RyKRyEVEZ3fk86G3njSkRyXFrkWH7cGNKNiZx00qQfnHkEItgJZAcp2ViC/GSG+i5S9wZj+oYsD73MxjRnqHQk439jlZgAoJ0ysd3n0xR54QGx6c4u39Ocek7GIZ9baFpnu7r5b35trTFSeHC/61v/o3+fTd4419y3nJv/HX/ib/y3/7n+Vrv373slui4Cw43rsIeM0wDC98LkJ4bo55LfIDDOwWv3zrX2Rv+CW+++B3mOfrPo7SHb5+77eZDvcv7VckEolEIpFIJBKJRCKRSOSLxZOHfeaKF6Nvhky6kcmdetjhmJLps48ZnzxCBb412eI/39nB7+0hEmbVphJqZhd4VDX8WbXXkBNZ9UHoFhFcquN4ecyXTw/XG43pdwNfJWBKp1Y0QXBtn0lC7Ld6VgerGGjW6O66ujcc7y8nqn8e9LvO2/e9XiKw7mdo56m9f+pa29QktWvemxTji01HuYJocM6ryma8uOracf0ibu5G+xdu04tuvIemzKCZhimCS0etmt2rz8r6OQbRfFUvfHMBw/r5Gl+gjRqixjvufe9vUQy32gY1kapO98VkDz4k2b1xxT1GIpFImyh2Rz4XBtMR6XRIMcta28XD4MjhE0e5Y/EJmCpNRxwkZx614I3gt806dvxFETYGc9Vm1PFj+aSP9S6j8jaZHIYr9WizCVugQimbTm4nc5wusExJmV54nam+WdcFb+LJ8eSVaGxY1chGlIJjSrWVGJ60ROEVQfD29bBkPfAQwIaht2g1cLMNofvowr6uBe+/zNd+/U517bXLvH317II3TfEsQQ2WER6Hob2yUDAkbKE4vnLjt1Bx5P6Mk+JjJoM9/skv/xWO5w9YFqcM0y32J6/1xPtEIpFIJBKJRCKRSCQSiUS+yGTLBVm2vPrAK1Bj8TYNtZQrksUZ2fRGLQrafMH4+AHzG2+E/dk5d773t0kbtY1/8zm8PRjyf3/jbc7SIVMzwFYCoFFhQdmWhTtis6yDyWtuFDmbfuIe4bMr8npPt/62t4NatEVdEPQb7cS7lttYV0aYlnZ8mdD9Y+Ya8emiDpVqslc9oq4tdK/i3jUsPmjGjau66u/Uf/rqHqVyJ190t6Zqe6GD/ic193jFMwqpp64tKquGz0sV258uzkiK9Ty+KXNsma8Ph0bEvwmf2Us+BgJhDrnj5t+M0b/GM4p1uyORyEsQY8wjnxv7X77EzSsC1qAjs/G9KA5soZjlJbEu5RWDKpELvytFAf8jDspcf3vBMNKbjPTGhV/4ljGi/dHaoFgG1d/673/Hf/2S9uuebJxZHE4WYcB64e0r1KJ3d51nCB5X/LWE7hVB8P4bfO+bT+o63N1zr8/f4+6u95sq7nx+4TF7ozd4MP9HfPv5v8cPj/4G3z/8T/jbn/4b/J1P/7dMR3vc2/saB9PXo9AdiUQikUgkEolEIpFIJPIziH/JOb2+Vvl4XYbQm4Tl7p1a+DVFxo0P/gE7j3/I9qMfgHfcevfvt4TuFbfzjH/pwcd4IGmIe0ak4em+Pud2c97Pd2ouBzGxit72Jeodqzm9+sc7NBmgNg1Cp9ggNK7mxbzvCN31mb+YXOB0lio2HO+DeN/a2XRWV6J/c3dnixLcxkZ9CPbWEMN9VQj4FwrVjWdlyrx2npfpGD+cBjHbe2yxDJ9rqeqFanV8k84iiv5o9KvpxribMq8+ww5xRe97nN565YWvE4lEIlHsjnxuZGWBGwraXPwHuKFQ7oRBmxrBD4VGqkmQW9PQyCz9Zv2UUhl9sCR9XlwqWpu5R7Ju+81EmRfCK/a4vPIwRcnkWVVzuisaGwbsY7RdB0jUkrKHIUXxzHlMzkmrfcmCE/kWQ25vtKcSi0Pct+LoW+VqMAzpH5Jdb/B9duj463/1P7+W0L1iJXh/95sP8GQ4Zh0xv1oxSTWo6nRLNMUwAqjur+sODyL9s/zbPF++t3H9p4vv848e/T+u3d9IJBKJRCKRSCQSiUQikcgXj+FohOkRg5uk82O2H/6gfr2qv6wdl2k52iYf76HAcucOalNEPeJKps8+rGt6Tw8/5e53/yuGs4trB39lPuPV5Y/uOAd4PhjyyBjSxSnp/IRkeR6E6/qGdO1gVh/ipq3tOHc7s3+qVdzlms360S8nYL4MG/7wjshZC+8tsXrTQb06j3Qc3a3z1jHt1XyiXHKfKxd4c9M176nd6HN4ji9yjtXzq13mbcFbUGy+BFfi01G9LSkzksVZ65obCwZ+FDrvq7gCKXNMvsAUS1DH6OQx4+OHjKs/0/lJ3S7ZvUl667XPqzeRSORPEDHGPPIj4fKS84+ekZ3MOSrO0dTgEkUcqIAfVzW5IXxpOYVEcEPCYMIrmgRXtj2vVtDlilqqmjGCXXiSTEkeFAweF7iJpdi3uN3Gx9cppghf7popmoBaQRODmCCyvyjmzJGeuHVd8cuegyxRcRScgp5jSLFMate2YBmwj9cSpaxcy2ldL7tkBlKSccgh3ySVLTwlOc9BDJYBY+7hNcdRhJrXzdQishD/rTkp+6zywQVLwXHlbF7FJPXFD0mjdret258dZvz1v/pf8Mm7h/Rx781tXvuFPf7R73y6sW85L/jX/9p/xL/6b/9FvvobB3g9QUgQLAljtKpaFNzjVR0dNZhOrfHwDDf77Cko9IyLeHD+Tc7zJ2wNbl94TCQSiUQikUgkEolEIpFI5ItLURTYJMW7/mjjdHHKG9/497HFAltmHL32y2gV5a1iUS8tUTSf7pOPd1rRyoIyPnnUOq917VKNfdzNFnw43Wu3w+Aa5QRFZNN1CyE8XAS85698+B2+dLS+fqihfbFHTZFQY/oyqjrL3ZY/CZoy9brWcyXJVi5k2RCyK0G6juhu71dAbYKuaot714qkb5yl/fdLBGTt3f+Te0Y0ntHLnaQpbrOOGl9F1qNgk417ND9KTHjjmiqANOd1Pa2A+GpBwup63lh8OsI0Fl2IetLlGcYVuNe/xs5v/ndiQmckEnkporM78tLMHx7z6X/6Rxz+8aecffY8DFYgDCYTQXsE4nqLE9SCDoOQLL5dK8U4kDLE0jTjzUOdb8fwYdGKNpdS2+1LMJkiXlsu8hfBjw0I+OHVX7BeGgNg8XjJKDnbcHkbEiyjqpb2+ryOvN6fyBZLeUwuz1ejskb7ASlTBmy3zruqya3i8OQYUgwJguBZD/xW0eSXD6MUwXB2mPGv/ct/8xKhe4f/9f/rv82/8n/+p/jNv/xG7zHLecH//q/9Lt//5rNq8UKJl6zq0/pNX/crXH/dX9vY3saT925f34VyuHz/0mMikUgkEolEIpFIJBKJRCJfTLIs44MPPiArSvQCAezgo2+QFAsEuPPDv8ud7/9uW9wzPfNKZtMpLh0BUK8xbX5mDbkvmfuSuS/IfElzXktV8ZXzdvVjACumFvT+0uNP+LPPG0I39AjdHRe0tRsC5ibXEW03j+nd0hM1fdHZlUqsN6ZacCBrZ7VItX11rDTsLZUjuyemUxF8MgwCfyWIG1deLRJf+Yw+P1FVmyJw4+fiS1fPonoGre0vSX+uZ8/WzjW0+n1oLUFYOeN99aOr9yUcpQKYJLQ1YXFGvRCB9QKP5pXccHrhIg5bLNn5xV/DjqcvdM+RSCSyIordkZeinGc8+Qfvoy4MPqTn21sAyUMM+eoLTrv7XNjX9+UvBMG77zvZFMr4gyVmdvFKNKGKRX/ZGPNEyG8l1xz39NXMLsk5urAWd7v1uv1Y7zHy9y6t050wJdUd+pT8klNKzhvX7buBzZo1azwnh3P+tX/5b/Lpu8e9R9x7c5f/zb/7L3BwZ4JNDP+zf+svXCh4Z3PH/+F/+l8Hwbvu4wxPTzy8BJe64hou9Iu4+o2x0o1+j0QikUgkEolEIpFIJBKJ/Czw5MkTnHNBNDUJvkco23n0w9brcrT1UtcqxjtrQU8Vnwz6hcKKM5vw3nSbGY4MR4ZnjiNvzAP2znc2hEZR5bced9ISu/fYKzRfY7Ky51l1Y921duW2+7uOT29Egbf6UQdnXzxz12i3qrFd/6z6J+v5yeZMZXfWUrvu5JUo/hPiqvj1IOibjmjdI2Q3z7d6L2T9LNdtPz8R3rjKLNSo6+1sihcTnNZi8DZluXWTxe49FnuvkFW17aV24K+9+rVT33Tfk8s/lQp4e/k8bfn+H7/cTUYikQgxxjzykhz+4EEtdENwXEvu0UF70CSAFIoWYM9L/NjUx4gGwTvU+NYqOJuN9n5oevfZTJl8kFGODcsvD1DZFN1FIZk7ysHLfdR1YNgold2lVNJySLG1GamtEqK2B+xe2NxXseZNRtxhqLdwOifnhMJs1stOmGAZs9QnOMkxq3MIlJxT6gwhoW/YKaxjzWVVZL16eKeHS/76v/xfXiJ07/Gv/7v/PW7c2SLXYxBfC94A/83f+GSjzUrw/lf/nb/IL/76TRBwLDA62oymkcq1rWDZq6POu1hG9L7pFamZcGf6y737IpFIJBKJRCKRSCQSiUQiX1y895yenra2bYhp3mF820xhy74kwEqiU1+LjMOzZ0wOP0XUs9i5gylzhufPEfUogktHlMMJSTbbuK4H/qM7r9aO2L7+aY9I3T3PVpmzn7943W9Rh5J2tnZmT7vX975Vs9sbi0+GACEOvE7sDKeq62I3zh/uqR0u3hc53YypbrZoh243ztFzj832XZF+s/b4y6KN2PRm39amrdW1pVoEsUEldNena95x5ULfmNfeeGbyOYr31ZtXXdUWGaOTRxiXI0AxmODScV3vvY7EX0Wfe8dgcdo7R79+0alz3it0dyfp5UoRX4urSwdEIpHIRUSxO/LCPLj/GfOHh3R9x/bcURw0az839i09yUxxuae82f5yC1ql4BPF9ph9SQQ3NSSz/oFMeZCAMfgR2MXmMeIIDvIr6m5vDm6ugSom84hPSbMRxXBzgOpZorrTO/gLVaszRCxGU7w0I8cNCVsYBuQ87xV8lZJMnqJSojpsX0MUpQiC8AWisGio6x1uxXF6tLi20A0hVt3rEoQXF7yrO7jIoW0ZY0nxuFDHqHOcYML16R8IvbP3z5CYYe++SCQSiUQikUgkEolEIpHIFxfv/YZgvDGLZCzZ9IDhbF2Cb/vxD3n8zj+1nuNTz9bTD9h6/gm2zHAmIV2eMZwf1efcMWkr7lxQkmKBd5bFaIuZL7lVidIfjKf8zs07vLu1+yOHYGfG4hBsUxhUbd+kCNoVE5XWPKa4EilzNB0FIdK7taN35Zxu1C2vXbZVe58MkCJHcEHJX+m9Ted3I8K62Y0ul4qk3S194nEfPeLwtWg8o2baaPMs2p0PFoNW99qsne5pP8P1OZttpeehXE/IvniG9MVZXy8I7bb6LHgxuHTcul817Uj8sLjj8v52Fx9cC1XwbqOEgJR5VXtdsIM4jxuJRF6eKHZHXoij54ccPT9k0POd5rYtfmQwuSIrzdkrZuGx52GDnxr80IQa29UxCmBBU4Mrtaq1vW4vc8/y9QHpiSN9WmKqWt1+IOS3U8r98DH2o1DzxSz9+twG3NhcT+jOFLGKJlevNAs3vBK6w02MZnsYf0Y+nKMm9NH4hLTchcTXYS8r0dZTBgezBHf1kNvM+RTFY6pfzZxjzsy7WIY0h2VBxj5lIZ+hUiJqSdhGtajPCWB0RKJTCjmpB2rrBYr/f/b+O16SJLvvQ78nIjPLXH/bd09PjzdrZtZgF7sDYA3MLgDCEBABQqAILgCKoCQKfO9D856eKEOQEikBlAiIfCIoiARAiCQIkuBS8IYAFm69w87srBlv219fJjPj6I/IMlmVdbund3Z3FnO+86npW5kRkRGZdbui4xfnd2Ke7Ngfx94V5Yfe9ZuHWpePhO6RSB/IERJUSxCdEryFP/zlJ+baqAvex1gP94Eoe/IYpRyMH1pCB08nviWnJMfTmgjzBAr2493QFKWYiPkqCAlXeo9d+xkahmEYhmEYhmEYhmEYLzm896RpSp5PAkMQh+QDfBEDH8ok4/zdbyMkLYrWEn6wD05wo4jdEDjy+AfHwjZAe+8iybA3fj/OL92ACyUf6nT4+ZNnyMqYSnHg49pUcgNW07OC5tAnfGL9KPdvXRwfCz4d20eP6owEWCEKlurTiVCsiiti1K7mfdQlM8K2TqzDx0g8VomgWo11XEcBmRJBdWJjXWvlRbDbvq4WZgRpde4Fpa0cS7dT93FyfUVDqEdoi5uPYhcH0hDdfSP3YPaDMBUBXmv6etqqPaOGzQZT/ZsTupkac8Vkk8RhNFnrz15bauUE8MMe5SjNQAik/d26M8MHf4Xy4lO4b/oBJDXh2zCMF4Zok6eKYSzgkU99hn6/j98raT03mWyqQO/W1kRUDorrK9lzeW3XYP9cBsmkDBC/7WYnBqXiDgLZhYLQdQxuqrzEVWMebgXNpkTp6SQxqpMJT9LQdhOl4obTk0hQL5A215VeiZuOQp/adKkowRdo4hCfUvqCkNRzi5cMmCj6UbD1tAgUPOH+JSIJSkEpPTLdIKE7dSlll89QusnEPNHlWEYlit7VvlBHwoBLBBmM646vOTUF2blS8Dff9Ys8+ZnJTthpTp1b4b/96XeweXyJOA3MAcXRGrej1X8IhEL5sb/2Hv7wlx9vbK/VTfiv//HX8ZbX/ulqf6NSss+QbQbuYq3NeuS2VEL3HiDVJoDRuCabAUb1v/bW/4611pnGPhiGYRiGYRiGYRiGYRgvXS5evMj58+fjmxBo7V0iyWOEtQJFeyUKvxXBJzVr8e6Vp1l/9sFJg6GkvXO+JsqVLpmLNp1mK0n5obteNSfvJQ3RrXN25wuszEcCZKnKid4uf+WTH6JbFhRph7yzVllJb1e26zIRQzWgUxHZCrh8ULMNB+rifZWHvGYlPm1DPXMeQKUe7YuGeevwGxT75yO7r52BPDg/ec6quFAgoTy80ux1p59XNZb6mF2tTKwzI9+WxXxk++xnp0lquabt+pTt+aTlSf8WyTcyey8POQ8MOmu13xdFau8Bsv3L49+xRajM1Kvygdd7T3Wsfr+K1jIh65AebM+lIBh3+9434d/5vYf2wTAMY5Yb8JwwXs70+/HLrlxyMWK6QlOpR087IXQdYWnqI+aYCN1VGdyCKGovhGVHaAuhVbeDCR0fc38vmlRJ1RcfI6mvi6k5hxCDhKXQiSA/g2slC5sWBF+m+KGPE1E3P6FxJLVNcCOLckfChr6WQnYppVcdq086BKHN8Zn6lUlDZV3uaY2jwwN5ra5QtwTfvtK/PqH7RLe6MaEae70dqYzFRQWfOH7wh9/Cm7/+lsY2BwcF/+Nf+A3+6EOfGddNWKbDaRJdmio5e/9Hkz1fs3WXcZS6q4+t/3Tj9Q3DMAzDMAzDMAzDMIyXNkePHmVtbQ2gJnQDhKQ1I9zN2yt3tp6tvXdlPr+cdw3Rtls2C3LzFutaCzLJ8KzITF5tqbINogRVAspznWX+3j2v5+NrR8k7qyCC+oTB0ibBJaOLVfUdrhzih734yvs4LZFpe3FxVKub1U2pC9nXyrfcJPJet9345wnREC2wAQnFDeTsnrdBP9RefWEz87HLhBDF7HFO76ZXFUE9fjbjJ9TQdnOE9rX6cj3I3HPUuWdbpp3ZEvPbEaoNEtM/Sy0QifEmDZWJ3C1AOtgj3buMhGL8qZ3r1afej+5tvdDhGYbxMsfEbuMF4SurHkQYnE7J1z3qiDmxGxieSMg3qjKjfDLXiwjDUykha/jyFgE3miAeQtM3ZuO1mg/JQKGY+uJXRfqBMCgpOw71i5sXBdfXRludGHWdEW/MqKORdX0lJ8q3k+l6dWa+gYx1lvRWvI4mIJMypfQo2EepJoGHTI/KMvB3fuDXFwrdZ84d4b/9qXdGoXum/4dOuxS8j4L3A19/W2OR/kHOX/+BH+GZJ89PtSss621kenTq3tSJWcY7Y0vzw8h895plDMMwDMMwDMMwDMMwjJceIsLZs2c5e/L4XLRpSOo2xzor4tJkydwgcV5jrfJ8q0M6s4SeVGEY42tPWY4rSoKj6xJS51l1Wa3sqFw5TngIz3WX+dTmSXzeJ+3tkPR28YP9GMGsGl+hxJV5ZTceZUJ3WMQ2zEdsQ4NIekPm2S9cAK+if6fXWK8nqhupEjCGAlcMJkL3KOL9RWNBRPZUv3V856e3F+jkGVXlFwrZjWOeH8eLNqqZZ+SK+u+D+pQia4/fB+fZ37yZvBWtxrUqoz6pBZ2JRBt8QtnwGZt+vg1dolqrHqUPcJ5abniAENDzj7/Q0RqG8TLHxG7jBbG2sT5544T8WErv1la0GV9gl1JsJvTPZQxOZy8on8roGuWyX2zF4qovwv1y8STrGoK39APZ+WFjfQFcHvOGu+0CGSjqBW3HyPHQ9YQlR9mVxkuIQtJfJNr6GIGtnUlkdsWK3sHN5XdwrviPWQuvbKyfscqq3kU3nEPIaueCDMjZZsgWh02R3vsrj/PIJy41njt1bo2/+ZPfwtETa839F9coxE9Hjrsk8IM//DYe+PrbG9vo9Qb81P/+7pn6nq6eYVXvQXSy43H2Gm5mzLO0/CrHl+49tIxhGIZhGIZhGIZhGIbx0kamcmyPmHV8bFr9KirRbkRIsvl6ZfOa4Ij3bZ5gyacsSVy78wipeLy4SsSejfCGDMdQSwZV7uxUXNRmp/qZICTiSMRx/84W3/r0o/hiiGjAhYIk79VtrGcjtOdoEn9vJCL72nbYMYpeau+DuGtebWy+fr1C90zdF+DheU3m+qoBtBy/onDNRNoeRS9PiexN/ZnPY/55ErJfIApxs0BlHV76jO3T97J34g6KrIMCw+UjaJqxc/Iu+ivHUJdMIrRdQpAq8GhqA0Zts8h4Y0C0vR+L/6N7JhLFbTezKUME3IzgnRy+7msYhjGLid3GC+LIsaPzX9pO0MzBcN76ZILE/NeHRXdrc32BxXMzVVwv4BXksOsviDwnKOnVAp+DO1igxFc78sKqR9sujmP6HjiBxMUc4g24ITBcnEdmZL8dmLdFSlmmq2caRWWAQEFgiMPjtF0/KYCEmFdb08b621cW52B527fezebJDnBI+DrNIv+od0gUvL/lXa9ZuNny6pWdxuN9OY9KWbMrr1/58OnhnZtfi5Pk0DKGYRiGYRiGYRiGYRjGSxtpyo89a2U9tpGeUM5Efyf9HaScrNFJWZAUOT7vN64pfmDzOA9uHgcgc541l5GKI8GRVmK3R0hxtPBkOERhV4dshyE7YcjVMKhE78l/Dhmvr6ah5Luf+BR+aoVNKpF8anCfP5G0acFu+t6Oo5pHPQF1CSp+YtTtPDhfHW9YK5y6t1Eg/kLbos/YilfpGZkSYaWKIB/fDZEpZ/Gm/l57U8Dni9m4Lm04Njk5enZxjGlvF1cMONi8KaYCcAm7J+5k/8hZVASXD5BQsr9xU4zoxlUvqf3ONToJML8BQGY2RdDwuzxVOJbprCBn7rzWbTAMw6hhSpDxgtjZ3kErK2/NqsjqUvF7UdgsnRCVZ+KX3WgOUX3bCnGDXCwzMwEIVNvMpupXiIKG+nHJAzJQXDHVeBjVrxuoJDsl2hLKtou5vCuRPN0qccPqS98LUmh0zx5FjJeKFEq55q85YQlth7qAGyoSiCL5QCEf0N+8TMLSjP12/PoXhEBBj+dAINM1UlZRSnblUa64D5OxyvSURQmU9MnZA1ESXWFTX8cOn2LABVRKUCGhS8o6SmCol8nZmTwMPPc/cA7n309o2AzwL37s/SyvZXzdd98xVafqtwqOtLKmCVO5V6TKUFSO65x/sMv/8Bf+1cJ9CPe/9ShDrpKxAUDBAX05Ty5XqzbdeMyje6AEAvlCIRzg6Z0PcveRr1943jAMwzAMwzAMwzAMw3jp0z1yvFpnnCwuJf098qWN8fuVC58luITdU3cDsPn4h1l/9kGKrEvRXibp75L1YsCFhijauSoPtK/swcskRcUhqjy/epz33/wKQtGLa6FAimPZp/hKsBuEgn2dBK8UqhQzkqOfErabuP/qJbrlTJDMi5Yjux55LhBzjcs4xpoYC1dOlZy23K5KVWu8itbs4hVfna/W50RQPKLNec5ne3ZDXO+9mbIOb7z/h3bgGr3Tz+PmA0ZW35NrzZ4b3e/pHPGIq4Tt2lOsN6iV/X0+ILiE9tZziCqlT8n62yTDgyroLJAe7MZKVT0XivomhVkb+et6Lte4a9XnzL3pm5GkOXDLMAxjESZ2G9ek3+tx+dJlevsHDIcxt4cA2TN5nA+FeGB4PIlfWeVEksTJ3JezUG0QnE65rDrZWBdGX9wahekKqYRzRZFBwA+nxF8hXktH19fYt0Rw/SpXykBxgxIVcP2AH0zVT6NwLwEkVPWD4gKUnSYboGY0c5RZHE9ysSC9WrJ76gAECvYpdB8QMjbxTHaXFuxHDZnA4/5fVpPDHJWSdjjFZF9c7POAq6hMJo4dPY3gWNW72COLNyHuE0UJCI42J2hxHNWSHs+CKGdv3+R7/uqb+Mn/6Q8bx/N//K3fo2TAO//M3bVn5ehWbfcn8xSFQACZTNAf/cQV/sfv+3l2dw4a23/tW27ia77rHFvu44jG/bBeWnPlRtHvt258FceX7uZ3n/l7leA++RBN7VMEYHvwFFd6j7PZuaXx2oZhGIZhGIZhGIZhGMZLH5+1WD19jp1nHo/vB3sxh7dA3t1g6dJjrFx8FIi5nQfdDdaffRCAZHiAywf4YuJuKGjMNzyFaCDJB+P3x68+zeXhHTFqGfBVHu6RcBpUa0I3wHAm2tzRZGtdZ3M4OPT89VM5XtbyQ88Ip1AtyrrKhjyuh6rK5H7I1ELfNBINvWuRuaM2ZnhRheAXKvzP3u8XGG2t11ln7r5eZ+vT9VQcRdrC54OJxft0u41pPaeiqXW63CQUaT7GWyfOpeLorZ+ivX95XDc7uIKb+uwmgwNcmPpsjyzJJ61xXaO/gUh394avx93/1hdczzAMw2zMjUPZ3trm0c88wtaVqwwGg7j7DwgtIXRdFIcB9dQjsUevw/JoB629r1mcNJWZPpdJjMCuHZx5G6r6M22IRnF7ur7O/CbUAtP9DUzRqlzlIRWKbGryHG8KOds1a/KRhbngWNf7CAxidDbgmN7JFu9sympt3pLQqc562hytTJSaJpuCI6HFkXH9b37X/XzPX3vTwqH8k7/1AX71n3+q1gVlSNNDk6lJ7qMPXuZvf/9vsruz39jul73lTv7qj301Pql2I0pJkCGBvLG8iOOOja/m5PKr2GzfNje+6VzhI/aG5xeOyzAMwzAMwzAMwzAMw/jSYPP2e1k/dwdeyyh0A+3di3QuP8nyxceQMkfKnJULj3DiM79bq+tCPmd7fq3VviwEOsVUoInzNeF6oHWxXFWnvA+v9yqwnTXlJq7XG9lIT95DKUnNWnwsco7TRI6E77pp+ChytyaMi6DOz+Uzb+Q6heAbZjZi+KVIQ/+UGW1ap59FVUImK5eKULS64FPKrBMj5pn/xMwYsMf2QhlfGqrNC1Ve8aqUzNzD6S0J/dUThHSSClNCWRO60Rj5XRuuNqTnvJ5nNKcLzH8yFCGIJzhPSFpw0z3XbtcwDKMBE7uNhZRlybNPPT0WuGuIkG968nVPSBjbds8xEqyndhPClBhdjnYdNlxiVKZB8Eai2B4yiVHdTUUAiuZzOKEc1Ye6S/fUNfBVH26EROjfnCHOz51SKRhwiYKDGKk+9avY1TMcK7+CVjheRbLPTyg8LVocwWkLFEqG43Mpa7T1ZMzhPb2xb7prLNHmBL4q863f+xq+56+9eeFQ/skP1QVvlZxAf8Hs1fHog1f529/3m+xvN+9OfdNb7ue///v/KVlr3lyipE9Jf7wZQAnk7LGvz/DY7m+zO3yOy/1PN96XWdrJ2jXLGIZhGIZhGIZhGIZhGC9tRISNW+5iebW+1rN86THa28/T2r8SX3uXcAtycL8Qej7hoLJSFiCZyTU8L2w3ce0yH10/Sn9q7bBMMnaPnRuL28F5euun6K8eH8uZwWfgPcGnE6G7FpE9YzfdJHjfaER24/qvTgmvVUtzYu/sxaT5tega18OLIJLLwuvPHnPzmw1kSpAetYXW34+cAZJqk0MoQYQyyWLQ2ChHumr1GahH08vkaO01Pn/IPVBx5J2V+ijCjOW8hhv/HFwTqekMQRzqE3AujlEDxS/8I/Lf+Vc30LZhGC93zMbcWMj21S1COETpFaFc8ZQrPn7BTdI0z6EKozQuo5nAOHq7XDz1G1uei85PWETQlqAtoiBezE/KYtS5oDTkUnFCaAs+L+l8ps/eq7s12/TRNVxxPbLqAhLByQrQmzulUpCzxUAvolIiUxHcLY5yLBxFUYZs0XfPztV3ZLTYpB1O0+YoQSbCcsISCUtV/asMuTxX39PG00aJNurf+n2vAeCnf7jZ0vyf/NAHAHjnd99d9X9klV6f7D/24BX+9vf9Ovvbw9kmgCh0/62//5dptTJyfYpC5iO/AzklQwp2aw/1jy79LJ+8/G6i7U+Bks5df0Q3PcKx7l2N5wzDMAzDMAzDMAzDMIwvPcJgkiqvtXOB5StP1s6LBnwZUPFRSItH0Soh3wgVB1ouFPY+dPQ0pWuOtm06JiI4rcfMBMBP+VYLkCDkVT8cQjtd4pduuZdvfexBRBzbp+8hJC1C0mblwiMMu+uoTyh9Qm/9NOn+Vdwo0lYcwaXIIeNY1N8mmqy5m2Jxp+2zZRxZvLiN+c68hCK3R+JrrU/VGMd54qdl7Yn9e9Sxq/yeU5sNpu+BTB2pbTgoC5JisMh0fKbNSVufC8GnNeG8EZH5Zygxr/t0P/SaT1onf1QW+KOUAFX8OTQEiAGET/w+5ek78He+7vC+GoZhTGGR3cZCRvm5rwsR3H65eFeXYzwJoFxgTd4vm23LVWk9MTh8x5gT3DA0R4EDfq9ZrpZCaT0zxAVoPZ83X2NRdPlcueYySdEmO+g2nlNCzL0tijTsPRGEVFdIdb25bV2iw3EcSaP9d6y/htfm64/KJCwB8K3f98IivAPFOFc2wC/+1IP899/zy9cldAM4bdfqj1CUkt7cnEkpKXQw6jiBYWN9UG5bfxtyrQmcYRiGYRiGYRiGYRiG8SWD7yzHHzSwdPXpxQW1rAmZOiusiaDiGleVnlpa5dfP3D5+H80p6yVbUm/PI6y51vi9A5YkrUWEt/Ck4smqJflll+JFeGjzJD95z5fxxInbopUzMFze5MrN99Usp0OSNYzj+oXserVQj74e53OMEdqqIdqaOw8+iX+KGycRjJkawzjSeKo7Xzxm13Wb3k8fW/DzJCJ7IuTPjUunhG+YRLbPXHMS0129qtNuaoNCY/vTQvf1RlFfYxOBhPm1+zD3eXKTqHMq01aXzFvcz97Lmc0CkzFp9VmaWaN1h6/Zlp/4/UPPG4ZhzGKR3cZC0jRdeM5vF4S2Q1PB9ZX0Uk6x6gmpVOJwVVCYCN1AslPiDwL5mkdb1WysBDdU/IGCKyk7jtCKX/7pVknr6QF+P5BuB/o3pRRrSYwSn/nS7z7SBycMjqcUq/GL2u+XpJdz/ADKfqBc9mgW+5huFWQXC9xQUYGQCn6nJHTiuFQETSX2xV1jqlZFthM0jlfiPUj2Am6vxK1v4g9aDLM9Sl+gUqKUaBWOLprS0ZMMuEIu25XwrQQGODKOhjeyL09yIE9TcIAjpaVHaHMcwVFwwICLJKyOhetIwJGyonfS1wsM5QqBYRWCPzItEnJ2KNhDSPmW77sPRflnP/zexqGOIrzf8d13AiWBgJDwz/7uh/nFn3xo4S16w1vu5m/+/f+MrOUZskVPnuFAnkRRPNk4sl0poogti+Lpp3fhKkGHCMk4wjtmSCp4ZPs3uHPz6w617zEMwzAMwzAMwzAMwzC+dOievYPeM4+S9vdw5XzgxwihirodidLOV/EsJUkl0gXn+OzSOv0k40R/n75P+PiRU3zkyEkGUyKgR+bEyEQcXUk40AKHsO5auCon89UwoC0JTgSHRMNKwFVrVIk4EpWaEP7c0hr9wrFSTmLDXaPj5rxsfU2qyNrgk1g+lLhQIpRj2+7ZOF11fi7ytnalWsTzS5CREDsW8heI3DN1dGa9eVbIrz45tYjsa0jMNxChfYMW89fAhYJkeEDRimvHCpTZEq7MY97uyo6+TFq4MkdUo0jtHIXr4oe9cX7v8e/X2Gq92YZ+tPo8nw/+8BHp1ec/9wEbhvGywsRuYyFrG+ucf+75xpzdmgjLn+yP3wcPg7MZ4zzXTS4kqvj9gCiklag8aUCj/lpGgZg9cL2SzhNDVKIVebJTsvxQFEAHJ1N6d052NvrdEj+Ik6zuEzHyVx2ElhvPPHxf8f2Yh8QflPjeZFxlx4EXXAFuN35pF6uOfG2x4F8j1G3ZAZKtgnQ7CvuCkOXLZHncfbq79Ax5OrEdT3UFQWixyYDzBJlERnf0JIJjWW9hWW+J4+dKjAivyGUHBArdwc1Ye0ch2dHhJB09iaLs8nDtGkO5Um0uzCnJ+ebvvwsl52d++EONw/0nP/QBFOUd3307oDz64Hl+5f96eOHted1bzvL//rE3s9v6ILvjW1aMBe2SPtBfWH8anTKEkrhTAB0bQE3Yy89zqfcpjnXvua52DcMwDMMwDMMwDMMwjJc2rSMnWbr1XoYPNqfhm0bXT/AgJUcHPQ685wPrR/nw6ga3H+yRhZInu8vsZ12WfTrOwd0Sz7lkmYtljyvlAI+wUQnZMeRjEonbdQleo5g9ErLXfIu2JOzqRIj34uakPdfgRji7nDoXDQuEpIUvphwVm2ynp9ugyg89JVw7LeezRc7UmbO7nlsfbkgZ+Xni+kTlUeEFOcUb25wWaAOj/OaIwILUntNm5NfqT7yP1zaGf9EYCfujnxto75xn/8g51HlC2iYkLQY+obV/BVcMY95w58hby/i8X9nUA+IoW0vIYH98TEaXuUaQ2LzQDdcyvJfuysJzhmEYTZjYbSwkSRJW1tfYvro199UTljzDYwnZxSi4ajq/S22OwCSndwmSa6y3qHjHk294kq35CN/sfE5+JKHYjB9hN2y2H5dC0dk83ERxW/ISV+nFmsyX8TuBshsI3Ruzwi5WPb6naIPw3+qvMUz2xlHHIwtzQejqzezxKEicODjmBfeUFYa6Nb6hSjUQgUJ3SVgd7zmdzWktCB09yz6Pja8RKGplFOVbvv+VAAsF73/6Qx8EAnfef4T/4ft+hzJvngTe87oT/NUf+xqy1uxfNzc6uVMCReN9meWguHKD1zAMwzAMwzAMwzAMwzBeiqy94g30l1bQ//szEzGugUdf+zZ+fv8il/r7AGQ4jvoOT6RtelqSIJxIOggw0JIhgdPJMok4TiVLdCRhP+RjIdvjkLEsHmmJn9Pswg2ueT2XJGwWfaQsohiZZARxkxzdqkgoKvtwqgClw0VndUk9QjsEXFjkplgh7trrvDfINXN6L7QBH+WJrt5dQ9S9Vh8Qz3SebaZt6a/jvn6hebFyoftiyNKlx+mtniBvr8a2fUp/5TidrWcnv0/OEZK0vrECKmv3F4ZomA+mm2unri24u9/4gq9jGMbLGxO7jYXkec7O7g64ujPN6GtncCajXHKklwpkGOq7xxqJduEj6x4GCuXhgvfwREZwOel2fRImCksP9RieSBmeTKN9+gwCkGucCPkZwVqEYtXj+oobBKRoziOePZ8zPJEQlppC1a+BEwYnElx/vu1e+3IV1Rw9z6fzbacss6p30eciOTsEirmdnY6UjE1KPaBkgJM05rgGggzJdQtPB0eKUs4J3inLrOidDLjIkKuIzI9PUb75+19BW0/xEz/yC41D/Kc/9GFa3YTBQdF4HuCRBy/x+7/0KG//trvmRnGjKCUBwZMdWm4pPXbD1zAMwzAMwzAMwzAMwzC+eGhZoCHg0gwd9tGH3wuXnoH2Etmxs5SdZfRgp7Huo0sr/Njlx8fvBTjq23iJluOZFqTixkJ2WxJW8aRTEc3rvkWhs9L1tIF1M/Nx3PO1AzHnsa+u50JJd+c8K1cu4rSMecJbS7WWWnuXSfL+VFuH90MB9TNW5DojdN+AWDwZyQtjJFUvFG4b+zJVUtxEJG0qO2tXvqgPNaG7mS+W0D0Ka4o3qepFlU9dDxPgX0CObz+yLZ+1Vw8z67vXdY+1XrayzB//WbXryuG470EcuIz675GiGiPr5cQt+Fd9xaFjMAzDmMXEbqPGcDjk4sWLbG9vE0Z2LSKTb/igte+hYj2hWL+Oj1FQ2k/nsa4bRRyDFEAlNKun0fakOJqQ7JajIOQxotB6PifZLTm4p0NoCW4wP/10OQTXIMSLEDpCaLvJ2GauL0B6uWDQvcaOxmquNVfCCaHNOIIcoJScPIk7SkeW3EPZItONcTS2p82Snl18PcDhcawgODLdjFbmFSoFRWUYrpS09cRcfU+brp5lx32SXLZwC4Tjb/n+V+Lw/OMfeXfj+cOEboB8UPIP/3/v4VMfOc/3/ddvHkd4Ozyi/pDc3IejFOhUru5ZVrMzHO3ceUNtG4ZhGIZhGIZhGIZhGF8YQpHTf/oRyr0tXKuNX9mg9/jDDM8/BShtAktPfhzJ6ynwhBiVOptb+snOEj9xSz2tXVeSsbAsIixJOreilLn6EVW9hpxcZxT3nYnjhOtwJlnGCTyfH3Al9MnE40QIqgTVsdCOKt/+xKc4t789ubbPauuMLu/XhO7rFqln7Mhltl6TQHw9bYugKtcU3MdNxkrV+urkvs7Zp4+P6mzNxlSbo75cd7/ncmhfn+35DdNgLb5I7J+zVp/megTvF9KtWZt6kfpmAoh528u8VixIgtf6sen7FW3Nk4l1eZhYnkO1ASPJGscoKHLuFSTv/D4kbd3IsAzDeBljYrcxZjgc8uijj1IUh4iXShSnG2y/F+ZPUY3R3wG01BjQ21A/vZCTH03nz2nMv02DmBwSoX8ufvkNNxJaz+dzZUSVohstxef7Numz5AHN5kVtidstm/OQjwtVIesL5kejiHYAdcXcQFRy+lygrcfHgvd4jBQIgjR0IDAkMCTRLp1wip57bq5MrrsoSoeTc+d25JMcuKeiWw/NwnNPn+fbvi9axywSvBdx5vYVnnkkiu6/8XOf4tEHL/FXfvRrOXHTSuyTnmbARUq5vnzds5QM8bTm7pminFt94IbaNAzDMAzDMAzDMAzDML4wDC48zfYHfxPNh43npczpPvHR+Yhk4vKaL3M0FGjlWiga+Gdn72M3rQd1pA35r2VmDXBeBxYShALFI5SV0HgQCnoa10+7knAmWWbNZ3hxqCrHfZdVH68fVNkqB7RnluHd1LVv271aF7oB9fXyybA3f3OuhxknTnUOZgKK5sVXrdcLJRLK+YhocaiG6xS8p0XcKGbPS85TZZS5Mo0i7wu1W7+e8tcO3r++SzGS9UcbCq5DqD6sf4si12/Acj4ZxEAspnJyF2mHrLcdbcer3xeVyaqrFEOcFuPr6fh/TN67+mdEQlF/zj45tL+6fQnJTOg2DOOFY2K3MebChQuHC92AGwTcQCm7rp7nukmMLhV/EEh2ynFObd9XJI/Ju8uuBxfzbfvtAlFwzw0pVzxl14ES618tKoG8+v4NEFpCsZmQH0vQNPqsJ1tl7FPQKj94/DN4oX9HG9dX0ks57iDghjqOFB/PX7zEyV7lsx5SoVzyFKs+njuMhomGFIrrB1BibvFScbkimtXV74pctgha0OYYDo+iBIaAkrA0uRSKUhAYRPtzAdGUZb0NX3Y4cM+gFAgeT3x/RT7Ikt7Mkt6G1w6F7LAjD3PgnqweX5uEJUqt2qwmYoIHCezyaf7E999Oydfzf/7Irxx+L4Cs7Rn2S84/uc+7/qs38c//1w8y7Bc8+tBl/vp/9PP8l//TW3ndW89wNHw5QsKOe5h9eZKCPYI0/+Mm9jMh9R0G5W51JFDSx5GMNwNEi/OCh7f+b+7a/AZcg0W7YRiGYRiGYRiGYRiG8cWl7O2x/f5fR8vF65HtnQuTnNULEFVEJ2288coF/n13pVamSbtUVURk/GdPC9LgGGiJAB1JuTtb52jSIRPPXhjyi3tPcDUM4nWBu9sbrPuJOHci6bLiJkL78+UBV6ryo2vOctf2pZkBzUf3HpabfBECSChrwrmOHLJH76f+HEvQbhTh6+KRUFaR1ZOUjOM+ikdDyWyrh8dON+XlZi7i+gtjJd6kbEstgnphgNf1tq716ObDS98AC1KLHtbvtLfF6vMPjzdR5Fk3/h6NSxT1TRChxBeDuXsyu/mhbqc+vxFiLqJ8lq3zaD5E0sNTVxqGYcxy40lzjT9WhBDY3t6+Zjk3jF96vh/ip8fLYiFYIb1UjIVuVJFcK2txpf3skPbTQ7ILeSzjBAmQbJe0nstpPTskO58jpU4mUF4gFcpVz/B0FoVuiAJ2SbTQ8Q5NHcE7pIT8WFpZljsGZ1v07u4wPJHGCd+oqz7WFSqtO4CmQrGRNEahN41VqBqsXjJUfE8nNum+skzvpGS62thM6fbIZZtcdihklyCDOXtxQSjpEyQfD2BUps1J2nqMNsdpcYSELj15BkTZd09wwf8WzyW/xPP+18dCN0RL81E7ngxPC0+Gw1PtHGAgl3jnnz/Of/LXXnfN2/Hl7zwDQJEHLj3T4+/+yz/FqZvXANjfGfJ3/7Nf5+d+9CFcuURCl83wOs6Wf5JT5dcf2u79x76bd5z7uzPW5Uogp6Qf70sl1veKK5w/+MQ1+2oYhmEYhmEYhmEYhmF84ek9/vChQjdAMth7we22G9o8CAVDLdkLOfshJ9eSoQb2Q8GBluPzl8t+VabgzmyN0+kyWRVI8Qe958dCN8DpZKkmdHuEZUlr132u2L9mf1thNo/2fJkymRH/riuaV5EyHwfpSFngQwGVBDkRLN342KjduEYakHISmSsQRXANEIrqVcY6zkeRfCyCx5dOv5/u/lxfp0XS6xS6byCimdlNAyP1v/Y+zIi60eL7c8lu/uIJ982i9vxrskit089WJEb3u2QsdKsILoSplifW8SNcOe+mOteX63geczb6U1cM4sEn8WUYhvECMbHbAKLYvTDvyTQj2+8ArhdqEc1zX2eJxMjrqbrjiULiCK3pnV8N13KCptJ4LtkqSa5MJq7SNC/2QkirNmbIjyUxYvuQ6/u9gN85fMI9puHWha4QMolC+gzt8gROm3eo5WyPc3lH5n9NE7qVt3tkZCgjSMzPrZMBBQZz9R2zdjBuXF+mDB90+qFVfMv3v6pR8D56ehJ9/hXfcjNZOw781/7Vg6wf7fI//+vv5Mu/9rZxmZ/78ffzl3/gv+HqlckmizZH2SxfP9c2QMoyZ5cfYDk9zpHWXY1lZhmUO9cuZBiGYRiGYRiGYRiGYXzBya+cv2YZvQHHvme6y43Ht8KQAy3Y14Khhip2NZLgamnybk6Xa0L2Tjnksby+znQy6dbeZ+LnrNHz64jIvtBeqr0XNIrIM9SWH6+5jlsFHKH4vI8UORKqdU6phNCxMjoVA1yLzG2+hkxHXc8J2U1C9ecpYvsGcmuPBftx/eo1akvDfP9G46sE7xcxo/cNUM8jP5GlpyOwpl+jQxPrcZ2xo1d3uLU4gGv4PF6bBoP7mXaKrMuFOx7g0Tf/WR79ynfxxBu/iyuXL12fTmEYhjGFid0GAN57kuQau6ZUa58YP1D8bokMAlLSOMEolz2DMynFShS3p/RZQttTLPkoSEtzfU0EbYgcF6D99JD2Y338VgHlgl1hmUPy5lwmvVsyeucyihWHFA025EB2sbim4B0nCQ0nRCjWXPM551jSc7TDCbx2EZ0SmKVkwGVy9ggMUfKGvnlSVvDaAXUEJn30tOnqWVJdx2mLlLWG+g5HByElTnvL2rnRccE1Du5bvv9V/NV/+DZue+URTt+6ynf9v17LfQ+cGp/fOLLGV3/n7QAM+wW/8NMfY2mlxV//sW/gz/31r8BVz/QD7/0of/Y7/hJ/9NFPTurq/ZwpvomVcAdeOzjNSHUNp10evvzLPLn9PrYGT89FvDexlt10zTKGYRiGYRiGYRiGYRjGF4HriOAcLm/W3isQXEKZtKtXiyB+LKrtJSkf2DxZq5PiajmyMxxepoNIwM+IfWeSumB+oezNCXfpzNK6Nsigq27GsbFBVPzIxnHy6f6EIuZUrtZK04Mt2nuXo1itOiXSHsKonGqM0A45kyjfkQhZfzeK8J4I4fPCb+39rNB9vRHZ18ENSZ3XG+mtoRJdZ64SmjYmzN+Bz5+9uk4i53UqyGx8nyfx2lXpeevwhj7PvZvNVX8ta/HxlRv6W3tbv3/BpxTZZCNH6TP2jt5KkXaAKHQ//ZpvZufUvWjlXJAnLc4/+wzPPPn4NftkGIYxjYndBhAnWhsbG4sLjPJfZ/UvNldCchBIdktkuFhwzo+kDE61yI/OTGITIXQ9YTlB3YKpgmvYBTaqvhvoPD6g+9hgoeCdbJfQIGYjQrGeUHY9yU5oLCNAdrk4fKegxHE0lhABJ7X6MVpaERwZ6yzpWZb0XF1UFqWUA4ayRV8uLLisw9MmyIChXKlNqB0JLd2kq2fYLL9sQX3BkeJpAWXDuQRHulBUfuPX3Mzf+Td/gr//y9/Gt//F+5ieOnnn+dbvvY+kspn/5f/r4+xt9xERvvV7X8vf/Kd/kvWjcffrxfOX+YF3/XV+9mfePd611+Y4m+H1pLpKxgaeNoLw5Pb7eP9zP1GNMeOwv8KOtu9io33rwvOGYRiGYRiGYRiGYRjGF4/26Zl1m1CSHmzT3nqOztVnaO1eoExaDNsxHaACIWmhPp2KXHVokqE+5cAn/Pgd9zH0k2hwgZrQDZDORIu7BiEvmxEA0wZBcDfUA1T6WpLP5BefbacfCg60GK+BDbXkSprwb8/ewdA5JJS4UOJDQdrfweV9soOt8VjQshIVp02rZ5hZx1QERtG8I9F01qq7Md/ytbgx2feaQvYLafbQNdvFFuoyHc19g5c+tFsc+oQamY7PBia28DC1yWG2xgvkBgcYGjamTAvgwXkG3SMEl1TvE/Y3b2L/yM3krSUU2D96MyFr01s7yaCzzuVzr6NoNbsw7Gxtsb+7e2OdNQzjZYmJ3caY1ZXV5m/fKneJEPNYhwZbcFTx2yWSN+yAU2LaZyDf8ISmTZuqSC9AaIjuFijbC76JVSc6ras5e4+RUuk80m8Uw/1uSffRftSrd8vm6zvB7ZbNkedQzUJGOx5vzGIlitNHF9x/17gzFGDIDoUcVDmrB43lunqm+cZMRoASqmjueYS0ed6MIipjkb4sJs/ee8exk0f46m+/F4Defs4v/czHx+df+YYz/Mi//U5e8WWnqrol/8vf/XF+9If/j/ieAVfch2e3i871IeYanz/eTY7w5lM/uGDMhmEYhmEYhmEYhmEYxheb9pnbSdaOxjehpL17gXSwi9MSQfHFkNbBVXrrp9hdO0nhsyr6eB51CT99+308srJeO94kZM8eaVp1mxWyzyRLc8L108VezW75iXyX9/XOj499YnCZjw8uMwwlqspQSwYESpQeJYWWYyv1z66s8w/uvJ9d7yl9RpFEC/XW3uVaf0dm1DVRdHoEOsnYPDqjrm5bLXNC9rwg/Pky6z6k57UjL0iTnV6PbRC3X2xm+xxdP93Ua+Qd7savqfj5eVqd+WNzn/MXKWq+KR5sJsd9mbQp0vbU+xY7J+4aR2SPxotMcr8Pl46gScqws0qRtukvH0F9As6xf/QWdo/dRqg+04jQXzlCb+0Urd1LtHYukO5fxRXDWj+2rl55MUZsGMbLBBO7jTEXz1+IYm+p8U+t/gwg49QtQug4CIoMA5IrMgj4vThJ8jthbG1OEeuOhG6AZDsQug7JS9wgIMOA65WkWwW+VFxfx3XVQbHqGR5L8EOtb20LGtsvKhFeoFjzlKuOsiOElCigD0Ls3xC6n+6Tnc/xuyXp5Zylh3usfOwAKeOXsigkOwF3EMcVMmFwPGFwIiHdDeO60g9R/3fE3yARCIqr+jO5f6N7xvwka9blhZJEOnT0NJlu4rVLoit0wmm6nKkZ5CiBnF0O5DmGLn7pe9qICKHB8vyK+xBB+gRylLLKB17fV+hZIqGLp4Pgif8U8DgydHSTx9fXsajuyHC0EE1rKVcS18GR8G1//nVjy/Jf+Gcfp78fC5X0WTkW+Bs/+bV86/e/elzv3f/mV7iqD3Le/Q65TOdBmpqQ42o/e7o4MgSP4Gm5db7hlr/HcnZi7l4YhmEYhmEYhmEYhmEYLw3EezYe+EbaZ+8k6+8uzAucDvf52VvuZZi2Gs+PuH/78tyxJoExzBwN6FyO4EeG25M2VPlw/yJhqowAeyHn08MtVJXnin2eLfZ5vNjlPb1neTrf49PDLYAobmtBLxQEVUpVCg30qQcN3X6wT9ZaYbi0Qd5dJ7gUVzakN5zKvzzpzWTEh1qNxwE13JUbYZFU3XxUAU1SQpLNiL8Nttufq2B9g/UbRzRtLT5TQkXA+Zn73HDPq3L6uq+DN3wj3P5a5NVvxX3Xf4W84Rvn+3CNteQbZyZCXAMu748t3Iu0w9WbXsn26VdQpB1UHPubNxOyDtun7qG/fHQsdI9eRdaNGyoAxJG3lina9YjtkE0EfRXHweYtpIN9XJnjQkmS98n2LuMH++NyZXl4alHDMIxprp0YxXhZEEJgd2dnMrW4hsdKuezJnssnGV5icpuo6w4VN9QYkb06tXMwKK4XQIRyOaH17LBul+Oq+iVQKiHA8KTD9ardhlPzhcoJfNL/lkAlqmq72lU2CKQHBdqKx10B2YX4JSmDQNKbmlBWorVozEXOQNFEKNcSkq2qTgnJTpx0F6ueYn3y6zPK+S3AaJ6qopC4ua2IgiDqUJlcf5Qz20lCopuV4NyM4CikR5DB+JhnNGHQKkp7IgjvuE9NnSvHNabLJFV9mck2FFvrN3dEZdxPISGUk4GO8r+fuGmVt37TK/itdz/I3nafX/+Xn+Tbvv8N5OyCKEni+TN/7fXc/fpj/MrPPMwbv/Yc+8ljM9lvZie8CehwfFgQZMpq/d7NbyXzSxiGYRiGYRiGYRiGYRgvbVzWYvX+r2Tvwd87tNzdu1doX0P8WsnnheGRkD0WiFXpU7As2fj9kEAg0JXoejjUkmfLfR4cXOaVrSN8fHCZTwwv40TwGsXrUcT4M8U+V8o+DhmL6E/muzyT7xOqsBMhhpWUtcCTGLYxWt+6fX+Pr798IQqngISC9u7F+Wjea+RnnudGReNqAbZiOqZncrBaQJYqheN0xHjVz0krGiN9q4jlkGRIKJBanuyZxehRu583mmK0Z7pwrdrTEdjX6qsq7vQduLvqKSf10x9sLFt71vXHsbD9WLa24l7vL8R85aPPWVnE9fjBHmXWYe/UPahPUeDq2VeT7V+Fyppcfcr+5s2kB1cna/rON1qRS1mgSbOLaH/lGKFh44oAaW+nSlWQ0Gq15ysbhmEswCK7DSCK3S8ETYT8iD/0O1YU3H6YfNHqVGB225EfSQ6t7wolez5HmnJxe0Gn9eCGfN/achTrvrKOmT9XZjMThhnSrZLWM0NouDV+p8QdTO02bbQfZ2EecVFHLUf3FDEC+/Dn0dYjOJ3OpT1WfgkUNTvzQN0CJnatnLE8d1V1iWJyrbOzb6XxxPRnaDLPE77jL7x5PMf6+X/6fob9khabtfF/2VffzN/4J+/gHd99N4HhQtv22KLD0W623cFxvHPPwrqGYRiGYRiGYRiGYRjGSwvNB9AQwTzNUlmync0LZNFSWVARtrKMZGa9qiOeZEqQLFB6WtILUTjPCRQEepTsh5xCw1iU/uTwKr+29wQfq6K6gyqOKFRP09eSHiU5gZzAkECfkmFlWT56jRBiLm+ZWrN881bdrjzt7c4bX99QtHLTAlqDZfmUUDu25a61EC03p1uTKv/3KJ/0vBDOuGb8wU9XbuztDcdzq9ZfC/pSu5bIJE+2zhqsXwc38Dz0yU/OH9you1MuujPNUeejdfdR5JpO/dzUVrWyG0oIxdQqryJakndWp4o6QloXnGWqjgLDzsZYOJ/ufzLYn7NHj3WEvL06d3y6rh/2ANg4cnRhOcMwjFlM7DYA8N6TZtmhZWaDvUPXMziVkq96Qts1ypOu0CgM90qkCDWBulhL6J/NyNc9Zbc5b0myF0guL9i1mQiagnpQ1zxpCcuecrn5Yx66nmLZU6ayUJRuP5OTXmqwCwKySwXZ+SF+u8DvztssCSBBG/OAC4ILHld6pBDcYFp4VwKDampcNArfgqejp2iHY3jt1suIVnVzAiVtbbbzVgoCBU5byNSDERxCOrYFF503gIjTolAX1afuoU+i3Xog56bb1nngnXcDsHX5gF/71x/Hk9GmOUe5SkFJj8CQkn6j8O1Ion25ZjHCPHg64QydcIpPXvrFxvEahmEYhmEYhmEYhmEYLz0kayOt7tzxuBYpKMKOS3h6ZbN2LjiH+mT8+rLtq3zns0+QVUtJbfG0XEIqjkQcpeo4+npPc66WA3INdMTTEc+Akr4WuGp1zCE8X/Y4IObWHr1EZO516Phm3iczQne3LDg1HNTKNNmX3wiqs8tvukDIjiLpuKxzqEsm58c23fF5TEduS4O99zwN1t5N/b2OMb0oTPfl8xo9PoObX6eWe94E2UwUs4Z6v0RA6uvvYzP7qTzt08fq5vaTGqOfZGbcZdKae0azmcKDT6ONORCSdozWb0AAn8+7harzc+L4XN1Qcvrmc2Stw9MWGIZhTGNitwHEnWxHjh5ZeD7ajNM0O6Nc8+RHE0J7wb4zBddX/IESkpkvzNSRb6YMT7Yol5o/jj6nUTAGwAnlkqPYTBdOhrQlMb9207kk2gW5nIWCd7odFk563EDpfrbP6scOYq7xBqRo2FHIKIra0bqkLD3joKydRKVEJV8Y6RxjsJdIdQVHUi8joBJQKVjXV8/VHaOwFl7Fkp6jXj1alDsSElaaxyWCMtmIMC12OycoJSX75Ozxp3/ggfG5f/t/vo98WOJIcSyYtIhSSp9ctik5aC6CQzThSPgybi+/j5vLb+ds+e10d76M5y88vXjMhmEYhmEYhmEYhmEYxksIwR07M36nQBCHShIFV/G8fvsyd/T7lD5aI6tzk1zJFR7ly6+c50899yQdSWiJxyMk4kjFISgtcVEEF89R3+KubJ3b0jVuS9c47ZdouQQnghOhrwUHWg/C8XLt5XSZWUCdfz9TvmHZMTSJiI3rk7PHJgFFKo6ivRpFyemyIqjzdSF7dH7aPlukuv/TQToyP4CGMTX2c6b/I9F9/Br9rylC+4VEUX+xhOzr6KPcdv/8sVYH941/AfzE9lsgCt7TnwPnkdvug+PnauVkRpJ+wRHqFX7Yi9ecYk7Mdp7BUtx0UiaHi9FSFnP3X0I5d41Z1o8dZ31j89AyhmEYs1jObmPM5tEjDPoDrl65Ujs+Ebolis65xk9ObeIAoeWQMuDyWauYqR8T0Bxk9jtNlZDEonNGOq6aZ83mKgFCKhSrcTdY2RXcMEaT18pkDtVAst8gGA8Cfj92Jl93+D5z/S87juFmQrpVzk0+k+2C9GoZJxFljK+em0yUCkFoSsOdbBUkewFFaF/J6B8Zzm1BKaWPquJp1ybHMZ/2MIrilOzyGVa4GzdzoUIHSEhRyeudU2FNX0HKKoGckh6u4RoFB83PBUUZVvtcPaGcPFTnoaQPArnucNM9G7zx7Xfw/t/6LJee3+U/vPsTvOM7Xk2c6M43roRYHyg5wJHhSOfKbITXcERfX7+ndLhw4QKC58TxU/M33TAMwzAMwzAMwzAMw3hJoKGk/5v/gvKph2NePBFUPPVcyAGvAUQo2suEYogUw0l0tCoSSlwxRFR50/kn+PTaUS6sHcdVZfbKnJabLIVvuhYnkkk0+UBLdnUSTa2q7IV6dLVrkBBfDGPx/SThYppxLJ+kIsyzJVpcPrT96XzYkxSHUi23KUW2FCO0cZTSxRU93EhoFEGlYUQNgu2NWovXxqmKlPk4mlir64+eORpttK+nPy8ZpnOWXw+nbkfOvbLxlNx2P+7P/RD6sd9Cn3sUkgx315ch974Jti6gvT1k8ySyvEH5U//NjXYY5mTxKafOMqe9c4H+2snxseBTggwmnxugt3ETybA5OKk2JqBz52so+/toPsSvH6N9+33o00+wd+HZhfXWb7rl+odkGIZRYWK3MUZEOH32DJtHN9m6ukW/32dvb6/aDlZZ0+SKKzQGWid1sRsvlKuekCsyDEihMWJ6CldW9fqBkTIsQaFUkgONubgrfx11Mbe3+hgZTgk4BYGy7SiXHJpJNTmDciWhlBht7QYhHquixbuPlZPvcq1E7oMwFsZDKuTHU3LA7wVcL6AujqdYdWjXM2w73EHA5YHs+Zz0aokfxPrFiqM4kka7nzKOSYqqz6mAr+8o9Dslye5kY4Am4ENC66qyv7mNiCfKuTngESkp9ABHguAqi/BivPWzz3l67mn6ep4uN5Nol0BOX86zL4/jJEFxqJYInq7eTEdP46vI6j7nKeWAnN3qGilKQUF8/oJjevo8TmQuPvZRC4opsVt9HyTa4qsEBlzmW37gTt7/W58F4Of+jz/gLd92M5LkTDWKUhJkiE6FuTtJCfQIOsTFXRaAIpqwofO7IUdcvHSeo0eO4/3h1jiGYRiGYRiGYRiGYRjGF4f84fdTPvVwXO3RgKpUNsejtae4tlcmGeAqe+eA+Ikgnhxsk06Jby7A9z30h/z2za/g/TfdxVBL+lNrTQIc9XXb6FlhOyc0JBa8MRStBZeUGkiY2J+fPNildbAFaRTfXTGks3shWj6HKQF4gRDdJHgrvh6V6xYI2zcY+VyrNWpnvEFh1BeZukaJC+VUfV+5ok9tWPjCmZhfk6bAn1niZ3YSLT/+UzV+hkfjFYfc8Vrc1/7ZQy3vZf048tY/PX/i2NlreANcm7qsPWF2nGvPPkzRWqZoL1cVhaK9RDLs48oCUNR59m9/I93iAJ5/YuE13bGb6L7+a+aOb97epb+7RdGbF8w3br2btLP0QoZmGIYBmNhtNNDudDjZ6aCqfOYzn2E4nOwqlEoclrHwPM4EMv5m1FTQ1MdJypWpaGjVcUS3poI7COMvU5mO9h7Z4UgsJ8WUFUtVxuVKkU1sdjQTcPHn0JYokgtoCtmFym5ofLH4mo4AL9Ymtkfliqdc8bF+ImhaTdScEJY9AY/fV9rPT2yMhkfTSd+TmM9ERfFlmLNuRwQp6xHkWpVJihQ/FPJWb3xuJEjHXNzN+XoGcjG2IzkHPIVM7X4t2K+G7SrRGlJdnbQLDOXquEzOTs0/ScYR1TL+v46PjCZyipvKm+6rezZtrX77a9Z41QMn+MQfnOf8Uzv83i99hq/6lltmrJyiID81ix/3GSkJlNXFPat6eyV+NxNCYG9vh7W1jYVlDMMwDMMwDMMwDMMwjC8exSd+D5f3o+ujc6hv4crheGmoSNto1hmXd3m/EgxjCTfs14Tuad725EM8t7LJg8urteNdSebsyPNZ++br1F2vJYp6hFTcuH2PsORSFKVE2ezv865PfZBOWTBsrzBsr9HevRjzYDsfLcRDQ8TzFE1Cpt5o8EfDwBePcepoLRf1rJF2Q/7oGdFXmqytv1BR3TOif+yfQ69DgBcUvelupLuKXnkO2ku4u98I97wRnn8c8gFy7Cyyujh96Avu7q2vRi8/c+2CDS6pjS4AIuP778shR688Rv8176SXF2goyNaPsnz2DpwIxe4WLs1IN46j+YD9f/Nj6MFu4+Wz+76q8bjPWpx+7QPsPPsE+xeeJRQF2fIqq2duobt57DrvgmEYRh0Tu42FiAip8wwbvhgF0KLBzrzeAMWaJ9kp523LfRSkXX8keDdYjCu4g4Cm8+27oZJcLSk2fBXZ3bCzUYGC5kla21GUit+rrt8wBFGqPN7zU7rBTRm+F2g9XU2+m9L1pEIIzfem2PBIqSR78xO57vYG++tXKLJhQ81mpkVlZQhkE5G44d7uyqdx+gpS1qojsR8xD3iXQg/GgvdsXqGIG9cZ8ZZvvZ2HPnCeN339Odrd5r9avu0vvpJP/MF5AP7tP/4IX/FN53Bu0r7g8HQotbf4XwoCaEnzTa8TvpB5eQzDMAzDMAzDMAzDMIzrJn/Pz+EuPT1+r9KqrfYEn6BJNjmgAVfW18uS4f6h13jt84/ysTvqzoBNduRehOnMhmll8T29sqQza4QjSXdUxiN0xDPUQB5jl1l1KSJCP5QMtGTJpZW1uiCqfNXzj9MpY0BN1t8l7e/WeycOpqLSr5sG8VidhzJG5ooGhFAJuvOM1msV6tHI2iB9z63Lzryf7cvIurxeaMFAXhhzvVsUvT673l2VGwndMRhr5EAaFi5TArhXfRXu3jfNn7j53hsZwjWR134N+kfvgcG1rcSnP6EC6Nox5Ow96KVnoCyQm+7Gvebt8X5ceQ46K7hTt7EiwkpDa76zPGk5bdF555+j/1s/S9i6OCmUZLTe8A7Sc4vH79OMjXN3snHuzusas2EYxrUwsduYI4TA3u4evYMeB/ujL81oHz6tcYqC5jqJ8B7l9Z4mkSjsDpX0YhFzfo/EzVQIiUNyBe9ItsNcTmxXgpbanO96P+B7gWLJUZxKG3erSYg5u5smhWHJR8G9F6KtegMSQIaKpvPnDu5s078pI3t+SFigu2rLxTHPNSzkx1KKtYDfLWOk/KhfviTrdUkGGeqUkEnj9Ue0sw4byc1c6F+dXJchWkVyO9qU1Cf+KgVb8nFSXSPVtdo5wZOwjGoxsROfncMi0RZ9yobpK/7EbXz5O24hSV01FVYS7VCwh1YDvPcNx7j79Uf51Icu8fQjW7zvNx7nze+4tdZ2tFFfRjWnZIiKzgvuAj15es4Gapal7vLCc4ZhGIZhGIZhGIZhGMYXh+KhP6D8xO+N3yuC+voCWJgWugEpi7lVIFcWHMbRg925kI2eFlHknVpH7JDUrM4VJcUxnKo5sq0e1fNVb0K1EtYWj4jQEo/TQIobl207T6ZunEMcwInwiqsX6mM8dDTXj5QFkvcr63AluIS8tRytzauodimGpP0dXJmP/RxnbbZr777QQSUza73Bp7iy2fUSqvhxuT4L8nH7MGNBzvz69rV49KPQJHZ/npCVTdyf+quEX/kJuDyV+3r1KNx0F1x8KroBnHsl8pqvhnwAV8/D0hqcvmOxlfrGiRfcF79xnO63/SXK5x4jXD2PtDok5+5F0ta1KxuGYbyImNht1Lh65Srnn32OsqznsQGirUkiyCCMv/QFIETLliDE/NSziCBBaT2fEzpCuZbUzmkmkEG5HEh250VnAXRaJJ8+F2KUdlhJFs5kQtcRfJUvfBYfr+8KcL1A6Myr1m6ghJbWc5SP2u44BqezKFYv6CNOFtjGgGaOsBTt4TUvOFi7WovoliC0D1bIE104Szt35m7S7F7e88jDFGEw3TuUQMoype431h/KFgO5RJS422PhWJDKvjwlUKDM/8NBGmaPSWVfLghOMzp6iiFb9OX5eFyEP/kXX8n/9J/+DgD/9h99nDd93S0NE2mpcvc4lBJp+Ksqd1vshcdY0dsa78v62gZZljWeMwzDMAzDMAzDMAzDML54lB9/T+19FGHr60Mq9eiXJktpFddogR18iorQSzLWgnLn1kWODwcceM9HVzfY9h3WfRTkhlrS1wIXY50pNXCgJYk4gioFGmN8RvHOqiRTQrav/BWnhexUHOmMK6FrWBtMwvVkBpeaq6PMiM7jaGRiNDIhIChp3hufz9tr9Sh5QJOM4dIm2XAfv7oJF5+ebfU6unYD8rwGZiObFj3HEf2VY+wdOcfq858m623PNznqy3SENhMxW25/DaydgA/9yuH9X5AX/fDhvFjZ3a8fOXEO/+f+FvrsZ9HtS8jKBpy5a7GQfezs568vIiSnb4PTzWu0hmEYXwhM7DbG7G7v8OxTTx9axg0CyeWC4kh9AqqA3432NyNr8XGdg0D3s30E8PsBKChX62UkD7j9aTW6bo8zymk9G/mdb3j6N8WJWvuxAcW6pzhS3wXqDgJ+p0Bbvi5Yq0ab80rHdXslIZU5UdvvF2Tnc3q3ttC2q9WXYkpEXzQHDIrfLSmXPfj69WWoSAkqsLd5meDrorI6pb+0R6qbBAaz6W7w0iZxKV48Hc6wq4/VbtLEXmnWeCmeU8rRtlQCJQ5fi5RWlMAA0WoCOnP92EaBkNTqOc1o6wkEYUnPkoU1duTTIMr9X3mSW1+5wWMPXuXxT17hw+95kte/9dxM38o43kNwmlXR6Uu0qe88XF5e5qYzNx9a3zAMwzAMwzAMwzAMw/jCo6GM+Y1rNIl09SgLdQnMrBeVaRs32Bu/7y8fYefUvQxWqty/uxf5zz/7CZIpIfWrrlzkDzaO8uDpO1mSlN2Qx4hsdRQoBxrX52KUdoILJeXMutpsb32TSHodQvBTy+vcunN5btxR0FZUZeouCGio3ZUo8voZkbZuTV4mbcKiSFtxlHd8GYkX9OLh68KNLAjwmbkI0+uScSkyjCPMR/1ozJGtSpF12Tt6K4iwc+pu2jsXaO9cwBVDQpKh976ZREv4xO9WbcnUlapmLj6FJNcTFDMT2SMSh3jY6M7ecx3tfn6Q03cgp+/4ol3fMAzjpYKJ3QbDp7fJz+9xPtm5Ztn0UkGyF9C0JD+axu9/B4iSPVficiW9WlCueFAl2SorEbwiQLITSLYKQtejLubfdgezuU90PAdSYSxAa4jH8zXP8HRGqMRnGQZa53Paz+eU3SH5RkJoCS5X/H6Jz4G8JCQCHtRJjEgfXcMDmSPZD6iPEezkij8occNYbunhPuWqo+w4ijUPU/KuOupC9hRuoLgc5GqJZhLb91KJ3CWDbJ/CD+aE7hGeJbykOJLKWlyryOsEUeHpZ56kTLfREtqcoscztfoFe1WE9Cj/OARyxtb0xLhuAUoGRMv3aPAUGOJoIZVl+eiZOBIUoWQHxoK3x2uHlh4joTO+fosjdPUMy3orB/IMOdv8qb/4On74v/xNAP7N//4x7n/LCZz4qocl00neY4T5ZFLsNCXTDTxtELjk/5BU12jr8Xi/2iX33fKuxntpGIZhGIZhGIZhGIZhfHER5yFtRXvlEWHektEVeU2klTKP5VwVlKFKkbXxeQ8XSvorx7l4+5vBuar+gI1Lj81FQgM8cPUSR07ewuUTN3H1wpOxfRGcMidsN45hNgq9wXEyqM5FcycIWRWx7vI+hbgYEENlkU6oCdkTqXsqaKjek7rYrJP1vxFl1uEwyqc/A6dezKCRWcHYoVrW+i2hjOupI8FbJEb3H70JGezD/jasHUPueyv9QQHPPzFuq792kv7ayXFbiWuxvvvc4U9t9yrcstTQ1Qaxfi6ft2vMgQ7A0hryijcfdmXDMAzjC4CJ3S9jiu0+W+/+JMX5fUICg69eu2adGJkN6VZJcSRFK9tyGSour8TIAtzVElRx+1Mituok6FgEv1MeuituzLTjT2UT7oqYy3pEslOO2/YHAX8wRB3kRxKkmEx1XBGjuVWqaPFq4hKm7NelBCkVyhi5PT5OJdTvBPxBYHhqshtQFwjdo3szqj/6Wb2yv3qVfutqnJNqimtKTA54WlX9kbV4nYPePvv9p0EgoY3XDqX0xufLaserTE2MBUFrYfKj4z6WH4nNGo9N6k+Xn9otUAneBXt0mEw2RX0UpQFPmxW9HUV54O0FZ+/4EE99dovPfOwyD77/eV71ppM1QX50ncl1q2fVYGueyza5RAuj1x77zsb7aBiGYRiGYRiGYRiGYbw08He+jvKhPxy/l1DUhGwJJUl/h9xvos7jhwe0di+BCEVrCXUeNCDiGC5tkAz2uXrTq8dCN0B750Kj0D3i3uef4teO3FQ7ptchdANzOb9LlGTmWEBxk5hsVl2LtBJ3k7Lg2z75Po4eTCy5p4Vupo5OXXS+I9dlu32NFVgNcPIWePh9M3Wu08q8Mbp7SvAWARI4dhoOduFgB9k8hbvvrXDqNvTpT4PzuNvuQ9aOzTVf/t4vHHr5YucKdFcO72PaQl71lejH/sOhxeKoG6K7kfGmhDEbJ3Df/F8g19hMYFwbDSWD556gPNjFd5dpnbwF8c1r5YZhGE2Y2P0yRcvA1X/1Ccqt/g3VlwDtJwf0b8rQ1nye61hICF2H64XpQN3xOU2AQhdPtw6ZU/m+0nliQP+m1lhwb+pjslUS2g1TPAVKjRHdi6x2vBDaDn8wv3Mv2Q2oz8mPJs15uq9Bv71Fv331Bde7HjqcoKcXKOVgYRkhBc3RmHB96rjg6VBqP6r+C4g5vBvGLco+j9PVs3iaJ3qCsCn38x0/8OX8L3/tVwH4+X/0EK9608kqV3e8wuLOK30u0tIjeKY2HBDI2aFg8bgNwzAMwzAMwzAMwzCMLz7J699B+fiDcLAzFhGT/IAi7YIIUuYIkO1fpci6ZAdX40qUKkl/jzLrxEhgiNG+qycpOqv1awz2D+1DuHqettTXNUf5t6dXA704Sq2vk5UoSS0VIBQoKXWxu9SAF8eKy8ZCN8C95x+vCd2NQnYDN5AhG1cOKRes0wG4taO4V34F5ft/OT6PhReXBf0UOHIG9q7C4ACOnMbd9zbYPAnPPgJJitzx2kYhG4ATtxze/2yBBfvo6lkLuefL0Qd/f3GZu9+IO3GO8LqvQz/86/WTM2K9ANpdg5V1uPQsZC3kri9DXvUWOP8Y9A+Qo2fg3Cuvy6r+5Y6GksHzTxL6+/juCtLu0HvkEwwuPA0IyeomxfZldMrpQbI2a699C62T5xY3bBiGMYWJ3S9T+p+6VBO6XQHJVkGxvvgj4XcKNBFkFME9UDqPDAhLjpBFu/HZnNo4ISx5KJRku6hsz2V8TtNqjhQUCQ0TtiqAuIlkN7D0cI9ixVN23eyeu3iJXKFQyBoE7xCviyi+hLDcsFssEUJb8L35iVy6VZLslJRdR9l2DG9qzvuiWbREH79H6S1tz5QqYUFkd8kA1xDRXeumLlNInMALni6nKHVISY9SegypC+sxXjpDCYRK9JYqhF5wJHRRLaOl+AKU0PjQg+TsyaN47ZKyRkdPkVC3CfK0+OZ3/hn+xT/4A557YpcH33ueT334Ine/7thE8FZwIzF71k1ICvpyHqctnKZE8/M+iPKpy7/M2dU3Hnq/DMMwDMMwDMMwDMMwjC8esrJJ9m1/mfx9v4B+5sMTIXu4j7p0LD6KBtLeDm7K5lym/j8iuPl1NW04VsOn3HPsJj52eZISUEToSMK+TuwenQhepWZvPi1kjyhUyZywlnXYGhzgEO7ePMkrNk7zB098qnbpOy89NX9PDu/t9dGQYzoZHpC3V0CaA5bSVz6ApC38n/xByn//D6NoPd2jzZOwcxmKIRw5jdz/dmRlA33+cSTNkDtfj6zH9IJaRduPeRHyWbfP3snguccXnu+cvRN39m703jehn3zvfIGVTdybvgkA97bvIhy/Gf3Ib8CFJyHrIPe8CV71lfDcIzDsIcfPLRayj900f8wYk29d4uCRP2J48RkQR7K6Qb51CR0uDrjLLz07d0yHfbY+8BtsvuVPkq4d+Xx22TCMPyaY2P0yZfjkrNgKnUcH7L7WN9vfDAPZhQIJWtvtJkRrc78Pwc9aXU/VLxVf5cMObTe5hkhsxAlaarQPn61Llau7IYJaFNwggBPKpZhzexanEBbVBygUF6DcL6MwP4OmQhgqrkH3lQDplYIsEPN5r87/SoWW4HoTZ/AyGRJ8vTEl1ATnaQr2Seg2nhuRsUFfLzIdQu/J8GSIOoayKIpcxoK24mvPL+bx9lXfdO7ZjvKGK3ljy4EhQQbs8Tjr+sq586nP+M7/9G386N/4vwH4dz/+EP+fH39rre2EDoGyiiRvusYAlfr1twZPMiz3yPzygjEbhmEYhmEYhmEYhmEYX2zc2lHSu99I/pkPj4812kg3OgDWjyXDg2jHPSW0DrobZPtXJ+uQWrcJT259FbesH+POjRN85ur58fElSShR+lPR3Ik4Ws6TOMdO3schvPLIad584lae2duiV+ScXlrn9cduJvMJ/SLHO0fqPJ+89AyzZGXzetq1mAv20RCP1HJM+1qObNFAa+8yg6XNSb7zeIb0VW8mu+fL4rvjZ/Hf+z+gn/0weuFJpNVB7noDsn4MVYVQIn5q7fO2++f6JwsE9c+F1slzZCfOMjw/v0HAd1fo3hH74d7xLvTELYSP/RZcPQ9ZG7nnTbg3fiOyvD6u417xALzigfkLnbAo4s+F/nNPsP2B36jlNx/2D3dXOJQQOHjkE6y97q0vQu8Mw/jjjondL1caBG1NpfG46wWy54eIguSKPwgUq75mTV62hf7NGclOILtc1M65Xkl6uYgTrBDb0HS+D4OTKS5Xskv5dMpo1AtlxyFFFM1HtZQoJId2nEQd3N6idbEgez6fSiWtqMLgeEayH6KlOpNzhIk+nF4uyIHQnYjxSsznPbi1Reu5vC6mqyJFjEhHlaUHexzc1aHYnNkw4IRizeN3S1wBzfbfEHSIUM/drQTCAjF5mkDBQC7i6ZJM2RKVDNh1jxB/1euCsRKq/NwxT3bQPo5WTVRXFKVECTiSmuAdBXAH+HoEuEab9FE0d0uP0ArHGcilmhgfyPmGb3oH//wf/g4Xn9vhI7/zLI89eIVbX7GJkI5zfTs8QWM/ag9/dOMakAVR8oZhGIZhGIZhGIZhGMZLB70eMUxkTuR1ZUE5Jby6UNDavcRgNUYYu3xAe/fCxOocQF2MPNaAtDpk90cR7VvvfD1/8Mxn+OiFJzjIhzhxvH7zLHceOcnju1folwU3L2/wumM3kzjPfj4g9Z62j06M9x85O9fldjJxaUzd/BL8paV1Nnp79XtB00rXTO5rHa3JVYeI0dQwE1yEh7UjsH0RVPFrR+je/9WEpXXKK88jrQ7p7ffhVutRs+I9cvcb4O431I+LgP/iSAkiwvob38HBZz/GweOfJPT2kSSlfdOdLN39Wny7W5VzyGu+Gvear0bLoi7MG59XtCzZ+eh7akL3i8GwIerbMAyjCfsb/2VK6/YNeh9/vnasd0s9/4kMA63nctxwslPSHwRcHnNdD27KkEIJmYsCMVBsOop1j98PJFsF3c8OcMXUTksBV0IpClO5ttVBsRnzXw+PpyS7JW6/JNkLqBdIHJrECG8JShDQzI2jtdVHG/LeSkL/poxkuyS9mJNdLAjLDu168q5H8oAMo6W669UnkIKQXS7RrZLQcuRrjrDqCW2Hth39W1u4fhTMs+dy/MFUvnEFF2D5kz3KtlCueAanU8qV6lfMC+V6QsgVLVu4kBLcjIgtMRq61KISaxWloM2JQ6O6AXryNEEG5Owy4CKeJYIMGXIVRwtHguKqNgMFe8wlUhclMMBpxnTCdI1qPkFzRjHXo/6CVn2NbaNSRaH78X1ZD/eRsUaqKxR6QMk+++4plJI09fzH3/8N/Njf/lkA/v2PP8pf+dGb58Yb++9Z2jlCd3+T8ycfWugicLRzF6lfnIfIMAzDMAzDMAzDMAzDeGkgR07PH9OAzkQIi4YpIU3i+yStRSovX3yUMm1TtFdYufBZfDGg3oiAeGTtON23fQeuskf2zvFVZ+/mgTN3sp8PaPmEViVW33d0XsheydovaIzn1o6S+YRhOQlE+aOTt3PHpacnq1sioDIvZAPzgrfAygbsXo6HNk7A/W9HxKFXnoPuCu6eL0c2TsQ8yEWOdKIDoodrJEt8aSLOsXTXa1m667VokYNPDs2XbUL3F5bB808calV+o4h78Z0CDMP444n9rf8ypXX7Jv5El/L8AQAhiQLtNJo5NBGYErtH+bqzSwWDm1qUTXmuXWyrXHa0n81xOyObbMY7DF0BIZnYoYf2RLjGS8wdvupxTw6jdfpU2+qmxVYm9UfR2JkjP+Yo1jzp9v5YiAfQ1KEp5F5oPTtsdEGSMor6kiu9ZU+YEuVD20Xx20H3M1MT5ql2fF/x/QLXC+zd52v26ZoKpJ5WOELP1TcbxCEJEhKCH07a02sLt0PZimXJQIS+TNoWHeXilur/DkdGoGkCoqhM7NSjbZSOOsco1nvU1nS/m/aeerpkrFVlHCnLpCwz0CvksgPAN3z7A/zMP/plrlza4Q9/7TM8/9CbOPWK7lxbLiTc8tgDdA422Vs5z8HSlbkyguPeo9902K0yDMMwDMMwDMMwDMMwXiK4o2eQU7ehzz06OahhkkZRA37YQ2qLeIqokvT3KLvrqPdQFjgCR1xOsdxBZ4Xu6dp5jqwenTvunWO19eIHUKTe86Yzd/CeJx8eHzu/eoTfu/V+vuKxj01CPsTFcS+twv5WPLRxEu57K1Lk6NYFWFrDveKBKGT39qAsahbds0jagrS18PyXIpJ8Kcr1f7wpPxe78kNonbz589KuYRh//DCx+2WKqnLlNW3aH83JzueI1nNxjxicSsku5Pjdek4bCbD8iQMO7mhTbCz4GImw87ouSw/1yC7ULbQFcAMlpICX5tQ7ThicyWL/ZpsGKEH9aOLbMMbMsXt/l9az8zbg2nYMT6aklwpc3nRxcLnSfmrI/lIbnZkTlmsJvdug/fSwFvk+TbIXWHqox/69nTjGKTJdhSLQ95dRqSzAFbLhCgPZIvgcGduGN7c/zXQkdEdPITiGbDPxc6/j6YASBe+ZmxtzcCdwSDT59C7TmY5Qag9Hu8r33ZDoHFjRu9jnMQZcIWulfMf3fi0//sP/FoBf+3vP8pf+3leyuz4R7Nu9Vc49+iaW9uM/RO556Bt59Pb3sLXx5Lj/3eQI95/405xYms8PbhiGYRiGYRiGYRiGYbw0Sb/2zzJ89z+AnSpSGSDkaNbB9fszQvcEh5J++w8iy+vo/jbSXkI6y/Te+0uHJgXUgx3C7lX82pFDSr243H/yHFmS8MFnH2WrH4OPnr711Txx31u47bnPxrEvb+Be+RVRyN7bijnGVzYXtjmK1jaMLza+u/qitylpi+5tr3rR2zUM448noqrXVtKMP3ZcuXKFZ5+NOS9cL5DslBRrDk0XCJyF4vuB9pMD0qt1AbNsC2XX07+lReg013e9QPeTPdKdcs49Wyv3nf1XdpqvXyit5+cF7xHBQ/9Mimau0b5GciW9WjTUJObdHsTo5dazReM18g3P/isW7OpUJb1Q0HlygDTrugxOpPTubLY3UpRSDtAykB20CFJwaf0Tk77jaOtxOnqqufGKA3maHffJ2rFAQUmPgh5Bho31YibsA4IMWLDjgEUZgyZ9XHBOhbXwCo6GN5HSPOEpGZI+vc3w4oCv/c+/h6t72zhx/Pbf/llOnFum390mzTss7R9rvE6/tUP2thX8gaf77BFEhPbZddrnNg61MjIMwzAMwzAMwzAMwzBeOmg+JHz6g4QnH4rpAm++B7npHsqf/m9igM4C3Ju/Bf/Gb6wd63/gVxk+9L5Dr7f8H/0g7pCI6M8XqsrOoAfAaqtj61fGHws0BC79+r8k3GiEt0jt9zxZP8bqa76K9Au4IcUwjC9tLLL7ZcrBwcH459BxDDsOqnzYs9HdACRCuezp3dIi2T6oCdYj22510Lur3VjfDQIuQNkSfK8eFSwaX+nzOcOzDbY6iaAJyAK9Oj+eElYTyHVOSIfKOrwhaj1eXCjWHCSCP1DSrXnFOrla4g5KQrfBsh1It4porx60MZA6vZjTP5fFHOOzl0dIdAlEEafkfqvedwJ9LtLiKO6QjDodPcWePlITtR0JjhUcLXp6fsHkWYFQRWE33eBJLqRGVBaeanOMLjcxkCskutIoVrd2EpafXkOAP/+138UP/7sfJ2jg//8r/4z/+Xv+KzqD9Si1L7jG6toZ9Pdziis9DrgAwP5D50mPLnH0G+/Fd8zWyDAMwzAMwzAMwzAM46WOpBn+lQ/gX/nA+JheeuZQoRuAg525Q8nZew4Vu93mqS+K0A0gIqy159P3GcaXMuIca69/O1vv/VW0nPFVmBGy/eoG2cYJ8u3LiAjZ8Zvo3HIvOuxTHuzhusukq4sdDQzDMJowsftlinPzwqsbKjIMMf+1XyRuwvBYSnplYv+tgLYEzRzJlYJiLYGkql8q6eWC9lNRhBUEXMwEPRKmFdBM8EMlu5CTbyYxV3hVP9kp8TslpBKPj/J8J7EvxZH4MR6JzmV3kv9bCiW9kEOpkBKF2VFub4nXHfdVoq265BP9VoHQgrLrGTmKj865XqD19JBkrxqIjymFCFP1PeQbSdWQ1q5fQ4TQAS2aBHFHzi4pywhpo2hcsM+ufIaMIyQsjcuUDOhxvrJK97Vc3EpJoBeFdgRIKtvx6X9ExBzfOhv1rSAkpCyjGijYHz9QUU9Hz7Cqd8c+yAEHPEVbT+CpNjMEJbscWPpsjhSgifA9b/+P+Ee/+jPs9vb5N3/wS/zlb/pezhw9iSYSNfVCa89FPQzP747zyE+TX9rnym99lmPfeO/8vTYMwzAMwzAMwzAMwzBe+qxsgk9hVjybZu3Y3KHk5Dn86dspn31kvrwIrde89UXspGEYANnRU2y+/dvpPfYgw4vPxt+1k+fo3HIvobdH2dvHL60ujtZud0lM5DYM4wYxsftlyurqKleuXJkcUMX1AxLA7QXURTFxNpo52QtoyzE8nuIGipQaxUgvaBqjvF0/R1NBikDrfDGx91ZFCgUnhEwIiSCqqK+igwMkuyV+tyS0oqzpBjHaXAByRXMFF0Xu/s3ZWDiWXPH9aEfuDgKaCu6gJLtUEDKhXEsgjGRcJbQEbU2Ec9cLuBy05dBMY0BzGa87PJlNBHGNsm/7sQGtizOR0M5Vrt+KKpRdR9l1FOsJIhJFXQBR1DMW5MeIkKYbiDp0KkQ9YQVEydkFdQiuEr4nz2bbPUiQnD7PI5rgyKKYLZN/DChFFIkBZTCXz1twU8J2tC4XBKUci+eKggqeDg6PkFS1MlQLEu2yqvfORaEXssee7NE+WGf94kmyi3GzhAyrjQFDZT1Z4l1v/VP8b7/yU+RlwY//6v/F3/wzfyXeKxF05KgeOxs3FeQNofwVg6e2yLd6pOsLLOgNwzAMwzAMwzAMwzCMlyzS6iB3vR795HubCyQZ7t43NZ7qvv076b//V8kf/TiUcQ3PrWzSev3XkJ696/PVZcN4WZMsrbLyqjfPHfftLunGF6FDhmG8bDCx+2XK8vIyXd/ioBzEA0rNAlxCfOkw1Oy3ZVipja6yBx9HRTMRnqGKto2R2FJORNWRvipDrSK1q7Z1ErUrgB9oYwppAQiQXikYnEpjZDYgw1ArI7mCjwLpOEp8VB9wuVK2JsfdcHrwAr4aYwHlkqufI1qnZ5eKRttyJIr3bqiUHQjZzPUVKEFl3lrd4emEkxz4Z8fHPNlU2wElUGiPlOXx4T4Xxz+rlJT0Gzo2fQ8W2ZaPcnBPiduz5wTQEkjGIniUxVMCOSW9Zst1FZYur+FyQZ1E2/zpPin8+bd9Jz/xH36W3rDPv/jdf89/8c3v4ujxaoeu1C3TpVwsdI/IL+6Z2G0YhmEYhmEYhmEYhvEliv+qP0Vx4Sm4/MzMiQT/jnch7aXGepKkdB74Jlqv+2rC1fNImuGOnLYc2YbxEkQ1wKMfRz/5h2h/Hzl6E3L/25CNk1/srhmG8SXCvGey8bIg9HK6v3GJ9uODGG0tjdoyrqdIP0QLbpiIjRLzaKur6i1In5NveIquQ0eB0aPqgD8IMTJ3Ue6dQ+aeLleWP9kjuVrE+rNR0gBOyI+mMXJ8tukAfi/EsQO6wFqchEna6inKZc/+vR2K5cW/QhIg2SlrYv/4nFY5yEOTol/l8daJ5fgsQQbk7BKIYfN1cVmrTi/OaSQkiCaHFTmUwJCS4fwJgV35LH0uVJboEacZLY6inRiNXq54Qmv+3h1ZXufPfuW3ATDIh/zEr/6LxZ24jn+bSGb7eQzDMAzDMAzDMAzDML5Ukc4yyZ/+67i3fzdy093IiXO4+99G8t1/A3fn665Z37W7JKduxR89Y0K3YbwE0bIg/Lv/jfDu/w399AfhyU+iH/51wk/9t4SH/vCL3T3DML5EENVFSqPxx5n9Dz7D7m89BkS78rLr6Z9Jo913A0qMcE52SpL9GfVXYxT2yG66kaCElqP1zJB0t15fpXq1pFm0Vq3lwZ6lbAmDkyluuKCMamVJ3tyCBsUfhJizvOF8sew4uHtxdLD0A26/ZPmRBvEXyNc9/VtaC+trqYgqoesp6HOQxKjuUV5tR0ZCe0FlOJCn2XGfYiiXF/WQRXdPUQIDVAIOv6DMYuE81XXcIoOI4DiuX0XC8riMFMLqE1VOcVVazw0nNvcV57cv8cB/9x0MiiHdVoff+1//HRtr6w0d07hhofnquHbCqf/k9Yi3PT2GYRiGYRiGYRiGYRiGYRgvNcIf/nv0D9/dfNJ53Pf+j8ja0S9spwzD+JLDVKCXKcXF/fHPUsZc2e0nhwujrDUBPBQrkyjtSQOVSK0srB9ajtD19G9qRVF8urqCC1CmC8LLReavOeoXMcrahUN2Zoo0RnfHBiqhu2DhNfxeILnSbPmNgmaOciMlX23+dUquFvidsvEcqrhC4/XLksJN7McFqUTiUIuSnqaQA3bcpyhlwGJBOzRGh0dGbSs3su+loL+w7SVuJqMuhmuiqB+5BAhlJnOfmRNrR/muN38TAAeDHj/5qz/b/LkSmfssTbP6xptN6DYMwzAMwzAMwzAMwzAMw3gJoqrox39ncYFQon/0ni9chwzD+JLFlKCXKdKaj8bNjySol6hZV8dUILSE0HUggoQY4T22L6/KqgM3UPxuqPJ1T+qXLUfoxI9auebZvb9LvuHH9UMq9M5m4AXXDzBj+60AiRCqvjFVLz+aELpR8Uy3CvxOMbYmj5UVDcrgdEq+4QnT4mgRI4NdMX2Nut6uAuqUpU/0aD8xmOQGr6LZx4VLJb2Ux/Ohfn0JytKDB7SeHcKob6No86EiGvN3hzQg0vQrqZQcEBiOhWWl5ECe4ZJ7L0GGjGzLR/8x9W5kaz4teseI7jzm9pY4UCE+1Pn6MPdXhYJoSko31pvCa5u18ArW9b6moSBBoFSSrYJ0J8TIbq1/Zn7gT/wZEh8f1k/++s+xt7Vb/1wExQ1CLc/8NBtvv53le080nzQMwzAMwzAMwzAMwzAMwzC+uAx6sL91aBG98twXpi+GYXxJYwltX6Z0XnGcgw89O36vwPBEGqO0PaBKEAhdATcRM90w5scuOw43DBNhWMH1ow242wtRJM+E4cl0bG2uxAjxMvPsvbqL5IoUSmgJMlTW3jeMubx7ioqiHrRdXbvq10hkL7uOcnXy8ZU84CqR3Q8K1EUxPHQ95bKDxFGsO4o1jxSQPTck25pSSkdO315QNxWrLILrKU6h8/iQ9hNDQks4uK1FcWSSJzu7kOOKapSjHOiJQCJIobgAnccGtB8fEDKhd2uLsDRR3stWvL6nHQdZU3FjbwIDYIACV+UjFG4SnR8omER2L4rkjsJ3qKzLpwPBHR6h2kygAZXp+lJZwPvYroKjg8MhVT0QFCXTdY6Fr1poGZ8eJEiA1lMD3CjAu8pfriiaxo0VZ5bO8G0PfAM/97u/wM7BLv/sP/wb/tI3/rmxeC/lVPdHP1TtdW4/wtJdxxuvbxiGYRiGYRiGYRiGYRiGYbwESDNIMiia04MCSGflC9ghwzC+VLHI7pcp6cllOq+eRL5qImg29XGQKHBKMSNajjRYR7QGFxlHfE+XFAU/iJHTNaZycmsqMeLbCb4X5upLwVg4nu4XIlFYn4rgno4mh6gVu0Eso5nU6msqDE+lhHSBb7lMxgXUckqLgu8r3ceGtWv6g8k4ZdT/XCFoTbce3Zf2U8NapLJWyq8gZKzP2LnPjA1Y0nMzvuthXH9xdnPGZYRkpllZWH9auBYEEYFKXJ89l8s2PXmm8bqqSraTRdv3dT911UkPRhsgAP7zP/E9uCrS/Sd+7V9yMOhVvZPmIQrghJXXnD50/IZhGIZhGIZhGIZhGIZhGMYXF/EJ3PKqw8u84s1foN4YhvGljIndL2NW33kHK2+/Fb/WQkqt229XuKEi/Slr7pHIWInGIalszxek204vF6RXiokwvCgneIPwLFTR4vl8HVFIrhS4gxKCoq65vt8tkcF8fU0dB3e1yDf9wlzd47IN530vsPKxfdKLOQRtFM4FkGFzjHWyH1j6VJ9kq4hW51OFUpZocRSn2cI+tdhkPbyKVNeqGz8tOjuuJXg7Ehzp1OB06pxHpnzqm3J5qxQEmnfcXZWPsC0PUXBQtRwt0wvZZ7C0B0B+LCPfmE+4LcQc6a4XuO34Wb7pjV8DwJW9Lf75e95dK1j7zGn1+c0Dvc9cOnTshmEYhmEYhmEYhmEYhmEYxotPGPYJRQ5Asb/D3sMfYudjv8v+I39EGPbrZd/3i/DZjyxsS175FciZOz+v/TUM448Hok1KlvGyQlXRfsHzTzzLzuWtheXKjuCGGq3M6w0AkF4s8A3CMsS448EtGWXHgW8WYlc+uE+yP5+EWYFy1Y0jrZv670poCEqO106FvVd1FtYnD/iDQPupYU10HlMo6c6C5NBAcKCJ4gYLJGY9XHoOHvJ1x85rWw1VAwV7DOXKwvpb8hD77jGEefF4krP7MEa9K+fOjOsvGECqq1E0byLAEX0znoloL6Vj85lTMTpblc7jg/nP06Q6D194lK/9O98DwIn1o/zu3/nXtNOp+xQmmyFGXXTthJPvegPSsAHCMAzDMAzDMAzDMAzDMAzDeHHpPfEp9h/5OOXuFgCuu0I42K0X8glrr3877VO3oI9+jPDvfmxxg2/8RtxXfHvlMmoYhnE4FtltICK4TsrmzcdrNuPThATwQmgJOvupqSy/y44sjNwuNz2auuh+vaDM4GTSKMsK4PbL5nqquKJKcV1qYxnJFb8zL+RO1yd1FBvN18cvlot11L9ygbV2VSYs+E1TAAfprsL27tx5wSEklAwa6w/Z5kCeBCDR+fwlE5vxRZMCqa7haPrrYFx/wQ0IlAvPLXFLTegGUB9QV20cECFfcQuzi4uDe0/fzjvvewsA57cu8XO//4v1/gWd2+MQ+gVhUDR3yjAMwzAMwzAMwzAMwzAMw3jR2Hv4Q+x89D1joRuYF7oByoLtD/4Hiv0dwod+7dA25WDXhG7DMK4bE7uNMVevXqVsR2F7JECqIwrcreqLxQnlkovC8sjavFTcQUm6HWJwcJiIzmVLGJxIyY/E6F9xQBBkGCbCdKm4/UD7mTzmax7Vn7KmlgCuF2IO76lzUjCOxpYSyBmL3goUXUf/TEp6tSS9kCODSmjVmBva9SsLcY1W6OWKH1uzo9HCPblaIjMi+si6fewYrjon+ioQfMxLrpkQUhm7hmt1bzUFRBi2+1zY+Chb8hBDtgAI5OzKI1xy70UpKBmiVW7ukj678tl4TkoyPcKp8A664Qwj43RFUUoER0K3isCu253HVxS8HW1AavVD3J1Q5fieWJuLJqRhnVRXQHyt3URXWA33xrziswRBgqt9ZmQUfK4z97XaePGD7/yecfV/9Ms/Q14UVUR3qOVTH48rcbhsPsrdMAzDMAzDMAzDMAzDMAzDePEoe/vsf3rGivwwM+FQMvz9d8NTDx/arp5//HPvnGEYLxuSL3YHjJcGqsrW1avgBG1PxN5G628nhK6j9Xw+jmwe2UnHn2OxkMLg5onl9Ci1tBAjsZOtMK4v/UCyN6rI+PouVBqrCFLGXNkKqI+i5tQAgEr4LkbW58LgphauVyIoyUEgOYj1iyWHLk0EUcljXc0cZeZAleRKQbZTxkj22Yj3kSA7NbjZO6WpoJmrNgUImoAmVfR7qJffOnUJBAZyiR0eqhqMY+qGm2OOanJKclC47D5IIXvj+it6G4KwqV/GPk8RyMcX8NpBEDwtPC0CAZ3Lt+0qybtFXonto/quqh9t0j0aoM3xOCbyKvrboyheu2yG17GI7uUW6fkCWiAFuIZ87NM29wrcf/O9vO0Vb+K3H3ovT11+jnf/3q/wnW/+xoXX6Nx5FPG2j8cwDMMwDMMwDMMwDMMwDOPzSf+ZR2ridmvnAoOVoyxyGk0Ptskeee+1G87aL1IPDcN4OWCKkAFAWZaEciYv9SE2IaHtKJbd5CurQex1uZJeyhvb1EQIyVSe5Zm8zUK0V1dhzjZdqKK4w1QdnS+T7AT8dhEtzmfPHYQYRT4e0GwDQrGRxBzjTcymwm7QbCUfRanPnhBw9cN5e1D1TUhZqzU4lxNbYEXvRHQi1ie6NC57JLyB2QjuaRyuIc+2VP/3eLqT6jpfXwRydmKUuUy3IATpcSDPzN4KAPzAsfLMcgyGL0DKJlt6Gp5FPbr7H/zaT1OWC2zpgeVXn1p4zjAMwzAMwzAMwzAMwzAMw3hx0HwSVJXuX2X54qNICAvLd7aeXZhwcxq558tfhN4ZhvFywcRuAwDvPc5d4+MwZU8OkB9JGB5NCJlMO1zXyC4WtJ4e4A7Kif04gER777Id64Z0wVec0CwkA+QKRZgXR6fKtJ8c4nfnhVFRSK4WMRd4qfN5yAGc0L85axS8xxHsgYW2LEK0Xpem/o0Eb4nDSwaT3NaeNhlHcdoGlcpKvE7GGpv6Otp6ElFPIb3xuWW9lZPl19AJZxBtNm8QPI4sCtkqYyv4eP0Oia4gGgVxbXgAQfrkbKMNY993j7Mjn4qCuCpu6Fh+rsvRh47g8yjQx80KzfeMkmhXP7azhzfefj9vuuO1ADx64Sl+8SO/NdlwMLK0H0Y7/IOPPNc4ZsMwDMMwDMMwDMMwDMMwDOPFI1nbHP/crYTs1t7lheXT3s61Gz12FnnFAy9C7wzDeLlgYrcBxCjq9Y31Q8t0P9Une34qUluEctkzOJ3Rv7VNsdacJznZDbSfHIIXdNoOXKLNd7nsyU+kFKsN9UWIHt7zouoowlvyaKG+qEx6qWg+p5DsB/xBoFzzCwXv4cm0UciXqg0p4muRKC9NVt2jsTkBL6xfPFar70jJ2KDNyeaGgYQl1vQeOpxmX56onWtznBPhrZwrv5O18Krmy+NwZKzqPSzr7fVhk5GySsaRmK+7AZUhKnnjuYG7xLZ7kOXhGY48eZLVp1fwxcwNdkJoeuRUDu4ltaj8v/z1f27884/96k8TQsz77g4U31NcZaPff+giOutSYBiGYRiGYRiGYRiGYRiGYbyotE7egussQQik/V2git4um9eND3OTBWB5A/cdfx1JW4eXMwzDmMLEbmPMsZMnaLWav0Sy54b4vkbheEEk9eB02hihrcDgTIqmMo7CbWJ4xDUKzqIaI30XRFBDzXV7/lxQ/HbZWF895JtJtC3vusb66mO+7Uam8m8XywvqJ0KxcsivmkDW75DuNH/RD9mhz6XGcwOu0uN5BnKJfZ5qLON1CacLnqtukLJGxgaZbjSWWb9yE0vbRxrPOW0hTQ9N4ejwjXhaDI8kC+R6KFvNGxkU4t9OIlDGZ/+Vd38Zrzn3CgAefvYRfuMTv48MdT5X+rBEB4ttzg3DMAzDMAzDMAzDMAzDMIzPHXGO9Te+A8km68++GLD+zINk+1cma7+hpE2J3Hb/4e294RuQdvfz2WXDMP4YskjCM16GJEnCrXfezpVLl9ne2qLo57Cdk13KSXZipOzwRIomwky6ZgA0dRzc2Sa9lJNulaBQdh35sYRyubKvHipSKL4fKLsePLi+klzJkVIYnMnw2yX+oIxR26WiCpIIqjNXlMkfCoSR3XihVVSwVlbjiisVdktCy6GpENIYlV6seEii4OpyjaJ2ZU/uCsXvlCRbBdpxlEUsQ5hqu8pVHhLo39bCHQSySwXuIKAuWr3nRxKSA0XTgN8vq1zeU5vYBA66V7m8/hBeO6RskNBBCQzlKkO5itcWOTu09RiOFoEBPTlPn/MgitMWPfcMQ92mo8dJWaFkwL48Rc4OXT1HrlvksoNS4GmR6VEyNpDqRi7rbQz0MgO5BEVBq9/l6PO3c+zpWyGUnL/pU1w8/QjDdg+ShIwjZKyhlOS6R0kPUBwZR4dvZLk8C0B2qah9VnT00BykB/FZ4eKNVJEqtJvxDRIFilj+L7/ze/jef/z/BeDHfvmn+PrbH5jbDSgtj7SaXQYMwzAMwzAMwzAMwzAMwzCMF490/ShH3/HdlJcfx12KAVk+77P6/KdRqvVeVeSmu2Hv6uKG1o6afblhGDeEaFPSXcMAwrDgmX/1EbSYWELv3tdBMxe/nKadokf5k2cZCZcQBeW9EHXOg5LW+UkuanUQunWBUvqBztPDmA88bYgenjoUPISlmfp5wO8HQipou15/cCJlcGaSJ1v6gWSvbn2dXiloPzOkbAnaqtd3BwE3nAx4eDyptQdRANfU4XdL/KB+c5KrOb4/OfbkrR/g+ZseQlECOdNJtL12cDP7UkqGTN/wTDdI6KIofS7U/L9Xwl142rX6nnbM191AepBx9iO3jN9LL9TE6iCBz77lE5TZfC5xgKxc48jwtVVHlaWHerWc4AqQRHv37FK9DRXi52t8QOt1Vfm6H/leHnr2swD8iz//93jbXW+stdF9/WlWv/q2xr4ZhmEYhmEYhmEYhmEYhmEYLy56/nHCL/1juHr+xho4eRvum34AWT364nbMMIyXBWZjbizEZQlLx9dqNtM6sikXYTbQupFpEVwnunfo+rq1d0Nb2nYMN5PGc+O2x51tsE9PHSGTxk95diHH70ysrqUhxXO+4clXfeP1Q0fQKW29yb5dCqDUxraL1aSWrzrPerEOEoXtqbFJQwdmxW/Bj8tmrM/UnzdwKBmiDbsTXO44/skTk2eu8zbhTh2nP3ELUs73y+cpR56/bVxfyrpYHftDjLwvm/OoUxxiVy/CD37tnx2//9Hf/OmZzgntV51YWN8wDMMwDMMwDMMwDMMwDMN48dCtC4R//SM3LnQDcvp2E7oNw7hhTOw2FlLuDhj+0UWSqwWuF5BCcVPRyDiJUdcsDuyG+slpgTw/mjI4kVB2HME1524uNhOGGwvc9pWxlfiifN6h66Pt+gyi0H2kT/uJAX63bM4jLkL/5ixanTecK5cdZSV6u0GDcAu4oTaKynghP5pSrHhCIrT6q1P1HI4MUQ8qjfXHZfCAEJhESHtatDiG1y6iCYFh052hpE8gR3LIdjPWn9jg7Adupr3TjrbhpYI2P9fly6vc8r57Wb14nLTXIet12Xj+DDd9+tV0L2W0nhrid4oYqd2Yhx3mZfSIKxUZhoXX/xP3v43bj98MwHsf+xjvfexjQPUxCMrBB55ubNcwDMMwDMMwDMMwDMMwDMN4cdEP/RoMep9bG49+7EXqjWEYL0dM7DYW0v/kxSrfNSR7JenVgs7jg3ohEfAS814fFumtsazORECHrmd4MmV4U0bImj+O5ZqvRVHPErg7w/gAAQAASURBVBKhWE8WRpprIs0O6wrZ5YLOYwNaz+ZRXJ0rJAyPps1CvkR787Lj8AdlY30B8M3Xx1V5w9c8G/v31HYCjCK8PRmLthGMyjgSAvXn4kjIWKPNMZRmu3Eqy/STHz3BzX94M0cePUoySGPbSsyZXrDwubb32xx/9Bw3f/o+zn761Wyev4mkiPV9P5BdyKOov7lgs0IijRHxo+u7QnGFxvzoU3jn56K71QOpQCr0Pn2J3mcvLxizYRiGYRiGYRiGYRiGYRiG8WKhj3z0c28kRHvUMOwzvHKeYnfrc2/TMIyXDSZ2GwsJvXzuWPuJAdnzTZHC16DK3a2ZNArXChSrC0RhhP7JtDFCWB0Uq27886L6i86pg9CKRuG+XzZGiEtQXD80R48HRYpoVe4GofkaScxR3kipUECWL7O+f+eCTgqZbjZWH0V9KwWB5mvEc82C95FHj7F8eaWKkG++ewvvHSCD5vuiAoOTGTiJdvVNGwlU0QXXBGr53mdL/cnXfR03b54C4Lc//X4++vTDtXpbv/AwB5+8sLhtwzAMwzAMwzAMwzAMwzAM43MnLFj7fgHozfey/eHf5uKv/nOu/u6/5/J/+Dku//bPM7z83IvQQcMw/rhjYrexkORId+6YKKx85CAK3qrxFTTmph6Jk7PButPHRAgdR2hH0VtdzHcdOoI/UEgqcVUqgVPjz8Vmwv7dbQbHE8puzMVdLDvyTR8jy5VYUCZ1x/UBEhkL7SoQHJQtoey4GKFd9c31FcnjeFwvkJ0f0n2kjx8ofi9EcbeoxjsMyDCacYdWtCUPHUdIorg+uoYMlNbFguy5IX6vHLchg4AMlJCU7K9eRZcSOtw0fbMAR5uTrOjtrIa7yXQTr11UFR17uMdSngwhqV4OweNp46UDFASGKCXZXofVZ9e5+X23cfzTUTDGM7GlH91/F6PmQWIubZ3cT5VYR5d8jO6vCAnkGwn9cy3CctzV0HkyjtsdlEgeoAi4XklytcAvCjqf+syEJD63MOqXQornv3jbnxkX/9Ff/+m5JnZ/93G0bEiYbhiGYRiGYRiGYRiGYRiGYbwoyNl7Pqf66lO2kyX6T32mJpwX25e4+ge/TH7VgpoMwzgcE7uNhbTvPop05i2oBVj6VD/aXIfK8nr6ZNRoJ6858VvQ1BG6nrDk0baLkdEFdVv0pBJWUxnXGZ7MOLijTe+WFqHrwE1Cf6VqG5F4fHRdNzmuiUMzh7YcmrqJUOtjGSHaZ/uh4vdLsislUn2/yv/D3nvH25KVdd7ftapqp5PPzaG7b2egCZIlCcirgM6MASM646gjjPPqwDuOEX11VGQURwXH8Jp1FNM4CiKIgggoUZrYufv2vX1zOvmcHarWet4/Vu1Qe9c+4fbt5tI838/nfO7ZVSvVqjq9V9dv/Z7HQ9QS4nUfcpj7fhfpfNzrV6oWX4/w9QhJLJVLQdG1HSG5lFE9mxIvO9Jqm8XrL3Dx1nNcuvYUABWmQ65tYgwRBktNdgGQMM2U3Mis3EbCTGFKY2p0JyKiSswEMQ0sCYZ8LoynsTTJtXc9ngN3XMvE4mSvfs9tL3nY90o+P5HBZEO+aglzKpEZzYcukO6KkW5I+kyIF7Iwr6kQbXjiNUe07rHjNvwNO7pt/56GPgEP3/DMl7N/ZjcA7/rsB7jr9AOFZvxGSvuhpTGdKIqiKIqiKIqiKIqiKIqiKA8X8/SXgt0kD+lmTMyQveibx4ct9461e26/7LEpivKFgYrdylhMEjH31Y/HVEa/qCpTDaomHhv6esd9lRlwjQnu4ZKn1NcsWWOLx9eYsXm88QRHeq9sSZGJiGwqKo3hbVyxvkTjEobTE8sHSZMmi9ddIm2kebF+oQYHMNLfZGAY3XAwJdcTSW3gSH8uHO1eePPC9YijngvcbioqnVcDQdzu3leRUqN+iIo+2od1BNd/PjfGjdbH5A770e7zPgeaLpvWPPd7Na7wn178yt7hN7971N0t7YcfQkdRFEVRFEVRFEVRFEVRFEUpx+w/gv3KV0N1NFJsgaQC3/xj2H/zPZgXfTP23/zf2P/wc7SzzaNzds6dRLJxIUIVRVFU7Fa2oHJ4ht3f+XQmn38tlevnqN68i5mvvIXqy68jW+9gm3nY70GB9DLwyZh83eNEZMBNx3TmY1zNYMZ9IQ46vAcwBGHWZCEMu0/K+0l3xWTTo2K/AUxKuHYvmE5Jru/uOOujf2bLN6wX/vqsVPq/U2GS66jJXmKZwDOaI91SYVaexKS/nlgmEQbzqwuOJo4OHocnI6NNZta4cPCBIIRHhmwmCiHhIwrKs5FwXSbzvTDypdfWofSex2ue2rE28UI6fm5tcGhvKXiPySUuscEnhlc+59+wa3IWgLd98h+4//xDxbHsmRjXg6IoiqIoiqIoiqIoiqIoinIFMDc/HfMt/28h5eUIaQe7voi56anYp/1fmJueholixG1lWBJENF2loijjUbFb2ZJossLkc65l/utuY+6rH0/9CXtZXVgGgjBqO0LUFszD2VwVhVzeZZhhF/YAIVy2CeHG03FfeGasEG8E3HRE+3AFP2qgBvKw3GMEX+PB16KQ09qVC96dvUmhflZzpFPFyUqYLKjKhogKszQ4hMGWOrUNlhp7sVRK3dxChqeNp4OnHa6l1qQ5uRQKWIOvhc0AJqMoeOfXZjMpd1cDVsA2y+fcZiFke7zhyWbHhLAZsxFh4AKC8D5urRMZ6pUar3rhN4biIvzP9/xh73Tl8AxJSd55RVEURVEURVEURVEURVGUqxVZvoCcO4a0N5CNFfxH/wb3l2/C/fWv4u/+COKuTpezWbm4pSFOLp0aOZbs2rdpnXhqDptUNi2jKMoXNmPkPUXZHO9KRE4n4YnabPeWlyCqlji20/kIc0Gwwy5pA75qMFkQPwexG47aiXavf6mMlkGEaNXhpqJ+ju+crGFp70/AGLJJS7LsR+qLhc7uiMpFN3LO1QxuyvbEbonMiH4rEfiKwbZDSG8flwnXEVXZQ4vzI9PXZpGGP0xqVkbE4Q1Ok5plBKEl56mxl+ERhBDp/T6dzXrzYtc9NgMfQ+tQherpzqj+7MIcjMwLhDDvMJJ/W0zYRIAxuIYNhUseC0mAtOSeDZbJ3eVlZSSCb3v+1/Kr//BHLDfX+D//8i6+76XfzpEbrmf2ZTePb1RRFEVRFEVRFEVRFEVRFOVRRlYXoL0BM3swSbV47sxR/Pv+FE7fHw5EeRpR33/5Kvd9HNl3BPuK78PUrjKjT20bUTZLQp3Xr72F9Xs/gXTapVUaNz7p4Y5MUZTHOCp2K5dFbbLO+tJq4ZgkZnOhG3qCtc9DaRewhs7eGNsUoqYP4nlkcFUDcR722oU80PGyo3IhJV52GAbFVRAf3MDGCcYJpEK0Idhmhq9bpGLo7IpJd8e4SRvG7AWbgq8HUR0nPYHWZEBs6ewxRE0fQpdbcI0IqQY3uq8a/FQEImGM3VDgTogXsyAGR2FsUTPCZAYZEr1j6iQyw7K9g1gaCI62ucS03EqDa3DSJmWJjCZr5ihtcwFnWmHuSXG2RdN76uwNA0dyt/dAP2KouBls02NbvpcrvXOgQvvaKhioP9gOMR/ya5DEIJFBRMAHgdlNRWTTMVIN91CyPJy9gFQMvmp7Gwsq5zKMz0dhBn4ArEWqkt+z0P6IqF63YMPcdTdL9MoYw+TEBN/xwq/nF//2d8m841ff/yf8zv/7p9h4jKNcURRFURRFURRFURRFURTlCiNri5B2YHoXtJvIZz8A5x+Cah12H0bu/Ricui8UrtYxT3wB5nlfi4kT5PxD+D9/I2QDKS3HObjPHUP+8Y8xL/vOR/6idoDZey3sOgQl7m0AohhzyzNHDtukytwXv5ylj/4dvrUx0KBh4panUr/u1kdoxIqiPFYwIg8j0bLyBUva7nD0E3cjeXhxMeAbW0TFF8F06InTkrClC9w28zDaQ8J4vJQxeWez99nVDOnupFjfCdG6J2p6bKv4mLf3x6w/sb+LzLY80caQW92H0Ox23RGV5OQedIl3xfNBTMcTNYXqiTbxWrHtpSOrrB1uUsZ58wFa0fne5+uyb6Iu+4tl7AdYs0d7nzM2EJOBQF0OYCkP6zLVPMy+5adTv69VGNPK0ybCZgEvzH5wFdvO7ythA8DgfRKgcyDBVyzEwy5yIKJfPpPCfRopM/zIeMHkDngIjnI3PbQnRwQ6UjCKL66v8MU//rWst5tUkgoPHnuQgwcPls6BoiiKoiiKoiiKoiiKoijKTpCNVXApTM5Ccx2545/g4sngZt51CLnrQwNCdgPSdsGRPZbrn0z0Na/BvfV/wgOf2P6Aohj7qv+BqU9e1vU8UshDd+L/8k2lQr15wddhn/ny8XW9o33mGNnyAqZSpXboRqL6NtziiqJ8waPObuWyiJIYM1HBr7Y3Tbs8TLesESAjuJvHCd7W4KuMhjUHstmY5pEqtWN5/7akjSjkpLYbo6eqZzPcRJvWkUrov2zLhzVItEV87XzsUqLzS8Xi3WhYdICZ45NkdUdrV6dw3KaWXRuP48z8Et6Ec0ZG/0x3+2eTmXVa5ly3t/CPgRYXqMleLEXxv9bexZ6VJwPQOlKl/kCLqJmL2l0TtDWsPmWCqU+u9+d96P4YILmQ0tlXQeLRc+KAKMyNKcm1Xigz/PRYg1Toi9llj4YxkICkfcF7bmKaf/eCr+XX3v1HdNIOP//zP88v/MIvlFRWFEVRFEVRFEVRFEVRFEXpI6118A7TmEaaa/i7PowsnoP6JGZ2b3Bod4XsxhQ018Fn49+Lt0teSI/jwU/jj98BRz+1s0G7DPIxXk2Ya5+A/fofwH/kr+HYZ8M79L3XYZ7xUuzjnr15XRtRO3QjHLrxURqtoiiPFdTZrVwWSwuLnDpxMri1M4LDu7JFGHMRzFB+5q7LVwzB5VtW3wl2TMQW0/JUzqdUzndI9ySl9e2ao3KpfBeda1jaBxJcw0BS7ky3627EmV24LGvo7I7IdiWl56sPtamdTkvPtadSNva08DVD0q6QrCU8cPN78Nbh2CAzG+x2z2VGHjfaL0LTnGHF3MOaPYozG4MniWgQSQ0QYlfj5gtfP9SAEK04kkVH61CFbNAZ74TKuZR4xRGtZCM5uQG8gfaRaulGg27IcrvhqD3UKa0vAOPc/SJhMwSCTETjy3ioHZwm2TXB6pzn5qffRqvVotFocOzYMfbs2TNaT1EURVEURVEURVEURVGULwik0wzvpasNpLmK3PlBWDoPE7PI3D7kMx9AujmyJ+eQ5ir44QigDjvs0hbBlDqoLoMnvgA++4EdV7Pf/jOYuX1XZgyPAJKlYVNApf65HoqiKI9x1NmtXBYryyvhF2NCOPLt+LtNcEqbAeHaALjwr48J4a2HiQzipNQhLTWLb1gMBtORXg7pQfyExS+5UsE12vDUHmojFUvz2krIDz1cv26R9XKHNkA6H+Gm4oLTe5DO/oTq2bSXH3uQ6mpC7Kr4JOQlX5k5g1iPwRAzQSwTtMxZpuUWzFDMb4OhLgdYN8eoyi42aPZ3EhhwbPQE8AOLJeFhjMFNR0hswz0ZHH9k6Bys0DkIyYUOjfvbI9WtQLzkyOZH/zNiANP2VE+Vi/zdMuIpv+cmOLwl3iQ0vjHE8zV2/esnYIxhBviu7/oufvmXf5mNjQ1+6Zd+ide//vXj6yuKoiiKoiiKoiiKoiiK8phAmmv4uz8Cq5dgch4zOYt84t19R/bMHlhdKIQWF0BsBDZ/Qbm2GN5ZMmTqshEigpHiC96SuJWXhfEO2SzXdQliLP7jf4d93tdcsVDm4h3yyfcgn34fLJ6HxhTmCc/FPPPlmNrOw4mbOAHKDWKKoihXEnV2K5fF8aMPsra6tuN60XJGvOrp7I4xQ3mgRQQTGSQZWiKEk5iMEcE5XsqoH21hPKTTEb5uR0VpJ1TPpJhsVIz2EUEgN4aN64LYPVxfMsHXDdWzacFhLoCbiXq5wn1MeTh1EZILGfXjbYwr1vdVg9QsiGCbnoXD5zhzTTFkjZUKu/0LiKljGJwzx5K5gw37EEiQx9fsA0ihE8OEv4Yb7nsRdmqmeP0i2Fa++SAToqZj45Z6MT+6Fxr3NKlcSEPI8kJ9aO+JSfcmRO3ipJmOp3ImxaYCTjCufOEnhrDlZui+CCCDx81omXi6xu6XPY54ptY7duLECW688UbSNGV6eprjx48zOztb0rOiKIqiKIqiKIqiKIqiKI8F/N0fwb3nj0JO7S4iGO9GBOrS+jYG2zfdhDedw+9CPXY4D7X4HYvdpQL5k18IC2fh5D3bbgOTR8OcP0D0jT+IqY66p2XhLPLgp0ONax4PJ+/Bf+b9sHwRJmaxT3we5mlfhkmqiHj8X/9aed7wXQex3/CDlyV4K4qiPBqo2K1cFhfOX+D8mbM7rte4q0m85tk4Uglhv0VCnmYrxEvBPS0R+MQgkekLrwZAQMB4iC9l1E53iDbCYkVscFBjDPi8XCbYjmBbnmTR9YPKGJDY4CumJ077imH9CfmCwINxgu14bFvwVRME7Tzst22FlvykRfLQ52IYFem73aVhHHghXnLYtidad0E8zvs3qRBteNq1De595j8VVjyT/kYmuTFcExZBWDX30zQn8CYs4CKpkzCN4GibSziaGBKqspuIChOXpjlw7/VkUxGSgKsGN3e3m2QhJVlyuAQ6Byr4qsV0hORSSrwWXPFCuDdiwrgFWHtaA1+zYa7bnmjdUzmbYtf7Cz2TjnHlQx66fuC+WMJ9LxG3AaKpKvUbd1HdN0Xt2jlMyeaCV73qVfzmb/4mAD/1Uz/Fj/7oj5beF0VRFEVRFEVRFEVRFEVRPr+R88fJ/vTn8hCSwycF47Itw42LMUhUdCCPuLtFMC4tCtXbCGXuogqR6/Q+d+ozpLUpGounLisMelfoFmsRExzp9otejJ2YDrnFVy7B1DxEMVw4MVp3+LoO3ED0iv8Cx+/A//Wvju3XPOsrsc/7mh2PV1EU5dFgkxjBijKeufk5oqgs/vQmZNLLfV09kwZhs2KR2GCc6UfgdhC1gviL74flpiuyxgbfsNhmfwHjq7b/JW2DSC6xAQ+2Lf0myN3hXgou7Gwm3wln8roVG9r04Gv5n4kxuJmYdF9CujvuCd0QRNpxGCe9cWXzMZ0DFTp7kkL/Jg1lqq0GMxeKeVaq7OnNgRgPRhCT9oRuAEs1LxJRk71MyHU05CARFQDW51YxHpJlR+ViyEE+uDDrbhqwKVTOptROdKieC87srlHcANZBlAnGC9KwvbmR2OAmIjq7YkxH+m1LudDdv/CB3wVwjBW6AWaffz2zz76O+pH5UqEb4Id+6Id6z+Yv/uIvsra28wgEiqIoiqIoiqIoiqIoiqJc/bhPvrdc6IaQKtFuQwLZph9w9G1ksV67MUdzZn/vqIsSFq/9Ilb23Yxg8DZiffd1NOcPs3Lg1svK+C2AS6q4pIZPKvikQvbZfyL94FuRS6chbcPCmRGhuz/+oV7PHEU+9Y/4Oz+0eb93fvAyRqsoivLooGK3clnEccx1NxwhSS4v50bUFibuafVE3pEvWYIoHW340sWGm4rYuKWGbKa3R0EUlxJN1DqwrfK2u0hicVNRaX0iE0Kgb9L9ZrjpiGwyKq1/6N7bmLq0e+DI6ACm5BZqcmD7AzCCDBSOV4LDvMfAnoKuC33T5jKhNChEZFh/Qg1Xu7xsNQYwHRm9LyJh40Ky9QaLG264gW/+5m8GYGFhgV//9V+/rLEoiqIoiqIoiqIoiqIoinJ1I2cf3LyAuVwJZPj95JCgPvT+0tuY9V3Xsr77CKv7bsZFCSsHHgfW0pncxcr+W1g+dBtiLNXVixjv6DTmdjwqn9SRKC6ahYxB4go+qY2vuNnY7/wgbKxsXqe5usORKoqiPHpoGHPlYSEirK6s0Gq2uHTxEt65sWWjVUf9aDuIqd36BtL5GFczSN2WOnq9BT89RuR0QuV8SuV0Bzcfl9a3a47a6bSkcp43OzGk8xHNWxvlZawglTGLIhFwBKfzmDKmIyF3dRmZEC9nJAsZUatYpjmxytrcRZibh5mZ8uqs05FLODo4u1HeB9BYnOTQnTeOHPdxuP541Y3k3RYb7o8dF4bcwNIXTyLVkuuWELK99mA7uMi3E8a85FzYzGBCCHcRkvkGE4/fR3Jwisq+qbHXe+edd/LEJz4REWH//v0cPXqUen00b42iKIqiKIqiKIqiKIqiKJ+/pG95PVw8Ob6ACNaVvxvuFcEUBWSRkP/bRiG8uQjGZ3mmza5Rpx/dMkvqrO6/BQGS9jpiLZ1kgtrGAtW1i1iX4ZIaiCfubPTqCSbkFd+mo0mMIatOjo2KiQhxa23rsO3Docxrk9gbn4Lc8U/jK83uJfr2n9nWOBVFUR5t1NmtPCyMMUzPzLB3/z727ts7vlzbk1zM8NXiF7ERqFzKqJ9KiVbKhXLrQ/1SopDb20Qhx3QZfsLix+XTBkgMUQbRalbehzfjnc7GYHwQvMeVkWQTA3YUQphLbEYc5PX1KfacvJ75e2dgzOXHMsG0u5U5dxtWxrjsBWZPld8bmwrxssM4GRmj8cEBn2vNIxiB6qlOyRnCbsLEYDsy1n1vGB/+vZui3UiYX+sEk4E7v8HK+x7k0h9/mkt//hncenn/T3jCE3jFK14BwNmzZ/md3/md8o4URVEURVEURVEURVEURfm8xdz01OC69vnPSMTIMS9Wu6cBjMWI9Oobl2IB613I0+2zcL7XthRTRKYtJs4/wNyJTzF1/n6mz97LrhOfYPLScZL2OlHWptJcptJaxfj+eAwC1g61tslYTTRe6IY8bPsOU48CTM3B3us2L7N4Dvcnb0BWF3bevqIoyiOMOruVK8biifOcPXkaP+TQti1P5XyKccFFbFIhWcgwA+sM17Cs31LFphRzPhNCZtceatO6rkK6a0DQFSG5lFE9mYbyTY+ftviGLezCsxueeMlhWz6It93qgK8bfCMsAEzH0zxSI5uLC33gc3d31RbybCOCyXNaCyBVUzw/2JETbGfIIe3CPETrYREVbXgw9HJkQxCDWwcrdPYY0noHsQMNiCH2VazE4AQWllnY9QBZtd2f+yxi/vRhqnYPtVMpdlDPF4EsH1Oex9z4UaO1j4LDOmoVx+8jyKZjOvsSOnvjwrVHyxmN+9rYLMyfcfm/g5ffsLg6JEujC04x5K5vE+ZuzJo02TfJ7m9+Sum5T3ziEzztaU8D4JprruH++++nUqmUN6QoiqIoiqIoiqIoiqIoylWFiMBDdyKL5zCNaWT3IfjEPyD33w4ugz2HkcWzsN4Pwd0Vr7F21JHdJX93LBLKuqSKqzQwLiVuLhccgoOvc83AsctL4pjXN0MRTkVA/JZtehvhqhOblonaG1g/xtRF/h47d3b3+hvsu0xMH5y7+QPYf/sTmCgeLacoivI5QsXuLxCaq+usL69hDEzOzVBtbDN/xzYRER780B1k7RQxIIkBD/GqK4QtzyYtRAZXMSFstxN8I+TG7uGDiGxbQrwWROpuGHJXt6SzURBfNwbCg3vBrocvZYnA1yyYPP+0ox/DwElwMVuK4rWTXhhxVzNk0xHpXIxrhHaI8gXQYNhtN7DA6bZXOjndn1zw9UJyPiNedT3x2KRC1BF8DK1rKthWcERnM3EQwAFB8LHHGw+JxRDTXZJEK454xUHmydwyab1FlMY0FmfoHKjiZiLwQrzqsU1P9XSnKD53f/ejIctdwyKx6Yn7SJhfn0DUCg5vH0E2G+5hvOyCcN9rgP6CUsBXDa1rqvi6ZeLOjcKmBwGIKGxWMNnmi8f5r72N6rWzpef+1b/6V/zN3/wNAL/1W7/Fd37nd27SkqIoiqIoiqIoiqIoiqIojwYiAifuQpYuYCbnkNm98In3IEc/GRzWe64J4cnXFjdvB2AoLHcQvA1GfHBkF47bIDYTwoKvz19DZ2pPr75NW0xcPE51Y/N+Hw6CCWL8IN5tLaA/4Xl0jt1BVmmAgajTxPq+c0oA47JCqPSRvrvu79ypboZCsgOjQvwQ5itehX3cs7caraIoyqOGit2PcVyacfKeYzRX1wvHp3bNcOCma7HDX6qXSXu9xfGP3lU8KEK05ntiphhwee5tMZDNROVO6C5eqJ5NiRcyKovFEOdiyYXoUN+kHtsqeZQtiDUjaqkYCqKqSaUgykMQvddvqQXhfrNxAj42MCZUelkI8ngxo3q2nyvGtn3Pdd06mJDuHnCw+9FANj6mkCM8uZBi85zb8XJxg8H6zVWIiy3UjrepXBjY4TcofDsp7FJ0U6O51F1+rfHwnItAOjBeoSBmd9ts3ljFOKH+YHvk3LDYbcdvRARg4hmHmH7+kdJzH/rQh3juc58LwE033cRdd91FHOuuQ0VRFEVRFEVRFEVRFEX5XCFnjuLf+ZuwdH7gaLD7XFZ7Y9oYfqcqEIRe03+vKsawtucG0sbsQEHP9Om7qbRWeCQQgOFw47c8C+75CGltCoC4tYaV/jtxH1fY+OKvoXXmeGGclY1lastnMQguquDjKjZtUV2/VLj+7gaAgqvce2xZmPetxO7bnod96Xfs5JIVRVEeUTRn92OcU/cdHxG6AVYvLXP+wVNXrJ/SVCHG4CYsvvu9PRgpRoLrm2yTBYw1dPYkwVU83LSHqOnH59Lu4in/QhaC43uTvR5RS2gcbYcQ4VeYbC6mvTcuzVldPZ2SXEw3vTaTkbusR8tk0xZXNb3pHnZqQ3CPd/bEI3nCgbBBgM2XljaVkKt8ZGBB9C9tt1sEqB9rY5ujCykDW96XkTqbbER4znOew0te8hIA7r//fv7sz/5s2+0qiqIoiqIoiqIoiqIoinJlkZWL+P/zC0NCN1yu0A19UdvkDmXDqNDdLWe8K7x7NCJMXngQBhzSGEtz7tBlj2driqPzSY31vTewcMMzWTn4eFYOPp6FI09jff7a3qw0p/cVhe58nJ2JOTZmDwahO6r02suqkyM9joRPN2brWS9/8b9VLUVRlEcVFbsfw7TWN9hYXht7fvnCIlm6hW12m1QaNSqN6ugJa/CTEdmkxU3ZYo4TB8mKI1rJsGuuVNyVxNC6rlr6pWscROseu+4wnU3k2TH5no0AGeAEVymvHa956sc65Q10xwibf7+POZftSti4uUY6E2GyYvHa6ZSJu5rUHmqH8OQlTdpUsE0hWnPFazQGNx2RzkdkUxbTLpkAG+Z17ckN0tmoOEZjQtj2bsj20e5D/9mYGTcGkhD63MflwrdxUD2blt/X/DyZgNl6mVu9YX7T86973et6v7/+9a/H+zEPhKIoiqIoiqIoiqIoiqIojyjyyfdCu3nF292u/NoTvAePiae6vlA4ljZmeuHOrzQ+ihHTf1fenNpD69QDxWDiNqI5d5C13dezPnd4U/E9q0+TVSYKwnRWGc3tbYZd3KVC9hBlpiSXIc3xuoOiKMqjjYrdj2E2VkYd3YOICK21jSvW3/x1+8f3lRh8I0KS0d1iNoOoI+WiLODrlmy6/FENoqtgMxmrihphrEvaAFIxUI3w1fIv92TJjR2bQHCe222osmOoXMowmYzOiwt9V091xrrLjZd+2PLhhUdk8DWL6cimRulow/fc3MXGw3WVjS2cB5+UnQiINRAbfGXMDkFjkGiTBZUFIotsEnW8cmiayv6p8QWAF73oRb1Q5nfeeSdvfetbNy2vKIqiKIqiKIqiKIqiKMrlIevLyIUTSGsd6TTxn/wH3Nt+BffXv4r/2DuRT733cz1EYPRdqk3bJaWuvIPZ2whshOQ/G3OHaM2Mf6/ent5Lc/7w5o0ag6vUCockise/rhYB8SE3+rjzmyB3fxj/h/8NWbqw+bgURVEeJTR57WMYs42dWdsps+3+7l+l9mCb9qGkl0865B8JYjcQBOWqIdoYyOVN97zBtDxSNQN5Q4R40WHXfT8sd7dDGRK4Sy6l57oWgvt5IIaNmCB0SxLGmk1bWBNs0/dzVue5xd2kDW7jgdzWPaF7M8F2cFxDawTb9NSPtYnXPWKgdSCmsuCw7aGc2RWDbTp8PSr2lQnRugvzKII4kGoxR7aPIZuJw7GuUzsnWnPUjneCQzs2ZDOWeM0X8n27qqF1uIIRSC5lYVNB91zd0tmTEK84ksWscD8HkcTgLdiW9EKqC+FZ6BxIiFYdycJQ/YjetRpHEPsthVzeCLilFuJl01Dmxhh+9Ed/lK/4iq8A4Kd/+qf56q/+6iv67CuKoiiKoiiKoiiKoijKYx3ZWIXWGkzNg3jkzg/ByXshimD/9cixz8LxO8K7OxuHd3lZP2qm3Pfxz+HoN8dHRVfPcM7sHWNjuOZxyEN3hvkwpid0dxEb05zet3k7236H2X2XmmLEI8aO5iwXMC4rvHse23o+5sL72EFWF/B/97tE3/AD2xyfoijKI4cR2UFyXOXzirSd8sAn7hzrOI7iiBuf/gSsffgGf8k853/9o0gzQwy4SUs2FdG6vtr7QhTA17ouaAmhu0WCu9eCXZOeLk0EtuWpnksxbSFeyxcW3WsRKeSi7gmkpu+w7grtYAoiK4CvgVRtYWy93OBesKkgFqRmSWci0j1J71wvobWhuNjYzjTmA2jc2yS55HqLiXTahj68kJxLw3hzYT6bjvGNfPNALlibjmAH11ouzIePobMvwbhQViomiOeD0+eFxv0t4mZ/ArMJi9RCfnVfMeH6k+AMl67ILIJtC3jBVw1SsZg0XxCJYFuCbTnipf6OAIGwpSav3w2J7ho2tD+R3wMfNhlEGz7c64FFlF3z/ediYCXW/bVy3Qzx3knqj99Dsq+Yi6Y37SI84xnP4PbbbwfgHe94By9/+cu3ccMURVEURVEURVEURVEU5bGPNNeg04SJWfAOuevDcPo+iJIgZD/wSTj+2fCOL64AAumY9I+D70yvQvlBCEJzIex3Uqc5d4i0MQPA1Nl7R0Kb74jaBLzom3Hv+cNNi63tPkLamN1Wk7bTxIjDJXWsd1RXLxB1NhATYV1K0l7DuhTYQsjeLsNCe8m9tP/+9Zj58c50RVGURwN1dj+GSaoJ03vmWDm/WHp+7sCeKyJ0A2RLTaQZEk8bgXjVE6160l0xbmbgMes6cI1BEuh95WZ9N7MBcEF8Fmuw2YBVeWidZAaPd798R7asjVa3HXCDKcYH61hTCGnua7ZwrtfmFq7yUvJy6e6E5FJfre71YQ1+KiJa719z1xUPRdd2GTYLDmo33d8hOBgC3eR9uOmIuNlPFN4V+q0Dbw1uasCZb/r3zNfyzQGWguCMMfh6OG9baRDFB871/h38L86gU9sa/ESEr1tsJ2w2CBND8bkoWRt3ji/TObHMxsdPUX/iPqa//KYR17Yxhte97nW84hWvAIK7+2Uve5m6uxVFURRFURRFURRFUZQvaOTiSfwH/gKOfSa8cK3UwbuCI5vPfqD/+5Bbe0u6JpirCAPgM8RGkOfljrMWkxceYH339SQbSw9P6AZorcOlk1uXy+fGpi2MeFxSw7qU2sp5ovYGEkW4pE519SJxGnKd9/J9G1sUpMUz4KF6+HTd3ZuxdA5U7FYU5XOMit2PcTayFj4Gkw2YYk0QN5vZaB6Sy8Uk0egxYPLOJs0banT2xD1Hd+kXZNl3pjG09yXUOp6oNXoOK4gf/8Vt6K4VRvexGQ/RmsfVLcSbfGG7kBd77Hgvc52W7orZuKVK7XiHqC0FEdtNRoiBaN0Hh7eU7MOLDJ7g2B4efXIpw3ghm47CnPds0X06+ytgDcn5FOuKRaJ1j/e54G/G3LNuSPhhjKGzLwkhz9fHK/O2I7iy8O/W0N6fULmUYTf89hZlA4Wanz1HvKvBxDMOjRT76q/+ap7whCdw55138sEPfpD3ve99vOhFL9pOD4qiKIqiKIqiKIqiKIrymEMWzuD/9GehvdE/2Gluv4FxQvZ2RNLPMUHwdog1kBvCDDB54WjPHf2w+5jdNzJHwVXef5du0xazJz5D3FkHwJsII27T96JG8kiYIkg0IPEYixjByBaOqSuI1KeQuz6M3H87eIc5fAvmtudjahOP2hgURVE0jPljmPW1dY49cDR8EAkCJRQctbc8/laSSuWK9HfxDz5Jdm6t9JyPDb5hWb+lRjZfssdCBLteDE3exaSeibuapecAfCR09iVUz2Zjy2y2l01ymTfdFZcuwlzD0r5mkzkaSSa+A0SonEmJlxzZrnjknMnDqROPceDnocFtJiOubzEhJLmv2RCyvQwf+rAtT7LqR+pLFHJzj6+/yWU7ofZACwbyohfaB9Ld8fic56mndirt5yUfx9BWxWi6yu7/8IxS1/Zb3vIWvuVbvgWAl7zkJbz73e/epGFFURRFURRFURRFURRFeezi/+bXkXs+tvOK2wlTfpWHMu8ynEcbwGSdKxIC3Hz99+M/8wH8/Z8Acke2jUbeQZusQ5S2LqtPP+BOD50IxmdXxtkNhbEKBmTIoJTUIB1yqtWnsK/4fzB7r7tSo1AURdmUKxPDWrkqaTUHduEZE0TFyBS+oFrNYcv05TP1guv6Yb6HsJkQrzga97XKFzfGIKPmcAAksbiJ8Y9quqeCm05I58Y0QBBuy08ItiNELSmEDi+MfcNjNlzpOWB7cWGycUo9xGs+5NR2Q2VMyIstsR0/fvLQ5oaQT3zwuEDUFqJVN3Kui0SGbC6isy/BD2ntRkJYdNP2Yw3sJnVjF6vxsiNuCXbDl5YxQLScjVbs1s+d7T4xmxvoh+bGrbR7IfWH+YZv+AZuvPFGAN7znvfw4Q9/eLOWFUVRFEVRFEVRFEVRFOUxibgMue/2z/UwPueUu6CvgFQsgvzZz2Hqk5gjT+w7uksMOhJX8FFyWd2Y4feul+moH87aKQyES88/Z9UGWXUSGRTXh4VuQJqr+Lf9KuI9/vxDZB9+O9kH34o/fifqvVQU5ZFAxe7HMNvJx22jK/cIVK+fY+5rn0C8d3yIknQ+d08PCrsimE4Qm03bF4XZTEgudojX/Mg3rk8MrQMJ2WxQaeM1H9odDAtjwdUNdsNhOkOia+5qNnnTeMF2hvr3gnF+vLN5G9iWZ/KzGyQX00Lb0ZqjfrQd8ltH0NkXBxf1wHrEJwY3YUOZwWsTycefa+0ZxBcySIvCtFiQisG2fBDc8/oC+IiQg9sYjBNc3ZLVTXEBM2FJ9yajyzsvROuO+oMdasfa2ObAojATknMp1ZMhd49x4VoLgr8IpuOpXsionu6EezNQP76UkSyGDQYGIBoTMb40lDqYEic5QBzH/PAP/3Dv8+tf//rScoqiKIqiKIqiKIqiKIrymCZLQ27uK0wQSQfMK1e9uJmHGRcPPv+53NyVZdz+90Q3Pw1z2/M2FaJ9fGWir5bN97CQXXY+5P+2/bKm6xi3CAZXafRyhGeVel7P4G2EtzHeGFxSo1OfIZ2Yp5NltP/gJ0j/9GfxH3sn/uN/R/a2XyH7k/+OrC1dmWtVFEXJ0TDmj2GyLOPeO+8eu1sqThJuefytpeGeH3bfi006J1dY+dv7escEWPqSKXzNBpG5I7kjOeTFts1+CBQxYDue5JLDZkK04XttAHRmI9L9SW+BYFuexgOtQhlfM7ipCLvhqSy4/jmbZ/EeuG4fg5+K+mVM1w1uSPfEtA9d/mKjeqJN9XxwGksEvhIWDXZgLdnZHdM5kO/e8yEXt1ggMiSXsuL15wm2B+9atJQRr3nEQuuaJBQyhPkZcJ5Lfl3ZXAQDGx2ipYyoJUgE6VyMzQSJDRIb4qWsH0ZcwvgqZ1KsE+KFfv4YXzGIBdvuh6Pvznevf5vPqzEYkV4ueSGI8mLDIHvXlm+EGPyMDLjZy+b7pl3MfdXjx96PTqfDTTfdxIkTJwC4/fbbeepTnzq2vKIoiqIoiqIoiqIoiqI8FnG/8yOwdO7yKpfk6w6fupFFg/Hm6s7cnYcBZ+hVo3THfoWkkwM34qbm8Sfu2bRY3FzZ8Xx5Y8AOhOwUjx3YxCCARAkgGDca3rwvdHdf4ApgyKoN0voMAFFzlThrYV0HI4JgwoaGqP9+HoIT3MfVoqjvPTYrhmg3+64j+YYf2OGVKoqijEed3Y9h4jhmfnq2/KQIe+Z3PSJCN0A8V6fxpH1E18/0u0xC/mgAiQnrnm7O5yHx1ghBbK0UXeBd3bay6jBp/7ht+ZEythXEVJsO1fe5WDq4GBvIG23y/o0PYWBc/eH9mUQDrmfjwueoVXSZ+/rA1VuDJKY3JtMZGr+M6rzdazQe4mUfwsmX3FsjYD1EG1Je34HtSMjzHZs8x8tgA0Bk8FN2JF93Nxz8SN70gULGB5HfeCncc5PXty0J57oMX2su3o8N625g4tmHx5wMVCoVfuAH+oupn/mZn9m0vKIoiqIoiqIoiqIoiqI8FpCT9+I//Nf4j74Df+YBmN71MBrbTOjOf38EpO5Bl7L0fkzRvbzNd97dcNwjpU24jivmEjz/EFQbWwzm8jYGWAkidk+gHxG680irxiI2HqkvWDZmD7J4+ElcOvJ0Fq95MouHn8jyodvYmD/MxvxhVg89nvXd19GdKYNgxWNdp/AcGPHYrD00wNF+5dxx/On7L+NqFUVRylGx+zGMiOA+dZHqyXYID55jm57a8Q7pHRcf0f6zNOPCTbBxQxVfCaGye2G8jcHXDT7eJISKMaRzEb4khLhxUD/eJl7OwAsSlQi7QLyUjebCzs/RFbxzt3BpGSGMezO2CI5QOjYBk/Xnw2wWMWgbf6UyUCZZciQX08JmgGGipidazsIYABnItR6tuJDn28nYRV02E5PNjM+RXhxcyTGf/wxhIIy7G3K9NEy5Ce58M9B0dzXroH3/wpZD+s7v/E727dsHwF/8xV9w1113bedKFEVRFEVRFEVRFEVRFOXzDtlYJfuT/4778zfiP/Q2/D//Jf5P/jvy0F1XTNC9ErJ2MWe0wUUVXFzFR3F4lYvJQ2ub8Hv3s+n/K12h25SbgXo87cvgwA3jx71V/Z1QrRPd8BRMlmLTFjZtj4SQNy697OYNQeQ2Po8ums+P9EKRdwsa/EAe7lDXE6WtEEbdWHxSw+dhygfpTMyztueGYr9D4no41g0F30eiEpH9zIM7vEpFUZTxqNj9GEO80LrnIot/cQfn/vATZKttkkVH494WjbubNO5q0ri/BQYWq23uv/c+HnroIVZXV6/4WBYXFxEDzZtqLH7JFEvPnSquWIxBahY/YXBTFinTTo2hsycudfLaDGqnU+oPtnETBl9S3wghJHdZ09BzLUtX9C4pk1zKNr1O05aQj3uM6J3uGv0yHxwbIti18Wq3m9jiz9SDrxUvPl71VE92qJ5oEy2Xjz9qC8lCRnI+DePojguI1j3JhYzkQlp0Wg+Qzce4xuYLvk0M2MG9P+acdQK5o73UxW1M7l4P6XQGt242P3UWGTPmLvV6nf/6X/9raF+EN7zhDZuWVxRFURRFURRFURRFUZTPV9zf/DqceWD0hHlk3Nc7JQizec5oY/E2Jqs28JUaPqniKg1cbRLJQ473hOgRMdrk7Q0eKr8+4xysL20xsis0N1kK7/pt4rRJlHWIsjZJe52o0+zlC4+GHdGDzB+E572CrNKgOb2X1tRunI17gnZP1DYWbATWhh9DEJ67762NgShGbNSbIwPU1i4ycfH4lpfRntyFG8otPix2AxgZPlYyj3GyZX+KoijbRcXuxxDihaW33sXS2+6mfXSRbLXVO2cIoapNJrSuqdC8oUY2G9PqtFlZWeH48eOcPn36io6n3er3jzX4hi2EC+8PLgiXWc2W7ySMDO295YKxAJ29CVhLuisprS/GIGNSbgvgYxPCuY/Rm6MNT7wwRvD2QrzqsCnES+UNZJN2bN50MeCrhqgj2I3y+m7C4itjFlZ5s75myBrFP2dD2BAQL2SYtMRGndc3uVhsOsUyhuA4Nxuu1B0PkE5Fmxvbewm5y895y3hnfJSHC4o2cf+XmL/9Roq0Nt+gAPAf/+N/ZH5+HoC3vOUtHD16dMs6iqIoiqIoiqIoiqIoivL5hJx9EE7eu3mZK9kf4G2MtzFibE/I7v/kkSQHBete5PPw2SBEaavoEDYWV6lvY6xj3j8Pj/PsA5DULucSC7Sm9tCa3CIcfKcJrfWRw9al2E6TuL2O2eQlqyydY/343Sxd82TW99zA2t6bWLzuaWzMXzM0j6Pvhw0lJi8bjcxJbfX81u5yY0hrU8OjKys4VKTk3fTFk8j68ub9KYqibBMVux9DbNx+uhDCucyRm81GpLvKd00tLCywsrJyxcYTx+UCNRDE1+6XrMuF3qohm4vwlX7obB9DNhUe02zSFtzbWcPSuraCmwoH41U3sm4RC75qcbUIVzO9cN/SOxdyYwuQTRfLAPjEkE1aGnc0qR1t9XODi2CbnuRihs0AL0zc06L+QAu70S8TL2RMfqZJtC4h93Z+TyRv203YsBEgCqJ7qaicu9uzKdsfm1AQkX1i2Li1FuaqO68i4AQjhnjBhTnuPhMD9U0+d40H2sQLaX8MXohWHJUFR7KQYZv9e2ZSoXIupXo+64V7H1nXmIF/hsYrBlzNBge3oz+u/JyPDcR5DhhfskSVEOrclGn4scVUtg6xPjk5yWtf+1oAnHP87M/+7JZ1FEVRFEVRFEVRFEVRFOXzCTl13+YFHkaobjEGb6P+TxTh4xoSV5C4gq/Ug0DdCzXeDTc+HEobGBJlg5GnMzJWia6QIziuYG5+2oAYX5LOcYv0lS6usr7rWtb23cz63OHLGkbks02Fbgju6YmTd9BYONE/aC3NuYM0p/cOly5pYVTwFlN8f2pEiFtrW453ZKwjL+QF4zoFgTvqNEMu7+67ZZ/Bp/8R/8evR1a3TkmpKIqyFUbGWU6Vq4Zsvc3qXedonVxCRKgfnGXqCfuIp2qk59fYuP0MnVMruOVWQSwVA529cQj3nLNxUw03OV4IrJFww603YZNt5mPehFazyQP33l96zrQ90brvO38tIQd098uxm0fbGqJVR+3EwMLGC65hcdN9Md02PY1jA6FeRPARSC0Kgu+gKDogAvearBqyubhQRiKQJCJaykiWg+taAIkh3Z3gB+YxiMJ9N7GPQmEjQRjuhUvPz6fzNoyt+3k2IpuNw/mY8YtMEfBQOZsGkb1bf9riJyLIhOmPr/f6M4TNAhL3Q/iICSHIzYDLvvpQm3jVBxG6ETYAkN+ebNL2niHJx5BccFgRyEqWT5tsoZH8fDZlwRsqi1nxXAS+PvDsSdgkUOjDy6Y5zmtP2MPsV946vsAAS0tLXHfddaysrJAkCUePHuXw4ctbmCqKoiiKoiiKoiiKoijK1Yb/5Hvx733L5oXEX1bA7mAoKrqEBYNEleL7TfHYrF3sQ0Jm6WJ7ZqgtcJV6wbFsXBZc31uMbLivkRIze/BZFlzXg2MSFwTdPLx4r51qHem0MeIRY2hP7GJj17UYnxF1moiNmDx/lMh1Rvq6kiwefjKu2uh9NlmHuROfHrp/Jdfb3XDQO+Cxrhgdc/nA40gbs/0D3gUX+MDn+WO3YwfClPcc+/lzYFyG9RliLGl9Gpt1iDsb+ajCxgJDf17N456Nffl37WwSFEVRhlBn91VO59I6Z9/6GVY/e4Z0qUm23GL1rrOcedtnWP3ICS79r0/R/Mw53EJzxBVsBOIVV/gyHxsOO6fdanP2XXfg2luELNkGtXqd+d3lIVykYpDYBDEYEDuUY6Wbk5kgjBewBtuSQmhuOxSCG2MwfrxTuuvm7o1nOLy6MeANeBnJZ20zSC5mMHg8K/ZjXT88+GBH3Sw48Yovupm7LmYITudxe1DysWe7innMu/WJDa3rqr1+gIJT3QBWIF4rPhc2z49tBGzad1MHcdoU6htj8JO2NIR46LB86L36HmwbzPDz2r32wbks68MW3ffD5yaetX2xenZ2lu/5nu8BIE1T3vjGN267rqIoiqIoiqIoiqIoiqJc7Zgbn4K3CZ3aFJ3aNN4OReOUfiTKHbfNaM5mgwTnbuGgHQmxXd5nyfvCUbv10McS1zJ2WO4ebWH5ImZjOQi6vQ7zHNhI7kw2fSH3q1/LxuxBskoDl4c/nzpzN3MnPs30ufuYOXN3af7qK01t9XzxWuJK2BCwU0bmDGzaKjiyp87ey9TZe3vX1Vg6XRS66YedNz7DuLR37414ko3lntAN4dmw4gp3Ru77ONLZavOCoijK5qjYfZVz6QMP4DujX5LSdqx94HhBMC0jagrJgguCsYyKssPYTEiXmix94sSm5bbLgUMHOXj4ENXaUP4TY3BTFlcPobk3zUmSjC5MDCFHtl0P+aR7Yu9QGduWEVG12z9xEIIFSufREFzZUrIusplQPdkmWs5C3RIjvBn5ZbB+EMzths9DuwwI50I/tHfJYg3A1yydfTGuEUT7Qed6Z3/C2uNqZNN5OKCSy7dtIVrqPhdSEPttRzAtH9zvUDo3vmFJp8fkWBegK/SXd0/U8tjhTQzk96zlw7h8ULpL+7AD946+Y12MsHHHubIaY3nta19LoxF2Q/7Gb/wG587trL6iKIqiKIqiKIqiKIqiXI2I92zc+wnW9l5Pa/YArdn9rO25nubM/r4Y3Mv1XBLGexsEQXroPZ+4UTF1KGz2dsKnl2aDdmWCcv8datdt7m0crnFgHH1fkkFMN4WiC+OXrsAtQfCOkhCOPUoQG+P/4hdoLJ0i7mwQd5rU1i6SDAi5QEEIfqQYCe0Oo/r/SM5s6V9jjvHFe2aAqYvHmD5zD4invniKanOZ6voCU+cfYOLQ9dTXLuZzGDYBYG2hvvFFIXtbT5TLoLm6dTlFUZRNULH7KqZ9fpV0qVl6zrZ9EEW3ge0IlQVHe38cclRvQryY0dkbc96ucvdn7+TYAw+yuvzw8njP7Zrnpltv5glPfiKz83P9E8bg65ZsNiabHh823U1FpU5eIxCveyoXUuKFrFSUNoDJKHdK5y5pLERrfqzgLdXyPxObQeVCRu1YG7viyhdfMPavzGaQLDnsRp7Pe+jajAMygvBdglQt6Z6E9qEYXy9efDYXs3Zbg+UvnqC9vzyPjU2FeNlRfbCNaRYXNzYLGyXsmifaGBWlAaQRIZs8TyJBgB63idK6MQvWfGx2w0O6ucOd2CARIb93FHYSNu88j7jyMZexZ88eXv3qVwPQarX4xV/8xW3XVRRFURRFURRFURRFUZRHCtlYRe79F+T+25H2xtYVhmh+6v207729eNAY0vo0zZl9I8cvl2Ej07ZaKntfK8XjBkLI8q5j2ruia1y60muoHITuuNeYN9GAOBuBicLvNgrhubs/Ipg8ZHk3smWYjyHB3iabOsYfDVxcKXy2aRubFjWETn2GtDrRH70I1rtc2Jcwj2OE6EpzmbmHPsXEQH7wyvoCjanpIEzbKIjcZc/LNp+hYFyy4f4kVWhMb6ueoijKODRn91XM+tGLXHr/A6XnojVHNCRQig2O3zJxsn0gYe2JdUQgaktp3m67koXw3rVRdXbPvr3s3b9v5PhOaTWbPHDfA+V5UvJ/y74SK2c6JAvZ6BemCCbLxeGOD07ukobFUur+RiSERBdIpyxuJhrtwwuV89lo3XzMUs3DtWRjljoiiA/i7jA+MbQPJiE0ed3gZuLR6pnHRAaplKjmIuDyOet4iEfLmGZG/WRamufadDzRmu+FXC8bv0dI9yZBUB7CxVB/KC3deCGWPPe3jA957qS8Lvn9yusbkfLF0pj/eu199bOIGuUifxmnT5/m+uuvp9PpMDk5yfHjx5mfn++dv3DhAq9//et58MEHee5zn8trXvMaasPRChRFURRFURRFURRFURTlMhDvkXs+itz5z7C2DLN7wHt46M4gMAIkVczTvgzz3K8OYuwW+E6Lpb/6tX79kU6FyYvHsC4tHLscf7eYXEDufgYkqhbe59ks5LseHkNPrB4Mpz6UX1oAHyXYrNMfXx7ScnAmfDesdiE3NfmLyWJ7wA4E24Fj3mGHw7RfLrc+C+756I6qeGNpzh2kOXsIjGHi4jGqa5fyewdppdHL6R21N0haq4V72puOHWK+6CX4T//j5oXEbxrBFcI98km1kAvc7LuO+CXfip17+PqDoihfmIwqa8pVQzRRHXtOSozQzSNVWkeq1I63qZ5OsR2Pa1ha11RpH0rAGKrnU+oPtmleUyHdm+ATg+0IyaUUXzFku8oFwgvnzjM9M0Ot/vAEvoXFRcQMLkhy8o1ypV+0XqhcysCD2IFCPrifu4shkw7ll+kW7bqkvSAxvfomC2HdjdDLTW2bgq8QwpIL2JYQrWbBHW7oOczFGIhyQdaEcDimk3cYUbgQAaRm8FkIi44HicFNRmQzURB0nVA750hbQjofh/srIdy4bXt8zSLOh5zrXT17QKA2qRCteiTy+KpFEoPxEK0HMdtNRZi8LXy4btsubg7ohSwvJE0BYkO86vA1i68YJDL4miGbi6mcTfF1g0kld9DnDVn6ub7zf3rrHOmGRx9YZw4+EpYQVr2bs92FOcPKgEt+/JLMVCJsdXykgDIOHjzId3zHd/Drv/7rrK2t8eY3v5mf+ImfAOCee+7hxS9+MWfOnAHgbW97G3/1V3/Fu971LqanddehoiiKoiiKoiiKoiiKUkSaq8i545i4guw/Avd/Arnzg9BcxcwfwDzlxZiDN4Wy3uH/+lfhgU/2G7h0arTRtI185O1BzH3uV285huzCyfFCN4AxZJUGlebyjq6tDOk6sruhwQF8FlzWxgQn8bjImwKSu6q7dUU8g+EyDRBl7X7blHtgLELw9g2I5b3XiH2Zd9SzvQNKco+XctNT4f5PjD9fn8xDyBdDrW+FFc/EwsleGPLq2qV8XIZOUsfnQjeAq9RJ2msjbvnLYmIamZxH1pfDMygujEH6weG3NX4Ek7ZxlVpvLuXccdK/+mUq3/zDmNrE5Y5QUZQvYNTZfRUjIpz5y0+TrbRGT3ohWcgKrtjFF0zh65t/2U5+ZoN4zSMGXMP0vvQFWH9CPQivY0gWMmoLnsY188w8/gDJ1M6Eb+89d999N96XhJgWKeSdHiRezKg/NJSLZPipzYSoNbwzkLFtBrfwwMfEjLjdTccTtWWkLICrGiQZWHClgh0KuS0WsKHt4XlNZ6JCeHTb8thOCLWTTUeF8q5mRlzVrlpsM1p12E7ITROtDe1oTOgLzwAiVB/qYAfztw9sGuiJ0N1TA89J97pWnjkJXpi6faO4QPKCHdgMWh6OSDBpeYh3MSCD7vR8E8Gw/l7mMu/SeMp+Zr70xrHnx3Hs2DFuuukmnHPMzc1x7Ngxzpw5UxC6B3nOc57D3/7t36rgrSiKoiiKoiiKoiiK8gWENNeQi6cwSQXZcw3c93Hkrg9Dax12HYTWBnLsM32hOYoh64yIjOb5r8A+6yvwn3gP8t63bH8AlRr2VT+PqdQ3LdY5dT9r7//LTcvUls8Vxe4SZ7fk0vBWImk3V3Z4jxjeJ4aWLMZnA2L3wL/SFaDz9rvvqgtRHkfeDBbHMi6CqC0zw5jRcsNO7q2c3SJYV5I3e5DJOcxXvwZ5+6/B0rnNy14mvZDtA+P1UUJaL76rTDaWiNMSfWELXFKjOb2PrDqBEU/l2scR3f/x8JxDeFZcStxev6xoAN5Y/NAzHH3xvyZ++pftuC1FURR1dl/FGGOoP20/K+8/NiLaSmRwT5oh+sxyT4jdKh83BKcwhLDftiP9OhGbCt0APjb4jmPtgQtsnFhg/0seT2W2sWmdQn3vy4XuLTDj8jYPlhmzZ0MM5bnN8w1zvZ2AZRHCE4PPBFsyZNsWXCR9Ebmsf8/YrXLxqiPthunuls2LRxsuCO8juw8H+u8Ivka/THeMxuBrwZHeqzaykjakexMqZzqjc2PChHXnpmzBZzzU72vRPpSMDs0afCSlIdsH+5BoIPz64CkBcdKflxK3v2GozCCRofHk/Zt0Pp4jR47wb//tv+X3fu/3WFxc5Cd/8id5y1veUip0A3zoQx/iZS97mQreiqIoiqIoiqIoiqIojxGkuQYLZ6Bah/kDyH0fR+7+CLSbsOcwrK8iD356QMhOIG31xb4zD/Tl2O47NZeBsQX3MoD8018gR25DPv2+nQ2y04KT98INT9m0WLznGohiouYqiMcntUKocUSIOs2hsNZDQrexSBSDeHDZpoJ3cHO7PGe2x3iPweTvGfvXPprKcqDPXOQ2AwatYuDtEk92iTM6uMPHpEV82MjWocDXFpE/+knMC74Ouf92OH3/FR+FKRmJ8Zu9lN0+7Yk5VvfdXHCxpxfPYid2MdFuhnD0xiBxhcxY4tbKjh3jRnx4rgb68MfvABW7FUW5DNTZfRXjnOOBe+8jW21TOZ8RrzgQyKYtnT0hh3K0nFE72SFedqw8a3JrZ/dnN4hX++qtj3JR18L6bY1NHbPJxbSQu7q2b5q9L7oFa7cXukVEuOuuu3bu7F7KqB8v2S03+ORmnqg1JvmzH7P4kDx+uYCvGXy9ZLefCNG6w5ZE/BHyuUtCuJ2oXb6L0FcNJKMjCO56i69abMcX+ujmX/exwTXs2PoSGyQK4cptZ9CpLdiOYFwImV5wdueYjidedkRrru+0Hpyb/H74uimtnzUMtj0+9LxxYRwwpowT7Jj/+ogBsfmuzuGxDZShW677bwSNx+9l7ktvKm94C+69914e97jHISJYa7e1OUMd3oqiKIqiKIqiKIqiKJ/fSKeJvPdPkLs/3Bey4wpkxXeS/XzSxciEiB/Ji1wQvLvlhhzS5skvCuHNsy2cwkPYr/peuP7JcO5YGO/ea2D5Ev7T70MWTmNqkzA1h3z2nzGdjXxMhk5jhtb0XjCWuLVGbe1iGLvrOq9lQE42Qeju4h1GPBLFiAk5GK3LCnm4R4Xsy2BIoB59u7hNd7cxJSHHd+bsHuypFxWzm5d66J6XYiz2238G/+dvhNVLm5e9DLyNimKxicjqU0SdFsZnYAy208Rsw5nfayNKWLj2i8Y444NTvL5yvnAsaq0RbeV2L8ENbcAw+49QecV/2XE7iqIoKnZfZTjnuHj+AosLi7isPKeKQAgXPbRRSyxburOTCykT97dLzzWvq9A+WCmvKEL9gXYItR1BZ3dCNhvCbSeVhLldu9i9Z3dv1904zpw5w6VLY77Y3ZgvXREm7myWCs7delHTj08NIgTxdcxXejZlaR9KqJzNygV3J8SrbuyCoDMf09mX0Li3VeoiFwu+MX5DgG15TCqku+PRxRUhjHm6pzyXOoQNC3iIN8YIs25zp3X1dIdobbyoK/mGiNJzlvE7JPONBCbzYzcymGz8Qqs3leM2K+RlfMMWxmBiy4HvfCYm2mb+nCG+8iu/kne84x07qqOCt6IoiqIoiqIoiqIoyucnIh7/Zz8Hp+7bXnkAE40I2UZcSbnhHH5FdzfXPh5WFnYW6tpYePKL4OgnYXUhHIsSxGX9HNAD4xruM61O0GnMUl271I+W6TKsFN9/eizGSK+MEIRQiZLiuziXYbP2wxO4R66xXHBm4OjWYrcdmouhtvO56YdeL57vCeHG5sagIHL3BG4RkPHvjHs842XwL+9i/Mvry0MgbDoYGL/QdUwPz48fffYADt4YnuXlCzAxi7ntuWxUJlm/71PjO/aeqQsPFCKt2qxN3F7f8TVkSR0GjHTm8K0kL/33mrdbUZQdc3lqkPKI4J3n2AMPcvH8hc2FbjvOTUt5OO0B0t0xnV3l0etlk3DhlXNpT+huHqmS7Yp7wnraSTl/5iwnjh1nq70TszMz5cKnCNFSVj5+k7ubS0OFC3Y4V/do4xgnpfV9YujsS/I+xuzFs5DOR6XnXC2vHxncxGjInNAJkJXPi8kE0w6udrvmy+tnAmPuTdfdTASmWT4PtumJVsvV7ngpI1oPOdxlnGbtAF/efzZpS0PA94RuAFu+lAsL5PHngDzkefnYgmt+aNEKSObxncsL2XPPPffw0Y9+dMf1uiHNV1ZWLqtfRVEURVEURVEURVEU5XPEg5/dttAN3feyo6G0L0vKnJiB65+0szri4VP/0Be6AVwaRNiBd4tBDO2+POyTtNepLZ0lyjpEWZsoa2Nl9F2axRcETQNELsVmRSOVRDE+Gm/U+VwgkAu8A8J094WldH+CM9v4DOIE9lyD5PdxxMGfbyIo3OWSuS1l8Sw0pq7cxXW7h7BBwfffqRvIxz3sVreUjdW+8JuIvvEHiV7180Tf8qPYL/pSfFpulOtXsnhb1BeG7Uzb+VsQgkhOHllTAH/qftp//LP4i6e20YKiKEofFbuvIhYuXaLVbG5eyBAWT2Vu2s1ctr36ho2bq6zfXCWdiXB1QzobsX5rjc511WJZJyFM+oNtkoWw4OnsjpFq+WOzurLK6hZi3+LJC9g1R3Ihxa47bMuHMOVH20it5IsYIBPqxzvEiw7b9EH8dYLpeGzTBzd12TeoF0wq/fzVQm8x46qGzt6Y5vWV4Fr2oRw2D6Hdrd/xiAit62ts3FqjMx/hagZXt7QPJDRvqEFk8pDgPgjbXgYWUITNCRKuA5//ZILd8Nj1sKNODNhUoB3G5qOQIz2btLjZGJsKpu1DWHAviMmF4ijc02jVUTuXUjnTwa673twkF1JqJzpUT3aonupg1xym7bFrjsrpDpUL+aYKAyQGsb1lX74gzh+5DiF3ug+ZYFzd0tmbILUINxXh6rYvSg8K3YRGBtdT3XbDpo08BDnFnzCmvEJskKrBx6YnyvvYhJD9JWH3bS3GVss3dGzGPffcw4tf/GIuXrxYev55z3set99+O4cOHSo9r4K3oiiKoiiKoiiKoijK5x9y/+2XUekypO2yOvfdDp94986boi8wehvRnN7H2q7r2Jg9QBZVcUkNV53EVSfJqhMjYnQkrhB+fJuyLQDWOxjKDS1RcoV9y4ONU5w7yd3mg8eG3in3rkd8T0wtNCiuJ1wbwB6+FXPwxuCStkW3dA9rR69xGznBTX1qy/zqD4de7uvi0ZKxjr7TL3v2bbWxeYciI7nBjXeF/sRYXFzdNHh6EOs9UdpExPejJbTWSN/1e+GYoijKNtm5IqQ8YiwvLm1dqPv9EIFkQ4uQ7W5dMIZ0d0K6e4sddwaqZ9KCEzub2fyRWVpcYnpmpvScd57VS8thseGhcbS/S8zVTBC7S6icT0P+Z0Ju6ogQPlsqWywmJAjI3VDbPcGbEPo6HXC425YEQXpwZecFm0kvhLibjHCTIYeIyaQ3JoB4aSBkTXeTYO647jqfjQB5HdP2hdDiXedyvOFJ9ybIzMBcdPNeO4JDHXCNYh7tZDE0FrWEqFmMCmDzUOHxigt53+mL5P1C+b8Roytblx9yYQyC0DkYIzb0hzVIzeBqNoR8L8xFPuHGFNs15AvToXNDq7AQySA/mYAk+ULNMHYx2Xj8XkxJjvHN6ArdZ86cKT3/3Oc+l3e+851MTU3x3ve+lxe/+MWcOjW6w7AreGtIc0VRFEVRFEVRFEVRlM8TXPrw2xgrfndfOIbfR95Y7TBXt7MJaX0aH1fDuzHvaE/txtUme2Wa89dQW71AdS1PJWkjXKWBpC2ibAvX7jax3oV80V16LueHJ3lnlQatmX00Fk5ic8dyr9Ve00Xhu/eO0IxG3Qx1B+/BGB78NDzhedsf6A42O8j9t0Nr5yG+d4LxrpD7OszF0P0wJkzXYMUsPPvSWofmGkzOUtt/HdnH/pakuQLG0GnM0ZmY681z3FrFuk5fnM4b9UkVm7vCfVwFa3HWEnWapbMv9A191mX4qJ9eVVYu4R+6h+i6x1+B2VEU5QsBFbuvIjI3Lil1CcYgCZButj/qYWIN7cMVqic6/VzU0aY1cNn48NHe+16Yc1+3ZNNRT3zdLNe4LQvh3Q0NXuLs7REZfCylYdOTSxmuYXHT+QWV5XWJDT4GKRmb5Hmyu/PSFaGLhQgu7pIxSsUgXYEdCquM6ukOrWurm16bbXpcZHtCcK//MtG4NP46EA0uBrvjMGAlzG9ed3gUBqic6dDeX7JZIjK4CUu03s8BU1Z/0Pg+enLo87j6DIx/gMaNu0oaHs9WQjfAt33btzE1FcIN3XzzzSp4K4qiKIqiKIqiKIqiPFY4dDPc9eEdVgphsHtu2ZJ8yKabR3kotDhs30U9jPVpcNV234nZiOr6Ih2ErDbV7ZjW9F5s2iZpr/Xq+riKzTplnt+dM/wuteRl37DE3PdRl7/PFmNZ232ErD5NWptm5tRne+HV+6L1FnNXIniPKVgcr3eYvdfAvR8rmncGXMz90Oi+9BXsWB5hoTtQMpLh96xl77+9w/3VLwexXzwkVQwwNRDKvLZ6gbQ6wcqBIDzXls9hRBDJwFisS/P5MPi4itiQjtRkaYjoaaJCPvvuXRzMlW4Am7b6mzgAWToHKnYrirJNNIz5VUS1Wtv0fBRFxNHA/oTIBNF0TE7jYcbpi5vhJiOaN1bp7IrxMZj25i1Ua9Wx56I4Ikr648/mYtr7EtyEDYu+MQsRNzH6mBrAZmA6IaT52L2TFYsvEY0NUDvRofZQm2jVIWXCsslDZZflq843G/g4zL0rCe1uIA9rXjIwY/A1g68Y/FBV2xHqD7ZIzqfYDddzdgO8/18+yBt/58380Vv/DHepFcK4t30xb/Zw3KGSv/KuUxsX8rDLoBPamDwkPr0Q48NETaF6slO+SKpZspkIVzX9kPBl/TPmeRxeBZf0YQbPeUGcIN4jmWftYyfLWi1lO0I3wC/+4i/iXH9R1hW8NaS5oiiKoiiKoiiKoijK1Y2IIOsrSDukj5SLp/Af+N/4v/s9/O1/j6yvbCsc9SD9ENmObu7nQp+DuZ/DEfov7UxwtV7GtRig0lwayZudrC+PhLJuT84PVTZXLLf2cIpN493IK73B6+zJ1KZ7/UW8jVk69ASyejCOuEqd1vS+Yh9c/iaBQu7uMhdOYwacx3gXxFuXYrJO+Fc8Rjy2bEPD5Y7n0WDknXbJJoNPvReOfrL/7KTt8DNE0l5n+szdTF44GqID5HNisg4262A7TaK0FX5PW0RpG+szrMswSOF57/0FeFd472vEF55rU5t4mBOgKMoXEkZkBzE3lEeUleUVThw7Pvb8dTccwUYRR48eLS/gB5zCQ4Rw0OH3MqfzlnihcU8LNxXRPlwZW+zGW26iVq+PPX/hobNcOnmu9JyrmnI3swgzH1wLIbNLEAs+D6FdusAQwQyHfB+gMx+uqXI2LYQmH2y/fbhSCBteHLhgMmHyzmZ5fQO+ZsYumiUXlk2rfPyubmgeTPixN7+eP//bv+odv+XIjfzuz/wqhzrTROs+D0FeIux3PFFz/J/5+i01sFA/PiZskpPS6wJI5yL8xBi7vxeiJYd1459Lsk3O5UjE+LkXwVWDuC5JeMBN6tn97OuZOrJn03a3Erqf97wQuuif//mfgSBgf/EXf3GhzH333TfW4Q3wnOc8Rx3eiqIoiqIoiqIoiqIonwNEBPnkP+A/+R5Yvhjem03OwfKFKyZSlgXI7gm7dsCBUvYKXgYzb++MLKnRmShGN2xPzuOqAwKh98ycvadQxl6BUOaDzlwfh/fEUdrq5QAvCtsUndK9RkaF48VrnoKr9N8rR50N5k58eusBDfdTOl66oxrrrg+pE+3WGx9ESsf/aDL83HkbITah9zyJgM96jutQyW055rQ2SVqbwohQWV8gGgizLxA2SwzlMzcuC5sChsZXeAbyMQ1vc/DGhvYG+0hqUKlT/Xc/jqlsbg5UFEXpos7uq4jGRANry2+JjSLqjQaNRoP9+/eXljEe7PqoKjmc43izDDKl57xQPdHBpoJddeVOZyBJEirV8c5ugN2H9zIxO1Xat2n7EJp8GAcb11fxSUk4cAM+z93t6qbocO6VMfhoTDTvhqV9sBJ2NiblYW6Mg+pDnfLr9nnIb2toHUxKHfa9nDJla9rehs5iTvFC/6sZP/aG/1YQugHuPfYA/+6/vpqF0xcA6OyKS68xnYvpzJcL0q2DCW4qwtVt2GxQgkTgSvKjC2CavuA87+GFaM31Q46XzV3uyt4ytJAbXz9rRKS7k57QDSCJ5cLtx1k5en5sk9sRut/5znfycz/3c9TrdSYnJ9m9e/dIOXV4K4qiKIqiKIqiKIqiXJ34f/wT/Pv+NAjdEN5BrS6AsVu8HzUDP5tT9jat9wZ28J1XmYA6xuW8HaKSXN/GFx1ORkrDTRY+re0+wtLBJ2x7DIMiZnDidgpCd7+boSiSI9c/Oh/xQMh1oJiDetNBbf5+0Qz8MPT7yIjEb/2usvR6Hj3EWFx1AhdXes+rjyqItcFxXxC6ITyLmwvdgmF97hDLh57Ixq7rWN99hMVrn8ra7iOFzQFR7nofnCOJYmQoYsC4voZn1pTkWDfeEz/3q1ToVhRlR6iz+yri/NlzXDg3XqDbd2A/u/cGt+qFCxc4d67okE4upcSrHlcNeZMlMfiqLQjdXfd3TwAvRNAZEHslhAhPFjOShQzbCcdbhxKyXePD3Ry69jCzc3ObXqeI8NDdR9lYXuv1L1aI1oNwLNUQ3ts4IVrzxGuO5pFqEJ1Pd4gXXRBSJXf95mGBslzQtS2PbQe3dfcb1HjyhQ8YCaHR0/mYbDbfieaE2kP5ItEOhoU3mFSI1x2+Ykh3x0EYnsjt2NINCS7EG0Gsj1cdtiWYTr6bMQKiATE276Mw706IWtK/Lzneeb7/j9/An370HWPn86Z91/GWH/tVpp98ELPhqCw4TOrBGtxk1NsMYDccyaLDZIKvWzq7Y3wjzFm0nFFZdJiOx6aDNwuyRgiXb1IJ1+XyPOgWssko5DSPCP96sKnHtPuObdtywRlu83DphrBBoOvEH14clm0YGF6V5mvYzRz3thJz7cufjI2KOyC2K3R3c3SfPHmSOI7HbjIBdXgriqIoiqIoiqIoiqJcTcjCGdwf/PjQwQE3ioCPK6TVSXxUweCJOi3izkZRfpathcKxY4CCa7U/huGCO3cJexvRmi6+q2pN7sJXG4X+a8vnqa1fyuvErM9fQ231PI2l07i4yvFnfj1pY5aZk59l/z3/uGW/Pfdz4XqK7vSRMqUNjW4lWNl3C1m1QWV9EeMdIsLkUvm7tkcSMWZ74y/dTPDIIsbgklpvfMZliLG9sOJgwKWUbefYzjPWnN7H+p7rC8caCydoLBbvg4srxWdbBJu2tn4Ohp51gVGh/JkvJ37uV21jtIqiKH1U7L6KuO/ue+m0x4eRqdVr3HjLzQB477n33nvJsqx//qH2SIjy1sEEqQx8qeQCY19w3eRrzgsTdzaxaf8RWbutDtH4OjayHLnheuqNxtgyAM31DR686/7+gUyI14cG74RkyZHNRHT2F7/04sWMibtb/aFWDG66uHg0qRAtO4yXkXlJZyM6h/rh2KMVR+VSVigT5shgm64n9nfp7Inp7O/Xt20/UsauOZIll4cpL86ZWArzaNoeW+we7z3/9U/+O3/6kb9hK244fITf/+XfZM/8LmxzKDR4iSvaV0xBJK6e7oTxi3D/A0epxglHdh8Omwhmh8L3iBCvhgl1k6ML9kI4dhGijdFFTP/CxzxLZszvAw1kDUu6Z/M8Q/uecxMTB2Z7n++9915e9KIXbVvo3gkqeCuKoiiKoiiKoiiKonxukHYTefDTkLYx+6/Hf+xvkbs/PFJu8DWTixI6jXkkivsHvaO6voiVgeiZD0fwHg6LfZli90jYahPRacyGkM/dNnxGOjFPZ2IOwZBWp8BaGosnqS+dpjl7AB+HqJxRe52FI0+nM9HP633tx/6c+kp5+snBcWxHwCwViwvXPiqQZ5VGvtngc0vpJoWRQo+e2O2iCj5OMN4jIphoYGzeEWWdwljKQuvvhKVDt5HV+u9GjUuZP357wYXtbYTExVSnNm2PjGPrZ8UU//4wmKd/GdEzXqo5uxVF2REaxvwqwvvNvyC965+31nLdddcRFb7cRutUzmfB4TyE6ZbfbK+DNTRvqOIHv2+2eGK88xx74EFazdam5Sq1KrbaD7td+gUcGdykLQ1Nns3FtAZzh5e5gRODn7ClocGTJUe80FeXh0Om9JoUKa9/ISNeGlCnyyJ5T3Qd4CV4iiL0UP2dCN0AR08e49te8youLFzC10xpOPVBTEdG+j+3dJFX/9rr+NI3fCtf+t//Lccv5qLtiPPakE3Y8j5McIH3WpbRW7OtxdZmW3C6DWzjv16S9f/HxHvPK1/5ykdE6IbthTT/kR/5kctqW1EURVEURVEURVEURSnH/8vf4n/j+5B3/Aby97+P/18/AXd/uBC+uix0deRSqusXi+9HbURamywWNOMCXz86iLG4pI4fEGCtOGrrl4hba8FV6zMsQnX9ElF7nbQ62csZvjF3mNXd1/eEboDOxBydRjE65/KBx13+GOmHf+8zMPMyWGI0T7kBkqtA6C5lTJj0K+Eg7M9K/ruxiIkQE+FtTGtiF62Z/XQmdtGe2kNncjeuex9FiLL2iOj+cOewunqhOMYoIasUjW1l79K3pPT9u2BcNnBOkNv/nuzPfx5pro2UVxRFGYeK3VcR9UZ9R+fr9Tq33HILBw4cYGZmBtsYdbnaTKie6pBcTDGtki++rug6Jneyb0SsP6FB63CFdDYKIukWeOc499ApNhZXcWlWWmZxYRHnHcTB5Twup7avWnxc/hXdvqbC6lMatA/EyJg84r5ucZPlj3n1TErtgRbxpaw8Vzgh5HmZ2G6A2okO9QdaxJfSXsjyYiFDNhfjGqMNhNDnhH69FFzWOxW6uxx96MEgeC9ewtdDKHgfUSpKG4LgbToeL8Iff/CvecmPvZJ3fvy9AGTO0TQpElOekzsKofJLN0tEBqkZfBxyqI/rH9h8s4XQW+iVNWDbWz+Lldn+DsDPfvazfPzjHy8td8011/DkJz+Zb//2b+c5z3kO119/Pd/2bd+25QaUYbqC9759+0rP/97v/d6O2lMURVEURVEURVEURVHG4z/zAeT9fw7p+GiZm2G9I0qbxTbjaghlPchl5GgWKHn3Vfa2a3zebsGEkNHG4OMqfsgpm7SWsVmz0EJlY2nEmeyGxMooz7W9WZniiAckahFCbuv8J78GrM1/8rSR3fSNxuTHoisiED8qlN234RzsxpbI9mOaoyhkh9/zuerNWdSfL2MwQKW5TNTZ6DdkLVllAhclGO8uT3TeApulI8eG+xn++xByt3exJQrSuwFT8ndkEIzPDUvd84tn8R8bn9ZTURRlmHjrIsqjxa7du1hdXhl7fn737pFjURSxa9cudu3axVo0wbnbHxwpYwSiNT8acpquezn8Ppwvut9JyFWdzsdbfn2btidqetqLK5w8vYKxhul98+y5+XAhd/LK0nJeIeR7JjJIVTAlAqb14Du+GI49xzcs2XRM5ZJDMkFKhHHfsMiaL4b27l5aS7Dn0tB/THn+58Qg7fKlS7QR8oNLZOjsjaGkfzcZYZtZucM5XydJDJKCbCF01+IKP/+NP8Sb3v0H3Hfu2Mj5ruD9+2/6Dfbs2h3GnglRc1S0NcCxkyd43a//DB/9+Md6x+cnZ/npb/2v3HzdDSHsTbm5HaxB/JjdgsZALOAMPjFEJZskeuH0xyAQQr2P2chgM8G0PFIbyIcuwurGGmcunWPJb/DeP/sUp06d4uTJk9x7771j+zpx4gS/9mu/Vjh27NgxXve613HLLbdsMspR7rnnHhYXF0vP1eubb2hRFEVRFEVRFEVRFEVRtoeIIB/dmVmkjChtF4VeYxBjMYOhzC+D8O4rf/lnDMNhvHtv1YzJTR/5+8dc8BPARdVCKGgfJdisL+wbIE7buIFc3XHaxLi0kAtZ7Oh7VTGWuLVKY+EkGEOydil/V1cUKHOVMq+Ui/VD0RwL1zl2QgxgBwTyqxMDiHj6PkEZuJeE5wPy+7LDEPe9+Sl5M9p3B/U+GKCysUwzrvWc+hiDS+okrUfG+ezjoqHOpi1sZ6MQHt14B1knPGP534tU6ohLgjhvbP+5FYCB8OUjfwtB8JahAOz+rg9jX/D1pQK5oijKMCp2X0VUKlWMNaUuZWstlcrm+Ynj+QZuJsIuF79gxUA6HyPJFl8MwojLOBwXyEXNaNWRXExpHamOLF5MxxOtD+Xd8MLymUuk7ZTDT7lx4PjoosYnYNolYa87nupDGe3rqiPXEK066sfDAi9aznDTEZIUF28mAyKQrCT9c77GCv0IUmH0+h1IAqQl9W2ob4B4OSObjUdzmtvQP0Pr497mAhu+4D2e799C6P7d7/hZXnjrM3n+TU/n63/tP3Pf+eMj5QYF7927duMnLJIYopX+c5G5jN/+P3/IL7/lN2l3+gvkVzz35fzYN/xn5qdm+2P0YROCVIdzrNAXokueGdPJF4IWvAErJdWrBpMyshEhCN3FA04cF1cXObN8IfwsXeD0xgVOr1/i7OIFzl46z7mF8zTbm4fQ3w579+7lFa94BTfffPOO6r397W/nFa94BZ1Op/T86173uoc9NkVRFEVRFEVRFEVRFAVYOg/LF7YutxUjL/wEU/Lu8nJyIfeEUwlO5259GW6x1PEKRjwyGJw1d88WSpeKxwaTdYg7G3SlRNtpEaUtjHhclLDv7vcyeeEBrPRH069e8n646zrGAL4gWPbE4NHJHDp2ZYTLh5uXeiv6gjd9cZu+Q3vQOS8SYV26qcu6397AxoEtrUDdUkKcNsmq/QiWEiWPmEu+tnIeTMT6rmvBGBqLpzAmRPjsbsgwBMHbAy6p94R4iWJ8XMX6gRfh+WaOrTDeIwNmOdpNyDqQVMdXUhRFyVGx+yri0sWL48Nxe8+ZU2eYmZulMdEgjkdv3cVzF0inI0zdEm24INLGebjpYQG2hJ7T2I1szet9rD/Ypno2RYyhfaT4RRM1/dhFxsbCCs3lNeozIedNY6JBqzUgSopgWwSHdZ4n27Y8yWKGbXrSvQmVM2kIz12z2LYnWciIVn0vt7ZJIb7kkKrHV8JIbEcwqQTHdSJh7deNFmQp7Eo0DkxTkEh682VcGIskFokEcWB8vovPmp7IG9arhnjJIVWDxMHRjDXYlgQxd3ADpCn27zPPD75lE6E7qfC7/+Fn+ZJbnokI7J2c589f/Sa+/v97zXjB+7Wv4nd+47fYPb0HVwVXt0QbnjvvupMf/fmf4q777u6VP7j/AD/5//woL3z8s6hcyvpjNITxZyCpy6+JsPDozhlhU0Nvbe76myPC53BfvQgmX9sTGySfY6kIzXabc4sXObt0gbNdMTsXtM8uhd/Pr1wKoe8fBkmSYK2l3S4PbbVnzx7e85738KQnPWnHbW8ldH/3d383r3nNa3bcrqIoiqIoiqIoiqIoivLIIeLBu56AaV2Kj2Ksy/rhwU0IySw7cfHm9H3apnBsO2KlySXkgcGGf4zFRwkgeBvh4iouqeWhtaG+dJqkuTwkrpueYB3n7vC0MUd1fWFgnONE6/KRFUV32braFSO4iXfkqib3aOfO4vHB47s95POWu7m7x/AuhPHuOpeNxUcVbNbZtM2e4G2i4aNbjtuUvBM1tz0XPvP+LevuFAPUl8+EvwkD1bVL+YkSR3bJuHyUFMXuXqubX+dI6oCJGYgrOxu8oihfsKjYfRWxWQhzgJXlZVaWlzHGML9rnn0HDxTCeKyuhPqSGLKZy7+1XdG7jMr5kLOjcaxN51Cl77R2QfjcjLULyz2xe373LhYWFvtfkG7A3ZvndJFKEGd9zdLNUxI1hajpMKnvC93d+t3qbSnkc5ZooN3u78PpcYbF2YE81b47lcaEHOOYUH6gfjevt8n7py2YxOCmImzb90/mzYihL3R7zw/8wRv4szFCd7UrdD/uWQMdCvumd/G/X/0mvm6c4H38Qb79P/4Hfvc3f5vdu3fTTFv86m//Gn/wh/8L58LNstbyra/8Fl7zrf+RyWoDL4Jfddis3w/578ZDlM+rq0vP0Q75XAiFKAAQHPyr66ucWb7QE7JPL13g7NpFziyeD0L20gUW15dLr30nTFQbHJjbw/65veyf3cOBub3c+MW3cf1TbuHw4cMcOnSIPXv2sL6+zld8xVfwT//0TyNtXLhwgZe+9KW8973v5dZbb9123z/+4z/OT/7kT449/93f/d38yq/8iobdURRFURRFURRFURRFuVLM7oW5/bB49mE1k6Qtouw87cndYGzI4W0t3iS5gJljDCF85MMzY2zJgKAovc/SO5fWJkPY9YFw5z5KCmHLLR4fV4lyUbtbcjhMeVadJOo0iYfylm8rJLlsV7K/AgwIrUGwtr37sZ0NCAJ4m0CUvxzO845bn40K9oPdUgxf3j2Gc0g84EI2BrERxmdsznbnq7jhQIZytUeVKtFtz0fOHYPzD22zzZ1RWz1P0YkOw6J1cHhniB0Qpcc9N1vlF5diKHx72/P1XaqiKNvGiGz1Xxnl0eLeO+8mTdNtl5/fNc+Bw4d6n+/89Gd5pG/n/N8v90TedC5i9SmNkEvbCcny5gu92cN72HvzYQCyNOO+u+/B5yGBTCpEa6Mhd+yGI1nKcFOj4r1teqK1fDGTCbYkLzTkYneZs31Q8HaCHZMuxsdj6ucucQP4iPJ83TWDbQs2LY6tG8Lci/ADf/Az/Nk/byJ0f9fP8sJbn1U8IYLJgmP8/MolXvHbr+X+08dK27j++uv53v/0f/OLb34TJ06c6B2/+eab+cn/9yd40pOeRLzsMF1NPvUkF9IgeEv5fREDaSJcWl4MInZXuF48H0KKL57n7FIQtJudhx9WfPfkHPtn9nBgdg8HZvawf3YP+3btYf/ufT1xe6o+MVJv/sU3MXHjaK771dXVsYI3wIEDB7YteL/97W/nX//rfz32/C233ML3fd/38bKXvYxrr712y/YURVEURVEURVEURVGUUWT5AvKpf0TOPABxFbP7IHL3R+AKmCgAvI1xSbUYdNtloy7VYYF0uww5Y/vCc1E8HEQIoaHFFt+NZkkNPxTe2SV1fFIrHIvaGwX3bS/X9ICIGHU2qK1dHOp3WORk9LP3BSezQCG8d/9aB9rybnNHdZxANv79eG/8g/OWhxvfWvA2+LhSvA4RrOtsKngX++3jo7h4TDxRVh7xsdDO0L0sdcgPzJkA3liy+nTY5CBCbfUCUdbGPOerkHMPwtFPbdrv5TLyHJQ44rOklm+0kJ4ZKk5b9EOsBrbzNxOe9wRzza1E/+Z7MPHmaV0VRVG6qNh9FXHyoRMsLy5tu7wxhpsffytJEv6jf+yBB1lfWxtffsOHzYfDuZe321/bM/XJjYKoLRba+xOyyQi/Rbj0A0+8nqk9swCcP3uOC+fO90+KEC2NCYOeeuLWmMfUC7blEYTKhfJdfGKAcfnK8y9g05GxO8XEMj7fefc7PDFjv7DFlwvp3nu+/3+9gT/74Hih+3de/bO88JZnjeS07jciGC+c9kt80y/9Z+4/9eCYgn2SJOE/vurVfMe///bw7HjBbniigXVku93iwslzXDh7ngvHTnPu4gXOLJ3n7HLuyF6+yLnliw8/rHgUs29md3Biz+7J/93L/pnd4d/J3eyb2kWtJGSNN4RnbtwOPwMHvumpxBPleV2uhOC9VejyYaIoYnZ2liNHjvDkJz+ZF7zgBbz85S9n//7926qvKIqiKIqiKIqiKIryhYgc/TT+r38V3PaNQpdDNpB/OHTsiYbF160E222yk7zTPkqQQSEZSGuThWNiDFltpvCuzGQpUVo0osiQ2G2zDvWVojt+S7E7d0abQp1uubx98RjJ3eQmCiVk9P1vr96BGzBHngQfemvJDAyVLRFhGRaNy+obGwTvwctyGXbYrT8kmZSK3TYaEfe7TvpNx2+iIVd+jPUOI36oX9MP7Z3/26lNEaetPBd7KGP/3U/g3/o/r0z++pHxml7IdiGELZcoJq1N4+MKRnz+jG30M8t3XfMuvbxNIQduxH7DD2KiaOuyiqIoOSp2X0U0N5ocve/+HdU5eM1h5ubnAFhbXeX40WPlBZ1Qe7ANsaF1XWW8QDgOJyQLGfGyo360XfpF1TqY0DlYnkcjqVc58uzH9wTlo/feT7NZDI9jNxx2zHrArjnsOL07CQJ+9USbeKXEhQxIwlgx27Y8ti0hH3WJWC+Ar5mxgrOrWyQx2KYvLyNSCLMOWwvdtdzR/SWPe1ZPUC8dvXTzh8Opygqv/On/e1PB+8lPehI//IM/TL1W49z585w7d5bzZ89z7tw5zp89x7kL5zl38TyLy0tj29guE9VGcGF3hevZ3RyY2VtwZ89PzWKTMQsXn4fGF8bOfdYYv8GiceMudr345k3H+HAE750K3ZsRRRG7du3iyJEjPOUpT+F1r3sd11133cNuV1EURVEURVEURVEU5fMd6TTxv/H90GluXfhh4uIqEg04b7ti9+Ar9J3kiR4RZC8PwYw6ueMKrlIvHMuqU8Xxu4x4aN6Gxe5hZ/dYQblwLUHILh8rA3mxN2lTBLG2LyLnOb+Nd9tzWm/DdVxWz8fVkWuJhjdRbEvsjgsbI4zPsG58GPPimIOI7KM4COYiIWS++NHyhc0Xgh0KlW6+6CXIZ94Hm/R9OXQd5T6p9kR9EfBJjaw6ObRhok1lfaF437wbndft8tQvw37J12EizcKrKMr2ULH7KqLdbnP/ffcjbozDuYSDhw8xt2u+93nh0gJnT59G/MASIhMqpztEzbCTzs1aOruTokjohHjNk82UCI9OiJcyrINozVG/vx3yNQ/oyr5qWH5GyBVjW8VddBJBvGeCGx53c09wfuDe+2kNid2knqg5KgybjsfVDHFrKBc3IDFINSwSknMdkktuRBgVE9znyYorhhPPHd3d8bpaSEJdyMUNZDMW4ygNRS5Vg6+FOYtWsjBwawplQDBZ/5p2JnQL3ho6exOq59PCnHeFbpN35GPDqeoyX/9j38VD50+Vtn2l2DU5y4HZvezrOrJ37eHA3D72zYVc2fsndzPnahgJ8y/dEO+FB0PwsYW4+CwB4PvPgY/BYIL7frBIYvA1E8LJWzNSf/LWvcy98MYtr+VyBO+dCN233XYbzjlOnTrF2tratlINRFFEq9UijnVBpyiKoiiKoiiKoijKFzb+0/+IvPt/PSp9ZUktiJr5+xvjPcanJeLr1i7iHldI8HZxpSC4ehuT1Ypp/YbF7hFndz52sXFvXNXV8yHs9BAjgnIvDLsUhGwIzvPW1B6ySgPrM6qrF0naayVtFYX2vhu8KD5bGXpZWCp4X56720XJkCN7m2J3IbS4wVVq4fnI5yPkd99kA8BwaPK4UhyH9yPOcBkWuwEz7Jg+8kRYOAMrlza56svH2wiX1Apz7aIKWX2mUC5qrVJpF6PODgv4O+LGLyL6qu+9vLqKonzBoUrKVcTFixcRBOzA96mw6Rf0xORk4fP8rnlmZmdYXlqms9Zk9Y6zRGsD4nkE0YZQO9HBTVgkMphMiDY87f1DOTAyT7zmCyJj5XzISdM8mOCmY2zH4xoRnb1xT3D0tTx/tuRidGLJOm1OnzxNo1FnamaaicmJotgtgvEmCNdeEAe25YiXPVhI91XpzIRQ6rYl2I4vCsuZEK96SEwQ+gdSwri6RSYiOhMRtuUxbU+ymIV56aZ2GQhV3q2fTUd09iXYtlA7W1zwuIoJ4eDz/k3qQ45rQEy4hz42YAFnCgud33rPn24auvx3v/Nn+ZKbnwkujMPNR/ipiOaEDWPueCoLWfHZELAdYc42OH3pXGnb2yG2EXvn9nBgdxCyD07u5sDkbg5O5aHF5/eyZ3YXyUQNjBCtS1/QTvIdmxnYbGBhFw1k0emGjXe5Vj9pwOb3zIeNGd1c5L3iVYtYA1XBpIJYg29YJDbEi+F5FDMwGbkTfOPu80w/61qi+ua5XaampnjHO94xVvA+c+YML37xi3uC904d3XfccQfPetaz+NjHPkaj0eD222/n7//+7/nIRz7CXXfdxenTp1kbSj/gvWdhYYG9e/duqw9FURRFURRFURRFUZTHLAtnty4zhmHp0SU1XO6QjrIOUadVeG9ns07IP9wVla1FTAVc2i9nTB6JcQeCd5ehvN0PBxmKYpnL0MXusjYhd3IQWq3rEGVtXFTBVRrE7fVSoRsG3+fl79165qoho5MxbMzspzV7sCeItmb2U105z+SFoxi6r+0EEZ+HNB/qo9CxRUrCnZfMAIU359ud2+Hon+KLLZW0EcaZv+82pud2FmMhS4kGn49t9GsAIx5hQOy2dtuh7QvBzhvTmAM3IB962zZq7hzrHeLSQvj3yHXwaauQI95VGvj2GoPSvBh7+WL3A59ETt6DOTw+xaSiKEoXFbuvInqClzEDNmAp+cYPzMzOUKmOhg2Pooj5XfOwC8yJDTbWlvon828bIxCvDYRFMSC1oVzesQVfXFhEqyF/SfVsytKNtfL83zZ33A6xtLDA0gKYU6eZ37Mbay3e52MYFG5tEIm9jTBLjqwxkHumanFVcJklXumHtIkGQ4gPuXz9wHX5moVaCH0drfZ3ysmgy70rYGeCJIZoMc/ZMrggERME2O7nAde3EcCBFcFXDcYXb+BvvvtPRuYGoJpU+a3veyPPv/bpmIEc5W4i6o3LTUdAhBGC4N27gPyfpQ7ZNkLWfMnzX8DjbrqVvXv3sm/vPo6szXCovptdk7NYaweEY8FujC7cgw5veuGKjIDpSB7LZmhY+bwVd8AS8qh35zC/52LDvPewFMpI1fRzpA9swjBlq3kntE8t07hp95bzsV3B+0d+5Ef4vu/7vrFC9+Az3Wg02NgI+XM++tGPsn//ft7+9rfzohe9iGc84xmFet57Pvaxj/Gud72Lu+66i6/7uq9ToVtRFEVRFEVRFEVRFAWgMV16uCD4lZwTbHDF5iKojxLS2kTPTeuTGml1gur6ItaH939WPJK181DX3RepJgjgrtPvJxe8x764LQxGdp5ScuR6THgXN3jMRuB9z/krNgoipHgkrmDTNlEe8loQbJZhszbd3NJR2iTubOQO6f5YRyX08SkGwzlhcuEEkUtZ332kd7w9vZe4vU59pW/MMUiIejgiOBePjYikV2iTgBDCpIs1/VDr+bs8ya9lHF3B2yV16LrnTWhnW4Lu8HWX9mXyzQndj+G+i7W9c9bY8CR0XeIP3Q3PfDnsvx7OPrj5GKyF/TeEct5tXnawWpYiNirkiK9sLOKSBmkjd3jbCEyUb1S4Qhs67vmYit2KomwLFbuvdgbWTYNLgOnZGQ5ec3jL6nuefQMXPnqUjVNLl9V9NhsRL7uREN42g+l/WWftKQ3c5Jicy2MQES6dv8DuvXtYXlwiTcfk7ogMnX0Jpl3y5Rgb3KQlWh+TJ3sL3GRE+3CF6plOyAtd1n1bqJ7qFIXwHJsJtDy+asYuVo3PBeDhCNu+fPFTiWMm6xO5oO1GwsEPku6OMV6Il4o5bKZqDf7nt/44v/C+3+foiWNjasOzn/UsXvkN30xiEwwwcWeTqDmkUm+yBrcb+bUPYwxYQfwm1Y2BWJCyAtbg63Z8/vN8WLbpy+uXlN0u2xG8v/d7x4fO+e7v/m4qlQpvetObesf+1b/6V7z97W8HYH19nRe/+MV87/d+L29+85sLda21PPvZz+bZz372DkasKIqiKIqiKIqiKIry2Mc8/jnIB/+qJ84JICbqCY1IEFDNQC7tPP5kELwhuJp9RqW5Qqc+0w8NbSM6jVmqa5cKdY3PkGjAZGTyENyX61J9mPg4gShG8rDZ3VzPVjzek7vRoxD90WXBie7SvgdbBNtpEvmsJ0R257H4ajOfy37g7W1TWz5Lc2Z/we3bnNlfELtDF9twdw8zToQeFJBHhPpReo5q18HbZCA/+PbE9OBSl8J4JYqRdPO5KrjkB496j/XdnPAGxPXKh8Y9YuKBcOc2GMS8623QYGMFed+fYp7zVZibnobc+UFYW4K5/ZgvehHsvxFO3gPWYq5/EnLf7cjp+7e81uL4BesyPBQF79YKPkpw1Ub+t9F/trpz/bDolEcdUBRFGabElqt8rpiamho9aEzP9dqYmuDAoYPc9LhbuOa6a4MDdwtsErHveTdz6GVPZNfTrqO2q6QPwu482yr58rGGbC4mnYvJJi3pfH9/RLzumfngGtP/skb9riamvYMvLyesnLzIfGWKvXO72XfwAKbkeqRicVO2dLEhFUs2G5E1LCIydlEUlV0XkM3FrD+uTutQgh8zlfGaJ14pV8NtR4hWPabpx/ZtHSNi+r994deUll1trvPv/vt/5hMP3IGbiUl3x2RTFpOWjN8YOvsqNG+s0d4T7k2Xl9z6xUxTHzOiwBt/4X/wkq/4ct745p/n7qP3ks6WbFgItuzS/0oYwmaA0us2BiITQsNH4zYpmtyNXXIyMvgJi6vly2o/WsYIWDf+nnfbqRya2azECF3B+/nPf/6O6n33d383v/Irv8LP//zPU6uFBf3GxgZPfvKT+f3f/32SpB9K/Zd/+Ze55ZZbOH/+/I76UBRFURRFURRFURRF+ULETM1hnhfepwmEfNNdxzbk708tYuMRt7cZcq8akWIOa4JY6aNiGrzhev0Wi+zYg7NDd7IQ8mFLd3zW4qIEF9eCyBhVENN13JpCRSEKAr2xYCOy+gwurhavJoqKQcm7c7nT68rbq64tFI75Sj2E+t7iGkfa2qbwTJ4vu5dLfMtK/QiU1g+FHjfb8yObYSPTNlz7A9sLco++YF2HOG1iXYb1Duszcv92v2mCC98M5hQ3Jgjsw2HsP/oOZHYvTM0Fkfj8MeTuj2I2VrBPeRH2SV8CZ48h//jH27jKkvEbE/4uBvLZAyStVQCitBXG3tt84Le1OWTwznVnyBuLNxYZE9VBURRlGCNyhZKEKA+bdrvNAw88UOr8tdZy0003UamMhi3fCZ21Fqf+8U4kG+0ja1jSvfGmX9DxUsb0x9ZLXbfNwwkbT2hsOQa77oIje7DdWoX6oVkWLy6U1vFWIClfGMWXMioLGXbDEbXKH+fW4cpIePMuycWUeNX3tN0yJDZjncaSr0JMR0rLCIDt7zLsZCn/6Td/jHd98v2l7U3VJ/iDH3ozT73piXl9IZuOocRhjoQ81sYJ1Yc6rK6t8s2/8V/45Im7StsuhI4f4PG3Po5v+KKX8jVP/3J2Tc0Vu3BC1C7fGSkimDHPiwDEeTigMXPnqqY8FD4hnLntCD4OGxtKy7THO8Abt+1n7oU3lJ/cgtXV1bEO72G6Qnd3Hl73utfxMz/zMwDUajVWV1c5f/48z3/+83nwwX4ooUqlwh/8wR/wjd/4jZc1RkVRFEVRFEVRFEVRlC8k5P5PkP3jn8L60tgyxrsRN6m3xfedYiydidlCmaS5Qtxp9ssAPimaSYxLi20POKC3xSahuAeDLPad66EPH1dzJ3rwB3sTkVUnkIEcyqXt5iJwYYwiVJpLWJ8NlRvKkS1yWa7cjblDbMxf0z/gPbse/GihbW8sZkAAH0yD2O97IJrlFvJF9+y2XOiDz0FZrW3kCndJDW8jrEt7zvIoK095eKUQCOHTB81i3mFdVhyvd6PPpLHYr3w13PQ0/G//IKyWv3/ftH9jkTx0u7dhg0SUdXqO9ebMfiobS/1nRjxR2t707yNsXOluyDD9TQtDN8AceSLRV7wKk1RL21EURQF1dl9VVKtVrrvuuhFBu1KpcOTIkYctdANUJmsceM7NmErRyRsERUO06kudtF2y2ZjVpzTwQwHwfRIc4Fthm554fXTRkLU6LF5cCE7gwRMi2KaHss2UXogXMpI8d3X7QEJnPi6EtxYDrb0xLjGFXWKD9ePV/Eu4TEsGXCUI+a4+mrFGDL2FZ+l3twjGeeyahzwXdSVO+NXv+ile+kVfUlJhwOF9/2fDGJcdlfOdUYe3CCbLRWhruDjT4pt+a7zQfeDAAd72l2/lV978P/ny/+vLCm7ju+65m//2p2/iGT/0b/jOX/9B3vnJ99HJ0lywBklGL6/32Uth0dmbl/wRE2Pwtry+aUuICCDFRbfJJISABzp7E9p747CpYLBMmpfpR8jpN+xBNsaEx98G23V4DwvdAD/1Uz/FxMQEAK1Wi+///u/n4MGDHD16lO/6ru/qlet0OnzTN30TX/d1Xzc2tL2iKIqiKIqiKIqiKIoSMDc9FSqbC16lLuIRsXSMMFzsbeR91ahLdYcesrLIlZA7q03f0WqT4Ny1cXB0y+C7M4MVT9JaxQwKrGVmlDzMuwwdy4ZE/FB3JwHLx+Oi4vvrpLmMjytF526U4HP3eE/o7o4/qWEq1TAakdI5G+bKjX5rBLBpm6S9TpR1iFz6iAvdkDvRs3bI0d47aHtj2hTx+Pe+JeT2vhyhGwqhy0PO905hzivrC9g8dL5xKXYzobub59yYEWd9f1PHQHfHPov7xz/Z8bgVRfnCQp3dVyEiwvr6OmmaUqlUesLZlWRlYZnTdzyIcYJEwV0brTqMz7/AKgYfgx+TjzteSKkf64ATJDH4iqV5cw1JNl9aJJfS0hzZYkIe6t4uLh/CqieLDokNnf3FUELRckblYobpbhaLoLMnCfUzIV53+AiyXTE4SJbyTvOnPV7OSBZdzxUs0BNnu2V8BFI1uImoJ+Sbtsd2hHgxw2b0v3u9hM8D9bubBkwqvZznEoG3BjdtaZuM7/mVH+PvPv6+0rmaqk3wllf9Ak+9+YlIJc80VDH42ITQ7phe9ytrq3zbT3wPn77/ztK2Dhw4wO/85m9zzeF+nvfl5WXe+bfv5K1//TY+89nPjtSZm5jhB7721Xzrc76qH3K8Kyz7fAmeDuXVscEF312g9tzygxsCBjfoSb++xEEYD/lc8tMGVp/SCG16IVrzxCsZtVNpf8trd9Fuim1iYO+/fzrx1OXv+tvM4V0mdHd5wxvewI/8yI8AYbPK8vJyL7z5u971Lr7ma76GZrO/W3j//v28//3v5+abb77ssSqKoiiKoiiKoiiKojzWSX/7h0I+4nGIFF3LBCcqAyK4txFpfboQbrm2crEgvAkGMSbPhW0xLsNI9/1iX6LejCDsxvReWokfyBHdLxNCRhYdxzI05hA5suhQ98aSNmZHXNEjDPWJd9Q2hkTPPBf4YDs7dXaH663QmtrNxvw1GO+YvPhgEEGzFJs2gxu9e13dPgfGb7/82+Gf/jesXNpR35dDYe57rvuuG/7K9XHF2jIWMRYfV/Lx+pCfXXpXAj4b25951lcgH33HzvqEfgj9Lt7nz8agp15Gnuux1z0cft3YopgOoxtLopj429+AmdCw5oqilKPO7qsQYwyTk5PMzc09IkI3wNTcNNX5SXwjCmGkvfSEY0PIRx1vyNg83NlsTDYd4ScipGKRitlS6MZLqdANRYG0m/PZ1y1iwVdH2/X14qPrk4E8PbEhm4lxUzESmZ7Q3Ls4A26o/lAylLDO6YreA/1L1eKmItLdScFBbvxo/e5fl3H9/o2DKBWiDU8lqfA/v+en+fKnv7B0TlZb67zyN/4Ltz90R+9YuC+eeLXvjr8coRtgZmaGb/rGb+KP//At/PUf/x/+w7d+O3t37+mdX1xf5of/188hrvtghPtCbMK1DYjWvR2Uwy7r7slufRva6M7dYH2bgU0FMxBZwNdteDYArMFNR7QPVvr3fyDPjpH8p1tZoHN6pXROtkvX4f2lX/qlheOvec1rxgrdAD/4gz/I9HRYfHU6Hb73e7+3d+6lL30pZ8+e5alPfWrv2NmzZ3nc4x7Hm970poc1XkVRFEVRFEVRFEVRlMcyZt+RniN4nINrOACgmGIOaus9leZKLy930lzrCb09GbtryHApJutgfDbgNN6hGNoVU22EREmhds8uMiBSGxjJCx2czsVjVnwY19YDKH4q9b4Vj4kxIzmhN6MnihpDbe0SExePM5EL3QASJ/ikVhDwKelD7r8d2hvb7vfhMGDV6Y2nm+P8ct2Bw4HtTcmxy2s3tBaejfDc9p6RgU0bm96xan2zs71+gqge9X5GNlDk9637PtiU/D1sOo7h9sSPHhtuwWXI+eNbjl9RlC9cVOz+AsUYw7W3HmFqbiY/UL5AjJd9CCM+/IVjDa3rqmQT+Zf/Nr+xd/TFbg2dvQk+Hv16lIqlfagyIESPtmwEbLM83I1ULe39CX4Tgd4I2HbuZh7CNyydvfFIOPdiA2bsX1jUFOKljIqJg+D9jPGC97f88v/DJx68o1h/wxOtOlZWV/i2/7ZzoXuYG4/cwPf9p9fwD3/5t/zm//gV/vXzvpw90/O84jkvLw+DFFEMK969ZIKTHbdFmKExz5uBELK+K3iXhdS3hrXH13ETW//ny8QP/z9xU1NTvPvd7+Z//+//zRvf+Eb+6Z/+iV/6pV8aK3RDyI3+0z/9073Pv/d7v8fa2lrv8/T0NLfffjs//uM/3mvHe89rX/taXvjCF9JqtR72uBVFURRFURRFURRFUR5LiMugPhkEydz5LANhugXwUYxLaj2BUaKkXxboOnmNCElzjcr6IlHaxJuol4tYbISPEnxUQaJKLpZLLuptX+gOYnlWfEdmzIiLtaw9Q8m7tZJ3beXC9XChYg8uqZJW+war4CSPeyHgu/MkNsaXhYUvQWxcELIrG4sj4b1H3Ltl79ZaG7Dn2m31eSXobSIYukeUXPe2RWsTjYSOHxHQd7CRoDfSrulHfD7mYv740TD7RWR2H0zNb7O7/O8kF7VH5sdG5SkDLoORTQfjSB5+ildFUR67aBhzhbTdobXRYvHeM7RXynfOiQFJgiNaqsUvMtPx2LYE8dFuIgCuO6KmL7qgu+0D6a44OIdLByBjFwF2zVE73qZ9TbW8fydEzfFf9nbNUbkUdkGW9eAaQVgfN6540VE92YFq+Rd8d35KqwPZhKVZ93zvr/0of/ex95WWm6pN8Eev/SWeev1tvWPLG6t8y5tey6eOlefoPrhnP3/ws/8fB2+9Fj9RHo4eQkh6mwpuqqjcm1SwLU/lbId4reymCbYpPQd82bX5mh2/lU+C03/saaB5bUJnX6X0uTCZMPWJjbH9myRi33c+A1sZf+2PNLt37+bSpRB26ZWvfCV/9Ed/NFLm9ttv5yUveQlLS0u9Y9PT0/zd3/0dz372sx+toSqKoiiKoiiKoiiKoly1iPdkf/1ryEMlho9c6BMT5Tl/CcKfdxiThyeEPEqh5M7YEGg5OJgH6hUYDA/usVn7skJSexsFwX1gvMalo+HMh8TD4fDrgoEoLtTp1GcKx/COQWE0q9RZnz9Mffkc1fVFxFjSxjQYS3XlPJWNxUJ5fBbetfXcwoLZJDR2bywmykO293FxUrwm70dCzA+7kc2TvgTTaSF3/PNwD49oXu6um///Z+/PoyVJ7jpP9GNm7h7L3W/uS2VVqapU2pHUEmKREFK3Gg0juqFBzTIsj27No+E8mD4wzcDQK8xr6OEBDX0G8d4w9IEBNc0+AwjRaKEpgdCGSlttqjWzsnK/eddY3N3s9/4wDw/3CI97b2ZlKWuxzzlRWdfDbXFzjxt27Wu/76+amlFQ6Mq1j56V3cZD8EIw4q2+y/uqVN0qvrRN30/fAGXqfVOqPm4Tz9PTRYoI91ofoL4+v89no5GJdf6pZ10mthbMLXkbc3Pz1nkDgcCzmxDZHSBuJSysLHLo7hMzo1WVCDoVzLadiraVxFt7+2/a5i9plTrMSPBt2oUImM3Ztjsqnf3lH69bTA7RrPJGMXNPhwhm6Lw19wx0z6FmieUCyaUMkwpkMwTtiJrl+RQtTUvH/ML/8G/5u6/fJcL73//TMsJ7T6H74FF+49+8m9uXjxNfzn2kdQMqdbSfykgu5pBP3NdYYRcM6dFkRhi2wrZ22dFo8OOqaH4ulEJ2mZ9kByLsSuwjxRuQSJEvzv4V1v2SozdV6Ab46Z/+6fL/f/M3f7MmaI947Wtfy4ULF3jb295WHtvc3OTLv/zL+dEf/dEvRjcDgUAgEAgEAoFAIBAIBJ7VyKP3TgvdZTSrIEqjcOhsgEn7mHyIdrYQb73wqHDl+SP7ZS2FALuXtbfSiI4bztmbqehrVSYEnEmTk6ZythCzi58Rkv4GOh8WhUbm7v46rYnprRwHbegvH2PYXS5ylfv1tOHCIdxEHvCqqDrq6/4ieGd4OIr4PjsLYsf3bDIyeXT+5bPIfX81Fp5LAfrpW4HvhhoZ41fzXyuNM3GlXbX3eJRjN+pvZSPBlNf33jLxpNBd6UnlpD3sy68HabDRn+Sao9NnNDX6j4xTCTCyUS/OMV/294LQHQgEdiWI3YGSzvI8x1/zIpL5duVoPQOOthCt27p4Kt62WuWgcupiuPjoYFNEBuuBoLcdKqvbrOhtixKfy7k2cXHe7ju+nGO26kK7Sh2tJ9MyKjtfinCJqgvLTjCbOWbT+fzj1fw3uRBftZhBMfVosN/2O+UgvpKhd2ztPd13dB8eEm35XXoqdV7wlomxyQvBW9evzUWKfMX4nNQG8hfP8fP/40/ubmn+7/8p//W+j+4tdP/4uzl19KS/L7awY5+4Z2bT0n14iLK+b2Y7R/fq12i2Le1HB36zgZsYFw1uzmAXTc3SXAAXKx/VXYyzbijvYoVoNfmIIQaGRyKGJ/wfEMlaTutc6sd3hBWScymm53BRfVwFcBGk6zuN4/PF5Lu/+7s5evQo4G3K/9E/+keN5yVJwn/5L/+FX/qlX8IUEzcR4ad+6qd45Stfydra2hetz4FAIBAIBAKBQCAQCAQCzzbsAx8f/yACzhXRs+KDdJxFWVuI2sUxcV7wnrQRnxArx9HeuyPa3BDB1S+FTQSdTNhcK0CJHYuO4tAuw2R9b40+NhsnGmyh8iGIpSqjbx885W3cAZRiuHCwHsGuFHlnsd45tX9RWVA4HeG0wSqFNTFZ0iVrzZMlXQSFcrm/D+LQImXnVOU1ale/4ivhyQebG7tBwupuVO20x5HMehxRXYrWzTm9pXpFauLf6nlK45TeZ6y6qtUx1a6Jxs+uUnDry+HWV+yj3j1b3XfkeZXJEv4ZafjcyHgNXapjLN5xobSST7qYr/lu9CveeM19CQQCLyyCjXmgkeFWn+FWjwuff6LxfRcr7MgaW6h9NfvdV3ihue/GNtMiRGsW5UANCztz7UVmMYqt13S9DXnxSOqeo3Uh80WTcc4YiRW6Z4mv2rJd21L0XtIp28GB2bLEVyzKSWmdLgAG1FAwg8quNytl5Pmo/2KUF6mN8oI0hWAdKS/Ab47FV1GUFuqCv65RPX4n4Nj6B4G8q2u25+mhyFul50L3Q1f4vl/7V7zvs/c035xdOLFyhPf8i1/0QreAEhgeiXEdPe4nQvt06qPRC/J5jWtrVOpIrlhcotCZF6lV5R6K8i/XVYjWEFHa7qhcwIK2Urte3auXdxHkK16hrt5DgHxR07+tYkfvhNZTGUoKEbulUE6Ir+R+k2pbl+2UsyY1Hu/41mXilQ7zdx4mWe1e83jeCH7rt36Lb/7mb/ZdU4rz589z+PDhmec/9thjvOlNb+Ls2bPlsXa7zX/+z/+Zv/f3/t4z3t9AIBAIBAKBQCAQCAQCgWcb2e/8LHLuEf9D1Q56EufQUheundJTNuXK2an1TBe1GiqsC5I6619zFK3VEWhdlssLQbi9dQmTD30u6JEFeEO/QKFkfFwAm3RrIqgzMXklDzdAb/k46dxKpTKhs3G+Vn+8s0Z7+0rtnKlIYXEMFw4xWDiEMzEmG5DsXCHubZYuoT4wJvLieqVfyuXT9u/FJoUq+su+DvfIvbjLZylsItHWR+VX+/aMxnercTS2KF3mGFcuRzlXs2lvtqE3hSCuijGU2liISDE+1aghh7ZpY+51MbHf1DGq85a74chtcPEJ/zzd/ir0S78M+luwvQ6LB1ALq9jf//fw2Gef9nDIRES5v8ZJG3Nb3hMfNFYEPxX3zUUJoiOUzf11VuvHbyCZsuqv5XZXxN/+z1ErR5729QQCgec3QewO7MqFzz/B5lNXpo4LYA53SYfpruX1wKJG80snxFeKH0QwO+P83fmiYedlnYlGhNbZFJ0LEk2YEFghvpqX5bNlw+DWiQmpE1pPZuiBm87r7ATTG0/cVCboCbtsAVxb4SI1lTNapY54rTLJrIjd1fJoauJr2XwErjvetdY/lZCv+glT+7Eh8f1bfM9v/Cve9/n9C94nVo7wW//Df+DkyVvGIjDQv2U653V0NSdZG9u+Z8umFPTjyzlRb7Q7wOflnsS2FK6lIZ6Y3ough+PNBaNxniRbMoihtmEA/Dj27mr7saGI3r8wmcuncAcQKTdBzKJ67xZfdYLl15zc9fxnilOnTnHmzBkAfuVXfoXv/u7v3vV85xzf+Z3fOZXj+zu/8zv5j//xP6Ib80gFAoFAIBAIBAKBQCAQCDw/yT/0n3Cf+3CzGFulIY+wwFQ+adUgmFuTNETi1sU9nQ+uSewWpXBmtGbpEBMzmCsirJ2js/HUdKDMhODdJPLaqFW7JgGy7nLtnP7CYYaLh2r1dDbOA0UQC9Bef4qkv1m7zrqAqdg6cud0BDiQbK/Rvfpk7ZjTERIltWM6G9Q2IAgN499ZwKWDqTa8SJrNHIcbRnXjAIXQXeYxt1P3aPIZc6Oc5TUx2JWbKrzQ3fR8+fr04ZOow7d6IdtEqDtfi3r5V8DWVaS3iVo6hFo8sK9LsX/wC/Dop6/l6qe7BEzmCQcq/a/cB1fkJ69uKnGu2Pwwfkb1KLVApQaZsNH36+n1z6p58zsxr2p2Qg0EAoERQTEJ7Mrhl51i9UVH0fF4R1Uy3+H4q+/gtlfcxfKhVZSePcVzLY2L1DhaevSGUthu5T3XMFFRiuHxBNtqeEyNIlspbMsBmlJqa8XweIxrNfRPK2xH40yD/cuoeQr774YTJNFkqwY3KfZOlG/sF6BzH7k+shZXlesf3N4ifeUCv/iPf5y3v/xNM+uvMhK6bz14Aj1w6P7Y8l019CFfiUgPRrjR3KFyjdkBQ7aoS2vypvHRQ0EPGypWCtdSY2vxSVv6gmjDogfT5ZVA95EB0ZXc979pAqgUbl6X4vx+2fzMWfpnrl5TmRvF7/3e77G0tMSxY8f4hm/4hj3P11rz67/+6/zBH/wBrdZ4E8ev/dqvcdttt/HEE82OC4FAIBAIBAKBQCAQCAQCz0f0K7+qXCfadUVoZH98jUxFreIjsKV6TIEzyb7spwUvmjrTYpR32umYwfyhsSCoNVlnqd7uPvJ5+wYmV9xGoqTyFtlK47ShtXWZhQsPs3juQeYvPQYCNung4jYubtM7cCuDxSNlH1E+ytwV1tLDpSONQjdAOr9K1l6o96Ih/7mYqHZMAc4YXCWCV/pbzZdpon3mDH96SPWllLfHd7bZ3n5is4UbReZPrmMq7QXfY3fAoVOzrdiVgpN3Y976bZhv+VHMO/8Z+jV/G5V0UAeOo295yb6FbgD1olft61p3e38UXY+43YVuAF1sDqgE54geR8aPj01sOIGG57gBHXJ1BwKBvQmR3YF94Zwj2xmgtCbutkgfX6f/+Yu4nRS92iF66SqX1q8w6PWbKxBh7rM9JNFlLudx5YII9F/cRpqEbSu0zmUzp3nivCCdHo+noqvBRwe3H0tnTxOdoKxMWWqXbxuw87t8qRY5qc1O865SUUxFVtfeR8iXDNuvnpt4Q7DrQ37ox36Y9//Vn88sf2L1CL/1fb/ArUfrUcujyPLh0ZjscNJYFhGidYvK3XSUtPPW5MmlnGirWbXPlgzMEp2dQ/cLK/uG4iNL+VkTPWdgeCLG9KWxPCKo4ew/LwSQRNXqbx9f4vDbXjKjxLOTtbU13vSmN3HfffeVx6Io4t3vfjfvete7bmLPAoFAIBAIBAKBQCAQCAS+eNjP3YP90H9CuRnRJQXK2Zr9dWNkt81r0boONbZUVgobtxksHkHZjPbmRbSrOA+KQ+e7rDUWuJGtd4XB/IHaMWUzOlsXJwrauq11EdEslfzN1sRIlJS22aIUWWveR1VX0wvmaS2aFiDtLpN1l2rHOmtP0tpZqx0zX/OP2P7sh4kvn0HbHJt06S8exiVjd864t87cldO1cjZq1QVKZ4myYs14NN7FOGubeffGqpX7JM5i8nT3iP59MhZyK1Q2SPhc6mqqnfJuaI0q772CE3fh+jvI1rQz6gjzZe/A3v9R2Lg8u2MrR0i+/V/s7xq2r8Lls5B04NiLSiv58v1siPu1fw0bF6fLjvpd/NR8nfX1VG8trqfO2gunoynL9iirR+87ZUqXgZKqKK408Xf9G9TCCoFAILAbQewOXBMiwsYfP8Tg/ktT70VffYJLbqtx82FyLmXuoQEuVgyPNovS5tYFNufy6cJAtJYR9Rpyl0ARgg22q7DzzZOi+KmUeIZgW1axZYn60+cIkM/pZlHXb9P05Xdsmfd78hSJpidJ/k0py2++ultamVfJdob8T//D/8h/+cR/nXrv+MGj/M73/jy3rp5ARvmzJ7Btxc5Lu9NW7oDKheiqH3PRNF6j3s5pP5k39t+2FG5ON7arUodOBXGCGTSL0q4Qu5veyxYNdsmAE/SM8uQO3fzINNrPm07MiX/42uYCz3L+2T/7Z/zMz/wM1V/ZX/M1X8Mf/dEfEUUz/hgIBAKBQCAQCAQCgUAgEHge4S6exv7mT0EpPteFuVk25iifhxmlvFhdEcxFqTI/sQB5a57hwsFSqDPDHu3t+lqostmUiDyJKD2VB3zYXcbF7Vo9na2LhT27+EVCmxdy63gNyOnIC8gVW2ln4pqo7Ps+V6sfQGfT9tH95eNINBbddT5k4akHasKpQjBpPbBJgO1DL2K4eLgYmx0WLj5SO2dS7FY2x+RjkVOq98I5jMtxyjCZV31cwGHSAU3i7LVQiy1vsqufFXk94uBJ9Df9IOr8Y5D24dAp1MoR0l/+n6C/PbOYOnIb0t+GzdmCOMuHSb7jX+7e/8EO8v7/E3n4b2B0P5cOo9/8D1F3vqZ+7uYV3J/+Cpx5YHxs8jrFx3hPfVb2FLvHZ+6G0xGgxhtPRNA2LT5X/vn2mx4q9udSdfpU6Jd/BdFbv23PtgKBQCDYmAeuid6nzjUK3QA7D1wkupqj0vFkUQ0dnUcHdB/yExqdCa3zGbpnS5sS3YpYeukxbnndi7n11lvpdCq5u0XAOp/32UnN2qTMiT1KBdIUFS5ALthFQ17kiZ5kZJmiRKZszUV5oVpngsoq7YvUhG5EcB2F7SgfyT0qb8B2FCqXev9HE9iivBiI1nPiS9l4/ESIrmSsfi7l3d/xb/iav1XPTXLigBe6b1s9UR7Lu96afdT39EDE9qu6uE7FWryoW/ct0bqf/OuBo302xaznpbU6TojWc1rnMiQuxqIyrC4GDOhUxmWKcmroUGlxLFLYeV1rX4prdh2Na6nSMh18PvNspRC68VH12QFvWT8eWB91nh2ISVcjL2xX7lmT0A2gk+euKPzTP/3T3HPPPSwsjO2h/vRP/5TDhw9z77333ryOBQKBQCAQCAQCgUAgEAh8kVDrF9DGoJ1FO+uFbWdra24NMmZpS421tchwYSx0j861SacWkWqTjhflKlyLtbY1MVlrHhu3ETQ67RP3N4h760T9LS9u2wztcnQRca4KEXL00i6HSrS6Ap/LuiJiKyAa7tSOAbgGG/G5y48R9TfH50QtbzNdjZpviKBXwPylR9GFCK7zrD4uMGUjr1z9nJqYqkC6i81C92j9tEGUvR7GBvH1NeZKz3fnylPeEeC2V6Be/HrUypFxP3dDHPrU7k6TduEAtr+zSxUO93v/Hnno4/X7u3ER94e/iDxxX+18tXgA/U0/hLTn/TM+uvo9LPObx3ifsZIj63ebo6xF5Rkm62PyISYfeqG72g+l0fjPZjmGVaH7S74a8+Zv3l/bgUDgBc9zV/l5AWGHGZuPX6J3fgMEOkcWWbz9EFF7hjX1M0j/3vONx0VDvmTQuaDXLaIseujoPDKc+pLUmdC6lBPfscLi19xJ1I5Rxk9oFhYWWFhYIMsytre2OHvmLKYv6OI73H/viRe4KwKnixQST9pw4+2vLSilsAsGO6/BQrSZ1yLFVV5YZRuFaKlZ04wmySoXJAeU4IyaSv+jlELaCtvyIjYCaIXuuzJ/t6+32CNXGZh8waC0Itq2dB/oI7FC5aBzQTQYE/O/f9f/wu+//M/4yMN/w/HFw3zPm7+ZhfZcOf4ohU4dm6+bQ9tC8K2KwG3lo4Kd0HoyR1fmq2bHohwkV3LUUxlECmX9mNiWn4BI7G+AA0jwE9dijE0qhc2P+PEetQn+XimFm/NR2t4evRgA5cfIGeXrjhV2sbJLVYHEvv2spcEKeuBILuZIopBEIwmkc8bbyfctUX/2BKx7x/7z2zwb+cqv/EouXrzI2972Nj784Q8DcPXqVV772tfyr//1v+Zf/svdd4AGAoFAIBAIBAKBQCAQCDxXkYc/hfuj/y8TMbpeBBZBlEbJ7GjrkYg8UevUeSbtkVdzURd5rMnTa+qvU5rt1VvI5lbKtS6dDuhsPOWF6gKbdDFZv8wP3SQ4jsTtkf13eT3O4rRBVc4z2QCbdMeLj9qgXOZF/SLiWolj6an72Tj+0jIn90hUdyouIuCb19gU0N68SO/grSQ79WhlMXFt0VPZdCKq3Fuu+3sG6uBJzJ2vxv3l7xdivvK5vJUej4NQCPHNzpPXSj1mvtp5YdfobnHeinyubgGvT96NfeRTiDIocTULfQB1y0swL3kD7oGPNz5DojTbuSAf/G2W3/A1JAePTbf92Gfg/KMz++U+8n9hbn1Z/fhwAMPe3hHrjXVWR0iRteYYzh/ExS10ntLavkI82KR8WisbE0YbCszEZ3F0XMSBqkT+I37NutZPQR06iTIhX3cgENgfIbL7WU662efJD3yeq/c9xXBth+HVHdYfOMeT7/88w6uzd3s9U+RrvcbjEquaNbkSkESTLzV/IUmsmP/KU8RzrVLorhLHMcsrK7TaLR8VPaq3eOHwwumovqZtG0Ukci3HjfICcL4U1aO8q9+9So1fE5M6VVybzpt2AFbKm0pksZ3uv5+Ij4tIrMqy+UqEHohvY1QI0FrzjV/6Nfx/vu1H+cGv/UfMtys5vkfn5NB+MvV50Zts15UCo8lXo9qkrhxjrXy0duaFbhkdq5RXSoEbT6rr16YaXIAqB7SCqOibmnhPeYFfZZWe6YlzjBfN7ZyuRXMDECncvJk+XhAvd1i4+0jje88l2u0299xzDz/zMz+DLna9igj/6l/9K173utexvT3bNikQCAQCgUAgEAgEAoFA4LmK+6s/YFaUqULQYq9ZDG0UlkdLcjbDpH2fo9nmPpe2zfzL2T3jXY3LWbj0iI+2Hl1D0mbnwK3e6rtsUGHjzp71lWJh5ZgWhzOj3N3Fec6VGwCqZbXLymPKWRTC3NoZX08+9II7lGJtLU/5BFHW94Ln6NriFurUSwuXzQyVDdFpD5MNfVvOjx/iMNmAKB0QZQPMpdPIPb9T2sJrlxPlQ3Se1qJ9xcRT+c+fHteX2VXac/RPP8T6x9/P+sf+jJ0HP8UQw3DuIOncKsO5A6SdJS/YAyQdzCu/CrV6lOjr/gnMr9TqsyZm+9DtuLiF5BnrH38/YqfHXR7+1O4de+phb5VeJWn5vN6TdeEFdlF6xtaPUSR98VKQtxdI5w+U/24dfTE7B24dl1cKtNmX40EpblePias9wwDZh36T9MO/P3VuIBAINBHE7mc5Fz/5GHY4/QXnMsvFTzz6Rf9lrzszJhUzxN/0WMzwSIyLx5G6wyMxG6+fYy3f2rWt4XDIMB3OtB5XOV5IliIqu+kkw9QXJQBGMTwUk3e1tx2/xpmwohBl7W6iN2Xk8kyKYOiqcO/mDdnhCNdS43Mm0QoxdWvxEe2zGd0H+pjtWjh8DbtgSI9EPmqbeh8l0bjY27GrGeWVxd/zJibHs6G8RGrmfTVbDl3a1jc3kR2KcN1mMT9fNtiOLu3kVWyYf8kRDr/9Zc9pG/NJfvAHf5D77ruPw4cPl8c++clPcuTIET7wgQ/cxJ4FAoFAIBAIBAKBQCAQCNxYZP0SXH7yxtdbe43kPaFz5Qzzlx5lbu0085cfI0p73mK8SIU4CgPZa2VWO8vChYfq62PaMJxfrR9Tit7yCazZw8lTBNH1IBaUwplWTXgsI96hsHl3hZDt1wujwoY8Hmyh8ozO+vlKJLV4QV+aFlw90ZFTLL7t24hufwXRkVuJXvKlRLfcTeyGtAYbJMMtorSHsmkR7Sxo8fm5a4FJZaRzfZ1Piy0j3ctu6egGmJlfAxMbBkAY/v7Ps/3x/8LwqccYnnuc7Qc+wc6g763iwd+LqEXaWUEWVon+3vehFrzArU++GPMtP8LW4Rexs3KSrUO3s3n8peTt+XEL6YDBU49N92WP/PBN5yht4NaXeVFbe3HbmQjb6lZec9goKQO/1OhVrUccc2tn6BYbI0YMFw6Rzq0y0WijgN6wOlzfoIEX4OvpAoT8vo9gH/jo3tceCARe8ASx+1nM4OoO6XpzJDVAtj1kcHl3wfhG03754cbj2oLZaZgAKUW+GtG7o8XVNy2w9tZFtr+ki503rK9dxTXkfhmxtrbmdzbOmVoe7LLqol0yUP2JvNGVkySeoZlGvm+DkzHbL2nX8kbvB9++oFJBDWeI3gqktfckLNqqj4PrGtJjCYNTCdnqDIFWKyRSDG6J6d3err2VXM5ZuLfH0ke2aJ1utlhyXUN6PEH1CnG5gsQK19HYjpqca44vzTHjmosof4XP2z1rE2hDTm0oBO++I1rLiS8U+d0b2rDzZmIva4H2lvVyssPxb34tJ7/lb7H6htswreeP0D3i7rvv5ty5c3zDN3xDeazX6/F3/s7f4Xu/93tvYs8CgUAgEAgEAoFAIBAIBG4gdjLv841DFfbZI8Evyga1qOZxXIdMCdT7iaAxecrCuQdRlWvIO4tEaY9qHm4Xt9g4+XLcbhHMRR+lsIF2ylt+j44JePFyhEgZsT36ORps1a6ve/Us7a1LpSipnEXbHKcjnIlxk+I6oM89ivz6j8ODH4Mz98Mn/xT50HtQ6WDcVUCL1K6xvIYGJttQDZHlom+grXX1Xo76Wcn97n+2Y4tuZ0k2LrJ09vO1eyk6mhZ9tca99CvQx15UO2z72z46euGAt49vGIt8a326r7fcvfu1tOemLNLtX/w28uinfZpOpcu86NWc9WiNi9vYyWeuoV+d9XNlrvYRw/mD9ftb5OKeYlIEHz3HxY/VjRrlseJeZ5/7y+n6AoFAYIIgdj+LybcHe56TbQ+/CD0Z033dcdxCs2gozjWK0gB2yeA6uiZwOufI89l2OGlafEFrRbZiGgVrofiuBuK1vFl81WpsE95Q3rU0JJrh4emJ2+icmbs0xVsbldbqTafoXWvwXUwFNWioQCtcR80e144mPZxgVwz53PTHWVlonUvRO827/6IrOa0LmY/UniVcF3m2mzswoxzeGl0L6OEu5bPJHZIFIt4uXiC+nDWXV8qL6Y3lYem2wz4f/G6R9c8DtNb83u/9Hu95z3uI4/HE9Jd+6Ze44447OH/+/E3sXSAQCAQCgUAgEAgEAoHADWDlyFSu5BuBF2Sdz6E9IWRPis6l4F07OIoG351Wf52lp+7zduiAoFHiMBXxUHSEi1r0lo831iEw7lMhCrq4EgCjFDZuj/NyAzrtY0aW4CLeQny4jSjjxWxlSLavYE2Ei5LiFWPjFhLFiImQKMbF7bE1N8Bge3osZiEz1u+qNIiranJzwQ2ktnlBxnH9iAXnRe5xKkpb/gx+80Jno77eJlE8FZWfP37fVLs6aU8dmzqnVT9HRGB7feYmAQAGO7hf+Z9xn7sHAPfQJ3D3fnDqNG9nn/trrOCi1qyl7UpZYeXMp2ltXSqP2aTtI/B3CWir1zD6X1X7V7QpBXC/cUOXGzrk6gVkP5HtgUDgBU0Qu5/FmPbeeUj2c86N5Gp/k6tf2qV/a1Jak9uuZufFbfp3dcmWvTV26c6dKNJVQ740LZArpTBm9m68KCrKiGC7huxgvW6fT5ryS7F1PqPz8BCzYacmUZIoX1ZXnMMNuE6RW9sJ8VULlff9hFFh2xqz41BDN44eF6mp4AK1uqU4Rw0c0aYrvqhnXKgCFylcV3tRt9KGGjqidW8zVC3vIsXwSEzvrjYYL/pKS2HbY2FcwFuFa8X8fX1aZ1NUWuTc6Ts6Dw9Y+HTP5yEajaOrjJv4vujMC9ZqVp5yy7hcUUYNnbeZx28G0D2pC9NW0D3no8Mny4uAG+dHEqOI1nO/GaB4X6UOs577cybLF2O49cSVGQP+/ORbv/VbOX36NHfccUd57NFHH+XUqVP8xm/8xk3sWSAQCAQCgUAgEAgEAoHA02TtPLS6z1j1XuicjED2tspSO49pe+siwnsvWTbKBrQ3vUgaDzYBL7QrZxGlyLqLAAznDzSWd1FrHDWrFDZqe3FaaQSFjRJs3PZ20NoHDsWDLaL+Jklvnbi3TjTc8XbgJvKiuImKiN/KwuMoUrw2FkXe7N0E1xk0bhLYB1K0W6trF2v1a2Xcr7E5uv/X1W28mV7WTbbXpuoTU1//bsq9Hc0vEa8emd0prWmfuKN2SD70HuSv/mBv4V8c8me/hlw+S/6Zv2CwcIje8jGGc6tT9u82SsgnNkq4qL1nzm0FzF98hGjg84Nrm43t8cs15Rn3aCRsU4/+FqXGNvDF+zZuje99FDdHiwcCgUCF55+v7/OI9sEForkW+U5z9LZpxWijufCRhxle3kIZTffECkt3HSXq7pHf5TpZW1tDEs3OSzv07u74LzGlCmEWiBR2MfIBvwjSnv1FtLi0tKvYvby8zPr6OuC/SF1b49ra70LcsURb4y94lTqUhWjHET02RIBs2TC8rTWuMFK4SI37XCFat+gcf9wAIj5vdcdgNvNxjvBc/HXFCql+eiqie3mo5zB98YJzdcbUMC/Jl/zuNYl8X3DjIjqr9Ff5vvXvbPtI+QKzbf2kpKtB+dxBZZnMT2faZ1LaZ1JEBNOXUkwGxhbuqrjO6hSo6IvKBDJwCNIZT/OqUe3ixI9jWXFRreCt3ocg4nzbCqStS8F61J3q3EUUSKz8vd2ysOVvnxa/WUGShvLFv9nWgNO//UniTsL8nYeZf/EhlH5+T4yOHj3Kww8/zPd93/fx7ne/G4Asy/j2b/92fud3foff/d3fRT/PxyAQCAQCgUAgEAgEAoHA8wu5eh73n38KhrPTPV5znZX/Hy/bCdZEKJuXx8REPmrV5RPLe1IpSbk+uhet7Sv0l0/QWT83Pugsg9WTiPaLjaN/R/1UgNUxedIhT+ZAa5TN6a2cZPPY3WTdZXCO9tZF5i89SjzcLuoxDJaO0F0/h057Y3HX5X7lb2RrDV4oRVfWNxuuUilERzUL72caZTM/HkoVIuqNjfRuku73I+ePcp97d0rrReJi44JyGQjoxRUkS1FxfZ1+4RVfztW/+mMknx7H+Ze+HtMeb+qQ9UvIpz+0/wsSR/67P8vmyi3Y1VvKw72VE8xfeqx8NrSzbB65k7krp72dPvi1ZR0VAvbscVZAe+M82+07aW1dLo9JESlfHT8p3x2XHm0KGG1msCYuN1gggkRJbYHY3PFq1HVssggEAi8sgurxLEYpxaHX3Npsw6wUc8eXOf8XD9I7exU7zMl7KZtfuMBTH/g82dbeFujXQ5ZlZfuiGE+AZHoioFCQz/5iXD3UvEtxxPz8PCsrK9NzmCKPt0vGLaoJJxMFxOuWaL3BJr3hy1EPp3PHjMRtNVFFKfxWrLWbbMZtR+OatPyGc0ubdaWwk3bkDdfffjKt5ShXo3FWCknUrrsslVK4ZHJ35rhu0ZUuyuS+v0LXT+u7HstqtNoz97kaRblPFB5bA42PScMmAqVGUf0Tx6erxOWWbK3H1Y89zqUPPoTsy1Lnuc8v/uIv8v73v59udzw5/oM/+AOOHTvG/ffffxN7FggEAoFAIBAIBAKBQCBwbchH/vCGCt1QrCEpn8u4DKAQAW1qYjMwznk81bGpRbtdGvTvaZszf+lRkv5G+VY6f4C8NUd7/RzdtTO0N85hoxbDuRWGi4cZLBxiuLDKYPEI2dwKWWeJdP7AWGQt+jhYOsqV27+UtFOxe9eG3vJxXOWaFEzlw1aj69/jeuQ6gyimVxEnT5heQx5ZbiubQWE17+/bzRc+rYmJt9foXnmCuctPMHfpMZLeVUzWw9gM4zLUpdMM3vP/xl06Uysbrxxi9U1/n/bJO8H4KKl49QhLX/o2uidux33mz3Efey/yxOdx+4nonkDvrLN09r4y+hpATMzW4TtKG3xvG67pLx0tTiicDZTa1z2Oh9tEg+26nXsh9pc/Aj6yany/nImQ0jXApwBQ4F0GlC4t+L2VvEBnnvi1f/uarj8QCLwwUSLPUOKLwA1juNFj4wvn6Z33k6DO4UUWbjvExQ8/hMzIhdw5ssjRN919w/vy4IMPjgVvKOyjARH0sHlKJxofBV0Vx4HllRVOnDq5a3siwrmzT3H1yrQ1jI/wdj6CescSb0wLmQL0b02wK7uYGIgQreV0H0sby+vMR2g3vSeRQoy/PokbJgJOiLZdLYq6VkHxT3YwIq/2MRdM36EyQQ8cuiEtiW0pskMx2bIhWs+JdirXbwWdC1gvzDdOAa349yxITF08duItxmV2eadBEtW8s856K/JRxHfjc4EgrV0mT8q3YYuo96nyGlxntjMAgNnKa2O38obbWLh7F6ug5xnb29u85S1v4ROf+ER5TGvNT//0T/ODP/iDN7FngUAgEAgEAoFAIBAIBAJ7I87h/sP3QoMl9NOuWxVrTs4WUd0xLvFOlipPUdW4VOd8ruNq+QkhzweN7L7UPhEPjgA26WLKyGuPU4asu1SzxhYUaXeldszpiMt3vAGp5BePe1c5+NjHa+0m21dob9dT/jlTt4f2aRon19om1gWdw+TNLqQjsqSLEiHK+mUNUuYRnxifWs7s2QjU1yCfBZKGKE3aqd+jUaR37Vo687S/9X+eivAeFxEfnPTRP0b++v++Yc961p5n48Qrasfa6+fobpxj+8CtpIVd/vylRzHDHfRIqBbn87zvgjUxyln0Lrbyk2K3A2+b33CnnTY+oruCOnCc5Gv+H+jF3QPmAoFAAEJk93OC1lKXw697Ebe94zXc9o7XcORL7yDf7M8UugH6FzbJe7tPPJrIs4zzT53jwc/fz32f+RyPPvQw62tXy/dXVlbqBbTyOa8j7e2/G1AOVOX7UQ0d3Qf7qN9/gvM/+5dc+fV76X/+YnNZpTh6/Fiz3blS2HmD62haT2W1SOvyFPBR0LuMFYKPFG9qAhDdPE1VgM69qKzsDKsirbDdGR+zIhQ5XzbkC6ZePlLYBUO+GpEvNwv1Zii0n0wxO47s4MQ5RuFaGtfVuPaMqaJRSFtjFzQumeijVl7In7Rrr57i/L2dVTcR/jWjeYXa9b6IgDJqKmq/xLH7fbUyVXbn4Uuzz38eMj8/z8c//nF+4id+ovyDwDnHD/3QD/HGN76RweCZcYAIBAKBQCAQCAQCgUAgELghOPvMCN3VH4pIUzcS29RYoBtbeO+/XikiVsevSlMT5ysgmhC6AbRYkt56bb1QIUTD7fp5Lq9H1wJZd4U87tSO2Wp+5mpnd70YmVrvzFtz5Mns3OlOG7L2EuncKml7YSygF2M61aTyBth7De/U+8+C6G4ljri/UR8j1eA92d9m+KHfRIb95nqUwn3+w8hf/t71P+sN4xEPttFZfe0vb8+TteZJ58Zr/A5di8hmYRVe+uW7NmdstqvQDaOl7+IZSjpgEmZ9kLSzPpq7gvS3UfPLu7YRCAQCI4LY/Rwl7+++u8qfc235U7Is49GHH+HKpcvkeY6I0O/3OXvmSc6dfQqAgwcP1qyRq7io2c7bR0ADSqEHjqWPbtN5IkWnAlbIzm2z8d6H2Pzgo431aq05KAvNYnYmdB4Z+JzecbOFthK8nXmTGC0COaAVg1NJc/8jhWs1fxGL8u+P7LcbA7gjxfBg804AlyjyJTNl310lW1Bki80f1WzZkB6JcB1NPt98Tt5R5DME9/J6lTRe++icmXNfOz3p9YXGgyGG2dbmMzYSCEDkJ8EqndEGPi96o+AtgunZqemT7e39uXk+8s//+T/n3nvvZXV1tTz2l3/5lxw6dIgPf/jDN7FngUAgEAgEAoFAIBAIBAKzUVEMB47f0Dp9ruB6fmqbdMYWysVZaiT2Fi9BIcqUr+kcfWpcb/W1Z7x3M0ocZkKs1DadEgXj3gaTuEqkt6+r3gOBsQV6wXBudUrIVhXB2+mItLtEf/lY3Sq9wJqEwfyhMhd43lrAmmRCiJ0leD830eJQeVq7JlEa098qcox78tP3s/Mn/xE3aLbjl4+/7/o7scv46Yn86s7EbB26g7i3QXvjPMnWFeLhdu1JNne8Gp58cP/tJ2122w2iAPVNPzSVknLqPDcRtdTbRDYb3F4DgUCggSB2P0eJ5lq7n6Ag6tatP8TJrtHgF89fIEubBfK1y1fo9/porbntttvodjq1yR5WfDRxR+HiQiBVhYV5ghcugc7DA8yguQ+9Tz5FdmF76rhLLfaDT7L019u0zqbovkP3Ha2nUuY/vUO04xBgcFuL/u0tshWDixUuVqQHInovatF6MqPzyJBoPUelhUBqBbIiehvIVyN2XtomPRD5nNYGXEvh2hqdF9fCaDIILvL5sUf5yyVWYMbi8Ogq80XNzivn2HpFx/ct8Tmz0xXD8Gg8Fny1HzvbLtqOFNmSIV+JSI/EDI/G2I7CRZDPa3ovarHzkjZohcoE1zVkC9r3S3mR2XY09kDM8NbEly/qHl3D2Fpe+d8Go3ERn5NcpYWFuq5f1+j6UQoyxmWKcrjxAEhLYee1b3tUjwHb8f2ctG4SDcSFYwDFRolRFLdIeY5EkFzNaZ3LMFvW5y23gh46oi3baP1u5vf43DyPedWrXsWFCxd4+9vfXh7b3t7mTW96Ez/0Qz90E3sWCAQCgUAgEAgEAoFAIDAb9dq33eAaNaK0zx2sFNZEPvrY2fFrMqhFaUQbpCpia82+Qr6bon33iZoQK31NExGwkzmWncNk9ShiURobjdfF8tYcveXjZQS4jdsMlo7SO3CKtLNY2HG7IkDHW7wP5g+UtufD+VXcVB5zqW8YUMrbwtcu4GkI2xObD54taGdBmfHzohTa2VrObFC4jcsMP/1fp8rLzgasnbvh/RK8HjB36VFWHv8bVh7/JPOXHmPlzKdYOv8g85cfZ/HiF7xbwEhoXjwIn/0L2NqnyKwNvPOH93i8BfXAR6c2aTT3eIJol9SkgUAgUCH8tniOMn/LAdY+cwbJm78kukeXiTpe7N65sMH6w+cZrPkv2O7hJVbuOkp7db483znHxvr6rm2ur12l0+2gtebYseM8+oWHy/eqX+aSKC9wixc9y+86K7TO7x5t3v/cBeIj87Vjwy9cQVJLlML85/1EzUXU8j3bRVP+nB7z1z0SoOOLGQowPYc57SN709WI7HBlh6P2fXddw+B2Pykzm5bWpRyznpfXNrJqF00pxsI4ct0XrAyKQLbq28kOxWSH/P/HF7N6ju3iUlQG2YHIC+cFZsOCUuSLhnzRV54vmdo5eujvgLQ1eTQhIBeidL4aka9GIEL7sRSdVSYQPvENEoPZdvXyI0FcjU8dXWNpE279S8qxrAxB0b60FbbN+Llwhc14fXMnVHKfi/LjXEa+C6AEl2j0wOcVV05I1vw9chG4udl5vOfvOjzzvRcCURTxJ3/yJ/zyL/8y3/u930ue+3H72Z/9Wd773vdyzz33cPDgwZvcy0AgEAgEAoFAIBAIBAKBMfqVX4W7fBb51Pv3Pvn1/w18/E/KH0dR3FIK04Iwir4er0Epa2v25ZgIEQc2r1iZN6QxVCNLxL3F18l83fujXkKUxilTOzpcOFQvojWX7/gKls9+jtbOFS9Wxy16KyfobJxHubyMwB7OrZJnfYZLh8uI7MHSUZLeetmGwjtn1oVsTd6eJ+lvloeMzfz4VATtyejxcvykEir0LBKur4vyudE+mttZQNDOomyGmLiMtM8e+Qzt138NqrpBYSpP+jW2PestYPncffWo7f60C4CiiAC/5SXoQyeRyudnT5xFfeETyB73UPIhtLowbI5sbyRKcE8+hLr79aipjRWBQCBQJ/yWeI6iY8Oh17+o8Qstmmtx4DW3ArD5xCXOf+zhUugG6F3c4OxHHqJ3cfzl5pzbNeobIM/HQnW706bVmoiSnexLIZCOalW5zM7xPOrHzrQY7namradV7usrz4mnx0EJPm9zPn1d8dUcvTMrGbTHLmjyOd3cZ0dtIiYzJhYCNVF6RLYa+cjoyT4D8ZXcR0qPjjXcF7Nla+eUGzoLQb6+83SyEUV6LG62FlcK1x7bCcmozsnqKpHbU+9Vw9rLyPF6G9XnovZWcc92Q4m3r1cN5+kcH7nfQPe2A8zdEYRcgHe961088sgj3HLLLeWxBx54gJMnT/L7v//7N7FngUAgEAgEAoFAIBAIBALT6Ld8K+rt78KZmOHcAYZzq1htvPhrIpyJce051JHb4cWvB0YOghFiooq9uC6WqsbRwWXc9ZSQrWuCuD92fZbk+4lobqo3b83VMlpvHXoRV+74MtL2IgBpZ5Hh/PR6l4tbrJ16NVnSgVGEtlL0l47QWz45FliVIussIboSE6cNeWexVp/Oh9P9nRBpy+VAm2HSHibto/LUC6I28y+Xo5z1UeMiU/bq18PeGb+fWcb50H0/oqxf9kjbHKej8XhnQ8jra92qM48cu6Owyb/G52sqX3id/Y6MAnSrjZx/7Fpa912wOUTJ7ifNr6APHEPnKTofom1aty0XKZ6Z3via8pTsv/422Qfe4zeeBAKBwC4Esfs5zNyJFU78nZexcPsh4sUOyUqXlVec5PjffhlRN8Hllsv3Pdlc2AmXPnuavJ8izmGMwUS77yJLKuL2ztY2w+HEJKdpcqJVaYE9shbfDbNaWOfkljzLa8eqKEANBTVwXhydIdRrW0QWT5YXaJ9JSc6l6J6dobwq0iMR2dL0uCjwub6LtpuE19FMWQ0bvowjxfB4XNqaSyVnic6E1oUMs2lRqWvMpa0cROsWvWNRWVVdxo95NLZdp6F519EMbmuRrfr2q78JJNbYrvb3SkPT4Cjx9c4UrN3oNcNWSKuZv32UFcgKq/kZ5XU+267I9KUcl2iuRfvYEge+6k4OvOkO1HM4B9CN5tSpUzz++ON813d9V3lsOBzyD/7BP+Dbvu3bcHtaCwUCgUAgEAgEAoFAIBAIfHEQa9kaZqzd+lq2jt7F1tEXc/XW17Jz4BYfPawU5Bn2fb+MJG14zd/xAtykxXdBkTyvoaH6sSmL8Ou+gH1EfmuDjZJSvM3jNnlrHht3EKUZzB9k/eQrsUmH9Vtexc7KSdZPvmq2kK4NvdVb64JnLVd5ccjmU0WdnjSE9WV0PiTubxINttDpEFEKp41/mYhkZ432zhrJYItksEmcDeoR4kwLsE93tS5vzdFbOXF9mxCebttxBxnlR1cKlQ0w6dhC3mlDHndwOsKaGGnPYXc26f/1e9n+v97N9h/+7wz+6+/ittcRExWbM2KcNvu/nj0E731X88T9Mz8vu7J4EA7d4sX68lWpF5CP/N9w5v7iXVAiaJd7m/7i/zVg8nScp764FvvIvbjHPnvd1xUIBF4YKNnLYyLwnGXrzBUu3vv49BtSRDsXFuMqMizcdoDsYMyVK1dm1nfXS+8mSRLs5pAnPvcw/bmJ/DAKL2I2UVhXzz00oPP49E5A8GXnvuWlXF1bo7e5A0DSbbN67CDpHzyK22oul60aNl8376N9m55mK3QeGcyMKs+WDcNTs3M5q6Fj6aM7zXWPrk0gWzGN12/biv5d7d0nG7nQOpc1Tu5Eg2vNnmiYLYuyQr5sGtsQRZkzvQk9cJhtR3Kx2WJepVK3PK/WzS4T0uJXi2trXHvGHxZDN3tc8ZXbjm6MjgeINuzM+xofnuPQN3/JLpUHRvzRH/0R73znOxkMBuWxEydOcM8993D77bffxJ4FAoFAIBAIBAKBQCAQCMDGJz/E4MmHG99rr5+ju1HPeWz+2+/Bfer9yFOPzKzTOxpORCdXrczBC3ETebOReiyxyKS8x1iAHNUlbldRV5TCmaS0Snc6YrhwsIwsz5MOF+7+6msWI81whyMP/cVEY9Nt590lb8Fd9Lt75TTJYKv8WbRBEKJKVLJQ2JRP9kka1gudnRqj67N1n8bGba6eejXdtTN0r569ATXus12TkHZXUOKjfgRFe/uKj3gv7nvaXqS3dKQW+axsTjzcrkW1K5eTbF/x+b9HiPhI+P10ZnJN+Hokn+4i6g3vQD70nmsqVn4aGvsg9Q0Wzu35HAiQdZdr9elbXkLra991Tf0KBAIvLEJk9/MYm07vykPEi8KVXNqSWzYfvkj+wBrdbrexruMnT3ihe2vIlfd8mrzfIDzn0mxBXcnd3buj5UXhyVMUDP7WEmefOFMK3QBpb8D5R55EveEQqjVdzrYV2y/3fTbbeRHlPIGC4bG4MULathXD47vbrEikcK2GnDyjaysmcNGWazxH7zjM5u6W6UQK225uQw1ds+U4oAYOlQpYL1o3YdZzorWGZwHKZ8F1ivYbEKRxJ6EAMmmZXr5ZsYFKm8el3HQxa/I1skDPpfHeIZC3m619REHr7mBZvl/e8Y53cO7cOV75yleWx86ePctdd93Fu9/97pvYs0AgEAgEAoFAIBAIBAIvdPKdzZlCN8Bw8fBUbmj3+b9EtqfzE187DSK2TKx1KYUoPT6zFL+Lda+98hlTEbqL+myrW7NQj9I+0XB7Rg2zGQmqyll0nqLyzAuONkdnQ3Q2RNkMPex5i2mboW3GcPEwWXuxjMTWzmKcq1mGK0CLg0l3wKb0hdXxqZw4KzXktTCyEe8vHZvOEX4D8eJ+ca8L+/x4sEk83CIe7hAPt3FRUojd3gI/GW6zsHamFj0vJiJrL9Sjn3VE1lmqNziRV/4ZJ24hD/z1NRcrY7mb8tlPOgk02LQ3RfpPug3Izo34LAcCgeczk34kgecRycK0/TeWmZG02XqflVMHWTl1gI2r61hraXfarB5YpdVuMxwO6X/kNG4rxWxrsgkt0WQCQ0FihUTKC5SK+m4+o9j8W3MkFzIfyZwJdsEwuCVBtJ3Zt7X+Jie/6W7sFzbIzm4xGA4YHNAMjyc+6tcJ7dMpSnw+7HzeILFCFTm708Mx+VJEcrnI1a0gXzLkK9HMaHSVCXroiK7kRNvOfxHrysWMNmgW/6+HQnzFYrvaW6crQVkfmayUwmzbsWW5ofZFrzKHFi/Smp715cUL2HbeYBcjyH1/lBV036GH44hr0UW+6vXc28bHGmUFs2XL6Od8PSdbjZBEIYmu5VBXQ0FaGpdZdCrj+2b9NajKNQv4vOCRKu3jRxv1kHF0fVmkpb2luarUm4lvZ1R29F6Rz7ua69vNGSTyf0coW2wuELx9vFK4LqiM0kpejEJi2Lr/PAuvPIYyYU/PflheXuYzn/kMP/qjP8q/+3f/DhHBWsv3fd/38bu/+7u8973vJUn2yL8TCAQCgUAgEAgEAoFAIHCDSS+c2fV90YasNU8y2Bwf27yCWjyAbF7ef0MiKLE+f3WxLqXyzB9Tpoy61lKsE2LGYq1SgEYqEcx+GWz8/7s0PHVEZ0NozdeOmWwwlUsbwAx7mKyHMzE2ajN/5Qk6G+dQzuKUJupvY9w4Ot2L63GZc9vYHN3fxCYdXOzdL0Ub+stHUWKJBxWRXWlEbO16lDhEJiPiXXl+OT5NsTDa+Kjvp2E+21884usyEVlnkaS3ft11zaISg11eZ5QPvcxbRHIrKJ+RarSyyVM6GxforZ4Y16cNLkowlUh5F7Vw2tSiu0Wp3V0xbyQbl/zruikWjnfbwDDjOZg+b+LHxQNPo1+BQOCFQBC7n8d0Di0Qz7XIdsZR2GpGbusRVx8+x5ETd3Pri24DvA3P5cuXefyJJ8jznNX7NtBA+8mUwalkLBS7inCaCWT+S9111PQXnFakxxLSYxXhzAqmP7tvIsKTX3gC5WDuFYu0jxxj/fz58v1o06KLDV/JpZzkUo5LFNmhmHzB7yCTlmJ4Ihn3d68vVuf7FF/1EwwF4/zXkwlmRgKvg2jbnyQGJFEMj5nyPTPwqrBtKySpWLEMCqG2pdHrFr093hE5vKX4mEYKV+RVNztp3Vp8NG/UEF/O69bexf9HW45oy0+gBrckSMVaXKf+JNfVmF4+PTaq/u/IVlyNZm7VDQB5/Ucx4w0BI0F8dL1MvCdKvOV68cyIHreF8UI2IqiBlPo4SiFJxTJndNn9jMFTG3RuWSGwf37yJ3+Sr//6r+fv/t2/y+am/yPxAx/4AEeOHOHP/uzPeN3rXneTexgIBAKBQCAQCAQCgUDghcW1q31qbglueQnu3CMIGhAvIlbsxJVzoKQUspVYtM0QlWPjto+GHtlIS46g6kK2OG+DXhG8J5cM9xO37OuXZpGwIgLbKCHZukw82AIEF7VIdq6Q9Dcr5zviwXbNet1FMSp3pYiqELRNcSSl4K0Ak/ZxUVyLJh7MHyAabI+vQylE+agUVQjaRWzL9EW5CcG78cILK/QJAX2/9JaOkc2N1/4aDOVviFV6udYpDhhHK/uIZuefofLkaffOeLCJskcQM5ZjnIlrYjdKleL/NVN5fqpbLW7Ete+XxudgBj6FwOgBEL9RI+4gWqNEygj9Uf+jl37Zje1sIBB43hFCHp/HKKU48ro7MK3KnoY9vnFcZnn8kUfp9XoAnDt3jgsXLpDnXkke2YSbnmPuvn4Z2dvYPvjo3f3szLuGOevOlU3WvnAOVY2MbrBP16lgNvJmOxxFszV2tUstje2oxrpL4XY3LN7a3Uw3pAfi3xtRGcdsNUIq8yNpiDxPD8W4ah7rcpauyJejPa8tOZ/VLd9H/6sV+bIZl5fpCaGieA6a7qtSdWvzSoR29Rw3wzJdCd4Kv8wH1HSS8hHyM66tikuvY3IY4A1veAMXLlzgq7/6q8tj6+vrfOmXfin/8l/+y5vXsUAgEAgEAoFAIBAIBAIvOJJDJ3c/wVlM2q+tFeXnHyf7+J/idORzSheRtM7E/jxxgKDE+bzINkcVArESh0n76HxYi//QU+Lh9OrUtdho++VFVbHHNjgTF1HXEdi8tIhWCIce/Rhza6eJsj5RNiDpb4Ay/hpHKE3WXsDpuvhqo1attwow+XAcgV0ca29cQmeD8piL2zht6leqisjw2prfxFrfaE1xVH/DOqJUo773gdzyUgZzq2RJl2FnmfVjL2W4eJi5y4+zeO4B5i88TNzf8OK6Nv6ltB/bfbWwN409nbS1n1FuKvd7Q21qQui+poh3qaSiVH7bxRcrKLzWjcZX5UlWBmeS8mWjFjZuewt4Exf/RmVqAPOKN2JOveQmXEkgEHguEcTu5zmtxQ63vOXlHHj5SbqHlzDt3YP5XUshIlw4/RSbV9ZZW1urvW8XxxOl9lMZy3+1Tfvxoc8J3ZRv2nphV2WyqzCO3ofeLeNI4SwWpLqzsTudzxt8lHV8ZXIigf/C18pHDjO7bTtvyFZmjJngo6Zds/CrAJ1Ri9Kuvmd6Dt1zPid1NJ7cSKwYHo3JVgy2rVBZQy7uSDE8mZAeinCxqgnXEiuygxH5vMYlhWX6BDoTWk8MiS9m3ta9elmJJjsQkc9p/zw07RUQbx3eiFbedlwXw9J03yOF6zSPu3JAJmB3yeltvOC9F8lqcw76wN60220+9KEP8Qu/8Ato7b8qRISf+Imf4DWveU0Z9R0IBAKBQCAQCAQCgUAg8EwSLSzTOnb7zPeT3joSeeFMoBBnVSn41dCmiCSWipAtKJdNRGTvHRW736hZL2ZrnDb+pTROGdBRIcpG6FE0a/HSYkkGW7XcxSYf0l1/Cj0RDZy356fEaBu362tqSvm6qmKqUrQ3L6Aq9SmxzK2d8TbqlfNG11E9NhLZaxbfZT3jqO9RnvPqeLnJXM5MC6Q1tEEdv4PEpsRpj1Z/ncXzD7J85tN0Ns6T9NZpb1/2OcSredKb8kY/XSbWKvdTswDO1NeYTTao1SVKM1g8jDXxuB1pWBfepY0iX2TRsYbn/xnE4TdtTG42KMd/9NKayafG5Gltk4V/Q2Ne8UaSr/z6L9o1BAKB5y5B7H4BYOKI5Rcd4dgb7uTQ616067n5gsFs5GTntjj78BNT7/dvrefsNT3H3EMDlv6mR3KuWf30wmhDiHAVrbx99QxEBNfyUcf5UlSz4AZwHU0+3/w4J5dyL542dk6Bqky8GhjeEjdHGJeNF68Z5VsXskbBVwE6F5QTXEfXRWWtvNB+KC6tv6fQCrsYEfUs8eRmA61wcz4neT5DrFcCZsOSXMqJtiZ2IBqFmy/KLzRffGk/3vjmKDe58oJ1E0bP/A2kwIvd4vOWNxLrXe9L69gi8UoQu58u3//9388DDzzA0aNHy2P33nsvR48e5U//9E9vYs8CgUAgEAgEAoFAIBAIvFBYeu2baZ24o35QHMn2Gq0tn5dbTIyNWjiT1MTNyZUpMdH0MuV1iKGluOhsERmeo8SO6xtFFCtVE7IpcjzXIq3FYbL+RKS1EKW92pqdEsEMdyaEZ83O6ilsNF63dVELk/bHVuJFP+L+Zk3wVuJo7Vwp21DiUCK0tq8AoLOBtz+vCN7jiGxd/Gxq46fchCW52FqM8SjPtY9ib+F0XNSpxmM0GZXsLHz0j9CV/OF6QkCvjtv0XX/mopyb6p2OJle0ty6N3QNcTtK7SjTcBmcRwJoYm3TprxzHKeMdB66hH6ry3736tx8EhVPjDRp71qNM+WyPj81w94Sp9W5ts8Imfkz+4CfIHvrkNfc9EAi88Ahi9wuM7tElVl5+Yuq4AOmBCJ0KupjvNEX0Do8lDI7G0+UV5F2NSqeFScFHjO81aYwWWrTnO9NviI98dl0zzhHeQO9FLWyDPbbP+Tzj61ikfCtey+vW3gUqdTVb8abypfDbFOGdCq3Tw0bB28UKSfR4HtJQ3mznJGfTxvdaZ4bEVy0qB7NlG89xsWrsv4DfYKC9VbuZFLzLCwDbEEXtJ7Mz7OCLOaUXrWmO7pbZkdu+b0Xzs6zwRXCm+c4KkBxbaHgncD3cddddnD17lne+853lsX6/z9vf/nb++//+v8e5/e8yDQQCgUAgEAgEAoFAIBC4VlQUs/y6t7I4N0d7/Rzt9XPMX3zUC4jVE/cjtu1HuGMcjWujlhfRJ+288ZHQXnQdmTSPChfi8SiPt0ys2zX0y7tE1tcAlTjyuF2zR48H22wfuqNmX+7iNhvHX4Ez1XVbweTj6GEvQouPKAaU9dHsuhTax+9Fw20QobVdd/2UapS0UuMI7VE0tXM16+1KnHG9Hh0hprCrjhJsax5XEetHEdnXLVBPriXe6CjnyforVuaCv76RZb7/WRMPd5hbexKV9mlvXESJ+M0L2QAbt4qIZ1826yx+UfNt1y4FcMr4/OJ6vEFDdNRs068Ncusr/GfvmlsaowDtbN1Tweakf/E7ZJ+551ovIxAIvMBQIk0qUuD5zqUnznH1C+dQuSCxIl806KGgK2KvSxT5Uj0qWPecPyd1tC5l6FSwc5rByRbx1RyV+vpcovy/bY1E7Ht35C23nULlsL22wWCzR7rdRwTsstm1DgG/dUMgvpoTrVtw4qOjlw3SmfiydWORe5SDuvPoEBTkiwbb1SgrROuW+EpGvOXG378iRST39BSpHD0FUth5+8hxhYsV2arBdTTpwQjX0mU+bzVwJFdyxAraenFfOVBDh+n7++ISRXYgwiUK3RdaFzNM34uMzuBzjMcKt1C/VrNl/Xmu6Pfoos14A4JK/X21Mdg5U46lTgUxPupe5YIaOpQVVOGg5DcxFGNhff3KjZsAcBHe2rxyj5QVVCrluX68ivPM6Kb4GtKVqB717wRl8ZHfo/sh43ZltBE0iTj5ja9Bx9c60Qrsxm/91m/xHd/xHaTp2OLqtttu45577uHkyT1yaAUCgUAgEAgEAoFAIBAIPA0Gv/cLyMXTu5zRFDDhxvmjC5vnKO35c0vb57ptuRcoDS5q1dckncVkg/0JkRNrmQ41LQg6i0JVzvV25jbulMd6S0fJOote2BfB6YinXvXfYNIe85cfB6C/eJSsu0Tn6lnm1k5j0j7trUsA2LiFKE13/RxKHIIi6y4TDbfLPNJZax5RiqhiJZ22F31e8FHPimh15exYxXaCYhxhPUvcbiKPO0hUdxHVac9HkpeNern4WoVfvw45OdZuIsJ89truXu35iH09zluuRrnXDWLi8f0sIuWrz4IbRUBXGMytItF4o4LKUxYvPbpHL+p9rvdcpo7sF1HK54yfgSpyyZdECfKSL0Pu/0jluveWnATARDX3gTzp4uJW8bkYNaggTuh+64+ikvY1Xk0gEHihECK7X6CsnjyMO9omPZaQHYyRibzPUETU2oljxTnS0uy8tMPWq+fo3dVBIoVOpdiBKEQ7jmjDFsLj/r9SnzpzlqiTcOyuU5x8+YvQKCTZOyrcd85HKWcHYvp3tOnf0SZbiZB4tg33qFazbYtdlhBvWNrnMlrnMuJNi06lXkBXrM9n1Km8j1ERie7P1JnQupDTeTwlvmJLoRsoRWtl/H2Ithxmx6HzQkTGC8+tcxmdJ1LaTw7LMkCZ89tkAhO24XpYnDeyio9UTeiGShuZ74vpC2ZQiONm3IabM9gFU+bk9mPhx11i7e8VE9MqPT6mHCgnqKwyVsV4aYuP9K4I3WKYtrdXeFG9/LloP/KvUZ8kswzObRC4sfzDf/gPOXPmDC9+8YvLY48//ji33347v/Zrv3YTexYIBAKBQCAQCAQCgUDg+Y7qzDe/MYosLl7K5qg8ReUZyuaY4Q7xYJt4uFNELXsR0q9NTYupoyjTybzKjATw/VDNHU1hu20nUhGOokgmorl1PhadxcSIicmTOQCGCwcBsEm3jPrO2t7hcDh/EES8XfkI50h21ss82iCYdMfbRvvW0fkQbXPSziJpd5msNUfc3ygi14uXy9F5inajny2aupX4tQirU2NbXGuNG5lru8navBI97gVss6+I8jIAp9JHNfr/mrNARRAfHWrIw61dXj+wj+v2EdjaPx9R4l/GlH25nlh29bbvwq0cwxWR6U1uBqInxidP4XN/sadzwexGKxsBRnnNJyPIsxR7+oH91xkIBF5wBLH7BYrWmqWH87HteEOUsgLijXxK8IZCnOxVbK+b7LsFksvN5WdhreXxRx8lHQ6J2wnHXnE7ahfr8lpnJ9GqsDCf8Z6qTHGaumgULlLN7+kZ9t3VU+xoc8B0BZ3Hh8SXKznOK6e4zkQu6qYNqbGama862rb1MZ81/DJ9jsKL6rtOTpTCzpnm9lUR1T+jydE5Ejd3S0m9/cnJ4F7lJxEb7LWfCQ4fPsyDDz7ID/zAD5TH8jznu77ru/i6r/s68jzfpXQgEAgEAoFAIBAIBAKBwPVhbn9FEaFdeTmLEltYhTtvz+1ytLhCqHU1UfNaREBV1FdFtLm2WOOqkI2M83r7N5vbdRacw2lD1vYCf550ERRbh8e5y23cob94pGKBbWhtX8Hkw1LIjgdbmKxPHrfJk67P7e2st2aPO7iojYtaDOcPkHeWyNsLZHOr9FdOYONxJO0NNgL3YzEh8oq6PofGhpXp6ZO0KZ+DUWT26DUWutX4+PW02iBkzywnUroNiNKY4Q7tjfN01p+ivXlpz1rUqL3aOq721vD7uFNNq9buvr/C9bYL4TxGimekbl+uQNU/Az7IKd99TXnqAnTtPGfiXa3QJRvueU2BQOCFS7Axf5bS6/XI0owkSeh0G/JY74KI0NvpYfOcpNWi3Zm29xg+dpWrv/N5xMDwaEy+aHBtXYs2LuvD21XbjsYMCwvpynuSKEQJrYv52Ja6Wl6B7WryBQ0zoqwnWTmwyvGTPrf49sYWTzz++G4XjDggnhEBPmEVM/WeA913dE+njafo7Zx4c8ZERcTnpG7YLDDCjaKpG8gXNIPjCbar6m2ItwpXuaB7DpPO+JhaQYwXv3VlbigUgnis0D1be2+6g4IeShGNXilvAK2w3ebnAudQwxnXLcVzkovPvd00/s6hB83lBZAInFZkR+LmXO3WobPpwyUKjv/9LyFeCPY2zyR//ud/zjve8Q52dnbKYwcPHuTP//zPefnLX34TexYIBAKBQCAQCAQCgcALG0kHcPksRDFy8CTq8c8h9/8V0t9GrR5DverNqIPPnZRk9skvkL3v/4BJ0atpeVtc3Q4bb788FUG7D7yleeRzShdrXDrto/clbI4aV+PgjqK+UT9r7oUV8qjFzqEXkXUW/QFn6S8fp79ywoukSqPTAdpltDcv+pzcNmfxqfu8Pbg2IILOB+g8q1tPi2Dy4UR+bcVwfrVuLS6O7tqTaJm0Fr8xTFmZO1tYzFcQt6t0W1qWV4Xfam7xqQKFgXn1/cn1YxEQu6dk7HRdGBelcFG7JiKr4ln0YjA4bUAZlOSjuH5AofPhdW0m8Ou48VT/RznZq+f5lqrHVPlffz0RtjXX0Iigs34Z0V7+K/XPmBRi+2TZpj6jx2lLHYq8vVAGPvl85q52Ta23fSfRrS9tGIFAIBAIYvezjn6vx9kzZxkOxlY17U6b47ecpNPZW/Te3trm3JNna/l0u3NdTtxykqQ1ttjZ+C8P0//0+VrZ9GDE4LZmGx5RkK1GKAum1zyRU31HNGh+zxlIj8WzJxkTRFHE3S8ff3k9+oWH6ff6zScXOZxdrJpFWdhd8HZe6G0/MfTW3Q3vJxeymhhcw/rc0015XqCYcLRmW7Hv3NkmXzFEV/PGNlQmxJczn7+noe7BqQSJNZ3HBs19LHJ1zxKldc/5TQozLOdtonDzzbvqVOpqmx8m61YZRbh48ylq6NAzyvu8LYps0WAXZ7Q/dDPvS/fUCofe/OLmNwM3lF6vx1vf+lY++tGPlse01vzkT/4kP/zDP3wTexYIBAKBQCAQCAQCgcDzE8mGsHYe4hasHIHHP4fc/xFksAMHjkPah4c+AWmxxhi3pkViFOot34p+9Vu/6P2/VmSww/DXf6LhGkYnNETZ5ll9qUvkugVF8JGnrhBmTdqrCcXXXFchkNb6MrEut716K4PFQ2ibA0LWXiBrLzK3dpp4uIPTBht3fF/2EDoRRzTcqUcei0zlH7cmIV04UOtHsnOVpL9ev4AbICkIeGv2ijiqsz46z8ZjIcJuHpLjCO3ifOemrcRnssc5Lp+51lv+/yhavLifosDF3bH4XDxz8WCrNvb7Faj3i1O6Jh4DODTGjjc0lGNV2TxQRmwXx5yJsUm3sQ2Vp36ziFRiuifGSFC13OOj66r9iB83tEaKFe80mcMlHb8JRClwOaawzB93QBN/yVeRvO7v7ntcAoHAC4cgdj+LSIcpjzz0BZybFoyNMdzx4ruIk7ihpKff6/PYw4/QdEvjOOaOu+/CFHk7Nt73BfqfvVA7x85pene0vPV35YtRNOSLxue+FkENpMzPXZ4DuDZEm45op95/F1HmBZ/MSDMLYwwvecXLyp9Pnz7N5tWN6TLOR1YrwCl8dPdkFPBE/pSp8kVUduvM0Pd98rzcEa3bqWv2O/woo9ml+M9kK06BXTLT0dMKhicShicSEKHzyIB83tSjwEWI1nOidTclmIuC9EhMvhyBE9pnhujB9H2RWIGdvmeIoAcOVY0IN2q6fFRYk08K9k5QQ/HR4xP53kdCt8Lff4kVqqF9NRB00+ZbKMV3AbIVg5ubELydTNdZ0Dq8wOG3vBidRA3vBp4pfuqnfoof+7Efq/0Oe8Mb3sAHP/hBut3miXIgEAgEAoFAIBAIBAKBOpINYf0StDqwsOqF7Ac+iqR91MFbkP4WUhWykzYMdppFwT1FP4X+jn+NOnjihl/HjSS/90PkH/m/Z58gI1PmyvXa3EckVyJvdTbcVTzdDcHnyUYcUTbY8/zdcEyvwaULBxnOreCiFspZnIl8tHatE66I0q6XnYpkbhBOlc2moqb1pKAI9BcP1+ykTdqjs1lfR95L7G6KIm48Tylc1PJ50J0lGm7Xop2rUcfN7ajSwv3ameEQWv6/nR7nUTmlEBEvdk+I1qI0NunUrdCdpbWztrfg7ezU/dgPgvICckXodzoCBJP2xyOpi/V9cfXnxjkU4q3yJ/OmV/pmiud+ptitVL18+bms99WZuLbJQYC8NT8ltOtsiLF1N9bkTf+A+O7X7WNUAoHAC4kgdj+LeOrMWa6urc18f35hgaXlJeYW5onj8ZdG2h/S29phbX2Nfn9G9DNw9PgxDhw6CED/cxfY+JMv1N7v35rgusbnsi4EynwxwlVFTltMMJy32UbE57+uWFWrrIgWFsElGtcZl5dR9LDdfaKysLTIqdtuBWA4HPKFL3xhPNkQULaIVh4fGoujinESmdHTPRnxXRG5wUcodx6u7OxU+PpzQWXibcRl1KY/Vo2W9u2rWh8p+mTb2gu1lXLpoZjscIQkftITred0nkgREVxLIYkCB2bHoof+OkfW3mIUw2Mx+VJUCuNm05Ks5YiM7w9KeStyKcapsEbHCqbnUNnEPVA+D7hECiXiJ0DGjwN4cX2UA12nDjUUsqMJEhX3MxN05tCD+tjmi6Z2jsqdj6AvIuKnJo163J/aLYsU6mgHfajL4Oz6zGh1M59w8hte0/BO4IvB5z73Ob76q7+aK1eulMfm5uZ473vfy1d91VfdxJ4FAoFAIBAIBAKBQCBw85E8hc01aHehs+CF7Ic+DlkKh29FNi/DAx/1kdkArS4M6wLlWKSqiGlF/t+qkFtKv3sI3upL3oJ+6393Iy7vGSP9s/8T9/Df7H5SKSQWa5QuR9vcWyMr/bQjuwHyqI2x6T5zM8/oZuX/q33Jky7bB2+r20CX97VaQZPgPS36KptPRXJHg80JATzHTOQkHywcrAmW0XCb9lYlh/Q+5ASnNGJibx0vu4i3xbNpdYSuiPP7FsufhthdWxmdjCAfRTVNiO2lCF8Vt1E1i3soBO8JO3Az7BEPt2rHpiKyrzO624+DKdZW9dgqXyl0NkA766O4R3b64vx16HFkt+gIG3dm/76weeEEMFr/bh4fMdH076YpwdsL/ZPCetpewsWtWtloWN/Io1YO0/3Gf7rPkQkEAi8UQtjjs4SNB86xvn3FRybPYHtri+0t/4W4vLLC4aNHuPDok2xf3QTAdtSuk9etzc1S7G6/5BBbf3kat+mtf0SD6/ode0pAZSCZIMs016kVkkDTlENihV2atp32E/HifO+YMvOL+2DRz+FwyOOPPuoPjsqqYrJuK1+Savy+qn5/qkJgn0RRi7I2W5OTRsaR26N2lBd/BeUnlelE+xN9LNsf3VNViNjg85wn445Fm7Y4RXkhepz+uLwWBV6szsXn4K5EgJveuLzo+nvk4/5LDMQKGbhmZ/FiniNmNNGpTCQEVHHNOvUR3TJqxyjEKGxLoYdjO3a/caJ+jojCDPNyP0IjDc+czoWV199GcmKRs39wL27QnGNp+VXPnVxTz0de8YpXcP78eb7+67+eP/7jPwZgZ2eHN7/5zfzAD/wAP//zP3+TexgIBAKBQCAQCAQCgcAzg+QZ7GxAe85HWz/+OeThv4E8g6O3I2vn4YG/LoRs5QXv/va4goc+Pl3phNANRXzHSKxS43Un0EglGrUaB7JrdOzauWu80i8+KmlOvVhSE2ALmV8qopxiWjS+Dkx+/ZHhI2b1IUp7zF9+nK0jd1ZOLlbQqtc32uhQE9yLQJ2a4Krq6f9GUb+7iNUCY2vrUb+GO80nz6pjFN2rFGIixErz5oBKXycF96d7n+oCa3XNXCFVB4DKmq6MgoXK434RWiqCrv9M1R0EFIKyec2+W4lDD3u4ZCwe26SNzodom5altTjESiEQ7762vysT4rJUBHTRBnEVN1Ol/KJtta3DtyKHTsEjn67U4+obJho21Ex1A8DmhU25qbQHE7HxYLOxbXlBlPVIq2K38lHg1ehuuXoRGfZRrb1TvgYCgRcOQex+FrD16CWu3nsG7mix36/y9atX6V3awKbNgl8TtTlRpFl95yu4+vv3Ydeao8EV0LqQMTwcI63rtYOZgVKgpVHwPnHqFrpzc1hrefyRx8jyfNqaXBfC7WR08iSzvnuVQlQ9AnkKrRDTXIHEGicN0dH7bD++kiORIl8x05MYo4pJ4OxqW0+mSOTzqE+VL/Nvzy5vFw1qw9YF+1GRVPxGhskxrzYxa1OGUuTLEdFGPjuXt1JkyxHR1QwzMc8t/u4AXZ+c+8mUQkcGpRVRH1In9Yh9EfRAMKo5v3fgi0cURfzRH/0Rv/qrv8q73vUu8tz/nvqFX/gF3ve+93HPPfdw+PDhm9zLQCAQCAQCgUAgEAgE9o/Y3AvT7S6YGDl9P+7xz4K1qKO34y6eQR78mLcW1xriNnp7bSwM3f+RcWWqkKEH+xcRJ0XrseCtp0SsqjhXLT9rpUd1F/fdj5uFueu12Ps+sveJI0RQhR20X29yRe7rp8fTFbr3Ikp7mOHORFRwdduCZ1LInj6jAXHjnNaVkj5vchGzLI7OxnmG8wdwcRud9TFV6/N92Jc7HdeeSacNxl5/JPzuyPSP4qhHHAsiqtgkQGkgX+qvk0FMtUX06c0BTZtNlFjIGYvW+I0RxmVk7cXxpgVtcCQ18VYhvj5lxmL7NY1ApR+AGzkZ1Do9sc5ai/AG1ZnH3Pla3OkHIBt6O/XJCHOl/O8+l+2ar14BVCPJR2UbBG/lbM3JQNlsatPG1Nq3UmDC+m8gEKgTbMxvMiLC2T/+DPn20FtTL+9z/0HuMPV0FdiWmrbrrnD46BEOHakLTCJC+vg62YVtrmxcJc+yxrK25YVZF+untbOutDEfd6A2Jzl24jhLnQV6Z6+ylfZYz7f927OuSwRyIbqaY5cbhF/8RrVapPNkeQvx5YzWpeYJrxo6ov6Mj4kIOEGMwsw4x7bVdL7pAhcp0kP+nnefmLihI9v0XMq84FN1txT5ogFhKve1j6THW843F/di/dChh4KeEKdF4yPwFc3jCuSrUfO9EZ9PO9q05AumefydkFxotuWZGsliU0J0qIs5Mkf/4Ss1W3ehiDwXiJc7HPmWV8+44sAXmyeffJI3vvGNPPHEE+WxJEn4jd/4Db7pm77pJvYsEAgEAoFAIBAIBAIBj1gLaQ+SrrcAPvMA7vHP+fWNYy/CnX8Mub+wFo9iH7Xd25pY42qqeGSb3fDm5PrYXn2sFq0eU0XEQynUuTKqVdXOmb0+pL/hn6Jue8WefbjZpH/6H3GPfmb6jUmbZMFHz1bH1eboZ1iovlH0l44wWDxSPziRu1vZfCK3syDomqV3vHMVF7d89CxghjtE6Y7Pl1zYugMoET9ezpbR74Iib3VJ+psTttV7Y01cy/mNCCYfTp/Y8BkQpYvIcpnOV97A2FZ8Mme5m4rkH1l9T5WfbMRNWppL42e4ydLcKVNGeCubocWRJXO4pINytoyS11U78KIuiZJp6/k98JH4EVl3CWciTDZA5ykKV7u/01b4DceSNrz1vyN/8JOoM/fPHnsRVCU6fRauGt09anNiHN2ElbkAw/lDtTHVWR9T3aiStGl9xdcR3fmaPXoQCAReSASx+yaTbQ04+8d+kuYSRf/21q4RtQDR1Zz4Sk56PKkdF009v3YFYwx33v1ioni2mL597ioXPvlo43tiYHg09tHOzNgJmjuIdo8A3024jozh4Hab7Ucu+c2ttyTYBf+FKIqZ4xKt5SSXc9KDUXn+dJu7l483LapnpwRfX4EQbbmZgnM+p5FEEV/K0VnDxEdBvmwa2xegf0cLO6eZ/2wfM2z4ODovHDdGeheCOAqyA1FzG1JOvRrK4wV1K0TrzRPIUQ73pufKdjRuvlnIV6kjuZJjWwq72PzcmY2MqDdrI0HzYRePN3UI4Dq63j8ROrcd4OCb7kCZG+xIELgunHN8z/d8D7/8y79cO/7Od76T3/zN30RfZ26lQCAQCAQCgUAgEAgE9kLE+UjF2DsqypkHcKfvB6VQx+5AnnwId39hLR63IU6gt7n/BvYSvG2Occ3BJY2RpLtdS0XmrgvZVMTLkTA5Fi3LSHKm14fUi1+H+trvQV2vffIXEXGW/GPvxX7qg8WB0bgJOOeja1E+KtXZQuzeZV3sWUpv6RjDxUPjA67BOroQu8ugZJuhxGKjNmiDSXu0ty4hSjGcO4ASR9zfKJ+bUfS1qrRhst6EIOrQk8LrfvJ162gq73ij2F2ttihHNYezCMrl/rVHm01Ctt8gUBeUmTivUewubOOr9t2zIvplQuwWwEXehntkV+60IeuuYNI+urBrVzatbVYQQLTZU+CffJrzuMPWkTtxrW55zAx7zF9+rD7m+xW8DxxHveXbsH/wH3bphe//btHdsD+x20YJ6PGzYk1C1lkc/14TwQy3x+kwRaBI1RC97MtJ3vgNu/YhEAi8cAhi902mKnaDF07TY8k4z/MEuu9Y+sgWw+MJw1PTuWqcweeFrnzJJknCyVtP0enuncdi4/GLXHngLJKPJzIuVmQHIyRS5QRAZVKL1tU7loXP9EgPxV6wnyFo6563zs5W6sKsGjq6Z3PUzniXVlXsNms5bs7guvX8I9GGJb7oJzzpssEumsLCu2JHg9A6m5IdiusR1qPy635iYWOIdnyUc3kKRYRzBPFVVxOzBXBdjWvrYiIDrYs5pu9q51CIxXbO1MZFDAxOJD46uhiDuYeG9fIa0oMRuudI1iaswUeR38V5w8Oxn69VzhHjy0eXc3Q+sYN3JHQDWD8WzdbpMs69PfGHT76gfa73CTt6NXTE6znKQboSkR2IiDYn6hfBbOTNUfO7/Faqit22o5C4WSidu/MQB77yRbMrCnzR+ZM/+RO+8Ru/kX5/nDrh2LFj3HPPPdxxxx03sWeBQCAQCAQCgUAgEHiuIjZHmQgRwZ57lPzc46A10aGT6Ic/iXz+L33e6/Y8Erdwg51rjqrelan0chO5tEVQLpstYu1T8K5FkU4J2cV7E9GoIHU74+VDqMGOt09fOYr6kq9GfclbUc+hTeiSpWS/+zOoc496++dC5FcV0W5moM5zAAGGcwcYLB0pBePO1aeIhjv0Vk/iokrwk4iP4nW2FFYFUM6R9K6Ox0Npb3tebUfpMuJ7hEl79ahiEbRMWkHu/XmxyvhnqhSLvc33fu6JF8rj2jFlM7SrO3JO3mPfq3pk+6wc01VhXMCXqYn6RZS4zX3ZXcVupizDXXHfRmK2oMjb85hsLD6rIpJeRmKwOPS+HR7qa7TWJGwefymukuta5SlLT91fv39VAb885qZF6y//+7iPv2/XfvjNFbtHoDsd1e+H8/by43V7hY27/nKKTOhZZxHRUfG7TaOzwfgaig0t1fve+rp/gjkW1n8DgUAQu286IsLZ936GfGv8ZSeAnde4liI7GNdE4e5DAzqPD8kXNNtfMtdQoy+vWxEHbzlCq91ibn7+mnZnutyyc2GDwXaPSxtXavm6RzbkrSeGJFcyXKIxO5Z4bfxF4yKFe9ki6mUrrK9drdWdnM/QmRdPbVf7uUMqmIFDb9d3kmUrhvRYgsqEpLAYdxG4lkblgtkaR2KLhvSItzH3kxQvzkqsMDuO9mlvEW7bykcCa4UZjqO1RfkIYQByQaeujKYWrXxkOF7E1ZmgLH5DwujL2YBr+/Jq4DADh9kscmKP/mah6JOG/p1tsoMNkdhOiC/nmIEgGvIFg9lxRD1vPaOHApnzAv24avIFTb4U4WLIDsXooSCRL59cyIi23DgKXARdOKaPyuue9VHlTb8N3GjLAGNb80QjCtKDsReeCzt6PXTEVy06H1e0/ZKOHxsn6IFDp0K0Zb2N+aWJnZn7+G0kGqRo385PWBRVUYoT3/RqTDdpfj9wU9jc3OTNb34z9957b3nMGMPP/dzP8f3f//03r2OBQCAQCAQCgUAgEHjWISIopRARepsb9Lc3UUrR7XZRD32c9OFPQzpAdRcAhfQ2a+sEJu3R2rpcj+5U2guGewnek3ljq+dNCtSqIj6NBJ2RYCbiI47FTdhOMy67L5FLTbQrUyLbdF8rkmAUo//Jz6GTNiIOtVvZZymSDnC/8zNwvtmZ8vmEjRK2Dt9BNOwxd+UJFN4efOvInbX7rmxGNNypra+Z4Q5RNqjVJxM234KaEpV11q8/o4XYXXs6pWkrgUwLz015o5si1BvIo1b9+RRB2WFNDB79X71dNW1nDlMR3gCiTGUdecIVofzsupq1exONYrfSNct8H0wV1SzKRSls3BpHPhc55k02uAbr9vGZaXeJraN3187rrj1Je+tivfDkppsmAfwr/wHuo3+8ax9Unu56LwX881Xd9FNEtfuNFhobd8qobgHyVrf2TKosRVPffDEZ5W9e/LdoffU379rXQCDwwuC5N6t5nqGUYvllx+vHgGjbkVyxtPr1r7d4zYu+0ZYjWp+RYxo4fOwIBw4dZH5h4ZptiHRkWDixyqG7T9JemW88Jz2REG1aOmdSkrX6l6S2wuGXneL4yRMkSUVotFJGRivxUdTRlvMiq52eJkUbFpU69HD8paZzX870XS3KuWrfrgDliuhzQO+My5uBEF+1xFdzlK1MOqouN5HCdQ12wSBK1TomLY2dN+TzfkdkebwiWktbky9HZIdiLwwXKEDngkmF+GrebKuuFfmSIVuNfP52o9Bp0X+lcG2NW4jIF01tvFyxIUFngHhL83zJi+mmNy6PURB52+/aPRtFrKuJV2XSMhpXbQFXiP2jSHWlQKtS8C/7FVWOaT+u+ZLBJcpvGpgegb1x+DzpDZHmNUQYXNi6nhYCzyCLi4t86lOf4l/8i39R/m6y1vIDP/ADvOUtbyFN0z1qCAQCgUAgEAgEAoHA842drS0uXTjPlUsX6e/scP7skzz4uc9y/2fu5eH7P8/Dn7uXMw99nitPneHy2dOc/sIDXNjYRlIfPCK9LS90Q004tkmXdG611pYSB02icwNe6KrZ1PmXVNdLhEmxuuo3OD54/Rmjm8oJygv32njxqIhiLV+lJOajUlWeIr/6L5CzX3hOCt0A8td/+KwRup/p6DGTpyyc/0IpdAMYm5H0Nur90NHU+pibELF3Qznro3RtjrLW/zyyDi+F7okFQzXxmpA9FRR5oic/A/uRuqm0Oy7noraPFK4db/pMNbXbcJ5U1kur/066Jcje65fCSMA1iNZllHL1BJ9D3pafRy3OR3pXNsyIiciTzp5j1NSfuLeByutramlncY+aZtR/2yvgwPHZJzREy9fe1sa7EpRCt/PPF6Nnw2GjsdDtG512GmDScaJhHVh2riHlRCAQeF7z3JzZPM+Yv/0Qq689hY7reUU6x5a47bV3c+DggVIUqoqnc/f3iS9n9S9wKxw6dYyVYwefdr9EBGubBXWJFBtfOk+2XO+zSxSD4wlp5Hx5V9l9dY3KpnLQfiItResaWiGJGo9HwylKvO170+5Y5XxE+ShquRGjisjh5vck3n1i6zqa9GjceE7rXEbn4QEqb5iSJQq3R9120ZAvmtrzMCI5n2E2x3+MNf5BFCtcVHnvWu/N0EFD31GK4eEY29rtxijSgzE2afj1s49+KPZx70bnzsjTHrj5/PiP/zgf+9jHWF5eLo/9+Z//OYcPH+ajH/3ozetYIBAIBAKBQCAQCASeMbIs48mnnuKz99/HvZ/7LA889CAP3fd5nnj0YS6dP8eFp87y2MMPsXb5UrkmlaYpmQMxdee2wfIxH+W6V5vteQbdScFbsCaprIuUu/6nzpuMemxeaSgEtlp0aPFvtXyTyLxf+3LGYrYohYtbuLiFREnx/21QejqOocrWGu73fx7ZvLJrm89GRBzy+Q/f7G5UUMh+xNunkQvdNOSqjobbU/XLxHNVlimeSSn+VTZHZyk6S1E2wwy2idIeUTYgyvpFfm5peH4qV9l0PQ2Cty/mpkTr/Sz+eadN3SB4J0xLz01bS6ZF9mmkCHKqvlf0b7RhpCEivLG/ozZG0eza1AR2f9l66vOvxaEnBGq0GVub78r0BhszWdd+mPj9k7XmWPvcR3Fv+DpoNwTBFc/RTJRGffOPoJT2myjyDD2yg6/2tYjyLo/J9Bq+zPrsVHK56+7CrpcXCAReOAQb82cRLrf0z28iuaW1Oke8OM6xnec5O1vbZPdeIv/EhVo521I+V7WDheOrrLz9xTekP1ubm5x+7InaMVFMRSSbjZxo2+ESBUowO4KeTzCHu2ynvdq5ycWslhN7XLGgd1xjzmjR+NzdTV9wIohAvqhhRu5mNXS0LswQ7fHicnrQoNMZ062siD5vrMDbd0ukZ07VzEZOcnlG+xr6t7YY3jqdfx3n7dKj9Zx4Y0YOFOfHDV2xYR+9Ffljuu/Qs+YgIpgdh9m2tVzfNWzztQswPJnMzJmtUofpOQbHE6TdcI4TFj+9U89DXu8aYkA1RP2Dfxazg9O7V8v2I82Jd74GnfhdgTvbO2xt+t1+c/Nz1+V6ELjxpGnK137t1/KBD3ygPKaU4kd+5Ef4t//2397EngUCgUAgEAgEAoFAYC+2trfpD/oYY1heXMKY2SJNlmU89MjDpFkhcogQi7umSByd9uuiic05cv+H6n/fFwJV1Q53OLdCsnOV+St+nctpQzq3is5TjC0EorLasUitnSssiE35nhqdoXTN3ngkzKha8IGqieXK2SnxXJTGmRjR2keAutyLRNVzmF4b8flu21M5ik3a21NOVK//WvSbvnGPs55dyLCP+9/+X0+/Hpga2xH7XSXyOZ+LcW+ygS4rrNpF3pgl+LSzSG/1Fi84Flb70WALkw9LEVKJRedp/bM1Erz3akAEqNt2j53LG66nZo1ebBCpjKrTMYUPQXFSQ47oCayJff5pkfIzOBKTVZ6ibUYtAltc/WeY3lgysXHA22xHqDLtgCr6f32530VN28I3XuuEjbi3756r9V3lGVE+ZDcm7dMFWD/16lpO9+7aGdqbF6cirEur9zKnedE1HbFx4mXYpAvasPK6t6I//sfIY58dl5+0QW9AveEdyEf/aNdzrEmwrXqK1rS9UPS1+O1pfS56XXHYUC73vyNHhUyEfuVXYb7i632e+EAg8IIl/AZ4FqEjw9zJFeZvO1gTugGiKGJpZZnVL7sNPV/fyWqGPvdxa1NYeP3JG9af3k5v+qAwNTmzSxHDEwn5kkFl4Lqa3HlxfpJ80TTvh5uwC6+9NWO+OCpnlwxuMapbkVe73NLY9gxBFMhWI9xChLRmdCBSuGjGvl2lcB2DtHVjlDV4od4ls3aiQb5SWLRMTn60zzmeLZvZUczKi/UyyptdLZ57u3ud7RIF7cD0/CaDWdNM0c3vKZhppQ8gRiGJ9vm5myax2keBz8QAsbdcb0IJkM6eHM+9+DA6ibDW8vgjj/H4I49y5dJlrly6zOnHnuDRhx4my7KZ5QNfHJIk4f3vfz+/+Iu/WC6KiAg/+ZM/yate9SrW19dvbgcDgUAgEAgEAoFA4AXK1vY2l65c4er6Os7VF2cGwyH3f+EhHn7sUc6eO8fpJ5/kcw/cz8XLl2bW99SF82OhG78ouevC5MiWu34QnY1FIDEREiXoifzE2mZlfliPYrB8jLTtbX1HdrnOFI58TcZ0bhxTXSyITee6nfzZOZ+zu3iVdtCj/jSIol5ML6I+tc8nbpNOrbWmVSWFoCcFsSbBrQE5fd+e54xwF57A3fcR3KOfQXaL6HymiVvQ6j7tapyJcTqqR/XrSv7mPagJ3UX5mWud18noaWusVyDaWScebBMPd4gH2yjn0DZDi0WLFyPFxPUnthCLJ+ucakMpoB5V7fXHBnvwKctw5S2sJ+ur2og3LjKOhWqhYsM+6m81AltppoTtqZ9HY1h9Td8PXeTQHjk46Inc3NdyB1Xj76uGezjRz6a49H1TS6cA85ceRad9AHSe0tq6PL5vRUS2At/PpUPYky/BJl3ypEtv5QRXb3mVF7oBnKV39hGUiH+2bIbeh9ANIINtiJLp4yi/kcHEOKXHv+PFO8Rqm/mNGqN7MZILCtt0hRSR75XFYpvj7v0g9sO/e31jGAgEnjfMkJECz1Z0J2b1W17Jxp98gezsOCdFdLDL4t+9k+jA05/0jWiKelWZoHJBWqoW0av7RQ7xiijcJKC6tiY7EJFcyMbnimC2Ha1zKbajyRdMmQtaFOTLhvRIhNmSUpgdvWfntY/6BnS/2DkbU5sgYQQ7r/3kZTie2oiB9GCEXfLl7ZxGlEMPKucosF2DrCjiKzm672rvSax9X6VZLRZ8PvHN13SZe2hAfHUcxmw7mt5dbR+VLwIZKOe86D7aDTx0dB4ZEF+y5AeieoS0E38/Ru1mgHK1+6IyIV7LUA7SAxFSsQ5XqfN50YsNjCr3ebBruws12LbxE5ueKzce+IkmmL7A5YxsJRrn7xYfka4KIdoMHFzJyZaj2j1XuWDnDOmqEK/n9bqNF8t9RxVSPEzVnZWuo7AL2lvS5/X3JIJ06P/gO3f2KXa2pzdeDAYDzjx+mhfddcf0jQt80fne7/1e3v72t/PGN76Rp556CoDPfvazHDt2jN/+7d/mHe94x03uYSAQCAQCgUAgEAg8f9je2WE4HBJFEe12m8tXLrO+uYk4odNuMxgOSbOxJa7RhhPHj3FgZRXnHA8/9ujUBnLnHGfPnSOOYlaWl0mzjMFggDGGJI5ZX1/HjKQdEcysaNgRSkGeg/YChz+mibI+eWFpDD6KNcqHZCZGtCnlJWUzREeINuW5w8XDJINN8rhdtiHKoKRuO6cm7YsbImIVzovbZYTrKKq1KFKetztaHCobYONOTdBzUYLZI7pTjeyWqxGe2oDdY3P/PiIgZeMy9n3/B3Lh8fHBzgLmq96Jvvv1e5a/0SitUS//SuRv/uy663DaeLEMf3+0s5R3qIjU31t4nBUSMnG8iLq+FnwNunZ/pLjHo5qSwSbRcJvh/MHxxgZtyJM5ouH2+LlVCmdMYSFNeUwKm+7RsWrPq+chGmHyvGL9s3ZdlWOK2mdKatHXas/xFcBFrfr1KzUWaP2AFP9Wf39MC91+IbHynJsI52xh1X5tQva+EalXrNSej1N1S01ZzNk9o8qb7kc82GLp3ANsHbqd+StniufbP0PViGwFqFtewlZnlTSZndd7eP40C9chxKulQ3D3l5ZpB0bR67XfcSIoZ9GjiG0EnfawRVoGf9Cna9BQ27wk2vhrqjwD7rN/gbvrb6GPveia+xsIBJ4fBBvz5zD55R75eh8znxAfvb78FC6zbJ2+wnB9Bx0b5k+u0l71+TgG/T6PPPRw7Xzds4WQ6a2xxahSAHfd+i46F6tSiJ6k/diQ9pMpYkAPxUcfFwiQvPwA7o4FLm6v1QR0nKBT8ZPSiihMLsRXbTlBE+Pzh7s5jUqFaMuV5VUu2I7GLs+wRi/OAZB4YmdgLujUoXuCdpVJq61fA4ArtijnCwY3b8rxMz3nx2bR1Mor6//tPjzAtTXK+k0ApufKul3so8ztgp7ejKB8ebORe9HagS7uzUgQd4nCGT/5rNqWq8wL2WK8uE/h/oNRSLFhEhGwoKxAJn4Om40nxa6tfP86ZjwZk/p9lVbRfqxKkb28rwOH6fvrrU58GAnZRV0uUuSWoVe1AAEAAElEQVRLBokU0hpbRjGa32jK8kff9lIeO/04u/2au/3OO+jO3bhNIoGnh3OOb//2b+c//af/VDv+Xd/1XfzKr/wKOlgSBQKBQCAQCAQCgcCuXN3eop8OaMUJ80mby2tX2NjcRIBOu02/P6gJ2dfCHbfdTpZlnD775MxzjDF0O122trfKY0opr1kX1rlTYvIMVJGDVkwMSmGG2yT9TURpsvYCJu1x4rPv80siJsHGbXQ+LOu2UYt0bqW0y436m8xdeWIcvQiYtI+2OeUihUhhm1uxNx4FJVSCK0Y5Zm+UaGajFmIqcUn7tCTP4/Z4MwBeKDMTke6TqK/8B+g3/Lcz35dsSP4bPwFNub2Vwvz970efeukePbvxyGAH91v/K1ye/fzNwmoD1aj3Ud7fWgO7WJKPToHaePuDPjp4aqtDg435XvfTB5iY6bJSj6q1Jma4cLhWVmd9v0GiUlbnqY86rjy7ooyPoq33drp/IijqIrPvny7eGx0rPiMVe2zlckTHY+Ha2T0/985EWBMXEddSfu50pZzXk+t1lCM7Gd096lP1+ibyR99IROmpzzAT0eIUAnQtaMdE2KhVjJ3DZMMyUnx/z4tuWOOe+Hly7OeW2Hj5W8munJtdudYcOnkb8qH37NGLCiZCv+t/9Rt2fuvfwdo5stY8Nuk0nq5sXm5AGJEnnenfhYPtqXQVxma161Z56jfjvPZt++9vIBB43hAiu5/DRAe7RAevX6QbXN7i/F8/jMvGqufmIxeZO7nK4dfdTrvTYW5+vh4VW5wqsUINHLqI3pVi514VlfnIY4mnv5aHJxPmzuWwPW1/pBLN0lfcjl5MuPrAdn2nsFa4wpJcofwONkDn4+mkAi/IDwTXoRSuR+UlGe0IpHmGWZzTSKRwkUEiQW1UdsQ12IQr5yOjq9fvugbXbdgAMCpuvJDbujgeF1XJma0zL6or8GL5JMZH3JtBZZJQvfxU0IgXnKubCEZz8ELMHkWHjyK4/ZsKIryQrhyk9TE3A0EPhLywL58aD0ANffu2o+vta+XHpq1RWY4e3bPqhsjRH5Z2PLZU32sYjq3LG7sK3QD9Xi+I3c8itNa85z3v4Z3vfCff+q3fyrCI0P/VX/1VPvjBD/LhD3+YU6dO3eReBgKBQCAQCAQCgcDNYWNnm2Ga0k4STBTx4MWznN3wguSB7gLpYMAwrURko1jQMYnyfzSn6fWJ3CMef/LMnn9nW2trQjf4SG4LIN4geV9iU1VIdhbRhmjoU+6NIpqXn7pvvDYhDuWyWt15ax6bdItc375OF7Uwab+IiFbo3NuL67LZSeNjKYRMAC8qKShEtCbr4utDOVsXeEbWzbuMt4zOq7JXVOjcMupVX7VrX+TBjzUL3eDH8BPvuylit2rPob/5R5BPvG/PnMCTaBFqd2of41vFC6/KR1oDKO2PjR4Xo1GqEpQxEZE9aqsqiTfh400sqPqz4FSEceP1QmMzov4GeXtxLGTrGJNvYaOkIm77FdRapLlSOBNhqrb0TWOhlC82ebz8jBQ/jspX83frqF6n7P25VzYnnmWVX244Aaj3dXSlMhl1PupnrV8a5epODjcKGV1v2d50qoPRRoHRc6Dwn32V9clNCzPahFDYye/1+2UUhHTNOEty6Hhd7BYh6a2TbF9GO4ssH0HOXcvvN4V6y7eh5pYA0N/6P2M/9ifY+z/mUzsopjYfiDY462opLXSeYkepHcA/h9r4+1Z5hkd9rt3fP//PyJHbUCfuuoZ+BwKB5wNB7H6B4rJ8SugesfPkGusLbZbvPsZwMGMnqFLk8xrT94J24ymA2bLeHjwZT3harRYrx1e5mJ9l7v4+8eXxLsps2bDz0g5zOqWV65k5lfXAEV3NyVaimfmylUC8bnENqYqUBbNpcXOmUYzfC0kU+ZLGbLtahPTk9WOBa/ybJz2agFbElzJfd0P3TN/vLrZzY8v3EW5ee8ej/tjyfRJt/aRKzPSuR91zuDbje9bwF5LEyucBn5h/KiDasNh5yk0Jje33Ha6jwEyI4lqRHoqIr+beTr7pvhZtZNp4y/pd0JP1N6BCpPCzkm/4hm/gySef5E1vehMPPPAAAGfOnOGOO+7gl37pl/jH//gf3+QeBgKBQCAQCAQCgcCNZbO3TZpltJMWkTGcvXyRq1uboBTznQ4bOzv0h+N1mlwcV/IBWbHwsDHwUcBLJiEuxG2LsO5SVnWLqGp1LdKYvm6SSSHF5jlX7YB5nRCra/972iGYfYqLylUXHYS4v4GuHFt+8nPMX36iYkGuMKklyvoocThtyKM2ce/qOHJwFM07iugVfOSpw9viMoreHgkp40UdPxYTiyQjMfBaBmG/NOZIrqMAkw29uKnNODJZ6fJ6ahw6hX7HP0F1dneIdE/sntNbnnwIyTNUtHd+8BuNanWQlaPXXnA30bAiyE5GCQveMr/ciDCKuB2Nr8I/Q1J5OpQCZUAUUs1zXNpa72ezx8j5sCitI4adBZKd9VI0jvIharBJVhG8lQg6z3BxMrqSCUZioS7k1n35bE8drNU76qebGGOpRM7L1KdnVs9m9KMuas7ubCXSl6buPyOf1sLtQfBbKvT44KgX1c9y9Tmo3LdoIiq/rHd/rTcclolzKswt0Tl8gt6jn0PSIYhj8dyDJP2N8Tm9dXhqz8ZL1H/7/8SdeDG9Bz6JSwdEi6tEW2skvatePMfnY89bc2ML/lEu+crmJiXOP0uaUvAuE2+OnoPapRWfWufXy+VTHwhidyDwAiSI3S9Qtk6vNQrdIzYfu4Q+0iXP62qmxGosbmuFnfOiZ5n3eaIeBUQ7DunB4ZedorPQpd3pcPbMk7iOZuu1c+i+8+JnS+Hm/B9jZ8+cxUwKlYXVtR6KL2OhdSnHGcZRwpPR5Q70kMbve52D3rC4yOfPpiLI7wdJNPmq9jbhqSa50hClLhD1HFln9h+Aqm/RfSmtzgHSwzHpwQjddyQXMjpnp0V/0xd031uWu7Yal1d+HF3X981sW59be7LdwjZdIhCtyghyH6XtkAFg/NhMRWorhbQNktoy13btmrcssg3ZkvH3ZmJYFT7HuusK6Ik3jSI7GCNWUBpaT2Wlg0C1jfiqZdjR0+ULdGxYueUwVx5cn3qOx5ehWFycnZsmcHM5ePAg999/Pz/4gz/Iz/3czwGQ5znvete7+J3f+R3+8A//kCgKX2OBQCAQCAQCgUDg2U+/1yPPM1qtNijF1cuX2NnZRqGIO23Ob2+yM6wHHFT/Et7u96bqjJTmUNThQt7DjrPUsmUzVkw9/VlPchZVUv6slOJstsUB06Gtx39XRSjySssKHx0+OiaFYLXtUpZ1a1+C+eQ1VUWNmdi8EMf8mTrtEw13iohuUGKZu3KGaLBVCn+G+vKDthnzV8+Qx23y9sLown1OYFQ9H7bWflN/TRxS0xJSk7J9DdHBuzIStytRoW5k6byLIKnEYbIBNmp5u+eyLyNHxPG6jGp1YGH16ff1ZjMr+ncvCgv9ev7nSfNxRdUWehR5K9qUwhzKIKIKa+iCxshoTWmTWe0Ge4u+9bhpf8RFCVlngaS/Wbyj0M6i89TnNrbeuaHM5Y6qifwCSHXTi1I1i/PqOO1G9Wwp29tDjC4Eyr0i2/fNvj93e8vFedQhyvvX3RWvaY9dH6QY+11ldzWKut+lr7vk/K7L2P6ZFV3koiwt4+sN1sb+8ln4jR9n5W9/BxtPPk7rzH11oXsPnDYo52q/m9LPf4SNBz5db9XmLCZd9GDLf5/YDN1bJ+0sIdHoO6m+lWg0LuJcue47up7yt9tEdH7VIl8und73dQQCgecPIaTxBcpwfWfX9+0go7e1PXVckobptVZIpEZ/sTTWt3homZXDB2h3fH6OQW88gXAdTb4alUI3+J3C6bBirZUL8eWcaNOL3aryfaatz/ut0ua2FeBm6GECiFFoR9Pcc19IpHBdje02f5xUz6GyGbtHnRBtWkzfoQcT52gvWg9OJnXL7mrd+Cht03NgJydN3tI8W4xmli/+avX25A1vKQuq72beV9vVM//ckkShzOi5aG56lisAAC1vbT48Eje2oQT0cPau3OWXH8dEhsNHj8w858Chg0RxEEuf7fzsz/4s99xzD/Pz8+Wx973vfRw5coTPfOYzN7FngUAgEAgEAoFAIACDfo/trS2yhjzYve1tHnnwfh77woOceexRHn7gPh6+//NcuXSRQa9Hv7fD5pUrtIbpdS3SaaVYNa3aMYvQUgZdkTpSmV70yBE+n67V3lNKEdUkGoVSClMcG0WRC5Ber333XgL5KDewiZHIv1zSxcZt1MgKWWmu3PllbB59caWvzUTZAJ0Na8eciackN5mMVK9G1VbbuBHCdgNa7NhefSR8a+Ojikd9nHqNciV78X4k5Koy33hxHcpbAstTD2N//d8gsyzKR3259WW7vq9OvvimRHWX7Z+487rK6XyIdj5HsBaHnngK/B2XqShwLa7I6149uRAWJ5haBlN6fE/hmgJtqrgiEtbGbUSpUuAE/MYNEaK0N74O56byckvNZr3S05E4PrJfx+FzdY+im1T5mtzgMv6U7O1E0PSZesaZ6FJ/6Sj9paPl4bSzxPqtX8LWoRddnx04MJkzu3yO6ift8XOly0pho8TnAAfS7jJbh25n69Ad9BcOYbVBtEFM5P/VBmciRBc/RwmueE7GzTX0Kh2gP/gbrLzxHXR2dv+dMIl2lo3jLyVPxqkh3cUz09diIjaP3o2rbKpSQDwstIlGq3lTngcUz3Gl585WHD2Kn20lUKwV0lUGAi9EgsrzAkXHDQmOJ89pipjUXtg1m7bYMut30em+EG1YJFLYOQ2FNbiODMvHD3Lg9mP1asze7ZeIEF/NpyKIJ0kuZbiWJl8245zTGrJ5b6Nues5bY4/mcRpcrCAqvi6f5taPbNUgEZhtV/ZVAExhDd7xkfGjMVNDP2Y6B5zQeWRAejgmW41Ka3KzbWmfScmXDGbHodJJmyD/ElO8tI9mH+10EwMYhe1q9MCh8speQl3vj0TFJkxbKR8rXEf7jQB6Ogo7OxyTHYTkfIoZFH+MKm9h7jq67OLImWdyHje6VrNjyw0Mgt9AMHqG8hVDP27ReqrShoZ8yfi85cVGherk/cBrTrF0pxe5Vw6sorTm0vkLZW6yKIo4cPggBw8duoY7HLiZvPGNb+TChQu87W1v46/+6q8AWFtb49WvfjU/8RM/wY/92I/d5B4GAoFAIBAIBAKB5yPZ1jouz4jmFpE8o3f6IdL1yyhj0CtHWMsVw8pm/YWlZY6dvIUoihj0+zzx2CM+Om0PDIoFNBuVXGgjWWiydAtNiiuX/js64kV6kSeyrTLCW6E4ZFpctP2ZAs5QLBmOc3mPW+OFsYVsEe1Z/TPeRysKg4qNuJtRsxOhJzkGRUdHDMXSdzkWIUKRieOgMrTUjLUhETD1NSkxEen8AUARD8fBGVtH76a1fYX29uUZV+kxWR8XVzYFKIWYqC6Q7AMpyk719wahEHQ6wEWJt8kuRFcZWU6PootLUbKyTqSoiJiVdRIpbJVH/V6/iH3v/4/oW350dj/u/lL4xJ825+1WCv26t9+Aq71+1OoxeNGXwKOf3vvkUZlrqR/BTVj9K5ejcpCKyF9GRpcnFedPPBMNcb27MvmcCWCTdtmG1bG/nkp7SW8d7WwZYa2sLYX7MlpWxEf/M2HXXuZBrne01kbtgqajquuxubswYVl93TR+7qY/mxqHOEG0IU+69JePgTbYqEVrZ42tI37jxHDxMFHao7Nx/vr6ch2bGATIOkuk3RVQYPrb5O150oWDXvAVh7K29swNFw/Rz0+ycOELmGxQRJML2AwxSeVeehcLnQ0m3AdGLY8q7MGv/nNUNiOV6W79NxEbx17C6ul7UeLGVv8N5w0WD9NdH3ui6yKdxGR0u1O6FLvBR4b7zUrFEyuCqmziQARl81od6iVvuOZrCQQCz32UyDO0HTHwrGZwZZun/uKBme93Di9y4HW38oUHHmp832xZkvOZF1ctU7mhO6dWWHnFCeJOqzFv8trlK5w7u7+kH2roiK9OWJNYqYnfKnMkl/wfXCORNj0YMbit5TeHlVtgxQujuUNVEn2LBmndIKMD8XnMzbbFDMAlyue/Ziwy651C5C4w25Zou9hBmYO0FMqCTsWXH9m0OwErRDv1fNz5vMbOGS80d5VXnBU+9/flig24E287b6nvxHTiN2BqH2lfppfRCvJJOyd8JLhWDI8nYzuZofP3atNOT/DURHnlNxoMTybjCXJxX0w6niAKIAnlz2rg0Lmg8gnhXaQU0zvHljn2hum8LCJCOhwiAq32tVutBZ49/MzP/Aw//MM/jKssGL3uda/jQx/6UC36OxAIBAKBQCAQCAR2YzgY4JwlabWx1rJ+5TL9fg+jDZ0IsiceIN9a9ycr5fOBuvqieh532Dl0e21xvtVuc/tdd/PUmdNsrl+9pj5tA/2K9ZxG0VaGHRkvInSUwaDYLo5pYF7HbLuM05kXgl8UL7JoEjZsyrZktJVhUY9tzDOx/M3wEgK0lOE1rUMYFLr4W9mKQ1V+FhGu2iGpWPJCYF3UCZHSpGJxeMH+XL7D4/lWGfU9pyIORR0WKm2LCJlYTpkO3YrgLSKIiG9z1t/sztK9erZ2DzrrT3Hg8U/sOq6iNMP5A7VjOhtgqmJ3IQTW26vf77EIWQlmuN4I9936y7RkKCif51ZNrodM2BU39ElG0d0VzLf8KOro7bP7sHEZ+6e/gpx/bHywu4h50zeh7379NV3PM4EMerg//N/gzOz1zcZyxb9T93XqmEK0mboPTke4kfjoHLrBNcFXIIVrYo6S8TYU/9/Zy/H+GdO1tbGsszRuE4j6W2hXid53rshLL2UZNWHRvt/2Rn3fT9lJwbkmoO9ariGf/H6ZsaFgqu2Jaxh2V7ywPfpd3SBQ62zAyul7r7lvfiOKbhDgq7sH6k/ZKGJ759Dt4/zV14DO+iyd/Xz9mVV6qi6Vp/Xfa/u9t3vgTMzara8BpZm79CidzYusH38Zeac5XWSyvcbihbrOMGwvgh57kAiqSN2QFZ8ZjRJbX8MV5y3Lq2MtgnK5v85Dt6C/+UdQo80hgUDgBUOI7H6B0j4wT2t1nuHatFU5wPLdx0j+/+z9ebgtyVneif4iIjPXtKezz3yq6tSsUkmlAU0YkJAQCGFsQAaMsQH7sd3XpuVud9Pu5mnbt31NXxtfG9rgAdv0ADYNxmoENoOMQQgBEoMoITTVPJx5PmfPa8rMiO/+EblyZebKtfc+p6pUOqV89SzV2ZmREZFzZLzf+36tFquHDrJ2fTaK0y5oXFt7++wqtGL1NXcQLXTmtr+yeoBrV67OzaVchEpnB4CiAVeIMC7YYavs79aVhORwWLYXVyojajWMCy/2F9PQX3lyO11S6DgtWYgrfL8l1Eg6Hdjl+6gUaCnl2C5ZkGvlc6V38UrvbLHLyHAloBJPludtFo9ftr2oshV87mzlfPk8R3cl0jIffDg8gV8gnKWlkZbGJpIrsEsbFbenoCqf7HcAYjTi3LRvinIka1t7kfmgHCzgo1B9+dVXnaAOSila7Wag80rA3/pbf4tv/MZv5J3vfCfXrl0D4JOf/CTHjh3jl37pl3j3u9/9MvewQYMGDRo0aNCgQYMGLzfi8RjnHFGrhU1T1m9cZzQaYkxAFLXY3FgjHntra5UpDYvYAky4SJfNTB0pnjDUppSnN0iGtDcuMVy9M992PBpx4+pVtrc2b7rfLaVRKAYFcjtQmg6GYUaqaRRGaSLxCm+TTWr0VECkNCKwqD3h0dGGHZvQVdMpQCfCs8lmTr04EUymrkvE+dh3FDGOgU1xCFrgih2w6eJcPd5VAaumTSezp02AJdOia4fE4tXufUnpJ9vcEyyyaKL8eIcYnrZ9Omh6ymAR+mJ5MFhifsI0vCIzbBMUVIjJJB/3LpAa8q2a89VpjSiV5cimlpCbzmtISUWdtwOgdN5eNaftflFHRCkEXFoms1QmeGC2H1UCfEb0eu38rmS3Wj5E8B3fj1w9i9y4CO0e6uTDqDnqzS80VLuL+bP/E+mH/g/ic09hwzbaxrT6a2UirLodkLR6KOcIkmG+zE2UtEW78RoVsnIpiAGl9z63WTDCpA3Z17WQWdNnrVoTomxCNNxCi5tey0WCWitEdP5sUpP+i29zN2JT4QNNSsTvLeahn70Sa1BT76SH+7pXarfPWp9DdENm9V4ISqoj5F3YRnTgz/FNYeK0UD4G1f0phCKggNZgA3PxCbZOvGauKjrvrk1K974LO/QP3kNv7ew0uKUu8KaaN/4Wz20Vw+VjeQBN2lpktChziW5gJuDD/6vaDyEabpaWC2R27dnxURrRKrMyd/k+iQmRe1+Hee9fbYjuBg2+RPHFMTpp8AWHHSeM1+uJboDBpQ06hxY5duI4YRSxdu06SVKIdlWK8R2hz6O9aVHOv3xcW2HGwvDSBtHSfLJ7OBySuKmn9q7RZHPsciTwamCEGXtt8MRt77EB/Yc7pXzg4MtLC0gkTz9zy5hnVRN4dXmwUxPhGXibbx1nxK4uDIWMwiFTxXxN3yTSWAV66NBZuUkxHQtOXE5GT0TeJUzacMyo8tVYwBW2rxkUKwfUBCEApKsBsm09Ge/mHB6Zs71S2I72OdgTmXteXCcLVkikfIws9C9t0DrQq9+wwSsGDz/8MJcvX+bbvu3b+E//6T8B0O/3+dqv/Vre//7382M/9mMvbwcbNGjQoEGDBg0aNGjwsmB7a5Nrly4xGnkSS2tdcoWqwzzTQ9vqMV48RHv72nSh0jhjMHZqXR4NNxi64yUi5dqVS7fUf8GT24FoUlyePztEM8ITWROtaag0sTiijHBQyqvADwedXAmnUaxkCuwJzqTbWBFOBouYzND4uh2xbkek2Qd2SxkC5Un1Cbo6pC8pNiPvBpIyTHe4I1jICW+jFA9EK3xmdD3P7w1w2Q5ysnvS1whNXyz9gjI2wRHuqTmsqDHTcq70OpUuKHQyxgVRptL3akGhQPxkJIpTCpOMc+Kojjiu66EAoszUahwvYBBnvQX2Hnu1L0jNRIvSOaHq/64nwGfQmj9vV4Q6chJ15OTN9/ULgPjGJTYThzv+UL6sb1MWrj1Pq7+267ZJZwklFpPGU+1tdiz90as/YwofKCFa1ZOLxbJFu+XC9vPgryHlr6PJPSwOklFO7E3IeBFbutYoBONMG1PM2FbPa3lmAm9f1PVM/2fuGHFU1d4lNTIqJ01Fbi04xFe6O1kfxAPfFzVH8TQ5vjdNdGf7UwiSmHeO645okIzobFxkcLB8j4X9dZLuct5fJcLCpadK6vR48RA2arN0+ekC4V09j1I+Hi+Chfxw4SDDlanYSJ24n7i3DFdmc3ZP0Nq8AoXrGiCIhz4HvQkQEYJkWH+/2BRBe/U8eF5AG7DlgCSxFtVu8nU3aPClihdTz9rgNsL2meu7jle2z1xHrEMpxaHDh3jw4Yd48OGHWFk9MC2kFcmRkOH9LYb3RQwfaOFaimTFcGnzGs89/SyXzl9gPCrn/HDOcfny5WwQpnzuaD2/O649Z5ijvL23KBArSM2bWlvoPTOqj1jTyquR25lN+K1GtTlgPBvNC0CgsFWivbDOdX3OaTWuDI6NV4e7COYdGQk1dinAhj4neBE6EXTfoXfs1AK9CqO83fuSJlmcPgpUZfs6ZT2AiQU1qosYVNilgPGxkOFdUVlZX2jDjAWV1G/v2hrbU75tW0+KT8qIw5+DrKrtU9fmTlQ0eGVBa81//I//kZ/+6Z8mDKfRrf/qX/0rHnzwQf+cadCgQYMGDRo0aNCgwZcMtrc2OXfq+ZzoBvYkuvdC3Ftl3FkuLUs6SwxWTkxJVZEZwvVW4JgqkMOM4Igym2+llM+BrYKcyFZAVxm08upNQTgR9OjpECsOKz6rdlSxCj9hejzSOsiJoMfRoMuxoMeiDkvE9lgsfZdiC2SeVorDpjNj/3zDDinCKMWRoEykjsQyqiipTc20ZMKUkKmdZ6mx6A5GWyStQkorpZAgwmlDru9UmiAdY5IRyll0Os7Kam/9q7RX9doURPy5MCE2aOPCDjZo4eblGJ80C2ixs2SZNiWb+xeCieJ8b9QfuyLc859B6nJy3yawg202/uDXcBXyUkzA9tEHy9dEBS6zg09bmVhiYp0/UXNPlmX/nTGnzmyTZ2bcRDzZ7Cy4FBeEJK0FkvYSSWsBZ6JdqVx/DTm0S8rnq5LHeFJ25h6p6et+sB/yc44ep76eArGab53f01NKfOKEMD32u/o6vCBIRvyHgw26a+forF/ADLfpXT/N6qlHOfT8H7J6+lMvTlBKqeHyHuXnrbC8vXmZ3rVTpXs7GPdZKCwTbWgN1lm8+lypPttaYLR0ZFp7xY6+6mDxwhRfPqf2ePEwi1eeZvXUo6ye+iTtG2exF5+fu01r6yphPJxRQynAJCPMPY8QHLtn1yABXX2u1qRmkEunbn6HGjRo8IpBQ3Z/iSLeHu263iUWO54quZVSRFHEkWNHS6QS4EnjUKNGjvRAQHIkxLYUo+GQtRtrPPf0s2xtbPp6rePMc6cYDgYUKmdiQ137utUKmfdNIIIZOTQKu2hqt1dj8WrleZiQ7rfyrhdBpaAFmPOt4QJqiXgAlQrheurzh7t6UnfXgWoq6DHokZSs3CGLNBWwLTW3fWdA2hq3YMp26YXtSeabLIXXk/p+AxL6YILkoKltXwFmw84NMtAjyS3p57WvxrPKdDtOcfHNR2E2uH3xXd/1XZw+fZr77rsvX/bss89y8uRJPvCBD7yMPWvQoEGDBg0aNGjQoMEXElcvXdy9QDE/836hFOOV44wWj0wXiRAvHGS8cAiY2qy+EAiQqnIgelcF6MxGWURoq4CxWC4kO5xPdtiysbdfLvxQkOKKMeGV3VG0aojXQGnuCHozZMO4QpRopejp8rzQUCxphYDt6tnj4WYsfWe/9kPr0OMBwbhPMO5jxgNU4byJ1gwO3MG458UYwWiHaLhFvLBK3F32qthJ29ogOsjyXPsWjY0x4z4mGfv/jvuYZIROxxjrc75q5xWzUrSJVjoj0Pc+z0rcLCGt6uesbglV+7zqvErNPEtOkhfXPfkJ7Af+f7ct4T049TiSzrmnlWK4crx2lVMGF7T8vzPyWQr3ns/VHUyPc5G4nfysRdsUnYzRyQidjH1uZJt4sjq3wFdTMlcbXNTBRt29SePaXPA184O1ttU3T9fO609xuSjt7ycqx6Xa/GTLLIe4KixTBb389PhUFNm3SDdL3U9pRBlEGZwOOXDuMyxdepLu+gV6a+dYufgYnc3LeU7rGUL1ljoyJ9CksFxNelhY1urfoHvj7LSMWMLRNtGOdygw4z4AUX8NHZcDjMYLB30z1YCIQsqNST/qzDe9m4Dew/DeQ4tj+dKTtPrr2fMyJTj/JMtnPk0w2p4p3zpxLwuBnntdKsBojRrOblvu6D6CfILGxLhBgy9lNGT3lyhMtMfDXyl0OFsmDEPuffB+2jbISU6VCsGNFG1BWrOXlIhw/tw5bGq5euUKgyLRXSo4O5zRQ0d0PsauBCQrJs9NjXhy1+y4PHfz8N4Wg4fapAWVcrqg6b+qjbT3uNTFE+IqdlPydjd1sHjFsYrJLcQlzFTm093xxj3O74dKCh8VTjBbluh87G3MraC3HFjJSWfBE9W2q9Fj522/C9vrofMW8gISgBiFbSlcdtpE4Y/ZQoDZcZktuOTrbMsHCKAUKpZ8t0o7kOXmdi3liXHK68xIaF2M0X1bqtuFPgDCQ5EcDLAFhb5osG2F0mC2benYqFQwOxaTBSh4O/VKBKn1yvNSbvBJa1qhghcnYrrB7YMTJ07w3HPP8b3f+735siRJ+M7v/E6+7du+7QWrORo0aNCgQYMGDRo0aPDFja2NjRlnuSo6W1dpb96aA1S8sIrNbLjTyKuWxwsHPUndWijnUb4FJCicAovD4nK726GkDLEMsdywQ56ON7hsB1yxA55Pt3gq3iApWFgLYDOV980iUJqFCpGdIjPuaVGNwrlKZKeVbTSKVmW7jjK0C8sOOFhMht62OYMSh8mIRGFq7xz3VlE2YeHas2gbo5Mxadjx56iorq3Ro2pxqIyMnChpTV4+a5d60rpE9u2CGTXlLZJ41bMogLIF4UCmMMZVltX1CWYJ7/4m7g9++ab79cWA+PruqQKSiiMDgEMR9w6UiLecIHTO/wSgcA1l10uRRvUKfn99+TMr/rotEZqePNW2YrNvwn09L2qvoVsgsqsoksGFyrOVRTX5ZM+YWo1n9tF7OSqqwq/SQk1vXjhk0l+tC79CwIpSmWLeltTAL7qK+yZQ13Zr5wYqjcFZwsGWX5bZ8Xc2L+XbRcOt0nZiQiTqTPdNHMomaJs5BOTXpuQhB/55qvOAIDEBEoQ4E+xfwV+AFuuV6BWYzgKM5qdSBZDzT6NuJWCseh0GLdzzn735eho0aPCKQBPucptjvDlg89RVRms7KKPpHV9h+e4jmNbup3bx5EE2n70yd33v+Ao6rCcMwzDkxB0nuPSxp324hAO0J5vnQZzw9BNPTgknofxmrBkk6R1L52xMuqiRUEGoSNsanBCupYSb00GfbXtba9fWpCvB1Pra7HPY4rLuWFA2M/8KgHDO9gnowveOBOTqdL87WftKYXZsXrfvlxBeSzHxdJ/12KEBte0Y3hv5fiu/fbDm8/soK1kKpsxivNC+65rcGrz/UAvwBDFKsfTJvt8+FiT2w5rkWADBdHBnBs733wgUxuCKLD+29rbqkkUimkm8gvY5wltXEk+gtzWj+9qFAyOoVJBA+fOSBwmIt11TCp2C3p5+FpfcdhTehl0pML4+Ugi25hOXvTtX0aaJ4/lSxb/+1/+ab/3Wb+V973tfHljzC7/wCxw/fpzf+Z3f4aGHHtqjhgYNGjRo0KBBgwYNGtxuGPR3uHD29J7lRGl6a+ewQYskUwbfDJLOEmqwnpNoEkRY05qrIJ3g5D33cfb0fItXB1ityoSx8nMLxdmSBRNxt9KcSbbzsiOxnI63ebC1UqlT8tzeN4O2CtimrJadncIpz+EYFEFFT3PQtNm0Y9actws/bNp0lCFF8r61lKalDBsuZuhSTjpNKdutCNFgA52OsEGL4cox2lsbhKNtJqpI5SxBQeXowjYqGZUUmpLnDC7kezUB2CTPfwye3BapKBCrOX4zsu9W8vreLLGXSQJy0+cpeejAJogOUGKnJcTVCkmKmARRlNp5+lHka7/71simlxFqT+J3euQky6OcRD1MOsYMNkDEL6+oXwXA7UEsV1Xfk8WT4JBifmqbgIlKy5wJPRG5j/7fFCaBHkXF9MQaXAr7qbTf/3l29yULd5XniJ4sI7P9fzEg+IAD0QZE0DeZ395BOXd5sZ9ku1NarrPc4C8DZua/s6drnppCCEfbmHSMzoKYtE3orJ2n1V+fbqUUiMPEQx+4s3SI4B3fhvv1f8ecMIa8Nb+w8oyTyvUSRPDAm1GXnoXNa/vevSAeYMZ97CQ9ABBfv0hnL0cME6Ae+DLkyum5RayJEGXy4+L7XbnWB5ukH/rf0W/7kwRf/qf23e8GDRq8MtAwQrcxdi6ucf5jT7B97gZJf0y8NWT9qUuc/9gTJIPxrttGy12W7z9au860AlZfe8eu27ePLBEc7qIyklgC5a3Ad0FJWSnUDAgr5XuadMkgUeUy1Ypk1SuF87JRZWuj9k90w4y3lwJUylyLboLK0KG674Voy2LO68mHiV0pW3srN10fXUtzoptJPyrbS6tsXTSxeVcOWpfTnOgGryovbq/BBwoUP+gmwQHKW8bn7UD5OGZRkq6lphVOVgkEQ0ewVhiszwwolSfZa4II8o82qS4sty+hKp37IiRQLD90rHZdgy8dvOc97+HKlSu8+c1vzpddvXqV17zmNfzoj/7oy9exBg0aNGjQoEGDBg0azGA4GHD+zCme/PxnefLzn+X8mdPl1Gf7wKXz5/dUGoLPgQrQuUV1tzMhg9W7vGoQQIT+obtxYTXoO8aM/aR/kAy5cu50bZA/kNuXa9QMOa2VIqgsa+uAVVMWGwwkZcfNEtS3gqpCu06P3NFBSaV9xHQ5oFs54R2iOahbvKV9hKOmw4qOuCNYQGX7EypNS2lCZWgpwyHd5iABQdAmbXVJW11EKZYuP8ny5SdZvH6alctPcfSpj9HduOjVss6ixbF1/NWMu4XABaWwYbuUX9vPNcjMOajPgexqllWP5t7zTVIl3m6SXJsQ3dP5pfLWCkG5pGR1XXeu6iuv7E+a+N9thtaxu8sLnKW1dZXFy0+xdPEJFq4+hzUhLmx5C/ogIrD+3tQuRYvF1BCruZ55H8+UaTBCATXznUrKKm1R+5mSr15DkinPywEayhbye4vL7sJK/5ViaqU/JbLzIJBdiP26e2B//d8P/P2athewUQfb6pL0DmCD+YKqEg7diXrkq30v6yXr+aoiRAez9+jLBKko9qOdG7Q3r+TPLJXG9NbPT8vjA24Wrp+mu3mJztYV2ucfI/7YL/jTSflXREb/zzgQUOOGqO54AHbWZ5bvBZ2WnQxQGnX/G6d26TX3jJgAjtwNSwdr6xQUtrWAjbpYHfqgiDTx09+l/cnCgf7wV5G1W3vPN2jQ4PZFQ3bfprCJ5eqnz9R+vaTDmOufP7dnHQdffxeH33QP0XIXABVoFu85xIl3Pky40N5129FwyPayJT4c4ELlydJ9DQI9/IsUTybP204pxneEpL2ay1QrRndFxAcNLiC3Mr8lzIT4TfuoxjJViVfal5YnmX3E5/x9lxrSXUJFcjjAdjI7oMIuBjuO1vkYvZMR0nV3aaBwXeXty5mS5QDhuqV9JsZk288EAgBmKETXUk+EiyBFsj5Q5TzjNfsmocK16j+eW5cSWhfG6JGrHVD67fXUkr4OxQFqzfXhepp0Qeckv2hIlg2juyLWdjbm19vgSwYLCwt88pOf5Ad+4AfyaG/nHN/3fd/HO97xDkZ72Bs2aNCgQYMGDRo0aNDgpcfO1hann32arY0NnLU4a9naWOf0s0+zs721dwX4+YnxaLhnOZ2MiAZ+4j4Y79zUHMYEaWepTGwrhYQ1pIzSTJS4OIcdbKOT8SxhBCRK56SLKuuafb/V7LJlM9vmwL04ZKV1rkS6d3VAW02XGBSLOuJksEhXBRzQLU4EPZRS9FRARxl6KkAphVaK17UO8lB0gCUdckBHrJoWyypiWbdY0CFdHbKkQ+4KukgQZsSbxrZ6rN39pjw3N3i78db2tTKZojT9Q3eXiSulcEHZJjoneUoLdR0vVsKtBA0IPhe0yxW1MmtJvR9Ug/+rq2+hb7UbLq5CtPs84BcjOve8Gt32ClJlU5YuP0134yJBPMSkY4JkVFYkgz+OQYjbF1m7j7nOWsJ076tmNh93ffu6QGQrsejJZNmECAWf39smYNP8OispuAsq7Rli+wUSvlL53SwUQjDeQSeFORqlPfm9n9QQ22tw5rGsrsJ+75fwfin03UXVf83144/VNHt50l5k5/B9bJ54DVtHX4ULopLZuBaH0ybv/2jxEK3B+sw15IKIpLN0Sxbkdde6nH189v7ZB1wlUKG1chB37glvk64NYryKXwpPZbt1neRD/zvqTe9B3fNIaR+cDok7KzgTYoOItNVDpTHKpSib5L9q/+0Tf3DTfW/QoMHtDSX7CX1t8EWHzdPXuP65s7uWufvrXkfQifZVn4jsw/7Hw6WWM08/z6A4EKlY9NwsqpZYN7v+BbU/sdWeV7Vi95zfGWkvkartgxo7orX5bLwaC2Y7pX1ptoyAJ7R3aV/F3o4rPTBrCSOAGViCnfmD6LTj+62Teusi29G1udjB26+reVWLD4hOjgQ+N3ht3wU17wnkBLNpSY6G3kq9vgnSZQ0F23KtNQ8//PC+r+cGr3x8+tOf5t3vfjfr69OI1MXFRX7t136Nr/iKr3gZe9agQYMGDRo0aNCgwZcuRIRnnniMNKknacMw5IGHX7vnt93O9hZnn39u1zLKJixfehKTzWOIUqzd8xZwFu1sFoQeoFyKdtmkudK4febWndemqSjcbBCV6hMgrpBPgmArdEUqrmRIZ8XxdLxRKnNH0ONQ0JkuEE9M38y38dhZ+pLgRNhyMUZplnSIUj6tmQUCFEGmRLcIAYprdkhfvEJ2SUccNh3CApm465yTCNEuqmcTDzn8zMdL65NWj3ihrABcuPpsyeYXEcJxOU+sTMi+Qhllk1LdTpmpcj8rI0rnpI8AcWeZIB4QjrZqyXEXtLxSEcBZTBrvk9ws10OVkH2RrJfzuieOgF/1rei3fsOLUPMXHml/i60//m3Cpz9RPv97QdzM/VlbjPq5vmpdxRICJZJQABu0S1bbetz3+aP3QbdOciurgg35nvOkk36oir237JOWViovmxvoF63ZJ3mga+qu7VcQ7uoeIJDlUi/k07Yp4XBzn/upS9vme6gq/8gCBKSwj/qWUhLMwczxqOkrOn/GCDBePEy/6BgCBMMtFq8+N6uBfuhtxFfPoUb9uV0IBpuYPSzy654vUrGCV/e9Aa1Annp017qqsEGLncP3kXSX0a0ui5efRG+v1XTCE+wuiHAmxAUhWinaf/Zv0f+5H0W5BJTBmYC4dwAbdfP+mVGfhRuns5QW031yJsrvPf3QWwm+/i/dVN8bNGhwe6NRdt+mSIe725QDpKP9R/XeDNF94dFnGO5ULMVeILGoADWsfs55SOW/9RUoSOZHXKrRnI+KLKe0UhmpXVuG+ZGc2RhRKYUe1LchkcLWqKuBnGiXlmF8dJasVoALFLa1y/Yp6FTQg9koYQWIqc3AA4ALgECBlnp1ulJe/Z3OqWE3RX8mSg/X07nKd5W4+u1FMANvvWS20/n975aJbvDqXWtvIWK6wSsWb3zjG7l69Spf//Vfny/b3t7mq77qq/j+7//+l7FnDRo0aNCgQYMGDRp86aK/vT2X6AZIkoT+zvbc9RO0WnMUqc569Vca07l+ljTqsXPoHrYP38/OwXswox3CcR+TjAiSEcF4B5OMvEoSr7w06dgrsm8BXjVYhrJlUkUBs9rivZHUEKcrFbX3WCw7kmL3oXEREQYuoS8JAYqWMhwwLRZ0wEgs2zah71JEhJ4KM0V2wKIOcQg7LmEslpFYrtohT8XrjAoE0m5zTntZb9uoQ9wrE9smnnXqcmYfYo8ZaafMkJRFxeFEkW1sjLKxD7hvLYA2pO1F0tbibD+CaEp0Ay9mbuMXC96W2s/HqAfehHrze17uLt0ygt4SB972HlqjvZ8VJdSo+veF6v007/4q2I2L0mixPs97Zkutc6J47/lUr+4t5xXfzyzsXqKinPaeENfFn7PeIl28sliJnT4bYaoSLzWost5WEITwZ75vz76Gw+3SM1JMgCiz53kqXs+lZdW+TXJ4V5bfqgpQlPJqY+PJ2v1Yu1dtxBXQ3r7GwvVTpXJpZ4nR8mz6UX3/G3clusE/g24WtfPxIvDIV8NNBnyZdMzS5adodTosHzyE2l7L7MsngR8t4s4ScXeFuLPI4MAdbB97kP7h+9g+dC/rv/sr2XM0wmnDeOmwzwFeeI/Ydo/N468mjaa5wRWgbTy9DpYO3fRxaNCgwe2Nhuy+TbEfxXbQvrXo492wfuoK480B6gVyiXpgPYHqBDV2hNdTJNCgp6RzPuiauO3sVqEI4aYlWLfePrtoj26F6EpKeCXxxK3LiN1UUGOvLBbwebAjhehC+8YvR5RXcBc75vxPTdq4nBBdjP2+TUjgrB1paWxb53VP9lsP/EDRhYr+I122X9chWTGIAdtSDO+OGLy67a3FC33DCSp26PHEFk0INizBeuqV3lm7Zjsl2HJIAK64XxpsW3nFtFKoBF/XhHye2CFZQVsIt6wn8212zhLBbFvMWFAx0/2V7GBacsW27Rj00JP6+XlJBd23BNuOYNOixtPzomKH2ba50jw+GmEXtd//7NpwoSJd1LgaxbvWGmNu3manwSsbQRDwa7/2a/z4j/94fn2ICD/0Qz/Ea1/7WtbWaqJMGzRo0KBBgwYNGjRo8JIh3UeO4Hlk+GjQZ/P6VXbW11BAFIXgbP7T4wHhaIcgHhLEQ5KFg4wXDuaKWwkiTzYVkJM4FfJKu8TXe7NQqiYndB2lUJ7tmDFgFNCVMks64qHoAGE2rXfEdGirILcfT8SRIjiEviR5nfOoNaUUIZpl3WLJtFg0EQdMm64KseLrsQgDSblqB6SFY9fTIQ9Ey6U+pgjn0p2alur2fm+qyVat4mt2omSDDLO2tiKebJycy4q1uFcFhl5dqT0RqpzN+6edJQ07JSIpaS3M6Fhn7MprroN9o0pCFuoskne3AgWoo/eg/9RfR91q/75YMNgC+yKqczNI4f9LS0vE6qySOad8RbxdenZ8lTh0MsKkhQCaF0C27oWcyHYWXAouRcRlynM9vdYzRbGq/Kr7hNjyPVVH1tctSxP44A/v2V/lLMG4X7pHy7nGd9l2useVPk/XTvvHC7p3JtWKMpnrg0a08QplXQx0meMAWmP63uqvY+JyOo7xwixZK+eeekH9LldWCQ4o2K4L4M48TvIb/ze8+7vhwLHytsfug6P34LQhDduZzbpitHCQ7SMPsH34PsLRDunjv48NO/kvbS2QtBdxYRsXtnCtHiYdl56baRwzWj6C0wE26szYoufQhsHqHaVFiuwZrDTmNY2TY4MGX2qYlZI2uC2wcGKVG4+dR+YoZjuHl/ZtYb4X+lc32Xz+CqP1HVz2jjYD51W1twqlaF+afrS6UE2tuqvjALe3pY9KBOVAOdBb/gPARYp0xWD63k7IjAQz8oNf21PYhcJgXvs+YZjNsV38/i3IzIulzMBHWJqhwwz9BsmKwa4EqNTX7RXefh+DGwm64JZkF/3y5EhIcqQcpNA+Pc63l+yUBmtpOU95Rrrn7Rc6Zyf26oY8x7i0FBTydOekeZoNuqqDMYFg6GBYWgQ6G0ikhWVBuYxrK5Tgye4YP3CyoFxmYS4Q9IsfbYXdCpU/NkrhOgo6WRs1edAnWFlZaSzMG8zFX/trf433vve9vP3tb+f8+fMAPP7445w4cYIPfOADfMu3fMvL3MMGDRo0aNCgQYMGDb40EEVzJrBzIkmhjeHalctsbWwgztHqtEn7O8SDIpGqcFqXCDsJIhz4fLcw/cbdTwq0CQFQKKdtgrsVQrCaA3XGllowdoQL2nl7Oy7FIXR14PN1K4gwBCKMsLmN+ILSvCpaYd2NOWa6vssoRBypCG1lMDmt4u3Gdda+iGRx6tP+hTX719EBR1WHi+nU3S9FWLNjjhQs0yNlOGhaXLNTwrkvKSOX0ta7Tz0WTIXnwiRlEijuHcCaCGP9xIpOY8Lh1tTaWcRb1osjp+4yq2nlLE6m+XAn8ER34RhkedeLCNIRcVSwitfe6n7SD8DbO78QFK7VuTRo8TrO7aZvAVdOQX8TFlZubfsvFnQWQQee0J2D/NrIF8ieqnuVF3V52XxZRmbv/jSRGvXzrhu8OMiuDYXve1kRLv7+F1W6hkQbr+berVpAxAKmfP05V2q3FvtxN1DKz20mY2yr63MyT+qVvZ8T/pzW11sp6AnRF3Cr+meJf1aXUlNogxM3E0w121c3c22Egw1s4fnic3dXdilsoZYP47ZuICivvq/uSBbQsOe5JBMsZQEK/vxm2cJN4JeP+tjPf4zoL/9D5OKzPrDkwDFcb4XtD/1fjO85Mr03nCu5WsQCauEI3ST272Ll+2viIbbVyfdfiSPqrzFePFK4rjRJZ2nP93XcPeCPQ+kYCOZdfw61tLrrtg0aNHjloVF236YwUcDCkZX6Aa3AysnDL0o7G6eucPnRZxne2PbEetaeTgSzc+vybtdW2AJZLi8wiLROaa5iQQ8dys4eI93PlMZ54Ztvs1RrzXg6VyzXIF0OSvsswfwOqBoLcbtk/DhvP52rBlnigwNKEXxuGuWNZf8fSpVBx0TlnkPPlkEpv3xeE8XA62A2CnKiZK/tDrC62gxmGuyOu+++mzNnzvA93/M9+bLxeMz73vc+vvu7vxvn9vER1qBBgwYNGjRo0KBBgxeEqN3GBMVoaYHUT4rrLHf2xeee4trF84xHQ+J4zPbmJsMkrRDPGXHhyspXTxTc/Md+7Rb7+UaukhtZrufSFHzFDlanY1rxkM5oC0QYuJQYr8ruuxSNQoti5FLGYolEEyqNZP9racOxoFvqdIBmQQW0lCFQvrxW2pvVTRTeSqGVypXguyFUhp4qE9ZDSUvqboBFPSu4iNn720qU2rWUGfeJCrmYnTZsH3mAwepdJK0FcJbeteezoHdPvAXjHW+9DLk6urinOrNnLmImp3aNQnVGtV23P3gSTCcjTDxAx8N9bTetYHqO9q0+vdWAfxEYbO5dbHsN+7EPkv67v0f6b//f2I/8NLJ26dbafAmgWh30A2+cu17w7gBF1a1o7VWj+7Bo9tfRbL70PYU5gJLquZ+/lQ9M2UPpvZ/rojjfV6ssrrmWlboJG+66lISy/7nEGhRmJT0xKoJJygr4edvlOulsH2wQ+Z8Jy64KmZuDdhNL9slvDoIQTj686/H2pHklqKkaOLTP+7N65pVNZvomy4dITYs06mGjLmnUIw3ahdQLDjEhaau36/tPSv+aXlN5cEGhz7J2CXfpedSJB1APvAlZOsj6x3+ZcdCeEvZKl9M3TLYNQoYrx2f2U1ecXbSz6LScMsS2uvu4yWbvB/3I2zGPfNUeGzZo0OCViIbsvk1hRwmD5294MjcpW0DrgWXjiYsviLAREZL+mBtPXJhbJth2BGupJ3R3y908QdFaXCmSVUO8anCtPaJQ9zEmmFFjZ5uZbeeJ3Zp1wbrFbFm/fl5O6j36lA+qashqJRBdTryteBWBIj4ceivugDJBXIHU5PuWQJGsBtiOt0av37Dwq/bNgRpLbiVfJN6VD++enq/dzk3NOr99Vq+jnpjWCtktuHvS77Q+p3feRsFyHeuQ1HHj2vVdKm7QwENrzU/91E/xi7/4i7Tb0xx/P/MzP8PJkyc5c+bMy9i7Bg0aNGjQoEGDBg1e2YjjMaeefhKbFiLHlYJq3tOJ9XTFwllMOBPjXUve1Ey+3xIhUyGBlE0JBpuluqKdG4SDjdK8h4QtXNjOLbJzEkQEnQzR6RhRGiXgxjv0JcHhsDgSLBt2xLl0m4u2zyXb55zd5oYdzVqdk6n08ORWHcElgKtMEOhMSbkXOjXq7Gou8Lp6osq047aNiQvk38ClPD5eY2umZ1mdNmXlwufzupNWj/WTb8RGXVCK0eJhFi8/QzjOcthm+60L18IsZV2PeYpsAZwOsp9B2YRgvEMw3CIYbaOcLV+L4jDJOCfUdA1JelOYR5S9UAU5eBvrxYO7FpFr57A/8/9F/ujXYf0ybFxFPvc72H//D3BnH3/hfXiRYL7qz8BS/b44E4EOcGELqwOkkG/aBdFNkLzz/56LyWkSN83jXWNPL2ivTtcGMntsKdrVV0m9FxgMofD316wt+T6qA6iEqLyQa9wT1brUfhAP0JP+1cxNTgIDUCY7bgGivNOCmCBLVxF6a3GVPXedmw1qKe7DO74d/Rd/APWev4T6k/8v9F/7p+jXv2vXe80HNFTrvLWjIVBqq7Vzo7zvB+9g8Lnfw/ULASrZ+zANO4hzKJup4bXBRm2qEJhe/9oU3m1FQdTsMZLNa/m/h6eewPa39r1fLmxjw3JfVE3agdyJJV+giY7f69+X6dinpqjAjPul8YEAcvkU7swXz7OpQYMGXzg0ZPdtCOcclz9/2pPbzltQm4HDZDmV42Mha4csjz/+OE899RTXrl2r/RCqQ7o9Zu23n+PiT/4hF37x07Mv9MqfZixEa5bW1RQ92qUNJ7QuJZidSqR1zxAfCUmORHPVujXNzq6PFK5GHe4HHfXbK8AMhfBqSudUXKugzgvWMsbTn13UtUprJRBszIngNQq7FDC+I8KuBHMHT8mBOaywUdhFgwvVruOoefulxCv0dSyIVjPrlMXbk88ZB+5qh+O/onGLGjVvHGk0bpcnkGhID4aelJ/TvnKgYsH0HWZHMH1h68INdtb3P+hq8KWNb/7mb+bChQs88sgj+bILFy5w//338+M//uMvY88aNGjQoEGDBg0aNHjl4tL5cyR1+biVQnRQQ2SnNeVq8mHvZRteg1l9opqxLHcV0ry9fZWF9fN0186DCMFwC2MTgnjgCe9ifdpgww7OBCiboNM4I5kgbS2Qthex7QU6YZtFpkpwARIEU9gHAbZczDVbtvXeL4rq7gmq+cDrUFfCVIgxJ5SU4i1lSBFsRkQk4ng+2eLx8Ro7LiEVx+lkm6FYnow3uOFS1lzCUCxDsVx3MYmJ2Dz2EOt3PMKNe97Mjfu+nKSzXOi8YXjgRKkfYoJbUvQLeBvnNPbEShrjdEDaXsK2ethWD9EBQTzw51Es2qU+76yJ8vP2gojtLzScw33wh5Fr5+YWsR/+KRj1Z1ekCe7XfhK5lXz2LwHUwgrhd3w/6g3vQpTK72MbtpGgYDNdQ25X7+8XC4K/33QyxqQxxsZoG5PRtKVfSS2dk/F6z/nQFxIMkQcJ3ULgxNQ1oaiyqf59M7WpLLe4/+lkDGJR2W+mzpysVaVaPClaDqKSIES/68+jD5YVxjO4fh516E70674a/fCfQLW7yL5ywdeo3PeDYu53ERZunGXp4hPgLCYe0N68PC1756tIjj8ASTx1MRHBxEPC4RZB7FNNFK8Gqbl+8vOWLyjOKe9C6vemz93Rxef3t38F2Jm82zUBW5X70rS7dLVw4OynWT3zxxw8/UcsXXycYLSdl+lsXvHBIZOdUAq5cQH7i/8C9/xnb7qfDRo0uL3RkN23GUSEs6dO01/bnl1nYHh/m+RQmOc0TpKEK1eucPbs2T0J73RrxNX/9DkGT11FUlfK6TxtZBotXIXZtvUKaRHCdeuJ+Z05gygRogvxrgOsvYYK86y9RSmSA6Z+eyfo2EfZhpeTesJdeUJ1bt8UYBTJoaC2jd2GeaKB7Bs6uJHWtmFbam4ggB469FDydmrb8F+zc9ZO++/mjO2dZi4p7T8gapYDdkF7BTfUBiIIMD4R1q9TGcmvFHpYr+4GUImgR+KJeSaRqXD+8VNs39io73SDBhWsrq7yuc99ju///u/PFRDWWr73e7+Xr//6ryeO4z1qaNCgQYMGDRo0aNCgwX6RxDH97dk5jRwF1WWOOtex/agxK4o7UapEbAl4O9hgSlbasIWLuvnkvDXRNJezc3Q2LhH117FBhElHtNfOY5IRcXuJcfcALgg9YVPZp6l9rkOL9QrskmJds6wCDlD+OA+UJqhM3/UlLSmkp/vzIqh9azDJfD1BRxlaqvwxv2wiXh0doK0MGsUh08Yi9CVl4BKeiTdIcViEZ+MNHhuvMZQ0r//5dJsLbsSzdsCzdsAlN6YvCba9yHjpSJnkLiBtLexrHyZK0Nls3R5KHMYmucW5FodxCTqZ5iFXSlXUkFndJpi1Ln4heDFU2/vFtXO4n/thZHttthtXz8LVXVzP+pvIqc+9hJ27OajOAqwcwUZdbKvrXRXqLKUrBPF+gmJuvjPeYcFQzqk8z2lgYpVereOlRon8vOnrzivUK0dz/wEfhTlFJTa/M3WNvXj+b22QI3fPff4rahTCgNu6Dls3du2O3Lg4W98dD4JSWBNig1YtrS3VyWgRXHG+tM6xkixAi4nC3ztEhKMtli8+wdKlp0oOFfr+L0M/+Qf0bpxhYe0M3bWzdDYuEg02fJDVuE8YD6dqfRGCZLjLtbbL/HuVD1hcRd35qun6tCZQbQ/Mvot1qQ+CwoadUhlz/RyDpz5VWhYNt1i++DjBYJPO2gVa/bV8zOCULrinOOzv/sJN97NBgwa3N16a0LUGLxk2Nzbo7/QJWrOvq/hwiLTqX/bb29tsbGywtLSEMeWBnohg45TNR8/ihtMXVp0i2FtmK08qF1dr/7IM11NcW+PamXXUWDA7Dp1ZidslH3XXOh9jexoJFWbb0j4bs/O6bnkgJzJlivV00aTd6hGQ0Fujm6EjSDUIWCw2UrhFg+tpgk2LHgl67FCpoBI/eBJAOyG6kmAXvLW6BMoT/qkQDAUXCy5S3jLdMO1r9h/XM8ShwmxZ9Fi84runsV2DLnyDSraNGPJ6zI6l93xMvG4Z3R35NjLldXjFK+IlABdqf6xTn49cj6aDP1Woe5JyhWyOQERNlzFdVzyIEmmsFnQqeVkJlLeZNwpJxZ/HbJ0zyivAC9eBKHCRwrU1ZNbu6YrBdXXeX0RwbU26ZFACo5P+vAR969XgkcL2TL6965UjNYvXhxrPH0Rfef4iC6vLtfZtDRrU4R//43/M+973Pr7hG76BrS3vDvDhD3+YY8eO8Ru/8Ru86U1vepl72KBBgwYNGjRo0KDB7Y/9BJOKUqVvzeoUhC80S2RL0ZZbhGhnDReEuMxC1as8IyQZY9IxLmyBMThjfCuZJaxyKaI0adiZEt3gSQ9t2D76AC4jw5VN6+3Si8jqdSh0QaWunS1P0AMLaLbw2cUmCJWeyZHddymReeEE60gsAfXW53mfdEhbGa6kAwQ4HHS8BbpAWjgzodLcFy6x7RKCjIwS4Lod5cQ2gM0ne6ZtprNnmJE4pE577izhcAvRBjPuo2yCScYocQhqhsr2f1VJToUUiLp5e29sjNignG9d6dK24K3O9Yulct7PPEZ1/mwfqKXcFDDu4z76s+g//b2owrUoe5CDwJ4E4hccdj/nIHuiTPKjv4A0kPuCUvs8R+JVu0VCXhnEq1heMtcAJYKI7GrxPS1cvO4caWuB8cIqKE0w2qa1s8bNKLvz585+Nzl8F/rBN+Ouz0+7qSQ7jrrginHjEnQWIN7FFaMzGzgTj0bs3Pc2MnNwdDKms3mJ9ublfFrVuAQnrvAeEP+MwJWurfITDz+viQ9SkkkKD6W8+r94vYggv/UfCAskvn/WWJwySBDN7ju7W7bn13818APKASImJPya70QVggvCA4e9jbmzVO3nAVQa++flZLmzhIN1UIX5XW38e1Z7oVPSXpyeLxGC0bbP2a4No8UjdDcu5PujRFi+/FQ54EHVhJGsXUKunUMdvmuX49CgQYNXEhqy+zbDxtoGAOmS8fmgC++tdGX303nh/HkuOuj2uhw+eoTewgLrZ6+yce4a6TCmc3pcei3ooYNlKSu8i+8Ozcx7RAmYocMM8S/teFpEFLiufxHZjmb50akNUrpksItz5L+KGWLZ55Ou2UmjsAuGO+69By1w9vHnfc5rpZBIkRz27YfXElqXp4MECXwZnYLObMdtV5McDNCxb0hbMhW1YDsqJ/RL3Y006aFKLq+43FEFXkVdyDMe3vAffdG6xS5ZTxZP1m36/qgUTOpPuB65sj14JfCgNNDQs440UnPuAAgUrpp/3GTHL1TYED8Ysn5woapuPgpcbzrQyc+5UriuwXV9F1xPgcOT34EiPRiQHgzACqZghy+a2pzlgO9D/RoA0jihv7HNwoGlXUo1aFDGV3zFV3DlyhXe+9738ju/8zsArK+v85a3vIW/9/f+Hn//7//9l7eDDRo0aNCgQYMGDRrc5gjDcM8y1fzJUiR/AMTRu36apLtC2l7MHMXCjIT0pE00WMdIiklSEhRxbyUnBVzYwukACmSxCyJ0MiIabuWkpbex7uVkOUoRLx0p9+0mLJBFG8SlpW9ZP+E/7YdSiq4Ytgt0t1ZqZg7kVlXcFsGIbycVxzU7JEBx0HRmrMmLCJTmaNAlVDonspVSaCnnAo+UoaUcxUzWPR3u23pdZXU4EbRS6CQmHO+gxOF0QHvzMovXTk3Vm86ibYKx84MoshkKzx+V8h7PktZ10GmMLZHdapbAfDHVwUU7671I0n2QqEKmpJwQUwUlST5n9/xnsD/7g5g/89+juot+3dLq3n1d3EeZLyD0sXv9P0rH0Pn8z5NJRpuinJ0GRYggSu+P7N0vaojEvTAhPqd/Tf6ps+Cem7jnbyoYQrydeaGFaYBRfoVAIZhIBLaPvYq4Vzj/y8cYrI5ZuvQEQcERYX6zhWO034CAK6eR4/fvXa56rFpduP/L4FO/Pn+Taxdwn/sY+nXvAGB85Swbn/h1iufChS36h+7BBi0WbpzJl2uxOCuFgCuZ/r+aTsIKZGr46gPdTQOrlJ/IlcxlQolFzXP8FIt1thyUJXsR3XMCyJSGk6+BtUu+7pMPY77sa7Fh2yusrSVYPUJn+zqdM3/sA8aUZrx4iOGBO3FBBCIsXXkGncZsHn81LurQ2byMcRbBYk3k35la5+r28Cu+Gfu530ONdkAcQTws919r0laPsGBfPgls2usek2S85/O9QYMGrxw0ZPdtBjvJFaIV4zsjWufiPNpZ9nk2B/0BZ54/zaK0Gd3YyTYuK3TB/x2upSSrwVxLc19wTkNKIYFAmhUpkNbpwYDBfS26z48BfN7pmu1nOjWBVoiT2tUmMPQWev7fnRBXze0FJIcCzMARbNm5+6AHDtOytS9OPRTECFLX731AJSBqGkhQVNG3LiWM7oo8AQ8oO7uTLlLocWH/C2p3sZB9uc7vgCVTle/eTz8oq0Y0KDCC1KStUQ5M32EzwluqxHvWpB4Jrm5+wyhcSO4EILt8K867NIqwyRdH7qgGtxfa7Ta//du/zT/7Z/+M/+F/+B9wziEi/MAP/AC//Mu/zEc/+lGWlpogigYNGjRo0KBBgwYN9gtrLfF4jDGGMIpYcGNk7TJKLGnYYbxwcKpOq1iWe6KuMOEhQmf9IkE6Jti6wgBIeqslsjEarBEOd3yubxFCmxIvVEi5qipaKW97nMa5Dbl2KeFgk6QjuKhssXpLUApRJstBO92fmWKVv+vS0rUwntgv5azde45C8CpqEce11BPQKcKGG3PQtHfdNlC6lJcbfLx9lVYxqBLZXVRPt5TBipDgCFBEyqAUOBFWdYsDpuXzlIvQ275Ga9wv1DvGthZI2ovevhZAG+LuKgzWCZK9CPWJW11Z4b0XiahqLONnq7614INbrrNu3RzCUGXlc7fliQpSBCkqhq+dw/3Gv8N883/jix25Gw7fBfNyeneXUPe+bn/78oXCYMur09Ms+MEJyqXoUsoAyqc9uy/FUS73QnGTZG5p7QxZrsrnqlhurz7sB5NrQk2ui5kCTKh4BfQPniwT3Rlc2GLr+Ks5cPbTLx3JuHoMmD8tLXVLzz+J7Gzs3qfBJvLhf4vrb6D/xDex/dgn5h6/0fIx2ltXS88cJQ5VeQpL8fznBQ1SCLZQgHLWW5/rwrtOaR8ctcc5VGIRCgFTu5beBfe9nvCb3j/tu7Ns/tFvMa7k6DbjPktZn7Q4OltXiQYbbJx4Dd2NSzkpvXzpCcbdVaLxdt4vLQ5bDBBzFhWPMDtr7OZTYoMWIfXpT+YenSBEre6Rp71BgwavKDQ5u28ztNrTDw+7YBje3yI+GGA7ekZBPINiwGkiU6IbQNfnVdZjIbqaYLYtIjJ9SRfrLP6qMAoJM4WuAAXidvhAm8239hgfDz2pWffy1mr+W1p7MrXatE0t1y9d48aVayTK1hOmSjE6GTE8GZEualQ8O5hVQLhu0cPZjxoFmB2H6TtUIrsPHut4fPCq90QgLZPmOhY6p8eE1xL0wOFMTQXaK8tdmFnKV8T3WDL1e70CPi9TLDev67V5zBWY+lOux5LZxbusjZohsgU9rt9eIoVtZznE7fy+7UaET9Dq7f6h3qDBbvjv/rv/jscff5yjR4/myz71qU9x7NgxPvzhD7+MPWvQoEGDBg0aNGjQ4IsHLk2IdzZJRwNEhO3NTS6cOc25U89z7fIlLpw9w9OPf55TzzzFs08+zjOffhSunyMabhCOtulsX2X50pOEw03vEJflsyajAkQHJXvT7o2zBPGA4dJRBisnvMIrUz6qTP2YRj0EQdsE7VJMOmbxytMEw11yhQMoRdJZwukycRCOdl48MnMfTEQ1tjxShkU9jRgPUBilSHC1RPh+sGnjknX4WOyMVXod9tOaQzAoOsrQyXJ43xn0eH3rEK9tHeT17UM8HB3gUNChpQ2RMrR1wLYkjDNiuT3cKhHdOZTKlJVRaVnSXtqzb7dKAs3kdBZBVeyydY3Q4mVBTU5q8HfTDGlfU05OfQ7ZvJ7/bd7zl7wqtgoTor/+L6NuwtngpUb6xCeIP/xTU6IbyFMIVHLMo80sdaz0Lfol7IKbzYedn5OqIqlOhFQOCppZV21zjihmEgxRKldbVkHYRr7hrzE+cKK2LgAXtol7B+aun4v9KOHDFtLqZTnZW7iwhTVhab5aASYZ+fzV4IOXBluI1vvKzy6//0ukF5/Hbm/s2teNu17HaPFwqd3qHuRvsplzMXutVZ8pk3J7HpW66fR3/Tmf2oPJrwwbtBisnCgfj+c+TfpzP4QMPV+w/dgnZohuANvqsXX8VaVlJo05cO6zdLaulJa1Buvl3ckC0Ipw65f3PPczOb8nv8m1WnPN6ld/Bard27XeBg0avLKg5FZHxQ1eFgz6A049+1ztOlHUK7DBv0jcNHDR9C1mWD71wVpKtF4/OBcF26/voqwQbNd//Mhu7iHZWyhd0LiF+litOhVwqf+7rJtYeuuRwwwcykKybJAoe6HvUnfr3JiFzw8Z3t9CotlBT9GKuw62rXAdPb+PrmznXkWwlWJ2LOF1W18mO3fzoMfOq7/n2HqLBgl3GcxNonvrSHVADEhQv72KXSkfebXd4b0tbFvPzSU/sUGqhfX53ic5v+ugBxU79wI6i13ufv2Dc9pt0GD/cM7xHd/xHfz8z/98aflf/+t/nX/zb/7Ny9SrBg0aNGjQoEGDBg1eejhrSZIEEwQYY9jZ2mJrcwMRR7vTgRuXGF4+g2ST9NLuMWyv+FzYu0Eci1efI4gH/k+lEYTtI69CjCkQAQK6QqbZFKoEm0hmDVtuo7t2jqCQo1VQbB99oJTjtA5mPChZpgLEvZU8T/cLgUpidOEj36Gm+U2VwgGJNoxcyqbEaKCnQrRSjFzKlks4OFE/41XUgdL7UnUXMXKWNVe2Gl7VLdrV412ByYiTqXX5RO2Z2fRmqlC9D+LKiXDJDnKCG/y8xslggdW1C5hdCOT2xiW6GxfLy7avTu3N52DG+lbKVFCdWjTNcr1P1qg0JkiGOG1wJgJxmHTWLrdY18Q5L88pLi9BDuYZgUp53i8PHtll/wH0N70fff8bp0W2buD++CPIqc+Cc6iTr0Z/2dehDs4nPL/QEJsy+r//VxjVBEgAiKDTcTk3vYhXlhaKqX0oaW8a+1Z1V67NKjH7td8FH/6pfLlkeaJF+2fmxK5dVVIllPqRNzjbHz9/WpmzrSv33r/K2jOf23V/OusX6K3NcQSY0yffVPm+cEp7K+/8jaAQrX3aipJ1t6BsWcEvgDMG5VyJcFZuzvxrcR+DiO1D99Sq18sFhaVLTxANt3YlbP39Xzm2RSv9DDZolesxgU8vsUugltMGMYV32sETmMUV5LlPz/SV7PhMLOiD0Q5Ll5/KyGTfrjr5MOqb3s+1X/sZ/76dg6ULjxONtuauB59exFXet0l7sbSP4Wu/CruzSXr+6bn1tDevYNLp+8op7c9/7TNPUCdfg/nT/zUq3P1d36BBg1cWvnjC7xrsC91el6PHj3Hl0uWZdcF6ih454jsqH1+ZujcfXOvJP8pIDhqUdYRblWgpBYP72kjkc1/ZpJxXmay6ZEUTDCS3oC6tzBbpofPEZR0p7wBdQ35OyN7d1mV1BzvFnB7+PwoIz8fExyOo5KMONlJ6Tw591N+WJT1Yw9grsB2FHs2SyS4gz90dXk1IDoWzpLGu2LkXVw0teuBAK5R1mZK9XMoFWW7rmmOmUimRvRM7oSL8WHEOqTwZ6AmIq28DmxWo7JcA6QFDsONmrwcN4xORr0/83zOk9MQWydSsc+KDFvCEtmur2r65tkIPZ+3sRUH3UGMz3eDFgdaaD37wg3zgAx/gL/7Fv0gc+yjxH//xH+fXf/3X+fjHP86JE188H/kNGjRo0KBBgwYNGrxQWGu5eukim+trOOc/2LQxuILybGtjA5ylowwmyy+tRn064wHDlRP1xHBOnCj6B+4g6q8RLxz25Lhz3o7V7JHTu05JqhRQyb+sNKPFI6W8qgoh6q8zXj46W0cBrq6N/RBg+8jTK2GEywipST8n+UedMiQZkdXWAeLKxHFbBzNktEUI6iYD9kBdN7VSxGIZZeRziKatTE4QCkKK1Mbj64zGVWr/tLtWigO6xWU7yJcJsGPHHN5DKW1rbOX3oo8zGqRcSil/2orUtDZZvlyXEUnTa1LZBJMM/fyLs2gZ50SRFPNhF2yhc6fE/Dji50REXjrb7Br4ecG9LxbVKh9btXQQ887vgHd+x4vQyZcG7vzT84lu8Odhkpe7aC2tDeJc+fy/2PrufdqXizaeuAZwFgmi7FmkIAjRn/kdVBBVzl5BT6w0LohQznhif7dGawh4hQ9W2VNle+PiruuBPAf4BHVBJLV9yp/j2T2jfbqGSWqJSd5wbROcKuw7IMbg0nLQk7YWxJasbfdzdlUas3j5GTbveC1pe2HXPg9XTniye7f6qDm2lXNQ65755X8KlcbI7/7H+XU7CxL755Q26Kg9S3Rn7TkdsnP4PpJMeZ+2FxgtHqazdXXaj7NPYE99flei22+7uCfZPdkvF0TZ/rqZJ1Bw7yMEQUh6+XTZlSGDiQclolu6SzAe1l+nSkF7AfPN/w2qmqqkQYMGr3g0ZPdtiENHDqNi4eqFS5n9t1f3dk+Nia6lxOcTxndE2AVNumRyohvIxkDK22ZXCErXNQwfMCRblnAthRRsVxMfCafKXK2wKwE29gSnsoILFK5nEA1pJKixeLVxKuhKQK3rmUwqzYyJviILMFOFDk++EfZYhwimX/5AUKkggUIPHd2zMe1LCfHRkHTRoGNH61JCdCXxRK8Bu2ggwZPqGiRQuJbCtjWuY3At8XmyUz84cZG3aEcp9MjRvpgSXU1JDgbYnsEu6ClBHChES2YbDmZgMUOHzqzn9cAS7DhspEgPBKU2dOzQqSBKMvW7r0PbAtFdCGYQ49ejQIwqHK/dh3MK/4E34+KkVG53LtqfN7/vinQlJD0IZtsSbFtw4NrZdZcFFthFjUS+DpUKKgUdO0iE9GgIGlQi2fUi6JGg4uknqutqVOrPS25dPiG+tcJ1QSXkuc0lUEgAN9ZucPDYYbSuXGgNGtwi/tyf+3N8zdd8DW9/+9t55plnADh16hT33HMPP/ETP8F3f/d3v8w9bNCgQYMGDRo0aNDghUOc4+zzzzIcDErLXZ3FqjaMlo7RXTuLmJA06oJSmNEAt1Agu2u+R13YYbRyR6EujbyQbHtK+fmGAmXgog7OhCW1r9kzrzMzyk6vECyT8MFgEzEBtpXZpE5ITpFZRWYFMiHTC+SHEvH25YUJ/LYKGLN3vuhb4Lqx4giVJsgIahGh7xLiApU9BPqiWNGtknpc1xDejinhfTOY2Jy7wnkbZ+T/rPnuFFUyzbv+7X6sRAe4sIWyCToncpS/9sSVz53SWG180IYIymUkTTLy1r8T8lrEm7bnBCpZPcXOqlmyK9tenLz4SuJdUSORKPZrcRVO3H4ueRKP9i4E02dRifDWWQ5l9pw7e6lggwgJ2tOAiOq1YlPczjoqiNBpnJ9Fr1imZOM9Ic3r7pG9rcL3fprohWXC4Qhz+TmUs6RRl6S7Mq1bhNbOjcpW04CZ6Rx1oc8T0j4jvB2SWWx78Yt/HlTmfW2C6KCs1jfB9FxOFyIyXab2obT3PRbam5fYae9+P0xSKOx21Gpbm+nD5P01mUuOMK/5Smh1kCtn4NlPzeknPlAsWkC9888hv/6Tc/uhxGGjclqC8eKhEtkNoK7tQ5W/n7QXSpG2FpCg8P4UyQPTzD2vxRy5C4DeN/wlRp/6CDazTletDuF9rycMQ9TV0xBEqFe9BUli7K/86/mNjvrIuSdQ9zyy9z40aNDgFYWG7L5NsXriEJtnrpLG0w+2cM0P1KO1lCj798ZXLHgSd4LsfenaGtlxuSJWAAkApUiXA9LlILNYoXYgJJEmbVMayCjn/5a2J4hxQngtLbcRqXzcXzcSUHnB2X3edV08q+7VQ4drKcIb/ljoRGifj7PyZTVy2jP5xwfO/0T7/ZSoQKx26ocuQWb/rlNoXUmBlPigYXyy8HGf5RgHUDuSE90AJrOGN7GQKkrnTG9O1ddqMk61lXjlwr6LVmUF+34G6sUAgppzPjn2ygdEIl2FBNN27FKAXQpypX1enfLnHKUgyIhoEcwgy1OeBQNIpJAIJBHMVjLd3gDB9Lwol10CYXnQL9FsBLe1lv72DovLjcK7wYuHI0eO8PTTT/Pf/rf/Lf/yX/5LAJIk4Xu+53v4uZ/7OX7+53+eIGherQ0aNGjQoEGDBg1uX2xtbswQ3SWI0Nq+Rnv7GjoZITog7i4zXDpWntAuojB3MK/OfeVr3Qs1JIZoA0Vr65r8y/6Dd7rcaYMNIkymMnNBq2SZq9OYaLiFQohdStJeovhVuh91pGgzY6FsJoR3vjvKB+jXbV/KsbtrU7Xo6pCWGHYk8VMBWX8j0SXC2yJsuDEHdTsvozIiutqvWyHd65TgWmvGrQ7tqlK3cEzTqEvcXSYabGaNO2/LO94hqAlocNrkdrpiQu9uJ26qpM3INDUhvQE9IeCyMgrARBlR46Z9UhV+e17eZZi51n2++b1tlW8F1YCBiRpdJva/xbzOIqA1+qv/LOo2FA3ow3fuWSbP+1unsEVl5+Hmye5s1i7/66bvASBIY5xITkRO3RQqbWkzVagXe1DZJ6cD9B7BH7cK9/jvsXT1bKkPNmyzdexV2KhLe+sqxk4Vuvk+TI7zm74Oee4zPjd8zu+Wz4cojSgDk2tR4++7gkW7nytMfaqLGbW+Ld2PginnrN8n4R2NdvYso7RCvek98Me/sWs5qT7rsvQdKlM7i/aW7SIOwhbBN/wVVMeryvU3vR957Hd3J7LHfYiHu5LQCghH24wLqUaqgVwAevEAuj/ADefsvwjt7Wu77K2HSWPa29cYLR2eOmQoBcoQvPrLab3tvdOyB4/Te89344Z9SMao3hKqxmVFHv/9PdtluIvLQ4MGDV6xuP1GLw0AUFrTsxHYwou55l22+JkBelizQivSFeODnmFXgrPu5Z+TwrsNDHZpYzfi+lZQJbrBE89mx+WK3yIk0riwOJCq2T4WdH9/A8O6vNHRDUt4rT5XVHIgwLanjRajeKNrCSopepPX7Vz9oVPgVeG3GIm6n/OqYG7edj+oLA5kmf3AV9l1UfP0kVCRrJqphVPNefH7uHsfJ7DuRbQDa9CggH/xL/4FH/nIR+j1evmyX/qlX+LEiRM89thjL2PPGjRo0KBBgwYNGjR4YdjcWN+9gFLYqIOyPlBZu5T2zg0WrzyN2sP29EUhtHdF5TvROXQyLi1KOsulv3UyorV9DV3I7Y0JSLorpKFXhifdaRC1Hg9ob13JSbFwsAkzOXL3E3RecyyK37mZzbXgSdcATZB9cFtxpJmleIqQiC2T3/uEUZqeKhMdSilMNZgcKRHgcEv8ei2suJKqG+DoaESrzpK6sI8u6rBz+H7GCwczC3xvT522F7Em9FNOSnuSW2mfW7tIBgY+l6yYwP8mf+uc4kYhaBtPLedhSqbVHIG9zkDtMXux74nsGHnyzHgb9kL7CvH74zypn7cetdHv+5voB9/84vbnCwS9cgR916vnF3B2DwV9vTOAVH85EasLhGzgAyK0AVV/bexrH2xS/wytBvBUCMAX67oqk/bzCgnqyukK2Q4mGbF88Qm610/TvXEawR8nl99NPrgEccj5p3Hb61m+8ez+U3pq9Z+Rwkpsed+VRnRYus/8PGblvCk1G9SkbiWMAXSrTefe16KTEWF/nWC4NUMmh9rA/V8Gh++qrWPyLEJVnhFZP30ecpP3WSGYr/tu9L2vKxRVe9qKY1PYuLp7Gfw1jLNE/TWi7ev+HVbaaY2+/w0sPPyWuXX0rp1C75FqYgIljqi/Mbu8u4iq5ogHdKeHXlqtJboBWD2+d5sHj+2rbw0aNHhloSG7b1MkGwPGz6/TupAQ3EjRfZvnji7CDBwrv7tN7/MDzFb5JSSRJjkUkC5obKs+oi0npZ3QbrcxgSmvc34dbk6kcUuTHA5IF7M23LSUEnIVtSdYb/YoTNFZqc+fYkZzQqAB19GkPY2NVC3xCmAGkquu50GAtFtfQft8QnC95uWvFfHRkPHRkLSbKeEzKAutCwnhtQSzY+vHmRNSuYb0VoJXuifOB0PsdVylXKZ8XuuJc+UguGFL53OmbwqcVuWAjEmT0cRif3ad6xnGx0OSJZPbp880IcA+xlSd7mwOrwYNXiy8+93v5vLly7ztbW/Ll127do3Xv/71/NAP/dDL2LMGDRo0aNCgQYMGDW4dbh9Bw2l7kZ3D95WWBcmI9taVl6pb+0bxCzIarKNdkpMTadQl6UyJa5XGhKPtTO22hSrmC1WKtLNI3DtQJk4y9V1eDAjjspLYz6Xs8TE+UQ8nI8LhJuFwE5XGtIdbLG5dYXnrMovbV1kcD4nQBMr/2jqgpcokQIxjIOktEd6B0jPkdvVvgESqZPetEXobdkxcUFgapbk7WKSb7dOR1LHcX59fexYAkEYdks4iW0cf9NNWYYu01SNt9RgvHCaNehmZHSJBRK5+zXdA1QbnOxNl9smT/QRlk9nzOUOm1XV2H8eo5py9UF2IzxE+sVrXBfV6oVdSzFMNxCNUq2xvfLshevd3og7dMbvCOXRNLmBB4TLSGlsOWMn1OUqXfxOr7fw3KZ1hl2CI/UDbcj/ratlP3VUyen+o3BNRYU5NMrJ6l6tT24TO1hVP+GdBJJggv/7yIJIrp31qier9WNHVK5gNQKghslX13s7rq9m/m4SEbTpPfpzly0+xsHaWxeunWL74BFF/zRdwjujysyS/8uO4h78C9eBbSu1Mie6J8rxerV/tm5z63Gxn9uG4oI7eAxWl9qQPk1+0s8aBc59h4drzLNw4zcKN0yU9mnr9u1C9ZTp3PcjSm78G0yu8M8MW3ZOvomP3mTZg0vV0PBPIYS+f2vf2/Z1t1m9cZ3tzE3X0btSRk3PL+vV331T/GjRo8MpAQ3bfphic8ZHWSiDYcUTXLRLUn07loHU58bbTVdWu9vm23XKAm7c9YLTm7gfv5fgdJ2bWTdJozx0yTNpYCXwO6brtX4DKe3llmXseup/uwcXa9a6rvR12HYwiXQ1ID4VzOxBszSF1J1CQrgZlpXgBrcvJXFLYdTQYTboSlAh3BQR9R3Q9xQyqMc7T7fOBtaFmQAg6zXKMz4P4HNpVNfh+zosWMFtzlO9KIUZhl+ZI0AGla0Z4EwQK11ZoK+hR/QBdZ0EY87CwuEir1Zq7vkGDFwMLCwt84hOf4Ad/8AdzmzHnHN///d/PV37lVzLYzf6xQYMGDRo0aNCgQYMvQnQ6+yO80s6Sz9FdwGye1hrcopJVpWOvRt21kM6UchCMd+hsXc6+bx1xe4n+wbun7YsjHKzn9IoCgrgyfq8hRCdW2CVUiKWcNLAJJh5i4uGs+hBvJ9vevko03CQabrK0eZHOzo3cftiIozveoTtYL32zB0rTVuWJDoeQ1Fn+7QNmH9OD1RKzJuYQ7EEm9V3CQFKu2xHjwvHQSnHUdDikWxwb706ipFGHwYE7GC8eJu6tMlo5zqU3fCOjxSP5+XJRm/HSYWzhXE0I3lmCrQKlcDXK2ZIF8rTGPbD3RJdo7Qn50hbKK4j30UJtnTkxO8FsXXW1y8Xn9lf/cAf7uY9hH/0vuFOf87bLXwRQnUVa3/rfY+56CJWM0fEQMx6g4yHapeg09vmuberV/lkwhDMhtuMdAfK6Jv+oCyCpDSqZDYa4pfO3j2NZJbIlV00X5vXqVMDF671QdkrsZ0IoEbj7EfQb3pmrsScU+9yrvqTILvRlkhPdBJV5Syk7JlT7V+xdVdleDTTJ92IvVOrZw7ReANleQy6fKp0X7VK6a+eItq/Ru3EWk3r3EPvor8E7vg3X7vrraxJossc7r3btzvpsuXtfV0qnMVtAI09+ovSeLKn1s3MUjbdnXQ4Unkx/259Cv/PP5os7dz7Awa/9Dlbf9a2sfvW3cPi9f4GF17wNBlu77tNM16gJwKjZlziOuXzhPM8+8TjPPPEY5049z9OPP8aZ557l0vlznDv9PE8//nkGX/0XYOHAbEOLq5j3/pWb6luDBg1eOWgSi96mEDs7+HFtjbWCHrhyNKKGndd1cV2DHjuiqwmju1uzL9tMaFu15NbGcNf9dxMEAe2ghRkItsPM9vnH3C79NhspwY4lvqNMQgpAKv7rKdj/h2+31+X4nT5q0xzu4ja30dWxUiqki4Zgy87sm2sp7EJmEzMWJAR05UM2Upgdi10wM+skD0vMLHmczJRRiRBeSUmOBuV14lXjZuBAgwtAJ8xYso8Ph6AgXK/kcMoU2YrMRqkFelyO78yrsvhjq8rbq0w47lOUyUz+GGHSr+zclPJKgQtUbU4uUZAuZJGLE1Jaz55Xs21xLY20K1GZiSOaWMAnmfK8srkAxAIhee7vHFbo6JoJiAYNXiL87b/9t/mmb/om3vWud3Hjhp/g+/3f/32OHj3Kr/7qr/L2t7/9Ze5hgwYNGjRo0KBBgwb7w4GDh1i7fm1fKuGkvVAiiJWtT+VVQk293bVzjJaO4MJ27SbKphibIDbBhp09JvwVyjm610+XcruqyWR+Xk4jQQvSqc25von+26DliW9xmW12RR0dDwiSUelvF7ZIo15OOiS9A4gJaW1fzbfWLoVU4Qo5VcN0TJiMSApKywCNwpbImkQckdrl2MzfqdJfFm+hnucNFmGMJRJDkFvtKjSS0+sGhVEaLd5avVS7CNsuZkdSdKYJ33Ixh/V0f5RSLJkWQVq2nS/1y0SMFw/PzEfZqMONe9/Ckac/Ps3XrTRJZwVdOLYq68tMvuYZMq3mGO5HNV+tu5oPXiS3W5/YNjsTgTao1KCTEaqoAsXtr90KlFRCESZBG3vVFczm7q3Cfuo3sL//y1C8V5YOEfzpv4Y+tHfe7BcbMthGPvtbyHOf9gElh+/CXDuLKeRtr04pKbGocZ806maqf0BpbNRFjfu5PbOf6ZvMSd1kkM5kPuxm96dC5NZVoZzNnjdTAlohiFgEg3Ipuo40n3P+85qK1+/pz+E2r+brbwYqI99L99Hkui4S8uJm78eJ5Xnpr7qZx7q9mCJp9Xyg0eQ6Ldj75y34CVWk+PTO+igoxJicwJf8XlZ5a92NS9M81Fkb9rHfh3h0a0FdkzYAeiuze7hwAPW6dyKf+c052zt4/tNZYZ33nex5Tul8TK5PKW2v73jAP4OK7SpFuHywUOzmc8EL4CrvbasMdmcTs7AMwGg44Mxzz2LttP4knnVksGnK+Wtr3P2t/yPtM59FzvhUguru16If/hOoqH4c0aBBg1c+GrL7NkXrcL1tt+0ZbFtjYqF91wobts/4RIhE/kXVupzQupSAwOjeysNfKSRUiBMMmuXlZdrdDsurKzjn2NrYZPP5q5gdi4hXa5eQkaEyscWW2aFI77kR4bplK1Akx4pkpKATQQmIEcQor8aukpgFRFHEvQ/cz2ijT38wYm1tDVkxqFjQsWD6jmArhUSQniFpKfRIULHvmGup/LjgfPskghiQQJEuGtIDAWIg3HTosfXbBF6RLYZ88GK2LNGa/8iUQOV1oBXSVphE0BcS7ILOFfZmYHNi3uw4zBhsC8Z3tjB9hwSK+FDgLcO3LXGkMAOHSv2+wfT4igEJNVY7b92en1P/f0pA7OTvLK7PFc6P9uVEgwsVyvkgCQkVeuhQTnwQo/ZtpcsBaU/jetovy863aHBtfx3lA7usblyhwxnDHmxb1KbFthSu69l4PXJ5wIYArmumYabKE+n+2At6gA+SyK4ZwOdot7Bx6QYH7zxast5v0OClxCOPPMLly5f5lm/5Fv7zf/7PAOzs7PCOd7yD7/u+7+Of/tN/+jL3sEGDBg0aNGjQoEGDvRG1Wtx5972cO3NqT3Ksqg6rUz1HW1dzUtdv46ZEiFK0tq+xeO15emvnWDv5RmyrN91YBGySW/sqwKRjbLS7+lxMiG310ONp3udgvDNbrlYhSCm/74wyT2CwcnyG5JghYFs9RGnCLBhAASYZIxmpNkHaXiAYbU9JWrKggaCcYzpMhiWyWymFEVUiluvU1jP7XCCxJ39rlc0bZMvW7ZiRWFZNiyBTqA7FMrZDDpnODOGtUBiBkaQ4vMJbK5UT2yhFWwU+N3eh7W0X01UhphRYP38eKOkszSWRxIT0D93N8qUnC8sCXBBhShbWt6aXrl4rNohQEmDSLKBBJhMvmao6s3320x8uI5dcbnHvBQStPHBDgghxtqJ+rBBx++/tPosVyDVArl9ABtuobr1zon36j7Af/4XZFVvXSf/TvyT8nv8PqvWFSycn61dw/88/gWI+4GvnZsrVHT+Fd3JITDi9ppTChi30OC2Vqz2aNff8zaKsdPbQNoF46AN/Cv3Ky03s1nPiWPL/qmx9LdG9B9Tk6VEk9tevsMsRqOxMNdAjm1gs3du65JAwIWJ3I7JLyuTJdjPKdlVqx2lD/9A9iNIsXnmWcLTt+1OgzvMeZLsnFJ6LmaV60R2hjnRXOYlc2MfBFqrdg9H03TN/vwpwDkVBvPbUH+I6PdQ7/iyqEKSlvubPQxghf/yRcsBJAfV9rQn0qevXmcfg7tfsWkaFLbjr1XDuyV3LFeGCCG0Tv4da47Qh3rjB+Df/H5a/6k8THjzOxXNnS0T3Xljb2OCuN7wL3vCufW/ToEGDVzYaG/PbFO07VwiW50QqGUX3rXdw8E8/jH7NgSmhCwRrfsDWupyg4jmDH604fOIoJ+6+k+XVFS6dv8DTjz/JuTNnGd7wH4dmICULaR8RVxgUaOVJ0EK1KhXCdf/S6j0/9gMhjf8JuaJZWdCxoEeTAVs9Diwsc/bjj3P+E09x6emz+UtbWhq7aEgy4jtXime24XbZYBdN6biodBoNqS2YsWCGDtdR6HE2tBKfAzzYcZ5sLgwQout+gKHw1uFmLOixZ5Mn9uZKINh2hOuWcNOWFOhmO7MoG/vyw/vbjO5u4XpmauNtFDYj4G1PV9T72V+Bzkl2dHmwp7I+KFFlohtyC3WVypTMb2k/tkumQ0uVBQW4SPlAhEm7ivxpIsG03dJ1MVkwCYQYS660N2N/bYRr3rY936Ia8CB40lyDsmoawTq5ZuKpWt05x2BzmwYNvpAIgoAPfehD/MRP/ARBMI0n+5Ef+REefvhhrl+//jL2rkGDBg0aNGjQoEGD/WFxeZlXvfo1aHF0b5xh4epzhIPNciERXKZQncCkY5YuPZHnx436a/Q2L7F05Rm/LCO6/felpbN2geWLTwCe5Fm68ky5DTUhUwuLxNVaglchuqpSrZnkd5aktcB44SCjhUOMuwdQaYxJY7RN/C8ZlS2BjSkT3Vk/6+CiDk6XdSYmHs3MdaTtMrk4OT6lZTUEVnXGRNftYwUxjlEhv7fKiOhFFaGATRvTlxSLcMOOsc6nVmspTaQMOy7BiZCKIxFLKo6xs1x1I9bcmA035robsWHHOYGklKJnQlZNuzQRaRF2JC65CMStenEHgN1DsTdeODizrFalXS1Ts6yoQpQK8SUoks4y48XDJO1FEEE56zUgk+tTpu58E6Vr6Tp2jmru4f1eV3tDMe6tsnHiYa7f82bW7noD/QN3lvZJZf3K51UAPv0R3M/+A6TGQhnA/dGvz29ysIV78g9usb+3Bvfr/7ZMdN8k/BxgWTlatJQvLN2zrmoJYR/XntKgA4qW5wowNkaLRb/6y/014Jy/vtIYbVN/fTnrnyPOomyCtinapreYq3va9uzCW7PT38+VW0dkV4+kEudtwif7lecOz/5UuuT0kYZtdg7f7+8lbdg5fK8P8Cn1LL/is0Vq5l6rzQO+jwOhFg6g73gQZa0PTJicp5mCk1/WtjHl68UmyB/9OvJbP1veTGv0V/9ZeODLdu/Ivqz2a87SZD730vPI859B1q8gm9dwv/0B7M/8r9if/Ye4P/wQ6o1fN/P8mgenDGnUQ4mg0zFWB8TdA/7aShO2Hv0I/Z1tRsPh3pUVsLPdzPk2aNCgjEbZfZtCKcWRr3uIq7/xFOlmOZ9R976DrLzpLv/vGzDC+dzQFAhlBwuPDdl5uFO2kM5U2WFG0pw/c5ad7dnoZyUQbFrS5Vlr70InQXtFsIISOW4GjsXPDth5XdeTo3XvfQE9FFyNZfrBA6tsPnV5aude0wVpa0YnI6LLNZFu1cDEmvaDvqN1PiZdmr1NzMAhBmwvi1KsGUvqFBg5WJjz8i8E2RWty7vPjOgHCrsczO1bumJQVsoq7gwu8gR91Q59l+ZzKMD0LbZncpK57uy2rsSMTkRU42UU/tjYrp5/XWSN1/ZvHwGjCiBmTgWVZnbLtd6gwUuIv/yX/zLvec97ePvb386ZM2cAePLJJ7njjjv49//+3/Nt3/ZtL3MPGzRo0KBBgwYNGjTYHeqpT3DPH/4KqmDFPThwB1de9Q5c2EY5S7JwCNtapHfjdG79G477LF1+iuHiETpblwFPZHfWzzNYvWtKACoI4x2KVEo02EDHQ1xBwSzazCjYZmyaJ8td6vOVKoVKhqUJf0Fhxv2ScjztrszMNwjg0jjPm+0DrH02bDE3P402qxT1xGixLqmxZa8qnGcsYEUYSEqEzhWJodK5blHVfM0n4ry6GhhjaYlB8JbiDiEV4ZodMpKUVLxiO0JxX7hMNFEgZ8feFc6AUtDF0JepzjzGccOOOGw6ef+M0izoiC03JRglK9vC1z/qLhONdjDVfL7MP++lyqrbVOrxwRkqv+4EhQtaKJegXWYLb0JvTZ+M0Db2VuPZPjhliLsr+flL2ssEox00RcXqbEdm518EJRZRhevgBSqFJ9g+fC/D1amluA0i+ofvZbx0mANnP5vfq7XYvI787n9EVfLeSjxCalTTRbjzz2De8DUvqO/7haxdhgtPv+B6lNubHJa6u6mo5mVCbMvUEcIEiDZImmAmhHohLQBK59ciymTX9kR5q9DJEBZXICnY+oubJbOVRpTky1/4FVQzW6g0+8klXq2litk80bry/M32f1IuCyJRgElGuNU7UEfugKvnQBv0fW/APfgWtn7r59E2wQZR2RkE75iQ9FZo9esDOG5mP2T2IpgprK+dgWf+aLpGJve5mj7n550krRHrSs8P+exvI2/7U6iFlXLZOQEpN4UaQlzWr5L+5N9BrV+ZLqzYz8ul52FxFfXu70Ie/c+wdWN+E0DcXUaCKA/8UpXgoSQec/355266+y/O07JBgwavJDRk922MYLHN8fe9ntH5DcZXt1FG07l7lXClw/b2NvHWkOGpG3QA29XYBe2J0Ni/oMzAsfSpPslqgF3QKOvJwfhkiyuXLjMajGaIbglVrvTVCYTXLa6tcEbhFmoIzgnhLSCRJl3QBDt+gBRdSznw21uMj4WkPUO6GsxsrxzoviCBsHT0AGEUYsKA0fmNUt5yHUuthZBdChhrRet6zUA+I1ZFQbpsMFdny0RrFj0WbA3hHWT5tm1Xe9K/Zsw/sVNPo10I79QT5/k2FhY/PyRdNCQHTBZqOntck0MhaewwfYsqdl0rXBtwoKyg0hpeuDjAxpdlMuZyXmkugbdsFzW7vbLQOh8zWDBUreaV87bsEijMVkpyJCyp6CdwYX2+7yLhrUYCVmbbyAI5dzc7gs5Sb5e1DRq8tLjzzjt5/vnn+a/+q/+Kn/zJnwQgjmO+/du/ne/8zu/kZ37mZ9B6f5GwDRo0aNCgQYMGDRp8IWGfepT0dz44873VXb/A8cc+zMVH3psrj13YYrR4hO7mxby8Scd0Ny6WcmSHo220TUskb9xdobN5udSGSeMS2T2BTMghEcQ5Wv1rBONtEK/4tWG7pPCLFw+jdm7kOcWDZMjilWcYHDxJ3Fv1hXaxxBZnS/uvXHpLZPd+1G8qrahLK2QAwDjqlojsbRczEkuCo0dAS0/zadchFYfFEaLRmWnxuh3zdLJBUojgtyKFTODCBTtgR1Le2DpEoDyxroBANGlhO6M0bQzDgk1xijAUS7dA6EaZ/rw4zZCIo5WpGkUbtg+coLNzg2jcz8oqdqI223bM8m7nQBxp1M3Pedxe4sqr3sHhZ3+P3to5T0qaEFAgFsR5632lERXhJPbE/ITYDtveermS41uKua2VIm0tYAa3Qj6pjNDLJnVqlaSqbLG8R2qBuLdaIrqLSFsL9A+eZPHa87vWIU89irz7u7xd8QQ6I2Z3CTdQNUEbLxk2r70o1bjqPSOC6CA/JwLEvRWCZITJieeJLFcyolt7ohJ8PmNtsmeV81b6zqKlrPB1yuDCcHqfuxDt0jzIBoCP/zwo459rIvNV29ogVmqDLG4WCpixu37tV8LTn/S5qHdDcbuMqM7TQMwoslXF9aKg81aKZ69u8PTl6zx0eJkHDy/7Z859r/Oq5gLSq+dJ2/PdIAD/btgDk9ZF6cJ8scJbS6pywaKLpktzdXlw72vhid+rrV+JZOkMqs/o8symaF129XAWOf151CNvL9e3sHrzZ7uSdzxvHiYnHp77Y38PFHtV98zZXkOe/AS88zvhl39s12ZNMmbcWii9n4Phlnc00ZqtIw9g93iu1WFhcemmt2nQoMErG80s+20OpRSduw6w8uaTLL/xTkYm5amnnuLs2bPceO5iXs4MHNHV1L+si9sLRDdSOmdiWhdikmN+wJ7ECdevzQ4cbbc8dFJ4a++w7zA7cwZdSuVvyOE9rfIqC+0LCQtPj4iuzM810u10EQXXr13nysXLDK+XrUqUw9ue18D1NG7eeFt5lXRyPCKdo8A2fTf3Y0Jl44/0gCHt1W8fbNtdByDBpvX24ZVv7GDb0jkb07qQzG1fQoWLtM8lXuqYAuNzks+sq5ab5KIpFFJkduwjN/c7RguEN+afs2ArZeHJEd1n5wyGtcJ15rkCeKI+iH1e7/qu18WpT7F0+ABhazZfXIMGX0horfmJn/gJPvShD9FuTz+w/sN/+A/ceeedPPfczUevNmjQoEGDBg0aNGjwUkJEsJ+cb1fc3rlBb+186Xss6SzPEMeqYoGmmFXZ5tu3FxktHiZuL5JWiAkRRRp2sFEXF7ZxUcd/8iZDTBpjbEw03KK9dRVdUKGLCRgtHcEG03kIBXTXzs/tx7SgQir240pqbG33g4oduUxsgQvqxdbOdVQ6/fZ3lXzdw/YCNsuHLiKs2xE7khChMdmRNiiGLqXvUgYuJRZbsgc3eLvyQGm0UhilWQ3avCpaKZ1LoxRB5Wt708WcSrZKy3TNN3lYM804lvKxVlku791gtaG/fJSNQ3ezsXonG4fu5sbiAXRNTvgcIiTdZa49+FWMFg5iTcT6Xa8nbS9y6TVfx3DpqM+RnalJRRmcaU3JpwmJXSG2qRC42qWz51TXE/CeCFX5OZ8Qo5OfSmKfrz0eEsRDTDLyzgQZyZ23r8x0aqbGcjlf9cg7GH/Ft84/RsBw+ejeJFkaw2hQrjuIUCcf3nUzdf8b9qr5xUNV6XoLEBRpu5enYhDAhh1Gi0dIoq7Xp7QXwYSk7cXsWVIIOpDsfOoAp43/mRARQWfpEEw6rk65+Tk3l6CK+Ym1xgXRjIODzoIy9lJWy4sUSO8vvfL1pRcPwlftfl1NK/DPSQUocT4FxOIq6o4HUd0lWDqEess3oP70f50dSn9n5OEDIvyD//JJXv+P/h/e93/9Bo/8k1/g7/+XT3lHiWc/NdOcbnfr++EcJh6gkzE6iadke/6bUQX5Y6i1fybkx7PgYMGky+VtlTiCt38rauMKu0Hty32y5t7Onjdy/YK3Fx8P4b7X712VK+ynZK4DE1v1wnmC6d++C/me7o4LT8OH/s2eexPGfR/UVriGtbME4z5J1CXt3DxprZTi4JGjN71dgwYNXtlolN2vIAwGA86ePTtdUPcONT4fsx67PF8ygAug/+pOrQK3hGwgUrXwEZXZuSTir6pSlJh4lTF4y3JmFbkuUKiRQ/ctrluOmuss9aAXsLWxuWvX9LZFND7XdLHLifi825qSQlrA58Be9gPJ4d0tOmfGufJ8UiZZDTJ1czn6TfA25hOL+J3Xdlh4fDiz/eiOkPiIIbphc3Lc77QQbFlMlhPcthVmVLYfF8C1vDW5SipDDRHUaJr3WscOCdXMsVdZbvTcTr6KyTjdkJ+nYvvztnWhIl00qJp2dd/SfX6MAlqXElxnxPDuVlmhLoIzCq1lpl2VSh684D8G/T9KZRKH2bI+v3jluu2tLHLs/vpI5gYNXg584zd+I5cuXeKd73wnn/3sZwG4dOkSDz30EP/8n/9z3v/+97/MPWzQoEGDBg0aNGjQIMPWDWTj6q5FOpuXGK4cny7QnvBRdjYgOg07OBOg0wRnQq+kzL4fbRBx/Z63YHdT5pkai+8gYrB6J73rZzyZhP9ejAYbjJaOTr9PlSLuLtPZmu6PEkfY3yBePLTrPt56vuRiR/3shzUR2sYo/D5rsYgTRBna21cJsn2wTjFYOgJao5zDacM46njyO++WIkRz3HQxGUnnRIhxJIWJoFQsKUIHk+fNrsOqaXNnsMC5dOrsp5WasQy/mA64P1xGF7/9URTD+5VS3olt10MiJQt08PbrRZxP+zw6usJXd05wKOiACIcI558SmRJmog1rd78JnEMmymRtWD/5Ro4+9TvTbQrCjOkyjWAr812qPouas9m1p1BpjNMG0YFXg2Yq3IlKtdjHKcEEGm+5P8kpPJkx8wrQwnWv1HRipLSs3DE58xj2wF1zDlJWxoSIMiipFxYAELagM3tPmi//k6Tnn5oh+wHUoTvR93/Zrm2/mFCH74Kj98CV07e0vQBJZwl0gFOCsgmiw+w8GuLuKjZoo7TCxEMQlz3H4pKCWonD6XLeaG9fPs4Vuv460Eghb7vCO2CklW2dCXPr7rwNZ/dhcf8iPK9yFOS+Irjf/0XUnQ/BW/4k/PGHwe4RLFTqlaDf9HXoir29e/z3ZnosIvydX/4E/9tHPp0vs074Bx/+NP045Z/8+a/35dIYttag1SFYPEBLQ3D1DEosadRBpQmt/roPFICcZC3Pd0pJpa0Acc7PHWfPo1y7X+MkWl0mV8+Urb9rsR+yW2b/Wr9C+m//F9RaJmozIewRsDV9loh/dkyeS4DYFJT39yg+j+pSeux5VdU8C+pgbEww2ikR2/6eu3lqKowijt9xF+12GzvYQQUhOmrtvWGDBg1e8WjI7lcQrlWU2OmCocXsh6aEivGB0JPeseBaiqTGQrwOZuAHZjYCMdlHjFZICCiFTgVJIexFdBY6bK5vll6M3ef9B1y6pJFAo5zgIoVr+4/dcMMi25bg+AK9kwfpLvdQgea5p58t9cNFqpSvejI+CbYdMnC4yLeqE0EPHTqzXhftid9kJSA9EOTkOwCBYnh/Gz2wrKgeqUvZiRJwQrRuS5HXtqd9vu4ied7WbL+pR7CRYrYsGEV8MMhzoo9PaPRQUImjfT7G7LjpB5OA0grbyQYSDj+mDBXpcgCBRowgFnDeGl0lhQ+kWNAO3HgSbMAkONKT4Znb1OTbKieOi0S3VqCyj9nJiEYBdjYwYXxnRLqkCbacV6XHggQKNXa0riQlwh+Ndw64mBAfDkgXDfGREJygE5BQg/O53XXi1eQTAl8Au2K8xfpkfBk7gp3pOdV9h4wcLjuXrXaLu157Hw0afLFhZWWFz3zmM/zdv/t3+Uf/6B95xYy1/I2/8Tf44Ac/yH/5L/+FKGrcCBo0aNCgQYMGDRrcBqiq4pwDl/o8xxMCVgcMVu/EthfL2xUm1JOJnfitQGni3iqdzUvTRSKYZIQt2KDbaFb5p208s2wGVSJxF0XtvO2VSz3HEIQ+57dSuNxGW2htX6FVsL/WLmXQ6pFWFMxavOJ6ggVTWa8UbQwKGBVIzASHQeX5sOfhmOmWyG6YJbJTHCmOaJe6RGZzaocYT+Zm/U9wqMyaG7IghYIifMclfGx4kS0X88v903zbwv0c0FWt+SxK6zPiuYjByh2z5M08NiefPFE+p7OzWZ5rH6DQ2rlOEA+Z5v32JGUpDzsgzqInasZcLVlRleb5kItHro5gq5DdddheJ+guMt6liErj3YlugGSM+7kfQn/DX0UdmKon9fH7Cb7pvyb9nQ/C+uW8/+q+NxC8+8+jagJTXkror/uLuA/+MIwHexdmevQEiDsrJAsHGC0cRkyAGe8AmnjxEC5sgQhRf42ly097xf0EheAEyJ458dBb3k/Ov8rywBeuETJL7BnC2yZYXQ5sEKVLluWq1UGSmJvNm30rmPRtOgea7ev5p1Crx+Hr/iLyaz9xU3XK05+Eai73zmK5TA3RXcSP/PbnobvMP37oA8jTj8J46Fe0u3SHO3m/o8FGzU5pxCiwaX4+pkQ2s4S3mT6P8nKFB0XdnSjrV6C3BKMd9o1CTMEELogQ59CpFxCJCUkf/wOUTTCTojVBZfNQIuyLTYmdefRJFpyVu0fcipPJLgjH/TLZDZh0D2t84NiJO+n0esTjEUEQ0ul2GTzzaa6ffgI3HgKK6OidLDz8VsLlgy9qnxs0aHB7oSG7X0HY2ank125r0iVDsDU7iDU7jvSuNklteOp8qCzft06EtK2RGoJcASfuOEF3scdoMCQe+49IlUjeF9N3jE/UE+xKFEdffZLWao94fcC5P3oaDpSjfG3PoEdpIfqM6eDEghlO92uSoxwy4td50j6ZE8StFiIOP3wvSZKw9dxzBOtp3kRexsrc4IB0JSBdqbm1lMJ1/eA2GTiC7dmPa6XUlHjO4NrTiHR/xyoklpzsBa+EBs9pi6uJOJzswGRx9Ttqcngn2+VuPbMh2ToVRANuGt2shGku90oQwqROnQjtiwlCgutoXLtgXKYVaHAazHDalkRqGpCQ9V9aCrVVsQyyYKxfdvC1J2b3vUGDLyL8w3/4D3nf+97He97zHjY3NwH46Ec/ypEjR/jwhz/MW9/61pe5hw0aNGjQoEGDBg2+pLF0ELV8GLd1w6tancOGbbaPPsBo8TBKHGnUK2+jFP2D99DauZ7nnNUI3c1L9IPWVJn8YqilC0jbPdisdGUfSjNXJYuTkd/P1pQYFxPgELSzOZl5M1A2ReFwE7WvDgDx/82Ow3jpCBrJCRoFhOMdkuBAyU/PZWSFmcn3WkaEZkw5lVpcyIc9D+2MTN5thkijCCo25VWFtlaKJRWx42Jctk2kNClC4E3dGLgUhZrE5NNVYU6ED1zCB7efzQn7sVg+N77Bu9pHdu3/vjAJ9lfKn38RcEmmBp/kTXYYkTIRpLx6d0I+KknRcTpTtbEJFu86MD0gdbmUsxzcpQrKxFIdwbYvLKzQXV6B66cJRzuI0owXDjJaPJSrhzubl/dX66XncB/8YfT3/ACqYBWt734N0ff8PdzVszDqow4cQy0euLl+vkhQR+9Gf9f/gvvt/wDPfaa0TshsqVEgzqutTZYjWwTX6rJ17CHSVkHBLoKx49zZMV44yI373sbqqUeJhpmN/xzSWqcxtphPXimcCTBFYlKp2ZvM7YPAXjmCuf/LcL/7C1MyuuCQAczP532zKBC/Myrjx38P2r2ZTfZE6uc/xaYw2IZ2F+56GKI2arjjie5feZT/7aOf3bWaH/nV34XhNv/ofV+JmtyzowG191TNfokx3lZ9smhmD7NlM4Em+5g77yyg7n4N8rGf272cc1MyudgemSOADhDjUx9om2JDH7glJsQFrdzJ5GZQPS7zjtMtP3f2jdlrdOW1b2NzpLBpvVLdxEOW/vAXMF/5PjpZ4M3GH36Y8aXThVJCfOUc6zcuc+Dt39QQ3g0afAmjydn9Csfozoh0ydS+ltVQwN5alJYSCHbs7PYiiAFRgtaau++7l063M7O9ttC6kuQkbV6vUhz5ivtprfaw45TLH30SN5594UmoSA8YT7ruhZpdNANH62IC1fYTIbwao6ygx47wSuLJ4+r2o4y431e+lVnExyNGd4QzeboByNTbu0XQuZ7GdnT9cMuxd/Sd8i42c0vtsXnn9BizUzOBoBXjO0Nca/7ASAELjw0x/frt06U9zqtSxKsBrhJPIArSBY1thLENbgO89a1v5erVq7z73e/Ol21ubvLlX/7l/N2/+3dfxp41aNCgQYMGDRo0+FKHvXqWJOqQdBZJ2wvE3SX6q3eyffQBxktHGC0fI62o8lAKG3UZLh8v2e1qm9LZuPgS9nb221OqhLAItpAHXJQm7h0ore9sXGTh2nO0tq8XqlZIlkNXTDiTuxlxKJt4paxNZr7DxQS4oOXVntqACbz9bJFE0YbhygnGxf5MDWhL9flP/d0/1icW5+Xt9p63SGS21JKOSke3owyX7QCbkWp1Ku4ATUsZlnWLAMWKjqaKbnFsZSQ4gEIRKVNSrHd1yLIuf9SfTsu5wndDwcxuBsG4z2DlDgYH7mC0fJTRyjHGy8dJW70p+WQMNmqXAxuUwoUt3D7sdnXddVDNpbzffLi3gp111Ad/mO7GZcJxn2i0zeL10xw4/xjKJoTDTRZunN27ngm215DHPla7Sh85iT758MtGdOdYPgTDqfhHyAIagshbtpsACSJE57pYUIpouMXh5z5BUFTiKoU1rbLGXhu2j76q3GbNOVTiZonr6jOjDjX22Kpaz/oV+P1fRGdBF0qcd42YBPZM8lG/1EjjfdlWe+X8EjsH72bn0D2MV+/EfvRncf/m+3D/x/+I+1d/E/k//yf0YAuc5e/8yh/uSXRP8CO/9Vn+9n/6Pa/AnmC/95Sqm0fdz7xuuW5BYSvuG3LlDK7VhePznSYV+HPo3Eyzog02iHBBhA1apK2F6bNpUkbVz++/6Cjl837x4HRQDurpLtK69xGOnZiThlIcR57+GOqpP8T9h3+EbFwjvn6xQnQXiqcJ/Sf/6EXudYMGDW4nNGT3KwiLi4uzC41idHeLwavapL3p6bY9jTiHGQp64FAjtydxazbTUp4i5SDctpgdix5YT15aAaO4ftV/IEZRxH0PPsC9D9zPsXvuQB2eEt86FloXYqIrMeGNhOhqwpGH76J3hx8o7zx/DTdOMTtu5mMBwLU08eGAZFlnqYvq+z+xNK8i2LJ0nx0RXRgTrCWEVxOiywnOOi48d5bLj5/FDF3Zkrt4PAaO6FqK2d5ffpIqxne12H5zj+HdPiBhAoVXKpMCqT8/M1AKt2hIDwa4UJVIc0WmYLcy/5z6QFSfj3te+LZkBetE4s4T3nXBEhJqRidbjO6McG1VW7VOhIXHhvXbB4pkxZAsaWyo6gMyAkVyOCQ+aEgWNMmKJj4aYBc01y5ert/nBg2+yBBFER/5yEf4sR/7MUxm9yYi/OAP/iBveMMb2NjYeHk72KBBgwYNGjRo0OBLDvbGJYa//lO4/lQurYDO9lUOnnq0THTUqLTFhCSt8txEEA/Qyc2r0fYDZdMSMSlkKtxMvSdA2l5k69hDjHsHEKC/eteUhLIp3bWzBOM+YkKi7avopGyrKhV7ar/QoW2KzmyqtbPednaP4zMP48XDTPS/o12Uk7dCdOynFwbl83FnpXsq4Mtah3hz6zAGRYBiSUdsu4RzaZ/UOZKKSi9E58R2oDQHTLukRFdKzfQlrSHoVkw596oTwVW3FKG1fY3lC59n5dxnWLh2CpXEfm+VhhoFfNpe5Oqrv9rndJ9UYwKSzjI2KLQ5IUordbgg3PP4K6ixCL95yii3kC7Oc4krL5szB6acLQdfiBDEAw6c/RwHzn7mphXA8vz+SMiXC/Kr/ydcfC7/258DQafjGbU8YkvLtE1YuvJMuUKlMmJ8inhhtXyNZOVqelP5c4+/AZwrq42d9dfQ5DyJeGvsinW130/nrbld+lKFT8xAPfgWqAZwFCBA3D3A9tEHGa0cZ7R8jO1RzPr1a9jJftoUBluICH/7Q5/khz/6uZvqw4/81mf5n3/x92eCf14MIliUnuPiMa19vHiI7eOvZrR4eLp6sIX92AeR+78M9ZXfUvsMKtUl4IIWadTFRl1PckcdbNTxwTVRm7S9gA2yvojDJIOX/DwXqPXpwu4yFALG6mD3cD4RvPtFe/uaf08qReetX4/SmuUDBzh53/10C7ddZ/0Cd376V1i68rRfMNxG/uCXGF14rrb+CcZXzuKSfaQpadCgwSsSDdn9CsKhQ4fyD4sZaDBj5xW9Blyn8MHhQKegx/PVxCp2RFdTr+atlNGpYGJBWcnzUw/6/dKgo9vrsnroIMvvuLdcL5lKescRdVp0Hp4OFEZXfPSujsXnwK7tWCZR3iXfuEQa1a2PwFUCZiwEfW8LHh8JiI+GbCcDko0s58+sk3dpewn3MdSYc1zFgO1q4mMhtqKGVln9uyrIVZZHvaaPk+136/+koNpNDT6HDFdAsFFvMwP+tChRc58yyu2yvVJIqJGuzq3z6+AChV0y2MXAlw81Y0k5/dzzWHtrQQgNGnyh8f73v5+nnnqK48eP58s++9nPcvz4cX71V3/1ZexZgwYNGjRo0KBBgy81xJ/9HUjr84GGo+1Sfux5SFs1ObLTl2by2YUtdg7fS9Ja8FbjYdvPMyQjsBYbdRFtUC5lsHIHW8ceIimpqAVrWmwde4it469m+8RrZomO2jRhnhApEqI+cD25JYWl6IC01aPfXbkpu/Q6pXdSad8hDFy6qypcK8WJoMdro1UWdcgjrYMopVg2LV4brXLYdHPieiyWTbm186nnUDVOhFgsqTgGLuWo6fCm1iHe2j7C61sHSShMSzjLgXOf5sD5z9HZukp75wYLN05z+Pk/IOrfmFY657xtHXtVWZWpFGlr1qnAVQMc5pDoM6ge5jrCUyqijkoZr1MtlKvm9K45l4JXTtog8tfmxHnAxmgbE8Q3kUt4t/5/EUHOPok8+Ynadf5+nLWbr56g9tbVmXIz7hAwez1ULb5h5vpQrjrnNauW1QhBMkKnMcpZTDLKCXucJ713m3XUe9l33ywmARV1511p5Jf+5a7W6wpoDdZZvvBY6bjaqFNSyO9FdGul+Btvfw1mznzvj370M/zPv/h70+fafoKLatwoJssnGC4fY+PO1zFa8FbY1bM87h5guHIclGK0cpykvVBq3/7xR5DOUuYwYLJfWVHuz2/q7+uJq4TSBMm4/K5UChe2cTpAp8kXLqDhz/z36G/4q6iv/g70+/4m6i//Qzj58NzyohSbd7yWjROvwdW4GQj+HYfSaJfSinfofe2fJ7x7WufC4hInzz7Kgx/91zz40X/NyU/9R3prZRcKeepRJN4jcE7E2+U3aNDgSxIN2f0KQrfb5eTJk4Rh+cNIDy2dU2OU9QSkmPrXoyhqBwd6YGmdj31eZgu672bst12gSFbqc3AX0b5/leVvfBW6W+5jdNcyq9/xCMoULslCXdGVBLNZIdrFq54nyufgeorZSmfLbFmSRY2tqIwFr/qW0LcZHwyQVqH9QvKd8aFghowWDcmSwbX3uI2sEF1OUGM3s9xsO3TqBwY7r+1gO5W6sg7rGuW9SoToSpLl7la1tuSCJ9QnpHdd3apUePYjTLlioTLMwGE20nLfsvMSXfODCxcpbEfNXDO2p4lPhH5dXeWT8oFCdKX7kqnWjfK/Cvo7fS6ev1Df6QYNvghx//33c/78eb7zO78zXzYajfjGb/xG/spf+Su4/eTxatCgQYMGDRo0aNDgBUBESM8+uWuZ9taV8oJagqFO8V0misxoZ4ZguiWIoJxluHyMtLWAC1qZFWwLJY6wv8byxcdZufAYKxc+T2fzEiYeFjoSMl45NpNneV+oIUS909qtBV6P2otsrBxHiXjFZlW1KMJQyscsFstYbE74xGKJ8aSxtxn35M4YS1/2Pt4rpsUbW4eJCjm+D5o2YYXE67vZgIj9UKJ+9sIryQ0KJYobdsi5dJuLaZ/z6Q4PRSu8rX2Uu8JFTgQ9jgRdrrohg2z7hWunaPXXZ+pW4ljJ7Lp3hdIMl4+XFokJZkiaOsKzbn+qf88IEWxm/ZwrrR26qNKWuq2ybZFMjbw74Sn4nPK5dXcQImGrdH3eqnm6uvs1t7DVFwbyxO/vul7JrGBnNrBAZknpyibKJgTF5wZ4wrdQl5ig/Dx0tvwsmEcgZ9BpTBAPS+foJTS8vzWIg/7GvooGyYj2Ztl5MW0vkLQX9kV0/9/f/S5+9Fu/kp/+7q+ZT3j/ZoHwrju+1eAjEVQN8exVQsJo4RDDA3eAUgxWT5JEPZCpW4iIY9xdYfHKM6yeepTVU49i4lG5jXiM/NYHsuCYKZGNMqWwBB+UNZx5D+pkPLMfLghrAideIpgQdf0c6qG3od/yXrjrYeQXfgSe++Pa4oJi++iDuLBN2lli++iDs2WUKb1X9aiPrsnfLeOhd0mZ9w61CcHS6q7d150eujWbTrVBgwZfGtg74UyD2wqLi4u86lWvot/vM+4P2fiDM5jh9AUi2r9o9VhwlWDrqkJZxT6vta4oa3Xqx+nJqkE5T6ZOCOO8H0uLc1Xmndceof3qQ4xPbyDjlOBwj/DwrE1X98QKwwsb2ceQonUlwd3wqnRvTa5yW3WVCsHAoQYgmxabEdBm5LAdTRwAB0NvCx471FiylC6+jy5SuSp9AtvWBH2H7WloaZKWJk0ElfjcKtJS+4ocNDue0G5dTXGh8rbjxgcOTLaWlkLahp1Huiw9ulOyi3cdjRKFGQqiBVFeEa1HUiKqlcoIb519PmajYpXKVJxdqLfYc9HZsRCv0KdQbz66rowGJRtsBjsO03c+T7dS6JFD2+nmEnnlvY0Elfq24sMhrq2xC8ZPEHQElQg69r9J5wR8vVqBEj/ec/7Y5Vbsc7C1sUl8PCaKmiTeDW4PaK352Z/9Wb7927+dv/AX/gJx7CN6f/Inf5Lf/M3f5OMf/zh33jknl1GDBg0aNGjQoEGDBi8U4vbMxzqTS7YGOo3zT0kAG7SwUWHy2VmWrzyNsimbJ15DOlHG7YV8ElwQpWlvXKS3fhGTjhGliDsrDFdO4Ap2w8qmeQ5xBUTDLcLRDttHHyz36VahvK6yGMKtavJf7wURYdBdopeMCTPixKKIg5A4U3qvuzGPx+ucCHq8KlzGIcRk8xMIBsW2898QguDj1qdf/gmORNwMcb0XtFJESjMq2HPfitZXRIiUxhazkStoS8AQS5qRH4HSJDhC0Wg11eLecCMMLY7skgNei6WzcYnBwZO79qX+3M9apc/8XVHNTwjxiTW4AoJ0jHMWF7ZQmdW9AkQJohTK2Wz/p+TcbjNL+bqa3M7FMsYm3vI9nF7/YkJEZO8AgHnoLKBe99W3tu0XADLaXa2+H6J4kie5tCxsoRKXk27d9Ytl+3dx03teQBZWcGlGRor4827jwpyd7Bmw8EVFar9IaO9cZ7hansNIoh7/ywc/ujvR/V3v4ju+7H4Avv2N9yHA9/z0R7E1rpc/+pufAeAff9OXl+8VZ9GZyteriiGbPAW0dz6YFAec1owXDrF45RnC4VYWzBSWzqN2sHLp8dK5ikZbmatIC1EGPe9ey9u1pXZ1OsZWg1JsUgrAEv0FytUNYBPkYx9Ezj6Bft/fRD7/Mbg03zp8sHoncW9KQCfdFdKwQ5BMg0OUWKRCQcnlU3DigdIydeQu5NQuaRNWjqK7/3/2/jxclqs+78U/a62q6nHPe5950JF0JCGsATGbGWODmWzAxCaxcWLieIoTj7+bOH6ceEjskBs79yaOnQQbX48xDjaewBJgBmGwASEZkITQLJ357Hn3WMNavz9WdXVVd/Xe+xwdcYRYH579oFNdw6qhq7vr/b7vt8nECFKgfuz6yam3DofjaY9zdj8NEULQbDZZ2LvEzP6F4ovpGRehQYQ5ERzGHLImkBMjutVWgqx46KocE7oBFvfs2X6MSlK9ap7a9XtKhW6AxhULeFPVwjc+GYO3pfHXkoIoK3u5LykavI624rem6Lz2BLquSKZV9oMXUkF1BDtPcXnj2+V1XRaW3w6Zc3TLyIryqlP8kqs9ka2/f6Doete54ys0VkhWI72u8i5tkbqd08KGQbGcGPkrkB289CGAYSi457+FTViBMDaOXnW0FaLz6x1UYAphryc1LDDIfqxJgalIkqbE5IupVXF5pLDTBkL3Dueg2+5s+7rD8VTkLW95CydPnuS6667Lpj366KMcO3aMd7/73ZdxZA6Hw+FwOByOpzNCKuTS4W3n6TfnRxLTrCCQlWIbgzSauDJlo1uFoDuzb7iNOGTm9L02qlcnTJ/5EhiD12vRWH6UxvIjBO3VscQ2khgV9ZFJhExiVBySVIYiuTCGSmeN6TP3FfqDG+XRm95XdNQZTXV95zj2XTPxB/YFrEIIqkhUzv2mMNTikGocsp70uS9cB+BU3ObRuEUn59SO0GzqsHBuNGYsujwa6ye9O2Kj0RgSNAkaCUhj+3QHQuEzFKa320dPSIKRR5FKSOZG+nQDJCNihgbiuIPaweHo9ds77s+YIGX0mJAt832vsQJUwTSQOjaNVOiRAgKpY2TYRcR9jFBo6dn5jU4d2BUbT6wCdhWNDuPie1kyo47HIqa18i5OKPMD5Ft+DFGfLg7j8S+hP/Ye9Mf+EPPwF7aNx3+yEQsHtn29bGRxpVE4X+25w4VzoKVCB3XC+jxa+VS2lpk698DweKeO7ezxWL2JfPX3oMIOqt+x/58XumFXRpmd9sNYD/pXTvS8BIzFwxvDv/0/f72D0P0y3nrL1YX9fMuzjvM7b3/VDg7vv83c3SKJM1e9TduIEVrbYi2djL3XAaROmDl9D5X2qn3/JhFeON4ju2wEApBRaPuvlx+KdMbxB6pljm0x+p6SEvWC16fR6ML+bbed3SAkbNcy49G7Mfd9esf0hKC9OjYtrk6VzDmCF6D7XboP30P7y3fSP/s4fN1LYaxdwJDuVc9m83MfY5LQXT10NfWrb9p52w6H42mLE7uf5iw85wqmr9lbjAcnrTZdTxC9XOxOyRfU/n6fOBV9BxgByZQkEXososn24YAweuL9uKSn2PfK6/CnxytuhQZvK4HYZGOaSNlnoBLohrSO5gnzGE8Q7vHK1y0EjEZrT6JkeZlgY82zYz98rXe0Qu9QkIm+Y19ywAr2DVk+tgRIto9H2g4jKUail62mLPIcMiF8cgiXxV+LbTT72PKCeEpl4n8pQmCC8Vj00ll3iNV3OJ6qLC4ucu+99/IjP/Ij2bQ4jvme7/keXve61xHHrgeRw+FwOBwOh+PSE9zwoomvaeXTXjiGkV72m08r30ZA+wFGa/zelnVASklUnaK1eAztVVD9NqrfJmivElenWDl6C8tXv5C1wzdR2TrP7Ikv0Fh9jMbq48yevJu5x+4citZCgPJIgmpBtNZ+lc191xR+e0odj/UVN8r2w87j9zYvTSzsoK9uDtXbKkal7xYhMMofi9MOkpAHw7WC+HsqHhd0J/XDLgy3bJoxrCd9Ho22eDTaYiPpFwRMYwxzqpJ56QywaSIeSVrE6RovxEknhMAbGasSkooo7neZWN+XO3co3k3P87A2S7+ZM4cYQ1SfI/ardoxxNIzSTZ3ReYFcI2w0b/o6I9HIkDr8pY8ZRIurAKMqNs43K/yXaC8o7XNbyi6e88jR61pILso3fM3zEHuODjfd75C8553oP/pPmDtuxdxxG/pP/gv6934e09648PVfChYObvuydfQO9z3xqsTVKcLGHFoqwrkDbO2xDuIsCt5Pn0EKgZYec4/dOXR1p7HUhaPZ2YIT92V91icf6d29P4eidvonpL1mpLR/Yvfmm8tN4lWya9YYwy/8f+/lV24t77EuheB3/9HL+Ae3XA3Kxl5bcdfu91uedfW2gvevfPTz/F9/9nel7xFr6tbZ+Sk1AU2YtlsExsbmX8SSo4y1UKg0CB+5G6M86/JO/0aLbDIG18t2W33NO2B6Ydt5zD2fhO7WtvOUOtlLigmKC0m6wmf5r36Xrbs+Tvvuv2Pjk3/J2qc/hH7V20tFePPMF9PeXJ+4Sm96nplnv8K5uh2Or3Gc2P00R0jB/C1HOfQtN7PnpdfQODiMFhEG/I0EfznGX4sRvZIvzVIQ7vPpHqsQzSniaUk8r1IBfOAgTgVSSea2XV5eviTj9+oB+15+bek3DpGAv5mgtmKieTUUrkfX0S7/smE8QTKliKek7ZVd8oXIBHJyT+6B4L3D56ge7cOdIhOQXYPaiKmcyRUHCEHvaIWN5zRpXV+zvdDL1ltXxAsecWMQ654uji0GIMYWA+w0Pknxi7IQGGWj1s02+ye2E7zT31LdY5WxXueDZStnI0RUsrwSJNOKaFoiOrp8HiHAKz9nA6SUNJq7jMNzOJ6i/Mqv/Aq33347zdy1/P73v599+/bxxS9+8TKOzOFwOBwOh8PxdMQ/ej2V571mzF2VeBWWr3y+jUgWAiM9G/0rAB2nzlhDElTpTu+lM3uA3sxeMAa/s4YXdvDCDkhFWJvJYoON8ulP72Ht8I1oOdym328zc+qe4uCERHujSWhVovpsYVrQXht72J74ReewgDEH7MXg9VtUWivIqGfXG4d4YYdKaxm1Q8TyJIwc7QMu2E9xv/smIRnrPZwub4YisTGGyCR0dERXR2NuaWMMy0mPB6J1ziYdziYd7ovWuTdcIx5EcwvBvKpyhTdVeIjYNwkn4ovbR1XyoGI38erGC+hOLW47T1if3bFvelKps7H/GXSnltJrxcYbJ5UmRmtbrDBwgeoEEReduiKNIC8IZyU9eaWOikUVE4SYQQHJBVO2vtIe1SPnfXQRBHo0KvnuT5C8552Yvk3M07f9Fpy4b3x75x5F/+X/uMCBP3H0338E84F3TXzdVOqYtIjAIIiCBuHgXiEkyYHjmG/8x8S1KeKgTlJpov1q4ZhaYXykR3DJMRf+eDKB3bDJpQZcwBnOej0PEzOKr+1c9PFUwA/bzJ74AiLs8gu//cf86vtuK51v4Oj+tluutkkEwl6PWnoYKRmUAbzlWVfxO9/1DTsK3gaRvh+HfCWOlqhd+DNII2ShYCpz76efTwbQ/R5hGBNWcykLQoAsL3wQb/ghqM9sv90HPgfdHe7f7U2Y3z49QauR1pFaE7RXiuPBfjYOruPwuhfSeeDzY4ViSWudjccfRvyTf4940ZsQ1z4fcfMrkW/7N4RXP3fbz+x4c5W4dZmKbhwOx1MGJ3Z/jaACj/qBWRZuOowYiR0XGmRoUOvxRPFQGKwAGkhkWxe/3OW/hKXTe70e+hL8cAQreE9fNTkWPZ72MDVFuKe8elf2DZXRD98UAyQNZft1b/e9M97mxcFLE45dUhfoCSksQhv81YTgbIzsjPwY8wTxnEd/r1eM9h5bibA9v0fezYKBID1514wgjRYvmWcQG84Oy094LVr0CA8E9A8GpfMIA/7ZyQkAqmtQke1PPlHU3qZib3HPEkrtsjra4XgK8+IXv5izZ8/ywhe+MJu2srLCTTfdxC/+4i9expE5HA6Hw+FwOJ6OBM/8evw3/hBrB29gY9+1rBx9Nqee+Y30GwtpNLmNbkZr63gd9NL2feIgFZgGgnhQI6rPFt3XSWR7ouZIKg06c0WXpt9v4XfWC9NGhWCAqFIUGKzDrvg8YjQxTUsPswsH8HbIsIvfWbfJeb0tVHcTv7uRiSpBd31nh1sZJaKvP/Lb1zoVDX2T0NIRbR3R1wldHbNpIvunQzZNyJaO6JuEnklYTrqcjtvoQa9oIVjyalwbzBXEoJaJeCgqnqOq9JiT1cK0jonpXgqHPGRj2o6a8FjbezXJhHPXnd6LDmrIqDcWoTzcUELQWqG6eZawuQBxhN9r4bfX8dvrIOw1Jk2CNBppNEhvTMgWZiQOORMhKc43Eode7uYQmTB7QZSZNsp6e+fGlZ75TFQzgBk4aUcjz0/ch7713ZjNZXjgc5PHceI+zLlHL3z8F4lpb2A+8gdMfCK17xjJN3w3vak99JqL9Kb3ENemiy7vjRXizRX7fsu77UdI/LL+7nkXNpjFg1CfzoojsiIJoxHG2L9d7NfAHV76DKwkxv6rIdJc9du883+8m1/9k1tLX5dC8Nvf9Ure+pxr0MpDSy9LDDGenxVBDYpKvu2Wq/mdt+9G8Kb0XvpkIr/5n8L+q7aZw6TnLfesVQhU3Ld9urE95IUQNhlCG5sgkV6bcW2mUBQGViwfuw4e+Bx0NkenFmlvwPy+scmFqPSpOcTS4fRzX9m/kSh9v99i+tQ99j4HTJ35MrLUXW+d7/Lr30iPyfc63W3RXz2PfP7rka/7Z8hX/iPE/ivRu0hL0WFvx3kcDsfTGyd2f43Ri0O6+xRJbfilwABJTZAs+rYJ0khvLNHXqFbaj6anUV2T9YGehBDikkaHzN98hNlnHED6ww9EoyBc9Ehm7LRwr0/vgF8QlmXVY+Y5RzjyguuYO7CIyMW4GAG6JrK+5KqlkV0NeqQ6OjY07+7gL0fF14w9DoMfmaJjEKEZO34kgnDJI6kVvxCIUOMvx8jYYBQkdTUWPy4ijdrSdI8ExI2RLzCJQfSMFbSFIKmnseYj2zeA8YoO7UHcfL5v9mA/Csun+2s8Mba8DgTRok8yowpivJE2/r5z3P4IVm3bOz0/+CzyrlHyBScxqI0Eb82K/6pr8FeScof3BPbs28vS3u37xjscX03U63U++clP8s53vhOZ3se01vzUT/0Uz3/+82m1Ls5R4XA4HA6Hw+FwlNHX0F46xta+a60ILb00QjdX6K48G9OcW04YPRYPbpQ/JhjJJBoTI3vT47/hRkXxMoFnVNhOvAA9Eokd+zUSb1gE328ubFs8vSM6odJazgQsAXhxv+j+NQZ1iR6+b5iYqpBMCY9p6TMlfc4kHTaSPl0T0zExbWLC3MMaw/DRTf6YdU3MclIUDqZkwKIqnqN13ac3ci5n5LiRoGsuXOzumaQgblsH+kiBAhBjsvkawscTkrjS5Myx59Ka2ZcJu7Ffo7V4Be3FK7JlZRIi4givu0XQWiNorxG0Vpk+eS/N5Ueor52ksfIYSXUKI9TQoS0lUX2uKKinYvSYZG00Za7b0f24uHjjcXbzVEQmkW0BMOhfbHQaf+yl10PRsGKUNxyzkOMC4YN3Yh78/LbJegDm9MMXsUcXh7n3U2Ou0AJnH8FsLNv9Vv5E0dOfcF6C9hq11RNUts7jddeHz8rSP12IFleYP/vv0FovOP2f2BPRXZzpr4K4ZmMM//ovP8t//vBdpa8PhO5/8OzjICQS2zs7u9ZS9/Jo3/lve9bV/M53vXJnwXsb88+Twvv/F/La58LUXMmLuX1KBe98zL5IInvPyT23FkaPXbvxSHFX2XVg2uswt3f7sTZnYe8VwwI2IdFpIVv29/iXSD57q3WfD+4ZUo255oPuJjNn76d59FoqyeTPPKETqM+QbK1vO7Rw+eTYNNWc3X5/hMRrTG8/j8PheNozwW/qeDqRJAkba+u0Wy067Q4mkIQHAkRkELGxQqYHJKkTOAGDAW3w2tpOS5Fd+9XY20xIpidXYk1PT19SsVsIwdzXHWTmun2E6x1Wl1dZb62PfahHSz7Rgsdic46ZhTmChUbWr3zPVYdYOLqffrvL8rllttqbwy8VkUGmva5lz4rPuiIwFYm/GiMjqD0SUnk8RNck/QN+QagVMUgDhAYTAtJYp7WwceB4kmhRWoE6NtTv7+G1hj/kwr0+eNadXTkZ2nh4AzIyhPMKE0j6h9JzFmpqD4fIUfFXCpKGxFtPGNbqgvHTcXiDODNAUfwCpXNfxGNSK7+dllSsw9tIYZcH2+9cSVCgPYmuCkRsBfDe4QoMem4bg38+/eGbd5kr0IEkni1eQ6KTEKwkhWsOQHU0sqOpHZ4lODDNudNnJlwp0JhqOqHb8bTlJ3/yJ3nta1/LK17xCs6fPw/Apz/9afbt28df/MVf8PKXv/zyDtDhcDgcDofD8bRAFlKyxGRhRQ76muWEyoEAmFtG+1WIigKrSCIrtA0WK+vTOep2LXFKR9UpEr+KSqPEO3OHiKtTeGEHYbR9gF+foVVt0lh5FO1V6M2MO9ouCKnQuW1OYlSI3w2jEdwdozlDjG8kfu40tE1MgKQhhsdNsDtxp2Ui5o3GywkpC6rK+RERvG1iqrlHh6rkOhiNJNeDeO90Xm0My0mXOVXNosrv6p9nOenx3OpeZlXFCuYCPCOGfcDT9SYYZkRAM5fYF1carO29ht78EXutlfSnlUmMCnvD0aUHpj+zF7FxBpXYpDmjPHpTS9Q2Tg/7dAtBXJlCdVaHKxS2f3L+nNrjbShKm2XR4uOTRhlNHyhbhS0usQ7JSfMLsAUnsX3/ZOUhg/dqYZ3jsqyREpHk388GtoqxxKX45YmKTwqt9e1fNwbpl7v/E6+CVh5SJ9TmlqiefBTR3bQdGaRH8/wjVDpruSUkWnrDXujCxmqbgtc/dezu0sG9E9bHYibfd79SKB+e/U2Yz95q21Wk7HZU/+/t9/B/f+QLpa8NenS/9eYrRopIDEInhc8GBmJr7pr/tmddjTCa7/zdj5Lo8ffCr3z08+yfrvOjL7t+l6MdEtZnUWEXFfcvbMH2Ouajf4B84z/H3Pd3mPs+Uz5f6pzOn18BqCQkye23dfkXBe9dJUA0Zu3fyqnJ83z5s2nce9EEZaD4+V32oSIEtq/n8D7hdTfxAw+zU4HXyS/vOHxRso/VA8fY+uLfTlx/5cAVyEp5CoPD4fjawTm7n+b0ez0euO/LnD55is2NTeJ4+OXE+AJdk5mzefSruZAC4xW/woh0cbWZjMdup0gpWVpaupS7MVy3p6guTrHnqgN4QfkX6aBWYeH4QSp7pjKhe4DyFPWZJnuP7Ed5uS8QSc5Nje2nbR3sBtUZfnjLBLyWpnpixOWti8sLbY+VMKb4LlNWQO8fKkZ7J830g1zaftUyNJmYbXL9uI0v0A1F/8CEuDUprPBM7nwWTqxAyJIaUzN8HWG17uz7TL5SMnXsi2SwoyKbbvxUoA9zP/wigxyJgBfp9nRt/IGJyV2Poyhfsef4QRaXFmk0G6XzCCnYu+8JPrRwOJ7iPPOZz+TUqVO88Y1vzKa1221e8YpX8MM//MOXcWQOh8PhcDgcjqcLjanp4W/mHQSX0YfvmeM1P88uRBs5IhwbUgd2YeWSxK9l69PSoze7n5WjtxAHdXpTe+jMHwYpiSt1EqmGIrpUtBevoL107JKISKbELWpjaCtE1SnioEF8oVHpxmRxsAA9o/mMaWOAEE1/JGYvNHrMEb1bwhFXq1ciYcmRaaPbkkBzxO3dNTEtE2U9xdd0n00TcSJu0dcx9/RXORG36ZmEv+ueYT3p0TUxVaFoSJ8qiraOeCja4Av9Fe4OV3ko2qQ/Ml6RCoxlQrc9jnG5KCeVjS8vTJNjjkmTRioXN3pxj1FHtSKDKEilWW/nbZY3A9enVOzmca7Q8XixxcixyoUpb8/eo1Ddph+xFyCuvGnn9VwqZnZ45igV4vB1xPVZ+s15+s15wtoMndn9dOcO0J/eQ3d2P+c//WFUawWVRMgkwou69KaXiIN6YV1xpVlMixD2uVrhyJW4+i8lY2fpEgnrZdsZXJ8miTFnHrYu+sz1P4zA345uFPPv/qo8+n4gdP+DZ11pn5uOtZ0YSUyg5H4rBN920zF+7ztfPtHh/XO33kG7H5W+NolEBWztuYr1wzcSVacuaFkAdIK568PsVBKQpWvmp5W2AxWgNTLq2vYMUQhGI5LE3uPK2jXc8zdw9yd2HGpZZH7pqEXZXaLEUX76oZ236QX4JfHpeSr7jo4vpzxmn/sqhDf+mepNzzN9w4t23LbD4Xj648TupzHGGB5/5DHiaHeRUmVfVHRVoINchHWusKv6WIi3FheEXj8SHDt2jGq1OrauS4nn+1xx7VVMzeQiSoRgem6Go9dehfK2r3SrVCpccdWVNJr2y7op+TQXBrwtXXpcVEdTv7+Pag2rfseWB+uSLllBPOvRua5KUrdvQZEThOMZj3DBG8axl3zXiec9ulcE1nU9gq5Jkpos3af8vqHHv9TYnUsL8yn/8gUg+tZhPjYdCM5GqA17XRg54QuwBspiyYUg3OPZyPbc+GtL0xz4+mvxG1WEEBw5dgXziwtZnDNAvVHniiuvpFZ3lXyOpz+e5/Gnf/qn/M7v/A5+rmL9v/23/8Y111zDuXPnLuPoHA6Hw+FwOBxf7Ugp2XPg0KVbXxwWJxhD0F4tPKhPKg1WD9+UxY13Z/ZbR/j44Ej8Kony0em8xgtYPfosNg5enyvKlhivUvy9LuSOccy7RieE9Vm6swfozB6kN7VEd2Y//ek9RPVZwuY8+JVdr66tYx6MtjhDxFkS7ifi46bFVu6hQGgS6/jMMSpa71YAEyNzjorJCjEWW16ViqNeMxPGl1Qtc3sbY+jp2EaPA20TcTbusJL06OiYTR3yhf4qZ5MOL6zu45sbR3lp/QAVodivGiyoGnOqyj6/wR5Vp2cSIjR9k/BQvMnHOieL/cFL+rdn+2b0tsdB+1X0SCFCUnKt7cZFOS45jl9fUg9j+61DW2KUskUbxiDjcNvx2rjjortzp6u4XMiesBVjcr2mR571CAHLJ+H5r5u8ree9FlEtNyU8GYhnvAC8yU7y+KpbWPvMh4n9Ckb5GOWjg6oVUUfjz0cimZGSztz+MSF77F40oWDmUtxdzMj6DWCEsikVkN7DdnZ+m5G/XW03e/CbGlQe/9LIPXRgXNl+270oYWuC0HzD/jle/8wjw1WOXHO7uoel98HXXX+YG/fPl87S6kf0ot23EIiCOhsHnmGvGanY2nv1xZ3PR+++qM8ZIwToBBmHyKiPiEP87jq1zTNU26tU2ysEYStNwxzmMowdrwva9oRnwztR1lKkWsfMH0h7fsuSeyOYqE/jyusnXrve3B6C/eNiN0CwuJ+FV76VxrW3ECweINh7mOmbX8r8S78FWXlydQiHw/HVgTCj35IdTxtaWy0efegCeuYkZiw+OsMYvPOxjTUf+d5rJGhfIBLD3mdfSfPoQvk6niTiKCaOIrzAx/MuPJk/iiLCbo9Tdz409qMRQPQ0lTOTKwHDGUm4P0Ak5V/IjLIC9CT8MyGqreleMyLSGmP7VAuK7uqx5SOC5Qg5OkRjbDR9rG1Ee9nYwJa8GJCj2nV6LLQSE7cfzSiY4MS2lccCbzNGltRbGKB1Qw1TKT82wsAVR64gqFfwquU/YpIkIQpDpFIEE5z+DsfTnVOnTvHiF7+Yhx8e3u+DIOC3f/u3+fZv//bLODKHw+FwOBwOx1c7W+trnHzs0UJ/5TGSGJkXSgd9bf1q9kB7z30fw+u3WTt8E9oL8DsbVNqrxH6VzVRcGKDCDsHWebrzR564A1vrYfzwYNKg//h2GBulO4gUN2kv08JylzhmuGcS7ow2CtP6JqY7IkI3hYfKCZ8ekqkR4XbMSWwMMjdWheCwN2WT29LX+yRs6ojHoy0SDEe9KfZ69XR9Bp0GdgP0dUJkNLNqKOaHJiE0mopQSAQGw5m4w4PROvkzsKiqXB/MZ5Hmk9hMQj7SPVHYl4Neg+dW9w52ilq/jSxxRIskHkaST6C6cboQQy+jHrXNYtGw315B5dejtY0QT/9phC28EElsx2EM5F4fJVEB2vOH140xqLCD3CnCXKhirDMg4nBHf61WHtaWmR4jPfDkFoOjyyT7MRYPwU0vhzs+COtn7bSpecRzvxl58yt3WvqSY778GfT7/9e4eD23l7VDN5J0tsqXQ5AEo8/f9JgLvr5yAr/fKswTdDfGlyv824xPu0AywXlQRII9/9m9RyfI0WssbTk4FKHTpMhB/Hc6jzB6x7j8bAw7udTNwAM+6WXDS/7rX/K3j5YX4r/y+H7e9z3fSD3w7P0139ICbDFK7p4l4yjtYT3YH023H/KW37iND325PK77eUeW+MQPvx65zTPVPN3pvTb5I8fU6ftGYu13g4BX/xPMbb81nDT4vMiuM4GRsnCcDQKtfMyIe1kkESqJRqaVJDdcJGYklWC02GIwcfSaE6M971/+HSSf+xB0c+8bnSCTyF6VQqK9CjRnMS/+NloP30PS3kx3SFI5cIypm1+KDHZfJOZwOBx5nNj9NGb5/DJnT50efyExtif0CJlTt+RLgOxogvPWrSuS8h90Xi3g0OtuQOz0o/Epypn7H2fz5HgfIgP4KxHe1viXCCOhdyRAV6UVpkuOnQZMBfDHj4uIDbUH+8jI0L66UugDnpGkx3zCOas+HiISg2rp8h/aiUb2ywsZDDBovyUSxgoZALSwonXZV8NoWlqxu2y7OnWQJwbZLf+y39vnER4MSpefm5/nwOGDJUs5HI4y/tk/+2f8r//1vwrT3vKWt/Ce97ynkILgcDgcDofD4XBcCGdOnWT1/OTkoPryIwhj6M7sAymRcYiKQ7RURLUZps/cx+LDtndpWJthY9+1+N2N7Ddib2ppTGC4ZGht+xdjW3YZAyhvZ5HaGOSImGALur3d9Uy9SO4I1wlHnNwdUxTrm8Iv9M6uCUU153JWCGrCY8tYccQYw5aOUAga0kMIwaKqMTVwbRtDhM56ZXd1jMGwqGrZOUow9FMxOzEGCVSEoipU1pvbGJP9d571pM+d/WXyuXkzMuDZlaXS+fN8unuWU0k7+7cAvrlxlCCNlBY6odrvIEdEX601frJNfLEx1FYfLxRp+J11/LR3M1gxye+3hnHgAyFz4KpFWDe4lEN3tp4QnT7YrLDx+nkG75ftsGLgiAC2g9g9dOkOBckswe9iedarkC//Dlg7Y4/H3L7L+gzQnD+BuevDNj7ZCxDXPIfo4LWsf/qD2y4Xe5U0Dn6wonHhrrpxlko7J3LuQuw2A0H5YvcHGD1DWioQwhbfkGqm6MJ7Z1QgL0wfmSb05H7vO61vfMbt9/WeM2u88r9/gOV2eZ/lgeBdrQT2fOSEbCPkUPA2GhWl75F0nm4Y8ZbfuJUP3XeydN0L9Qp//UOv5Zn75rbfhxyJCli74pbCtMbyI9Q2zux6HQA0Z+HA1Zgv35G9Rye997SQxWsRSLxg7P0uo16xsCdteXEpyq12J3YP7iPpdJ0U7z/7riRZOztefAJW4E8S2wN+0B/88HV43/JDxGvn0FGINz2Pqn3l0iEcDsfTE/f0+2mMp8Z/gMmOdSnLdjKMKdEG2dH4awnelkaEuQiTxKDWE/zz9seVDK2oKqJc/xRjEH2NOdslWut+JXbtkmOMYTNuE9cFJveu0B7ETUE0p4hnZPaaAeKGzIRujBn2Mc/FuhsJeIbgdITajG2hgd0gaiOh9pAVurUHOhAQm+HyxkaFe5uJPeZ9XThnajOhciK0/cEjg7ccI7tJ8bxEBpFAPKNsHD3D8duxYeOYPEE0q0j84jxagqkI8MGIYe2vVtDf74MSeGtJMdLckCr86b9V2hteDScZAUlNkkx7kFDsf24MxIb22lap097hcJTzP//n/+Sv/uqvqNWGVervfe97OXjwIPfff/9lHJnD4XA4HA6H46uVM6dObCt0V7bOE/S28Pst6uunkFE/iyyXOmHm5N2Z0A0QdDeorZ8qPKCvtFbYrl/xE8VILxWpPSt0w86xrUKglVfoNS6wAugli0EvG+sOTt2a8NjjFV2px7xpltRw2oKqssers1/VMcbQNTEaK2h3dcySqlEXPmtJn7WkR8/EaCBAUkExIwMWZQ0FeELiCUmARCGIjEZjiDG0TcymjrLf7ZOE61lV4Zhf7H27oUPWdH/H4zG6r4Zi3LqRio1KjTXPoyMlbSlZ9jy+5Am269Tr9TaptFey/uhCx3hRF6Sy0rDW9t9C2OsHhsJeGtGbCd2Daaqs63mR0l7EE5ayjl5pI4Fzfmz7Z9Lp22wLRjuDP3Fh7M4PYT7+Hpjdg1g4cNnNLmLpEPIbvxv19p9F/cN/g3zOq9HR9oUDwK7czbLESZtfauA+HvSSHgiERqrCfePCGTim7Z/Use0pnrrPJXqs5eDgXJf2Xy7pfb3T3l+qvIrr983xwR94DYuN8ojpv77/NK9/1630+uHw3pr+SZ2g4j4kCSoKh3HdxuwodM9PNfirf/GmCxK6gUy8FUmM12shwy5yF9fTGK11+PJnC2LwpGNadk+QcTR+3kbbNmRx8k8Me28riTLPTyv0hx9Mz81/zXPRjRlIYvtZniYNGCHRQqGlj/GCwvvCPH4fbK7gz++lsvewE7odDscl4cIznx1fNUzNTCNPSnSu94lqJQgN/mqC2dK23GHwO0Fad6/X0rZfsjHILV2oiJB9jTCgusb+CEvTcQYfV617zzL/4iu/Ivt3KWltbRGFEVQkcWDsZ7cAPIlsJwghiGc94hkDCbZXdjA8MrJvkPZXF7Jv88zjGYWuK7zVCGlAriV4awkoUG1diB2P5zyEtGXmcl3b7yuGghtbdQ2mayf6q8VocG8zQQKilRYrSJGdl2hWgRIkU8p+IUkMqqML/blMIEEKkimJadtzbL9JimEDGB8whkRC68Y6wgimP217xci1BCMStC9Ipkt+4CmBrilqB2aYuWYfp/7mPrQv0FWRur/BJMUvgVEY8sjtd1P1AqaOLNI4OLdj1bfD8bXOq1/9as6cOcMrXvEKPve5zwFw5swZrrvuOn75l3+Zf/kv/+VlHqHD4XA4HA6H46uFdmuL1fPnJ77ut1YKjjcv7OD125hcL92wOd5L1e+3SSrDB9vCaESSYLzthTPVbzF19gGqW+cAQXdmH609V49HEueR2/To3imGXAi0VKhcX3GRjteIS+/ujo1mSnispo5sAdxcWeR80uX+NN78an+GJa/GtAx4ONrkqDdFLXUADvakIXy0MVSFRyXtR3zEq1ERir5J2Eoi7oqWMye3QnDIa3DMn05/c9s1aawoKIRACEFD+AgEG3oo/kRouiahLrZ/vHjAa/BgtFmYtpL0mFcX1mdVIqiObGtV9/GkxEuPw2YSclb3CHyPqyPN6JmScZ/GymNIo/F7W8R+jaC3aQVQIUAKvO7W8LlGKmDmY9Gz6yD3xGzQR3tXTy2MzvoUC51kPW7zEdTkIqgL3tD0HBkvsC7KS+Tu3C3mjtug10a8+nu+glvdPXI3vcNH3vexX0UlYSZwG6Azs4+6OWOjzI1BJSEIiUkLc0zaDkELaR22hRSIoqN+t5TNv+06xu5hJr1Mtr+vFa6z3VJ6v9x5PTfsn+cvvvcbec3/uJX17rhw/PEHz3LlL/whD/30t1MLwEg5TFcwBi8JyR+FbhhbofvLk4Xu//PzP8711Q60V3e/f0AiPRpnH6DaXs3O55NtwbECfvEzxRYuaMhNe2IFFDtsH9Lr2t5z8kkQ5SL4iKO/Wkd84fYs1WBQCKI9L3cPk3af9GBZg9laRcwsPin75XA4vjZxYvfTGKUUe/bv5czJYZS5jHOhOMlA0R2PKLEiq4BAQJj7YMulkYhswSHx+lens7vfy1UUDwReSGNhTPE1z/a31rkveiIeqdYzVoBOamm8ef61JO1xHg2/+OqKyNZvagLRKf9SbNctSOoKsTns0TPYhgBkYorVcvl3uRDgCXQVZC8XZTX4fSYFJhCIfAGrKC4vDVTORMSzXkGMFwZUaDA9jamOP6SQFY/5m4/gT1WZOb6P1RPnitdcyf5GYYhZ6dE9u0n9sRn2vuCqy1457HA81ZmenuaOO+7gZ3/2Z/nZn/1ZjDForfmRH/kR/viP/5hbb72VavXCHio5HA6Hw+FwOL72WF8Zb/OVJ6k0x6apuE+cE7u1V8EIWewtmv74iyoNjPIRcYgpSaYbRcYhtc2z+D3bizfobtBcfphz17yUqD47eUEhLt6NXda3djfrGhGGZNxHaL2tMO8JybX+FGeSHg8nHY76U1Slx2E5hUTgC8mSquCFXfYATX+eINfntiF8Gzeei0Ff8upUhMxiv6eARezQvhSuAzai/NG4RYLheDA73AUYE29rQtFCkOQeBvVMQn2Hx4uBUKiR5XZzRgQCD5EJ8we8RqHXd1fHPBJtIREc9acQAk7HbWIMDxPS8n2uaW0yi0QYg99dp9JazoRrAQT9rWJ/byExKoAkJ8yVFTeUiUA7YAAV9bJI6sE021t5sF/jT0eG8xbPiJHKxgmPxO2Xr+XSYe7+JOb5r0fM7nkSt3Jx+PN7EUEFE05IDjAa1W+RBHWM8jEIunMH0SqgsfIIXr9lrwG/SnvxCM1zD1FpryKyayTttYxBxv2hWUbrzEl/uTIKd73tXc04+u4fOHptwYUBUB7GaHtsjGG53eNL5za479wGXzq3zn3pfz+8urXt22O53edbf/OD/Mn3fCP1SnmrQ9id0P3HP/NDPOPwXuTp+4p9zHfoMQ7gR138qPhc+ytSSFJycMZP0TbO6ye6+dw6y0T1wpSybX7+Y2MJEiotAEmCXNsGITGC7H4lmrNPaNwOh8MxihO7n+YsLC7iez7nz52n1+1ipBiKtxr7ISUZ/vgb7e9SkWhp3cJCs+MXIln1J7/4FEZ5428FgS06K/tmI4x1cxsPG88txw+M0FA5Fw3qCUY2KEjqNhZexCByLm0TSLQwyJ5GlLQ6AXte4hmsQzsyGDXcvkjswI2yFcmkxXmF5QfbCNNtmOK6tTT2nJvy4s3K2RjZKY+ZU60EnRgb756OoXFojtmvO4g/ZQW2hRsOoyuS85vbPzzJ73/n7AYbD55j9vi+bZdxOByWf/tv/y1veMMbeNWrXsXa2hoAH//4x9m7dy+33XYbz3/+8y/zCB0Oh8PhcDgcT2XCcPv4Vp0TtcdekwqERPY7xEGdzf3X0ptasiJfEtNvLqC3c2SXEDXmOXvNS9l/zwezHscqDll45LOcuf5V2y/8RATvsnVth9EEW6sklTpJpQ7GELTX8KIeYW2GsLF9tO4+VWVKVagYg99rIYzmmJB4UZta+0QmzE4rj05zkV66PiGsMIwZ9t8G6BvbLbuSE2yP+FOsJn3OJUNh52Tc5qg/lQnjANa7nCtSF4KKUIU+4noX8lpkdEHoBhu3vhNH/SkWVZVPdE+jEHxdMEwK2Ez63B9uYMPiDI9GWySYbDwGOEvILWuPM9OfbMywjspiX3QjZcHskU0HBg/GBomIwxf1jteZgJxomptmNFoz1rt39IGMMAaDLhRhGKkgGT6fEdjew8JopC7u16XDYB68E/HsVz9J6784dNhj7ZPv30boNojE9mAXvS3C+hydhSNor4IwCe35w0yffQCv3yLorFuxzq/YfslpP3YDkGwvgj6lMwmNsb3Fd5jNXt7Fh6Lplc9Ku88nHznPfefXue/sOvedXeO+cxusdnZuTTCJv77/NG/6zQ/yJ+94NfXK+LPlzk5Cd6PGB7//1dykVjCPps8ac+kIg/emeQI91b9SlMryxvb3znrCX4L9yNnhbAHDQEAfMRllrSp2UTCQR+oEncSYXFGW3Q7IA1c9JYtlHA7HVzdO7P4aYHp2hunZGZIkYbN5ntV77ReDgQPZJDYixXiCsXwnwPgS49ve1UZBcH7yl+XG8aUnZyd2SRiGrKys0Gq1AGg2mywsLBAEk3+EA0zPTHNmJPId7DHSgUT1xn/lCGMd1YkQxNMyjQYfmScZfBkoQQl0TRDX7fJ5jC9IfBs7LkKD6o6vwwSSOJD4y1GhzzhYoV1oGzWvWpDMjr/V89sYK3LwBcYX2fbLRHd/S2Ok3VZh24DqamTfsPc7bsKbriLUeDX80jUH2fhii7A34cuwNshuceWbD593YrfDcQHccsstnDlzhte//vV88IMfBGBzc5MXvvCF/ORP/iT/8T/+x8s8QofD4XA4HA7HUxU/8Ol2Jr8ukhCtPMLaDNqrgtFo5ZEEjeHD7UqTx5/1LVyq/qI6qNFaupKZ01/KpgWddYL2KmFjPDL9iWMwiKz3aubCnTi7we9uItHIfguMxu+3UVEPLT28fos4qKP9yrZbbWiDF3WzWGV7NAVaBUhthVuVxExtnAEMvdy+e0KiTUL+13RoNAGy0BrssN8siN0GGy2+32sUpo0yehbLjkZiNBKRbc9D8MxgnvvCNWIMU9JnXm5/DAY0pM9Lavtt7/CcEL+uQ8LcXuaF7iIXXuRgizIihI5TgTn17MqheJaJgYPrQUgSr4pMoosSmYXRGCOL75PB86ScYGdjz81QGJ/wvtJeAJFGmnKjwhMmebKE9Itn8/OfJN4oMVUMnvUlEdqrEFWnQAi0kKh+i8bKo8gkwgiB6ndorj5W6NmdBPXs/fxUFkoH96d8r+jWwhWouE9tc9ByQiBk6sje4doYiNuD/wY4tdHmlv/8PlbauxO2pyo+1+6ZYalZ5TOPnmd5G0H8r+8/zZt+4zb+5B3fRN2317cR0A01b/nN2yYK3QuNKrf+4Gu5cf9sYaxmNNZdCEA+BQVvY1sSZO9piTQJRhtbzGK0NacrD5I4vTdNcEddzLbTe9jgfm20LgreWRHPhUfzSx2TjIjdVOqol3/HExu2w+FwlODygL+GUEoxfXQJ6RcV7TTQxVa4TbgikorABJL+Pt/2qy5B7K1TPTJ7KYd8QXQ6HR544AFWVlbo9/v0+31WVlZ44IEH6HS2+YWOPTb7DuwvfU34kmC6vOLcCNA1Cb4kbpYfPCNABxN+fChsj2spICr5ASZsrDi6/MeZ7Gm8zQR8gS4pVBCA7Gr0dmUtgy99pb9ibYHDpO1rxcSq5foV8/hz9VKhe8D+IwfL+3Abg7eeFGLSAeJdfpl2OBxDgiDgtttu49d//ddRaTykMYZ3vvOd3HDDDayuXlgfK4fD4XA4HA7H1waz89v30jQqYGvP1YT1OZKgRlJpYFKHZEGky35zXhpndXdm/Le76m//m/+iERLt+Wgh0z6k3ri4aAwiDhFxhN9ZRxhDVJ0irE0DhtgL6Mzspzuzj+7MfiuW7yRASklcaZConMNRCOJqEy2LP/AbW8tjx1aVPO6LR370N0r6bE/46V8gGdlWZSTiWxtDhCYkGToChWCfV+dZ1SUWZIWbK4vlzwImUJd+QegGmFO7E8tP16a2fX1M8NMxfncDFfeRaUS4NEl6XRcd1MLo4rkUAp1GY+cZRMLnSVRQOL8im3MEo8fOr8hPG3nNkLq9oeiovMSIQ9c+aeu+GJJeh/6ph4cTjKayeY7p019i9tTdzJy+Fz9s0507QDi1SNhcIG7M2edOg1hlY9BBja2lK9H5956Utu3CV3aXCpRdQ6Yga0PiVQgbc8S+TU0IazN05o+wte9a2vNHiysQclfSZfbMOOXURqdU6D482+BV1xzgn7/4ev7rm1/Ibd//Gh77me9g+ef/EW+58Qo+9OVTmdC93Vb/+v5TvOk3bqUbRggM/TDiLb852dG90Khy6w+9nhsPLmKEKu4iMHbUxOgeXX4E2KIUnWCETAVuYwXtJE5bFRjQ2n5+5NogPNHtDvSAMUqmXdRHeMlC/hu+H7lQ/gze4XA4ngjO2f01Rvv0GjpKrKhtrDvZCDCeIJpT6IrEa2nrqDWASoXuVOA2vqBzfY3gVIi/EiNj+3q0xyfcC3PtDo1mY9sxPBkYYzhx4sSYMxtAa82JEyc4fvz4tj+m5hbm8XyflfPnabfaCCGYmp5iZnaOk/c9gghsn+3B9yRdEcOobmNjuyNhXc0iBlIhPG5IvHaCFtYJLrQ95kldkkwpu7w2qI5BV8VYv2vZ0XgbCboq0IHdnogNaivBX4vtF/PEfl/T3sDVnZ5XX9A7EtA7WsFfifHWY+Ro8d+gQs9g+7hLbPy5sRHrsqMRERgfe8cY9OaR4HWNjVH3saI4gLa94cMvraBfESOrk28zjekmV1x3FctnztNa38Rog+xr1FaC6o1/IVJfpTH5DsdTge/7vu/jNa95DS960Ys4edL+UPziF7/IwYMH+cM//EPe+MY3XuYROhwOh8PhcDieSjSnpphbWGRtZbl8BiFsz1shkXGYPXwXaVSw8Z6k328lv+tHe2HLuI+RXib6PdHtGeVZl2De1W0MfnudoLueCaaJV6E/tYhOxSb8qv29nfbzzcavddpSbnsPSuJbp3C2x0KQBDVk2rccbFSsH3aIKsNnMbsRQvolgvucGk/Fy7u0tTE0lU9gJJs6wkNQy4nmidFEqdvaADEaPxchOC0Dbq5emkRAke6lwkarx2h6JmFOVphRFSSwpUP+fmqWqzdWqJYVGKTX6vCfhurWcqkbWkAmRuXd3Rhjn/dkMwrioJaJ5YP5Yq9iXd/Zuo3tNd9ZR2Uu4vEzN4yTloVpmAQjvDGHp5HDgoxtUwieCAePIw5c/eSs+yJJ2hvDwgNjaCw/it9vZa8Lo2msnSTorHP++EuyNgzG8+k3F6lunh06gpVPb2qJ+vqp4QakwigfkXN8XyrK+qyPTxNWoDb2XmLSf9tYaJuqEaeO9aTSoN9YoLV0ZebQbS8cobZ+KnetYZc3F+YQfu6RJX7/7a/knrMbXL00wzX75rl2cYppX4xdvSfW27z6f97KRx84nU27Yr7JI6v2vHhSEJdU2Pz1/af51t/8IP/77a/kH/7OR/jQl0+NzQM5ofvAQro/grS/wPY7sYtZRtndOXpiCKPRQiB0nF3LCoGWCpF7L2u/BkmY3V+eOMX+7KWH5yKTWUZ7gIt9x5D7r7yodTkcDsdOOLH7a4zNx9IfqQZ0LdeXA6xwKwXxjIIZZX+MRSMf2tJ+UPWPVOgfqYxFYK+trl4WsbvT6WzbTywMQ9rtNs1mc9v1TE1PMTU9ZfvXpPt17nEb9WM8ifGwP2R8AV7uyKT9ekxFEldkOo8EX6BaSebQNoFdPmkoGxufIiJbTyl7hiQwVmxO8bZsvI7qGVTPdrnyN+JCtLiMhuchaebjeSDc64OyBQnRHh+0pvZQiMwnTg1+awnbizwfTSPitNovMhCl/bimJGhsxDn2/2H065Gme885Grcc2PaY1xp1Dl91FID2mXXOfuqBifNOHd3eWeBwOLbn6NGjPPbYY7z97W/n937v9wDo9Xp8y7d8C29/+9t597vfjZQu9MXhcDgcDofDYdl/6DCNZpNTjz9WWlwO2OjVEbeyMAnGlLigLwEiiUhUgErsM4CoOkVYnx0+nzCaoL2G0Nr2Bh9Ehpf0U5ZxaPuL7ySKl7kBhSCqT+NFHVTUA7BxwWun6M4dGArewsZfm5wbT5BGxW6ThGYHqDBSFQTNUWc3jLuTxxygxhCT4OcEk76JmZcVVrV1Wy6qKnU5XqCgsXHA0pD13Q6EYkbaHuF5U8FoX+4Eg5d7vnKhaGNI0r7hEhvHHpFgDHR1zJX+NPOqikzXH5mk4ICdURX2Tje4bX/CS889zmw8FPpaUnLS99jX00gMD9fq/M3UDP9i49TEh6UCIIkwys8J3sYKzDopFDTElSZev1UQpLRXQURdu55UqIyrTVR7zS45SELIrtN8l3D77+xIGmzceu7cayGtI3mw/KT37BPh4HHkG37o0q/3CSKDYQ94v7tRELrz+P02zXMPsHng+mya8QK0V0HFQ8dyWJspit2AlqoQb37pEJloPTzXA19y+qQtK7KQw/j8XFFDVJsp3G/N6H1NSPqjAj6jz/GK0xEijfG3yw+KJ9787Gv55vlD9BvzIBVxHNLZPEd9/WTWyvGPP/8I3/eeT7DWtfdpIeDHXvZ1vPfzj2Tb+NVv+3r+zV/ewXK7N7b9v77/NFf9wnvY6pcf7zGh+0LYQeg2QOIFyCTOilPM4HMua21A+rlnBqUHlwArdI/mQkgdp0Usg5YJtqWFMP0do+h3t1X7GTHWQqFw3xaIV38P3Pobu16vAWQSAz20VwEvwH+hM1k4HI4nDyd2f40Rd9IvGWm/aRMMPigpCKyA/THmGYi3+dAe+cEShU/Gl76d2U7oHhBFux9b/odY1A9HX0TEYORQlBajlYjCuq9tBPjYypE9TVKXw2M++D2EdVLrRq5SOB6JqwKShkJt5mJr9PCrsAiNjT5Pyc7xACkJ9/lUTkZjMeGD2HKZDOOwRueRgO4ZUONfiEf/nWxeWOx4Y98szSMLtB4b77EUzNSYPb73gtbncDjGkVLyu7/7u7z1rW/l27/92+n37fv0t3/7t/nIRz7C7bffztGjRy/zKB0Oh8PhcDgcTxUazanJQneKkQqRFCOeJ8sokxFxaKOX04f6qt+mvn6K9vzhTDzuT+/l9Ne9mj33347Xa7F69JbM/Sq0SYVuKzAG7VV6M/uGzy5SV3Vt7SS1zbNWREAQNuZoLxwZCtS7RSq6M/torDyaiTwCQ9BaoTd3MLdjoyLmBIFhN8doRNxIgGWlmM7Pg7G/3dN/90zCmaTPjAzYo2r0TULHxCx4VbxEEhvNM4K5idu0gXLFhwN+iWtYIsb6Zl/4VWBF7k0d0jXDKn2FQOX7gEuZ6yks0jEpTBqjPhiFLySHZ4/ybl9yuNdhJopoeR5frlbpoQvPf2q9NrUdelGXCd6DlAOSQcKBPd+JX0X220NhTAiM9BA6ztIIjPKtc7NMbMqTcy2n/2HFbCEYSKRaKmTcHwp02+7JxSFf8lZEffto+MuBNzWHN7tIvL5M0Fnfdt762omC2A2Mid1IteO1W+bsbc0dotpexQt311qhUOQwELIRuWtBFP8tBIjx9pQyDoeFPYAXdce3lSuUye9bvqRCS4/u/GH6U4sYqZBRj0prmcrWcqFYx+u16Det0Gy8gO78IeLqFPKRz/Nj7/tb3v3p+7NtHZpp8Fv/8KXcc2Ytc3W/6poDvOP51/K8I0t846/9VangfcmE7tx7axDzL/PFKSNo5WM822bARD2kMVnhgJEeJonH4r8v5j5XGCJg0nvaKAJAxxhZvOdo5aHinZ+H72bbE7Y6xA/gU3+26/3Mrikh7LGuVFFv+EHk3if3WZN5AsVVDofjqx9n3/oaw6sNI6lkZHs+kxgrlpY1Z1IC4wuMTAXgHT4wfP/yxEzvZrsXOzY/GF/OispAbOO/y/pSC0D0y7rqgNCg2hrR1+nyw+MqY1AtjQg1aDOMB89hPOvA1xVhBXNvuH2ZpO7s2FixOhx/KJE0Fb2jAfF0GsOeK3QwniDxhY1BF/b/R5GRQfRHf8KOo6Z210Mrz9ItV7B0yxVU5uoIT+I1Ksw94wAHXnId0nf1OQ7HpeJbvuVbOHXqFNdfP/yR//jjj3P11Vfzrne96zKOzOFwOBwOh8PxVEJfRKPOvDNxgEjigjjg9bZonnsQOXhYrxMq7VUqm+cQSYzQMY3Vx/B7W0yf+fJwPmPQns+5q1/MmeteQb8xb6NShUDEIZjYxo57PkiJ192EfNyrlPSnl7J+xgJDpb3K7Mm7kdG44LIjUhFVi+KfF/VsFG3xCFz4ugd9W3OokTF+Xml+v/0Qn+6etYtghR1PSBSCno7ZSN3bGzrkdNzmTNLJuZ8Drq/M412CyOvBHibGEJoEbS7O8SiFoCl9VG7pBEOIzvqAg73OOjoqTBNCjD2GqUjFC+r7OVOf5vPTszxUb6KEopeOcUDPC4h2IZQIyM6vyYuR6TE0aVqWSft365wwbqQk9qtZjDZgew2nfXqHvbi1LWzQOi3k0JmTe/BnxXNlo6qlQhpdEPC23ZMrboCbXr7jvo5ivvyZC17mK8XU170QlCp57xUpFwhHjCZl85iih9f2V/ayaf3mAr35Q6wffCZRdftkyWyLOYd2dg1djFg32rs9dR173U0qm2epbJ3H624Okw+ESJ/5yWE0v5AIo1FhJ3Nxa79Kd+4Q7cUrCkco6G5QWyu6xD99co3n/Jc/Lwjdb7nxCj73E9/Kcw4v8u8/9PfZ9F947XMAuGH/PB/8gdew2NhdoVFe6B574moMoz3uxeg0IUF5aC8Yi9g2QKwC+95M59d+xb7HdGL/0vcdacd0cclc3Wx73odSfW684hK06diO/AGOQkxnAyPVjs+CM3L7I9obiMbMJR7gkO7j97Py0T/h3J+9i3N/8W427vwYcXvzSduew+F4auLE7q8xpo8UY6BFYuOxvY5BtSZFkgmMLzl2/XGW9u3Zdv1zC5MrgZ9MGo0GQTDeW2qA7/s0GhcXrz67Z750uq2chPnpOY7f8IzSyjEBmFHH/OA1A6pv2DO/xJU3Xld8LQHVMXibGqMmfNlRgqShmH7pMZbeWKxIFRpUaFBdQ/VkeZWfrkr6BwLmX3Wcpa+/qviitP3BdUVaQb10/GL7O4gnqV1/4b24hBBMHV3k4Muv59gbbuHIN93A3HUHkP6T/CXO4fgaZH5+nrvvvpuf+ImfyO5hcRzzvd/7vbzmNa8hjrd/SOBwOBwOh8PhePrjeR5BZYdCZp0UxZZRwcZovP4WfnfDtkxLYuqrjxN0N5g682Vk2KPSXs1EvMrWOaZP3wfa0K/PE1WnCbbO43fWqa+dpLF6gmrr/DAiWkgQEl2pEzaXhr26hcBL+lQ6awXBW/tVNvddW3hoL5OI+trJizpG2is5PmWGglF2KCTI90IHkFEfmXOffkkZ/iqw6/hc/zwPhOvFfQI2dViY1jLxmFiRd1DvhDaG2BRF5wGRSXg02uKL4Qr3hGt8MVzh4XiT+CKidj0hmVPjx3XUYa6BZCRSzxOSU3GrsN09qsY3Ng5RSQWiwe+fvkmyfQmV4s657Z97ZaTCdEHIzoTDXH9d5VlH7WB+6RNXGsiohwo7yLBnhW0d257eSYRIovS9YMU0aazqVAwVxk7Ppy6k4veu5LetVUS3vbt9zRNeREHIV4hgYR/zL34jTG//LCqqjAjRxuD1WsX3o1S0l64kGRQlaA3KIwlqqUg8FKaN8ujM7Gdrz9XZsq3FYzuO94k6gbVUJMo6kBPlE1Wa9JoL9JqLhPUZGssP01x5hNrmWWobp0FAHNSK4rpURVESqG6dpzZyL4zqs7YneI5Ke9WmFCSa/+eP3s8b/tUv8eC5dQAagcdvfPtL+N9vfwXz9Qr/7+13c3bLus2/7aYreM7h4fPpG/bPc9sPfPOOgvdCvcKtP/i6XI9u+17LHPZpDLw9QMPCEevC1mjS92cqWmvhYYS0x9Cr2vu4tEUCaQkLAuugtv+VTkvPff5O9BXxEo/dc8fvwReT5mD3ywzTI9IEjcJVMbhGRq6XXaMTzJmHL2J0O7N199+x+bmPEm/Y1q0miek99mVWP/6nxFvrT8o2HQ7HUxMndn+NMXVogfre8kqq2WqTyoQfsHv27KFarbK4tES9Xi+dZ35xgcYOPbGfLIQQHDx4sLTXrJSSQ4cOXXSMSVCtsOfwvomvLR3eh+d77Dt2qHQerxYwvb88Wqc6XWf+6B6CeoXFY/vLl5+pUj9QXkRQ2zvN9BWLBAdnaDyrfPlmUp0o9M/MzTI1M0398ByNo+VjDI7N4e8pP6/Vm/chmyVFBgJmvvEqZO3yOP0dDseF8Z/+03/i9ttvZ2pq+OP11ltvZc+ePdx1112Xb2AOh8PhcDgcjstOFIalv7UzjEbqGDCp8xG0l4tb1Qler5UJDkFnjekzX0IYTVidJvGr1NZPkvhVutN76c0eoDe9l9bCUTpzBwkbc4SNOZJKE5EMRXVhDH6/RW3zXEHwM8ojrBWfewijx2KFk6BGVJ8tTKu0VnYUoMsYjRbXUmXO8QFebwuR7/drtBU2R5zb2TrjEJWLIu4pn41qk63mPJvNBU4tHOZPKxDnHnV8sb9aXIcQ1Et6fI8K1btx78dGcy7u8mi8xWNxi0fjLVaSXmHZqvQ54DUYhPFq4FzS5Z5wlWTkGHmex9HDhwH7cLLsCvNTYTo/Xo0hGHGha1NcXmD7e59PhsdPCEFTBllce2x0ZlzUGNvX3Gj+7NBVrPs7p9QJbP90o3LPPYR1cSdeQOxXSZSPFhIZ91FR1/7FPfzOOl7YRUV9vEEP75F1l00rHceIkxWGzvJtWTmJ2cV+jlF76kWY5/FnF1E3vITu9F5a84dpzx2kX5/NnMoAcW2K2trJ7P3o97ZQOkKYZOgOxqC9gM784bTF36CwRpB4lbSH8vCsaC8o/DupNIiD8uenOzEobRiI6lbYlmjlZX+xXyMJ6mi/gvar1tWfxMNCIyFJKnWiSu55oBBovzoU8LPpckwkrY7cVwHCRvHZpDCa06dO85af+c/84u+9jzhtZfHcI4vc8ePfync/7zhCCFbaPf7vj3wBACUFP/uaZ4/trxW8XztR8F6oV/jgD3wzN+2bwRiTpXlkbngdb9u/epDGIOIQqRP7ZxJbGJJ3tiNSN3ixeEt7QfEY5ZIcLgUmuMAWGjD22TFspHFxz7/FYCU7PD83F7vf3qV/RhxvrdN54POlr5mwR+ueT1/ybTocjqcuwpSVYjqe1hht2Dqxwubjy8TdEL9eYfrIIs2D82itWV1dZWNjgyRJqFarzM/PFwQQrTVrK6usr60TxzGVSoX5hXmmZ5+8OJLd0u/3WVlZYWtrC4CpqSkWFhYmivgXQntji9UzK/Q6XZRSTC/MMrd3AeUNHcedrTZrZ5bpbLWRUjK1MMP8vkU836d1fp31k8uEnR7K95jeN8/MgUVkLgK9vbbF+snz9FpdpKeY3jPHbDpP68QqW4+cJ+r08aoBU0cXmTqygMj9iOk9sEL782eIVzvIuk/9GXuo37AXlGRtdY311VWiKCYIAuYW5pmZncmKAIwxtB9ZYevB88StPl7Np3nVEs0rlzCJpnP3WTr3nUd3I7y5Oo0b91E7Nk/SDunceZrefcuYWBMcmKL+7IMEB57aP4AcDsc4vV6Pb/qmb+L222/Ppgkh+Hf/7t/xMz/zM5dxZA6Hw+FwOByOy0EUhjx8/32TE3+MRkW9rF+1QZAE1aIIEHZsL+eBay4Vv2VSdC0nKiCuTRddhkmM6reLjtYkwh8RrsPaDFG9+EwiaK+mInw6VCHoN4uOz9rqCRprJwrTlq983rYiRlmfXhl2qbRWsp6//cYcUWOYEiejHkF3w8bkVppo5aeu3VRsVTZyfbgRg9/dKGwjVB5bI9HIH++c4oFoI/u3QvCO2WLy23rSZ0OH2ZgNto91TSgCYSNpAyTVElF8lI6OOZuLQAeoCMUBVS8YDFaSHvdH64VlD6oGh/3ic4JEQkWLwrLamIJ7+2zcYUtH1IXK5ptVFRKjCVNxqy48qtKzojXQ1TGPxfa50D5Vpyo9poSPFDbW/X2th9nUIf1UwPRSJ2OUrm8m7PFPH/wiV7WGxxbs9W3jjyVCJ0S1aeKgPozET2KMKO4POqG6tVzooTzoG1y4ztLI+kl9hLdDCzl2/cgJRRQZyodv/ReY9/5n+54zgz0s7q99TRfls6tuRr7u+xFPgnj1ROl88VN07/7U2HSRRNTWzxDVZ+jOHQRssUIcNPB7w/daWU/i2tpJKu2RQpKR1IWoOsXWvmsK80yfuoegu32Uskai/WCYRqGTNI5+yLCv90iRh/QKfbgB+vVZkkpRZA9aK8XrQWv83mZxP9MkgTzrB59JkhPLve4mU+cfyv79R5+7nx98z+1sdqzbX0rBj77h5fzCi47ip886tfL48Q98gf96qz0n//QF1/Drb31xYTuZS94YvnBqlW/6tfcXengv1Cvc9oOv5bqrrgQhkWE7SzsYIHRi/7bre89QEM5/zhiELVopTKP4nsJeQ2PvK51cGlf3m38Mc9tvQms93ZgYxstDti9GelnLAxX1svvFWCS+1hd1LzGIrD95Nm20ranWhc/W4bJptLoYbD8bmT1vL3wj4pZvRFyEsD+JrXs+Q+f+uybPIARLr/lO5CXcpsPheOrixG6Hw+FwOBwFfvmXf5mf/MmfROcquZ/97Gfz0Y9+lOZlSvBwOBwOh8PhcHzlOX3icdZWlifPEPURaYwvCPtAfvTB+AREHI4JuolXsYJ3Dhl2x3rs+r2tgotPS4/u3IHCPF5va0xg7E8VI6rry49S3zid/Tv2q6wfuXnbces0OndMmDSa6voZjFT0p/ekIqFBhW28nGBvhCCuFEV9LaTtMZ4ff7+NzDnBtRCsjQj6f9s9wz3hGpDGDwuP75q5Nvu3AdbiHoFUNFKxN06FNHWR7rxNHbKcFKOsF2WVaZXrQW0Mj8VbnE46uWmwpGpc6U8j033f1H0MsCCrEwXvU3GbLR1RFZJAKDwEzXRbPW0j2WdlBSkEBoMGTkYtWsYeuzlZYY9Xp5q6xLUxvHvjXjq56PbBscozFYX83Oc/SSUVtxKvQlxpjIlkcaVRdPGnzuBRIbG+dqpYfAFj7mC0RpodROoSLkrs9quYSg3aG2MtBzJhbSAAahuzXig6ufFlyFe9/YLH+mQSb66w8YH/b+LrBkiqF27M8DsbNFYfK0wTcVR4/4e1GVp7rsLvbiLjHloFNM89iNqhf7gBEr9STAhICx/kiFO5IH4yKJSpFO8l0qM3U7zPqX4bv1+MrPe7m0UndInYvXboBnRQy/5d2TxHff0Um92QH33v7fzup+/LXju4NM+v/sg7eMEzj+N31pk6ez9SJ3xJLfDsn/wV+lFM1VN86V9/G4dmG9n4M1E3t++PLG/yr/7i03zx9CrP3DfHz7/1lSxd/2zMwJFuDEFnncbKo+P7MCo+TxK8SwoH8iLvsMCgWLii8ukc6bTtPu3KiqPG2HPEvg/bo8U1xXMuctNkEheFbsTYPWA7p/vk8e5G7E4QWheO4aD/e2EMOrHpJfmV7T2GfOtPXDLBe/Ouj9N99L5t51n4hn+A17z8Bj2Hw/Hks3PZpsPhcDgcjq8pfuzHfozXve51vPSlL+XcuXMA3HHHHezdu5c/+7M/4xu+4Rsu8wgdDofD4XA4HF8JNtfXt5/BC+yD8AEX0D7MeAHaq2RuaMD2o9ZJUXRQPoyI3VoqVDJ8kF/+UH802nnkEZgxaKVIlJ8JGL2Z8hZm2SL5Pr1S2ejcbBCS3uy+oogiBGSh3oOxGoSOC+KWSOPfi6MXpf8erNEAoU64Lphjj6qhhCQxms0kZDbtdS2AeVUUkr0LFLmNMYXlp4RPT8S0cmLxpgmpGEWAtL1eheCoP01d+jyYc56fT7ooBMcCW9CgDYQkdE1MXeSOR/r/iTG0tD03oTEEAiq5a0MiCITKxHOM3cZA6AYIhKSCRKfHeDPpF4TudLExWn7Au6++iX/ywN/jCzkmdNtxGrx+i6g6PRR50nNO/poUkqg2XXAHW+FqxEecOayfIGZszeNEPUTUG7q3c2MFY6PQsz69EowoCIfm7k9iXvRmRO2pUwzdf/junWcaFORcEGYozGYx19qK0el5VmGXucfuHCvM2QkBqKhPIuTQ3T3ovZ6MF00gVGFZYRKMGN7bpI7H7qHlSRVm+38KQdDdpOdXs8KdytYyf/fwab77tz/MwytDx/q3vuS5/Mfv+0fMNK2jPKrPsrnvWmQS8ou/9Zf0I/t++75XPZeDc1MkgyKPLC48f48xXLE4wx9+9yuLyRZnH2Bz/3X2WhSCsDGHlorpcw8U9tOIEZFXFK/b4Q4WrwNhNIbisd3xrbgL/2BUm6G1dIzm+YfKXf5T8+AFY0L3YAwYjUnvq4Npo4VWAvv2LC4s7C7uOEKbLBLWphGA19kkH2o/toc6LYoYEcTtWG07iHx/bw3FAoGzD2PuuA3xwjfuYmQ7o5qzO8zgIasX107A4XB89eF6djscDofD4Rjj2muv5fTp07z5zW/OpnU6HV71qlfxAz/wA5dxZA6Hw+FwOByOrxR6J3foBYtGRRK/6O4SUHAzw+76g471KDYGTFEwjnMORbCRtHFthtbSlSReQHd6D73pvZO3wYgTd9SRCKWiki6Net6Fojly7CMvwEfiC4USEk9IvqFxmBsqC5lLWwnJ2aTL2XjoqBYXcI4SY9jURbEuwWTx3oP17fHqLMhhuzhjDDGaiGLRwZKqMSuL/YHPJR1io9HGEGL3cVR8FkIggOWkmx0pg6EqVNbHG2yEelUqNAaNoW8SQpNwxJviGn+Wq/0Z5lWVGOsU1xiaKuDbpq5iemRcoxjg8zNz/MKNL+HM1PzEa11AoWAj3YGxM5yU9ce+RFmbwuhhf+WBACfkrnr3CsyYaGcLWEaKLURR3CKJ4FzR7Xy50Z3Wtq8XYpXzGIOM+qh+BxmH1mEf9VD9tm2jEIfEfhWtAozy0V5AUmnYOPt0vX7YvmChOz8uObpsyf1lICiOjn18hSNFGcnI+0sn6f0xtw6TDF39qbO8ufwwU2e+DFoTnHuEX/qLv+EV/8/7MqG7Wavy337ke/i1H/unzDTryLBHsLVMZeMsMg554LGT/MGHPwnATDXgX73kWuugTtMxkAqUdVRnYxHWoTx6vQW9TWq5FA6AuDZNFDQK08r6j48dnh1eh/K3ptDjRVXbrSvxKrSWrkT7VTb3XTv2GYQXwBt+AE49uO1Yx+4mJfeXSTttneC297vtRG+vq8FfZ3ovq0efRWvvcbb2Hmft6LNozx8uno98UYCUE4onyu8l9tyO3Evu/sTE/b1QvJnF7b+HJDGrH/1jorXzl2ybDofjqYsTux0Oh8PhcJQipeS9730vv//7v4/vDx/S/fqv/zpXXXUVZ86cuYyjczgcDofD4XA82VRrT7Ijquyh+ahQMxoDnIox+UfqXr9tI21ToVzoBOMFNmIaQezX0H4tW15EPesiB4zy2Nx7nPbSlds+NC8VmnYjJA/ci1pbAVsnaKHQyiPxAhIvQHvjwYtJtUniWYFUC0kc1MaEayEEC6rKzIhwu65DeiPHLTF6bNooSgjOxO2iWA7EaOIR9/yMqlBJBamBWzxCM9otcUnVC4dNA1s6omWG4l5SItitxn3WdYgvpHVnC0mM4UTU4sFwg4ejTdZ1SGQ0g+69vlQc9Js0pIeXxp6LEjlqUdV4feMK1C5kr03fZybevuhj7BotYzddJEsc/rtBgHUZ68Re39kLu+zaOzK2XZdHPMV6dquyqOLB+88Mrs3i3smoT3XjLNWt81Taq1Q3z1HdOGP7IRuNMBod1OhP7UHn4+qlIqo2d1WMsxtEWWHRyPu99FyOziMEMsoJ58bY/txJnB0LGfczh7SNu06Q5IsBhtdQpbPG2l2389pfejc/94HPkGg7iuceP8qH/8vP8G0vfwFCCPz2GtWt83hp2wkv7PIf3vvX6PTa+vFvuImFRjUVREdEYzHceoYcF62rm2fHdj8aaXuxm3ty2XEM67PonFtZpJHo2XsjvRaGKynZjxxaKtYPfh16UOQiFd3ZYqsN4hDx8BcnjGibAZdGsxu0VCReQOxViJWPVj4m94fyMUoNY8mFoNZaprGSK1qRkt7MXjr7rrb9tY8/G3HwGuQNL8X7h/8GDl237VDLUlbGitEGfcmfIL3Tj7D+qQ/seG9N2pusfeoDJN32tvM5HI6vfpzY7XA4HA6HY1ve9ra38dhjj3H11Vdn0x566CGOHDnC7/3e713GkTkcDofD4XA4nkwWlpae1PWPC9kav7VacDUH3U1U2M0eaAudgPLQXmCjmpMIYTQq6lFfPYGIw2FvZCGJqtPE+T69QiDKPK+76m+6G0d2jNfbImgtE2wt43c3QMdIHSN1gtQJlfYqMuoNXXMTRP8kqBH6NTq1aYTWeFHfuke1RhmNrxN8nbBfVqiOPOJb032S3D4pIVlOumwm27tPNXAm6WTC+GANcYmQPSWt2FnLRcTrkWMUlDx67OiInklQCDwknhBoY4iNJkr/jDDMyoCm9GlIn5r06eqYjomJMYRGcybp8GC0OSbEWwfj9udqWgVcHezcxzXBkOwooI28XiK+yKg/7tQ1yYgj24qxF2v4FqbMy32xPtZ0TGmBxtj7Y2oe9l914YN8EvH2HkFLhZYeeuAoTd9zUmuUTvB6rez+IuKIytZyoZc62MIBr9cu7rOUhPXZ4gaFHEunuKSMOYlFoW1E1tM5H2ltDNX2Kn5nw0aPt1aQxvaCFzpGRV1kEg/3zSSFXt2jnv7fv+NBnv/O9/C3D9tCdykE/+b1X8+HfvTbOJ7WQsmwi98ruurvePgU77vjXgD2TtX54ZfekHu1xAFceg8sTlNxuHPB0W6KSkbGEAc1WnuuYnPfNSReMIxWx7acIEmQ8aD3dNpqwOht31lSJ3hhUVwdu34A4mgXAn0qrOfei2Op5YM5pbKFDMpD+5VigUb2WVNcurp1Hr+zXpjWaywgXvB6vNd+L95bfhT1irchFg9BZzxu/YKZeeLfK0wSs3nnx3f5uQ0m6tN95N4nvF2Hw/HUxondDofD4XA4dmTfvn3cf//9/OAP/mA2LYoivvM7v5M3velN6JJIL4fD4XA4HA7HVzfTs3Ms7pkc7b0tZXG7SVSY7nc3rMswnRZ01mmunWDm9H2gE7zuFiruI02CirqIJEaaVAhPe2fnhSqVhPj90Sjjkpjmkf7dpa7t8bUgwx7Ncw8y/8hnmX/ks0ydfQDV74zMKVMXoMlEdaMCdE64ERiCgeC9A8avUOm3aHTWqPU2qXc3aHTW8KM+0m6NADiu6szkevdqY2x8d77PMrCqe2Pi8ICujumnx3dV9zDGkKRy90CKzeMhmZY+folQNRDNwnR9MvcXoanjUZM+VenhCUXHxJkLFGyv8XlVjP6uSo95VRQX+ybhXNIt3Z+dOOjtrt/0PdOzxH6VqDpF7NfGjkNUaaJzsctGCIz0hn3WdYKKQxKvUphv0HO5IGCJ0uDiXbGb67iMTNrLxRtjNCRRVqAx6tgUL3qTjTR+ihCeeZSNT/x5dl9ASEwq+OWPiNQxfq9FML+XqpITj7TAoKJiYYhJ3bJ5Rv+9W8a2KkTR3T1wYKfTbBsFBUKlMixpJLgorjEtUPC7W9TWT+P3tlBhF9Xv4PXbqLCHTEJUEqGSaKJgu9EN+a7f/Shv//2PsdmziRlXLEzzwZ98Gz/1hhfhKUmls4bqt8eEboA/+rsvZv/9f73+RTQqw+M0MU5+B7Tyx4Rhv7NeuOaNEGjpFdc+moiRG0NYnWJz37U2BcEL6MwfBoZisk1NSIrHaZetIdRu7u/z+2Dh4I7zDQpZxhsMDMep4hAZj7QBKYkRL0t8qG6NxHzrhHD5NKOI6cUdx1ocgBmLfxc3vuzC1lFC79TDmKi/84w5+udOPOHtOhyOpzZPnW8lDofD4XA4nvL86q/+Kh/+8Iep14eRlu973/vYv38/997rKmUdDofD4XA4nm7s2X+AQ1ccQ8Qhlc1zVDbPZXHh2yGjHjIaCtkyDvHi0Aq8xuB31vHiPtJoVNwnaK0QdG0vWC9sM3XuQYLe5nB9RiN1cbtaBWMP7UcFhlJZIos2TiPRS+KNRxGAxOBF3UwoqrZXmDl9r3VRZgOVxNVpK0RlCwsbJTuyPr+7uaM4KQATNAqimjQar98qnAchBIdllYGUOuhtPRCr+zomSUfQ0uPnzxjD6WToRAy17cG93eg8IWhKnwqKGh5VFJ6QKGy0uScke7w6x4MZpBC2F7cQnEu6PBa3Ck7xBEM40vPbF4qGKBYmVIQac4uvJf0x1/lupLTdhIZfn0iWqgt05w7Rm95Ld+4g7fkjxKmjVyufsDFPVJ+1scEAWMe+kQoRRwTtNStPCpElEgywgre+KDFt8n4xFK53sY+DMWTbFsL2U86JhtmI/Aritf8Mef3XP6ExXkpMHLH5d7eO9bkHQEi0V4z5F0ZTWzqA7G1tu96yePp81PXFYrD3rkIBjDGosIuIbUGQinq2OCR18xrppedTYIR1r5MfizHIqIfXb+GHHfywnQndMomQOkYlkRVuR5zco9fbJx46wy3/+X38wZ0PZdO+89lXccePfQsvuLIYxe13N8Z6ggM87yor4L7k2qO8/aW3XOSBGhFJk4jmuQez8+L1tgh6Wwx6jWfvPaly78XBwuWZB1F9FpO7PuJqE+3txq2/83s0UQGVrfNMn/4SMyfvZursA+Mzfeh3YHl7EfZC7gayxP0+FiNeciwGbT1GMVoTLp8iPPs4OuxhjjzDxqQHddseZKSwQOgEkRuDvbfl5jh2I+LmV267D0nYY/Phe1m+629Y+cLf0T1/auz+rrvjBRY7MdoGxOFwPP0YbwrkcDgcDofDsQ2vfOUrOXv2LK94xSv47Gc/C8C5c+f4uq/7Ot75znfy4z/+45d5hA6Hw+FwOByOS4XRGvXgnSw9+PlMEDNC0pk9QGvPVRMenIe2h7DREFsheeDAlkbjtVfxcxGvAoMXFt25fm+LpNIoTBPGYPKbm/Dw2oB1dg7/Nfa6AaTJ5BFEv00S1DBq8qMy7QVs7rma2dP3ZqK6wNBcfpi1wzcNxyMEcaWB390cPugXgsSvoeJ+dhxl3Eckoe2nul3v38H6OusFx6GKesR5EVwIZoXPqolopmK7AbTRrOmhmFHm7H483qKtIxrCBwxSCHomJtQajUEiEBKqOfHZR44ICKnjlNSJKARSCPZ7DSSCB6JhUUDLRKwkPRa9WjYtwaCN3faAqvBom6KYVpGKMOcW1BgSDN4FyUL2OFSEytzsV/kz3FBZ4OOdk6zqPvu04E0bW/ij4pEX0J05QKV1nrCxYGODgagyhd9ZGx4TIazunT/eAxG8TJgtILhQ96t1+1qROrsWpYfWMULHE4+OdYRr0BSvfynByKLoGIeIfVde0LiebPonHtjW5WnSe0F+/6OTDxZE3/IFx18fPW9Cx2Pr3naVpA5lKTHCx6RtGOw9SyDjEBH3MconqlTtfSGJbZFE/rxqXRASVdQfi2O3QrbEjAqOg30buX9GieYXPngXv/ihv89SFmaqAb/6lhfyHbfYyPowiQrisIxDEr8OI9t+83OfyWtvvhZPSnzGr3WTFqwMRqClQiBtWwqYGNVd3TqPirp0Zg/SXH44m26MGbr6B/stZGkP6TxBe43e7P7CtMSvoOJxV7aWHolfQSYRKhxN9Bhn+twDO26fXRSOXQgCY6+nkaSJnShLKEgevZvVOz+GHqSXCIHX3qDiVbLrKVEeIrHx+HZfDdIYTBLD1Tfb+dbPQ30acf3XI659LmKbgpHe6lmW7/yEXT6lc/oRKgt7Wbr5JQhll5X1qUmrmEiw9/AFL+NwOL66cM5uh8PhcDgcF0yz2eQzn/kMP//zP589zNFa8xM/8RO86EUvotfbObLL4XA4HA6Hw/HUp3Pnx+jdf1fhob0wmsbaCZrnHhybX8QhMu841smYCFMmKJe5L8vEJgMkyk8joUWJS9tGt2ovwHgBxquMi+JeQFJtFnooC6NtJPlO7XmkorVwtLCs1DELD38a1R8K+Eb5JJV6sU+zECRBvSA+CKxjccf46TKHaslygZAsqSoqt93lpEvPJLY/NhKFoKcT1pI+K3GPlbhHIDyuDeY4FkxzLJhhv9fAGBs5nmCIsIL5RjIUFSc55coiz/eoGhVRFDnyAvyAZGRJtQuhRiJQI9LYRtKfGNcOEBnNklfnG+qHmJI+c7LCC6p7WVBVvrlxlH2qxjeGAn/SOqSkP713TBw2I+coKXWJTtin/LV8ETHPAlA6RuSd+4NUATn+nhvbwqAvcH7SqCvUGMxj91zw2J5MktYOfYSzXsU5jEYduMren+J+qTtZ6rgw3QhJb3b/sE+3rk5WTQABAABJREFUMYgksQkTu7hOM6F7EBOPIZEeiQpIggZJ0EAHdeJKk6g6hQ5qtu9ytWGvs/wmpBxGVJfcY7fd9xIeXNniZf/tL/n3H7wrE7pffOVePvfj35oJ3TB+5aqZRao3vdgWUySRdV2n75mq7+Epu69JLtHACInxPIyUWYQ+UtmYeK9ihe5tikH8Xovps/db13vh6BYxo/td6u4eX07Gxfh6LSRbC0dYO3IjmweewfrhG9k4cD3RSDHW2Lp32U/6SaespcgIfmeT+sqjw5Yi7VXk5z9KcO6h4fzGENen6U3vKa5OeWjlo4WkO7ufrT1X0Z4/hD7+PNQbfgj1Xf8O9ZYfQz7jBdsK3TqOWL7rbwpC94D+ylnWH/h89u/q/isQQWVsvknISo36Fc/Y9fwOh+OrEyd2OxwOh8PhuGh++qd/mrvuuov5+fls2ic/+UmWlpb4xCc+cRlH5nA4HA6Hw+F4ouhem95DX5j4en39pI0szWFGHmaXSUBGlD/wNkDiBcR+lVgFNiK6Pkt3aone1CL92gz95gJRY46oPkM4tURn/nAhMjzobdJYfnRsXGMISRLUipMwY0JHGXF1ivUDzyTJCZtev83Sg39ro9vz2/BzYmcaEa2VXU57lXS7jEX2ljF63MqObUN61KSXuZ0jo5FI5mSVGVVhRlVQQtLSEX2TEGHjygF6ZigeSSFoqoD6SIx4x8T0JglrOUYD0IUQzMmiOBGandzNkJQcF4Uo7PumDvlc/3w2ro6OeCxucX+4PrYNYwx9k7CeCu1V6fGy2kHe0DxGNb2OqtLjudW97OtfeC/wMYEtmy7Qyktjf00WR22EKoifIuvIfPEMoq8L2x/tYwyAGCu8GF+25Cq7BFHelxJZ2150BMYEPhV18c88QHXjNNWt89Q2z1DZyrVoMJpKe5XmyqPIqGfvTX4V7VfpzB0ikX6a7mAwQpJIG5uthSLxKrYYp+SYyyTOYusFILMmzMMECEEquOYKb4ZnIbdGITBSjoi+JZT0aB4eFsNvf+Z+nv2f38enH7N9m5UU/Nw338KHf+CbOTo/7Guf9QnPr3r9HPrv/tLGV6euYpkmCQz6hwuj0V6FxK9ihBy6iEUq2Kt8EoEa2d+JAy+Oo3zHd1oLWnnF690YOnMHC0UqEkN94wwqHBb0x7VpNg9cTzzyGXK5MTAW+Y1h7K5SuIMajTAJ9fXTNM8/RNBeo7J1HoNAhV387kZaZOYRewFhY5ZwROjvN+ZZO/osOgtH6U8t0Zvdz9p9d7L597ePj2cC7VOPYOLJTvf2yYfRqRAulMfMLS8vvxeNFDV4M4vMff3rkJWn1rlyOByXHid2OxwOh8PheELceOONnD17lte85jXZtFarxUte8hIXae5wOBwOh8PxVUx05rHyPrgpwhiCztrIxMmuVRn1kWEXkYRD+2/6lyif3vRe+lNLhM0FwqlFtPKI/SrGC9BeBV2pjz3cTioN2gtHCqKd1DG1zbM77p9RXtpDfCgqyV3Gymq/Qmvx2HC3te093lh51P57ILJKK2gOA9Ptdg0QFwSDckFg4Hw0jDsFdT7WOJ1XpFLwYG1SCGrSKzikhRBUpMIbeSzY0fGYOFyX4/G2HbOz2L0becMvEYZ7Ji6IIy0TExmdTZPAvKpyMI1GD03Clg5ZTnp8pneOtbjPo5HtxRyiOREVe7sKIez6ctMCOeoLhykZsFsGAp6WHsZoEq9CVJ0iqk2TBFXC2gxxdZqk0iSpNgmbiyRBPSt+sPHLirw490S7y8okLL53Sx2+Ju0FXdya1MnwPTEqVEmFuOLrnuDoLi2Vw8dhm/YDpELsAKETvC9/Bk4VeyirOKS6dR4Z9wg661bA1Qn1tVMkfh0v7FJbO0Vt/TTa89HKJ65NE9dniOuzhI054koD7QVoLyAJasSVRlYAYXVtM5bIIGAoDuemyaQklnwUIXcMhZjEWqfPP/ydj/A9f/BxWn1737tqYYqP//PX8VOvuhk14urXXiWL7AfsNRL1kEk0Hu9uNEJHyCTMxm2UbwuE8tdbyeeFKYnUnkg+1QNBWJ+lvXCE9sIRwvqMdY3n5x1sM/2rdNaZe/zzqEEbDSGskL3veKGYSeqY5vkHC+fISEV39uDux/oE0VIR79hPXODF4bBoK20nkaUAZMcqddTrQZKEwAhJZWsZf/McYVpY1m8uZCU42quk7vuA9tIxujN703F5dOcPlgrP3Ue+RPeRe3e1f9EOCQ0mjkh6w/j4yt4jLLzsTdSuuA7VnMGbmqNxzbNY+Ma3Mfei1zPznFcy/9JvZeHlb8KbntvVGBwOx1c3rme3w+FwOByOJ4zneXzgAx/gN37jN/j+7/9+4tj+MP/lX/5l3v/+93P77bezuLh4mUfpcDgcDofD4bgwdlZRhLWS2Shgo0lS8UwrP+2ZalBhh8rmWVQqiBhIHX1D4cPkooEHQoSK+1TaK/SbS5NFdGwP5X5zyToz02mq30bEEcbbXjgRGPzeFlF1etttlBFXp4j9Gn6/ZcVFoLZxhq29xxHJUPzRUiINufVbUUYrj6w3swGRxJmz1AhJ4lcK/ZfjSgOMQSVh5jTNjgEQC4EUksAYwjR+HNK48VTgyOMLORb13dMJgRqKFlIIAiEJc/NtFw8+CWOsnznPHlkjQBIOnOU6tlHpIuSAahCh2dJ2XyMMFSPxU3d7IBTT0udk2MrW2jExX47WaOQE+i0TEZqEIOeKD4SkM3IwxpzowPlKnal4KMAYIeg3Fggb8xgp8XptvLBl586dIxV1Uel5TJRPp9Kk0lrBG/T5lYqoNg3dDdRAlBICkBiTPGGhezB+mYRogm2c2Ol7TygwxZ7eQmuMGu95LG54GaI5ewlGeOmQQZXmzS+jdceHS1412bkA22ahtnk2F/td7I0ujCbYWk6dryZrMzB34u8BWbhHGCHRg4bdQmBUgJEaGfWH4rqQxH4NL2wjcltEJ4UIfNt3WqdFD4MN6OH9cDsWD8DZR7K9GJu7RA3/2IOn+ce//3EeXx+2XvjHzz3Or3zrC5iqjt8zzeIh4l43W5dtMzHsqy1MgjGqMFZhzNhYdtNHe7BU0Yk8PtegmGNwBpNKnc7cwUwsDxvz9GYPMH36S6gknHgcVRIydfZ+1g/fOFx7WnzVWH08N1+E390gqs9m0/qNeZql47v0dOYO0ZvdT33lUerrpwuvlSUIGPIFLvY6MkagPX94T9AJMomRg3MioNLbAuUT1WfSaYKgu0FkNHG1mU3rTe9BRb206Gqyn7Lz4BepH7t+x/2T/s4FRkL59E4/Snj+hC1W2HuYqRtfPN5SYzdpDw6H42mHc3Y7HA6Hw+G4ZLzjHe/gwQcf5PDhw9m0L33pSxw6dIg/+ZM/uYwjczgcDofD4XBcKN6eI2MPseOgzubeq1k9fBPrB64nrtRpLD9Cc+UxGqsnmFp+FL+7ZePM04jauDZNb/ZAJmIM4pJl3B9zM47Gecskxm+PuMdLCJvzdOYPF7exC5e2SOJ0LFZ01BfiKgQSv4Lf3ciJPjoVvk0uOtZGl8dBjTioEwU1kqBmxbFcX3EZh0gdI3WMSkL83tYwVhkrwET1WWIV0A5qRJ5PgqGHpo9ADxykQuCPPPITQowJMlII5MjUstjwUSlndJmJxybnyDbAUX+aa/1ZBDAlfPZ5DTwhqSDp6jiLFu+bhFNxm/NJd9jnF5BCFkSNWVkZ69XdK4lG70+ISxfpvgz+XyGoCElF2L7mevYgOhUftVRs7L+e9tIxovoMcXWK3uw+WktXElfq2TqN8ogrzWLcsxDWITnSv73fXCTJX29CoFUl2+YTJXsPZO7X4rnN+nGLLEs792IqJuaXufJGxCu+45KM7VJTO3Y9My97M8H+Ywi/gqw2qF51A7PPezX1lceprzxK4/xDNJYfsS5eo1PRdbwIRJI6sNN/C6zre+x+ZfSwgCGbKIt93CHtrz0ybSBk5xctKbjYES9A3fAytBfYAiKp0EKWR9YDUaL5N+//LK/6tQ9kQvdsLeB/v/0VvOs7XlIqdKM8xCv/ETKJsvuTyAndg7GK0ffZNvHpBQZx50mUFvzEgzKD9PNnPNxf5P4G/660V5k5eXehz3oS1NjacxU74UU2rjtPmBO1B2QO8Gwgu4hKl94Ff67kMUBn9gC92f02Zn3+CFF1qnzmQrFBvjVCWhQgJYUrSyrbFz5XECOAansVNXJte72tQrQ+QK+5iPa3d5sn7Y1t48kH1Pcd2fb1yuwiG596Pxufvo3uw/fQfehu1j/1V6zd/mfoXMS8w+H42sU5ux0Oh8PhcFxSjhw5wiOPPMI73vEOfuu3fguAfr/Pm9/8Zt72trfxu7/7u0jp6u0cDofD4XA4nuqoepPKFc+g//DdAHRm97O195rSB/y19dNZTG/Q3UDomO7cMOI1qTToTy1Q3VrOpgmj0UKSl2aEgTBoFJyQ1dYy1dYyW3uPbysuJJUG/eklqpvngLQf6zbIqJ+5PmUS2p683i7iq3MiVdBaJazN0p3ZZwV+o61YqVKXozF2nds43+wAFElQQ4WdzPkoAK/fIlKzw+WFoFufZk2HwFBcqiKo5QRuKQTCjLsjdxKf5MjxNcaMCeAxmpaOaAhv3FGXYyAlSkPmMp9RFZ4h5qkLL9uWEpK+iQtj65Pgm6K4HRldiD6XQlAVHi2TKwhI/99D4AtllxkR/o2BqlA28D1dv0TgCYFK1z/jVTAqYPXAdcyee5Du7H6SnKidISS9qb00Vh9F5GKS46BG0NvKzSdozx+itnEWFVtRX+qYR5/zFvbf+5Fh7L6w1zH9NnIXPc13QgwCi3XRMW5KY83zjC8jbn4V4inWrztPsHSQYGl4zzG9Nvp//xIybE9c5kIcuQKD0HEhZlsYbcXZ3L3GSA9GCm2MlJB7G+3mvWhSsTg/Rq/XIvGqWWKFCLvEt/8fZN5FLQQGaSOsU8ETIbj/3Abf9Xsf5Y7Hh/fgl121j99620s5PNdkIkkMD39hh9EOdyjbrxJntxh1mRt7TAvzKYUWYjh9cA8wgxKiyXhRj+rmObpzB7JpcW2aOKiPFyaMoMIuUW1mOLSS98doIYPXb+14DbUXj9JvLDB17gEq7dUd5h7HCElUaTB96l4rOGPd2flrI7ue0iSAgat77PgDmCRNLh/un1b+2Ps96GzSDeqFZVXUK9wHk6CG35/8/gKsi3yH+0bc67D6hb+d+LpQHqLXIt4cP37R2jk27/w4s8//pu3H4XA4nva4J80Oh8PhcDguOVJK3v3ud/Pnf/7nVKvDSt8/+IM/4MiRIzz88MOXcXQOh8PhcDgcjt3SePYrqRx7JnGlMVHojqtThPViT0y/37b9sHOEjQX6I2457VfpNRdzEbyGpNIoRMWCoNpaob52YsfxhrUZjBDEQR2znXCtEypb54dbMIa42sBImbUSH8MY62xLXaFCJ6wfuoGVY8+ls3CE7txBuvOHbf/gwXHaUVTM76bti1qYhBXl8/hCjTuyS72cI8Mv2eToyGrCKywXo6lJj0puHwzQMhGbZme3nikZW1P6Y6J6Q+ze+djTCWtJn56OiUiYEj57VY29qsa8DDiimlwfzHNNMMv1wRzVEVdtRSqmRHEMCYaWiUnyzl0h0NVpzh26kX5jYfKApCSuFMVCo/yx462Vz9aeq0hy59iogJM3vGboBE8j/LVf4VIhktj2hB5sMx1LHNSIKk3ioIYeKUYu8Xpj/viX0R/5g0s2ricb/YF3weqpS7rO0d7Uk6aNMarxCjHWKz32qoVpYXWafnMhc//LqIcX9Qi66zaJIr0X2ftGUFxfun6DwRjDb/7tfTznl9+XCd2eFPyH1z2H277/NdsL3YPVBRXw/GFKQAlaShKvQhI0bH/6SsP2ec52euTOasYLKjKktMVDhUHsrjSh0loZmxYHJYUqI4xuz+u3i/tqDJWtZVRO3K2NxIkX1ge05w7Rn1oCKdnaezVJejy0UGjpYUpd+EWk0UyfvR+/u5kVlNn2B+Nud1sRYGxxxYTjZV34IwkeaV/vPIOinMJso20NpKT23O1F5qgxz+rKcpbyUcbyXZ+Y2LNbVevMP+PZ6LVzE5fvn3mMuL257TgcDsfTHyd2OxwOh8PheNJ4/etfz+nTp7nhhhuyaSdPnuT48eP82q/92mUcmcPhcDgcDodjNwjl0XzeN5Hc/A3big39qUXCkWhVv9caWZmgP7OP3tRSbqIhqs/YHsak/byFJAnqmTNbpaJ5bePsWBTzGFIRe1V603u3na2yeRYjPfqNefrNBfr1OSs+SM8KldJDC1UUIoQoHgMhrKBeEkl8sRipxsSPsXhgxoXIMWGypEd3gi70pvaRLHo1mmmP64pQVFMhXRjbmztKj7cvFAMZfOCG7pr4ovp3l1HmEDfG0NcxLR3S0iFbOuT2zin+pPUgH2g/yp+0HmI16TMjA5rSpyl96tJnTfeJUhvtJOe5EIIK427DvokLoowAfMy2DnaYFH8/soywAl53eg8AUaVJEtTQQY3NvcftetJzYaS3g4e1SF48tU7QKcL6bPqeHFmTkCR+zYqRQZWk0iCcWiKq7Cx6mjs/hL77E7se1+XCrJ6Ghz//ZKx5fNJoGsJIfLcBwsZcIbI+qjQJazNZfHSiAoznWzFUSKKgbvsjC0lUnUaEPbz0fiqwkdIy74gWYjwqXQhW2n2+/bc+zPe953Y6oS14uGZpmr/5F2/g//fKG1EjRQ75tgEmbY1ghMQENWRtyrZ9SGJEHKUx93YJLRRJpWld71mhj0T7VZKgDpUast6041Ue8prn4L3gDWPR7cXxl8ex70Tp/XKkIGG0oMkYm9KRjymvr5+ybSQGSRs6IehuMHvybrzeJvWVx8ac2oPjZhAkXpU4qDN96h4WHvo08498zh7TQfsK5aO9ii0I2OH+kheyhxMH0nfJfDsVWO3i86psTKP3uWhqid7cAYI9h0rXoaVHa3ovZ0+d5ORjj5bO0187T7Q5uVVJ0u+hO1sTX09HS7x+fod5HA7H0x0XY+5wOBwOh+NJZXZ2ls9//vP81E/9FL/0S79koxCThB/8wR/kve99L+9///sJgl3ERTocDofD4XA4LgtbGxusb+zgmhKC3ux+zJZHZdBje8ID9bAxT9BZRyYRcaVhp9Vm8LubVhhJBZjEr6PCVeuww/YflnFU7nrNbas7ux9pDF7XPiDXflB0TBtDf2qPdWDndyHfvzcVto0RMCIqgcTketYKrDC7W+fhtmT9k8cljAHamIJoDRCM9HkWQlA1ighNjI0iH3TP1kCAzNzaTenjIagIlYm6AohGRCNfKBKK03omoblb53oOYwwJJnN9R6NilDFsmriwnyGaeVXhTNwhSl9ZSXp8Tp/nOdU9WcR5hOZ03OaoPz22zrxoLYUgMJIwly8dYfAxeMYew9HexJMYFdNEEhdkKAOZ2BnVpjEINvcNY/n7U4voc3527dvrjzS6eXBODFqoNIHAyxzbcXU6e0+IJMIgC5diXJ3G765nccPCaILuBmGaojDYXlybQiZRqaOzcBzv/DA888W7OCqXD3PqgSdpzSPCNqCVSv/LvhbWZ9FTS9TWT6OSMEuqiGrTNFYexaQtCxCCqNpEhv1hCoUQREGNqJFLyhACHdQQ/WHxkEyTJQrx6SPvw498+QTv+N2/5uTG0In8jhdcyy+/8Xk0KkPR0gCD3tj2nmfSmPtMOkV//I8AkcXYC0BojRFg6lPEXnXs2GTrVz7+N7wN/+BVmKgP0kMoRfLZ23Y41OkYLrCQKFF+FucN9j3hd9ezMzQoqAIBJsnc0pXOGn5vi40Dz6C6dZ6gs56uMM72Gez7Z+bkPROSM0T2HlY6YvrcAzYJJF1O6jh1dleGgrSQaFVBxr1t7zV27CPB9hdxfCYysp7BZ/MALVWhzYeWHu36PK0TjzN36Jk0ZxZpP3w3Io5sgUd9ls7swayn9+b6Gq35BZpTxaK4/sa4E784Lk0ShTsOX3gX3xfd4XA8PXDObofD4XA4HF8R/sN/+A986lOfYmZm2Afrwx/+MHv37uWzn/3sZRyZw+FwOBwOh2MS/X6PE4/uvgVNv7lge1Zj+3mWIgRRdZpEBVmPVOMFaOUT5uPLjaG2cTYVodPuw0KAThBJZF13OrFRuDq2Tkcdo+IQv7OOF3bwwg5Be52gtWpjf9PtjwrdMBBwRlyBQoz3bi0VtS+R4KCTMfe6ll5hmsEwIwKC9LFegCz0sh4OUxAIlQnL+eWrOWEboCqL/beFEHgjjw3LHiIOygNio+nqGL0bx2A6nhCdCd415bOgqpmM0zPJmKAPUJc+VwczhWk9k3A27oxNu7e/Ot5v3OiCc9sTkmqJwzsZuCh341w3Bq9fTDFQIxH+iVcZ9q0VkvUDz6C9eCyLhRZaE9amWd//DFaO3sLmnqvoV2dozx9ha981bO09TmvhKO2FI4SNBaLaDGFzgf7UHhI/H4tuBXMzIohFtVmSkVh/v7s1tn+jAlcp5x7fNpL4KUGp0/6JY3tvx0NHsxfkXLSGKGiQBHWM8unOHiCsTQ/7QEtFZ+6gTbEouJ8rhXvKQMjOE/tl99LRc2CvpTCK+dd/+km++b//eSZ0z9cr/NE/fhW//tYXFYTuArnWC7a3czHhQDD+fhBG47/mHYU+5mVEj9xt5/crCJW+D4JdRPVfxGUW9LaYffzzWfuH+uoJRK6fuBHSnjMhMOn9cYDUMbMnvkBt40w2rSzSv+wTYKL7esShLrCFW8WFS5z5F4lozCKe8cL0czK219LI+1XA8PMQW1ATV5vZPUJLRZjrX66FJGzMZ9dI7FVpLV2VFWmsra6gjl7P2uGbWDt0I2tHbqa152r0yHeAjbXxnttih37eAMHifkTJZ3ae8PwpdNjbdh6Hw/H0xjm7HQ6Hw+FwfMV4/vOfz7lz53j1q1/NRz/6UQDW19d53vOex0//9E/zcz/3c5d3gA6Hw+FwOByOAmvL2/faHENI4loTFXa3Fc60F9BeOlZwpvWmFvH7bfzeJkZIVL9DZ/4gvak9GOVZcRuBTKKc2JAMnYmpSGP8CrGUeN2tbD6ZRPjdjaJjsmz4GIzRxRhYIUtEz1H3NQU3YSmD45gXlaO+dWemD/z93hZev00c1GzMrfIRUoJO0MJghERjxeg6Hh4JQYlYm8cXMosjHxChd1xuOOxU0jYGhI0/VwPRw2g+1T3NybiNwUahX+lPc30wP9aXO9tnIfAQCCPo55zigVAcqM2wZ3GJOx67n4b0MRg2k7Dgvp5VFW6qLPCF/ko2dTXp87zaXk6n4wA4Hbc5l3R5ce1ANt5BD/F8Z3IpBJ4RxNYTnc1njN6VSyhoryIH4qSU+FIgkjRIXaq0R7cg6KwhdELs11g/8ExEHGVpAp25A6wfeEahCGPl2HOZPfEFqq0V6+71q/Yc6BiRv5YMaTkIw2npectPiytNVDwUmwQGFfULRSl6N+7ISnXHWPfLjTh2oxVgR0XFJ8BAJLVJDgmJXy+kTMRehag+FAiN8ohqs8hcQoJRAYZuMXy6zJ1rNOTen6O9ku31KRBxWHjtS2dX+e7f+WvuOrGcTXvl8QP85ttexsGZ8uIjkW5v6PDOb2jknmY0Awd4NunLn83cz5MwJSKkvOpmktvfawt8ShcaCxsvve2W4UVdZk7dQxzU8fot+qlQq3otVBIiknjiip7IlV2a8iEEmJGBD1pf5I/jRSRklLq6/QD50F2Fa99gr0cjvWwZZWI0Ci2V/QwSwt4Llo4QHbme6PEHAIP2KlkSQbZLRhdc3mCFbGMYphSUkMTj10l97yHW770jLQAwtoVDTgBXlRrVxX3oa2+hdc+nJ6678+AX6J99nPmXvAEZVCfO53A4nr44sdvhcDgcDsdXlCAI+MhHPsJ//a//lR/90R8lSRKMMfz8z/88f/7nf87HPvYxpqend16Rw+FwOBwOh+NJp9tp7zzTCImq0J+bHxN+TU4k6dfnrOltIFwbQ23zPPXVxwpiQ0+AmbEiwMA9aERR8C4TGAb9UPORzDK2IofZwSE2EHUvmIIoZKitnSBsLg7FxEy8SYX5JELpGKNjtF9FhV28ftv25A279Bu1LH5dYB2fYW47tu/0zo/2VIlku5vyhcho1k1IPxXrJNDApyZzrnABe1Sdk7G9Tvom4d5wjfWkz4tq+7cVRVVOZB6go5hzZ85ytT+TLXtAGdZ0n8fjoXv6GcE8+70Gt7Yfw2DF+ykZoJXhTGJd3gmG9aTHY9EWx4LpYj/ikUhzD0lMgp878bvpmT0zN8/8wf1ErQ2k51Pbc5CtjQ3OPvpgKnIbKq0VZk7dncWIV4Dq1nnWDt9EVJ9FAHF1CmF0odDCKJ+1wzex9MCn8KK0l/DAAZov+EgFb8YE1OJYR8Upu5FRp+7uClv0nR9G3PzKp6TobYzG/N2fTxZRL2adiIIAJ2Csp7GK+/Z45kRLIyUkuXGkTl9G+0qnKQIijRAXcUylvYrqdxicyHyAtQD8sIVRPkZad/K7PnkPP/nHf0M3soKiryS/8Prn8S9fdiPq0HFEtQH3b5OoNjL2Ml25bJoJu4jmDKa1MXHVslIjueODJPd8EjZXYGoe9cyvR9z8CsznPlQyFoPIt48YhoTvOrpbxX3ioMba4RuHTn9jCNqrNM89VChCuLSY8SKBkQM3LKm50PfP+PxjU9bPlc+TxLYth5TD60gnGK+YLKA9n7g+S9SYnTgKWzAQFYTtJEnw/YBom8jxSrUoQhud0Pri3xL08j25+2jpEacC+8zxGxBC0jh+EyKo0L73s+h+lzKS1jrt+/+eqWc+f+IYHA7H0xcXY+5wOBwOh+Oy8MM//MPce++97Nu3L5t21113sW/fPm699dbLODKHw+FwOBwOxwAhL/zRUVRtUNk6z/Spe5k58UWaZx/A62ykzjJlRSNZjHZFCLpzB2jtubowvdpaobHyWHEDUpW44MyYAKL9orgnIHWH70RRPpBRr7juVAwfHX+e6tY5aq1lps9+GRV2rJA1kE+NRkR9ZBxmW1P9NkF3oyBmqTgsuunGRrY9xpjUlW9H6iOpCkUFhYdAYR3WvpDWaT2y/JQKmBZDp68GtkzEmi6KGQf8BtcEs4Vpp5MOp+KdCyV8JP7I48lOEtEyw/MkhGBeVdmv6tk0JQRX+NNcmfbl3qtsQcG0DFAIYqNpabuOR6MtzEif8zIRzzrWh2NJ8j3cJ2LwpueZvuJamoeuZG1tjVOnTpL41UzY7E8tcf7qFxFWhwW9KgmZf+xOZK4Yw16fIwKcVHTmD40MdrdXwsg8JQKhGen1LqP+mIg7Rr+L+cjvY277rV2M4SuP+dSfY+64bXcR9Ltf69jxkyNuZtsGYXybBki8gNivkigfjSEO6oTVGcLqjI0o1zEqCZE6QiUh1fYyXr+NNAnSaKTR9t7JyP0giVjebPPWd/0V//wPP5YJ3dfumeVvfvRN/OgrbkJKYZMjdhD/R6PLd4tcOEDl2udMnsEYxOduI/nk+6wQqxPYOE/yyT+Fs48iX/xmmF4YjmPpMPJFb0qP3eB/g2Np76JGyKy1xXZUOutMn71/eC0IQdhcYGvf8Qvez92ym3dmTrrPLSjYrsDGpPMMJ4w633celzRxYQsCG91e2M7Kqd0ViozcJ3zPY25xcdtF5haKr2994VP0TjwwNp/UMb6OWLjxhTQOHMum149eh2rObruN3uP37zBwh8PxdMWJ3Q6Hw+FwOC4bx48f5+TJk7z1rW/NpnW7XV7zmtfwvd/7veiShwUOh8PxdMAYQ6fTpdPpPvX7Xjocjq9ppmdmC/822P6dWnrpnxp/QC9tXKrUMQKDF3Vprj5GffXx4TwiFWBGROv+1OKwx21KdfNcGjubG8dIn88Jgdklk3aQIrSmtn66IIrveeCTHLrzz/C7G8N1pJHGVm4Qw/0whtrqCerrp+ysRlNfO1FwzFqpcuSoSYUeORYDMXziHg3WaQwqifHiCJXEJDphQ4ec1z3O6x5rOqSCoiF9qsKjJj2UkDb6OucS94REjhyzGVVhVhaLBromJhxxRV7tz3DAqxemfaG/wukdBG8hhmJ7bsfoGz22jQVVRWJ7iTdTEf6aYA4B3FBZyNZXFYozcSeTgUKT7Eq4Hut7LgTxSL/dUTbW1njo/vsI+32iKOTcmdOl8xnls3Hg+sI0qWPqayeLmyzpi1zoYz+ccWdG1uOFxb7mBhubr1LHOTpBRV2M9IrXohCl7xtz9ycwpx7cxUC+cpioj7mzxCn8BJl0uE3hTxAHdTqzB9nYew2be4/Tnj1Id3ovYX2WqDZN2Jijs3jMtniQEqREBzX603uKPdWFQCt/rPe6GSkS+uB9J3n2f3wPf/6Fh7Np/+zFz+Rvf+It3HxoKCyak/eD2r5tQdl1Pt4VfORa8Hzk9S8geMbz8a+4njGMIeisI0cLD1InuzlxHwiB96I3IfdfhZxeQNSa8OCddj6pss8JI6QtxBj8yeE9eDuC7ia19TOFaVF9lmg3/ekvgrLx9BsLJLm+5lF1ms7sARIVZMsYqUiCmi3kys2bSdppq47h8d9N9sTo4MaLNsYLHASVfUdIlE9YnyWszaCFot9YYGvP1Wzsu47NPVeP9WlfWV4mCkOaE1L6Dhw+QlAZxv7rfpfuY/dNHKoIewTN4rq27v47opXye2x+ve63lcPxtYmLMXc4HA6Hw3FZkVLynve8h/e85z1813d9F2FoH+q9613v4kMf+hC33347hw4d2mEtDofD8ZXBGMMjJ9d48LEVOt2IZj3g6qOLHDkwu+t1nDu/wpkz5wkjK6T4vs/+vYvs2bO9G8LhcDguB7Nz86ytLNPv9dIH8t6I8CUwyvaUFjn3XH96D/9/9v48zpLkrO+FvxGRmWervauq95nunl2jZbQzlkYSErIEQkLs9xVYwAvGYGxsLn4xXPNyMTbbCxhjfI254GtWA2Y1CCEhAVqRhEYaaTSavWd67659OWsuEfH+kXnyZOZZqrqnRzNo8qtPabriRGZG7qfi9zy/R+qQSntQI7jaXMNvLKAzIoNN6mFn1+hPL+H1hWViwVgFHaJaduJ7H9P8hQlvi0htwcdRba5Sba3jdbfYPXgrc5ceZGrjLACHHvwrzr/4q9L62vFxkEP1WYv5hq7fRkRBzvI1zkwvZM8VracTu16pAzAGKwTWqSSitE13UeoQmdlXFwgE+IleabA0bYgxlobMZ2oLa3O1tZUQaGNy9tRzssKOCXJD842mppx+xXSEENxTO8ID/iafD+JzrrFcjjo4SJac0fWCB2OObcSNtWkdbt9qvEzmsRKSunBYUIOa0XXh8Lr6UZYzQvuq7tIyIQuqgkBQTWofq0JWbM4WekwQhBGCCImaUL9bRxErly9Sq08Wz4KpA0RubWBJDrid7eGOBXdjUcyyTDL2cyM2BoRNgy6EiVBhNxZMlYvQEY4/CDyIxbP4iLh+B2FMXBqgfx1JhdVm7HFJ1/PQxxBHbprY5wvKyhnwO3t2u1r6NeuF1elzRUgnPu6ZsgiV9gbducNYx8MCwfQSgdFUm6soHf+da5VDUJ/Da20ORGAhCeoLVHev5OzprVL5QJ8kq78Xhvybd3+KX/jQ59OPFhtVfvkdr+crX3AiHlf2jpUKcctL4/rae+7pwGTbuDWE1YPgn2wQhHJx3vRtiNo0APXXfA3h0Zvw//p3AYswGhV0kVYjjM2sOw0Rirfzgd/FZJ/VmxkxMy2XkPy3KGKOqoc9gmpzle78kVxbWJtLSws8Ffpb7u+PUS7G8VCRj7BxFn9r+SaEiZi99BDCRPgzS1jp0JtZprpzOb4Okn3UM4s4b/pW7O//bH4/s4woU3BVYxYicXWwmCRLPt1GtcHuxXM0D92eP+7ZMiGMqstt2dpYZ2FxiRtO3sTO1iaRjqhUa8wfOEClkrcwDzauJNfpeIK1SzhJJre/eoHO4/fvuW9qanbP51ZJSckXJ6XYXVJSUlJSUvKs4Bu+4Rt43etexz333MOjjz4KwJkzZzh58iT/7b/9N975znc+wyMsKSl5LqK1Znt7mzAMcRyHzz+xw4Uru+nnzbbP5bUmN92wwJfcdePQ8r7vs7a+QbMZ16KTQtFs5+vMhWHIuQuX0cZw+NDy07tDJSUlJVeJVIobb7qFlYsX2N7dHZsZPVa0bm/m2iqtDTrZjLoR6zOjamoP9Stmp5mkhuig/qj2qljl4Ha2Y9Gh2hif2W0N1e3LVDtbACgdsnT648ysDixWXb/N1MZZWkunJo4/qkxBaz3XJo0uStv5fbBxxnzYmIktsAGMQfWaqIzNrBN00F4D4w5qeaNcrI7SYAMBLFiILHQzw2vbiKp1UJkxB1YjETlRuWlDhIXpJKPbEZIqCh+TWoEbwBMqzZqOtyt4YeUA56ImTRNSSda5ojssZgTqUQghECauE97HjBBzDjn1nGA/ryoEVvPR7mVaJsRLwgDu8BZwMhb8a7rLkqrn9j057ENhE0sHDrC5vY1OLMWNEAgrmJRD2tzZwXHcsZ+n++S4kBG7KZQJGLIqBoxUBNUZvF7y/UMAysEaHYvTqQg72BkV9OJuOsTqMLkHzGAbhSANFfaGtmulGgSw9MdVFBu7LZ5VDJU3uE6rBbA6d604YRcV+fiNBWzyzHL9FgtnP836TXcPaqRLRdA4QG03K+JKtFdH+oPjZ5WDcSpx7e9+m1BA3tXi8ytbvPM3/4b7L2+lbW+8/Ti/+s1v4NBMfTDgXD2IOlTqcPBEHBAwdh9NXP5AqvgZIyUWCfUZnOe/Gru1EtfoXjqOev6rEFPzg7EajX3wozhBe3AtSQnaINIQluF7SMDIa0sQB5kOXZcU7tl91PCWoT/x82sla0duiYNNTFLCQLtVtPJoL51MAhdcdg/dhuO3BteplES1mVxwF7029uLje7uQjKygPuYIJ9vrW+obx0vXb/ur6m/P7zD9mb/AHL6D7WMvSFYxYSyFc7S1ucHSocNjM7zTUe2jREq2T/fMw3v2B6iduGNf/UpKSr74KG3MS0pKSkpKSp41LC8v88gjj/C93/u9aVsURXzLt3wLb33rW4miaMLSJSUlJdeX7e1tHn74YS5fvsz6+jqff/RSTujOcvrcJucvb+fa2p0Ojz52mo2NTYIgxPeDIaE7y+Ura+nEOoAxhl7PJwj2U1+2pKSk5OnDcRwOHTs+yGgehRBDdbSN42FUPgOsWB90FEX7bu14sYCc66TQyk0n9mXk44ZdHL8JNs5WQ0iM4xHU5wlrM7mM8uHxS1ShnndUaQwZxVZ3V/ccP9ZgEQS1OXrTS/i1WSKnkmTTydzPYPugK/X4eCVjRzno6nRqdZt0QwXtodrjcT3fPPNG5LKZAXo2f/yVkKxEHdpmsD5JnB3dSdpsUqM8azXeF7KdZGpRIZBCIITglDuDIK6fDRBYg2/3rgEb2FhM94TEExIFdE3Euu6yEnVYi7qD8fTHn4xpW/v4VtO0cb3vc1Ezly3atZpVvb+M31q1lnsfw/5cwx1nj5wiY1BB/ntAZ+bQkFV1sS5vVJ1i88SL6U0vkUpZQsTnPAnyEMkY42zads5dIM78H4jWYsQOiWRbV4vNiJ3PCg6dhCTT+Hoz6hoQ1uB2898NlQ6ob13ItRnHy93H/bYixfIMWenSWssvffjzfMl/+F+p0O0pyc991Sv50+/8ilToNsph++gL6E0t9hdE7K5j/+jnESdfgLjtlRPFS4HFOF7s4tHftpDIl3wZzpu+Ffet343zJV+ZE7oBog/+Pub8I0NOF8ZxMUP7tc/M21GZ3NfAqGPtdbZG9JxAZh8G1bIHtupWqtiePs1Gl4SN+Zzdt3ErmIL9dxrclGNMUBkM6pbHhSgy75N+cQwxeIekP/EYhRA4YS/3jhWQBM3ks6xnLz+E19rY87B47U0qmfeiNYZOe+8gGPfAYcSkACEh8JaPp7/q9s74vgmVwyeon7pzz34lJSVfnJRid0lJSUlJScmzjl/4hV/ggx/8II3GYELyXe96F4cPH+aBBx54BkdWUlLyXMBay/r6BhcuXMhNqG82J1vtPX42nhAyxrCxscnp009iMvZ8e80hG2PY2W1ireXipRXuf+BhHnjwUe5/4GEefuQ0zdZTt1osKSkpuVa01vuogzk8QV+09NYFG3GhQ5xeK1d/OqzN0F64IRUBO/PHR4scUmGkgwq7qVAtjUboIC9MOC7am2yjDbG4nV+/xBYzbycJ/gnarbF19E5aSyfpzB+jvXQqtjrO1lxVDtqtYTIZ1QKQUQ+yttVCoL163t2cJBM3S7+OeAYHy4Lw8DLTf0M1eG1cy3pT91Jx2E9Ejy3jJ7/r2PJcxOJ5LGTHIkXfAr2S2Y+6cDmo6jiZ8QgExloCqwmsztsWJ+OoCcWCrDAjPWakR0O6GCyBNWgsIYYdE7Bp/PRaFEJw1J3iJdWl3Po6NhbJs/Sspjci2KJ4TNqdYVHc7qGxCSmpN6Ymi3FSsnbLq/HrsUgYVGfozh/FKicVqlKBsS8+9bOJhWTn0K2FAAkR21PnBiJA5K9RmwkKGTQWLf4H/+2LaRgzqPE7qtYvwH3vw/zlr2H1syMoWSgH8Yov/4JuU+kgbzVO7GBRZJKQ3acYxCKSc7Da7PL2X3kP/+IPP0ovip8Pdx6a4+P/8m38i9fciWNDhImwQtI+cALruHQWb8SvzyHMICPdfvzPEHe/DSqTn4eyMA56bez6hdGdAbO7gX744+M/V87erttPo/W0jHymVh5HJPe/29keqmE/kaUb4MveObg3UkE5UxphxD3i9EaIvmPcB7L138XBGzGzS2jlopWHlg5aKqx04ueFcrBOJb6m0jrmxZremTUXxqXCwnsm7Zlfdv7cZ3C6zTEHJVlGucxdepDq7srEfkWk61G/+YVjP6+duANVG7yTZbU+ti+ArDWYffmXIZ4md4eSkpJnP6WNeUlJSUlJScmzkte85jWsrq7yhje8gY9/PP7DeX19nRe96EX8+I//OD/4gz/4DI+wpKTkiwVjDGEUoaQkijRnzp4jCHxkYa4oiEZP0zkKZuoSaXtsbe2wtrZGt9cb2XccKpmfunJlhStX1uh088u32h0efexJbr3lJNNTk2uClpSUlDwdOI6DlDIXxFNEFLJ3ld9Bhr1UeLZAkIgvNpmYrzTXcf0WUdDBn1qM68MCwdQCVkqsVPjTS8MbSzfiDGWkqbCHLmaC74tY+I0qDaxQqKBDUJtl98jz6M4sI6wZysobha6MmJQfJeSIuIa4CDuD2tHEQlMuE1JKVNiLM3mT7RdFsXEIKZmxHusmfq8UM737GdcWaJuQunTYTUTuntVoEwvM6fqAQ6qOyggKNeEgEYSJjb0EZqWHIyQiEcdbJkQVXqwVq6gKFVuYi7yVenx4BA0R7292DL7VdGyUfgZw2GkwJVxadnBctrSfq+UNcYZ3dY/pUKUU9VqNTncglmsEakgKGtBoTHHuydN7RrZpr87GyVcwfeURWgdvGdwbfZE7W6O4UJfbOh69qUVqzUwW5ajgi2I932RMttingBUyZ6tuhYcxGmGi8Xm41mIf+DA4HuL17xjX6wuKfOmbMFpjP/lu8JNzKBXc8DxYefJpsV4XVmP3uK5EIdBCBZ04oCA55jIKcHutuIyDVGAtUke856HzfMf/+CCrrcH1+E9f8wJ+6iteSt1NarQD6IjdQ7djqoNnX29mmVpzLbdd8z9/Gnp7CL0jr+PxYrQ588Dkaz9xtRB2cuDonmQF5Uw9aZtYeo8boQCqrXVU5NOdOcjU2hNXt92Ni7C9sqcgL6yJbd+L7TpERkF8n+sIt7ON24tdSKyUWGty4nn4nv8HdIhI728Z982WCkmyyTF6EFQ21tLdJiq6SI+H22sRVeqDd4q1dKcWcP02TpS8L8IejY0ztA+cIBrjmCCTwKvG2pP0ppeRSsWBP/tg6raXAILO6fuxYfyMF8qhdvJ5TD3v5bm+lUM3EKyOD7ion3p+Wau7pOQ5Til2l5SUlJSUlDxrqdfrfOxjH+Onfuqn+Df/5t9gjMEYww/90A/xJ3/yJ/z1X/819frkCN+SkpKScVhrubKyyubGJlFiVyqEwFo7JHQDuAqiQhLE8pxkcVYmmW2Wc+fPj93eGJ0jEbrjD4MgGNpGdrwXLlxmaXGeza1tdBRRqVY4sLDA7OzkunglJSUlTxUpJXNzc2xubo7uYA0zlx8hrM/Rm1kGoL59EWUiTCISd+ePYh0vFjysodLawE1q1jpBB9PdwWQysIP6HKaQCT4KozykGQhBYwUVa/DaW0gdElWmiLwaUodx9qQAIxStxZNp/V2A1tLJWAy4lmyxEfVmh5ASqTVWiFT0EiMy7hCSSnsTf+pAIoyOWm8hiz4RSqQQVJL62tWMoGytpZmxLw+t4WLUJnv01nSXUAxEpBnhIhFpJrhK1p0VGWZUBSFEbt0bpkfNKqYzVs4+cZ3pmpg8PVkXDk3CtF44QNtEudrdAMtOjVaY2R/2J6wVj2Qz7LF44ACdCxlhRQgiJE6hLj1AtVan2+nsw/kgxiqH3aMFq92R18lwW79W+1BPHSFNGMt9FqT2E6tim8lELawvc33GVsYGa+xAQBcivReKQu3QPn32bzCnXog88fyJ/b5QyFd8BfbFb4DzD0MUwpGbwatg/vM/e1q2ZwuBGpFXQ+goPX4y8nNlEoTRVNpbCKPRbg0rBNXdFQQ2DnaxlqDX4//404/zf33kwXS55akav/KO1/Hlz7shdmXIBCIIYHblMZoHbyFKBO/G1sXhwXZGl+TJ70/heVefRiwdH90ZRmYJ770R8pf4iPtHWAPGpsFRWIu0/SdBMsZU9E7/byxurxmLzFeL0UOOCaOwCISO0me4kC719bM4wSCgKS5n0EFmgsMssZ15+u5J7rfcIRJxKNFowTvK9xv1LLIaUIN7PrHgD2szA8FbSILGPGp3JX4eqLh4RW33Cs0xYndtO65F74Q9nF6TuRO3otTex6rP1G0vpnrkFK1HP43ptlBTs1SPnMxlaPcuPUnzgU+MXYe7cJD6yefte5slJSVfnJRid0lJSUlJScmznh/8wR/krW99K6973etYX18H4BOf+ATLy8u8+93v5jWvec0zPMKSkpK/j5w5e47d3fyE16SJ6oUZycX1wcT5/JRgeW7/kzlx5prNzT9lhW6IE3yKyH4hTgs9v8vFS4Os7yAMaTZbLC0ucuTIoX2PpaSkpORaOHjwIN1ul243bw+NtTQ2zqF0gGqugtU4QRevG9fYlNbQnj1E0FhIFxHW4Pj58gwq6ObE7lSA25fIQFLvWgxlegM4vSYzFz+Pm7H/DitTtJZPxYK6BduvnVoQAdEhtr/uzD4PiYc6ijMyM9m5MuhhXG+iWG6FQIU+2quOFcdl5COsxfE7hLWZ4Rq0BQtdC0SZmrsKwaz00neOtZYN3UNj8ITE2tjKPMAktWDjfQ+EIZa3k6AsLH6S+Q0Q2jgDvCoU1WR7SgjmVCzKZgXvrtV4RlPJZCP7aCpWpXbooxCJoN7N1BvXI4Ts4hvcG3HMp2R+KlQCEoFOlvaN5vLGFS43t3jekRtYX1sjSAR0IwS16TlqrkOv20UqyezcPFIqLpx9cuz4nyqxeBaBkMheC6fXRPkdhLUYqXAiHxUNzklRQxTYOJBi6DtOPtsT4uxOW7i2rVQYq5GTxHxrsH/085hXfw3yFW95Svt7vRBuBU69KP3d+t0JvZ8abm+XsDodW8YLiVUOU5tnac8dxSiXSntgay6igNruClJHkDwH3fYmyoSIJJv/gQtrvPO3PsDnrwzqSn/5Hcf41f/ttSzP1KEveIq8+Kkin9lLD7J99E6kifA629e0P8Xni/PiNyAmCJjyyC2TV2jtcBBS+vso623S67VfT9oKka5DwNB1ShKw+rTl9t58F3zqvZDWu864MIg4t1pFPbL74/V243eTUx24JkiJrjQQfiu3PyrsEclG7v0RlzKg0Eb+/SME2q2hIn/vzPmi4E0caBbWZjFCxc4lQhB5dVy/RVCfg2RsMvSHgm1qWxeoZGqfz83NsXTwEKbTBGuQjVnCMGB7c5PA7+E4LnMLB6hUB3XKexdOs/PpD6TXQ7hxhd7ZR6iduJ3pF74a0+uw86m/GRtQ4S0fY+4Vb0SoUuYqKXmuUz4FSkpKSkpKSv5ecOedd3L58mW++qu/mne9610AtNttXvva1/K93/u9/MIv/MIzPMKSkpJnE9Zams0WnW4XJSWzszN43mDirtVqDwndueUZzqc6MC3ZbVua3XjybXF2/0J3HyVBx4lsSJEXuovIJMlvP5Z8a+vrTM9MsbIZcu5yEyHg1LFZbjg8U1r6lZSUXDeUUpw8eZKNlctsXDiLlQon6FBpruFkRORqcx2pg9yyle4OQdaOXEi0W83VTS3aoI/FmLgObd+eWUj8+kJsaQ4js9qi6jQ7x17Iwrn70nq0rt9i5vIjbB99/iCrGsDoXHZ3LKxoyGYgCxGLHok4EPezON0dwurMYH3W4PiduB74OCE7saEVOsI6bm7bENsb9wMDZORjEWh3IBZYGy/bX7sRgkB5uXrjdeEkOkl8bCIMdelQE076npi1Hmu6mwrUFujaCIuTq8ktEOl6+vSsxrEyV6d7Wnq0TJjr2bURFQpZsBg8ru6dqgpWwf3a40lsGAC3unMccepciboYLA3hxHXArSVK8p0VsYW6sLEwv5MI+d3A5/z2Oi+97XbanQ7GGGrVKq47bGO/ub421LZfZNhDBV2scogqhZrf1qJ6TZygm57bcGqRqLmO10kCSUwE1mKERGaEs5GMyvi0Jl4iW1+9GGAiBMapgQ7i7U3AfuSPsMduRxy5ae+d/wIjKjU4eAJWzlz3dSsdIjtbdKYP0ps9BEIidER96wJaeXj+Lm6vBVgMAq+9hQr99E4S1iBMnFn/nz/yID/05/fiJ1Y/VUfx/3vry/nuV90xOIdZ8bOQ7Susob51IQ7+uQa0W03t9fFqOC95A84L88HlUXuX7tlHMJ0msjZF7cZbkUdvwVx8bOQ6s3XDgeS6swjbfyYVAlMK17LAps/7TKehYI38E+A683s/jYiy77X+UzATGNVvLViGy8jHuNXceYvcGk7QzmXmq7AXH38xaBWRj3WK7iKFfU/epyqbQZ7FDkaaPimTYyx1BMYQTs2l6zPKxW8soL2Mi15BSHc728ysPD5oUC5zFUnnXb+MWb8ULzI1z+aBU3QO3JB221hbZXH5IMuHjxC1dnJCd5bumYdxZhcxvc5E54CouT24XktKSp7TlGJ3SUlJSUlJyd8bHMfhz/7sz/iN3/gNvv3bv50oiidb/tN/+k+85z3v4cMf/jDLy8vP8ChLSkqeaXzf58kzZ/H9wYTUpctXctnP29s7E9dhR8yfCSE4eUixvmvYahoq7tWLyEIIHAdMfwNDnwPJHKZS+1+/H1p+7z2Ps9seTELf99AqR5anePsbbqbqlX/6lZSUXB+klNS6O8ysPj6+U5LplhXWZCbzNEeakWyx0sEKEf+3L1oUs3OTviJr5SodpDXxs7W/7RHoSp3m8k3MXn44bVORT6W1gT+9mLF3tcheC50RqIU1Q49tCRAFcRZk0k8ajeO30/qmwhqENbE1cTEbmzhrty++SxMR4ebrghtNfetCTsCIqtMgYrtcKwSRdDBuJbb3TWrjDm2ncEgckRemAVyhOKwaWNvO1b7u2QgHkavTPYrA6tw6VVKH288EMeh9Wn1nibM188s1ChnaGsvN3iyLqsp9vTUOqCo3e3MoIXAcybbxOahi4UYKgWMT54D++RWC0OrcVlZ3t/DDgKlGY+L4XG+0qCh0iNQRVsphO36jaayfpdJaT8+tdiq0F28kTLIpkZKoNhdn9CfBJMatsH38hUgTUe3XYu7fMzooCIqF2sZx44hM0URo6p+7keWa+/Xl9QjRMY+9/wPPCrHb+h3s5z+KPf9InJV88ERsaX49twGE9bk0Aza2sQ5xeq1UyJYmwk1+T8kGFwBIxcXdLt/523/FXz4ysB5/4eF5fvObX8edh+YH2xyR0YzNi7xeewt/anHvHXj118AT92M7uzB/GPXSL0MuHMGsnAXlII/egnDz13f79OdoPfDxXFvn8c/SuOUVeFAQvAXiwGHklTOD67EvdGdXMOSUIYbu+SJPo6w9migYaooDoQzkgoEygnLaZhE6yDmEWOUQ1mZwe830nhLGxC4fbiV9lwksIgrT94wobMOmmeTxc0DoUdd45nhbC+TLMYTVKaLqDEYqhLVEXp2gPoeuNGKbdGswTj7Qp7FxLvd7ZX4R/wN/QPasiNYWB1qfQoU9moduTdvXV1eo1mqIC4+MFLr7dJ/4PGpqduznAKbbwkZB7ORQUlLynKac8SgpKSkpKSn5e8c73/lOXv/613PPPfdw5swZAB599FGOHz/Ob//2b/N1X/d1z+wAS0pKnjGMMTzx5BmCYHiiZ219HddzWFpcRO+jtqCx/TwTm9byDjW4SrB0DVndWaQQI1Ov+vN8crKekB+nsdz/RMBuZ3jK79Jqi/f97Vne+rpnftK5pKTki4l91iZGEFXqgIgF3H5GdmJBLXSEiPw0p0/qCFqK3uzBYZG7jxAgFAaRr4FrLaKQkQ2ADuPs64TezEGcXpP61qVUTHG7O7HYnRHLpY6QST3TsXW3ExG2nwkrEzFE6gCSTMbUplaHUBS7TVwzNbNzaLeWHhsrBLWtiwgdop1K/LnjIcMuMlOjVUmFX5lCq+Gs48Gah7Ox092IJbq4nxAsqhqtgigYWEMtJ9ANr2+UkF08cqpwLK21dG2EK+VYJxIhBHOqStVEbBqfilDUkyx7ay0aS5BcU3Oqwt21QyypWmqNXpMOtaJ9+Yht1aRDW+czl7thQNWbLKJMTc/guC5RYncudITX3kCFvUG2fZIpafoZ+VLRXrwRqcPU7l9FPtNXHmP3yO1xQEO884T1edTulYHILATNpZuo7q7mRGsrZFwreJINMgIotpHJ8O5/PxlIielZFQIjXZQeFv2y2M0rEz//QmDXzmP+8D+k9aktwKP37r1c5t97hRxawG8coL18Epu5voSOIPTTdVjpEFanY1GzvwUp0V4VJ4it1d/1uTP8k//x16y3Bw4Z/+I1d/LjX/FSqm5x+n5UtGS+WQBqbhFa62nz0P5U6tjqNBqB9Xtw5Un0J9+L87I3oW56UbE3AMHG5SGhu0/7sc/i3v12PKsxlx4HKZEnXoBob2N+9ydHLjNi6Lm9nHQOxj/N+pfwCCeD64AtCPECsEbH76xiYEnaA6QxWJsPjrLSIaxM4/V2065x3fYoFpdNX5S2yT0q8+Kwtbl33qhAp77lfbbIhZEO/tRBjOMio5Dm8i10DhxPnzsy6MbvwEygkttrob0axqlQaa7htTfTz7xjt8D5hxh3VmYuP0xr8QQ28w7cWF9jbndzZP8+UXMLNbc0sQ9SlRbmJSUlwJBHSElJSUlJSUnJ3w+OHTvG6dOn+Y7v+I60LQgCvv7rv55v+IZvwIwqfFtSUvJFRxRFqcsDwM7O7kihu8/a2gbWWuq12tg+WYyFyMBO27DdtrS6FpMkRUX6+k+gCSFw1N4TrBBP8PcCw+q2Hil093n83Ba7rTEZlSUlJSXXQGXxSPwcdGtEXi0Wtd0anfmjtBZP0p4/Rnv+GFvHXsDu4TvYPXw7raVTSZZznBkqrCWcWiCYXspIAhavu0Nt+9LwRouihZSxkJ1BGD3UT+oIp7uby3L1Zw7SXjwxfgeT+rLSDLKuh0SExHo83W6SkRfvBwgToYLJNYLdzg5ud5vK7iqV3RVUUo/Za23gdbaotDexykV79bgWsIoz2CvtrTgwIEEZTa27k451HGJfbxeoSIVbmDIczmsfpiggG2tpm/yYFmSVaiYLsmVCzkZNzkXNOGN1AlXpsCirLMhKLiM7KtTvrkrnKdXtlQhcJApB1d3bCloIwdEbbkTIWIiq7q7gZIRuAKlDqruraUBE3KhoLd+Uu7YEltpW4foXgshr5M5A2JhDK6dwvffF7VF2zzb9dyqeQc7euC+iDcYzsEi+qmi8xszefZ5GrDWYP/0vqdA9sg9ghEIrF61cjJDxfgsF0gGh4trbE7YjgGp7g5lLD+Vslq1yiKpT+e1JlQSsZJCKdqj55//zg3ztr7w7FboPTdd493e+iZ/7qleOELr756poR1/oVJ/BvfVlsTjpVjFOBa1cbOYeNaGP+cDvYDcG15tdPUf4F7+Kfvy+kfvceeLzI9vTz5/8PPLgjTgvfgPOi74UObuYCv/7IfHtIHu12uTcjBO3c8ciuVZtNuDjKZbzsRQOr4hdGIYCI0bee3kEcVBWbv3KwUgnb4melAuQxYCurF09YKSKLbwThxTRd0pJ6pxjDUYookqDqDZDVJ0mqM+xe+g2OgduoDd7mM6BG3DCbhykkWC8GlF1KucyIgAVdFmYm+PYqZup3fFyand+CbNv+mZqJ5+H7Y4vDyWtprZzOdfW63aHXAOGjpfjUjs2OWC3euQkorQxLykpoRS7S0pKSkpKSv4eI6XkV37lV3j3u99NLSNc/f7v/z5Hjx7l9OnTz+DoSkpKnk52d3c5ffo0Dz/8MA8//DCPP/44Ozs7tNvticuFYUi310Mod9/JHrFFYWEuTcS5I3tNzF8L+62xHUSWSEO7t4edqIWVjc7EPiUlJSVXQzOIaB69k9bBm2kt38zOkefROngzQWOBqDpF2JjHnzmYy+JCCKxyhjKvdaVBVM2LY26vherlJ86F0bitfBaYE3ap7K7kBbsRqMhH9WuDJw/0sD5L5MX21GEts31rESZK5RYZBfG/sjWMrc2JzViL292hn1VoARX0ILUVT8SX7DvDWpACr7uL67dw/Tb13SvMXHksFc0hFkJiYSVridtffz67sBLs/azfr+BdfBUVlzLWEhRqrFcKAQEbukfThnQSwXtKukxLl6pwqKJomYCtpEb2jgnY0D32wpNq6D1ZrN8N+/MesNairSG0mtBqtLXMywrLqsaiU2PJqXPx4kV6/t5iXWNqmlO33saMw9i61oL+dZIZg3LYPXhLLivf7e4MWftalQiwufUl+ZpFIbu/7Kj7Iidu28Ey/Y+FzLkqxBbJMr2uxbHb4WVvGncYAJDPe9XEz592nvwc7KyO/dgCJrH+t46HdTyMV0M7XkEklem+T8L12wNL+f42HC9f9xyGyhh89vwK/+Bnfp//+yMDAfkrn3+C+/7V2/mHtx2dOH6by8ovZOADdHaxf/1b0H9OCQFSYZSXEfZlXE9ah0PZwuHH/gw7Ing82tkYOy6AaHvE58s3wB6ZtxaBdqvoyhS6Gv8YpxpbaPevSenkRO++nfeQ4D3JOumaSCzCB4ONBepC8EIuiCRHvq0vdmeDXIxUQ8K8jAJk7ryYQUCXMbERiQUVdHCCNipoI3RAP1ygf3xkVoQXAmkNjc3zKH/wN5OwhunV08hsgFZSV7x4ZEXQpXLkFI0Xvpr68+/GmVvC7iOgQRZcM5SUVI6cwq/P054/Rmf28FBAiHfwOM3PfmT8Ois1Gre/dM9tl5SUPDcoxe6SkpKSkpKSv/d8+Zd/OVeuXOGuu+5K265cucJtt93GL/7iLz5zAyspKXla2Nra4ty5c3S7gwmZXq/H+fPn8YPJ1poAjz76OJ/5/Bm2Wxpj9p4OF0LgFepzV5x4ktkYcoK3tRa9j3U+Vay1hMmc0X6SrFyn/NOvpKTk+rCxusKVixcwWWHzKmov2MSCPIs/tUBQywvetZ0rOZtUqxxqzRWqOyuDNgRedycVEEc9ffuZcSrsJSJ1mMoWQWMO7Xj4jQOZAVpUmM3ItljlxlvTUSw4hD1U2MXp7MY/iTBvlRuLXMqNj4kY/Ehr40zvtD6yIKzPsX3keeiMCBZnwF0ZirAyBbFI9MeTQenwmm17hbY4PYvbsciegUK1j2npkc2XbtqAFd1lR8cihyckLgqJABsL3Vd0LL4HGKpCcVjVU6G6IhTNQib6htlb7N5zP5L/RtZwJtjl3u4qn+6tciFs5WzWrbUYICL+ryEW0j05sFcRQLPV4rEnThOGe9d6rlSquONq0yeMyvbXlQatgzenWZSxEF3YL2MGAizgdndR2RrdIwIw8kK2zVgiD9ryQrfASDUI0CDOSDbSSZwFXHR7B7t4HBaPjd7Bm18CN9818Rg83dj1ixM/F4AyETLy8/eLVDk78rizZD9+O5Xm+lBb8Z7tC9TGWH7hL/+O1/7Eb/LwlfgZV3Md/vM3vpY/+PY3sTQ12X3IyuHAh7Rmc7aJvpCdf5b0XSL6wmrsRFG44Vtb2CtPDG17z0xc18PqiO65R2k+8DFaj3wabSzijrsnLicxeWcKITFuZbjWfSEYoz/+oRvG5r+fP2UyIrRN3ndWqmLlcbDjikVkhWyLGco4T6TpJBsba5FRmAZn2aRMB8bEGd7EIrbS/qBUBknAbCFAQ2DjYK+McC6w1HZXoNCv2iwEiUg5dE/0WsOOCWrh0MCafeT+k9a179OYnubCTofW8k30Zg/RnT/K9tHn01q4AQvISp1wYwXdGZ0xrqbnmL/nbTjPsJNESUnJs4eyoEFJSUlJSUnJFwUzMzPcd999/MiP/Aj//t//+1hw0prv/d7v5Y/+6I9473vfi+ftbUNYUlLy7MYYw5Ur42tB9rqTLWMBOj2LtRBq2Ng1VD1BoyqQcvxkpueAMRBE8VyOUoMJHZ0RvPvlXqWw+87QLmKMpRtY6pXRWd7GWkzGQn1+SiKFZpzGXq86HD80fU1jKSkpKclijGFtdWXvjrmFdFzTup+52s/wTtr79OaOYKVDJRG4hbV4nW2M8mJL4CSjzWtv4DcWsI6L67cAcDvbhPW5JFsxkwGtE0GLOHMNE+WEbK08dg/elooXWBtnuyWiH4CWDl57C8fvJFWqxWB92d2UKq53mogYcc5tUvciFZUsKvTR3kDMso5Hd+4IU+tn0jZpIpygQ1RpDPpJhdVhTloRVmPJ28ySbDOtqF0QhkZJMY4PXkajdRDcwTQXnS7rTkBdDGpe90zElvHZMXFw2a4NmbEeDenm3lkrUT7LvGnC3OdCCGaVx3omm9u3OhZ1rvr9aakgkQiEEFhrWdEdHgm2U4vzy1GH0+EOr6wejG3OhUAB0sq03ne6NpvXoaIoYm1jnSOHDu89kj1LKY3O/LTKpTe9RH37EmFlKh9AYm0crAH0Bc2p1dO55aUeuBHEjjQmPo6F7P/sKIpHuW+TnIpbop85blJnA9vaJvzQH+K88i2ozhb2838L7R2YP4h44WsRd70eMapu8BeS2tTefQBpNNbofM1jKePdzXbcR+1nMSKbXxSWEcZwabvJd/73d/M3D51N2+86tsivf8sbuf3gfN7mvkDqMJFaNiusiQZjjW2HyF5j/ZIKNuMcQHKP5J8lw4UKrB9fc7YfOCEk1WM309oeFvb7eAuHWH/f72L8wXO2/fCnqJ18Ho32dpx1PwapQ6yQg7r2xEFOVoeF560YXc/bmsHzrn/OijfzVVI4g1jswNpbCKyUw4EC/e1nlkvHR5zRLXWICv3kuhHplgYW5XZwKkXWjyP/Tskum992vra3IM4Uzx5bFfnIsItxB+8jtzfCIatw/KRSWGPorZwnam0j3QrywGG27vhS2m4DKxVeZ4vplcepb8eBJ0F9jmBqEFTmuC6tZhMdFe4bIfBnlqk0ppmZn6N5/0eHx5Ngeh1UpT7285KSkucepdhdUlJSUlJS8kXFj/3Yj/G2t72NN77xjWxvbwPwgQ98gOXlZd773vfyyle+8pkdYElJyb6w1tJsNtna3sFoQ61W5cCBBbrdLlqPmFRK0HryJLMU4EeZzC6gG1gqnsCbMDcrhKBWEXiuJYpGT3j25zQdNVqk3i9+aDEmFuUrHihJOnlvLOhCSVpHCY4cUFxYH31cXvWSoyhVZnaXlJQ8ddqtJmbCM3gkQqKCDtrajK25iO1pdbY6K/jTi3id7Vh4STNYd4iqU3F70s/t7RJ59TSjWukAa03eNt1o3O5OKjhZwO22UCZEJBmEYWWKqDYzyHK0BqsUKlNvWVmTCC19MWL0O0AajdNrEdUHWWap4J21ILcmFu4zNUb9qQM5sRuIRfqM2D1asMm3GSFxdIQb+chkv7VQBG4lzTIVAxkl3k6YF7oHaxYcjWoopXLvEFdItk1+gR0TcMAZCCZSCGakl1qUA3TtCDEwGb9CIPuhBNfw/nQLdtFCCA45DerC5e96K2m98ZYJud/f4BW1g7m+oTa4WXFZQEsH1KWb1iHf3t3dl9hdnV/EnyAGZsUmAOyghm9Yn4PtS3Tn8ttx/NZA7BOC2QsPUt+5PLAkNzoWNLMWz4X6wUPC9oixCSwy8jGQCsBxlrnG2kFWOUB031/h/KP/L/JVXzN2X58pxC0vxf7N78AE4Tjta6J8aYV+xu1ettgFtFcQ3axBhl2y9c7fde9DfO//88dstbvppv7319/Fj37FK/AchdDRUBBNYbQjxpoXNUcL2eOyjfPrzv8q0JU6zU++H//yWbAGd+EgtZPPw5lZINrdHFqDbMzQu3QaGw4f9+6TD+K8+E1UF49hP/kXY0chIz8O7MmI80Y5qOy5TEX94dHbUeL2NQreqfycrXPueLln91iKQS+ZTG5pNYRRfN9mtlRkVMDUYGRFMX1Y8La20GuEKC8K47RFlxZrEZGfu/drjSlW/uaPML1BQJNFEM4exFZnAQgaC2ycegXhpQeZ3r3C5k13J8MSzMzNUa3WWLl8iXF0qjPMtMfXAAewYUDU2sadW5zYr6Sk5LlDKXaXlJSUlJSUfNHxspe9jJWVFd7ylrfw/ve/H4CdnR3uvvtufvAHf5Cf+ImfeIZHWFJSUsQYQ7PZQmtNpeKxsrJGs9VKP99tNlldW2dpcWHsOqwdb50HsdAtxOgpy15g8Zy9J8KUFEg3zubO0p8XlfKpCd3WxnW4AYyFrm+RIs4sz027ivzE1tFFhaPg8qbGT1wg52cq/IO7jnLbyfHHrKSkpORqsNdSpiERjWTkx3WJM8+vflac7YsHQhJWp3G7u2lmq4x8ZOhTaQ0ERBX2qO7Gdqt9Wcc4lZwgoPxOmm3Zt4VWQRsV+el7wAl7RNqnO3so7iUkxqtjlYvTaw4EFKnQbhUnzNhsj8j2lCZC6GioLnkRYcxgn2Gotu/ItsK2LHFmerp/xEKq6tv8JvW0ldVUgw6+V0vrQmcFb3eCHigQzGuXpjt46SkhmRIuTTuwHO7aYRFFFoTsUW9GCZxwZphOssLN9bQdBmaUx0FV47IeiDKrUYdP99a4q7KYCtkRhs/3NnhB5UB8/Iit13u6xwFVjQPO9szYjpk+coLm+dOYaNj23AJBtj59Wh8++VVKWos3Ejbm0ze88jt4rU1qO1eQOsBIh+m102kmd7+fFSqXDW6tjF0V9lW9fEA/A1T3awjTv39MrsYwQQ9z7mHUTS+6qvV/IRDVBuLVX4P9wO/u3Xlf19zwvWeFQlidnrv4GTLA6bWQ1mCtoRUYfvi338Wvf+De9PPDsw1+7Ztfz5femtjBGz221ntuy0PC7f6+c/Yt6fviuNAmWbYvt4pYoE2uIXPDnex8+oODmt9AuLlCuLlC4/aX4S4confhMWwUIpRD9djNyFqD9sOfGjuGzmc+ROXi+Mzu/t6osDcUHLV/Bn8M5Ja61mdLVuiWsaW9DP0kwEAk7hrZjGziYKaCSJ5aqmdqwlupknt0wuYZ87fNNQn4+f4WBlnqCdqpxAEviX18pbnGwplP0V46SW/2EG6lSnD6fijU6BZYajtXMMojrM+m7btHnsfy676amypVdBShlEIqxaXz5yaONApDtLe3bCWcUtoqKSkZUD4RSkpKSkpKSr4o8TyP973vffzSL/0S//yf/3O0jm0Rf/Inf5J3vetdfOhDH2Jubu6ZHmZJyXMWYwxaWxxHsrm5xeUrKxMztiGeKFrf2Bw7KTRqHkuQm1cCoOIKQp3v3AssNdfiuntPHPWzrItzTLF9+Z6LA9DqGupVkU609xmlIxkbW5fn7V+h4pIK2wAH5xXLcxI/hPm5aV7yglP7G0xJSUnJPqk1rt4ytF+HNbXTldnKzwKLyNUEjbP64t/7j8T6+pNor07g1cAanF6T3sxyXANUxhmRxbrhujYdW50n9byFAOu4aCFymdtO0KXSXMefWR6MQbkYx8tlE9qklnHRmriIKNgij+5UOEZRD5tI0PF+C7qzh5A6QCbZeFY6RNVpVNBBGh2LEUoR14i1GKeaChTGqSCCbs7W2gt9ujJbpzfJMtwjgMHRwy82mWRWSmJR20mEat9qIkyyJ4Zb3TlmpYcQAj0iY/Wg0xhe71UQGo2bCRow1nIxanHMmUrfmUtOjcfCbRoiFtSFEDzob7Khe3xZ/RhCxGL8uu7xSLDN8ypxgJjBEmDo2oi6cGnUGyPHUERVqiy/6G5WP/cJTDAQhCyCoDGPyVjYC6Nx/DaV1jpSa8LqFJ35I0lN5jiYQkU+cxfup5JcxwDaqyH8diYzlCT7GrI2zrGYFl2VVAjJXWlNPuBixPmzieBljQat96zn/IVEvuSN2Kl5zF/8Kujx9dZtMUs3kwUtkt+L+25lXPPaWoOIfLoLNxDVZtLlne4uTlIu4bNPXuI7/uvv8/iVjXT5t77sefyXb3gNByuZM5Nk5e8tfO7Ry9rkmarS4AQrBNqpQPa55FSQ0eD50hdpLSAO3ki3Ngu7WyM30X7008y/5qsRrod/+cn0C3iwMb7MEIAWEhMG7MdrSOoArRwQcjjb3Q5Vyk4ZHKOnRvrk7EeyJusWuWvJJsEDNlPgYoyjByOyzoVIe+89mqu8i0e8p4xyc2syTgXHbxMB1vEw0sE4Ll5rg7A+h9AR8+c/i7SaqdXH8RYP40036FweYQWSUGmu5cRugJ3dXZYO1pGZknKymEE+gtrB4wSPfnp8Bynxr5xDnZpG7CfbvqSk5IseYe11DpssKSkpKSkpKXmW8eSTT3LPPfdw8eLFtK1arfL7v//7fOVXfuUzOLKSkuce7Y7PY09e4craDsZYZhou07X9ZUv1UWo4mw6Gs61hWIC2FiJt2WyaIWHZVTA/vfdkiR9awshScYezuKVgYu1vgK5vOL+maVQFhxdUrr+1llZ3eN+UjO3K07E68bbDyBJENnc4qhXFi194x74mkkpKSkqulovnzrCzNVoEGcJoVNBJJ9e1U8FKlRHobJJtOHi+ebtrWMch8hogJSIKsNLJW5RfRVab8ttpbe+0LeimIg/EQmR78cac8CV0iNtrTlxu1LsorE7lxmr7FrT98Vobi09uNWeHK6OAmcsP4wQd2gvH6M4fi4X9zg7SmkFfa8FEuW0YIdHV6dw4RBSgCiJft9JIa5H3qbQscsJrOJSWjVrEjvHxrUYJSU9HHHEbqZAdWkPLBLQKVuUN4TAvK0/J8aSPtoZ13eOgMwi4WNdddnXISXc63cbHupepS4cXVZYAWIu6vL9znqpQNGScxbipfUIMr68f5YQ7w9mwyQP+BhJ4df0ICsFaUkvcE5JFVePWm26mUd9/sIfRmic++0ls0MMKRVSp56yAsZaZK49Q37qQk7Eit8bGjS8ZiKfE7gZH7v8LKp3MfWcNbreZy9y2RZvreCDx9XOVaKeSr2WNyNd9Btx7vhp55nPYxz4dZ7MuHkO85I3I57/6qrf3dGCNofPR/0Xv0hl0ErxS3V2l0lxNJUa/cQAEgwAYY+Jjam1qKz4IQokDYbLBOX5jgc6B47ntuq1NCHv84l98lH//h39FlHxBrXsuP/XNb+EfveYluH4br7ebW05kXCdG7g9ghQPCjrWojzO4naHnoyV2fshdH9bGdaOz14dy4Rt/gK2PvGvCSMaxh3BrLQee/OREq3YL6bNOKw+r3Nw7pB98MMmx4Bqk4cnjyVjRp2MY6miHxmSL2d2QfxcAGLPn/ZmOoUi2zejCe8bkArOMUETVfi17i5UOfn0eZBxk4U8v0ZteyrxnDHMX7kdmHC2cIzfRmz2Ev3ph4ni3j96ZG9vC4hKHjh7L9em0W5x/8LO43V2sEIT1+dgiPqFWb3DyllvZ+fQH6Z1/dOL2vKWjzH3JmxHl3z0lJc95yqdASUlJSUlJyRc9J0+e5Ny5c7zjHe9I23q9Hm9961v51m/9Vsw+bQlLSkquDmst5y9v8+F7n+Sv/vYxPv6Zs/ztvY9xaWUbkyjNFfcqa78CWtuR80yjJthsfj4QSyxGz01J3BG69l6xwMZagjDevh/Gwnl/mb4R5F5steJnTrtneeJyxOq2Tq1bhRCMKq+tDWjT7zMQ2V1HUK/E9cRrnqBRFTjS0ul29xxHSUlJybVw+OhxpmZm9u5oDSroACKuJZy4YiD6v8shoRsgmF4krM2m2XTW8eJ/Z0XmqxBPtVejmAdYtG7t1yqm0LoXReFY6IjpK48iM3bnwug4G7D/nLcapYNYSM/sk3E8do7cwe7yTbHQDSAkujqVrxErhkVH2a8Dnmsc+ZJL/jN4d0V7JKFfFB0eDbe5rDtsGp813aVJSNOEg3eRkMyrKnMyn9nbthEtOz6rto+2hqaZXF9ZCcmZsMljwfagDcEl3eZi1E7bQmu4ELXZ0PF7sP9f38YuT5E1hMTv4ceDHYy1nAlj0dEAO9pn1wzGbIETx2+4KqEbQCrF0snbCGuzschUEKvqG+doFIRuACfssnjm3tSCH+IMzI2TL893FDInDgGpSJtvvHrZLxZV88uJwjUmdATv+3XMI/cO2tcvYP/yv2M+/AdXvc3rjbWGnU++n9bmOlESgBJVp2gtn6J56FYMEFZnsI6LVS7aqQ6EbqBf9yYrYArIW7nDUEAMwPntNl/107/Gj/7P96VC94tPHuFD/+6f8s7XvnRQiqafNW708P07AgEIGyGMSQ3Ic0K3Vx0pdPeXlZGfvz6EwBSDI3SI+dP/CxVcy/fIyd+B3c723kJ35vgKa5BhIQDgRa8tBHj0f0T6cz0Z+d1+3/dUfrmnNLLcfZ3sdb/N9n838b8db/CsB7RyiaqNVAy3QqVCd39cMgoK7xlJWJvLDSG6cmZPQTn7F1Efx8m/r0zoE3z2Q8yfv5+p9TNMrz3J/Nn7aKwNXAKWDx0GYObF99C47SV5V4ICwdrFPQXxkpKS5wal2F1SUlJSUlLynEBKyW//9m/zR3/0R1QqlbT913/91zlx4gTnzk2uG1VSUnJ1aGP44N89wYfvfZLzl7dZ2WhxZXWLMBpM5sW1qK9t6sfYuLSgNhZt4kzrcS7otjgfRJwlPT+tWJiWzDYk81OS+Wk1MfvMWoii/O9hFAvRjhJIGQvgWk+e7Ov6mUwLC9stk65XaztS7AYII8v6rs4tD32BXKCUSMcfBJNFg5KSkpJrRSrFDSdvYnZ+If+BDqnsrtJYfYKp1cepbV1E6iiepJYKpIPEIowZZKCNeuYKkVj6FsS2UULefhASq/Z27SiKWEO2zX174P6vgD+9SHfuUCp6NzbPMb1xhqXHPooMumnN5L79rdBhKvYILCrMC0pWuQTTS/k26exLwBnKdBxR47tpNZeiNqejXU5Hu1wIW2w6AVqOPq4tEXJJdogr1ea5pNus6fz4p4SLKqyqacI9A8mUkKxEXdb1ZIEtwnAuaqXCeDMRpS9GbYy17JogrSV+IWqjreGxYCfd/9CadBmAntXc11ujlWlrm4jAalwkHpL5xjTGGB55/DE++/kH+PzDD3F55cqepVcAZufnOX7iFKoyEKXbJuJBfwt38+z44xH51LYv5dq6c0eI3FquzchRAtD1MfCUOowFbUjFNGXCWIQ3enDtyuF71X7yPdjt1esyjmuld/5x/Cujj3HQWKC9eBJdGQQwWDUiG3pEwIgoiNKi4J7wZ3/7KV73r3+Wjzx8Jv5cwP/+llfzvh/6Nu6Ycak01/Ba6zh+G0yINBHSamS//nf22ThGtGbUs7A+jXjLd00UYoW1+PV5dCZYZtQ+0mnS2DgXC6DXC6NpbE7OCE6fMrafWR8ibeZ4L9+A8/pvghvuiLv1l+lnXqc/w9fkU+KaTXGHs+uHeuzDdSF/zrNysgGrIbl2BCDq0/C2f0ZYnSasTBHWZtCVRj6IAIs0+evWKbifAMOBEFJRPXgc7VQI6nMEtRmMdOhNLbK7fDM7h26juXzz0DW4tnKZ1cuD59nuJ95HULg3BZba7gozu5e54dRNNKZjpxIhJFO3vxRnam7iMeqeK8XukpKSsmZ3SUlJSUlJyXOMr/7qr+bChQu85jWv4aGHHgLg/Pnz3HTTTfzX//pf+fZv//ZneIQlJV8cPPT4KpdW8/aMozKpR2EL9anH9iMWvPt25ONEYktufiiHowTOPsZVFMuz9PX7SPd/LFUPHDVscw6j5yF3OobFGYk28TKeY9EmXpc2sdDd9i1hFNc7n2lMjlt2XXfi5yUlJSVPhW6nQ6dVmBwXEmFtKk44YQ8n7BHU54gSi20BCBNh+vWEJyEk1uq8XGANiGuozVnUgQsfx7VKK/k+jkcopnF6rbSGMcrBJNbqYX0e41YB8KcOsPTYR6i11oE4O3fmyiPsHH3+YHcgsV8fbEPqEL2XJXtfwJkguMSZuIUsc5O3FL9CxENRl4ZwqCYiaQ9Nz2pM1XIg9PBCknrblnUV8LhsYpKhKQRR4chditosyAoqEVKEEHhC0bQhTtKmsRhgr7NmsKzpHjPSwxtxjne0Ty+5ti5HHequw5WoA0CIoWVCHgw20/49E/GR7uVcZnnThgTWoJPMyG3dI7KGCIMhzgjaNSELsoqTZDD2Ol0e6ZyhKuKAuMAYrqyusr27yy2nbsLZI5BienaWi9sX+dz2ZYQQdK2mFoXU9xASK+0tOgs3DBqEwLgVyARIDNsmM+ThvB8xbWgdQqb3qoa4nEDyudQh6DB/Xw5dnxb70McQd3/V8PqjEPvwJzAP/x2210IcOIJ8wWuQx269qnHuRffswxM/D+uzODuZ4AohMNJB6ex5GXVf5q26jfKQQRd/Y4Uf+q138VsfvT/97Nj8NL/6/34L99x6HHQPGQXJsyTZnlNNrMsz2eRDmxu+9+MR2ORcJ8t0mvBXv8meJR6EpDt/jPrmuaQkw0gJFmENXmuT3tyh8esagzO9QLSzlmYKO91dGhvnUEE7t7Wi/frwKMjsj0C+8i0AyLd9D/avfgv78N+NH0TiJHJ987yvlvw5Ekkmf+poYs2+x5eec0SuNvjQe6G9A5dPg1QTw17EkLNdIp9LB6PcOKu+8IySN9zOmm9pH8rcq4XrbdQ2rbWsr64glWLWk/TWLqGr0whjUEE7dwy8zYs4I56Nxp8cCLXX5yUlJc8NSrG7pKSkpKSk5DnH4uIiDz74IN///d/Pz//8z8eWhlHEd3zHd/AHf/AH/Nmf/RmOU35NKinZL51OBz8IcB2XRiPOknns7Hquj2BY+DUWgtDiuYN2reMa1FVvtFBcpO8EKcX++l8No3SFUe59cYZ3nF3epxfEE2z16nAN70ZVsNPOr3y7ZZiqxhnaEO+Lo+L64Gs7+Qmpjh9ns6sxtcE9z2Wq0djHHpaUlJRcPVEUce6J02idF1ORit7MMsJEOEEnbXY720RePWeRKnS0D7FbXFuSamHyXegQFcV1kxGxrBTMHCSKfKq7K2At/tTCSIHIKpeoMoXX3R7UPxWSsD5HVBvUyDZeDQpZtrWdy+wcuXNypmW8FShKHtbg+B2E0RipMIDxGmm93XifBrV2jfLy2zE6l4G6jeZRYtG3bSOUlbiZTL9N61OtOHQrAmEtVkBgQYf5E3BAVuhaTSepzd1L/l3DScVtJQRhYrOciuBjj0BM24SJAA07OmDJyWcwa2t5PNxJf+/ZiIeCbQIG78fPBRts6l66nkthiw4ak0hEWIisyS0T2ICO1WntcQM8Ge2yaXq8tLKUjl9j6VlNTQzOca/XY2VtlaOJ3e4kOqFPD5Nez2ZU/d0CQ8ELOkT18gEmNikRMHALAKxO6sTLga3xPhlkyg7OmLQamzUGFQLRX3emrRDHAd02RWwUoP/kF7GXHh+0bV5GP/Yp7N1fhXr5m/c91r3QveHt58YyMiu+2Mmmx7j/hdP2xefkGCkd8NAnPsy3/cb7eWJtO130a196G7/wjjcyP5Vcy1JiXC9vyy0ERrkFgX0E+xW8d9aQjHgeZDBuXIs9rM1SaW8iCg4Ftr89wA069IZXsSf1U3fifOR/wtr55Lk5eHYOakrbRIzOZionZYpyY7fgVpGvfwfyprvivl4N8eX/GLN5BVYnubPlAxOuK+n7oD/W4e3kzlHSRwAYjU3Ciq6GvPi/R79RQ858qpVH68CN9GYPY6VCRD5RZQrrDoK+Nk+8nJnLD9HYuoB1XNYO3ESvVbDtv4q/vdauXKaFpXviJen7X4Y9GpvnqbQ24k5Gs3rvB5i746XMHDuZLqumZjAT7mnVmN33OEpKSr54KW3MS0pKSkpKSp6z/NzP/Rwf/vCHmZ4eTFa+5z3v4eDBg9x///0TliwpeW7Tr3Pf7fZ45NHHeezxJzh37gKnn3iShx95jO2dJt1e3h4vzsIentRpdgeTpdbGQre1g2zpvRBCJEL3Ne/OVaFkLKwX6QVxBnYWC8Nt1tKoiKHxWgubzeHsq5o33Hd5To0VuoUQHD929LoL/yUlJSV9tjfWh4XuPkIQ1OfzTZATv+O2a7UkHxaFhYly9hsiChBRkFrhep1tpNHIxE47qs5glUNUadCdOURv5mCaeT4K67hDwqMakXnWm8nbj0ujEXbEy8wY3M42leY6qtvEWhEL2tKJbamtobpzhWprnUpni1prnUpnG2miNMvbOh5RZQojHSKp0IlAYbCEgAYi5RIql7Zb5T4CdFYLtxYnI4lYoGsjEGATz/KacHCRQ8LJYVWnkhyPvnWuj06tyv1kn6Pk96pQyAnvJGMtqxn78ojhd+Hn/A06NmJZ1VhWNXajgHPhLhfCJmeCHc4HTS6ETTomJLA6/sHkpS4BjpRUCkKzbzU7hXrhOybgXJQXljUWXciS3tzaGrtfWQ7U8teXrxSXqpNrgHdnD+Z+r7Q3aS+djANHIBYLlZNcB5lAEogDHXQc8HA13wZE+n8ZRtynxXreI+/lxSNDTebe9+aE7txnH/tf2LW9bK73j6qPv6eBIftxrEUWRWchMI6LlX2bbJk8u+IgAm0MP/Xee3n9z/9hKnRPVVx++VvezK9/x1cy36gW1idj4TxzvKyQifvQ1T8PB8Ey+baRzx1Au9W4fjwQVaaSfR48yy15O3dZqeIduvHqxiQdvL/7U+TqWaQ1hSrambEKMdICf6RFu+shbn3Z8MZa+7v/rgsmEzhi+7XdbfqeGcfgHA32VADX2Wg9U7scxMGTSK+G8js4fgcZ+nHQhvKwKq5RL01EVJkirM8SVacIpw7khG6IAyO2b7iL3pHbEa/+enpBOGrTyQBMfIwmjdFaOpZcoJtxqzQP3oLfyJdF2Xz88wStgUNY/cQdE9dd2+PzkpKS5wal2F1SUlJSUlLynOZVr3oVq6urvOpVr0rbNjc3ueuuu/jxH//xZ3BkJSXPLowxnLu4wt99+iE++ncP8LF7H+Cxx0/T6+VzPoIg4Py5cyg1PIXjjqjP3Qtgq2nQxmIy80WjhHFj7Mi6n8XM6acTIQS1EWL1OMIoP+YwskgpWJqVeIWkIj8c3j8pBbMZy3LPgbmp8X/GeZ7H1NTU/gZXUlJScg20i/blBbRXG8pXK9a53ZesY/MZz9mstP7nUkdIHcXClTFxjVcs0hpk5FNpreMkts/CWoxXQ3uDrGFdqafizySMUygNMcIaup+F3V44zu7yzbTnjgKgwi6O38LxW7jdHaZXHqOxeYHazhWmN85y4Oy9OL1WKmQbp0Jn/hiROxDKpDVUd1fzAp0QhF6NVdejqwNM2MWGPXTkEymHwKsReDVwPF5YOUA9m5VsI44706lo3T+++XzKuKSIk5k69BIr7zkZ16CeSTKiASIsUaYmtkmEoFnpMYlzURPfahwEDgIXicHG4jIW32qOuQ3urh7izsoCd1YWeGX9IMfdKXpWE2Hx0XStJrAmfY8KIXCEzIn6EGebq0KbbzVR4ZxeioazCHXhyo2iaOT3EmMNqztbXNhYZafT4tbpJV5YWeSe2hFeVTvMLe4cn50/yLi4Pr+xgD+1mP7u9Jo0Ns9jHY/2gRvSWt2xOC3Qbv6ei8W0/Vsk7wtjEDpKfnQibun4p2jHXKkjbv+S4VU88JHJm/j85M+vBvfA5Ix7t5Alr4LO8PFKBO64BnSmGTi7scM//MX/xf/553+HTr6zvvzEQT72b97JN9/9/Pi+sBYR9vJiqJTx8zCbGZzJdr4m+jWu02EPn3kjHdqLJwYNjotaOIiRitCrE7lVrHLJ1nZWx25l5kWvRniVofWNREjmXAsXHhn+KDPO/Adi6NgOvSHaO7Bydnh7U/PDbU8DcVBPP8hhIHqPErLHL38d6R9Ha1OBu3+dIiTmf/0n1M5qHGxgDUqHuL1mzpbcCXssPf6x2N1kD1rHX8B6d4LQnWzf7e5ec533zsLxpByHTEuKNC8Nznn16E3UTtw+ctnayTupHr66oIySkpIvTkp/zpKSkpKSkpLnPNVqlY985CP83M/9HD/wAz+AMfFE2Q//8A/zJ3/yJ/zN3/xNKR6VPKex1vL5R86wvTOYGFTCjp2Ts8CBGZfVrcGEx+KMZHlOstk09ArzIB3fUvVETvzVJs726meDWWvTuR0hbDI3mNSXM/Fne5TNHLlf/W31fEujJnIThKNKpPa326jG2edax76djhIYY/ELc0HaxCJ2JdFJ+hnrniNYnlP0AsN2K94fZ0SAAMBcI86s2+kYpuuT45V938f3fSqVfU5MlpSUlFwl+yoxUfjdDFkGW4TRqS33mA2BUNi+wFCwwJU6TO2bpTVYHeS2K6xFRX5ulSroEtauze7UAsapJDbGw2J3d+YQO4duwzoDcVdEAdX25sCuVkp6swep7azEtY+JRYeF859h/dSXYPrLSkVvepmpzYFFr8DidpsEU4MMOCkkR9o7WKeS2jJ7VmP9Dj2vlmbQVaXD7d48D/gbBBgkAiUEB1UtzWCOs7hT411aiWgthEBYkIhUMG8IF0mPJTUIHDAYVqJuTqZaVrVc/W1rY/Hat7G5uMUiETSEk15XPpqmCZhKRHJHSOZVPkNWCcmdlQMYa7nPH5RN6QvkWYF7VK1xR0h0Ifs1sDq1YodBhvokPM8buh8ub23w0MUzBNHgC4GDZFFV0/Wf9Fz8hQZ/Y+Elm5dZCOLAQS0En6s3qM4fYaG7gzCaSnsTr7M12COpCKYOUNu5MtioVLEVsdmnLU6BgXRnE9lO5ERPEQbIzPEYYbw/wK0g3/o9CC9/zmwUQGd3zEJJn531iZ/vl/Zjn6HzyKfHfq6CDipIghmUg3PkZuQT9zE2+kCIuPZOcq5/79OP88/+54fZSb7QSiH4wX/4Uv6PN78U5XiYvtW0ECijsWEX7Q0y+fvCqRVqz8xgYM/MYVvM7j5wlHB6ES6fRlhDVJ2hN7OME3TxWusIaxCHTtBbup2eO52ea+V3qO6u4IQ9UA7qRa9FVuvM3/0V7Nz71+j2zogRDI7R3Cv/IeqP/8PksRZtuPdbrsLo+F2wdjF+/i4eRZx4Pmbt/KBPoUa3kU6cWW6i6yI2p4J9se0ZJHWvyB7X/nMgYwkvAMdvEaj5TJtl/ux9XHnel018F/u9/dfDdnotgsZc7vmxH3QSiJa14A87+YCUmRfdQ+XwCbpnH8F028j6FLUbb6eydPSqtlVSUvLFSyl2l5SUlJSUlJQkfP/3fz9f8RVfwete9zpWV1cBuPfeezl06BB/+qd/yutf//pneIQlJc8MaxvbOaEbwNljDmOubtjahVDHEywHZiRCCA7MKPzA0vEtxlpcR9CoCFQiFmfxg0Ht7uzcUn9esBdoIgNhFNfGrl+l2q1NnFUOUHFHT1f1Be9IW5QiEQLiMblOPlvdSoiMpVD+kDCKJ/cqhcTA/nYdFc+hLs3KRDQfnvebbUjmpvaXG2L2sBEsKSkpeSpMzczQao4XrZxeM7YzlfGLIp6IN4goiIVgaxFWI43GWDfN4hqLSHy1R1iY57oNLZfUw80I3uPsfbEWoUMENhbms/XErUUrj2i6MXEC3589mAghGYtix6M3vUhtZyUjeCv8glgpdURt6wLtxZPpfhq3QlCdxe3tpsuqcLiCrrSgOjv49fn0mAssXtjDrzTSfq6QHHTqnI9aLCTisScUNaEIraGaEaW1NWzqwXGTCJZVPSfsnnSn8YTENxohYEuHeEJxQFVRCAyWSiHIwZJkgGesyhvSJUwytPt94uxwwZR0h5bPnufbKws84G8SZtYXWYuT09IE0sbjSduGjuIwFTH8ncLaQcY7wOJC3np3o7nD/WcfG3qHRxi2jM8BWU2D+CpCsTx/gr+dOsB00MMxmrZX5THT4Rs3LjNtL48dW1hpUCs2Csl4tTYZf9wxcy9ZRt5botCmHKwe3D8Ts1jf8k8QN4zIwFQuVBswqZb2dcjUDbfXaT34ybGfV4/dxNTJO7Gf/AtobiAWDiNOvpDokY9PXK8Amp0O3/tHH+e3730sbb9xfor//s438qqbkkxyq0GHceCKjUVtacHoCKucgW24NWDjeusTazePEbqH3DOyv3g1Khjo7iKswevuUt1dwSg3fUZw5nNI+SDhgROp24Wu1GkfuIGp5hrV134t8kBsRe/OLbLwuq9m/T2/hR1XwsJawo0rOHsENOzT1yOPVOgnH4D3/ho0k9rObgUb+vGeD1LaYzHd2vh+kDIOThIgxo37aWR4T4tZ/NfHyjwNeMiI2+kICoK3290mqk4PgqO6uyw/8kE2Tr6cqDZz7WMwOrmWQYV+zkFlv4TVGazjpWUZpDv83aCyfJzK8vFrHmdJSckXN6WNeUlJSUlJSUlJhjvuuIPLly/z9re/PW1rt9u84Q1v4Hu+53ueuYGVlDyDrCZ1CHPsMTvjOoKThxwWpiWNqshlLVc8wfy05MCMYqYuU8tzKUU6BwfxPFDXtwShYYSrOcbGQrLrgKMkkR5tcz6Ofv1tIWC6LoaysyDOGu/4ht2OZVKpOkgszj1BxYv3QxDPKVY8QdUbvf6+LXrFBc+N7dGVisfWn2uWsv8jUHv8BSelLLO6S0pKnlbm5hfwxtnaWkN1dwWlA4SO5cuo0kAIgYr8pJb2wPJY6nCQhTaJkWLc/qa0LILIrRJ5dYzyqDTXWXjykxx88K9YeuTDTF95FLe1geu3cPw2XncnFuz7YroQcS3T/WxPDAclWekQ1OdywodxK+wuncrVWq60t/L1x4nt0yOvnqs7PbTJJMO9KIQra4YyfedkBQfBIWeQZeqhWFK19B1lLZyPWlgsDeFQFYoFVcWTMs3GFkBoDRu6x64J2NEBBpiSLg3pUpUOdTkc4SVFLGAXhWRXFI3FoW2CPd/prpAsO3lRpZjlOopRPeJSKoNPOjbis/46YSZAQgtLL6lPPjM9zfJivk77EyuXxm7dYOnZvOA2ozw8oWhVamzXpgiVw7ys7LkH6bFKrcQNthhpN2nh/heMrFtC9uO+m0IGq5z9SXOnPzN6s0Ign3f3xEX3+nw/dM8+NPHz4MxD8Os/jPj8hxHnHoTP/BX2j39+uIZ3gY89eYWX/ewf54Tu/+0lN/Gp/8/X8qpTh3J9+/dxNqNYmCgttQD9LGEz0vbZjvwRyQ+JgCvjoJwRNutceBhx+r7U+UIASoc4QSdXV1kaTX3jbMFmXRHefjfqxuflx+R3xwvdCbrXBmdy2YKh5yMMP9+L15nR8Kn3QDOT+R/6o69GIbBSxq4W/WeaUNe5QvZkBiFP/fdU5l7LfrkvnrcJ6yuiHW+0/ftQdLDOtUmjY6eIzLtB6YCFc58e6ViyX1TQzVzr459FIgri7wHE7y6vvUlldxWvtU5QmaI7s0xv9hC92UNs47C9uXHNYyopKXnuUYrdJSUlJSUlJSUFpJT88R//Mb/1W7+F6w4m6v7Lf/kv3HLLLVy5cmXC0iUlX3yE0fDkVrSPOVXXERxeUNx4cP+GUn3Bt7itUTW8+9nYXvJfY+NMcj1KGR+BEIJ6dbQQ3fENO23DVsumtutBtPd6hRB4jqBRlUzVJY2qxHPi9QshRlqt1yvQqBYmmzMid66cI0yc/D+wsICU5Z95JSUlTx9SKW686WYaU9P59rBHY/1MbIFLLO5EXi2uA9vvEwWpAJO27SEyTcQalN9G9VoIE+G1Npg/dx9Lj36YA098Aq+1QWfmEP70Mv7UIv7UIjLyqe6u4fptKp0tZi8/zML5+3OZf1KHieB9jTV0C8JKVGnQmzmYE1yi2gw7h28ftAmRCI2DF6wwGqSKMzKBKGOFDCBDH5Ucv6JlO8T27lmUENzhLSARtExIz0TMSo+KUCgECoHGcEjVuc2b46Q3w83eLEecOm52ClGQ1tjuY7Cs6y5ts/f5rI3ImnYKU5QGchnb+6UoaVlr0Zla3hBnrg+J6zZkS/uxBXXCmu5yn7+OzdgjW6DSqHPqxhO57w7GWjZaE2yeGW2N7haCKCzwqDvZqcZtbyGiAKlDpImQJgTHxe4RkJHaMBev61HXeaY2cdok9xa8bWt77Gfy5V8Oi6Mth+Vdb0AePjVx3ftBtyZnFhvHi+2wi9s3eqRIF2nDv/+LT/L6//xnPLkZuxxNV1x+7Zu/lN/8R69ntuYNPdP6QrbKCNnCGJygjegff2OQkZ/L6s77QvTtvYtCqSR3lWfa9xMkIXVeXJcmwunlj5l/5ezQMRJeZYQonUdW6nDjnXsMYjgYSHv19Bk3WvzOLbGvpqJVuv0Cfjce5TKSkr2n9hm0FWdu53dTGMP28ReiM+/XkYI35AVva+MSH4mNv0mCApywR3V3dc+xjEL6ndy1bkecP6+1wczFzzN/4XPMX/gcsxc+x9TqabzONq7fwuvu4vlNHH/g/BBFmkvnz7Gxundd8ZKSkhIoxe6SkpKSkpKSkrF80zd9E2fOnOHUqcHEy+OPP84NN9zA7/zO7zyDIysp+cJSr1WH2oLo6rKo94sUIqnfLVKx13XEyHrWSgrqFYGS+c+0mSwIZ6lVJBVveN1SiCFB39r9C+njcJ1hMV8IMdZGfRTF7LM+MzPTHDq0/JTGV1JSUrIfXM/jhpOnmFl7gsb6GaZWH2dm5THczER1bGeaF1bEyIn4fT5X0yzWCEyE6jVprD1JffsS9Z3LNNaeZGr9Sao7K7h+i0p7k9krj7D05CcG2eNC0J0/ysapl+f3x29R3zyfa5NG75ntOZI0Qin/XDdOhaA+F+8KscigKw2CRmzd7DcSS+xEDJNRgEzGbaWLkYqwmgkw0JpKa3KN46L46SBY1z0eDDZ5PNzh4XCbJ6NdelYjhUAKQV26zKh8LWolJNPSzQnSQggqIzKyt/Ww6F5ECUlxyVFvwb2ujNAa1qJ8Pdme1bRNlL4noyTXux8spq3BACItTJJZHyYV6/uf7ZqATePnjsdup/WUS4b0hWdtLYuqykl3mpPuDIedOt2ZQ0RjRDAR+tR2rgxbXye2/aOEpuHtmmHRzeTbBMT3Wlb0FOwpqorZpfGfVeo4X/v9yLu/CuYPQW0KcfRW1Jf/Y9Rrvm7iuPeLrNYnfi6iYKxcL0w+uPPJjV3e8At/zL/7i0+m3//uPrHMvf/qa3jHS28eXkFy71prUWF8XRohMUIiTITUYfxfE8WlHNINx8+MIQegop38xB3bX185Ijt7qDyCNRQtlaRboXLoxonrrqydgdP3jf3cZjKd+89Am7hbGMfDCMVo+4rx+3W1+drZbPmJ7Pe4j1s83dre29lniC4UQiO0V6d58JaJ2xXZtkyZDRXGz2mTycR3e8OBIlMzs8Mj0RFOr4nb2UF1mzhB/hlcLE1S2V1hKhMIB6CiANdvI8NMmRGg0t5EFta3tnIFvV/nipKSkuc0pdhdUlJSUlJSUjKBI0eOcPr0ab7ru74rbQvDkHe84x18zdd8TVkbt+SLmv71ffjggaHPrIW2b0dmXD9VhBA4jqDqSaqexHUEUg6LxACeM3oy6mp0eHeEkF5x8/NcUoCjoBfYq7ZLz9IX8x01mKCTgtTKPcukaTYhJIcOHuTAwjyLiwe4+aZTnDxxY5nVXVJS8gXDRAHSb+P2hie7+4yvkW2QYQ8Z9gCLCjpUd65Q3zxPdecyyi/U9U2fuTadvI/qs3TnDqfT+gIIa7P0ZvJBP9XmGtMrj+Xa/Okl2gs35Npqu6toJ28h/ZSyznMvrfjfUaWBRcQCQyLy+I15tFulN3Mw7SmMxu0MsoStlHRnD8VCUSJKVltrgEU7HtrxMI6be/mFwA6aKCNWKiE56tSpi4HjStdqToc7dDJC37AMnLihFGpwCyGGMrJDTG6b+2VUDWKvsO5iCMFjwTZWiFQ47wvZvtW0TERoDWFmLJG1hDlBd3g/uzYa+hKxpgtijrUEBdcbKQQHpmeRxMdEJmuvCsWM9JiRHnURHy1XSBwhcaXi1socB506delSlw6nvFlONg7x2OJx2gVL6G2laLXXxtd4FiKuOb8HowXv4bZY8NYMZ6OOzzwXL3jN5G1XaqiXvxn3H/2fuP/4Z3C+9vuQt7xkzzHvl+rxWyd/3lwbP7ak1rO1lv/xyUd4+U/9Hh8/E2eVKin40Te/hL/+p1/ByYWpuK8xsYW8iUsGCKORyY+wxEJu8mMdLycC5q684jHfL0PfRa9NoLUyfz6d2UXECCuiqee9AlkZXYu5trCM+vR7R6+f5Mmd246I60Zn3RGcwpfvp4AFtHKJ3CrarWKlioN/hALpgIh/n/ht/mqCDUYtDiMcEuyItn0K/Jm2sBrX145qM4SVxnDfjLCd/p5ztLDxcUkcISwCUyg94VUqHL3hRpQaPFOcXpNKcw2318IJOnh+K3YLSAKztFPBZvp7rkN969Lw+BJU0B26jr1uXnQ3xtDa3asWfElJSQns30+wpKSkpKSkpOQ5zC/90i/xdV/3dbztbW+j0+kA8Md//MccPnyYD33oQ9x2223P8AhLSq4PURSxurrG5tY2Wmtc1+HAwgInjh/izPm8hb8x4EeW2ojM6KeD1Mo7W1pQJnNGhb6RAVfYkXWy97ctwXQNmp04IyxbK9sPY7Gl6sV1tK217HQsc43RQrO1+XEIIWLr9cyckiCePC/OW/atC4tt0zNTHDw4PnuqpKSk5OlGOh7CcbFRXhC2CLRXg6S6s1FuPKkuJMIanO4utdZ6av1rhYhrqiZ2qirycf02QXUGvy9cZzOls+JlbYbA71DpbA3aqtOEvSZu0EnbZlYeJazP0Zsd1NbduvEugsYcc+fvT+x9wzgzVqq4tu11ofAUFxKtPKJMhrZxPLaOvQArBDL0McrB7bZACLSKxU4rVWx7rHvpGiOvjtJ+LLolW3KCDpFbxUjFjuOgsbRsyDQuKskUVkJywp3hwWAzHZkFVnSHk3ImM3IxVP/aFXLovSSFGHpRFd9b8ZWQkVlGBIzNSY+u1bRsfD1NSw9HSEwyCgHIZB3GGh4Jtrnf30jGIAmNJsxsOcQgTDK+/liBYvhFcX/6EtGobw9dE+FbTV06WCxPrlxio7mDEILZWgMvssyrgaBZfP8jIMBQsSIdlxICaeMM9D5KCBr1A3zG85gKeng6wlcuq47kS9bPjBhZdofk2PEP7bc1QGKRbTNtQqVftnL9+udNCKwd3oa45+sRS8f22PLTS2X5KNUbbqV37tGhz5TfprY9XnijUqf5irfzPf/kO/m9+55Im08uTPEb3/Q67j6xnJwlm953AMpqrDb07cYFIKzBJs+UtHa0VBinMrLkwDD7OYvXgojPY39MCMJaPnu3ftMLRi7pTM2y8Jqvov3oZ+hdPI2NQpzZReqn7sT7+J9M2uLI77LZccSN+9zfvpCbXo/Z2vPJM0K5GLeaZk4bx0NGAU6vFffIvFPsiLIG+cGKq4uizS5K/PyLT6fIt+WKI4wn/2n8XO7OHU5bospUzlWlv5Qo/I6QRE7/mAjaC0fpzB9DVxpgTRwMkJTOADiwtIxSihtO3cT5J09jOk3cXmvkPgoTMXP8FM7cAXrdLlJKZubmMGsX2ZkQ/CSwCB1hnWy5k+H7w0yoA15SUlLSpxS7S0pKSkpKSkr2yRve8AZWVlZ43etex6c+9SkAVldXed7znsfP/dzP8S//5b98ZgdYUvIU0Vpz+vST9PzBJEMYRlxZWWVqqsGLX3ALV1Y3WV3bQIrx9uJPF3Hd6/jf+QlkSzRiHiXUoKRFCq5J9HYdwdw0BCFEOj/VZIkdHiWwvmNY3zVobTkwk8+EMdbS6lqUsDRq47OuhQCVuIgWk+VHjb/VbA1PopeUlJQ8zVitiXY3EVKiZhaQh0+x22pjlYOMArCWsD43yOyyiQDUXx4I3CpCCGq7ccaksBZho1jUzNQf9Xq7aK+WE4b7Nq7ZJ1937hAIQaW9mbb15o5g2ltU2okYajSN9bPIKKRz4Hjar714Aq+zTWPjHEY5WBXXJLZhD2FNWkf2qZGM1mhAENRnYuE3EU/CyhSV9hZur5mKQtqtETTmcxly2frbArDKJUqE+X6mr8Aiox6r9VmijNOHbzX1zHlwhWRWVtg2g/f9jgmu6b1SFMSLtbwBNBbJQKwWQjCnKnRMRNdGVISiIh0qOEgjMNYyLeJjLxEYbLpsvJ+Ch4Pt3JYdIQgK78+h5fYpWrkIllWdaelhsVSE4r7uKttmYMv/0P1b3OBM4SVZzhvNHSQwJT2UGOznKAI01cyUbH9c2ePvCsmuDghdD9eLy8nUrL2uFp05Ia6YBZrFprm547n15ciXv/k6ju7ambnrNbiNGbqf+SCRW0XqkEpzndr2paE69lk+/NgFvvVHvpqzm8207Z0vu5n/+NVfwkzVy7lIFBHYQaBAv83aWPTOtFmpktCP8dfhKHF4v+wlkQssjt9Be3G2sz+zNHjuCkHj1hdTOz7Coj1B1aeZueseZu66J3e96j89t4+RjWlL60nvsYp+38L1KKzGmjhoCpEE/oQ9tNHo6lS6qHE8tFfLO5H0n4uZ68Im27le37HHns+9nkVCJIFBgwxzKwTtpVNEtUxg0gghuDhyKxVhZRoy75SpjXP0Zg7GAUBJIJMKu2i3xsLBQ8wfWASgVq9z8x13cuFTHxkKFsqhQ2bn5pmdm0+bOtHe7ijFsKpR9dVr9cnlCUpKSkqgFLtLSkpKSkpKSq6Kqakp7r33Xn7sx36MH/3RH8VaizGG7/u+7+MP//APed/73ke1OlzfuKTk2Yy1lq2tbS5fWSGKhmv5AbRabRbmfW4+eZReZ/e6107rJTPU1X1miWcnoKQUKCy6MH8pxWih+GqIbcehG1iKVQvCKBbSN1vxB6vbhu2WYX5aUq9ItLH4yRyPFlAfM3E2cEkUKAXS5vclu0zHN7Q6lshY/PvPcOLYIksHpofWWVJSUnI9sdbSefhTdE5/DhvEdTdtpU5r9gjh9OL4BcfUHfanl3D8Nq4/yBITRmOkk3vmud2dvNgtBKCSTLzB9Hh78QRGOdR2V9O2YGoBGfm4fiuxrxVUd67QnT2IzdhDt5ZO0tg4R3vheDpe43gIHebE933Rr7Wd2J8b5SKiAGnCVPCwUmGVl8vyiyoNHL+NSDIMnbCL3A1i6/K+9e8ooVZIjPJQmTrZylocExHJwT4GGIpSQXWEFfVeQlloDZG1qZgLMCU8OoT0Esv6GVnJnUOTnKf+f7Pic106OEbgZeyNp4WLkPlRyMKopBAccxo8Fu6M7ZPbL9sXUyyDf43HIjjo1FMhG+CQ06AVhGkG9mbUo61Dnl9ZSLPmDdA2ITPKG7XazPohtBoHmR4riWDHhjRw0qxvCzwcbHOHN4eTbOPS7BI37KyOWTMFq+J9kMng7v/XFjNuk3x3k4xBFJYBkK98y9Vs9WlFCEH91hdTfeyT2Ec+sWf/UBv+3V/ex0/91f2YZN9mqx6/9HX/gG948am404EjiFteCh//swlrskPZysKYvE24EFgpRwqUE8lk1Q+199tE7H+wV6aywKKiAN7wTiqzy6jmFtKrUD12M6o2NWHJwnqyY6nUYEw5i/5Wc8OGxK0ijC3g+22I2LZp/EaTZ2HBct9aLPlgA6VDTBTknvfarSJDPxf0oJ0KVkjcoJ2O1KYOCdcadlCkmJ/dDzQZEURSKIFhM3bqkdfAn844O+mISmtjaN1FpNF43R3C+mxsH09ct3vxib/jyh1fmr7rBNDwHA4dyTs0SCnR3WL2eB6/uT3U5s4Ol8LKYolrt2eJKvlrsN6Yolorxe6SkpK9KQu6lZSUlJSUlJRcAz/yIz/Cpz/9aebnB5HLH/nIR1heXuZjH/vYMziykpK96VuVnzt/gYuXLnPm7DnOX7g4Vujus7W9DcD09GhxdVT97v3UttbGstU0bLVMOsl4tSgpcFVcV9uRJP8W1y0rwxnxl5Ox0OyanAgeRHGmd8cfCN0Qz8eNiw8YsgEVsb2pEIPxW2tZ39GsbsXrDkK4tLLD337qNA88cvGp7VxJSUnJHrQ++xHaD30yFboBhN9hevVxKrsThLeEQvVQANrzx3K1RkXSMTv1P7JmthBxDdycPAfd2cOpGNcnrMf2vJFXT3paKu2tfJ/qDEF1mt1Dg5I0RqhYZM++Q6xF+S281gZeezOpN07ucxn5OH4LFfmJHXsLpYOcOCiNRka9nFBjHQ9/Kh80II0etowd8U4zajiPxdtHQFpEPoKrJpyc5be1Ft9qdGacm7rHjgnwE6HOQ1KRinlVpSYUs9JLhV6LRWNSkRtILMkL9VkLQsd+39t9wd1Yi7Z25PcHQ7wPAZYQS8joa7HIJd3mb7tX0BlBrCYdjrv57z++1VwI8+dIY3nU38otC6R1xQdji63Ls9+TDDauGZ7QtbFt+mpSMzywhkeXbqDjVhiJtch9iKiW/HHICnoj82+lil0GpAQpsUphncpA/L7rDYil4yOWfGYRX/bNcGR8ljLA4+u7vOY/v4ufeP9n02vonlOHuO9fvX0gdAN0dtO6xGO3N7J1+IiKPb7rDp0Nmzljo5Ydqqm+Ry1q4uAiGfnUbriV6TtfSeOWu65K6I43m2SzA9zysr1657KnBaCMRhiTe5ILLEPRpSN3YHgfhTVD58jtteK60GkngXG9IYFVV+pEbiFgXVw/qTtdZfaX5LxZIbFCYogDIYx00h+rBnXfkQon6jFz+aHYSQWYufLIvgV5gUX5+RIdKgqob17ItfntJmEwbCUuR9Rxz38+/C5y55dwF5bHLhM/Vwbr1cpN65EDVKpVjt54YuJ2S0pKSvqUYndJSUlJSUlJyTVy1113sbq6ypve9Ka0rdls8qpXvYof+IEfeAZHVlKSx/d9dnZ2abXb7Ozs8tBDj3D5ygpbW9usr2+wu9vceyVAFGl6PZ/d3d2RnxsDfmCItEUbSxRZeoHdU/Du+PHUt7UwSm/XI0T0UfRFYimvn8gNA8FejljlqPk4bSCI8mOuOHH7yICAEdssDr/di+3QR3H67Bora6PPSUlJSclTRXeadJ/4/NjP65sXhgQYt7ON0x08lwaZcpmHm3JoHzhBkJnYpl+/u19LVU6YXBeFPlIR1udyn2mnglEuYTY7vC+G2ER8MZrVW1+dy/6zbiWflW4tTq9JpbWB67dwe01quytUdlcGAo4QGLdKWJvJPddHWh5bizD5F57xqkPC9f5qh48QwAuif1FohbhGdl0MtresarnPQwyGOCs8tIaNqMeuiYMP2jZCIajIwfJzqsqcHIiwIvlfkasRj2zmf5E1bOguF6IWl6M2a1GXjglp25CODekw/AXC0JcIMxmg+8x73jUBT4b5d+us9HDIi2xXdIeH/a1cUMCa7vGx7kpOgBeIkdnn/a8RYXIdRcTivW80l6I4k3JT+7G7gokIHI933/4P2Kzlhfeeclhz3Fjwm0AadiEkGXkxM86kV0aIY9R9KER8z7zqa5Cvf8fEbT5TiEod+Y3/GvGSNw59Zq3l1//uMV72H/6ET55bB8CRgn/35S/l/d/9Zm6YLwi/3Rbsw5J5aDsjMrFHBlzYwTEXZO7qjGV38dyMReTWMJ4rT+7dBzBhQPfsw7QeupfO2YfxVy6w9fH3sPqn/43VP/1vbL7/dwke+/TkIZGI0TZnXVQIXOqzX8E7v5wgKfdQELydoIsMM+KtHdjJA2mms/bqg3OTrQF+jYG4Q8Ptn+OkZIEled/J+AflDCzv+9ncuXrkg/2ZXn+S6VvvwjNXd01KHeTPAQwFgAGYEX+QNZYOD7Xt5/O5l70BNTU31C4qNXRixy6UonHkBAsvvJv5pWXmDyxy/MQpTt16O657PcqJlJSUPBcobcxLSkpKSkpKSp4CjuPwnve8h1/91V/lu7/7u4miCGstP/MzP8Of//mf8+EPf5iFhYVnepglz1HCMOT8hYs0m629O++DarXCpcuXMWMmoKSKM5uz4rQ2sQV4vTJiwttagsgShIP+Hd/iuRn7U9O39LaoUWrzU6Bvayr3EMaNjYV0R9lEsB5YvdYrcTZ5VEj2aXYM81MyEd5Ja5uHEUhhY7ty2c/aZmhOUog4Mrl/KJudyZN+Zy6sc3BpZmKfkpKSkmvBv/QkkyRKpQOcXosoI75ZqZg//1m2jz4/J0BbIcFEg0eeEHRnD+H2dtPl4mw6ibA6l+E1TGzvajOCq01E3r5kJIDu1BLB1AGiSgNhNGF1Cre7g4x8BLEwrL06WjojM6f744xqM1jlUmmupuN3wh62vUUwNbBqtcrFOF5sE5xlyN5YD9mkG+UhdUZk2EO47K8ntxkEeDUkNs2qHmVZPiU9bnZdngh3mJYe86qSDNMSYNCZc961mk2Tz/TrWU2d/PiLr7NrfWvbZOz9EVhr2dQ9NjJjuMGbpiYdHgqGhZq9EENVYkfzSLBNaA23efOp40pFKoLke1B//7aMz9lwl1Ne7CQQWMOuCbgYtTnuThU8CPL/tlisJZfRHVnDvf5qKoRra9kxYRyAYC1btWl+5wWvZWlnlZluk47j8sjsAeqhzz//7Adxs9fEpO84/c9sPI6clTkgXv21mIc/Advj3Rtsb7K18TONEDLnSAGw1fH57j/4KH/w2TNp282LM/zGN72WV9ywxDjEqRdhPv1+ss/Dotl7fM/KNCs4+3zCWoSOEEmggbV6D7vx/HkZtI2gaD0/tmOGEQ4BwcZl2o99lmD1IghwZhaImlvj7YmAsN0kXLqJKQvV1vrkbVoTDy43Vgl2sP6sxffE63cMwhqszYvEKuxh3EpimR6v10oJRqPdxI1CKqyYVBAhsxuQuX/2qGfPCBcnSOu8Wyuuej+V38bVPhSu7b2IHVRsbkDFoDIhJW5l+NqYveEm2usrmDAY+sybnmVqebTYrWoNFr/0a/CvnMVfvQAIKgePUzl0HGssJvSRbiXNHJ+9qj0qKSkpGVCK3SUlJSUlJSUl14Hv+I7v4I1vfCP33HMP58+fB+DBBx/kyJEj/N7v/R5f9VVf9QyPsOS5RhhGPPb4E4Th1WehjGN2doYzZ86N/VwKgVI2nQ+zNhZrTQRta6i4AkcJrLVEOq7TrU1+/qzjW+qVgeDdr13dz4qWkpzofS3zYFoPMsnjpInRtbSz24C+4A0oUHJgtbo0K7i8mZ8EjDRsNg2zU5J6oQ65sYDJlyQ0djhzXAgw2tLqWcLJDvO0OsN2gyUlJSXXA6v3eADBUDap1CHCWqZXT7N54qWZbNJY8M72t46H9uqxLWuakSyIkizpseMSAiu8WGiwfVnX0l44Hi8nJDL0sVIO194OOsgofm5Ka5B+C6lDwtrkaXbt1dBuDScc2OI6fpugPpfLfjVOJSd2j9adRtkR54+jcbzci64vnqWCDUmmXoZedRpHukxbS9OGeELijhC7IX5vn3Jnc0FfQgikFTmx2xUSB5mzPg/2IcRbYpvxwMZ25gKoC4XKWKZbGwvb2bX1c8L7grQQggNODUdLVvTg2C85Ndom5Fy0d1BfLBpevXB2RXfxQsVNiZAdFfa7f5TWdJfjdpooEboBLoQtjrtTaUa3SGT2bNa7BZomRCeW5kIIPudvcC5sEthY8q8Jh5Wwza6NBW9BnK2/0mggpgYZyFGlxvvueBVf9vDH8HQ48gvS4FrMhCYI0VdqM/0sIuzB7ubE42PXzu95DJ9xMvf/Bx6/zLf+jw9xYWcg0n/bK27h59/+JUxVBv2MUMiMAIvjYj/0+/G/+8+pTC34bOa1tRqLwjpurq/U0eDZJwTYEU+GYlDMyB0aESV5DYhbX577vXfpCXbu/evBF18L0fYe4nW6MkF78UYq7Y2JNu2D+3ry+AUkFunDmc0pYzaTWzZBGg1Gp/bfEL9DoupU3sVDyNyKLRaEjIXx/t3T/zgjdltrEXsEL4wea2IFX3xG7+MPHLt67qq3l71S0zYBKuiivdjdY2ZxebQlebXOkbu+hM0nHqazEQfACKmYOniEhVO3IyY4sQgpqR45SfXIyXy7AqnKetwlJSXXh1LsLikpKSkpKSm5Ttx4442cOXOGb/u2b+M3fuM3gNg++u1vfzvf9E3fxG/8xm8gpdxjLSUlTw1rLWfPr7C6uk7F27v/fjl86CAVb+8Veo4gIBa8s47dkYZIj7Y0VwqizNzxxq6hURPUvby1piUWvaWIJ4PTubgR80F9QV3JQQZ1HyHi7GxBXrS+GrLTdHNT8X29tqPTDG8hYKYuWZqVWDOc+W0M6aR2fx90IngbazEGun4sdFs7dj4vpeqVFn8lJSVPD+6BQxM/t0ISZWpvA1STOt5O0MHptQhrmfrXqbA2QCsXmxEmjFR0547kRYgRZMUFAfRmD+deCGZMbWPt1RHW5GzCVeQTRUHOznwUUaWRE7sFFqnDXA3YIeviEcR27dkMXwhqM0gdIk0sNUeVepLxmGS8Sye1vBVRgNU+TiLI9aRCV6aJEsFCCME07p7vuFHuJqOOukx0HpH2if+VtUgfWpON61r7GYHYt4aGsGltbyFEvA5rc/W9ZZJ9nb1UZlWFHRPQy4iQR90pVnQXv5AZKqAgoO+PrPzY37dLUZsT7jS+NXST7fRFzn5fA7R1yPmM8B5agyzYuUsEraSfwTInPNZNjzNhk5YNcZD4VtOzUbruntVs46d11S2x3TmAawffYyIsn5ieZuNlb+PrPv3n1KLRgXAjgy9EHIyYy1S+8iRUqrGF9ziKdY6fhYhbXoz/qffxo++9j5/5m/vT74/zNY//+vWv4mtflBfgrBBsHX8hlc42jfUn42MShbB6NukAqc10//dCtreRMp/VLcSwHXYho3n04EcsN+pq7pdl2C8nX4C44fbB4kbTvP9vx1t2W7Pn89gql6A+T6U9OUBiJCP2MxWtRwXrpHXMx6zOWqzIHykV+ljlEHrTgEX63fhvgaCbjWzNWy4lz+lBNrroDyw/diHiQ7TX+Rw5VoNlcj3skcvVpmD5BKyeGdtHSweZCY6yUiEjPw6kkgqtXJygy+zFB9g9fDvu4lGWjp8auz63PsXB578MHfjoMMSpVkcK4yUlJSXPBOXTqKSkpKSkpKTkOiKl5Nd//df52q/9Wr7xG7+RXi+2Fvvt3/5tPvCBD/DRj36UG2+88RkeZckXM48/eYnLKxvUKsOR+6PICq6TqFQquK6biMwTJpeEoOIKrGPp+LZYNm8kM3VJsxvX94Z46qrVjWtUL84OT6wZOzwRbzMTjcZAmIjtFvAKnfu7K69R6O5vI5sRPjclmW0IukEsTlc9kWagW2lhxHGINDgqf/yNhbVtk2a093ETi/hxHD9alksoKSl5evAWj+DMLxNtjbYy7k0vYTOT3V57i0pzbdDBRIM6pKOwFiNcoloD43qk766C1WqRkR9dxTM9cmuooJMXQyKfaA+xe6TgU2gThWz49K2ZRGdZkvqwUqaZhla5RG6VdqVBfeMcUXUK41QSXUWjZWWQPS4EHcdly1Vga3EfIWgIh6z0eK3vuH5Gtm91mpGtkBxzatRlHFyl+0LuhG1IIZgWHtKEqUgMcc1v10hqGTFQkhen4zaRszMHuMGZZk132UoszV0hWVJVtrRPO2MFroSMLYIzy47OsM9/nqWfER9haZmQK5mscgrZ6ACPhzu0TJiO2ROC82GLC2GTjo3whMJayxXdKQTzDdYVYVBCUMOhmxG8LbHVeR0nd8w1Fof8713rjxW6rwbhVRGn7sI+8GGGMsET5K0ve8rbeTqxfpeH3/W7/KNffBefurCRtr/u5sP82v/rNRybywfqWATN5ZuxboXe7EGwhqmNs+nn466hYq6yNHroq5+VcqjswMgxw0BYNWbEs84OBPcC+7rjX/Aa5Je+g3BrDeN3UFOzRM0djN8dv4yQ1NeexJ89iPbGZ+KaaxI+i0LzXt1jYX/Svlpsvka4EAT1ObrzRwfHzWgqzXWquyvpuoxyEUbHmeBkgpGGbOJHBS+IvV5b186IyF5z8THE9pWx2zNCYd0K2lpU2MUi4v3DIiOfoDZHVJ8BIZDWMLdzifl7vnxf7w3lVVDe6GCykpKSkmeKMrWopKSkpKSkpORp4G1vexsXL17k+c9/ftp28eJFbrrpJn75l3/5GRxZyRczPT/g8ko8kbefiRZrbWwzbvaeWNptNpFSUhlRw20UseX33qNwHXAdwfyUYLouctbeVY+RM4r9Gt5FQg3dAPxokFUeaYbEeSEESu1fExlXKnx4jktQr0gaVZmzWhciv199xpQ+p1KwPVcSlucllTHJ28uL0xw7ND9u+CUlJSVPmdkveTPO7OJQu99YoH1gEMSn/A4zlx4kmDpAZ/4o3ekloupMnIGtw/inKPYIgT93kKjaiEXjJEtORT5CX79SHEMk9VlzQ9lPZqQpCNlCxuJ2xm5ERT7ZvMNs+Jm1Fu014gABITGOh1FuWjfVKpfOwjF0JlteMPzOqmYy5fuZ5NEEKdfagbtKZA3rusvlqM2G7qELLzQLdGxEx0b0rI6F6kJCvhJy32J6XThDL82WCTGZNiHE0CSlQCSZ0Zk2AYedBtPCTffLYJmSbs4uHIpZ54N/76dedy1jtQ5wLmzRMoPr0dhYAF+NOlyO2qxEHVZ0h56NCDFEGM5ELT7evULThFjiLPcAw4z08vvE8L5LIXAL16eFnL08xAECxe85bWCyFDiCESKjXT0HD/1tYr1Okh1q077i0EnkrS+5uu18AbHW8ivf96287Pt+MhW6XSX5ybe8jPf+kzcNCd0AraUTBFMH0t97M8s514ZkzflfR90Ho0RbyyAD25rRxxwRuz70XRwcF6OcoaCN7HkYjEHs48oGs3GFjb/5AzY/9Cdsf+Iv2fir36f14N/tuZw0EbOXHkJEwzWb+zjBBMGc/pHLHK+9MrSFgNteAYkNOUbvKXT3tyCSfvG/LY2tC9Q3M7b7UuHPHsSfXs6PUarR7hx7CfHZbP+nii2cX2uTfc/YWl18DBsNP/UtsdCdOpsIgXarGKeSji+9WrLjbW+jN69cn/GXlJSUPAOUmd0lJSUlJSUlJU8TCwsLfO5zn+Nf/+t/zc/8zM/Ek5ta813f9V384R/+Ie9617vw9mELXfLcxRhDpxNbrNbr9T1t8Dc2d9N/R9riOpMnXDIl+fZkc3OLVqtNEIyf4CriOtArdC8mQnjJGIUQTNcEU9VYgBeJS6Afjp7k1yYWgbMoAcXkZ88Zndkm98hQz/WVAmvs0ByXsTadWN8LR8VjKwrcoyzYGxVB1x9sb7oucZTg4IJgt21pdQ1ax+ucqkvuvHl5yKq9pKSk5Hqiag3mX/91XHrgXsK1S7FA3VjASkV19wqOP6h/u33sBUSZWtsWJtZwBWLBVnlY6+cEZ6HD2Ar4egkIxc0WhUNZmCbTEUqHaLeajkFXp+lJRaW5DliMquCEvbjmd3U6zha3Zqwtr3aqeXt1IYci1KzyoCD0C2Ow2dKy9Ota59cfWcOq7hJaQ00o6sJhxwZpZrWLpGmCnDB+kTY3OFPMqXhcrpAsySobppfLyN40Po6QVCZl6gO9JCCgmhxPkbzUQ2tSATfCElmDg8yIysN5s30hWKcyWdz3gKrRjELaNq4kLoSgJhRtG6XCsUjOQf7wTggISP7rInDE4A0vgJYNcYkFfmMNm8bPWadrLNpqJIIaKv3uERLX8O4fWwBHSKoiztzO7mdxbC6SoJA/rq1lj693RI7DxfnDHN+6NLljFiGAOBs+vS+2V+NRSYd+1F48Sou4+SU4b/hmhHp2llHZ2NjgH7/zm/jjd783bbt1aYbf/KbX8dLjw4E7fbzONv7MwUGDVITVaSqd7T23GWdky9FXWCLqWqsnZp4JbOKG4Q6ee0JilQs6JH+nFPLJ95kZLS49xtTGJXYP3RbXFQd0a3vP5Zygi9Qh1d1VugvHhj5XQQe31xy/AuXEX+Bz4zST3w9TC4jOzpgdKT4481byo6hvXyJozBNVp9M2f3qRSmstNw4jFCp3f+7v76VrwQpZsFGPj4m1DNw8koATaw2xP3sm2EmqXBCZIC4Fks9Ez9ciB1Bhj2I4mZlUsqCkpKTkWU4pdpeUlJSUlJSUPM389E//NG9/+9t585vfzO5uLEa+733v49ChQ7z//e/nJS959mZElDwzWGtZXV1lY2MDk6ijSikWFxdZWloau5wpKKmTLMqNzec17cfO/GqEbogF5XoFOn4xszoWqituXK87/5mgnxAehHY4aSVBG5vLnoZYlJbCplndUjAxu/xq7F2VFGkd8CCyaAM933BgRqD2kcEuhMB1Btn0/fFpE4tA2bEoJViYluy2DaEmzeiWQjA3JdIa4X12dneZmZmmpKSk5OlECMHiLc/nSTyMMSi/TWP97JBgXNu+TFdIoupUvNz+N4BRLipjvywAYaJY6LnOWGvRGStzC7GoPeiAm4g7fSE7Fby9Ov7UIq7fSuvySqNxu9v5/R1RB1npAM1wRmmOxOo8u5wtBn1hqffaHGhtUg+6WCHYrtT5VNVjxxm8XCUwL6tUEtEkxFARKrZG75f/wHI2alIRKrUWF0IwLyt0dSe33R3ts6hqI2t993GF5KFgixPuNFMyqc2NoGtDJE6cFZ5sQ2MRNv73uIzrWNjPS3t16WCsZT1jLS6FQNm8tXos4YqkBngssksGNcdtsv/ZLYeJ4FgTA9E6sBqNoYZDJGxO6M5isIQYvEwN3gCTE/oBKkLlxO7+WHPBCyPq24/CYnOZ600T8onjz+PQzgruCNvscUd5IHjrnKhaFF/TbFnv2Vmv+/3vfz/f8i3fwqVLA7H/O+++jZ956ytojLPJSZAjspZHXel9YXvQKc7I7gcFWIgzcTNuFdbxYmEy7E58LqbHPPvcEyJeV9F9whoG566/9N4XjYp8GpvnaC3ftGdfAKfXwgniZ4HX2RoSuyWW6dXTgzEcvx1uvBMuPgq9Nhy5GfHSN2F/9ydgd32wn3vR3Ih/RjEqYnQfVHdXaWXEbqscIq+Omwna2s/gis9orO1L0pMXz4j9Ng1bSs5aJuNfANZoEILJZ3f4fSGMxnIN702vRuuRT+NfPoM1Gu/AIeon78SZKcsllZSUPPspxe6SkpKSkpKSki8Ad999NysrK7zpTW/iQx/6EABbW1u87GUv40d+5Ef40R/90Wd2gCXPKq5cucLGRn5iR2vNysoK1lqWl5dHLjczE0+eKxnXjB4l5lob19L2Q5iukWYEX+N80Z64jmBaJgKxBkScze2oyWKztTatW9138ktt15NZHlcNC/SeE9uZaxNnPl9PYjvyuJY4xFnrq9uGQwv7t3LNivlaW8IIjATXye+L6wgOzCoivXcQgikW+C4pKSl5mqhUa9x40y2sXLyAXD090jRXYKnuXKFVuenqXyyj6mHvq4aryS3rdHdwgl5cc3dUd2KBI6jPo5wKbmeLqDo7yKIzBtdvIZPa21JHyCjIZWRrr4aKgnwm+pD6MWasY9pV5MeCiZC43SbV5hpO0MEKgT+1SGfuCMarAbFF95xbp2rXkYml8YFeiy/1BR+cmWXLjYUOA2yaHkuihpMcIyEEVVSuxrUF1nWP43IqbVNCckBW2DZBKowHGFo2pJGI1qMwyfrOh21u91yEEATJfvvWUBcSL5MdHos8k83F+xneqTBkLeejJj0zqCturEFmhCEseELFyyXXomsFhliUjteb1Aa3NmcRHmIQNrYz76Ox3HPDbXxm8yJrO+PtmiNrcvsHDInd+6kraUZc+xYbO8tk7q0IcJK2wGpaJuKDnsDe+Vq+7MJDzG9d7h+OzHoSR4H+NmR8dOM2ASbKC2yFL4r20uP72IMvLL7v88M//MP87M/+bNp2oF7h//6GV/NVL7hx7HKxcB1L+EZ5ON1dqq11ZNjDSgenuzssJvYDJIoic3Kc+vKltRoy1xBSYRwPVRDVbWYtcYNFRGFS7iBZm5D55026rGVcDe+R+9u/FzrbiCjAOhmnsRGCuox8plcH51sql8ZtLyHYWMFGId7SYRq3vAgR9GB3A6bmwPGwf/Vb2LOfj0X/y6exn/1rRPQ0lqbYZ2a7DPdRz94O/9qXsPtH2SgnDtTp3ytCgHSwxuTun7H1vePR5IJIRrmBDP+RNiKjvyiDj7gULALjeFjlYkXi2GDMwLVh/iA7930I0xuI/t3mNt1zjzH38jdQOTT+HiopKSl5NlDW7C4pKSkpKSkp+QJRrVb54Ac/yH/8j/8xtaO21vJv/+2/5aUvfWma9V3y3CaKIjY3N8d+vr6+jtY601/Tbrfp9no4UqCkwHOHhe6Ob2h1DVutWOgGiDJzWZa4dvd+rb3T5fYzqSQFVU/SqMX1rF1ntBCfZVwZcZ0kPDSqo9chhMBzBFWXkXWynypKxhna2sRZ3h3fcnFd0+qaqz52YXIatYmF8zAaXn4/dc+r/3/2/jxakuyu70U/v70jIucz1VzVXT1rVqvViFFqJAbZSJafsFvXAowwiOnZxvYFPxnbwMLLvGuBWcbiIlha9n3SvUISyGa4CKMLAklGA5rQ1BpaPVUP1TVXnTmnGPZ+f+zIzJjOOVnV1V3dIj5aqeoTGcOOyMiIyP3d3++v9fR0VtXU1Hx90mq3ObyyiNqlnrYycS7a/AlRuNaraIzK1oW1Bm+wgZ5MM4beuYdYPHMvvbP3l1ZncTVZJ+K4c2kfKESLC5LkHbG6KJCIYPR8HhJJYhpb52lunEFXHBdJIoL+Kv5oC3+8TTDaRNkYFbtYd2USWpvnWH78S+hw5rS2XkB/3425msK+tdzZz0fRWiAs1LkVEW7wugQZAbZvy5+pJ4pFFcyiwdN/i67kLBuJO1Yxhi0TEdpkOn+SVpNu58RuW1lvPLaGoYldLLq1aASN4CFEGNr4jG1CZA2hNWiUixqf/G8iEhb2W4uUypDkRPKUEFMSnO9dO8NmNNpx3wHmGYJWrL0NlNqUYHN1x8E504c2LrUrxjIyMdsmxkfhieK+xR5Ld343YaPHqLOfcWcfUdAl0QHW853oNRW/Zg5klHZlBSgKbBnmPPefKu69916+5Vu+JSd0v/Lld/H5/8/fywndRmliv0Xc6BAHLRIdkOgAowOXLBEO6J1/EH+wjheN8MfboD1XQztdh5Cm8hRc8zuKlcXkJeUTa78U2J+NQHfypUVM4XtW9eybX3v54BTfnQx6gZLo7i8foKMM/vYqjc3zdC6cYPHxLxE1e2wefhYbh5/N+KYXEW1cIrp0mnj9PIMHvsj6J/6UOAyRIzdDewHz+7+Gvf8zTuie8GQI3Zf57A1gikkhJkEXvtNWKZJMrfRJ/XSrdFoTW7nPS+vyfUApd4+B2ec1+W7tOSDhMgaIzUYDu0EwyiP2GsRew+1j8dgolX7vPVAeAvijLSSJkWYH21rICd1TTMLGZ/8nNt75ml9TU1PzdKAWu2tqampqampqnmL+xb/4F3zta1/j0KGZ2+hzn/schw8f5s/+7M92WbLmbwJbW1u7iqbGGPr9PokxnHz8FF+992s8+NDD3HffA3zt/ocIPItX8ZTv4rfz04qdqhYnMpudlOYCSeIE3yeDqq4eEUHE1QLXSnbtL3KR5k/cql71WfRaiqwGMo7g3JphczB/h5u15RrgcTLf4IEsSin2rSxf1jI1NTU1TxQz3tnVOqEk0lRRcBD6w3W8TM3XieN3KphYQzBYo7l9EX+wAdbijfooXP1Rb7DB8skvEozcAML2+mn8/lpV6/LNKIoVVUL2Do5si5B4AYkXYJTGaJ+o0SVsLRG2FpEkYvnkF1g49wC9CyfYd/ILHLj/o3nRWvuE7WUnOKYYr8Fw+WhOcFQmpnvh4VLbB0vHcsuuxDErcb69oU1YVo3cvd8Xza3+4lRQLcu9zgGtRGim7lQ/7Uo0ODG6SGQNF5KZcDS2Cefi/PmyqIJZlDllcdhay0Yy5nwyZM2MWTXuvwcmdqK0CB3l893d63lhY990ORHBF1USiC3l+2tVh2jxuQjKovRmOOJga/fSIVXrTmxeOB/ZslCqRU2Pb5I6zUUktz+TSPZJjLoT/xUeCo3ioG5y2G9z0GtxfGOD7c9+iLjZw3gBxmsQtxZK5xoVgwIQyX8vioNObnnxrsfgqcJay9ve9ja+4Ru+gS984QsABEHAf/pP/4k//dD/5OidL53Om3gNkkZnJlpqHxM03d/pPHnvbgal8seMibu7+NxWlXZh3DUsW5dZ+xgdFGZUpW2LtdNrj+w6jMLuKfy6gT4eVsS9AKMUQX+N9qVHaV98lOZgFT8JaW+cpbl9CS8cEXb2MVi+jrCzQtRZZjAaE559NLe9aO08ax//E+LNVeyDn4Pzj+7almuJP9yktX562v5guIH1G871TPoJKoXVHkZ7GKUz4rXCKC8dMJV+VkrPBotMEDV10O/Eru9mhOzKJdPyGJMXyncCt9LuNTlXs3XMrSs/QqG+t29iOnf9PaK18zs3Jw659NE/It7e2HWfampqaq4ltdhdU1NTU1NTU3MNuO222zh9+jR33333dNpwOOR7vud7+Imf+Ilr2LKaa808YufJk6e4774HWF1dm85vpsmJ1SJww5fC39AIBGPK26yKzaxqZ5w4s8q84vjloHYQsz2VdztnjRJzmybmJDGW/qi8b74npeMJVM57+dvM/y3ianvvtEs33HA9nvf0clfV1NR8/aPb3T3nMWr3eqESh/TOfI2g79JMxCR0LzzMwrkHaWyeTwUHVzNZWYPEIY2tC1NHuT/axO+vojKiuo7H+MN8Z3xr42x+u8A8NW0ncyXad0J2Sfy2JF5A2Fkibnbdq71I3Oy5WGClQGnGi4e5cOu3kWSErcZgjf0PfTIvoCtN1MgfV6t9BktHcoK3P9xAxXmXedxaYOvAzTmHd8sagky3nyBoUXQzn0uQxomvaJcQsqTy4pvJRIsHqTgdFBzZWRJrORFukGBS8VXYMGNaSnNEtznmdTis2wSi8BA8cQ5kryCziwgLKqCdiX92cexjtk3eHfri5gGWVSM3zau4axY/calwcs/z+LDgN7m5t3/XeRRCbPOJL0MS1swYYy1jk5RqfksapW5S0TLKCJsizs3eEk1H+bSVT0u8qfCtxL18pV2EvLVoY3j1qRPoqmc6pYmDQt34qocnUVjnL86XGGj1UHd8567H4KngwoULvPa1r+Uf/+N/zHDoBlQ897nP5VOf+hQ/8zM/g1IK9eofR577LRjt59MbsmTFwZTpfmenaQ+jigNjdM4pXOXudtOnMur0fau9mSA6/VeVz1Vj8sLnjg+6u9eKNuIi1I3fxPhNkqBF9+KjtNYeJxhuEow20Q9+DnvqgczGBS8a0bn0KFJRzzy39SSi/8AX4cHP7zrftcQiKCzttdO0Vx8n6K9N70FWe6nreXYuWJU6t3NCdvnHRknY3u3HyMSNbZ0be7B4hM3Dz2Lz0G2MevvTkHI7O2cydbxLcffTv627NxbOvemAscxyKgnz51g0xpx+iL1INldZ+9gfkwy295y3pqam5lpQi901NTU1NTU1NdcIpRS/93u/x+/+7u8SBLPOxf/6X/8rN998M6dPn76Grau5VnQ6nV3ftxbiJCGKotL0CabC+BF4TuCe0AxS74pAfwSj0DKOLKPQ0h/tLmBn62kXtz1hFJajP7PLzyPq+xUaroigroKYPc/2t4aGUWTZHprS8Wg2yo0Yjt3xm4ed9iOK84MNhFTwVjPRezpNwK+F7pqammtAY2k/fm9px/eN0qgk3FkcMQmd1ZNok9BaO0Vj4xyLp76Ml0aRt9dOoZIkJ0Apk6AK69OFWFyrfRK/VZhnh/qsJsEbbuINN5E4BpMgSYTErt1Ge4TtJeJWj7jZJWmUxUHrBXONsIqbPTaOPjc3zR9v0750MncTNV6DsNnLCRFRe4mNo89zsbmkYkVFHLDxmwwXj7jjAPS1h8q4ghdTsT1AoVLhdCJcLygfH8U+PSuLYawlJC/IdsVHp+tUCFiIbMLQxAxMzKYZ01SaBRXQ1T49HdBWPh3xaSmPhmhaypvW9J4dSrfOouC9qIKSS3sjGZfu4bcFS7m/q4Tsee7OxXkUlIT0+zfP875H7plFpaf/my3jjo3FucJngxItoTWsJiM2TUhkDWObEFrj4tptzNDGjGxCVCVaiuTWJ1LeBrhBAWNruGVrnXayc7qCmUSX73VMtM45vOW6Z+Hd/dNI79qmyvzZn/0Zt99+O3/8x388nfZP/+k/5a//+q+54447ptPEb6Be9eOYG1+AUZ6LLFde6Qgb7ecGiwiQ+E0SL//5G79RisG2mWVdTPgO14SKJAQzjUcviN75BV1d6F3cvlOH7w4YwDRauRrgk6j0osDuBPv8d1+ZhMb2zmWWJozOPIzd5by76lSJzDscf4uL6J/Q3DxHY/tCPqy/NJhhzh8dk/kmTnxjpnW+jShMeoyL16640Wa0cJCotUDUXqR/4CY2rnshSXqOTT9Xa2DlCLJ0KDNwohyZXxWtHwftnBivkhiTiWgHYI/SDBPMeEj/wS/ONW9NTU3NU00tdtfU1NTU1NTUXGNe//rXc/LkSW677bbptIcffpgbb7yRd73rXdewZTXXAmMMu3VXzdNZK1LuBxMROk1FtyUEaQw4gE5T9+LECa1xAq2GoHZQlBNjWd00OVE3KbjDo9gSxjAYWZKCSGytJYpd9PdegrNWQqNQe9sYSxhdmYPaxa47QbrooC4SZyLaR5FlddswGM8W6jSra4KfuTRf/W7nGq+ebxy67VtrS0YSpTLCt8D2du2uqKmpuTYs3/4tqKDslLQIUWsBweKNt5FibW9r6Z5/CC+N8RagvXEGfzS7ngnQ2L6YX0x7syjZKTtEi4sibC0QthaJgnZh8xZ/sEHv3AN01k7RWTtF78JDNDfPIyaZOeqUQmw8h5tyPgYrx9k4+KycyNbaOOOc6JltGL9F1FrKLRs3uwxWrnftR0h2cKhGrQWM0pwLGoy0O1YKIRDFSiraiggBioN6dlw8FLcFi3gZ8XNsY1dr28QMTUxsDS3x6IpPR/l0lY8WRZTGbRssvmhWVBM/4/5OsFw0o1Jsd1GklYo62iJCuyA+xRX1vbt7pAhA+cmq6v5rCus9pDsc87tc5znHfWwNCeQGEUzWPRG5W2gOex1u8Hoc87o00AxMxCAVszdtRN/GRNZg0uMQYUsDANz6iu0j5/iGKsnLrXNxvId4JTKX2K2/91/gvfE/oO/+Gbx/9Et4f/+nkZUjey73ZDEajfjpn/5pvud7voezZ11qw4EDB/jjP/5j3vrWt9Jut0vLhF/+K6KLZ1xMtfYwXkDiN/MubQHrNUrO7SRolaaZTL3tyUCAmUi683VCIB2RWnxIT78v1laOWBVrndB9pbR62JWjJff6bANlgbjKoe6n5SF2JTFw7La953siiIKjtz3ha7IbOLR3TfQpqYg9GXAgJkElkat5ncQQR6gkQiVxOjiBNN48re+tyrXfG4M1Fk9/NRctngQttg/cXGqrHLgeBsXPIH8FcOdJOZEgbC9n7j1ugEM2rUQvHcDfN9/3enTqxFzz1dTU1DzV1GJ3TU1NTU1NTc3TgIMHD3L//ffzUz/1U9NpURTxhje8gde+9rXExR/iNV+XbG1v8+BDD5OYcj1nmEWVVzHRpp0Imoa0VswfeEK3lYk1FaEVZEb7i5snS5w41/dm33B+zTCKYJwRu53bfNZxHMazaPX+yIm6YWQII8s4ctMn7++FUrPI8FHoRPQr7dsK07rlxpYd1EWKIj3AOBXZbdqRdGhJldzZxsKlTcPqZkKS7Lz+rYElSmAwLg8IUGoyCOEq5bHX1NTUPAkEvWUOvfRVBIdvwCgX7xsHbcbdFWzGlabDQn1vEeJmvuaxVbrktNzJke3EXue4tOIiZqNGh6jZIwpaDJaPsXbdC9k+eCvbB29htHgYFY2mN0QRIWl2GS8cyokO/rhfci46J2VepL1iRBjsu571Y8/PTVNJlKvfDTgxLj2GxnOO7HHvAFYU4+6+6fEtb0PR9xvc012YTvJEuNV3QvbEPX1Yt/EzwldLebl4crecmtaNTlKBecuGxBmxVYlziGc7F0WEjpRTRzZN2eVflPVUxX1PV3Zd5u+bfVNMuyk7o33ytbxFZHpMwEWwZ9d6VHe4zusQ2gQPRU98QgwmFfYR0DinfEP09LXfa3FIt1jSDfbpJrc2lrjRX8i1xaTHdC+qaqgXBwlM1lekP0/ySzHyOHWLT9l3FHXD85DeCurYbcji7vHtTzZf/vKX+aZv+ibe8pa3TKd9z/d8D/fccw+vec1rKpeJT58g/NSflN8QqXS324yQPREDJ4NLpvOKYNWklnN6nCfu6Kpnt0xstXNppykSSYxYk8ZUJ4hNADNXnP6UVg/aC7vOIt/4PdjO4h4rqnaU5+aYJ5Vp3yHU81/m2vVk0erC7S/ffZ4dHPI7TjOTuupOzFZxiI5G6GiMiiN0OMQLh3jREC8coMOhE7WtdWU2REDr3D1F0s869z0TwRavtdGwNLgrai8Re818i+/9BIy2d/gxmN9G9vO0olzqSeBST6a14tMyBTRaeMefy8LtL0WCJnvxlDr3a2pqai6DWuyuqampqampqXka8Ru/8Rt8+MMfzkVZv+997+Po0aN85StfuYYtq7naWGsZjkYMhyPiOOahE4/w0EOPpM5uJ5omZlITe+Ke3nl9T6Rete8JnaagVXV0+HBsubhh2BraqUAdxnlXlDFOQE6Ssms6MRCbvLhtrXNYzxMnDi6GHcDT0Gpc2c8YL7OYxTmoo6S6DVVCc2Kca30ydyMQrjugWOk5t3zgOcd3p+l8gdEOYrcxdiqcJ8YNCBhFhsCHRuDqq88GLOx+fHq9J7EzsaampmYPdKNF0uwSdlcIuyvEzW4uJhZwNbWL4pyXrw09nS6asLVI2Fwg1gHecJP2pUfpnn+Q9sVHsaIZLh9l3DvAeOEg44WD0xrZVntYv8lw5TriTOS4ADoOneCdIW52iVp5kUiHAyTKi7LFWNgrJj0G44VD09rcYXvJbTcaVhyjBkbpqTBhlSZs9tjef+Mum7B8urfIQtDlVn+RW/1FbvEXWVQNeuLc2D3x8aqiSQr4ollUjZxAbHGiddGR7RfEG5W6x7OMbVIxyGzvZwBTkMQ1grL5e/R1XpfnBrNYbREhED2t3e0haKXQokqx6ErE1c6tiAS+N1zjnvElvhRe4lwyLLdfBCv5aeeTIafjfm7aft3ikM47jg22ctBdccq8kl2R+xdWiHZxblvcd2ASj29x51ziN50A5jfQ3/n9c2zpycday1vf+lZe8pKX8KUvfQmARqPBr//6r/P+97+fw4cP77hs9NW/2nnFIhnXdiZGXLSbPokmnwzGyRxPqzRJ0MGmojlBE/muN6QDBtKXNUgcouIxOn2peOTcv9agbOK2mnnmvNzHeHnZ3bCHQGnv+2uIdq+3PQ9x0NpznvYtL0SabdTdPw0L+57wNisZbMLFk3PPnvU+W9ygjlm0uEWPtvFHW/ijbbzRNjpKPyOToEyMNpEblJAi4ARuU3SFq1L6iGBL31erFElmUAVQjogXIWm0d4iY3/kKUBq8IQqTRvG773b+c7RK0XzpaxHPx1tYZt8r/h7e4u6fm798YNf3a2pqaq4VdYG3mpqampqampqnGa94xSs4e/Ys3/Vd38WnP/1pAC5cuMDtt9/OL//yL/OmN73pGrew5olyaXWV8+cuEE7rbsuOoua8oYUiglbl6DpwfSLVRhM7FVU9LXRb1e1oNYTNQSEytC3T+m/TULzU4V0Vo25MXv+IEjevp+3Uub0bWgu+Z0uu88vB0267EyypQK+gWTDJ+dq53IsG762hYbGTqSGrhIWOoJQhKvR5zaLI822uilCP4rwrH5woHtly2yYsLCzQbO7twKipqal52pGERM0eYXsJoz1UNEL1DhJ2901jgSWJaW2cIRhOYluHBKNNlIkZLh9zk3aqzeoFmCR2QnuKSiKMbeQEq3FvP2It/mjLrQ4IRltE0ttRkL9SJImn98vRwkHYtIRtJ9BOa/Fm7wFKY5oLiDVIEmNEs3n4WXjhED1YByAJ2k7YT5czIjy3eQC9y8i3y0kNcc5tj207c04bIMTQYHZT9xCKPnwtMv9DTEpiLYk16MxnFIimJYZh6rDvKh8jQDpfYi2B0tzRPIBC+Eq4mi6nCEQxsgldFXCT36MjPn0TcX+0zsDu7k48lfRTd2bq/GaW7pJ1oLviMzYXwb5qxhywrZxb/pBucS4pOPgLy81LKZKd/DNdUzQdv8lHDl/Pd555tLp+uXKpCKH2CfqrzqGcLp90Fml87z9DzRlr/GRy7tw53vjGN/L+979/Ou0FL3gB73nPe3jhC1+45/Lm4uld37dKpeENhe9e0Jw9zFqLUR5Re5EkaCEmwVrLxrEX0N93HJTGj8csPnIvC5L5RMVzX+vECc2C+65b7Cy6HGZO3CuIKrf3fxqi6hSMKdEIuf652I0LO85itIeKIybefjtt8Yyws7LzNkToPv+baR650f158AbUG38Z83/8K9he23tHLhNZPJgTsYXs5Sbzl+jpeW2x7reLqOk0ncRg3VCXqR86FZizAnfVjxuxFmuS/A8cURgxqOyAICxG+S7aPN1Gon2sUnjpZycV9dxVEqXbLb5Tvl+kU7Fp+QrSQTxRa2E2nwhRc8Elg6Tta3zDd6N7y5hPvA+iMerILSy++BVc+sgfVkbqA7Rv3vt7V1NTU3MtqMXumpqampqampqnId1ul0996lO8+c1v5ud+7uec48QY/tW/+lf84R/+IX/xF39RWZOu5ulHGIZcuHiJzc0twOJ5HoPBLNLV9TVcfufWTlSJqzvRH1k8bWkGrlPZGOe2bjfzy3vaOb/7I9fOwHfTqlpugWbDZzjKR4oa69avlOt8mdTDDmNoFMRcY12Muy5khHeaMlc/oLWurneQcUhD6vTyXBR6bnumfNwmNc63hvmOHheBbvELonvgCVE8a5ynodNUlZ9FVTl0a11Me6sxc3SPUzOkYAm8bDy9RZTHddddt/fBqKmpqXmSaS+usL16gazAYLXv6uOKcrGwhWth2DtEmHEXJ6nTOYvV3rROdXNrJtK0Ns8RNXvErd2je5OgBeFwKngLTnC2WRFbFKPFQ1ilCVIBGZzI4KJfr1K3mUlQycxZGfttNo48N63n6hygJeHCCq3Ns3jhID2ykqn/6ub1x32SwTqjpcMY5ZGI2lXovhIaonNiN7ja1Q0p1k/PUxws5qNyIrG1lg0b0RaPZuquHdqI0DohPRCNwaJFsaAbSBKiReik9bkNYKwhsoYNMyayhsNem76JeHZjmRXtBoNtG7eN7LZf0NjHZ0bnuC9ax9hyDfBpG9P/L8aJF58ZqkTrjSTkgDdzUDaVVxDkqjZYFrAm7u/sM0CEwcc9Y1hriTHEQBMPLcIB3aIhmnP7jvP7fsDLzz7G/jAVRAtiH0oTN3v5sgHRGDvcAq6t2P0nf/In/MiP/AgXLsy+///8n/9zfuVXfmX+wX7+HoNWnNUXMIixWAHj+UgSurhxnDt2uHyEsLs/v5ieub8jr8HF6+8g9JoceHDmJrfacw7vzMAbIU3uyX3WzgN82d/e8QgO3wQPfWHHWeTwTXi3fzvhA59z1+OKQzBYvh6jPboXH3HnQuYcsQijxYMuuWMH/JXDdG4piKAmeUJCd1HIthnhWhBsewHG7jeVtRZsNgJeSqNCBEkHG5h8lPjkPpWLAlfuc9ujjZOY8um9QgSUhzEJKnuslU7j7JNp86zy00FZCVGznDLiTcpbTNuXPx5ZLK6WvJvXToXtxG9hlXJ7by147t/JOpJ7P0X8wXei0gQTixtIsPjSu9l48EuQjSwXofucl9A8csMeR6Wmpqbm2lDHmNfU1NTU1NTUPI35N//m33DPPfewb98sTuwTn/gEhw4d4mMf+9g1bFnNTvT7A06fOcvp02e4cOES9z/wEBcvXiIMQ8IwygndV4tRZBmMDZuDWTx2kar63UrBxQ3D6UsxZ1djTl9K6I+qY72XuorFjos6L7qrbeYlgCKqNNvFplwLu1g721pXG3yzbzCFeUUEVaUUF7eTuG2NQltax07JrXFFSm3DFxbbCj/TH+bp6nX4Xj4CvtWoFrph4lIvT98aOJEe8vXZwxi2R66+93Bs6Y9gaxAzDqPySmpqamqeQqwxjMcj0D5oD7SP1QGJ38J4DVf/No1QzTFHjPaEwdJREpW/aLY2z+0dL57GwJqd6ltnGHdWpmklZuosd9fYYiztZWMtKhphlUfiBSRewKh3kLC9RNReJGovEreXmNSKneIHjLv7p050wbrY40IsvE4igs2LhKKm+/BkUxR2q3Jl9ukGrYygtKDyouPQJsRYNm3E0MQMjBO6wUWeRwW35YIK6Kr8ZxnahFPxNueTIWtmzEUzYsnLR693lV+qBa5E+KbmIQ7qFlGF+Ffct72omqcYi16sCV5FgnO2T57DbKZmurWz57MYw8jGGGOmNdQtkFjDdV53OhDBE8WpziJDb/L9TMXZoqCuy4KwvXRm7x1/khgOh/yzf/bPeM1rXjMVug8dOsT73/9+fv3Xf/2yUm28G19A1Oi471uzV4p5Buf4VSZGbIIySRpjPUtiEGtobZylsXFuuozgrkONzfO5dW0eeQ7jggPaFCKr3UbLkfhXRGcB9eLv3vl9UciLvwt14Hr87/x+dw5km4EwXDxC0mhjvYD+oVtR3/0GRvtvZNxZYbhwiK1Dt+7u6gaiS2cw48JvHO3BFSRkTIVt5YHysKIxyncDB5TGKo35y/dis9sTgUncfOUas39W/CiScrpV6Vyp+IycWz+t951Fzep3T4R1m06bussBozyMKEaLB2fLmoTOpccq9qO8V9PI/Mm1NoncPSKJEJNgtOfuw9rDBC2M32RytRYgHvYZLRzGZO9zG+fxP/7f2f9dr6f3gm+lddPz6DznJez/7u+j86w79mxXTU1NzbWiFrtrampqampqap7mvOAFL+Ds2bO8+tWvnk7b3t7mrrvu4md+5meuYctqsiTGcOLEIzz40AkuXLjIhYuXOH3mDElyebU+d3IuT/plqt6PY8t4qntKSVDeiVYgKOWczXHiHMf7FncWabstxaFltWvsuO+BVopOQ3IiseBqWrcbQlBYfpAR2KPYtSUxsLZt6A9Nbn/2cnZba6e1so2FYWgZhrOObCVOsC8SJWk97sIGfE9Y7GiWu8JyV+i1hHFoS8fYOcGFVsMd02APM2CvrUp9Zha3z6PQVCYHTmqfT7Y8HO4RW1lTU1PzJHP2oa+xcS4fEyxYdDREkkKMxhVE9AKgNBvHnk/YWpxNiseoaFTeRgWJ35gNylI7XJyVIg46Llp2InZbk9bprRC7jYsWn3efTNDG+Kn4r32SVhfjN2fitIiLD7ZJbp0maDFcOJRbl5svf5PwoqGLvH0SiCnfkIqubiVCW7ypyNwSTVN5HNZt2uKxpALaypsmFW2biIiElnh0xCPCObTb4tFTAV3xXW1unLCuEJRIyWEdiOYGr0dXZiK4xUWQj4r1dAuICM8Jlkui9NXCLwhla8mo1AlrsEQ2mQrZE2E7wjjXeubYF9tpcXHyWUJM6ZRcUg38PQT9Sn2weW0SpO655x5e8pKX8Na3vnU67TWveQ333HMPr3rVqy5rXeGls2xcOMd44RBhZ4Vx7wD9fceJmr3ZTEphGm2SjOA/iRsvHszG9gUkzte+bm2eK823dfDWfEMmMeU59j7vkjkG6vDQFzAf+3146d/LlWgAQHvI3/ph5NCN7s9nvYTgB36e0fLRVMg+yNah24g6y9NFjChCv8W40WG0eIiwuzJ3woWJ89cgEcE+6xsZLhyiv3Kc4cKhvKi6K1mXtaAqrntMQ9dzGy0P2i18ljKZVlhOKH/mpfXswMThnZ3HpnHodvI5pvXcTfY+pD0GB292A06sIeivsnjma/jDzcz6yt/96b1JuZeIuJIXmX0MRpu0107lhXilp/fE6fq0R5S5vwKwcRF57Cu0b3kBC7e/lO6zX4xu7+zsr6mpqXk6UIvdNTU1NTU1NTXPADzP40/+5E94+9vfjufNfiD/5//8n3nuc5/LxYsXr2HrasZhzNfuO8HW9vZVWV+xf22vvvSJeOyl/UdRDGFcdjUXxVURYd+Cnk7vNKXkfioiIuhd+qkmxmulhFZD0Wu5WuDdltAMVFpbPC84hzFsDy1RbAkzUeA2FasnbudM6cRKEmNTwTo/3Zi8ezzwyscCnMi+07qVuEj0MIJxBNsDm4stB3ds2g1hpaf3jJL3tbDSU7QCcYmiabuWuio9Trsu7tbhP0G3YU1NTc0TYNTfYnv1YuVILIF8LDKACDoclMSiuVCa7QM3kaQuQZtGQqs43PsmKco56rS3q6PcaN/F9E6E7HQ5f7hJc/Mcja0LeMMtWmun6J1/kN6FE3QvPEywvbp7G0SqbzqTSPLsJLd3uWlxs1cSiIr1XQXwruC4Zl3E4O6VF5MhURq1a60lsoYg4+XuStkpDe4e2BRNV3n4op1b28YsqQCNcCkZcc4MOW9HRDZhQQJ6yqejfBZUwIIK8CYudqkWt6sQEQ57ZWF21ew9IGy/bu05TxXFT7t4Vgmwnow5Hw/TY5hwNhmgReVc55N1xeSFbQtE5J3gTuAqil7l825YqEWuRHi8sft+llISvAB901Nbl9cYw1ve8ha+8Ru/ka9+9asANJtNfuu3fov3ve99HDx4cI815EmGfdY+9QFMOMq/IYpxdz+xnz8mxm+UXcEV17VsuQNw1zkpDKwwc7mZq7c1dQMjbBx7PhtHnrO3QHz2YXjky6gf+xXkpX8fuf0VyF2vQ/3Yf0Q9/6W5WZMkZtxaYrR4mLC7v1LITrbW52h/Ae2jgnyKx/Cx+7kUWfoHbmK4fJT+gZtYveHOkvO9iBOjTfn4V9xrbFHwnlybsvNJGtpdqKOdX9HsyE/+Wy5jgFalgI6Q+K3c9d+mv+NVHKLiEHnuN9M4fAOt1cdpbpxDj/pTkTy7HiuSOsLd7xGFKaV8VF0tVRKVzlmULrnW40anfDU589Beu11TU1PztKKu2V1TU1NTU1NT8wziR37kR3jlK1/Jy172Mh599FEAvva1r3Hs2DHe8573cPfdd1/jFv7NIIoikiQhCAIeeOQC9z10luMHd3ZEZynXht7dzT0PvnZCabbz2RiILDQL/WPW2rROtpu34QuHlzXbI7OrYzuLp6pjvwVKx0Ck3FVtrKXhwyBbHjKBaFgW6AHGkaVVSMGd1Dqf1KucOLN3Ik5mbmsRoelbEuPc0gBauddOn+FkO6NMzPj20KKUZakzE6dzdbX3OB88LSx0hKqqs1Xu8yzNZkC3c21cVzU1NTUAGw9+mdb6aVffGiFutIlai1MXm4t2NQWBWWhtnGO0eGhOQSi7qGLcPUB7/dTU5T11Oe9RP9oqb+/tmZiFiycI+msu3tVvEbV6xFkXaL5BKBPT3L6IiseMlq6kvrGUI8CtzU8QwXgN1KR+607NVwqxFpXWYzUChh2Edtx9amQTDJY2Hgphw4wZ24QLyZD9qjV1GosIvlU0RaNFsZ6MMVj3N8IY4+YDtJX0vzPPJGld6QljDOfNkIPSIkg/OxFBW3asn70bgWha4uWE3qLoW0XT83n19S/g/zn5lWlrk4rt28L+iMyEZkmd59P3gJZ4iAh9GxHFCWtmPBWzlQjGloXsK6FqOS1CaBMGJsbiBit8YnGJF29tUPktsRZVGJjif8vfQYL5o8KfKGfOnOGHf/iH+cAHPjCd9qIXvYj3vOc9PO95z7uidQ4e/Ro23iHtQISovYi3kY/BNtpHJ7NBI1W1tYvCtk2XzeINN/PbM0lJXBUs1iT5AS9pvWUrzh1u/CbGb7J98BYWzt6/+w6fegD6G6hv/ju7ziZzuLRVo4W//wjRxcuIsk8iLv75e1l8yXfQOHg94eo5Nj//EUpnqdJsHboV/fiXZzWpM3NlncnWutrauWkVRROs8nLHeCqWowo/tGxac0EqBzbIbK6yo3reH2XZwUOiEZO475c1qcBspzWzAewXPoRpdLDdA65dXkDorRD7LZpb5wtXlopzqHD/q6rn7Y22CLv7ctOs0rMfQZCeh4Wl50kWqKmpqXkaUTu7a2pqampqamqeYVx33XWcOHGCH/mRH5lOC8OQ173udXz/938/pir/uOaqMBwOeejEw3z13vu47/4H+cRnvsJX7j+TOoXnE7qrEsafaIlNJ96WV2ItJfH4zGrCw2eiXAy31i6qe16xW0RoVPSVWais951vk8UYJ/R6Fb2uOzmuR2H5vLYW+iPDYFx2WReJCk53EcHTQsN3L0/Lnp+hUC7JZ1LBXERyQndi9j4Wu25LZMcodBHhpuNH5zrnampqap4M1r/yaZJTD06jswWLP+7T2jg7rXXtKHTOp4JE0F+7ou3GjTZRo5MToKciUtb1Zy0qHOKNttDjvqvDvcc1M1w4yKh3YCoueNGQ1uZ5Glt7p+cEoy1UONxzvhJzXseLzttiDWCLEIQjgiTCw6Kx+NYSWFPpTpwI3UkqHfVtzCUzYtOErCVjLiUjTsXbXEyGPBJtcl+4xkPRBg9Hm5yINrloRqyaMaeTAaeTAeHECY4Tq4suZCVCoyC1WmDd5N3ozrF4ZRQd08W64jvx6MWz+KLw0ldAtfu6Ku5cAI+8A72Bzg0+HNkk59q+nLZVYbGY9GWxiAUfRSAaH8XFZMTpuM+GDV09dBIGrR6/f/AIYbFWN7Cl9fT8Wu0u473yh/Be8LIrbt/l8r73vY8XvvCFOaH7X/7Lf8mnPvWpKxa6wUWY70biV7jdpfy5F3E1jzPziCbor8+uPSYBpRgsH5uKpnqHEgMzUTbfhv7y9TlxMmwvk/h7Dz6wpx/ccx6vu4i3uG/XeZpHb6L73G90EdmXgY3GrH/6z4n7mwwe/BLecINgexU97udnlPT4SF7KLfut82737Jz5STKthz1ZrvLYZtea/aytRWySm0NsMtvS1HUvGNGYkvN6IpCbaQsFUDZBmRjSeHFlzXQwUnZv/HGfxnb+PmOCFnGjHBte8o7bvctllZIbqDiKFQMy7PoF7EadHldTU/PMoXZ219TU1NTU1NQ8A1FK8fa3v53Xve513H333YxGLqLvd3/3d/nLv/xLPvrRj3LLLbdc41Z+fTEcjXjwoYdzgwnWtlzngZlD1LTWEsWpoQCLUlfW0VnVLz4R0avcxFECgbjpUWy5tOG6ay9tJCx1FZ528yfGCeONYL52KeXc0cY6l7Pg3MiJoVLEnrQze6S81FSQPXyTdRQP6fbQucHzx0JQUh5AoITKQQVRYmlc4XGfbK/KiT8KLb6Xd9Vb6/ZDq70d3jvhBHh33kz2RytY6rVZWtzJaVhTU1Pz5BJtrjJ49L7K98QagsE6496BtKZoXrr0UtFDx2MkieeuBTvBKI/B0jFX+zq9IFtr0ePBzHEp4mp6Zzr4vfE2caNL0ujsvHIRtg/eijfu01k7NZ3sDzcIWwvYkjM87zD0R1uMgyuLxd4NSaLp/XPiuxsuHwWE5sZZxCQYP8BPxniDiHF7eSpSCeBZQzRxOKbEGNbNOK2dbVAIoUm4aEbT+/R5RiiEljjxNsayaSOUFRZUMBV0EyybJmJJBbn7XdF/6ZzbknNOj21CbM00vty1ucqbuDvW2qngPmFJBbuuyVjLMI54kb+CGMv94fq0nR6CtaaiTrbNCdlV606wuc5WJYKyclVqgxelO4tzyetUPhcRxqlI12BWUkWL4vHlg5y6/RVsf/XTNEYDhl7Ao0sHGHkByiSItSTa4+WLB7ntCbd0bwaDAf/yX/5L3va2t02nHTlyhP/r//q/eOUrX/mE1y97CrUVgxeqhMPs5y1qmioxQdmE7qVH8MZb9FeO07vwEMoawu4+xCR0Lj5SKjtQbkrePR4M1hktH821IWr20NGoYuEM3nxO3O7zvon1T/5ppVu5ef2z8BZczPjyS/8O2/d+ZurwVo0WzeufxfjcoztHnScJgy9+lOYXPoCOZokBcdBme/+NmPQaGTe6xI0O3ngwOz4CoLCZ2tOTB+/p9WRSFmLS9lm0kpujGH9e3Eet3aTpOqwbhDV1cqe1rwvfc6M0qNmgKWvdciq97wju/metnV1/s7Xa9zgHvPE2YWfZudQnx6zRxR9nS2Rd/rURyK1zuqZJ2Yt0f6L2EmvdFXpn78ebnGcPfAZz8l7UP/hXyP5jl73dmpqamqea2tldU1NTU1NTU/MM5tWvfjVnzpzhRS960XTamTNnePazn81v/dZvXcOWff1x7tz5nNCdGBcHDjAKIU72cjTPuieipLqm9pUwGBkGI8soNJXR4sa4mtjGWDYHs67W/simjmnLKHTOaJeeWN0may1xYnPvT+pv+9o5o0chbA5s5bGw1rI1sAzHs/cmJacn/VZKIPCEZiBUadJVxysrMoMTg1VaEzyrMVdFrM9LGLl2r25VH+NxZBmO3bmRde9b61zpe50bWYrHXyt3PFoBtBvOhT4cDYjjveNZa2pqap4MBqce3vV9HQ7AGIz2cxdiPe7n63jvJQABEo1pbpyjc+FhOhdcxLhVytXX9QKs35gKEBNZQazF6iBX59a557ZRe4lFwPb+m/JtAPzRdvXM2fnmSdZJ8tduiSO37vRYOMdhpqvOWoLBBmifxGthEIZLRzFeA+MFjBYOuahj7ZPoAKN8dMFhroC+CXMD83zR9FQwdXYnWLRSrOhmTqA2WIY2ztf1TqdRmC+s+DyLNaWrHM1XQwQWEW7yF1hQbkBCQzT7dBO9Q9Xv2CYM7Mxt+4JghWYhCr/o7p6XqjraYNPng/R1FfZ5QtXnYYGo8HkYa4m1z71Lh/jC4Zu4b/8xRukADqM0STrw5EJ/46q1bSc+//nPc+edd+aE7te+9rXcc889V0XoBmgevmHX973xdkEUNUgye8ibfRdTcVMU/ZXjO7qdm9uXWH78HoJMhPm4u2/P9Iaqd1WVE9yaNDFBmNSpHreX2DjyHC7d+A2sHr+DvvUw472vcY2D17H0Ld+Dt3Rg1o6gSefZd7Lw4rum04KVQyzc/lKa19+G7i6h2z1Us0Uy2P16GD7+YE7oBvDCAQvn7kem10ADokhyA4Rk9qMAZtfCicCc+e/Z33lpQ5KofEwnqR/WIt/+D1Arh1DRyA2KikPnfE5TMKbCe/H3jjV5h7QIVnuleurT0hrlqbsiUBrMYOdy1lfEsRdqeSsT0V49OU1dkTh0g8FMAtaS+E3iRockaLN59HmY7LVwtI358HvmaEdNTU3Ntad2dtfU1NTU1NTUPMNZWlriC1/4Ar/wC7/A//a//W8uQjlJ+Kf/9J/ye7/3e/zpn/4pQXCZdTFrchhj2NjI19/Ldi0EnhNEJy7pynUUejls6ohW7F0GLjFOQHYx44VtpMaEKEmFUnE1tXOOBFuONN8eWlZ6M0eyUk5YdS5tOxWHJ5HcYWyxFlqB7OguH4Vu/ZsDS+BZgjQWPU6cWJwY8JJZvXARoRVYhqm5YFIzW4BWQ0iMRYlrW+BLZZe1Vi7uO0xjzCf7LSK4j8MSeJJ773LZHrn2exr2LwibA5srcwdu8EAUJ7Qa5fHEdgfXfZEksWwPLe1mWcQvLpsYU/+Yq6mpuSaYcHcxRcAJ0hkntIpGNLYvTf+2yFyubjePnUoFXjxCb5xl3DtI3EwjXkVcxK81OTe3VT7WJLk7hxcOCPeIA45bCxjRqIzLc56oWFPcHxOjksQdB3GOw9bmeYwXMO6uAEIw3EDHY3QcMuqkjuzJ9d4kNLZX8cLBVKQfdZYxyiPYvoSYBCuKyG+SBJ1ZbXRrnYghs1FfkU24GG9xvdebOpO7yud6r8sj8da0yb4ouspny8zENsPErTw7kmOb0LZe7t4UYUpR5XshuBrf2Q/pSoVgLYpjukMTzQGvhU5FsOo64HnxSYlw3Otyf7SRmzZvU4SZOK7Euden+2Fdve/sfk3c61dL8k6wJYd8Ve3xc8Va0hX4FS7Qq4Uxhl/7tV/j3/7bf0sUuXOs3W7zlre8hR/7sR+7quVZmtffSv/hr5BsV4j3xhD019Oax26SDkdTJ66rg5wdNSn0l68jaZZjpbOoYly00sSNLsFwjgEE2QEl2ifor9LcOIcOB1jloeIRILPvufuLOOi4pAvtM3jkXsYXTrH8sr+LbrZ33Vzj4HU0Dl5HMtjCJjG6s1Byw4/OPMLGX3/QjZwFEiBaO7+3gL/D9VIlMY2tC4yWjuAP3XXHKu1qWVuTO94Wm9a4zhyiTPvs5FiU6qlLZrmZ8Dyd68Pv2dNpP5234LhXNiGxKiewW+WV7jOkv8dmKxSwe7uyi3XEZYf4+2JqRu56n94HLZMBZ24WHY9pr59m2DvkaoibBIUbABO2l6b7abyAcW8/rc1zs/Wf/Bp24yKyuH/X9tfU1NRca2pnd01NTU1NTU3N1wm/9Eu/xKc//WkWF2fxeh/+8Ic5ePAgn/nMZ65hy575VLmdlRJaaeR3ryXEiXNZJwVVWyR1G1f0C+1W19kYS2Is48gwjmxltDc4J7Sxs866KHaiszEGrZx7OkhT99oZIdYCpy8ljCO3oM4byTAWhmNXD3sczdYf79A/FCX5Lpwwhs2BYX3bsD2cicOxyce+e1roNFwbVeHXiVZC4AvNQOViQ4toBTuPM3hiQjc4RzXAQluhtWKxq2g1ZqK/pI5035MdP6edTPxR4o7v9tCwOXCu8L3qj2ut8b1a6q6pqbk2+L2l8kRrkSRG4hBrDFYUrfUzdM89SPf8Q7TWz+YEBte5PkeXlNKMFg6R6JlwLuDqm2YFC5GcuD6ZZgtu3Z3Eg/y+mJIYEgd54Sj2m4Ttpel9zwJeNCLYXp2OMNPR2AnZ4WAqXIs16GhEY+sSje2LqCQi9lsYpZ2gnT0molDRiOb6KZr9SzT7l1g8/yC98w86N6I1KBPjxWO88VYu1lfcCLfpqkxao3vN5AcqdJRPq3CMWlK+v8RVdb8Lf89zlw0kXw+7KRojs+cCY5+YACwiHPBa+Vh0KQ+Vq3JtNwrHoer5rGqfNUJTNIFyL50KdZkG0FQerYKIXD2E78qpEreLdPwG+9q7l0G5aeXg1WpSjlOnTvHKV76SN73pTVOh+8477+Rzn/scP/7jP35VhW4A5fmsfNuraRw+np8ejWivn0InbqSlWIMOh6jc9aR8bZon3aGSPUa02un/zzzb/miThbP3u8EwSYQXDVGTmO1sQsNoi4Vz9+emJf1Ntu/9DPbSacyH3kPy3l8m+b//d8zXPoVNyqlAut3D6y2XhG4ThWx+9n/mriPz7lMwWN/xPX+4icQhQX9tti1RpWNuM5Hh4Jz1+cgmyf9tEsQyGzAkkgrAmtzVaY5EkXxDCr/rigMaiu1wC13eNtIlxCa57XnREKO8/NrStIFJ6DqTv2wCJkZMjBXljpeJSbyA4dJRNg/eymD5OiSJ8MI+fjTAi4Y0Bqu01k/nPueovUiJ/vpl71NNTU3NU00tdtfU1NTU1NTUfB3xkpe8hPPnz/Od3/md02kbGxt88zd/Mz/3cz93DVv2zEZrTaPRKE1f7ikaPtP623EC/aEljIxzJMtM5NY7PHm7WOxyp8goslORe0JRSAcnFheFYIsTlT2dF5BbDaHTzLiwEjh5IeHUxaTkVAYqe66LUea7UdVtudB2sedZlHLx3LpiRECSTwyc9ie5BAMXvz4O7bRueFXbKvftMmj40AqgmeooSoROU7HSU3Rbik5TOef5Lh21ZoeBDXFsGYxcXe4JYbTzIAiAlZVlVHFkQE1NTc1TROvYLTlhRJLIRZRHI3Qc4ocDlk59hWCwjkpdZjoJUXHo4s0b7Zkrex5ESp3vTqAa5KZV1SUtixBV0ST5m4QkMcOlI9O/E+2zevxOBotHppLUaOEgo4VDDBcPYwDjN0EELxoS9NfQ4QAxBqM8QPC3LmJFMertZ7h4iKjZJWp0GS4eJuyuEHb3YRqFYyLCcN/1bB+6LSNqQDDacmJ/Bp1EqfMzu6dOGLPWsp5Gdm+kAl+WjuTr/FYNLqs6isVpXfFz0xpoehJMo8s1Qld89qkmHgofRU/cjTXBklgzl2C7F1VrmEdGXU/CqYA0eVUtZ9K6NJPg/DGGoU2m920RQVUI2b4o/HkGeFwhc5zpnFq/xNqgnwrtZbn9lpXD7O8sXPW2/cEf/AG33347H/rQh1zbRPjZn/1ZPvGJT/DsZz/7qm9vgm62WbrzFXTWTtFaO0X70qN01h7Pl1MQKcVFVx27ymhxnJvY76/h99eQJCLor7Jw5mssPfYFFh//Mv5odze9UP4+7XS+Vk33woETKzPPjaOTD5D89r/DfuGDcOoBOPFF7Pv/C+b3fw0bla8BVYwefxA7z+CgAioe09i6uOP7YmK6Fx9BJZGLNM/Wy85Ea2epji/PHzEdR9WO81T0vlopCnsHkru5ckzrge++TGOwQXPrghssNSn7oVT+3paL3mea5CHG1QuPgw5xs0fS7JI0e4Td/YwWDhG3Fgg7y4xWjjFcuW7qIhcgGG7QWX1stu7ibxBRsLBvjv2uqampubbUPSQ1NTU1NTU1NV9nBEHABz/4QX7zN38TrV3njbWW//Af/gMvetGLWF9fv7YNfAYRhiGj0RhjDJ4uR3O2GsJSp/xIHSflgf5nVhNWt8qxfsaW+xTARZFnUen6qkRQv6J/P07K4rgI3HDImzqVJwzD6jrbxTa4fZJprfLcvBXJpSL52ttaQTNQaa3vskFDqXIbqpzOk+XCOK0jXthmkcRU1/uuIoptznk+WedyT5XWLVKOdFdSfSwm+1JkEvWexeJi5qs+6163y+FDT47rqqampmYedKPJ8ovvcg46k6CicVloswZvtJVziwkQ+D77XvCNe8bgFkkqosdLDrsKMaE4j/ELA9eMwe+vosf92Vq8gLXjd7B+9PkY5XHp5m/Cej5hdx+DpaMMVq7HeE0whrjRZdxZIWp2GXX3MewdIA6aJF5A3OySNNokjTbRwkHC7grGb2K1jwlamKBVvhFWMO4dYNzNx8f6o61M7VtHsd6r2xnLJRsSpccmZu/RX0nFveeo18nFmO/TLRcVnk5riWZJN1hIxW2N0BKNFqEjHj6Kjnjpc4GwohqsqEZOWH+C49JKZGtkJ9aylow5GW3xSLTJ6aTPOBO1vG0iHkvyzl0RwRddcoFXyVYRphSVXvVpFsXuq+ntFpt/RhSEyJrptIZoLgw22bb5+u0T0fsFh47z8pufd9XaA7C9vc2P/diPcffdd7O6ugrAsWPH+OAHP8gv//IvPyVllux4iIqGeNEQvZN4u8N3zyIk2ifRPsYL0OM+jY2ztNYed/+uPsbiyXvoXXiI3oWHWDr5RbrnHsQfrONFI/zx9mV9wvM8qVoR+kvHcvO21s/QvfBwTqw0VQMrHr8P+8n3zdWWZLC15zx6MSOAitA4fAOLDX9aA3tWRylxyR9JjA6H+IMNvPE2XjjAH/cR6wTvmfA/qTttMg7t9EguHkA971uRA9cj+46i7/hO/O/7WfD8qiZO2zbfkJe9KUaNT/exMFdOtLdmx61PBlBNBHkVj2luniMYriNJlKZ4JOmqshXbs3+7Y6atcQL5ZOAN0Oiv0V47ldtm3Ogy7h3ITfPCAV56Hyw582++Heku73ZYampqap4W1Nl3NTU1NTU1NTVfp/yTf/JP+Nt/+29z1113cebMGQDuuecejhw5wh/8wR/wqle96hq38OnL1tYWZ86eZzgcAkxrV1cR+DAqmCTixDmgJzW8ByPDo+ddp2oUw/4Fhc64m6vcQ54nxGE27tu1w1hch5DMhF1Xk7rcvsHI0m3N5hMRPA23HvPZHhq2hwYRodd2kexFMVYpwffyrmOoFueVCA3fMi70IyolrtPNzGp1T9qSNXgba9kaWAKPUu3zxECxC0spQYnNtdn3nIgeJ+WjMamPvhuuNrpzkwe+nTr2Z/tdrrvtKeeQn/7tuWMhYqciu4gQRpZhaNm/mFfCtRKaga08h/oj4fixFeI4QivN0tIivV73qkd91tTU1FwuzUPXc/Dlr2X9Y3+MCYeV8wgWHY9IMhHgyahPuLFWOf+uVNx3rC4IZda6OPBU4JYkorV+mrjZI252sQhx0MnMb/BHmyhARUMQRRK0pm/3999Af9/1GOVPheW4uYAkkXul88WtBecMTd2hlgoB7wlet0cLB2lm3NwC6GhIrGeR1FV1aDdsxGk7c7HqijuhTp3Ik5rSXeXRki6n4z4xlv26yXMay4xMzJfCS3goDuoWSoR9usnQxBzQ7rgpEXo4h/fkXqVEaBei0XcrTXK5OCF7xIYJMVia4rFfN2ip2ZODxQn9YSqpJzZhZBM64uLFPzI4veP6tSiMzXvODRax+QF2oU1yYvakLneWJ+vurXEjImMsnk2fQ9L3Yiw9NC00Y5NgsBixU1f9hE7QRF1F5/lnPvMZ/uE//Ic88MAD02l33303/+W//BdWVlau2nb2Qppt8BsQjfNvWJvWlpZSVLcBkqDjrgfpZ2yxBP01xLjv/sTpnQRtJBW1BZwT11R/H/fC6LRe8vrpHc8VZRLGi4ewnk/34iPT6cFwg+bmeUaLh5AkRlVElgPYL30U+23fi+jdJQG1R81vgOVv/ttYk2BGA3S7h4qGmIc/izXxtP3F3zjalNtVta8CiNLIG34RxkPs5iWkt4I6cnN5n9bPww77O1uh7Bm/Pg9uAFWaBiCCmMRdB3IDSACsq/2eitS59gK5ut+icrHtYi1iktm9zGYXdPsiO+yTMjE2DnMDu/zRFjoc5u5vYXuJxtb53LH3RptYpfPJIYsHUd/5g3Mdm5qampprTe3srqmpqampqan5OuaWW27h8ccf5/u+7/um00ajEa9+9at54xvfiKmqw/Y3nM3NLU48/OhU6Iaym9pamwqjdsdazP2hi9kGOLc+O85nVhO+8mjEYOyizgXLKDSlbSgRmv7MGZ0VXi15l7CIlNza4KLMNwd2Wpc7S7elOLzicWhZ026oypqW4MRYrVxfikw7/Koj1dsNIajoO9NpffMqB/qEwcgJzZMa4VnXkdrJ0V5wRTu3uBP0J85xkUmU/N4dXHEqWltgHMEodDXTR6GrXR6XjfloLVMnt9tWdmCBMI7gkbMxpy7NXBlFWg1Fuym0mq5jXinF4YPL3Hn7bVx/3VFuuvEGjh+/joWFXi1019TUPG3wWh3sHu6/ovsYQM8jApXqpEZpJLjDaD/v9nY3KeeY1s5Z2No8h8ISjDZR8Ziws4zNCDzecBMxSVrfNK2ZXWivFYWyydRNJ9i0JmxW1HQCFCWn+dWjytlexBZr3gLbBR/iuWTA50cXCFNXswBHvA63+YtoBA+hiaarfG7wexzzOtzRcK7ypvJ4frDCTf7C9F7niWJFN3PitRvw9dTdqyyuHvnIJoTWsGlCTkRbrCYzp7sS4YBu0S1EtvdtzAtuum3nWjOT5eeQqeeR0Ypn/hOrUO6YfG42/V+CRRBiDGMbE9qEbRtzJulzLhlwIRlyMt7mZLRFkvkuntm8gkEoFSRJwpvf/Ga+7du+bSp0dzod3v72t/Pf//t/f0qFbgDRHt6tL55NsBYVh+hwgI7G6GiEMhHZTzBpdEga7dwgFUGw2seq/Dlk/AbGKwxwkfnCrouoJGSw7zj9fcd3nMcoDyuKcXf/7LqQtnMSH97YurBz3PZoG0b96vcytK67NV8LqUBw8Dp0q4PXWSDYdxiFxfy3/winH5wrkn0u4hDOPoI6fBP6WS+pFLpdY3vTwUZPChnHvLvex1OnurLl2PXMglPn9WwKwMSt7l5CYXCECFYHuXve5aCScalN/jAfp2+1Vyr9of2AxZUV5MBxOHor8vJ/gPrBX0B6tau7pqbmmUHt7K6pqampqamp+TpHKcXv/M7v8LrXvY4f+IEfIAydhfQd73gHH/rQh/jYxz7Gddddd41b+fThzNmzc82XpDWYqwRQcGL0xsDia8tgbErvbQ0svZarzzwMnQO408y7hJQSmoGUYrUnZJ3GrYZCxDAclwX4MHb9VY09hroqJWnsp2uPtU4wn4yJyG4vikF8m+vgFhG6LSExluHYOZtnYnPJOJNjlHGxjyPnED+wOIsJNwaKSfJaCY3ARY9nXWQT1/ikQp+1lu0hNHxLM6iIDU8/x2L7rJ3V+xacGK7E5lz5rh3seB600kEIDR8OLStASMt95jh0YJEbjh+vdI/X1NTUPG25Aidoc2ERvdUnSaovnJLE+KNN4kYH4zVSByaEnRX80SYSh4wWDs6EqEw9VAskXkD74sPEQZvB0lGs0qg4xOq8SBU3e3jhEJU6DQXwx9skQXsqXlVejSc1fpN8NO1EOH+iLu4qVJx3pVpwbUxFfgCjNDLZTxGMKPZ7HTqmwcl4i76J2TQRm0SMRhf41uYhdPr5tZTHDV6XtWQ8vQc1RLv48sxn3BKPeBqK7kiwpfSVpxJPFMe8Dkls2TazeJkz8YCe8vFl9vCwrBtsx/kImpMbF+nHu9cxrnJpF6n6JmgkV4fcGouHlCLP96LokvVFoVI501qLyQzqm9Q/V7hBBxbL0M7O8cnQxi0b8Vi8xY3ewjRe/oly8uRJ3vCGN/CXf/mX02nf+I3fyLvf/W5uu+22J7z+KyV4yd/CnHsEs3oWFYfT7/yE6Z5rD254AfGFU+nUUmg1VnnYJMw9qyVeAx2OZuLwZLTlZTqJJ9ed0eJhWutnKmPXs9e+sL1Mc+PM9DqskxAPaK89vvNGlAcZh++OszVa9F7wrWzd8/Ed38tiv/SXsHlpz/VeNuvn9pxFGi04eis8ft8Oc0zuDzJnze3ikqR1xTPbtMnMcb1Tu3aclrq+s4OmrMFayTu+lZdzyVdvpHyeFduarq3wp0mTDWY07/gOvOd9y25bq6mpqXlaUzu7a2pqampqamr+hnD33Xdz6tQpnvOc50ynPfroo9x000284x3vuIYte+qx1rK5ucUjjz7Ggw+e4OTJxxkMBoxGY0aj8Z7LT1zQxqYO60wvhM28wEVcV3mmL24kxImZuq7HkWVty9Af5RXXrFhcxBTqMzYDxVJX0fSdAKvVzBFerHu9274pcc7mMM4LwFLYTzePLdXD1kpo+M4RXmz7TnHwVUJ4lLj2JInb1yQp17F2MeCqsvb1hDCexIJbtodmWp/cidwuQjyqiD6HckdVGMM4rXGeJJYodstXluzDRbIvdBTLXTWt8a3S45J9hWN33tVCd01NzTOJ4PBx4qDNuL1M1OiU3o8bnVztWCvCuS99CruTs9AYvNE2Yq37NxqjoyFgsUoTNhcZLB1Djwd0Lj5K98LDNDfPpw7yVChQmq0jz6G//0ai9hJxs0fY3VfeltKufRl3mwA6HOw+Ogtmgnd2ktvD3ZeronjzsBaJ8s48o3wGi0em0lsctFOHYTSNb0d5zoWehMSiiFIXe0t5dMTnXDJLrNkwIZfMOHfP6aqgJHgOi6JgGnlexdgmbJqQoYkx1tI3EZfiEZfiEVtJmHMRX20kdW4XWUvyInYgOld7HGAURSzuIf5VObAN+WcSA4QmmU7TCA3RNNKu19garLhYdC+Njd/rbBHARxGIdi8UDdF4KLceUfjK/Z1vGyQVay9OGdqEbesE1RuWD5Tmvxz+23/7b9x+++1ToVtE+Lmf+zk+/vGPX1OhG5wY2vy7/2/8F30HkkQ7PrRZEcLeConfJGm0SBptYr+ByTqcJ/Wfs9cIpVHW7H3d2IPRwsF0G4qwU3bAR40ug+Vj07+NKBA9++2hPZbueNk0/roSa7B/+bvYcXX5iSztm57H8re9muDQccRvoJod2je/gJWXfy9ebym/2gc+P8ceXgHtRexjX8P82TtI/uitmL/6v7Fbq7PtWkPyp2/fRehOSR/Ay8MX0vWQ+rBlVhV7Ukvb1dPOy+RP+Gl9UtM8u87i+VNxn3HL7n7lqJS6CwPT/OEmkmRc6Z1F9G137tXqmpqamqc1tbO7pqampqampuZvEPv37+fee+/lZ37mZ/jP//k/AxDHMW984xv5vd/7Pf7oj/4Iz/v6fkS01vLYY4+zvrExndYfDFhdW2ffvvmjFbV2wueUrO2mwFJPsd7Pd2BECTx6LmHfwqwTw+Iczp1m3t3rxHVb2bdRrIUnIvi+Ii4I0L43f7eMiKCVnbqawdUMb/jCOM73sUzmCQrDaD1Nrn63AM1ApvXPs/tnrXXu6EIfT39k8LWaHlJjXUqsUhZdGgFQ3r/0qBFm2jGO3MCCRkVN7iqq2mssVJQcTPtOy87sg0uqFPte1LTH43Ht6q6pqXlGMR4Nudg7yjiNuQbQ4z7dCyfwx32M8hgtHAARgsEmkkQYz9W/bm5dYLRwKB//ay3eYB3r+US65bTrJCHxfOdGTK+POhzQ3LqAF7mYan+0RXPrAlsHbiKZCO7zOs5FSPwmarw9m4SLEzZqr+jwOa7XGef1TjTXT2O9gHF3P4igw6FzmHsNotYCYmLEJox7+zHao7F9iai95FpgLVZwDvhJjWxrMBNnacpBr42Eq7lHlHPxgMPerC6vEkGjiDNh28XHDmstBudO1hPh3VoeijbYtDNh2UexqIKpqzqyhkESs6wbBPLkxA23lZerPe62u3e0fNsPeM7iQb548eT0uSGyNicWN0UTYxln1mdxgreys7rncerYbIuHl8YTe6IIjUHjBPlANDGGc3GfbRtPB0RWSd8WJ1pP6oNLGo9tsNPjD+6zUza/767kjS0NYLCpv3XClgm5vrPMTSsH9zxWVWxtbfHP//k/5//8P//P6bTrr7+ed73rXXz7t3/7Fa3zyUD8BvrSSVQ0nDpfjSh3DUoFRYlDwscfxHjBzP2ttBOV43BWQ5msE3cmfE+nwWW7uqNmj+Hi0enfRXHSIGwcfjZBfw0vHGBF4Q03sbmRqBbzx781qx9ehTXYe/4Se/4x1D/4WcTbPZchOHCM4MCxXecBoMKFfjWwH/t97Hgw+/uhz2M/8/+gXvXjyLNe4vbla5+qWDAdAjB1Ps9ilaa/ndL3nKjN7L4hlD8/kXQVO8nll4fLDSj+itt72K1l74GxcdAm9pvoeOyWtpbm1nl02GewcgNiE5ob59Lflhbp7cd/9Y8jfrDremtqamqe7tTO7pqampqampqav4H82q/9Gh/96EfpdrvTae9///s5fPgwX/7yl69hy558Lq2u5YTu3HuXVucWG5XIXv3XU/YvKI6slDt3NwdlpzJQWWN7x46rin4RX+f71idCtbWWMM5vMzFlZzZQckoHnutkbXiz9QvOlexqehfFXMlFhnverHMmTpg6o5PERYgXI8rBRaUPxhWdvxXGmZ0+C0Eq66pXmW92+jjnjfYMvOoOKBHB93b/6aW1roXumpqaZwxxFPHIQw8yDvPO2aTRYfPIcxm3Funvux6rNFZ5jFuLxH6DxG8RNnpEjS4qHOQFBRHizjJxs5fWwW1gGm1IY7mn2wjabB28hcRrzBa1hu7FR6pvEHtgtVeSL2Su+tvlWFhVEHxUOERFOyfG+IMN/NEWje1LNDfOocMBXiq863iMN9xERaNp66L20lQUn1AVdVyc5osqicyT1rvyJRZjDQZDIIq28mgpj4ZSufu7iNAVn0A0Wpy7uKE0x/0ezcz6IwyXzIjY5oXz9STcMeHlalC8ixYdz4m10+j2Cf21DZKtAZ4otAieKFpKE6TzeYjbT9E0MvsomX99NG3x6Io/dV5nHdlLusH1XpcDXotFHbBPN3leYx/HvV5mfVKZBGSwOREbmMaXZ9EVy85TE7wdNHj1s1+MdwU1jz/5yU9yxx135ITu17/+9dxzzz1PK6EbwHz8D+Crf5WLeFbWoKNR6ftu/GZeRBbBeL47mtYiJsnVWfYi55KepjvYyxNEjWg2Dj2LxvYFOhdO0L70KH5/NTePiLD8+JforJ6k0V+luX0Rr5BcgEmwJsEof+9P/uzD2Ps/cxmt3B059iS59zNC95Qkxvw//xW7tYr53Afddd8ks3/TAULZ6WIn9bMLn03291zhflQidfU/eVewCkqiu8LKbCBw8X0jmqi1hPGbxEE7vU6489Qf9+lceoTu+YfQ6bkjgH7J30btO/Kk7kZNTU3NU0EtdtfU1NTU1NTU/A3lZS97GefOneNbv3VWc+3SpUvcfvvtvPnNb76GLXtyuXQp33k06+R1om+VMLoT3hzO4IbvoraPH/S47ZjHQtvFhHsaui2pNH70R3YatT1BRFDKLTsRvgvGrdy8naZMI8SD1NUtIkSxpT+yDEYuMn04rnaMayW0GrMo8okLWkTwtND0nZjd8Ku6ZtPjo4V2Q/B1/lip1GQxiYGP4rz7OktYIfxXdfLuRpXOHCf5dUyOZxVqjl9NIpRqeWfZq7lLS0t7b6SmpqbmacLqxQskcSbiwhoam+dZOPM1eucfJGotpK8lotYiUWeZ0dJRwuYCxm86MclrOCE4K1DPO+hH6Vnk72SSSQgG1YPZ9qQUFlK48FsDST7So3f2PhpbF6Z/e+M+rY2z+IN1t4o4RJsYHY9RqQs9i99fo7lxZrppf7iOP9jINUXHYalppuDErKrPOpVjrEWsJUnjtW/wetzZ2M8djf0c97pE1hDjXMyxtazoFi3lXMm+KAywaUOSrEAoUooC90Vxo7eQP2RA3+Zv7qbgjr6aRNbgFc6fjvZz8elahOu8LsvKDZRYUU1a4nF7Yz/PDZan8ymgKYoGaurQFlwdcx+hJR5t5dNWPg3xaItOBwe4f5WUBbG+jemb/PE47LVZUQ32Yp5I8rkGzFU8i7zsumfT8vduQ649ScIv/dIv8bKXvYwTJ04A0Ov1eOc738nv/M7vPO2eaezWGvYzf1r5ngAqdgNSLEIStJ24rQsu1zTOWpIo9/1S0RgdZiLBjZ2K4JfRQlYe+zy9Cw/T2jxPe/0MfpwfJCPWoJPQxbDn3qj43JWaK93C3je/2G1Ngu1vYCMnktqT92E+/B7MnyuE708AAQAASURBVL8T86WPTqdfTabR4tNY8QxJjHn3L8HaGcQaN9fk33QWybyqN5D/HVD6guwoeF8lqn4bmEJ6hN8g0f4sql5p9xJd+nGRaJ/RwiFsWsLCar8Ug+6N+6VBWfahJymCvqampuYp5us7o7KmpqampqampmZX2u02f/VXf8Wv/uqv8q//9b/GGIO1ln/7b/8tf/iHf8iHPvShnPv764HxeNZ5FKeu4nxfgSHwdhcuJ/iei8XO1XCT/Pr8zHpWepqVnubMakxinOC92FVsDQqOHQsb24Z2U6bR37P1z+co10rotpyoqzP9Xb4WV2c73WTgyY77OhG8zS5K7UQwnkV45ztclRIaQX79SuX6chiFbrnsgdTaieWtoLptcQKeLsa9T9qUn7cZuH3OtRsII/D9fMRndh3NYDLNDRKId+ifTxJL4MNekbY7pdkGQcCBA0+sVmZNTU3NU8n25ub0v1U0ZvnkF/HCmQOvtXGWeK3N2vUvwvguYnvS8a6icUaMsKg4xPh7RYaXCVuLdDiZm6YrROU9saYUJqvHfazItF3eaAtv3CdqLpA0uzTXz9Dsr0F/DUkSolZ36sgOhk5wz8YQqzh0ccmZacZv5MuQACqJXP3tWeMqGuyWMqLdDTWJ03q9M2HDiMafuE8B31q+q3XEtWmHhwgRwUfQVhgyE/YtMLARPQly8ypLznE8qQ2eFbhHNmGxsJ0q4XYvNpMQi2VR7yzKKoEb/B7nkyHrSch+3cQXRYwFa6aO7sQallSDjniEGL40vsTIJrRE00TRUj5eOm+kErZNTJg6IwVoKz91W08OBgxIsFZy7naTxo9nnzEGNqZlvdy0Q16b1XD2bDqJUs8yGeSXKwFTOGurBgEWl4sxGGNpiEuTWQpa3Ln/+I7HtIpHHnmEN7zhDXzsYx+bTvuWb/kW3v3ud3PzzTdf1rqeKuz9n8k/eBYQa8EYwt7+mVBYNdLRxOh4NH3QFGvwh5uMewdIghaSxDS2LqKKjus9UJchjitrSIzZcySmFbW36J6mTlhrsFGIeAGiFOHFM4zPPoo1Bn/5AMHDX4SvfBSG26A9aHagnxlY9KW/nLv90/YBs/O37ISfvp/dT+vKBEznHWxelUjxCS69fO/SE1cDO92gmd4XJmkB1pC7D1jtY8hEr4OrP24k5zNXJi6dt8YLUNkRxcUfqoANr+C+WVNTU/M0pBa7a2pqampqampqeNOb3sSrX/1qvuM7voMLF5xL6TOf+QyHDx/mf/yP/8ErXvGKa9vAq4jneURRRJxYooq6y+BqcUti8fXuoreI0G7AIMy7o0VcpHWwg+u5FQjbI8tyV9PwBdWx9EcmJ6YGvhPTjYU5dPcd2+cXnvh9z9XZntTaLr5fxW4x3sW+Vff37rWnnTvc1QRPkllt8Gn/jZCrZW5Mvn74hDiBfSsLDIcDosyHWdy076WfUyES3ViIYyeae4WDPOkLmjjaPT3b5mxfLcPQst63LHeFld3LHmIsad3N2fotsLy8jOfVP81qamqeOWTFuMXTX80J3RO8cMDimXtZO37HbKIorPaQjEvaCU3JtG7u3KTu2ezV21xBFDOiiJsL6HCATiIkiVEmRg/WCZsLTtAa9wEIRpvojbO0Ns9NF2+vP86QIzkh2xv3iZvZiGqQJMZmapRnY9inTG6qxjjRQ2ksgvECJ8JZ917Y7GH9ZnozSWWQbLR5cRdFCABjDRE7C96QOrdtvnZ3giXJCMbg3M/FW3NTdMHNXRZg1WXKU9ZaPj48w+PxNq9oH+O2YCn/fhrzbdN27ldNuuLTVB46DQY3wDAJ2bKRE7+B2BruC9fZNHlh0reWNBAHXzRLSrFpI0apI30i9NuCJD2yMQ1U7vnHYEv7G9qEpszu+a05a5gXn6uqjmK2ZvnUCYrFS583onRgh7EJ17eW+NHnvhS/qo7MDrznPe/hH//jf8xmOthFKcUv/MIv8PM///NP7+eYqijsAnGjw3DpSEbIxg2SCIdORBSNN9pCGcNEnLXA1qFnEXWWpusZrFxPe/Uk7fXTT8aepG1LsNmw1ioBc54VHbyBra9+muGj92HDEaI9xA8wo9nxGj4MOhyyEIXuupLEeaH7Msl5qTPCrLVuUErWlW3TSPjp9UoEUHnB+6mmYlCJUR5gpzXd91wFkPsGFwR2sQasyh8f5YFN8hW+lcpF8Iu1qCR2A6sm88jO25mgDlw/V7trampqnu48jZ9Eampqampqampqnkqe//znc/r0ae6++27e9773AdDv9/mO7/gOfuqnforf+I3fuMYtvDqsLC9x9tz5HYXuCdZCbKprSWfRWug2IUqcKCviYrvVLhHn3ZYijBMaaV1s3xOWupo4MSTGObFz7h27u3i8F9nlXS1tJ9omZr71TtxC87ZhHlOEE7yhqjvOWAhjO41fd8fSYsxsbgHa7SY33XicM2fOcv7CxV2312o44X8UWjeYAXecJ/1IVcc4TiBQs/b6nhPGN/uW/tgyjmYO+cHYstJjT5zLKr/bG5tbtbO7pqbmGUWn22M8GuGNtqdO5iqCwTreaJu4OUuJsUqXIsHFzlNdOI8uCOwWCNvL1TPvhbj4YtVfRZtZ2/zRZskdWf7boqMxSdDKTCuLHoUAk2qnqTX4/TVU4uLLrShGAsP24lRMD/2GE4VS5/Y8ccUTFKCw7CUVeQjFx6QEWxLRi8QF+bstfk4Ut1i2TIgSydW/3onQJnxieJaTsXPN/8/BKQ7pNg3RrJoRibU0RRPZhAtmNBWkF1XAMTo00ihqDWjlMzQJcTqPJ4rnBsvcF66xnhG8t2yEZ2Xq7hYRuvjTdU+mKZt3qVtcrfIgc5SqzunitHjOMz+2xon3MgtcNpPa0KmFXyOIza/TtcsNVphMNVi+/ehtHGrno+d3YmNjg5/6qZ/iXe9613TajTfeyLve9S5e+tKXzrWOa4kcPF46yi4S2nODZqxl2DtIa/0MXjqwxWjffQ+z4qbNy5QCtDfOMLSGsLuSThQG+46joxGNQt3tq8YcpXyqyhvk0D6bsSF84Iuz1SYxNin/QEqCFpuHn83y41+67KaW2jXZ1hxCdqXTWgRs6Wp6Vaj8vqYDCaYtEIF0sIuk77vUDoFojDK7/8CcbiP3m6M4bCt1eJcGNMyxDyJIEqHi9JpmjRvAlcTTe9AkCh0RUBr1gpftveKampqaZwB1ze6ampqampqampopnufxR3/0R/z2b/82vj+zqb71rW/lWc96FufPn7+Grbs6HDiwH+0Fe88ITlydp0NJhMATmoFyTu09anl7WljplTt5tXL1sJ+IsF3EpgJCrj61CH7a3vnWMYspv5ztzoNWkotZn9Afmtw6lBI8zwnkngbPE8JwTBiGLC4WQ1Kr8bSrZR54ztFeSEYsYaxznmcREbSGYZiv7z6OYDi+3BqNjuFw5AZgRDsULq+pqal5mrGy/wCi1DS6ezfK81zBPW7i/s5crBvbbpDTZMpo4RDW2yNiYzcyseXTSRWzmapniElJDxGsKAzKOY21T+w3SbxG2XWuNOPOihNT0peXhDkxXayhtXme7oUThbaqXEz65aDnuj+X97yYVVMSD61lv27lnMrH/S5HvA6BqKkTOsZyKRkR7lC7eyMZ87nReT45PMtXRqs8HG6yqAL26SbLqsHHh2f4/PgCZ+IB55Mhj8XbnE4GOTF6w4R8LVpjKyNiKxH2qSY6sx9KhBv9suA7LLRNi+AXulCrzo0rObLryajsxK9Ye4KdDiaQzDzFbSopL20rBpP89cXH5mgtfPzjH+eOO+7ICd0/+IM/yBe+8IVnhNANwM13wOL+6Z9GaZKgjfEbLjXBb9BdfRR/uDmN/tdJ5NzdWaT6mDc3z+cctoBziT9ZFL/7FTFLVQNupngB0Tf9XcL+Ltdva2lsnmfx8S+z8shn6Z1/CHOF15wqJN1GfuIO36rSfFetGYV15xMyXNS4AqXzDmlxZ4kRTeK3pssYL9jzGiCZ/9+5Hbu117h7oUlK55wVIeiv0uiv4od994qG+XsKoEzi6naLwvvuN6CWD8237ZqampqnObXYXVNTU1NTU1NTU+IHf/AHeeSRR7jpppum0x544AGuv/563vve917Dlu1OHCdcWl3jwoWLbG9Xd+BorTl4YH/le+V5neB5OSLvvFQJvFLRQamk2lFtjCWK926XLfx7uey17zvp8vOK4yKuLniROIFxVF7e1SyfzX/y8bOcPXeuNN9u2/OKeoM40b0KU7ELnWa1QH92zdAfXb7gbYzh3Lnz3Pu1+9nc3Lrs5WtqamqeaoJGg+M33Yz4O9dQnmALIq8Oh2n0dvo+kOg9RAJrXG1Sm4AxNDfOEgw3nStThO2lo4wWn3iHvdU7i+UWcV4+a7AihM0e4+4+xu0lomaPUe8gg+XrGaxcz2jpCHGzhwlaWC9wdcurxO6Fg4wWDxemq9IxC4abeMPC/UHUk+BtnJBfc2IN5+PBVKC21pZqb4sICyrgNn+Jtnjc4i/SVQFKhP3aud4FCFAEotg2Ye45wVrL2XjAH28/wqdH5/nC+CKfGp+b1suebGNgY87E/ZxYLkhOxAbnJn8syj8LKhG6Kv8Zu1rj+eDLuKLWcfG2X3XstS22weTWZaxl1YzZSMZYaxmbhIvJCE8UXtHZWSGIGSZu7sLAg0JjitHpVc+R4woHb5Y4jvnFX/xFvv3bv51HHnkEgIWFBd797nfz27/923MPNHw6IEqh/l//DDqLqRO3UXqAFUBMnLs2TUTN/IxVA0Es/nAzNy1udK/o+7nXMhNn7mxCWehWJtpdD77juxnu9rhqLd3zD9K7cAJ/vI1KIrxwcFm1xeejSsjeO67/qjMdDOI+bxfAJE7ong5GKlxvM4OUstOsmidEt/pTtpkXuAFekkSZV5yW2UjKkenpb0gvCVEmyh/XisFRYi3end+Fvu3OOdpbU1NT88ygFrtrampqampqamoqOXr0KCdOnOAnf/Inp9PCMOT7vu/7eN3rXocxV7vD44lx/vwFvnrv13j88VOcPnOWh048wn33P8B4PC7Nu9DrVqwhzyTmGpzgaax9wqK3MZaNvuHSZsIj5xJGYZWYm29DsYNyFBo2+4b1vmV7aDBPgts6296K9MZCe+UJC96thqLdrBa8d8Nay9r6BltbOztTqjYfePluYj3pyyITTSluulblfRARDi9rivq4sbA10tx44400GnsLQFX78+hjJ4njPTL2a2pqap4GdLo9bnjJXbCL4G1FTWNUJyyf/DwHHvwr9CQu2G+C1ljllSWA1NEtGSnCG2/R3LownSUNv31iOzOLMMEixEGLsNkjCtrEXoNxe5nRwkFGi4cYLh5m4/CzCXv7iVoLRJ1lVzs1iWY38UlE7BxErcVy/e4KITsYrBXmuTIZaEz+eWZsEh6PtokyQlZDND0JULiI500TsW0jHou2CE1cErrBRY5fSoasmjHX6Q4jE/Op4Vk+NHicvxqeYT0ZE6BoKE1DNL5oBjaaPseICIe9Nn+/dzO9jCBtsGyYca7NBlhNRvnDUSEP923EqBArHFR0heqiEFQSk23u+AB4IjmBWiEkYqfitqsl7qLNI5vkBgj0bcz5ZMiD0fp0mq4Y8FiFmeNcn2c9N/b27fjeiRMnuOuuu/j3//7fT5/3X/ayl/HFL36RH/iBH5hj7U8/5MB1qDe+GXv8+Tt+d5zgXRYR51p/cbls9PUOWNxgnezAVCsaI7r6U1Ya01metkmuexb62753JobGUTl6vYq/fj+NE5/b0U0c9Ndobl/ao/VPnHmObGULr/T32A6fpQUXjT45rpOWFd3cxeWrxP95r8tpjfLJy2JLArpKI92nv0+UxmbOjZ22JNaWym2QOc+mTXjwC/O1taampuYZQi1219TU1NTU1NTU7Mrb3vY2PvCBD9BqzWpR/v7v/z7Hjh3jgQceuIYtc1hrOXPmLGfOniuJkqPRmBMnHikJ89pTeN7uj8KqIiHwiTqoRODipmFt25IYOL+eVMZkq11K0SkR4jRePTGw1TeYKvtxBfO231pLnFhiA4kpv1ekSvCe9dfM1+nTaSr2LSi6LRc1vthRdFu7f0bGlj+nfFvz/05QyrnJtXJvzuqZpyK3QMN3Ue9VywM0A+H4Ac2+nqLdcG0+tKS45WiTxYUuvTkGVFTukzGsrq1f0bI1NTU1TzXK9+m86K4d3w/bS/jjPq3100gcsvj4l2huX8KLhqw89nlirzGLBRfBFus4V9xDkqBdigTX4fDKdiAO8ftrNLbO09w6jzfaJGwvOAG60SFuLRB1VpwzexJV6zeJOstEjc6smYA/3i7VEZ+XqFmI0q5yj1bV+N6LjIgPbuDe6WTIqbhPbN2AuTNxnw0T8nC4masLrUVoi8daMsZYw4IK6CqfdRMSWcPYxozS11oy4kS0wblkyIVkyKPJNmeTAQPrhOYIw0Uz4sFoIycaG2Bgo9yzRVv5fFMz79I3kIspBxc1nhTrp1fIP8Wa2EV5yljLIMmXERnZmEFGJB/ZhAg7E+YBH0VLefipj7qRdrEmOME7OyAgxhIVthzapDRooOTI3kMO3KnSvcXVXW+gaIqmkbrpJ3iieMWR28rLWcs73/lO7rjjDj75yU8CLhHpl37pl/jwhz/MjTfeuGt7nu6I38CO9/iOXqF72RQcvY3+7mLxxKFtlTcVMK3S7sFWVZcpkL/1w/g//h/xf/iX8H/sV/D+7j+Bhz6Hssa9MHMJyACNC4/QufRo5XvNraembJWLCc+3OPYauchwq30Sv8F06MATFbornfnsrBzPgzFT1zV71OyebdPmhGxlTe4av2NzlKp+tzgwt2rQRnHfi2khNTU1Nc9warG7pqampqampqZmT175yldy9uxZ7rxzFnV29uxZnvOc5/Drv/7r16xd/X6fr933AOcvXNxxnjCKWF/fmP5treXEiUfRYioH34tAw3cR5kWeaJq5iNBrzTYaxvDYhYS1bUOcOKeVMU7EnsXY5fE9F7s9aUuUwOqWYWtgKoXo8j7s7FBPjCWMLVEyi++25Pd74taucjsrNXsV48bnwYnQinZTEfi7L2usJU7m75sq7nJioT+yjCrKZLt9zu+jc7nnV+J7wr4FxXX7Ncf2aRY7itFoSJIkdDsdrpTRaLT3TDU1NTVPE5q3vJDut70G6S1PpyXaZ9TdT9x0A3+UiVk89RV6Fx+ezuNFQ5rbhft3hfusajRVUQiyosAkNLYu0lo/TbB10dU13QvtO1d2+qeyhmC4mRet0wjbInGjW2qHl7rVLxdbNcKuuL2gVZhnD2GrsI7EWk6ZMVEqvJ6J+zwSbTKyCW3x8EVxKR7ySLTJX/RP8kdbJ/hg/3G2TMgR3WG/brFPt1jWTYpj8lrK46jXyXUyeqJYUPn65iGGs3FebLSUBemb/YVSrHdRLAYqHeZZFNAsDKDYMOOcSH4hGdInnk5LrGFoE84lQ7ZMSGgT1tPa3xYQ69zhk2echiia6NwzT1W7ilO0FKXt+Z9pDM4lbtJt2YJbX4ugJpE1uGe0QDQt8fCV5kef81IOtfMDLNbX1/n+7/9+/tE/+kdsbTkR7Oabb+bjH/84P//zP4/nzRPP/AxAX8F+FJ95k9glOUzfN3QvPERr/fT0/dbaqfw2M9cKSxp3PU2CUJm/018AokpnvH3gs4hSSG8FaXWxf/YOOHXlA4+bm+fy+5Gi4rBi7idO8beNgLtOp8c30T5Js8e4vYwR5V7ad8fCC7CpC/opiTafNnriwJ4MGpq9BIsKh3jxCJ2E6Hlc9ezmyDZzDbYo3S+uEFk5vPdMNTU1Nc8garG7pqampqampqZmLhYWFvjsZz/Lv/t3/27aoWeM4X/9X/9XXv7ylz/lAt14PObEw48Shrt3yFhrc3WQt7a2GY1GruPPc+KxVk7cDjwndDuxduf1zUvVvCs9hZ/pd00MXNo0rG4ZEpOvEV0VA14UzCeMI1tyYUO5Q2XSRVMVf161z9aW61bPjGJP1Ot+ebiBAK5WeZQaJ3ZqQVXTotiy2Tesbiasbrrj7Y55haiQlNfh/rZpje+dkwrHYcjJx09VvzkHumqkRU1NTc3TmMb1t2GOP5/+8jH6y8cYLR0habRz88TNcg3bRjEqd55BUiZBRSEqGqHHffS4T6N/ieXHvkhn9TFaG2fprj7G0uNfwh+s774uEeLmghNUMnij7QrRoSy6J34zN0klUfUNaA+kUD858RpE7cVZvLEo4mbPiVDpTVh2KydT0YZ1E6KU4qjucNzrctBrs6IbHNBNFnXAog7wRDG0MVsmIsaybSMejDb55Ohcrva0FoVf6FIMRLOo8nHsrhZ1fr61QiQ5UHJoa1EEBZG6eGYopLTuoudxn27hZUTGgYlZNyFDmxBbw0YScn+4DjjBPbQJw4yD/GIy5kI8yp23hnxqjUyE5QLFfSy6sG1aJ1gAndYcN5iJdD3932TfFeJi5XE1xYux7knlNvNoEf7Odc/nzv3X56Z/5CMf4UUvehHvfe97p9N++Id/mC984Qt88zd/c2nfnsmom293322TgDHV39fsQBlrIIlm06zBi4auhnU0BmvR0QhlDe21U7QvPcri6a/iRZnfRa/9ZySNNrHfIvZbzqlcHEBTNfJBezmXM4NZXXC7dg5736ev6BhMN2EtfoW71xQH1lwFnIvbfUNLgrc1JDogbqSpSEoTtRZciYusI1vpqyp0WwQjytVxn9bqznxvTIJYM40Fn5Y6yryKBSekykF9GZTix68WaUmQ7Pkut7/8ydlWTU1NzTWiFrtrampqampqamoui1/8xV/kr//6r1lenjm4PvKRj3Do0CE+9alPPWXtuHDx0q51w03qUg5jOH9pgy9/9QEura6zvT1zXYkIWrm46sATtJ65kXfqppgzMZw4sVzYSEodj54WrtuvWWzLtOazt4O26WsnvBfRWkr1ooEdaoAL47DsSrYVO6IKceSTRYy9or77ubgcwTwxToTONv1ySscrgWHonOvZabriYFaJ/JPpu/VhNZtN1tfWSZIriJtNWV5euuJla2pqaq4VJhq7WtVqh5ua0hTvrrY4r7VYa6bOSUkiF8dqJ7KggPLYOvIskqA9FRy8cIhKwtxNQVlD98LDe0ecixAHeWFesE7I2gNbuCFc6a0y7O1nsHhk6hcM24uEnRVGi4dIRNFfud4JPdZMj4mKx/iDNfzBekksz++ME19WVMBhadAQhRZFQzRLuklPB5lZhf26xW3+Ym4Va2bMI9FmblqVMzlba3uCXxD1TOpIzjWx8PfQuHj0LM8PVujKbP03+wvc3txHJzNNIwQoFNAVn+OeE8+stWwkISfjmbC3bSK+ML6Qc2EnFc8kxRrZ89TMnuAhNMWjKdqJ8yI0RNEQRaCc872hnNvaV5quCmhL2Xnszgub+7uqHVUtK4rsX7o0G4wXRRE/93M/xyte8Qoee+wxAJaWlnjve9/LO97xDnq93tz7+kzArp/HPvBZVBKjTIIyqUN7KmS7QSQqDt13ylpXBxtQJkHiaDoQxgIqHqFHW4iJU/E8obV+plTOwP7f/zvE0TSiHKWx2isI3tPKzPllVaZG88qR2fSHv8SVX3Fm9F74rbRvfgHtdpvuwiIr3/y3aLzklU94vRNm4nE2RrwY15/eC7Lx5ap4fNy0K2/IdKQuFkjEc25x7WN0kNbDztTMTtuZO8JpyseTOtR3npXPM9LXmtngKFysubIGrLufyh3fibrtG55wc2tqamqeTnydZNDU1NTU1NTU1NQ8ldx5552cPXuW17zmNfz5n/85AJubm3zrt34rb3rTm/iVX/mVJ70Nk4jFKhLjIq6zDIYjHnr4JMuL1bWUiyKmiKCwOwielr0iule3DIMxnFs3rPQUwbT+syWxLgL74JIT2CeCr2TiyZXMhG7nxM60DVdTelgQt0ehJfDtdFsTYgOnzib02oKnxDmcB5ZbjrjtZ/FU6mou7jPlLrg4Bs/b+1jsxHBsGEew2JmvtrdS5VTanQYKVC8vNHxhHM32brGr8HTq8C70vkeRpREUhAy7++d/4MABTp85l5n/8o7Pysoy7dbVd9TU1NTUPNn4nQVGl87lplkRokYPqxTeeJtxdx/bB25m3FlBrHGO6uwNWAS0DzYfB+uCNWbzWe2zeeg2lk59GZ1G7rpI3Bgr/nQ+wdLYOs9g3w27tr3o7Abmi6MtOrL91hW7+uLWAkNATIzxGlilMc0e40YPvEZun4KtC7Q2z07vyxZh3F1htHC4ujYr6QA/LFiIM+8HommIYZxxNO/XTR6Nda5O9mPRNrcGS7l1KiQnFlf7LguD/pCS80aQ3P3yZLzFPt1kLRkTY7nO6/CNrUNENuEjgzP4Ijy/sYIniluDBb4WrhFbM12+jcdz/CVUKpaJSElk90SxqIJpRLlrx16tr0YBPRXQUT4aIbRJyQFurYsej9NWaIQFHTAyCds2mrYzEI0xtlSjvKpdxWcMw96upkHsBnE88MAD/MN/+A/5zGc+M33v5S9/Oe985zs5fvz4HHv9zMKGI+I/eAtsreamT6K0J4KsTEXRMeB+C0zcttZOrguz79hk/t2+9WISlHHnhJ3EqIs4gTfZO5bbinIDXW5/RXbqPLu9OyLImYdoP/wlGKQln77459jLGUm61yZw16fiNan4u0IlIQmZ59/JdaziOlxyhl9Bm5SN3XP/ZMCVCO7ymPksq6Zl9mr3jVS3/bKZnI+567p1wnzVeTf5TQlO8E5CrChU+gNKAJ79EvQrXv/E21ZTU1PzNKN2dtfU1NTU1NTU1FwRQRDwgQ98gLe97W3T2GVrLf/xP/5HXvjCF7K6urrHGp4crC0L3Vk2tuavp+miKdP+BdLOkTl6VZLEMhi7zoZRaDl9KeHsWszW0LAxsAxDS68tdFuKViC0G+5flenHyJZjkzQ2e/ISgWajOmp9s2/oD/Pxlp2GYAysbVkubBjW+5bDy7okdE/22dPlzqNiv5dJI9fj+MrizI11gvsotKxvG6J473WoQl+Zp3YWyXfSGnotwUuPrach8CTdZ8H3YBQZLm4knLwQc24jqeyncu7y/BtRbPGbSywuLjLpAHM12PfcrUybhSOHD82/QE1NTc3TCLVyiOHiYfr7bqC/cj2DxSNs7b+Z0dIRxguH6B+4hfPPuovh4mGsF7iIWqWdKzJ7TRVF4jUqBI3CBVlpRr2DuUlV8/mj7T3bXlEpHLtXSYlUPDCp29CKEDfncMIag8Shc5QW7iVxs0fUXCAJ2hi/ifFb4DfdQ8HUcagIe/sZLs5cnoKluX2J5ua54tZKKMpxLaXIcBEWC/W29xJfoVx7G+CAbuUizyMs90XrjNLjp9wOEOGeXc7HA+4L1/BEsU83ea6/zPd03GAFXzR3tY9wV+voNJ5ci+KgbuWeB2IsA/Lt7VS4Qr1ilHSGbFSxL4qWaNqiaUnFeSHuWcIXhRKhqTzaysPPPE2JCJ6o0oCAptKlSPhGxTaqXduXz2LQ4u1vfzsvfvGLp0K353m8+c1v5oMf/ODXpdANYO79JGxeyjl8MS5FQiUxKg5R0di5tZMxXuxeKonTGGvrvjtSqGNT5QCuQEjLHOQmSjndokq+FZC7XoccuXk26Ybn77q9SUrE7jNZ+MrHZkI3XF5k0twUjs4uA4LEJGmqR5z+2HCOeold0ocRNUsQURp7hU5rAVTp3lPhrq9qq+z9eV85NpNm4mLNlU1m0yYDXIrn4Q6ItVOhe8qjX30yGl5TU1NzzanF7pqampqampqamifET/7kT/LQQw9x7Nix6bQvf/nLHDt2jPe9731P2nZ3ilbcU3e15Ujv7LK28P6kFqNS7mUthLGLSa9iHFq2R+X3xqETRK2FXlNK0dmSdpRqJbvWg560UythqaPwC323flp3PLuLSgn7F2eP/g0fFjqFaMB0v7Ou+GwTLORqgk/6woyFMGIusTqLi1ZP/ztydcu3h7MNDMamdIxFxEW7i2uvuoJfM0oJyz1FryU0g/JnoETYGLj659ft93bcxoV1w6e/Nuarj0Z88UTIR7405ssPu9jKbselBxgzOW47n3NZrLVs7pJYUFNTU/N05dKF85w6dZokaLvYXe1jgpaTgApCtlVeSciWYme8SCmy1jnVCgONWgvlxhQut6XauBXrsRaSTJy3UdpF2xbaNKk5izV44z4igtUeiddg3N2P2ISgv4o/2Cg/kFiLCof4o038cIA/7uMPN/Nx6SKgvQoxrUzY3UfU6OSmNfqr5QiUAkK5zmw5kLxMUSy21rJlotzgr5Z43OD18NL1LamAW4MlXtI8SENmccxDm/BgtIG15OpuryYjPjE6O3VgKxGO+O2cKB2ILg106xaEeSBXYxxmp8W2ibgQD1lLRvTjiMQaovQVY1GAJ4JOX+mJl5Z6qa7PDbBpQrZNXsz0KqLei3XGoSxui8j0GD4R3LPdbFDicHObt/30L/CjP/qj9Ptu8Odtt93GJz7xCf71v/7X08GrX2/Y4Rb203+CmNhFl6cvZRME68oWWIMi77J2169kTkF0HuHRwBXUZJZbXoz6xlflp+07Cre8eMdlrNIYv4HR3pMozF4hVc/E1uIPNgiGGwSjLYLRJjoeucEG6WfkBN7C1esJRIsLVNbILq9r78+2lIglQlKRGLJnm0Tc/lrjhP+0fZNzUayZDgKYRLKnC86fKjLcwsbR3vPV1NTUPMOoY8xrampqampqamqeMDfccAOPPfYYP/RDP8S73/1uAEajEa997Wv5oR/6Id7xjnegrkSZzGCMZWNzizhOaDUbjEbjyojovTo7JhrzLDpcpn9bl+7pDFQ7LB+nfSJRAtra6foSA+PIEu0ghFsgiqHbqq7DnUXS2LyqRkzaCK5292JHEycGY/LR55N9muzfSk+jlHBpM6HXKn8WE6f2bpi0z2/SvOLylxPZnVT09YWRhZb7dzCyjENLr63wdHafYDB2jvADi9Xu9gk7JQiKCO1m9YKdphPUXbx5Ji7QwnrfEEaWc2uGi5tuB9b7M1Hh7IVt1jZHWOtqtU82bS0k1nVUVbnpjbFsD53jf3t8gZtvUBw+sHDF8fA1NTU1TyVRFHLu9KnK96YRwTrT/TQRjTMig5AOCsrVbNVgdqlFzQ5ChZRvn3rcJ5kIw9am256I14D2iDrL2NEmOhoTtZbKwsHEDYpFD7fS+qezm0z74qO0ts5Pt53ogP7+Gxj3Dkz32/hNdy+YRq9bvGhILGC8xq77WkXYXsYfzxJrxBq8cDCHw3wWgStUC8Nt8VGMprWhb/Tz69y2ERsmpI+wTzenruWO8rnBX2DDjDmi3TFvKY/b/EW+FM5SfyIM62bMYW9WL72nA1qiGWZc5BeSIc9iede9mdxxm6JpijfdnwfCdc7FAwwWXxRnogFbNsotV3qeATcwIfP5j2ySOrx3F4M3TUhHvNz920OIMlsREcTmn6NURSrynmM301h2sbNn2cgmxNbVBZfUfTrZw9Of/TJ/+v/9TbYvzD6DH/3RH+Utb3kL3W51iZ+vB2w0xvy3X0Uy8eWX83QlgLUGsp/9LvHaT8aTm/qGv1U9/dU/jvnT/x888NlcG6zS08FCVnnIC+6CcAj3fvJJaF0ZC06Anlxfp4JtFsnFg+skmi43K9mQnr+W2fV4p7hxdnjo37OxFa7z0nrKA5eq3s1+/lHQcekc4wF+OH+q2Gzdxf0jjdDfw68/OU67HYv2AuJdvhBfU1NT83SnFrtrampqampqamquCkop3vWud/G//C//C69//esZj51T6Z3vfCcf/vCH+ehHP8oNN9ww9/pcBLRBa82l1Q0efuw0UeQ6vbUCXzvxVau8wLpbB0AxBhuc67a87eoVTQTx2bIQGcsozM+nlODpcpz6MLQsdubrBrNpO+bRO7WSHePVswL0Ukex2JbKhEJRUEj8xPfcPmaFacvOppTEzF9DW1eMfQhj5xAfhWa6vvVtg69BlGANjDL1tsMYmmUzV46qPp/sMS0K9CLCsf1lh5UInDgTs9HfufNoHBn+4mP38tzjfuV5aCu2N44sZy4l02O8PRxw7tLDrCx1eOlLbsa/nKLkNTU1NdeA9T3LltjSDc2mgl9pvl3u4rZiDgvEfhMvGgEQNXtsHn4WnUuPEQw3sICOx/TOP8hg5ThhewmsSQWsdI3Z+OtGjzho4w+38EdbiDUkfouw2cPqWQC19ZvYaITKiLJxa5E4GuKPXEKHTkJ65x7AiiLs7nMziZD4rTQaeXYz1dHYOckvc5BTyX0+D9aiTORcx+n2PCyCZjOtwN0UzQub+ziWdPjE8CyHvDbHvV66uGXThKwa95wXY9k2EQcyUeIN0RzRnZxgvD+NM48ylbM3TMhhZmI3QFO8nNg9YWhiQpvgiaJdEJQFuNVfpK1mAs7IxM5tPRG3LbSUJjSz+uQyk9NyOBG5cL+2Zk+x29Xktvn48jnq+xZLoxhbbpNr12SAwkzItlg8qzDpflgsY5sQ4NpqophP/B/v5bO/8z+mD0PthR6v/zf/gh/+gR+k3elUbOnrB3vvJ+BS9WCcy1hLxUN54XOdo0bzbHhJZrGdHsrT64O6/RWoo7dWrk/8Bvrv/hPiP34b9sTnAXECc3Eg8MVTyBMcdDzBpOUj4lYPrCXor9LYXp0GuTvBOo1nn7ZDOReycYNGZg/nedG6amDB7BtaSLsoHeu9v2eVVAxqyt9jhM2jz6W1eZ7G9qXMMuLaOtl2ZvB03Gi7wUvGkARNVBKiixH2xe0X9qfqTiA7zDudNuf9Q15411zz1dTU1DzTqMXumpqampqampqaq8prX/taTp8+zV133cVXv+pqgp08eZJbb72V3/zN3+QnfuIndl0+iiLOnjvP+voGxhhENP1R3tk1qbksOIe1iJ12cVi7c3fHvH3IO8220zqLfS6ehuWu4uKmKfVHRHMItBOMdXWH9mq36/ywJUFXRFKXeb7Dtqq/S4lgZLaOyfKeBiUu1tukx1Zp1wdXHCeQJG7evZzr4KLUq/qq1rYMxRTNKIEkKh99uQwPTdUxnLivi2+1GqrU8QxwaFmz0d/dZXj8oGu8KKCi/zK7PWstZ1eTSpf76nqfL371cV5y+/wDRGpqamquBXG0exxq5T250sVaEIEmNa2nF3BxNVpTsRprSYI2m0eeQ/fCCXQ0YuvgLVjts33gZnrn7scLhxjtY7yAxuY5wkYHlIfNigaFyHAVJwTDDbxwCIAXDgn6awwXD5E0UmFWKZKgBeFwVg9VhOHCIXQ4mE4ToL32+EzsTudLvGAq0INzZIs12D3E1CIqyY+2c9G5jV2FDzExQRJhRTlBRgRBaIugLAwE2uK6C1d0k5e3j9IRf/ocISIMbf5eOLBx6X5qsLl4dCVCQzRRxYi5LRMyNDEN0fTTaPTJXImx3DteTWV4RyCKY16XTiput1TZpdhUHi9uHODTo7Osm3Da9gXlczGZrU0QFLZ0y67aH1NwfFex11OJQuiIx3bmGE4i3vvptNgaPHHPInGhZVm39tRFWpjH4ATz/mNnef+//985d//D0/ee+40v5o2/+LMsH9zPfeceZzAa8t233v6EE5iertj7P7v3THtQ/bui7Pbd67M3np//XpqkXO176mBWqJe8Cv1t/68922cHG6WyD7n3184i1z/3CceZR40Om0eeg83Ec4fdfQyX+iyevtdFxEMaaRS7RI+sI1upfE3wih8C04FIT0G60WQA1fR6aadTpu8P9l1P0uiyfcClH0wFb0gHJaTzp/tlxZW88ocbLv1jsh2RK3dkX8nx2GnwxZFbkG/6O5e3rpqamppnCLXYXVNTU1NTU1NT84QYj8f0BwOUKHq9LlprVlZW+MpXvsKb3vQm/tN/+k9ulHsc85M/+ZP8/u//Pn/yJ3+C53lYa9ne7rO6tkYcx/i+z9bWNnE86wAcjsviYrbfZGK2mPyc91JDQxSXO6aqOk+KHViuL6a6Q6EqqltE8D1LmOnrD3w3/cCiYnvoIrct0PCF4DJT44zFud/mSKXLMuuUJlevESBOLFpTqhuu1SzOPPuWq1deaJeymAp9I4pBa5vWHa8+jk5kFhbalJzSxoKYcp9Osc+m3RAaQXXH7Dyd0dmYcTOJck2XGUeWOLF0ClHnR/dpzqwmbA2qPwStoNN0bVJSPLPSbRmQNI1gMC67/7M8fmadFzz7KM1GHTVYU1Pz9CUIdh/BVXXF9MbbWO1P483FGFQyJPEabkSVMaipE045AWHqFFTOIWhNGusqbO+/CSsKf7RFsPo4AInXZNTdT9RZyQsJBXG7iPEb9Pcdp3vxUXQqSAuW1uY5tvfdMBsxJoLxAlQqirtpiqi5QGOwNp3kj/uoaIzxZzHllXXESweu0FZrkDjE+s3ppPbqSXQ0JPFbIELUXESbCBObqZCdXZ+Y2A0iIBXYTZwTrpqiUKJmgwGorofdEj/nvrY4V3NV7e/J/damDvALyXBa23qoW5yPB1ORF8gJ3QAXzIhL4YjrvC6tVNALreGRaJNb/EWau4h8SoSb/EU+P76Qm9YsRKVXua+vRBj0kFx9cYDnB8usmZBHYuf4X9YNespnIwk5k7h4YxGhJR4YWEvGJFiWVQPBxbgnhdYowGfmzLfWOcon81lr+eIf/wWf+I3fJh47oV95mrt+4gf4zh/4+ywHs0j6kxuX+NK5x3jRkRuvYI+fAcTh3vPsQXmwjmVWCkF2mmuGKOyRW7DDbQiHyL5j6Ntfjvncn8O5RzLzFRzZ6+fma2CrOoZ+2qJmF267E+771Hzr22FdW4eflbteTEgaHbb338jC+Qen01xpikL8e+Uw1arn5fkHs06XEAEr5BzmKJw3u3qoghWdxv1b8AI4fDPmzAl3PQvajBcO5EpC9Feux++vTUVst6J0UPFkb6zFH29TjGOnENv+hJgjRQCAxQOwchjWzkGrizzv25Dnv6yOMK+pqfm6pRa7a2pqampqampqrogkSXjs5ONsbm5NpymlOHhwP4cOHgTgV3/1V/ne7/1eXvWqV7G15eb7wAc+wMGDB/ngBz/Iyr79rK9v7LgNa21lHels/68WVw8ZUtdxqtL6nls2jJwrOUln6rULXSwTwXyyDxW9EIORc2gnBhpBeQZX29kSRWm970ksqBaWui5ifFL/2Rh7WbWtYeI62H2eSdR2MWq9iLGWYegc2O1mXvAWERC7Y0x5FpWK/HGS729Ril2F7iyBLyz3YDS2hLH7LAJPELGMC0J6sSuxWHPbGEsUu888ii3NQBH4O4vtpWnA2lZCf+TOl30LZSFCK+HOWwMeOh1z+lJSOjeNde1QStyAgYKBZUJiYHuQMNrdDImxlq3tUS1219TUPK1ZXFnh/NkzlddWYBaBkqLikObmeRDFaPEQRvtOhAV0NMLoAB2PJwtjrcGqTMT3ZH3JzD2NtXjjbVrrZ9AZt3MwWGcraJEE7dmy8yCKUXcfnbVZ/PFExIhaC9NpVntlB7BXJf4X3IvFGtkiJQHcG25gdTB1k/sjF60eNTpE7WVa66emorq1MFo64mLaAWUSbEHIBpAkzrVVkvI8ylqSOd3LPgotQmwNukLGKbq4bwsWOTXYnjrDH463UMA+3cKX2WAxsS4efYIBzsQDbvJ7M4EXuJiMuE7tXm/6gG6VpmmRy1azPQRfVE547uARYQhTeX6xMDDgeq9LRwd0dIAAmzakp3x8FPt1k751LvajXoeWeAxtzFoy5pZgkW7qVu+biM+PLvDlTL1zA7m4dBHBRxBr2F7f5CO/+n/wyEf/ejr/yg3HeM0v/gsOPesmtokZ24RGRoS89/ypr1uxW47cjD394N4z7rYOwNoEUEwixtNMJff3vqPIhZM7r6C3jH79z+IVvlfmI/9t12uSvXR6vvbdeifRqRNYpREsEofuzJgMzAlHxH/xTpcWNdcaCxw8TvRNfxdz784u+bC7grnkZwYpueucpVDrfK648UIriyUnKmpmJ14AotDRCDFJKjan8ek2KZW/sOLSOcLOMlZ56KBBdPTZhDpfViG3He2zdvwOFs494MpVWFMppLvzxeDOl8x9y7K34D2vkF1sG+XPVr36J5AjN1/2umpqamqeqXx9ZtTU1NTU1NTU1NQ8qRhjePChEzmhezL97NnzXLg4i3h76Utfyvnz57nrrll9sLW1Nb7hG76BX/mVX7my7Wf6AESc4C0UzVoyFXJHoRNlO63qx1+pWD7LROhuBkLgVQviWrk+paoUSGMnIvTEcZP/+2oiIjln+kQEn5CWPcdY2B5a+iNDFDsncxjZiXYwVz+LUkKQutV9j/RfyTmNqshHvgvdtmKlp1juKjpNod2UUk3vibbhKWgEZVe6iKvhHSew3recWU2Ik/L248RFhw/G5fcmNcq7TaG3y7lyeFnx3OPlqFlr4dy6ST9f12GvVSaSEVe3/dTFhFOXDOvbe48q8P26ZndNTc3TG8/zOXr98cr3Ju4594dFjfu01k5BKu4GWxchiUAURmkn1iQRRnsYr4HxG9iiQxlcnLnfYNq9L0LSaNPffyMm4/RVJqZ7/sQViQdxs1eSMdQcLlFJ8ok0ifaxhe631top9Gh7No/XzO2jDgfoJPr/s/fe8bYkdfnuU9VhpZ1PDhOZBMMgIILkpCJmDHjBAIiggHIVUfCnGJCfVxRMYCYoKuaIgpIRFJCcJ5+cz84rdqi6f1R3r05rh3POMDNMPXw2c3avDtVhd/eqt973ixv0cIZd3MEablIL3Bv1mDpzK9Nn7xjPHw0JG1PFQQWldmR1dPOT0nicbSKBfU6bg94U+9wOB92pSqJK3Vr3uR2+beoqmjmhVWHczMWmiopLPEQVHOBg4s8vhLgilpV+16budV6sn5UNOtLLROKmcHCkpCldGjjMywbt5HMfyUF3it3uWDjb73Y4mByrg575eURzD49s7eVyb5pdbovLvWm+qrkzE7oBOtLjMe39PLSxq7gPaOLSYIITH/scf/+clxeE7gd8+5P5wTe+mj3XXZVN65aieXrBkEhtEDVzL0Z81ROhxo287fWAcXOrKBM4BSDm9yJvfPTGC68twulD1enNCfXSkxdJ0ZwsvKZEJ+9g8In3EDc6KK9J7LWIWrNEfnt8VccRSjgmAeJCWDpNPBptPI+QxLnUCWCCpr3x/SaLFU//RrXOUijQquKk1oByPPNMEILYa6KFgxbSPH+kNL+XttPbcTmrB25kMH+A4eweeq05gjMbDFhIkQ7re641z5kN7p3pIKzixEvi665FC1kcMLX/Git0WyyW+xzW2W2xWCwWi8Vi2RZnzp7j7NmzSS3oes6ePcfOHQuZ6BnGmr/7h3/lT/74D/jFX/h5lFJorfmD3/893v++9/HGN72ZdrvaoSOEQIqiu1sKaoVQZ0L/QcMT9IaaZkNk7uo697PcwI3se4JhoPHcNLY8cRLHxjFuHL0k665vR1rvOmU83/Zc3lsldRhDul86E+3zRLHp7HZLBzAV5LfStrKgDua4hLGmWeOE33hdJiFgtqPpDTWjcNyh2GwI2g1RGzMvhMBzNP3EJQ5w9GzMTNuI5wLojzRrfY1S4DqaVqO4nnZDsOpoptvFC0xrTXegUWq8bkdK2g1VEc3vOBmxc0YWjr3jwPKq4uxKXLg+YgXuBsd4eqrJ3MzmHZ0Wi8VydzM7v0Cj2eTYkSMEoyEgTI1SreksHqGxfg6EJGhOE0ztMPWuUwebEEYQT++FJUF2okAgJMrNu8CN03o0tYPW2jj+14lGeIM1wvbs9naqZrvlurgijk2Ues5t3F84AAKaSW3XqDFFc/0MYXuOqDlNY+0sXtCHoM8ITTC1sxBxLkc93KCf/e4GfWQc1ET/Fn/zB6uMpnOC6BZiWnTNfqotPPennKKDeTvvMR3pcaO/wCdy0eIRikDH+DkRXEKljnbZKb4VmX5ZjZAIVC7iWyBwEUToQv1rnXyeurdDrZAIdjpNmsIh1goPiSsE09Jnr9vGE9LUG8dht9fOxPCo1FYhBNOiURDx08jzWKvKvpZ5SHMXnx8tZi5yMO5uB4iCkA//8V/zqb/59+yz5uw0j3vZ87jyMV+NV3Kcl8V933EJ4oj/Pn0Hh9cW8aTDTTsOcOPC/k3LwtzTEXO7kd/6AtTb/xiCYe4DCTM7YPXc5IXL66qbuHgCvbpY90mR0NyndDgyjmC/hbzfg1HnjyO0zkoHjMszAIunUJ/7IPKmx9auUg17DN79V7VR7drxUDrGyTmtteuholExhnsrREFW0mEjhKqWnirEcWnjhNeJM76uRjb5aPgkLj477ipGC1m43ygEw+ldBFM7UF4TVEyjt0Rr5RQybY/joLWEOEQAw9m9jGb3bucIFHdJOgynd9LOJX9MmPMCVn4hrm6Rif1agdx1EPnNP7r9bVssFsu9HCt2WywWi8VisVgm0u0NOHr8HItLa2g0s9M+tYWaS4RhyGAwBCH5wi1HWVkznbaPevw38Q//+ECe+0PPZmnJxDF+6Utf5ElPfDy//Tuv42u/9msr6/JcCpHWnmscxXWCdV1/nJRG7PTdyW7nzfBcURF+pRQ4SjPaohEmVmQu37uatZ5iFGl2zow7hNJ9FqLaiRIrcEspg46zvc7rPFprhqE5P1FcFdI3SjDMtA4pmG4LppIoeyk2b0/DF6z0xh14ShuX90qvGhk4GFXj5NM6637pW5IQgiBSlUjyK/Y4fOlosWOvP9IcOxdzxZ7iSjpNmUQaFikf+/E24abr90/eWYvFYrmH0Wy1iRFZLLY7XGf3bR8qCLcAQWuW81c9HO16IEQuItipf5BvhJSZqJ4SNqcLYjeYePSQ7YndMhplkcVgHlujzpxpc7I9JxwitKlWjZDEfpu40WZ97/Xo07fhxCOi5hQC8Por+N0l/OFatg1vsM5g/kBpw5WHkBF4cs8QXVdzNU2PwcTVaA0ohRMOEhEqiUrPxcqXxXsFhXrddxVXeTMFsRuMOOyLjdNMyjHQEsFIxTTKAyQStNacifrMSJ++DhmpmJFWSCFo4KB1RJSty5QPiSgKz6GOUUpznmEmmE9Ljxu9onM7bc+4rfUJMQqNSNJf8supTYQxT0gu96a5PVwd7x+weOg4//nK13H+9iPZ9INfcxNP+Nkfob1zvv69s7SpPTPz/H+f/A96OdH04+eOcNX0Dp73gMfSvJfX+BVXfxXyea9B3/xRWDkD7VnE/R+B/tR70R97+8Wvf27nxmfPcdHhCPX3r4WjXwI0zO2GtSVk4qgXuiaKur+KftefotYXkY/6jspqw1s/uWFNcuX4yETgTdGulwnv28E/eA3erZ/A75nSCUFrlrA9l91LnFEPNxgUlhFoiEPzTEjvO0ltbS0dRHsGVs/mjp0oPgO0OSL5e1L5Xw7Q6K8QTO80k6XDaHoXYWuWmdO3jGPVhXk26ThkcBFCd0rU2Lh8Qi2pYz23P+m+b/uumxtgpaVbGCwmnvp8xNTc9ttnsVgs93JsjLnFYrFYLBaLBTAdgquraxw9dpwjR49x9NgpPvnZ2zl7foVYKZTSqHhyh4rWxvkaxabm8ZduvYOPfurWTOgGaDUEV111Fe9+z/t48pO/Lps+HA750R95Hr/8yldW1utIkYmPQozjq9O47nzfySQxtN2QFTf4dvG9mhrONf3y7YZgUvJ03WD91EF9qYhjTXeoCSMIasYl1AmrKhGlUzarub1Ze2M13te4JgEgjKgmA2RJtOV4chNHv1WHuevWz6cL88HeBafWreRNWL5Vcqh3moJ9Cw7XHXQr11Z3UBW1Ww3BVKu67ig2Nca93InZuTDFY77mGvbumqnMb7FYLPdksueD1uy848MVoRuMA3nuxOcK08bd9hewzbKoWCMyKmf7Xg8Rxwxm9xIl0bzD6d1ot4GWHhqRRI0bx7XQiigRulN6u64iaI0FdgFjp2GC1DHusFfcH2ey4KuTuHdUjJIug5m9dHdeRW/hckadBSKvSdxoE/ttlN9CRkPTzijAiUa44QAZDk0d29zABDBCdzhBoL3U1D1/ZamLMtQKlXvf0GjORn36yaBLrTWrKuBTo3Msx1XXaaRjbg9XWVMBGmjhEmhFqBWhjolQuELiC8m09Jl1Gsw5DWZlAzfXFgWcUn1Gejy6cV2F/Ff/JKej4rlTOaf4RpSFbZEM+tiMvICuteaL//Qu/vqHfzYTuqXn8qgf+36e+hs/Q3vnPAAOgjhpGRhB/2Tc41C4itKamUaLjywdKQjdKYfWF/mXQ5/ZQsvu+YhGC/lVT0A+/nuRX/ONiKl5GFXvT9tGuujWDHj+5HkOXId+2+/D0S+S3edWzkLpfjDpGtD/+3Z0d6UyXS2e2rhtolqle5OK0fXsvQre/WfMnvwSrdXTtFZPM3v6FmZPfB4Rh6AUU+cP1zeBXGmHfDz5NQ9BtWeIGh2i5jRRYwrl+uO0CRP1lEZvFX+SPUlxgwHTp28vfNFSrs9gdl+pMQIczzjALxK56zLElQ/afMbCdyZdiDfPi/y6Mm+Ozb4DlUtI3PqxzdtlsVgsX4FYZ7fFYrFYLBaLhSiKufPQYQaD8Yj81V7Ryeo69Z2TkAjdpbKPw5Eiiopf2r3E4Sul5LW/+Vu84+1v5xWv+DmiyHSC/NM//B3/+5EP8+Y//TN2796dLefI+jrZsHX38V0RFS6EoOkblzCYY+Qk++g55piUhV9ZI6aazzePDE9FhI3mGwTjYz6KNI2cSKu1pj80n5ejwMPYtK/hbex6V8rslyOr7dXaDHTIC9xRDL47njeKNd2BQkqYahbboZOo9YtxlDe8DWzjCdMtU2s8WagohE9YptUQhJGJMRdAM+nTPLjTYe+85PRyTH9o6rrPtAVK68rfy8FdDifOxawPiu3bu6vD4x5+LaMgSuqg269pFovl3snU1BSrq6s01s/iJzWm62itnmE1HBZFB61qherNECWBQMQBJqg6ERSEJGjPbX2FWiPDkRGmhSDoLDASgqiVDEBKBBc3545Mhex82It23CRmfSwiVoR5QJQCrHVOiNZSmvYgCBsdlGsePkJFDGb3m8jj3LIyDlE597by20TCwcu5yaVW9OOA436Dlg6QWjDQMTNOk/aXKbL6TFQVGXsqwBENPCHRWrOiRsRoZqSPJyQKzQjNkWidy51ppDBuaKU1t4xW+OrWbiKtWFajzD19IuoxUFEmLgtE4twuvycYB6kQwtTcFpKleESYOzd9HTGNlz3bNfDZ4SJ7p4p1lxUaZxNB8UKHOA4ScXSwvMoHXv0nHP2fT2WfLVx5kG/8xR9n1zVXEmlFiLk2zLEz71hSk+3TugqJmy5X7N7Hh++YHMf8ifNH+NarHkTb3UDMvbey+/KLX4eK4O1/NPnzy+9votIvpia6itG3fgzx0K8vTBa58ge1lGLCwURwbwvXN/flU3dUPvJGPWZPfgktBN6oV7NwtlWITbpE9o5/y8fM/c1tjO9XsgGOaxIzttdK3HBQKVcx6szTXjpakfvL7uoLIdaa8NxxNso8MKklKvmXoCByZ21Iv4/UOPth03aabZT251IM4rBYLJZ7IdbZbbFYLBaLxWLhxImTBaE7inUlsnmjr9qmxmFxWhBVu/LKZt6nftM38R//+S4uu+yyXFuO801PfQr//K//RhRrwkgzDMyy6iJc0JfSPZ3HcwWdpkDKsdANY0dyquUqrRkExsVb377N25gaIjaaL/9Rf6gLDurBSDMKTSx8FOvCehxpBF3fm+yiTgc1AJmobeLkzXbiuGjaSNszCsfbGiZivFKw1tf0Boog0gTJeQ5ryv1tRqw0o8DsW9MTNCf0PGnMoIlOs3ieZO5HiPr9F0Iw05HMtCWNRlGQdx3B/gWHPfMOsx1JsyGSY1E8T44UHNztcPluh11zkt1zkiv3Osy0TAdos+FZodtisdyr2blzJ0II/P7KhvMJNN4GYvhE6h4y+RIRWqOlR2/HFcSuEYL6CwerdcA3QsU4+SQbITKROduM46Eq9bvrHmCJMCpkInTrxJG9h+6Oy+nP7SfwS3G4wiFszaK8Jtrx0W6DuDltRKpULJEu2vXRJce6VLFxWuZ3x2tUnO2tOCJCs6ZjVnTECJ05pu9qIq04FK4xK/1MFJaY+tPL8ZCRillSo6SeNqypgFgrIq0YqIieijgcrbEUDzkd9TgV9zged/lA/zifCxY5E/c5Fw84qwZMSbfQ8ekIwbTwCnHjAEMdF57ZQgimnerLRFAamLCqAlbjYiT0Vt42y28ZWm/FDw5PnbqC6U8d4++f87MFofuB3/kN/D9v+FV2XnMFYBzgPpKmcLL3FQ0F8R7gcG+JU4M1NiJSinODC/hbvQeiRwPU5z+I+t9/R9/2CXR7Znv3hu3itxCP+JZt1QWfyLAqYLpX37ThIkJFhWtNSYfV/Teytue6+nIFrgfTO5KFJdzvwYin/nCt0J0tEvQ3EbqTwUBamVIMub8zqRSynCggnULixHZwy88U6VQGUInLbsBrT+MOu3j9VZxR/4LqZEeDHqt7rimkd9SROblzA5PqQtkvVHyva7nYcaBmqsVisXzlY3tSLBaLxWKxWO7jhGHIyupqYVrdd/5IUalxvNH8dYyC1Hk7ZufOnfzTv/w7v/zKV/G2f/5bs60o4pde8bO8993v5Fdf/VtImY9t3H5/QFrf27T/0rq8tdbJsakfECClEYYT8zqDwAjNvjsWx9PmbDU6fKN9MTHcaVQlLK0r5qcljhSZAx2MqBwCO2aS+uOTrPP5NlTaZK6LMuU1RbFxhHsuhHFxLWGcuI2kifCMYo3jsKX2pEgxdkM0PDiw0+HkYsyg1H821xEsTIsL7lASQtDwwdfVMcNSClzHXGeONH7CMAYpdNY+pcw58b2csxwIw4j1bo+Z6Quo/2exWCz3IFqtFpdddhnL5w9tOm+5XrSIY7TI1QdRChkOUF7LPEzzLkWdLhOZ52AiggsVI9Box6U/tx+kNHVlt4PjFpzhAKI8AhByNVOzh3gSwSvNM0kbYTucnkUlDkwRh8SODyXxWasYmYr2UqKlRMVRVs+XZH2a4kuQli46jgttlXFEnNbITVBuA5kT4x3A05qgpnbsRsRaIXPuzNU44HC4xvX+HM1yrfEahiriI8MzrGtTR3hKeqwr87BO3daLqhhJroGVJIo8W4+OWVMhM9LDScSsFRWwrkIOeFN4yTRHSHa4Tc5E4wGdQghaOPR0cXBChMJjLHz6wqnU0o61glJd8VAXr42tvGFoKCTAbOXYj0Yjfve3fpu/eutbs2mt+Rke//If4fJHPhgHh3wYulObIlDc1iAOJ77E5987W18Brm71uf9Cv/+vs3rVd80Q2BLBAI588ZKsSs/tZu1z/8Pw2O3ocIQ7s0DrqgfgXHYD8bGbaxbQhUE7Sjr0Fy4DKQmmFujFVzJ1/hCx2yBsTpsBSA/7Bhwp0Z//IPTXYdRHf/AfLkn7wQxy0iX/slQxSilzj8/a6o5rbW9IyQtdFrajoDgYClCxpnH8i4nTfLy94ezu2nhz4fnocEIZLyHp7rqa+aOf2vDv/pLmZdTWxMrdl5odxPUPv5RbtFgslnsNVuy2WCwWi8ViuY8zHI4q02RN/k/aQVb7hb3me7fniEIdaIFxDk/ix37i//CYx30dv/B/XsxoaDo6/+sD7+NbnvpEfv8P38yVV12N51bjt7dC2QS2lcjwzQhCRRQbITslinVBxAQT/e5IXZgvjM3PbOfihPc64b/hGZd2ur0ggjPLipYvCGsSFJUSE+tUVze4tdmUrnaoqszhXdeGpCRf8vso0DhS47kiE8HTMn1aVxMCRHKMZVJr3HXg8t0uw0DTG5pBAZ2mwHUuTXeTEKLWXd/yYVQy9qVR9nXInO5+2+2HaLdbXHHZAdrt1iVpp8VisdwdzMzM0PmaJ7B07hDD6V0ANNfP0egtZfPEbsMIsml0uda01s6gEQzn9qGlk9XE1nFI2JyGXF1jrTVCRWOBWAjjnMsLG9Ih8i/wfpo8cHT+9zxaEQuHsDM9dn1rbdzbiVNUA6OZ3SZqPGmXdjwkGqXioqNUOmilC5HsWjpoFRfeu4RW6FJIo5YOIlf7V9Q8rMt1ejUQl/ZJIgqDGpfjISejPtf6s/jCQWvNKInGbmgHheZLwRIrKmBlOOKRrb34ouqSXY1HnIp6aIzYfSRcY6RNlPjmhUfG7S0To1lTIXPSz9oco1mKh+xxx7XTHSFpCZdBTtx2E293fr2x1pRe4ZBQ8EKXK2tLBO3yoI3SPAJTN1uhC+uK09Ityb834rZbb+PnXv5ybr/99mzaZY/4Kh7/sz9Ce2E2WZ9Csn2X8lftvIwPnrqd8UBJbdqW28cPnrqNp17+wHttlLk+8gX0u97Cl0niLuI1xi+wW2TUmQchaXQXzYTpBZaOHUINxw7qaG2J9c98iOZl19LcsYfw5o+jhz0QAufgtYhdBwg/9T6ccIhym/Snd9McLDN19k5kHBJ7Tfpz+40Ant4LjtxBa+Uk7eXj5iruLl+645BSU65C6Lh4X9vKdyNdnS/ozBV+b3bPF/4aNQJ99ggOELvN7AuvVBGtldP0Fw4W0jJke4rpBz6S1f9918RmKK9B2JrB3yQhYfJ+XNw1KQChTDKFbk3jfMsLEBvVj7dYLJavYGyMucVisVgsFst9HMepvhI60giGeaZaYmLN7joFvFE0FdFqTBZV05rcD37ow/nrf3wv113/gOyzleVlvv8Z38lb/+JPcTd4e50U7V03fSuR4ZshhKiImMZ4Vl3vJJG1TnzeLuXtCSHYMSMpn9Z8Le88veEEJbaGutNf6f/XOhPhm56pY56K1a5DxdkPSUS90oV1xcpE4TsyEcKzz/SEYwzlw9z0BfNTktmOvGRCt2mvLtRiT5FS4G2xnzkvdKf0+wNuvf0Qo9EEB4nFYrHcC1BxzInTZzh37WNY33s963uv59y1j+HsNY8mdjw00NtxBW4U4PXXQMU0uueRcYgTBzRXTuGOupkrUWiFEw6Koq+oEXUTR3Vh0kZ1csuR6Nl0RSwEkd8mas0QtWaIy44/IYnas8V4cyGM+J53gQthROuyAKqrD5FKPe9k2cKktN0bUBtrW3Y3Oh7z0i+0qq9DzsUDlNZEWnFzsMLxqMvHBmcJVcwoqUiuga4O+cjgDKFWXOFOsdtpcTIsRhlrrTkarvHu/jE+GyzyuWCR26JVXCEzKfVipccYXYkW76mw8p7gl8W1unIlpXOktCYqtdARgnzgeFu6fGG0xPm8c7ywTiN0CyFwRDk83bjZNxK6tdb81V/+JT/wzGdmQrfv+/zMz76cb/31l2VCN2x90ICDwEfSEA4t6fIXN38YiRG1JQJXSLxcd7FC84GTt/G6z72PYfTlibq/1KiP/wd3i9ANsPdKuOpBW55dSZfejitY33MtvYXLoT3D4IbHFITuPMNjtyEOXEf7/g+j3fBoE9EYrOJ85n20l0/Q7C7SXjnBjmOfYur8YbxRFyca4Q9Waa+cpL10bLwyKRksHGQwt/8id3q7VAcTFX/XNfdrBTrOpo0688T+eJCLFw1prp42i5OUkkgGpggolqrA3CPLMeiq3yVc2TyCXl1g7LqJNtfZz7gxYvxTZsJ0oRXOU56D3H+/C2uLxWKxfAVgxW6LxWKxWCyW+zitVguvpk5wuzmuN+06xXrUZerM1lIKplvjdTT9jSK6wUn6c9vtNq/7o7fygz/0wqwzUinF63/3N3n2s36Q4XBYs7xmfaCzetBfDlyn2NcghRFyJzm1a8YUMArqhdtJ1PbJ1wj3riPYPSeZmxK0G+Znx4xkpl1tWxDBWk9tqR1ClLuC0+njf+f7+DWCpi/ptCSdpqThCRxZ33dTlxCrFIWa42BEcKXqRf6tiPEXi6lPnrSvRiepGxBSnjSp/wogjmPOnjt/CVpqsVgsdw+nThyju151uQVTO1i86hGs7b2BoLMAmDquzbVzuKNxPVonDnCCYn1aWSOy1YnDVeoeODEiCpBxgIgDU+M6L64IifbbxXrY23jAiJwAk7W1FJlTL1pv/sDakqApnUrb4kaHoDVrRB8EcWOKBelxUDZMPV3MczRAcTLu8dFEyN7vtpl2PI5FXSSCJg4tHKaEx4MbO3hMex83NOa5oTHPFf50ElJsWimE4HJvhse1DmS1uQE8IenICxSHaohKwpgGyq8U5eOmtEaVjv+CbBRE3qGOC52mqRgcYwTgpnCYkw0UcEe4Rk+FSZB4Lkqc4nthVe6ezPnz5/nxF76I33j1rxMERpi75tpr+Yu/eivf8/98L0qY8+YicJIfTwiaQtKSDg0hcfMx9VrjIXGFHL9fa81aWH2vlkIUjgXAid4K/3N6cu3mezTHb/2ybGbUWTApFDn0v/4e4sC1sPPgpstHfovVAzcCAq+3TNicIv6un6K/ujR5IRXD216Pft9b4cxhWD4Nt38SZ/FEZeBFHe2VkxWRdzC3r76m911AmtJRqOWdxuvnponk7pWfnlzFDKZ30d11VTavO7eLmesfipYuSrpo6RmhO7dPZsBR8U7hBgPKiAlCtjvs0lg7h9dbNnW/t4mgek7G43ov8PvsbZ+4sOUsFovlKwQbY26xWCwWi8VyH0MpxcrKKuvdLgKBdCRhGFXmc6RgpgP9oa6NNc8jhEAKXYmXdh3B3JQRKOvE3pT+SJs6x44mSkxY3/eDz+eRj3oCP/OTP8x60mn+mc98mic98fG8/vd+n4c+9Kuz5UehqQsdxZpYaZqewHHqo6ZTLjbOXAhBqwGDoenW9dzJQjcYIbw/qgq3vaGm5W88mAAgCI3w26gZNFC3L0KkQnduPheGoSYoaQb9kSaINJ2moNXY+GSnNcjLGJcdqFwuaBTrZFCAyPYXBE0fgrAY7e5McESPQk3TH0eHZ0KzAiHGbvBx3GZ9uy7SyJ9R7TA3608HdUgJ8SaO/c2uuJXVNS47+OV21VgsFsvFE4YBq8uTo2+DqQVAF2pRG7ddsaSKiGN0QWTQldodIokZT93PQilTw9prVBzRxZVLEDHoVHRWECu09MZ1XC5C6DHPnHKdkbr1beHBVBHNHZTjJrXJE8ei66OVg4zMMVROfYStdn3C1qwR8xMhvyUc5nCQKGaUwAUCYMadxnMb2T7onLiUDnybcvyCy3kSu9wWV3uz3BauZNN8IXEQm8Z3XwguovIuMCjV5+7riBEKX0ukEHSExw63hdKac2rAehzQU6F5T0YjEfjCyb1nCXY5rcJ71+moz6zfKGynXP5nq1fVf33gA/zSL/wiK7m/pSc+42nc/7lP493+iPbarQiSOPZcG2KtcZLfpTDivEyuRUcK4rqRhROQVEvSfPzcEZ508IYtr+Meg3QKNZrvCmLHp7vzKrTjMnXuTprriSM4HKE/+PeIb3kB+ugX4bMfmLwSpWgvHcPvLWXXivq738Cb3Z/cO6u0l4/jrF3cIMnm2lm6OZFeOx5RYwqvJIJfMlSc3IcFAo2MAmQcETU6CBUh8udKJyI36fWYF7qTMgCNdiEaPVo9j/LdSlx6hbSOQPprus44MtHgQuLPzKP7y7irZ0BrYq+JO1zHC2oE7vw9/1J98ZhETTS+7q3etdu0WCyWezjW2W2xWCwWi8VyH2I0GnHLLbdx7PgJVlZWWV5ZYXGx3i2glCYITSfAZmI3GCd36tpNY6ulNKJ5w5MTheA4HoueriNoeCYCvdMUPORB1/POd7+fRz7q0dn8/X6fH3rOs3nta34jmxZE4y/7oxBW+5poUqHkHKkr+kIjzR0p6LSEcSxvEl/te2bfyoSRaW93MLm9Spna04MAhjVucOMU3rwLVQgT6z3THsfUp/HiUsIw3Dze3dTETs41Y6E3jRvPXytap3W6zTrTgQxSGMd3uyGY7UjmpyTthmQwqm47ik0Ee6x0xf2tdeL+zhk9yk5wkvZdMn/KBHe9cZabH8+pcWskx9kvGkvqN3E3JW1aLBbLxTLobe5wq4ixta7pxIHs+MRuA+V4aJEPfBUo6aDcBtrx0I6H8hqoZscIuZvEwGrpFW7nAgp1ry+eLdzIa+qAV9biJM7EZI1xbn81ZIKRdlxTB91rbfjSpl2/6FgHdkqfHcLDT9zBLQR7kHTisUNdCCNMhyXPdH3eCxUR/EpvpjKPu4X3lq3QEsX9mXMauDmRa6CiQhz5UEd0tRn1F6CYFT4H3SnAvJ/MCp9VNY44FomjO/+epdAMdHFk25qqliDZkhNfawId09cRS/11fuVVr+InfvzFmdA9s2OeF/72q3jcj/0gkW9e3vo6Ss5HaRAlmrB0HTlC8IxrHsZ8LuJ5K5hBDcVz1L+XxpiL+z14w89HnR1E5VIFW0QDYaPD6oEHINC4w3UGM3tRJaFVv++vYNDdcF1uNKKRE7oB5LDL9Jnb8PorNRvXNNc2j9nejHSgzJcD891BJxHkY3e10Apn1EOGo9JVVywCUeeI9gYlkVdrdGuqvgEqNmJ6OuBKxaAiUEbg9ruL+INVvFEXf7jG4N1/ibtyGiccZvHvMhHCK+Rf4C/2/nYhXwam5y9umxaLxXIvxzq7LRaLxWKxWO5DHD5yjCDcuKMqiDRhVOo8i0G7m7ugTU3C+s+U0siavPOyJm1c4vnazi6/+7o/4F//+R/51V/9FeLENvvnf/4WPvShD/KmN/8Z0p+lTBhB2p8upchqSU9q94UihMDfYhpnqyHxPRO3HoTFTtAwSqL8atoyyp2yYWB+plqQps9vp/1CCNpNQbOhWe3Vi8s1qfa165GyurwjIX+FKQWDkU7mLbYzPddSCk6dixKxHVqN4j6lpU0n9vvkVh0pcNBJTWyRLXPJ9OOyzSlBaZ1FmAsh8FwzLd1+2h7z+eRrEWB6qnOpWmuxWCxfVkRdXZMKiRQqEtlCRyjpGAFXOIAmdn3CxlR97Ef6fBCbjDLbsKGmHna+prdAo7Xa3A24tQ0Uf02jzVOndHkerSt1tbN2Og5aJIMEhAClTMSwdIpbcS6si08IAcII6vnj0dCKQEvCvHMYPfFdZSOaF3OuchhHuGSojXzdFA6+dNDa1L6eEh4LsolA4GhY0wFryryVCCEItWKlLEoLUShB0pQuHeHSy7nBVc2DPy4J/2lEeawVirEodzoashIHxGhawmGH02S6xn1/28238Ms/+3McvvNQNu2mx34tz/y5n2B6fg6ACMW5eBw7rtAFN7eZR+OVztHnl07Qj6pi/OZoZoMRD1xdxNMKuffqC1jH3Y94+Deh7/g0hFVRN/aadHdfjQZmTt+CP6iWYABTlzl2G8g4xMmJwwLjBO6cO4Q/WM3+JitXTG8F7vjUhbUfTXv5BKvtueJ0FSMvwSAd5RYTCUQc4o42FuYvlixVIz9NJ385F/i9zBn1kFGA8po4B65BoRHJOdcIpI4L91kZBUSNTjYAyA0HOOGAqDWTJYtoIRlN76S5dtbEqwMIgXI8ZFQW5ss7WXVfXyiVb1F16/38h1COh3j80xEbpZtYLBbLVyhCX6iNxWKxWCwWi8Vyr6Lb63HHHYc2nS9W1drXxpFaH9NdSeqsQSlNpMCVVATvMNKVeG+Aplec13Xg9OnTPPtZP8iZM6ez6Z7n8Qu//Goe/bgnF5aXAmbaY8etaWu1zvPdgVKalZLQrLWm3aiPEe8OVCV6vOlDu1mcdxAofEdsGomest5XRLl+Js+FTmPjOPZym+unQ3+kKvWr6xzoUhpB/MT5cQe7I2FuStBpyiwdIN3exATOmibLmu1dLFrr2hh3IEk22Hx7G61DCMEN192Pdrt1Ea20WCyWuwelFLd98fPZwLQKWiPDAU44Kr47KGWiY/OzCsmoM2ciiAtcuBhSbIsaixdpM6Rbs71NUHHygBs/kzVJTXHpGCE7DsYimJDF+rFaIVSMGwxwRj20dAjbs5X1peTFtEv6hCu1EyAQgq5bHNHnI3EKbat/F8i7gpfiIe/uH8ttSrOigm0NRHMRNJIocaWN23NKetlz10dy0J0qPIdX4hHruniOz0b9Qnx6R7hc5xcdkbcHKyV3NzSky26nxaz0GemYWCsCrRjqGNDMSJ/r/HkW3LFDWGnNcjzMBPeU3U6LXa55ziuleOtf/AWv+53fJUwGpDaaDX78p17CDd/2RIY5UT3Uii8FxTIBJmK9+D7YEE5BAL9iegcaOLSduGuteeqJO3jE+ZPk/yLE7ivwvumHEZ3qQNN7Mvrk7aj3/AWcM9ehBsL2HN1dRuiWsTnfc8c/X/gbUELS3XkVwfTO7G/WG6zSOXcYN6zWeL4rWbzyYZVkhh1HPom4oIEMY1YO3EiUizFvLx6lvXLyotZ5oejK/T1xdm8gXwStWUQcFqLFtXTSmke5Venx+nJrD1ozhfu+FpKwPVdY1hn1aPSKaWgiCpATBikVt7k90sFgkwZObHY8xEOejHziM7e9XYvFYrm3Y2PMLRaLxWKxWO4jDAbDzWfCCIv5BEwhwHNEFhGd/2691e/vqbAX18zv1kQ+A4wi00mYtkEIwb59+3jr372db3jqt2XzhWHIK/7PS3jVL70MlVNClYb+qCg+5qOm7y6hG4yI75X60rWG7iCJji/PX9PUUTA+PmAGDQShqQG+VZql+t9tf3vHpW5e4/gWDEamPngYmXrg/ZEmrLkAjPO72FEUKxgEpg66I4vnbyJ18eJb3pOtI4SYWH9+q9szx6j+s8sO7rNCt8ViudcipWTnnr2TZxAC5bcJWzNFyUFKtFuKFtcKb9i7y9pavmlnseDbWodxZEsVj2NxSUp8aAVxhIgDnHCI11vGGa6jkRUxZOrsHcwf+QSzp29m7uQXWDj0MRprZwvrK8f3XvK3mJrY9wvtNCwvt+A0eUxrP37yyUhvr1q3zAndkJRDkW7hvSBAVWqAN2oc5U5pH1NJaV0FnIsGrMQjeio0runkxxGSRzX38pTO5Xxtay+Pbx/gMe397HCaKDQKWFEB/zs8w9FwXOdYCsEOt0W7FLV+Nh4Q6JhzZ8/yYy94Ab/5mtdmQve111/PG//qL/mOp383O9zi+4AnZI1LfvMjOe032d2eyfYnRqPQhYEKTeEU1v2EM0d5VEnoBtBnjxD+2x9dcAmguwux/xrUt7yI5YM3sbrvBpYvfzDdnVfROXeIhSOfZP7455k7/vnKclIrOkvHcMLx96iwNcvqgQcQu1WH/oWylaM58+DH0thzGY1Wi/aufex4wnchrnzgRW23P7tvLHSrmNbScVo5oVs85Ovguodd1Da2ik7/P4033zTayeAPVis1tE1KRWlZUb6LGte8Gxa/IwutEKWBULFX826+lQGum85RM7+QIGRSsmPcUpOEYvYpLW1Rt3792Q+g+3dRvXWLxWK5B2NjzC0Wi8VisVjuIziTFLoamp5gGBoXrbtBSTKtjYA52fVtxHGdW64cfymEoNmgUq9ZaxPX3fIpiIvtpsNPveyVPOZxX8erfvGlBIFxM7z33f/BZz/9SX7n9/6UfQcOABRcy3cHqRNZiKqjvd0QrA10rm64mb7aU3iucW37buIg8cyxKKwb6PY1U23TmZrWLddMjkMv47mCqSb0RzqLE98uJiq82tXS8AXDQJOGK6bpAHXUlNmmP9REscYtudRTJ/hWMNfe9uNWN8MI3jqrFW6mbU94kEIgZNLNnFtHFF3KmrEWi8Xy5WfHrt1IKTl7+hTxpHuadIi9Fm6YEyhSsTX3TJHRyAgeBRH6AjzN+Zt1OklKtJbjWNtJNb4nrk8jVJy1RGiFVuCOerijHqBR0sPvLRXijWO3QXfX1QRTC8lOOqzvvQ6hYlrrRuB24pDpM7eipUMwtWN7+3oxlJ7Hdf58hUZu8J4hEbhCopJo8ZT9bofHtPbz773DlXrXm1EbI64VXmlwQoyu7ehM31M0EGmNk9ThTvncaJGBnvz8HemY9/SPoYFrktI5vnB4WHM3w0HMuXjs8P3SaIk9TptGzik65zTol/4W3v7ud/K7v/JrrKysZNOe8awf4Hk/9kJ834iobs3gi7KT3qkZkhBrhUSadzTgc4snCgMk02OhAYlOnOBmPU0gikO+9vzJrO600Cr7QQNnDhN/5G04j/gWxAY14u9pxIN14kaHGBPVPXf8czhR0cFfhxMHTJ+5jZXLHpRN047HYHYfU4tHtt+QhX2wfGYc4z2zk3jX5bh3fHLyMq0pvKNfwPvSh2GQCJmf/A8ILtxdLh7+zTQWTyHP3G4GFyX1qPPoM4cveP1gYuKVdHHCQWXdE9t1UVssrkeXnxfJ95b8NsoJH2DE8sJfTF2jav6mKo7spKSSqJWlx20yq9PF51DyPNTCQTleVsZCxoEZpJNfTqvxNuIIfexLiOsfPnmbFovF8hWIFbstFovFYrFY7iPMzsxwQp4quJ8nIYSg6SVO7g3mi2Lzo7XG9yjEViulM8Hc93LTNZW63r5rOgZG4Tje2ZGmbrdXEkibiYj6iEc+jr/6h3fzsp98LrfffhsA58+f5Qee8a38xEteznd9z9Nzdb+//KQObZVEVrdLdagdRzDTNqLuqNTHEkbG7ey7pg7lJFN+FMPquqbR0OQTY4MIGlusI+5ICGM90a28Feo6vNsNwSgci/hNTxRqaKdIAdNtwWqvWsf6zLJi34IsiPBCCBynOEBAiFTkr7ZNJ2ryXSJ4b2OVWhtxvOxUF1DoQBv0v7yRmBaLxXJXML9jJ8PhgOXzk2OTleujw34lulzookNaaI3e6H5bI2TXzSNUZOLDpTTPDOkSSxcZDRFKoeUmD06tIa35qs32RK6Wi1AxzfUzhRq6DgHa9VGun4lqTjRi5tTNrB68kbCVREELydq+G2j0lzPhRQDtpWN3ndhdrkOjqz7BnhBEWuEwHtQYoVEofC2T51giuKCRCNJK4jJ55ueF6p1uiwWnyYlo+479SUMc0lj1WCukhoGOiJJthkmt9PxeLcgGfR1lQnyIQgIOouIMz6OAD/RPcIU3hZc4oIUQXO/PcW4wfnZr4FTU40p/JpvWkEaSVsBwMOCtv/X7vO+f/i37fNfuXbzyVa/iQY94WKEFQWlQwEjFhKXY5Ou9OQbEnIy62bIRGqUVfiJ4Q/KOrqnso4PAQRJo4/UWwJPOHqchXJSX/E1ojUwSCjIh72PvID53HOebfwTh3DvqAzutqezfzdUzBaF7M9ygjztYI2qNz2swtQMuQOwWD3oC4tqvhvPHodFC770S78P/hr7zU5NdzIMufPKdxWkXIXQD6HNHcdaWcLobxNsvnYbLrt90XcrxGM7sJmxMJWUZ+ow6C8TN5JgrRaN7ns75I8gJg13uvm9t1WOuS4M4ZDiq3IO046LjyAx0Sn437us4OY8iGw2rlRGjC+klgM67zQvPsOS+KlyU55tnF4ADsesjo2D8rBEChINW8VjwvpclL1gsFsul4N4z/M5isVgsFovFclE4jsPevXs2nMcIiDpzwEgpKnWXM3eMNs5bSGKnR5rBSDEKFIORoj8a11fOO39jZeqCl93AniuYaklm2oKZtvl3KnTn5xVCMDcl6TQFMzMz/N3f/wM/9NwfzjrzlIr5zdf8X17y4uejakbqf7lINc0gMqL0YKRROQuzOX4QTjA5BKEZMBCE5pjV9eGnJULDqNhNMww0cZ1dOiGKNb2hYqWnOLuiCCPTzksZSek6gvkpiZeUJU3riKeGBSnMwAXfEzRcycJ09avJMNAcOxczqol2T+PSpRSZaFxrugDOrylOLN49jmlTn1sTRhDHmx9jeTGjDiwWi+UeRBRuct+tiZQtoxGm9nVxwcJv3nCNzvnDyEnCj1YIZeqBCxWZ95xUOECjnAYaQXvpGAtHPsnCkU/SOX+4pg6uRiiF0CZcViTiYCoq+P2VgtCd308T257fA0176XhxPukwmClGwHujLiK6gHeZ8rNGKUQpqtfvLuIO1rJ58y51MEJ3ICWKqkCq0JmgnCISoTs/uKzuiXaZO10ztZ5UPJeY5+dIxfRVSF9FRFqzQzbZ63bY5bTY63ZQGPFaJTHdjpBMSz8T4AEcIZkSXsHZLYSojTwvE6K4I1grTNvlVOONhzUucQ0cvvlWfuEHfqQgdD/xyU/ib/7+73n4Ix5RaJPWmmEcZe3SWnM+HuAKme3Ple40bcdjh9Nkv9tJtmP+F6OItEJpTagVgY6Jk/Dy4j5pI/4ngt1XL57mkUtniy+eQqDcRiXKWR/+HOoz7930uN1T8OZ3486YRIVy/eWt4JaisvWFDKR0XMQNj0BMzyOuugmx/xp471vRH33bl1+gXDoFnZnaj7KY7PY04n4Pye7FuhKvbeYbdebpzx0g7MwTTO+kv+PysdANICWjmd2s7b/hLikzdDFo4Yxd9pj9ccIRIk7+jrXGDXpo6RTLbwiJcjyUkMkzJR34kxwjIZJjZY5dOp92PLTjoaRrtp3Elmc/+XsTGplvCyR/j371+hNmIBfSQVx2w6U8RBaLxXKvwPakWCwWi8VisdyH2LVzB1dcfhnNZvOi1pOJ4qXpsTLibVwyj5cF83Q+VSPIlutp68QZnZ9XCCOG75ozHYAvfvH/y1ve8hdMTY07VT760Y/y5Cc9gS984QsXuJcXh3SKNc7DGNYHmvW+Yr2vWOnprL72pL6y7kBn8eTpfCYSHRzH/HejZQeBqhW9tYa1vmYwGp/DONbbqve9FYzg7TA/VRfDWazJvmNGsntOFmqZe66ZvhWHfiZ+Jwm4g5Fmra84eibm9JJieW3jAQCXGq1N/fVU5E7ZrAlzc7N3bcMsFovly0QaxTwRpSg76kTJtRr7TTaqoy3DIY21szhxQGf5+LjOqlamhrYydbMR0ggL0jVitYoQKkKqGKkivKBLZ/kYjd4Sjd4SM2dvZ9cdH8Ed5uqeCmlEinx7zcZAxchwQgxLsmzsFd+9vP5KpS5H7Ne9n13Asyutd5tua7hGq7totgm4w3WcOMAbdXEGqyzFI9ZUQF8rlnTMSaFYz7l1FdXBWjHVpKDylAtNVRFAE4e2dGlJl7b0QECEQmHE9q4OuSVYoZ8bYCCFoFmQtk0b2rIYbFknbkshSkvW09WbDz5oiWJKwDAO+fe3/DW/9JwXcerIMQCazSav+MVf5DW/+ZvMzc1lbfKQaK05Fw+IBck0wcm4x5oKUEkE8+XOFC3pcihc5ZZgmbU4RGmdHB/zM0Ix1GOJO/2LK8fCp/XJpVI85txJJqEcrzL4RH3ug5sej3sSMw95HMLzK/earaCc4nn1htuviywe+z2I9njAh14+g/7sf217PZeE5jRkQnZOnBUOSNf8rC+j3vUW88UmFWOTf6dXkQBaa2eZOX3LppuMmtMEnYW7dLcq5O9dtdHjZiCDUMkQHikRaJygh4gCvP4yIg7RQqCSZBCSut5CRSTWbUQcIpNpouDsTr68SacyiCRrwwYIQMalwVdCVK7HdACZeOBjER37fcJisdz3sDHmFovFYrFYLPcx5uZmmZub5cjRY6ysrG46f1o+s5x2udG8edIo8ijWFaFP6c1HX6bbjrURRx1JVic6n1x604MexHvf9wFe+IIf5eMf/xgA6+vrfP/3PYPnPe/5vPBFP7bpvl5KpBAIUe2+iFVV8HQdAY5xcecZhRrXgbKLre5cFOrDJQShEbGnWiUXnCtwHeM4TxmMNP1hzFX7RCFq+1LgyOoACDAisHTHEeNzU5LZjshi3csR9ltBCIEUmkOnSzUHgfW+Ym7qwqM2Y2U6mLdS21wk578utn0SnU6b2Zl6h43FYrHc2+i0W6wO1pJYbkHsNYj9ViZedxYP01o5RXf3/VBeI6nNnSysQUmXqDk1rlVBTjwAiEMTiRsHiKQWbGvpOMOZPYmXLnEmCgfluQXRvHArFoKwPc/iFQ9j56GPjuPG44D545/j3P0eWaihqqWbCBw5lNpUJtWy+PypkzlkyU0e+h2U628v3jdti9ZoHeMNu3gjExvujXrF+FuMyHPM1YS5FwtfS/ZSHKyggPwebCTQjJRxEXtI+jrmcLjGYjxECsGZqIfxLo7jz9P159c9IkbqccKQIyQtBP2cazpCcWe4ygMb46h3IQSuloS5NTpC4iIKbnQPSTkLQG4SZQ4wVRKyz8fDwrodBFd704hk2pnTp/nln/sFPvvxT2TLXHf/G3j1q1/NFVdemU2LtWZVjZAI1lXAqajH2XhAqBUNJCtxUGjb0bhbW1RdaoGTLyuEBk1hGpBElhfnO9Dv0ok3SGQQwtRfzgtvqxtEYN8D8eZ2seMJ30m0ehJO3b7l5TTQWD9H7LfNfUxrmiunt75hIRHf+MPI+z+iuN7bPsEFDWjZArnhstmUwlWwdBL9gb8dC7L5WdP77aTrIb2f5gYN+INVvP4qYXtjoTXoLFyQs75MXmyfhHkO6NzB0IXvTFqaZ4PQGicYoFqzCKVwwj6gkUEfLT2ixrTZZ62R0RC/pr55fpvmIZaUztjoC3Tdl+e62bQZVEXuOVJNPQFx5QMRT3zGpuuzWCyWr0Ss2G2xWCwWi8VyH2VmeroidqcicnkaGHd1PnBU63oxr7AsJGJtIvLpYseEwDiFNnL+5IVhlXzPz3ffuLnv+b7v84Y3vom3vvUvec1v/DpKKbTW/PEf/xEf+MAHeOOb3lxwf2/GZm3bDFmj5Iu09z1HuwGm27dav1sKUesGzgveaSy4EOBKQRCZgQVCGCG9bj9mO5KldWUGEsTjWun9oWa6XZxXKb0lgXcSQggcqSuCt9LV/h0hBL5XnR5G2jjat9AOKQXTbcF6f7ySlm/E9SjWZnBBjq2cZ6XNYAQB+N7WjocjiwMKXGdjl9vllx285LXFLRaL5e6gt3iWc1/8NG5OCJFxiBMMCDrzeMN1ps/ejlQxsye/yPLBByb1uRVojZIeYXuG5tpZvMEaWkiCznzREShdRtM7aS8dy0SHZm8Jb9Slv3A52nGTdcaIYJgI7Ru8b3gNeguXM3N2LIC5QR+/v1zcbp3TfAv37rKTNGxMFdelNaOpXbijHs2khm5/5xVGLNFqa07UUhS50Ap3VKyPLeOw0F4JzEcxZ71xF2G0wbay97eazwIVc1b1CXLLr8QjjkXdTKiVQrLgNFmJ0xq4ImmHrgreOqYlxu2SQuCVhOy+juipkE6u5rqDoOy/llsQlcqO59TpnbUdwaoacTbqs9tto7TmRNxj1mnQUyEjHfOw5m4aiZP83e/8T37tlb9Cd804gIUQPPPZP8j3/uhzOUKf23vHmJMNIhQ3BysMEiHfF5JIq2LSUW4Ax2b7IHQxVUmhkZrS+qoiodhKjHZ5ofbW36vvKUi/ibtj37bEbgE0+it4w3VW9z2A1toZ/OHapstlaAXd5er0cLT1dWyD7EwW7lfJd4L003CUXFNiS/ewKqJyHfm9xU3F7jqRdrsYR3Ya8R9vTfCmOtDJfBGKsul+b9k8M5LfXUBJh5Hjoc2Ia5TXYuj4NLvnJgre2bZUnNTy3qiB6XnZHpW/VyGRT3kOYrPtWSwWy1co9u5nsVgsFovFch9lO/WZTU1kI2znxeqGC8OwPK/pN5DCRG2nHWupaSD/RV7KLURcbtBMR9a7bJ/5zO/jUY96NM997nNYPG86jG+55Wae/KQn8Fu/9Ts86tGP3niTST1tDfjbfGPWWmcibhzXdwhLMRbxTU1rsw/tpqDZ0KgYhBR4jpkvL9qOt2P+mz+mWoPvQcPfvBPJdwU7ZyQrXcUoGK9/faCYbo+XV1rTHWoaHluKE5+EY8wQte7+MuVjFiud1HoH7Yzd/RuxZ86hN4iy9U+3TYfcSldltcIFEESa/lCxc9bZcJ1pFLkGRiFIofHc8fUXxzqrS54ipcBBZ8tudqmvrq6xa9fOjWeyWCyWezgqijh782fRJcFUJw7t1tIJZs/cTNSYThySisb6Esrzs7rRGmitncYddrNnXLN7nrDRYW3f/Y14IATB1A5iv8XMqZuzjn8nCmiunmKwcFm2bYE2MbTuxtHqw+ldBbEbwB31No3d3XXwCnqnNP0YEA4yGuHlnX9a0Vo+Sey3jYsdGMztM7G5wtQlEVqh/Cbr+25An7mVsDnLcGaPWRxpBO8NW0HVJSgkyvVxoo0FtUzoERKJMHHYWhNrExsuMHHaLRycZCRf3XukKyU7aHI67mfP8TmngS8cbgtXsmmukExJj3U1fokUyaC/wvMf0468cOsKQVja9EjHdChF+pZQpfYqNFopbn3fR4jCkAd83aPZ5bVYUSOG2py3KenhIujqkEArDrodQhS3hivEWrOohqypAF84uI7kWm+WBafJ+e4qv/Prr+Hf//lfs+1N7d7BU3/+xzj40Jt4Z3Ait5/rpmRPbko6WEDk9l0k53Yrb+8KXaj/DfXidpmTrTaBlPhxlCxQFUFFFBZHXA56xO/7K+RjvgvhbVK64B6AVgr1r6+Hw5+/oOWlipk78flS1eotcu5oZZLYd/Vd4usefzcoxUHVCqtbjPCqbERUvuRUBuXUrNe9gPj3wirBiPjZeh20Tl+2U8d5sbJ4ReTOpqlsjnHahsgGl4A5543eIsPpPeNtSoewOUOjXzOAodzaCzm21bWU94LBzG784Tp+Up5CXP8wG19usVju01ix22KxWCwWi+U+yGAw5NjxE7WfpYJfuRNTlqKopWPcOS1h6kqnnwnA84xQmxcPy7HOpv9sC1/8N7CxlHXuvNB88LIreOc7383LX/4zvOud7wRgNBrxwhf+KN/xtKfxilf8Io5TjbTuDxVh0l/iOlT2YyuESeKf6wpcl0otbCGMk8p3q+5vKQSON3YwS6DdNI7r8r5GsRGLO81x+8J4awK9UqZGd29YdFx3B5phoGgmgnkQmnM2DDRRrGl4YkticxkhBJ5rOpvTEqWpI72mHw7JWAjP17yOYvPje7pSCz5PqyG4ap/D6SVFEOmCI3wYaHoDlQ3UmG4b97xTszqdtLfOlZ7G8EexZhhomj4V17gjBXGsk33c+Jitd7tW7LZYLPd61s6cIHQ8tN82gkMUovwmyvXNDV7FxK0pvP5KyYVcFCaU2yBsSbzBWjafN+rROX+I7p5rs3ljv82osyNzQ4MRqEUUFMRtqeK61OcC5ahxwLQ7h4wC0OM4WQ2cXV4l9vMiwxRBZ57WymncUZf28kncaIQTjRh1Fljfey1hZz6JG48hLjoT1/dcZxzd2QExdXSF3mwPqi9NOqsLa0bHaa3RwiFutFGOi1AaR2qu8dq0km0qrRnoiPXc9vo6IkIxrxvJO139M60hXRZ0k0U1rmHeli6z0mdFjeOvG8KhS1ipgV5+5asTbst4JadoWRKOtSZAJa50I2SdP3qCN//IyxmsdQF472vewPf/+s9x9cO+ivPxAE9IPCFxEMzgMe34TDk+TiLLH47WmZU+N/jzeMLU2dbAxz77aX71//wCJ44dy7Z/05MezWNf+lyaM1OESbx7mPORCyFwNIWYdZJjkU+fEUIgtiB4X6h4umfQJYpC2kn9eQ1oxzO1gYVARgFuNDK1ndPrU0Xoz7wftXQa+Z0/cc9PqLnz0xcsdKdckNAN0Gih+2voL30Y1pdhdhe62QHXg2jzWvAXhh4PXMgo/qWNnc/lc7fJEImaAS9aFL+EuIM1Gv1l+gsHTQmIOKK5fnZ7u4C5f+l0oI3S4HjF+7WKEaUBQVqrbABVpd05wbuyF4XSGQapYpwwSQhJiL0WmuUtuMo32zlN+VjnB5ebf8ikprgD0iHy24xmdjOa3UPn/BFacwvIJ33fZluyWCyWr2iE3o6lx2KxWCwWi8XyFcGx4ydYWtpsJHoVpcbCaLmectrJJ9hY1FPKCH9bcnVjHLNl92+6nbo2pO3LC7L/+Z//yc//3M8ShuOOpH379vOmN/8Z+/btLawjCDWDQCfOdIEQxsG+nRjvIDRtbnimDXGsGYW6IKI3PIHrCJSq7l+5/WCO2yg04rTWRfG13Si2r+mLiuia0h0ougMzQCH9JqC0zgR6MAL07jmHqbagN6i2b7olKsejLh58q5hrpmp6UCp1Ulfj8l2nKixPoj9StYMFBiNwXdg5azrLpCged6USh3+NIz2dv+EL+kOVfe5Ic12m7v04Hi/b9De+5oWAKy6/jNlZ68qwWCz3Tvq9HkfuuHUrJUhxRj2aa2eKQoFWlWhWd7BeqBGsESxd8ZCCkO0O1pg5c1uxLfMHiJrT4+WEIPbbG7apsXaG+eOfG7sihWB951UMZ/dldXrbS8dwoiGDmT3EXhPlNtDOBFexUuy+5QM0c/Vpg9YMZ294wobtAFOzvPBg1GrDyFwzj0aGI/z+MjIKMjEo9lrj0XVaE/ktlNcsrD9GEJUexkMVFQRqgI5wmXY2dvAqrTkWrRdEnuV4xJGo6OhcjkZEuUhyXYoyB2gJt1BvOtIqc16DGXS222mz22nRzA0Q0FozIibWmnUVFrZz7shx/vBZP0kcFAVGISUv+O1XceXXPAgBzDoN3ETIjmtEd4lgj2u2G8cxf/3mt/Bnf/jHxEkNk1a7zY+/7KU8+VufyvsGJwrx7krrQhw7GFG+HKUuKb47aF09RnWUBwC4VAcoiOy/gsvWV3jeHZ/DrfnjVdIBkQ48MZ8b8dEpHBH5HS9GXnnjFlp396H+7Q/Qt378Lll3WT5O/5Uxs9NEmW/2d3zJ21V6yU7EVVGeJzcCdyy9lpYr3ZPqyisEzRnW910PWjN78ou4Qd+kcuy+lpmzt+ONuhu01Qw6Mveu5DhqKqODq+7upD25SPJ0Wu19s1LDvmZfS8cobEwRtorv6K3VUxuWmNCQpXdkxHFSf6rOhV43lML8rSHMZ6OpHQzm9mfrFNJh5zd+P/JekKxgsVgsdyUXXyTDYrFYLBaLxXKvYzAYbGk+rYuD9qUUuI4R9MoIIZATnD758ZVSikrc8yRSgTcuKY2TljZOo6rg/pSnPIV3/Mc7ueKKK7Jpp06d5Fu++an8y7/8S2Ednmv6H3J9wgxD4wauozbG0y2Kpo4jaDclsx3z02nKTKidpH0qVT1urYasdRmXj/kw0PRHiiiuts2RVfF4uiWZauWEdQ2nl2PuPBXVriMs9RkFoebMUkxQzhXdIpqxUzq95lKhG+rPd6zqj30dzZr49dRp3moU9zuMYRRoRoEZAJAlEdSsV2kIQlUQwmNljv8oNA7//GebNVcAZ89u3+1isVgs9wRUHHPs0B1bEroB4kbHiLAFqh39qtSBL9C4Yek9pqYGbNmlrUXVtV2cQdNcXyRsTqOERANhcwYv6DN1/hBy1Ke5eho3HCC0prV2FuV4k4VuACkZTe8qTPIHazgbiD25BmXtqryQTVxE4feXaHbP4w+No7LRX8YbrOYeaAI3HOIE/cKiDhqndPSb0sUrdR32dbTp81cKgVtarq4DsirsVsVYjc62pzGpLi0xFllbwmWgI45FXYJEBE8FYU9LVlVAjMJB4CA4f+Q4f1QjdIOJuP6Dn/h5Tn/iC8w5jaxmtxACV1T95QrNmWjA6ZOn+KnnvYA3vf4PMqH7hgfeyB//9Z/zjd/+LXjS4XJ3urCsFKKyvkvpiY5z58hB4AunNtrcvINpnnLqcK3QDcbV6g3XS3+dujIwRd/2iUvU+rsOPexvPlPdctmPyP5d/hwYC7BCUrmfrZ3/sgvdk6hca3Xf3/Lt19qkUKg4d0+qF3n94RozJ7/E7Ikv4Cb3GW/UY+HYpzcUuscbTqT29DiWY7DS9pe3L2T1WZDcy7dN7Re00v1JxROPQWEZwfj+qxUCNV5Wj68m86/xfdokeoyF7rQFMo6KAxNUzOj0ke3uocVisXzFYcVui8VisVgslvsgsiams8ykfkwhqq7ezYhVsVZiGje+GWEitGqd1v8eu4BNDejqSmSNQxhgfn4Hf/+Pb+N7n/HMcbviiF/8hZ/nx3/8RURRlO1fu1EV7Y0YW3UHl4Vn0wYzKGArmEEC1emTDk9enE1/7zRFZQCCUtQK1U3fiLwpjoQdM5K9Cw6znWpHbt2xHIW6cCxWe0bwXVyN6Y8UsdJJzLqmN1RbFqVTB7XSxf2vSZtHaxNnvhWkFDT96o54rsCrG3hRM8l164/FpDaU99l1Nk4HSK/b0WhEEAQT57NYLJZ7Kqsry8Tx9oScqNEpTpgguJRRshiVK+JiHLZyPGKnkb3M6GTaRFTM1Lk7cYMeCEnUmCJoz2WRtUIrphcP4w/XxtvUCm+4uXATtqtpHUJtLJBoAKUQcYhUEVJFG7oHM6TDcG4/g9liao0X9HCCXmGaEwUV4c2pEdWb5UEDVEXqSvtrHMrliO6wpgZ5U7hMCS+b7mKEqgiN0sXY76Zw6AgXL6kzDnAm6nM+GnBnuMYd4Sp3RmsEOjZCtxAsHT3JHz7rJ4lqhO6s7UrxWy/+Wb70v580db3z8fo1AvVH3vVenvf07+Nzn/w0AFJKvv/5z+V33vwnHLh8XDd+ZhM3/MT21Ezbylu4wtRclwj8pPvXodp+gHY44ureWs0nufWVroPaNkT3/PcXsevgtpfZipCdHY/8348QlfnuDuq2nxfs64X78RcqnQjd2d7oOPt9Et6oWxmUtJXrVgAycWhvifJ3sxphvG4w1FbWW2lvHBXa5Qa9DffJuM9ztcBVnMWqC4xYno9ez9aVLwM2XlNhu5VtBaON98disVjuA1ix22KxWCwWi+U+yPxcteP1riaKjAM4CI1jNigJpnWkfebpoHfXEaYOtmME9zoXeeruLpP2fbz0pS/nj/74TbRaYzfZB//rv/i6Jz+R2267tTBvZR9KffiRMsJsFOuKuLmdYkFSjgVvrXUiotcL6Z1mUUjvNM1x8F2RCKr5OO6q6CqEYNesk61jqiUzV/6eeYer97ns3+FwYKf5d1lcT/etNzRitlI6c73HGgYjzWpPs9zVrPW3Nqhh0+Mj6s/JdtbdaYraWuZbKS0ppbn2Gl59qkEdxqU+bmD+nBXqk1MdoGErTVkslnsjg/72HZO1wkRlnqLIFvkt4rxIrjWx36a7+34o6aKB4fROc1/VZsCVchuTH+6A31umkYsaJ1+TONuOqjzcnXDIRBLhWEYhsddkbc+1LB98EKt7r6uK/CVSUUmUpm2V0dTOyoAAb1QVSGRJnNzqNuol0yJzTiMTobXWzEif+7kzuAi01gxVlDjAzdqawsnczm3h4SGROTejAho4zAifOdlgVjZoSw9XSBxhxOwQxaoaEeeckoFWdFXImcPHed0PvnhDoTslL3hPeiIPuj3e+Euv5o9/7v/S75pBD7v37eW1b/gDnvPCH8H1isc/Kg1WMAM/q2svH9nUeZ3+IhDILZ0Bc8x8ZOF92alZ0t+G2zhzg9d8JvZeveX13F0E+69nZf8DOH/V17B45VfT3XEF8SYDEbYqZNcJk+l8dxep4KoLL58lwT4XB54J3WBGzjIWurPFuev3SOh40y9Ttcf7Alqma9Mzqtv2ogHN7jlEHOKEA9xRd+IXCQ1QcmRfzD29sO4a8d6dWbjAtVksFstXDlbstlgsFovFYrkPMj8/R6vVrP1MayNgFqdd3PYqruPE2T0MqtuaRFjjUp7EJBE8FZQf+tUP413veR833XRT9vnKygpP/57v5k1vfANCVJ3SYMTuKHOb52tem/jrMNJEkSYM01rPk9tc/sxExAsiBUGUCOu6KqJLKViYlnSaAs8BR47j0NN1uK6Jined+gEBnivYv8Nhx4ykVerfcxzBVMtErZvSfEUneIpSyU+ueVqPByikTDXr27AdhDD76o37jDZ0909ax0zHYW5K0moIWg3BTEfSqnF8l/sl02tBCIHvCZp+MqhAYo71hG9VqeBdrr+eDkZwZFq7fryM53n4vq25Z7FY7n04dTEcmyBKD43YbTCa3p0JMxpBd/f9WDlwYyJkC3o7rhgvoDUyDhFolNekt/MKBvMHiRtTZv0YsVw7NQ+yHEFnviptlAeL5X9Rygjp0kliSYxjj+Qn78geTu/k1I1fx9r++9PbdSXr+24wIshmx2bTOTZaWFRqy8o43HifSAQarXGjEY1RD3/UR0ZFcbglHNxNnJJCCKalz163DVpnru6mdNnndFhXIb6Q7HJa7HbbTEsPBQx1xJCYgDhL8zHCrvlfXjCWQuAJWYlLF0JQPrrnjpzg9c/6f7ckdGfHIhG8v/i/xWhuIQR3fPaLvPIHfpQPv/1d2fQnfeM38Cd/85c86KEPIdaKuCRuHwnXC+J2iEoc62NhXoh6IVtTM3hxi/tRrgteJ5Ov+g3W3VLyQT6qOhnoEbkNokaHqDllyhC43vjvptlBPOCRW2zV3UP3lk+y+sWPEbVmQDpox2M4t4+Vgw8kdhsbLjtZyK6Z7x4yaFGTDBZKXjYrrUpF71I9b6Fic//SMVJt7OC+qzDHcSvV6UuUj73WaF2TRZETt8ev/XWid6ldWtHsnqPRX651Yhfbf2FCvM5+jDyupEd/bj8r++/PysEb6e66qjC/Mz2Hv2v/ltZtsVgsX8kIbW0DFovFYrFYLPdJ4jjm1KkzLK+soJTKosXTfmfXqYrGF6NZxkpn645iXeh0kNLUVS5vbxSogrvZdYxQezHiaaw0SplobCkEb3rjG3jd63630Il400038Yd//CdIp13r6HEdcKVxdhfIzey59aI7GJH//FrM7lkHv1RPOog0YaTxHAp1vetrodfsWzJNYI7VxRBG4/NkYskTl7UQeJ75r9aak4sx+UTWpm/E9oYHnealHV+b32dzTWn8mmsn/VwwOT48PeexmuAS13lBuriOMC7WPTcu9+LiQkAjOU75NkyK2gfYv38/CwvWnWGxWO59DPp9Dt12y8TPdRqLW4qvdoI+zdUzAPQXDhL7bZygT3vxGMPZPZmL2x12jeDWGtc+NqJyUTAXUVjwW2pEYZlJLBz6OAKdeO802nEL9bh10obm+nnccIAGBjN7WD1wI8HUjk3X/+WmuXqa5vq57HctBIO5A4V5wkYH7Y4HWMlggDvqm8EBuQdVXwhOeR5CSHa7LTwhUVpnDuoyAxXR0yECQT8OuS1a5VzUJ0DREA5tYUTv/LN1JR5xOFqrrNFJhO4UF8l0KZI+0qoam548pBePnOBPn/PS2hrdAI7r4Hoeo0G9S19IyUte92pufPhDiaOYt735L/m3N/45KnlBbXbafPdLX8R3fdu3Z1HltwUrHA7WeHBzJ7vdNifCLh8emmvcQ6LRDPX4unUovsfoCce27MpW6AlnYExDODSTevVaaxAmQt6IaRqBQGnNk84c5ZtOH0sbQF0BAY0waQz5lxilcLwG7re/CLH3Ku6pRL01Ft/9NxM/97uLzJy5bdP1ZPexbEKhsvWW5kn/dVeIyFpIM8AnHYQjRKEEgmbC96jyNKXu9gD22PEKA4M0xWNWdqUDyHCIUGpc51orU1t+wjVdpryNDSmd48q66gYSZMJ78pzJapLnhlNkzvvxevrzB2qfM7LZYf5RT8Wdnt9qqy0Wi+UrFit2WywWi8VisdzHUUrxiU99oTLdiHwTXK9bIH3NrHTeKVPzuUzTF5lLOSVWmlFQEyPngudenIiqtc7adtttt/K8H34uKysr2eetVpvXvf71POjBD8viy4UYC92aCfWa9Tj2Os9gpIgU9IeaQbJPC9OSmXZxP7TWDEaahlcVWMvno2pe0FnNa+Mc3vxk5Y9DeXpYs3+eUz2nq13F+qDsQIfZjmSqdenDpHTimE7j06UE3x0LyqkwH8XmOJQHFOTbnpLVCteJS16konT9skrpymAHrTVapS774vEvD1ioiy6fmprlqqsu39axsFgslnsSJ44eZnV5uTI9cxgKacSHkltQBgO042U1ssEI2Zs+xbQytadziDgqiTsYJyeMb/IlRDSivXSc4exeI65rhTdYo7l+DicytVC97hLttTPVJgjJ2esew3Bmz2at/bLSWjpGo7+S/R4mdcghkVmEJGzNjI+Himl0F5EqRknHRL/njlXPcaE5jYPIvMKxVvR0xEBHKDQOgoGKWNNjYVlrzaIaciRcL7RvSnhc4U4Xno1L8ZAjUXE+mcR255mRHk5eDNK64mCOteb8JkK3dB1e/ie/w9zOHbzi6T/EaDConU9IyXN/8WW8/x/+lds/O35nvt+DbuQZv/RTRHtmkQge0tzJSMV8ZnQejYnT3Ot2uCNcLQweLAvZAgr7Y9pfdaNuVeze57RZcJpEKM5FQ0Y6Khyd6tAA833ge4/dziOWz1UGpOTRQlRKCziPfhreVz1hwhL3DLpf+ji9Wz81eQatWDj8icrgmcpsWxCyq4KyJl8DOhNpa4TyC0UDkddGezmHulK4Yd+kOuS3Xd6HlLJ4u8F1cFeTPjO0HA+8yYvE2f/nylOIOMyeBxqyuO9sHy7h8TYrnix2m+tAol0v+3sRKkaoaFPBvu4caaC76+rxsyyZZ+FJ3403PXcp9sZisVju9Vix22KxWCwWi8XCzbfcyXq3WMvRc9M+4e0L3lqPBd2WX3UQ9EeqItS6Ehp+VRgNI0UYFadJAc3GpRVRoyjiJT/5E/zXf32gMP2Zz/w+fuZlL68VhYOo5lVak9TOLs57bjWmNyzO32kIds7KynonRbvXObzr3uZT547c5ESl4riomXeS2F0W0ePY1Bdf7Y3F55TptmBuavuxtpth4tJ15finx6d8TJr+JGf8pOO8ta69KK6vSV4eh6G16ceqOx8CiJSmN9BMTbV5yE3XbGnbFovFck9Ea835s2dYPHvGpMYAZG7QnCihIuO2S5eDgqhhJqpNhSe0zsTobN1xlIgeI9Da1OOVgkZ3ESccgJAErVlGM7uNoLsRKmbq/GEaQtE5/JmJQknQmuHUA5+y8bouJSreOAo9EaoavSWaq6fR0mE4s8c4trXxLobNqWwdIgrx+8uF4x27jUL8uwbWWzPIvNNSa/o6Yl0XxeSRiumWpp2J+hyPuoVpB50p5pzxOdBa84VgqSJcl6PK28KlUWpHeZmzh4/z5k2E7p/4o9dywwNvRArB0plz/MLTf4jhBME7j5CCr332d/FNz/4+ek4uWh1TIzxPqFWNEF8Vm8vR8JPEbj+JbldohjrCEw5+7vhc689xP382+11rzaFwnS8ES4V1GaG8uIVYax5+/hTPOH5H4oqFihtWa5QQkLs2hFa4X/VE5KOfdtGla+4q1j79QQZHbt5wnvmjn8YJ6x3+MEkoLgnZQqIcr3KPMx8m10EqbuYE5czRq7lgQVYDkV9Ma0Br3FEXqaLCfLWCd/n31BV9N5IeT513OwuJvOHh6Fs/ho5ChNYm5aP0t1c3MGEr7u4ttQuBcn1Uch+SKjIlNQrPNYHyGubZlmuDjIPKgKytCN5ho0N3z7WFdkw94GvoXPvgS7BHFovFcu9n46JFFovFYrFYLJb7BHv37mT99rHYnUaYq6RmtCAVEU10s+Ns3E0QK7L48UglNYuTz7Q2YnW5BHekQMYar7Rus61EVNSpoDnZkXyhuK7L777u9fzLv/wLv/LKXyKKTKfQW9/6l/z3f3+IN7/5z1jYMY6PiyfVGp/QpKmmKIjdngM7aoRuGPd/bQUhoDtQFWd8EGqaNfWo84xdRtV2CyGSONcisQIpdHY9qGRAxMK0SJzrCqWN07rdEJf8PJm2UdsNWHfMgiSKvd249J2vUtTHn+eNg1onIo4yHctlx38Qafojs5Jub/MOdovFYrknI4Rg1569LK2sooIgnViZTwuJyMU4J4GuFB9GW7hva2WcpmIcA+tEAd5gBScRbj16RjgPR1kd2EZ/GW+4RnfX/VBec/L6pUN02QPYp9YIDn964mz+YA2vt0zYufgoWREGaM+f/Hkc4Q3WiL0mcaNdnSEnoAWdhUzwyYRrIQi9VjEe2HFR0i2I3UJFBbFbYJyJsRCZC1kIQUd4KKXp6bGY1pAOozguiLy7nBanol7B1bysRgWxWwhBR3ocP32St/7ATxMNRyxcfRmPeNZ3ce0THjHxmJQfxee3IHS/4I9+nYM3XkdPh7TxuGb/Qf7xX/6Z7/qOpzHo9yduq71jjm951UvYf9P1rBDi5SqE11UYLrvSJ+5DrnZ3+l/B+K9AIOhIl7YcR7hPaY9Iq6wmOsDt4SqhVtzQMNeiEIKr/RmGOuKOcK3QLicOeeS5E3z1+VO044jTzQ57wqA48CS9njKhViBVbKTyJE5ea9Af/0+010A84pu3tL9fbpzOzMYzqBhZSomopXI/S/6+tAIEyvHM79KFODLv0tkyJmJ8NL0rS1nwBms01heRuatHa2UG7WxT9BaAG/QIkzak7Y29JnLULcxXu+YJyRcbsa3Y7wtAaGUG9xQEfIW87Ab4zHu317rtfMHatGGYQVyJs1xJH+V4OMEgE90FGhkOifP3WyFQjo+Mhrm/bXPOEU5+9ZVz5I3Msyw/cEwN7XcHi8ViSbn0mYIWi8VisVgslnsdc7MzXH7ZvkyUzPpHAJUI11Gss9rGk5zHkDqCx5/HyvQrqNzPpHTtINQMQ1Vw3KZCuyNNHWgpx6JunTP3YoOLvu3bvp1/+/f/YP/+/dm0I0eO8JSnfD3vetd/ZtuISz2a4/rPujamvdWQdJrjHZ/pyInO60nicBrfXSaK4eT5mLMrMedWY04uxpxfUxuep3R95fanxLFmtadqtxfGxfrgYM5rwxPMTzvsmHGYagnCGILorjlPk66hYjS5cX/3hprecPPjsd22TeoPjHV9X9ow0HQHimFgfroDlQndAK5jv55ZLJavDOI4Ho9Oq2XiTdy8eKgYtMIdrNNeOsbU2TvonDuM3100n6VIB+X449qoQhA3Ogxn92eOO7M5aRx2uU1JFdNaPbXpvgxHI4LRaNP5nHgToSypoZtHRCEizonE6+c48Pl3MD2hdrBQMd6wa0StcIhMXKgmsleYmsoqwht2aayfp7F2riS2GdxwgMw74oUgnFogbEzl2luzC8JEmKvSQ64jvMq8jZLzXCZCdp6oRh7WaE586ouE/QFaKRZvP8LbX/Gb/N7X/yD/+Suvp3t+ybiec20IdEyUTFs8coI3biZ0/+Gvc/UDbsh20xWCK70Z9u7dyz/+yz/TatcMIkjoL60QjcZRyWU2uuLTIRka49L2kh83kTUVafxxKnSP/wfQUxF9Nd4vIQSedCrx5keiddbi4jV7pTdTOGbNKOTFX/o4Tzt6K5f319k5GvDA1fPs6q8h89dyEluuC85zbQZGqETUS8Q99an3oKP6435307r8ug3TEJrr5wtu2zKZ07ZMct/R0kE5rpkzuX9pKcZ/e0mNm9hvM5zeRdSaIWrNMFg4yOrBG4lyJRwQEu14F+RBFlAR7c266vfoYlnd9wD68wfu0uredQkf6tQdW19BWrN7g/O7XYTWOMEg+xswEwWx3ywcCwGFGPl0Pi22knyla34rDQrvTG+90RaLxfIVju1NsVgsFovFYrEAsGf3Th78oBvYv29XRfQuY0Tr0hfwxAWuS0JfFBfFwzQa3XOqgqUrwXdM9166iBAiX46t0i5Tn1kThEZILNeO3gpZH0iy6J49e/i3f38HT/vO78zmCcOQn37pS/npn/4porLSDYQR9Aaa4YisU7LMzhnJ/JTAkSbefSMmHfs0wjsv3E61TCfpMDD1vpWCpgfrA1U5TwDtdocbrr8Wz/MK682z3FWMQljtmeNbaBuMe2Nz5NuUDowwNdrNYAnjBDeDIcr1rreLEBsPuAAIczHn/ZFmcV0xCscbDkM9UdhOr+eN2Eg7TwXv/CyuMz4eo5DKgIldO+c23J7FYrHcW2g0qvHgMhzRWj5Be+k4zmAdr7fM1NnbmTn5BaZP30Jz5RQiGiF1jNQKqRXacYwgrDVSRTR6y7SXjiPy4kcSb5u/32rHJWiXXNZCVmoNu8P1gtg8CT2zY+PPEYSNjUUHd7jO7Kmb8XtJnLRSyHiEEw0RcYA7WGPH4Y8jtGLuxOdpLZ8obUQjB11i1ydozRC0Z03EbyqMSRftuGi3gREjI6SOcaIANxggcyKkAJxwiCiJYlFrGpVG7pZevmIhiRPBsxywLYXAK3Ux1jmay3kx5WWU1gQ65tonP5JdN1xdbNtwxM3v/CBvfNoL+ONnvJgP/fM7iOKYUMfEyZrPHDnOG579UxsK3d/7+7/C3gdcUxhYuKoCgiRpYGFhge942nfULp/sBP/0kv/L0Y9/zvyqNZFWhDomVEZ0H6mYvgrpqZCRjpDaRLE7mAjyJg6uMGV+hBBIIXAoy1ii7lWLnoqIVPEFwhGCuPTO8qHBaY7l6qS3pYsnHKJE8HvKids52C/WR8/WFwWVgRk6/RvLD0hVsbku03mHPThzZPKxuxuRjRazD31CwRWb4g67tJeOTly2cGS1Sn5qM4YQWpEMOzHnszToxw16zJy+pSBIa8elu/Oq4nZqaqNvlXxqxgVT/kJXQ2/+IFF7hv7CZfQXDl78Nic3pjqp0YG53VtYtHg+LqULvV7Irj5nRF05ji046MuDHVLneIbj0jx4LRaLxWIx2JrdFovFYrFYLJYCYRjxxS+Na9oZMXn8efm7eZ3DNow1QVScx/eMCFwpX6c1jiMyB3fuk8LvShsR19SXLq6jNzRR0AIj/DY8UamZbbY1eT8mffbfH/ogL3nJTzLKubp27NjJH7/xz7jsssuyabEyQrfnwFS7fkypUqaudRSbdta1sdgmnbUr/W8qsApBIRJ7tadY6ZoOTN8F30sGLGD+7TpmHUGkmZ+b5ab7X8mhw0dZXlkt7LcUgijWnFkudqS2fONGF7njkzr280hpzk8QVcXcdBtKGaf1jhmnEL2+HcJE8I8n9Oc1fEF3oArXodkPwVRLEkbmXDhyck3vjeLXJ9U0T3GMgQel8nHxmmFQL5L7vstDHngtjUbVHWexWCz3NpaXlzlxIhFrtWbm9K20l48V6pnGjkfUnCo8dCOvRXfX1QUHpgwGdErCr6m5vau4URWXagsrOotHC1HAIo6KrlVgbc91G0eZI7ji8stZ/d93MmpMoYFGb5nO0jG8JBp4MLOXxSsegvKahejv/D5MnT+MVCZwurdwmRGohTD7qmJ23/pBhrP7GMzuQQuJE44YzO8vinM1McPG1e0UxWmtaa6dxQ0HhfmiRruwPi0kUbMo0rvDLu5wndhvZfNqoOe3CV0vOSLVGtOL8bAQWz5SEd1ctHmkFZ8dnS/IVg6CWemz1+kghWAlHrGmA0KtWFMBayfP8JE//Gvu/O9P1ArYjudy1SMezONe8P0A/NlzfnpLQndbuOxwiuf8a5q76UiP1/3O7/LmN76xdh15hBR862tezmUPe1DhfUFrXRkMAEbszif6aKrzaa0pD72oE+gcBNOOj5c7B2ejPk3hZtMCHTPUMY9t7WOv2wHg37pHGOiIloZf+dT7aW0w0CN2vMrfhRl4Emd/U8a1LAvOW+fpP4PYf7+J6727idZX6L//7wj76wgV0+gu4vWWCaZ3EjZnsjIHfnepcO8oBWJn09Jay+bfW3+nHczsYbBwWWHa1Jnb8Ye5AQhJfeftEnmtwrkTcYQ7Wi+0P3MJ17XZvKxvGKPeW7iMwfyB8QQVs3Dkk7Uu7ItFA7FfTFuQ1zwUceRziN5qdYFKne67Di0EUaNTbFs4xInzNdJN4kihidGoWGNcaxOLnrvnhs1pnChAxqG5zzsuCMlgZg/B9C5mH/Ykmvuvuqt2zWKxWO51WGe3xWKxWCwWi6WA57nMzozr2glhhFIpq508UN+H4JbmVRqGgRFay5ja0FQ6CsuOcCkEriNqxfVUH2z4Juo8UmMncdrGC+3rePRjHst73vt+rr/+hmza4uJ5vuc7v5W/+eu/zKY50ji2GzWO7cFI0RsouoPxwIFoC31BxtVu1pdGwKeUI81nO5Jdc9LU7s4ZCjQwCnU2ICCKYWllHa01vl903mltRPuwXFAd40QW6EL/Ud3AA6XMvqkNnNv9kRkMcW41ZhjUR6VvhEoGAQhh9jU1zUhhhP5OU+C7As+tnothYETyIImajxX0hmZ6ns3qjNcJ1gJz7bvjEn6l4yVo+sbhncdz4Oor9lih22KxfMUwPz/P/LxxVk+fvZ3O0tGC0A3gxCHusFuY5oYDmuvnCtOU3yIqiW7ecL36YC/ft4U04kGBkrgoJMop1ceOw1LcrebI4TvpzexBuT7a9RnO7mHxiocy6iwQNKdZOXCjcfmFw7EjNn35UIrOuTvR0iHyO8SNDn5/ldhtELVmiRpTRK1ZTt70VFb335+wPUfUmmE0swsRh5WY3DKCxMlZGrUXtGcr88mSuClSl2oOJR0Ct5GJLkMhWPVbmdBdPYoQa1WJJJ+SHnNyfGxPR33yb4cS4/5eVyEnoy7L8ZA1bYQ9T0g6wmVh/z6+6ZU/yQvf9Ra+4ed/jIUri+7ROIy4/UMf503f9xO86ft+YktCd3osANrCZUb6tIWLg2ApHnLo5DGzjCN55DO/HbdZTSkA0Erztpf+Goc+/tlCio4QotbVHlEu01Odzyxb2g7gljKDFJquCjOXdjpfX0fZNpQ2bvcvBssALMVDBsngAz8KNxS6gcrfa7LT42tGK0SsiuJmexr2XLHheu9u3Ok5Osc/z9yJLzB76mbcUY+Vyx5Eb+eVBFMLBNM7Wd9zLSsHHzhOOaD+O5BJOlLbFroB/P5yZVpl0I0QsP+aba0XqqkNpmRBUboW6ZS686ziDYVuoHLvRjqErdn6mTdBI1DSJXY8YscbpwjkV5+WXUhe+tUdnyIORpNrj6ds87xcCsp/O2FzmtjN30e0SeFIB6skEesijkDFZmCS3wHpEPstYsc1NeARZiDT6mkWHvwYK3RbLBZLCSt2WywWi8VisVgq7N+/F5nrIE5rZtck/5mR5hV3r6DVEJX+BVO/u9otURYO4zjrH94SrmNERC9nplLa1Jauq9NcF+2dUtcnMjU1xd/87d/x/Of/SCaCKqV47W+8mh99/g8RBKZDqeFDXdnlNM57s+1sp02mDcXj2W5I9sw7NLxNhNpY8dnPfZGjx88Q1wjbdQMK0gEL5XaZOurV+ScZtlWupnkUw/k1xbmV7blAiv3+ZoBD0xd0WpKGL7MBAs2a46CB1b6qXHPp4IM0UhRIarNPijmvb1u5RG31d5M80G5AqwFTLWg3Jd31bnVlFovFci/mwIEDXHFwP53l4xPnceKwEiNeJwKVXX1iYoxwDqUq8bFBcxbljEXboD1fdEQrhYwjZDiq1AYPW7PjOuDJtpf338i5q74W0DhBHzfo4w7WII7I6n0I6O2+H2Fz2ggc0kUIQXv1dFZzO91G7LUKtZEFIFS46b6molth971mpVb3RjWJU1ZdlztbLQ77Hnf6Hkc8lxVRXO5E2OVcNMjeQfo6QuYEWReBIyQd6TEjfY6FXc7Gg6StRuR1cl2SPR2xqoovGX6upq2Ukvs/5bH8wJ+/lue97U944Lc+Cb/TYitI1+EZv/8qrrnxBualz7z0mZU+l3lTXO5Ps9/rcLk/zbIa0VMhP/yyn+T5L/tJfvMv38xPveSneNFfvQ6vVe/810rzjpf+GksnTxeFbGHqbJfPWkixvIxA4JYk73pR1cyX/x1gmFyjgY6zbQWJqB4kgw/Ox0NGKuLzo6Vs+b7jMqhJIDBXbBL6nLp74xAZBYgoQKoYoWKkUkilzCALNR5oIR/2FETNeu9x6PF/1vZeh3b9yixxo0N31+Ziovnb2/6I2rrBBKIciT2/F/ENz4bW9uoyCzRu0DPnLBggVZS8jNZJ2HWC9+ZfUpz8vStd0wUIyzpZTkvHpFxIB+X6KMfP2iowdbudcFhsazLv3YlGFO+9ybMpS3USkvW917Jy4P6M2rNkF5+QqLQue355FRP6bbR0EHGIiIJE6NZJMkmEE0fo9/w56uQ26pZbLBbLfQArdlssFovFYrFYKvi+z+zsTGX6JAEzL3gbcc+I452GESF9FxqeoNMUtbHVqaM4q/udm15mkuN2qlnv+q50NEaacytxtQ71FvpnXviiH+Mv/uKtTE+PO50++YmP841f/wQ+/7nPmrbVrMcvOYx9j1rXMdS70E09x5p5J7SzvL3K555gGJgO0liZ85ouIZLly+5jgNX+2BGdtguMq911jNDvSONcrlse6h3RQcxEUXmrlAcTaG0GXXSaNe6qUmpASlgyOSllftJrM0/d9VI38CM9dxXDYZJU4CQiSxTVu9EsFovl3kxjCzWxyzVPK4IPUH7iKenU3ojzc2np0J+/jDgRtyOvyXB2D+u77mdc1X6bwezeZGYNcYSMRrhBH7+/gjso1TMWgsjvIKIIJw5xVISjY7ywh5PVGo/xoiHN3mJhP5TrM5zeNRbLMcJza/VMxYWYF+OhXsiuYysyU6UGrHBMBHqOtnCZFS6hEMRCsKJGHIrWOZ7Uf16KhwQoltWIc/GAdRUwTGoESwQuohBxPiVcuiUhu+6JH5emygkvZq3ZaZ7408/n+e94M9/y6p+hOTO14T4fuOkG9l1zBb6QuMlPiOJQsMpQja9NIUy7p6an+aanfxdXXns/XCF5+MFr+YG/+M0NBe/3/srvVzpY09aX97Xi8BZF4b8cly0ZD8RLZfH08xCFUoquyl1rWhuHd24dHx2c5Uyci7SXko/v3F/YppIOyvGN0Oj6aCGRKkQmNY8lGhynUI84k0+lRD7qO5AP/fraY3RPQ1x5IwBBe27DEgZBZyG7f2y8wu23QTleYTCOiCO8wer4OxCgl88Q/e1r4NHfCbNbqE9dapIb9HDyMeiiGop/ob5nJV1kOKS9eJTp07cwdfYOvN7KttcjAKlVtfa1lInIm5tXVwcwaelu4kHnkrm7I6/Jyv4HEOYiyaVWuKO+ec5pjYzC5PugJHZ9Vg7cSOS3kXFId+GywjMAIZJnmdlX7XggXbxggBMOkSo2x0arLC4/o7tC9M+vQ524/ZLsm8VisXwlYMVui8VisVgsFkstM9NVF4HpbKufv66jQQiB5wgansR3BVKIDePQy1HdSteLknUYUbG65rL7ebWniGI4txLTG447HE10elXULPOAG2/kXe9+Hw9/+COyad1ul+c+5wf4g9/73dp981yBn+srK4vRqcC90abTWtjj/R0vW6bh14vj2efe2B2ttTl3UpqBCFIKhmG9Q11rWFwfO7PzpJHrUhrXSKzZluO7O9iijZ/6Piuli4J5+q92QzLbkfjuOOq84dUPuhiFOnO6a62zazGNZs+vf9LhjWrMhungj3QwgBkQULxeG359TKrFYrHcm9msJEQyV+G3stgLxh2XdzyHrZna2HKS+Ns0Vlh5DQZzBwia0wxm9oIQaMdlfddVxdrgQuBEI+aPfYadh/6XhWOfZtedH2bh8MeR+brXXoPRTEm0hspDXGiFP1gttk9KwlJ9bKkinKBf3FdZ54zd/F2o4s2Mo8K6NCBUXBh8EDfaaMdF5Y6tIwTz0mMah+V4SD+Jvj6vhhwKVwsO7BUV0FebxGELwW5nay5srTWRVoRaESnjgja1pyMGccDiydPc/pFP8Im/ezsf+N0/5Qv//j7iTerCHPvUF/jtb3o26yosuKojNEfC4oAGkdRezr8LdqTHvr17+NoffvrEbfQXV0CAt0XpsCzspyV98gM+U4qObjOgIP93taIDgtxgiBBFVFrLGdVHYs6tIwQazb/sv5ITLTNQQEvHXCu59aayeuXKk041MQAQNz12s92+xyAe9hRw3EpiRHVGYWrXb4L8hh8Cr2H+vlScfvkYz6D1OLYqwQ36zB7/HM6oB1rTXjqeub3N/ycjJcMR8f/8KzzzZ6G58cCOSvPTbW+V7D62+TJe0GP+6Kdpr5yk0VumuX4OR194vW6hVSXSS0unel8r1wRPhOWLZZxqUI8Sku6u+xG1Zljb/wCi3HUhME53JzACdXr+Y8fD66+w846PsOuOj7L7jo+Or49sWW0GkKR/U0IgtDKx7aUSFpXjEUfEH37bRe+7xWKxfKVwL8iWsVgsFovFYrHcHczOztBo+IxGRTeOFKAoGZFIanpvoVPbxE7rLKY8i6hL+nTKfTJRDK6jC+vOx0yX21ZO5dYY168jjXg5ytVqXl5XrPVgdsrJlp/kSM7Wp43z/Q//6E/4u7/7G179a7+GUjFaa978pjfwwf/6AG96858yM1N0xjd9iedogkhnMduTj1HdNFOfWmpdcDErbaIQ88dHCsFMR9IdqEJtcEdCpylxHeNwTwlDndUaV1ozGJk2NjxT4zvVeBsuTLVkbV3yPGnfjEz6n7Q29dpTB7/nmIj5POsDjesoOs3NO6zSvrjycQoi8ByNI0Hr8Ye+K/BdhzBpA4CUmsGouu7+SNPwNI5TP3DCrFtvGLEfKVOHu8xGfx87dsxPXqHFYrHcS3F37Ae/SeA00NLBHXVxcrVkNTCY2Y03Ws+EHiccMXX2Dno7LjdONyDszBM1OrSXT6Bcn6Az4Z4pjBw4/jdox2U0vYtMPAKQVUE9bnRYPfBAdhz6KE4UIIDm+jl23vm/nLvmUVlbtOMStOdpds+PN0vyTpJ/FqsYGQWFmN24xkUq45DNJaItvF9phVbCvJAlx3I4vQtvsIo76hkRRQicZHtBew6V1pGVDjouSj2zwslqPKf0VESndOwirQqR4/Vikai8s2khUErRX1rh/J3HWDl2isWTp1k/u0hvcZnhyjrD9R7hYEgchOit1rapIRqFaKCnQqaklz2PBzrii8Mlrm3M4SWCmRCwHAfMSj8blHbLu/6HD77uLRPXv/dB1yESEdrRRswupAxQPINqLGcWZsrvocAI3TJxdOvEl28GFKpsvSqZnkabV+XyLFB/vD0hCLwGr73/V/PkU0d5yrmTG15h5fZr4SDy10Ycog9/HnH/r91gLfccxO4rkN/2Y4gP/fOm85br3Nfygb9BDnvj9WPeN1MXvFDGHa9VnBM2BVLFTJ+5jchr4wW94jrz74zhEP35/0GU62Rvhwmidyav63Huw1bk8a2URNguQsfovC8vc6KX/5ryv1ZHC6eDMfL7o6VjBiPUbLcwuECT/a2lKCFZPfBAhI5pLx4FrQlac7jBeCCUGVhQXL8/6uGPiteFN+qZv+FELK+Ls0/XJ+MQJXODYVNhP3fs9ak70N0VxNRc7XosFovlvoQVuy0Wi8VisVgstQghuPqqKzl8+CiD4bAw3RFFoXlrzq3iuo24rSux1uVVaW3ipR2pK4J6/t86cRJrVV1n2slX108aK1NH2oi729uX7/me7+VRj3o0P/ScZ3Hu3DkAbr/9Nr7uyU/kNa/5TR73+McX5nccQatGRM2L/Jtt3jjYdcUBLykK3o4UzHYcotgIs0KCl9u2lGPBNlYwChWeKwpR3lIKfGmc4GUROj3/dccr37Z0EEMcmzY3PMFsR3JuNaZsxlrumgZtJHgbB35x/XmixDAhpa60LR0M4Tqm/me7qRkFxcEDnmuc+BOdHYkVPu34zc+XDvowseVbv45279rJ1NT23DoWi8Vyb2BtfY3zVz+CTALQiubaOabP3IpUMcPZvXT3XIsz6mXTQOMN15g6ewfre68fi9auT2/+IDjuxg/L2hFjcvN5gKg5xcqBB7LjyCezaW7Qp710nF6ufq/yGibGdzNXc50LsUTFya1VQVzUgHJ8E+G7gQwlMGKRUlnVZRCCsDWLjEJkznUpVDwWutPtCGlqMCe4QjIrPJZ1LiJ7gpAK4Bi5F4Xi2LnTfPTWL3D48BHWTp3h7KkzdM8vM1hdY7TeI+wPiYIAXa5Bchdx3RNMGk+gFUvxiHmnkQnZS2rIZ4bneUhzF07isI7RdFXIjOPzX//xLv7+l147cd3N2Wke/zPPx8lFjGuta49VnvT8pm5zBTSFw5T0cYRgpGIUGk/IrK2hVvRUSFiq+11cr3k7KW9doRG6+H4SOh6LrfYmQynKbztMiNi5cFfv3YG46iaae66m9663TpzHCfq4peSFWsolD0jOb3JMRH6aVmgx/puXKsYbdeu/AOW/56ycM/XQtyK+p8uk/7+BkJ2eXVGado+g1mUuisdGK+N61uPBINk9Nbk/a+EkzmgBKqo5FrmBUIngnf9UasXUuTvwRqUBCdWWbQkByCgslASoJan/XbgOhECUD0lYM3rXYrFY7oNYsdtisVgsFovFMhHf97nuumvodnscPXaMMCzWNpyE1lWhcasIYQTHcv3kWAECarTiAo4UiFwE9ViAFEnnb7XbZBhoZtpiS20uu88PHDjIO/7jXbzi5/8P73jH2wEIgoAXv/jH+NZv/TZ++ZW/gqzL874IjIlhfIy1NiKuELoitLqOAKe8/FjgTeeMYyNI1/U7h1H1nKYO+a0OEPBcwSjUtBsm6nz3rEN3qOmPFFqbz6eagqa/8bHKC92pmSMTmNlY/5DSXEfpPI4UtJsCpUyncOHYTXBaxHFxG+k/Hcmmjv1JdKY6m89ksVgs9zLWVlc4cfQIBQlASIaze4i9Bs21c6zuu97Evfpt+nMH6CwdJWwvEHsNhFY4oy5xPvrb3UL93ItkNL2byGvihuOBfs21MwWxG0A5m4vduiSye4NVEy/umO44EYfs+dJ7WLz64Qxn9xlRSmu04xuhRisjSktpEktUvKHgDSSieH6CIGq08YdjQU5qZVznXt41SFXTzAm43dU1Tt95lPXjZ1g5cZrF02c5d/YsK8srdNfW6Pf7DEcj4mjrYtyWEQLHc3EbPv5Um8bMFO2FOTq75pneu5veuUW+8E/vmrj4re/7CB/+07/nEc/6LkIU6ypg1jH7roGuDjkb99nndhgmAmWA4v3veCe//fOvnLje5uw0T3/ra5lqNLL3h1QsL+Mg8ISRxBUmqj3Mebl9JAtOk1Yi1E1JD53U307X5wnJrPRZVQFh4u6se6/dSPB2cleHcaJvI+Y6oyp+i4PXX8B67j5UMGLtE++ZPINWdM4fuaht1L4V1sYTleXm4icAstVBXPsw9M0fuajtb3Xa3YKmImSX2yZVhAhVlpIh4zgZzCTQOjb31vT7kXSL6xMiKYmROKTTL3WJqJxtS4jka8B42mZC93YRKqo8Hyrz1E4t/e01p2Bm4VI1y2KxWO7VWLHbYrFYLBaLxbIpU1MdOu0OK6urW5pfYxzWIhEPtdZZX0PZmS0pupRFMt1zjfCaJrWJCbW+oapLSjGuWZ3vS5JS0GoK+sPiAsNAM9Wa3NG0GVJK/u+v/hpf//Vfz8te9jOEoXFBve1t/8rHPva/vPlP38K+ffs2XEddhHsdWmsGoel8aXjlz7a2C8PEzezKaidpnV6rtIkIT7cXx2N3tV9jsJOCirveS755pIKwlIKZtmCmvb2BAOX1ggmsLbc766QqXW+eW+P4rtlpU2e7XvyvO0/GXX9hrK2uMTM9vfmMFovFci/i3OlTxQkqxg36yDhCC8H6rqtMGY4kDjlsz7HmtytirQxHJgr8AgfRbRshiBpTBbFb1NSiLcf4asdNBJPkIaEUjfVzjKZ3orwmKMXsyS/iDbt0d15J7LeZOX0zzfVz7P/sOzjxoG8mmN6RObK1TGppJ8K4mSarbvFyu2qmpeJ6aSrd9XXuvOM2Dt15iGMnTnLq5EnOnTvL4tISq2trrHV7BHelgO06uM0GjXaL5uw07flZpnct0N67k9mDe1m4bD/zV+xH+G6lDjVA9+wi//my17B4x9FNN/ehN/wNCs3DnvWdDHTMdOK+ToXkc9GAPU6bXjKA4aP/+V7+5BW/OnF9qdA9Oz2NBkZqHF5uYpBF9o7lIGhJFycTtxx8remqINuvAMXxqMtl7hTNRPAWQtDGpavDXNkfQUd6rMRjN+ckwbsu0rzMnZ1Z849CfaKyEFtadykqSVz3NYjZnZtu657E2qc+QLh0pvYz4TWYvf7BuIc+dsm3WzhX+Vgnrc19RpvflXTRcizIxqcPIx70eDj6ReivXfJ23ROQOkbHGpWUjJgUIS+0wgmHSRrF2P2tRFp7PlfnXsVF0bzsphYChAPaxMznBe+yw/tSIgAxPQ/rSxPn0UImd5LccqUvQvKmxyCcu34QmMVisdwbsGK3xWKxWCwWi2VLdKbaWxa7BaZusSHpgNAarQVNvzRvTvBOhe50uuuQuZLH8dWb17zeiLmOJIziinM8CKm0rQ7TPl0RPLWGJz7pybzzXe/huT/0bO68804ATp8+zbd881P5+Z//BZ72nd9ZWV/qmFZaE8fG4bwRYZyYEEj6ZxiL3FvRAbTWWb1sDTR9gUod0sk6IlUVeXtDs88ND6JcYfRYGcd0HkdW0yyFEBVx/kKo69CNa4Tm8sCKfDu2irnOqseirg1am2tcXoAYU65jarFYLPd2giBglCuBIsMhje5SwZXsjXpEfpugPUdaT1p7DYgjRDyOzhZaGRfcl7FDX+bqigME7ZJzTmvCxhRCrSGVkStHnQW0kDR6S8g4xAkHyDjCXTpOf3Yvs6dvwR8YkWrq/CFEOKIxNL9LHbPjyMc5feM3jLchah7sQqKprzub0h8MuPPOQxw+cphjd97JydOnOXPuPEtL51lZ69Lt9RmOhoW0nkuJ53k0Gg2mpqZQU038+Wk6O+eZ3ruL2QO7mb/8ADuvOIjfNs7MhnDwhCTIDR4Y6bjgdY1LAwuUUnz0D/6Kz//dO9A58cfxXPxOm8FKvRj4P2/4WxTw8Gd9J4GOCXPXY4RmMR4Sa8WH//O9vOkX/r+J+9icneYZb30tjekOEbrSPiC51kXi5Dax6FPSywRvKQRT0mdFjUVrDZyPhxyU49ImQgg8LQlyLnBPSCRi06j0zdBas3PYY6Rj2omwmMZAjyOWE5ds6nJVuZGoANc8FPENz76odny5iXprjE5Pdm3rcIQY9rY2CnWbGP3UCLTp+6RQRugWuZmEiohFM3Mq67NHCN/7l7iPezri8Ofg5o9e8rbd7SQpXDIOjfgsJMpxQINUYbG+tVaVgVEO5vuHchtjd7fjmms2F18+aduVkce5ePRLzuxO3Gf+HNGbfw6CYe0sg9m9jKZ30V4+buL0VbGUhbz2oTgPf+pd0TqLxWK5V2LFbovFYrFYLBZLBaUUi4tLLC0vE4YRnucyGgUbzG/qP7vuWKgWoigID0dGDBSAX4q+rqsDXt2G6X+IYnB0sX73Rq7oclKglILdcw79kaY/VFm7vW28Gac1x/Nx4Om25ufn+cd/+hde+5rf4M///C0AxHHML//yL/Lud7+T3/nd1+O6440pDaPANN6RG0fAG8F/vKNKFcVxpTVhBK47WXTNGwJilTiOksED6fFvN6A3rLqoR6HGL9WzDmON61TPp+sY8b64CnFREfdghPWykK612RdHptvfnqi98fbMtQzjkMkorkmgxESca1mNkt8MG2NusVi+4sg/lFVcEbpT3KCPcjyi5ljc046LVlFB2BBxlDj27gLZIY6M2y9XxqK380qc07fiREOUkPR2XF5cRgiU32Lo+jS65wmbM5kYH7TnaZ8/lNQfN2L97Olbaa2NXaRCa9yoWGe1tXISEQVodzzyLvXmDodDDh8+zKFDhzh+9DAnTpzi7NmznF9cZHV1lW63y3A4JIyiu2QAleO6+A2fZqdNZ2aamfk5rth7gP1793H55Zdx+ZVXcuXVV+F32lkMN8Anh2f52PAssiQXld9RfOGgNYQokwaUTE+fu3kp+dRnbuZdr/gdhiVB+/JHfBXf/KqX4Louf/6DL2XlWClZIOEjb/hb0JrHPefpRGiiRLj1teTOeJUPv/M9vPOVr594LJqz0/w/b30tzenxNStLbST5vezLHOmYds51KoWgIRxGueSAvo6Itcq5wJPjVYmY35g6V7emODDvwUtneM4dnysMGBQYoVVpXUoEEEYwzLtfEcjHPR3hFeu/39OJVs5tPk8QlKsAXRIEgI4BmYi76USJzom3AnDCIZFsj53KKib+9HvxHvJk9JdJ7L7w3KvtbYNSpLdyG4UyC0o3kXGADIfmGp2wLqliKJdokBK0LA7SgOrLvJDJudkmNz7GOO43cGmXEQ/5ekSzg/OtLyB+2x9CMCh8PuosMJzdC0LQ23E5s3v2484swNmj4DWQ1341cs8V22+rxWKxfAUjtLURWCwWi8VisVhyKKW489Bher3+xvMl9mKlxqKo545FvrETG2KlGeT6dKWAVgN8b+vBz2FUdVMXt7f5Osp95ErpQg1oR4KzWVHwEnGsM5e1U3Kcf+pTn+JFL3oB/d64ztvM7CxveMObuO6665J2awaB6bRp+vUiaRoDr4FhaAYWgDmO7ca41nj+GJka0tX1KaXp5mLcHQktX2Rx8/lthrERdoUAzxHZ8Q5CTRCN53UdaHj1Nc/zEfZaG3G8sY3zXre+IKo/31JM3u9LRaw0o8Rw6MqaCHdZvQ42wvc8rr/+2kte191isVjuTrTW3H7zFwmDAHewVqgXXUZJx3Tq5xBxWImwjb3mtsVuEQVGhE6XUzmXuBCgFY3uIloIgvZ8IeLWCfosHPo4a/vvz2h610Y7W2lXa/kEXn6ftWbq3B0FgSbur3P4xEluPr3EnWdXOby4yu1ilvNLK6ysrtBd7zIYDgnD8C4RsF3XoeE36LRbzE512DE/x+4dC+zfs4t9V13HVVdfzf2uvpq5uVkiNLfHfbpq7Ljf67TZ5bYK6zwZ9ZiRHlPSCPafHp7nI8PTCCgI3kIIHIzvuSM8GtJBpfWptS7UskZrAhTRcMg7X/G7HP/oZwrbbM7N8NRX/iSXP+QBWXy4jiLesoHgDfA1z/1uHvqspxXE6Nve/T+8ZxOh++lvfS3N6Q4SCsuqGnm5PA/AjPQL7yhDFdHXxWv9Km8GLyf+jXRcEMQBlqNhJdpdF/49OcRcIhBa80uf/W92THCVakA5pfIBWuHkUhcAxGO+C/nwb5qwpXsmo9NHWPnoOzecZ+YhT8B7xx+MI8PT8jiXqA2ZwFs4vrpSHiF2vKJwC7g3PQ7xsbdfopaU2pQE4BfaiC66qreBEpLB3H5GUzvQjos76tNcPU2jv1zZbjkqSknXlIDIIcMhTmmgUN1+xH67eGyVQqqaNIvy8S+PqH3QE+CWjxqn/yQe+FjEgWvR7/zTqqBeg7jx0YhveM74O+xoQO/f3wDLp9HCYTS1QNwoDoRtX/tgph/wNZuu22KxWO7LWGe3xWKxWCwWi6XA+cWlTYVugLryjUqBk/QTp+5epalEhqc1oH2vPN10d9S5kifVSU616c1qXtf1j1ecucp00Eunvg21602MAnX65kMe8hDe+97386M/8jw+/elPA7C2usr3Pv27ecELX8Tzn/8j2XHKR7iP21PdIUeM3UNKQz/QND2z/fz+x8r8lI+xlMVa1LGC/kjju0a0zvZLCHzXxJaX2+XIYrui2Ij+rlsVslMXPMByNyaOYbaj8b0L6y407TJCfL5kpKD+HFxq8oMjImW26yVmw+06upUWXH31lVbotlgsX3EIIdixazenTxw3kbQbIJOaqkVnX/FeuhWZRUQBThQQNRInpIrpLB5FuR79+YMgJDIOEVqhtUJJD2+4aqJwNfiDVYLOOK489tucu+4xFcdhzc5m/4yiiGPHj3Psi5/l+O23cOzseU6dW+Tc8iory0usDUb0RwFBFGfvPJcSx5E0fJ9Oq8ns1BS7Og32zbQ5sGOOq3YvcPX+3cw//mns3DMeXCCjEY1e0ZEYNGcKYouD4Ep3mhNRj+UkdrscoZ3uz5oKaQkPRwhOx0Ygys+ZCTzJev1crLdWmigndGttfv/CP7+LD7/uL1C5F0ohBQ/8nqfyqBc8A9/xstrbaI1yJN/9Z7/G3z3r5axOELw/9sa/RwNfnQje2xG666gtccJWHNhFjBBdXLAXh0kKkpk4K30ub05xKFxjKandLZNBi5p64T2PQnN1d2Wi0J3uj9AKLZzS1BLhxsLjPRF/1wFwfYjqU6uE4+Id+hR61C/WeNYa1MZlBLaKuV5KJ1oIM3YmP19dRP70/CVoQZG8+K51EqeVifEicZ1v/55lTOsS5ZuBMWF7lrA9S7R8gs7SsfE8aLPdfKKBilAqLpwD5TaQ0WjDc2DSCeJiMsFWTlr5nux4JrVgg78TAD7/QfThzyO+4dnoT7wTzh+fPO/eq5FP+aFiexstel4bdl45cbFw6fQmjbdYLBaLFbstFovFYrFYLAWWlpY3nwkj7OW1WFEdkJ/FkzsOEBY7EMLIuIxlLkI7ToRE4VSjruvEbKVAivG8dfMUB+wX1ytEUfgFs08qAtfZWm1wKQRaTI7mbjab/Omf/Tlv+bM/5bd/+7dQykR0/v7vvZ73v/99vOENb6LVatUK9XUdp56bxGjnjkF/ZKKzvRpXel1seNMX9HLubqWNY9zX4JdqhpcNa1prIlU9bhpzTn23/lgE0dhFv9JTeA50WrKyva2QCvFpeoAZKDC5zZeS8viDSa5+0476Y6G1Zn2gGIUwGIY0Gveu+E+LxWLZCgs7dxFFEWu9jd8rMldfDhkMICdUyDhEqoioMVV/g9cKb9hFqggZB4TNaVorp5A6RoYxrZWTjKZ3Ze5EoTXecK3gUpVxiIjDYm1wIVFKceLUKe644w6OHj3G8RMnOH3mDOfPn2d5ZYX19S6DQZ8gCFFqc1ffdnGkxPc8ppo+s+0mO2em2DU3zc6rb2D/FVdy5RVXcvXVV7F7xwKd1VOFSGqNoLN0tOAyX2r8/+z9d7wlyV3fjb+rOpx48+ScdndmR7sKSKtdIZTJBpFBBBOEjQzYVgBj9CBAgEEYTLARQiBA8AOMjf0Y/8hZICQhlFbS5p2wk8PN957Yoer5o/r06e7T5947s7NarVTv12t35vTprq7qc+7tnvrU5/PVZKUbJcumBkcfSoQQ7HbrrAR9NFAvHNfNuJN7OiJQinPh8LwD13WWCenlEoH6KBOfnZx/fWGJP3r9f2L1fF6wnjt2kC9825to7phDA4GOcZGmLWEEY9/1+dpNBO8P//r/AmBq764bFrpvJt65bP+g4NhWaJ6I1tjlNmhKj66KTL1uDT6SKekznbjDD3uT9NRyeu1F8iC8FUmyWnSwljJcQJDfItLBiPrkFtr59EFrTeuhD0E0fhHOhCfR9//N6BtCmFrmt0jwHlG2t4IQMDkH1Tr0Nl+cvKVuQMFlLkhrWGfOezP1q4VWZtGRdOlP7ki3d2f2UmktmlrUaUe06U3mvDIOUTK3GhctnVEH9siJC/+eKS5aGlx7PdxX6KRO0WD8+++AD//Z1gbaWoYnHkAcvwf9jxuI3VfPolsriOZ0vrvSQW9w/xDyqQjVt1gsls8srNhtsVgsFovFYskRhhs7sAY4jhGFs6/HCb7j6mG3e5pmzRxXYmLOUSZkD2o15x3J5cfHsS51OjuOKHVQ34jhaiux1f/yW7+NF3/eS3jtd3wby8tm4v+hBx/kFS9/Kb/wi/+Ne++9d+SYsjE7UlKvaLqBzl2zcf2NY3AL19+RgnolL0BLQeoYKpIVbQcCt5QCzzHXdNAP1xkvNIdRvoNhDL1Aj4jdSpnJp60464UQSFGI8NSafgS1MZHwTwVRPKwXXtzuFhZuGKF7GIW+ut5leqo5erDFYrF8BrBj126qQjH/+EPEro/QGifspvWsAWKvlhc3wj7bz36QfmOWtV13AAIn6CK1QkYhQWOmEE8b43dW04haGUfUly7hxEPHqRt0CAeR5piSLVfmlzh36hHOnL/ExavXuHztOteX11haXWNtfZ1Op0MQBE+JgC2lpOK51KsVJiYnmZmZZdu2OXbv3MHePXs4ePgIRw4fYffuXUgpkWGfudMfyAnZnek9rO26PSc+BY05/O7wWmjpMH/0Xuae+Ejq3i5G+ZbFE2vHz70eSHuOMGJrT8c0xfCBKtKK9UzEeVuF/FXnQqnoOnCA13Hpa0WgwmFtbq1y0dx/8qa35YRut+Lzku9/Lbd9wYsLkd0Qo3EzV0MKget6Wxa8xzGo0e2PcXRvRPEpRAPrKqAuPVwh6alo6EjPoIArUZs5WTVC92C71mxzqulzhRSCnW6Nc1FreE5hIso3e4y9WGsSC4FTELJjr2J+TrRGRGHys6qHCzAL0dvq7/8H+toTyC/4tmeEINd+7GN0zjxQ/qaUNE/cg/v3vzO+gcTpvLW8ic0ofENKfhYj15RvSH9OlSL6k18z9atv4EyRXyf2qsg4xOmtm4UnqQCsM+Mi+XvZ6mGZCN43PvbBgqPsd6c3sZ3m4rnhKUbPWv4PnE1OrxkVt9tzhxAqornwROKW1wg9cNebmK7BNdZSIl781fDxv9vq8Mxxpz4Klfpme0F3HQpid2X3YXoXHht7VGXP4Rvqi8VisXw2YsVui8VisVgsFksO3/fp9TaJayOJKXeNG1vrjcXJOBED48J8cRTDWlvTqJKb78nGocOw7nMZWxGltda0e7q0tjgYR3pxLjtWIOV4x3bZOTbb98iRI/zN376HN73xDfzd3/0tAL1ej9d917/ia7/26/h/fugtuf2FMHXzBmMcaOpSChpVI9IrNXAWm+tc1O2VhijWOIU61o4U1PxhnW4hBFFsrlFRu9eaYTRm9joJkVvIoBT0I6h4euT7UHZl+oFG1Yb7aq3pBRohoOJvTfAufnaDePNuX1Pxb6x+9lZwZD7KHMx3JYo1bsFZr4HFdUXVE8jk+98P8hPQbplKbrFYLJ8hBP0+88tr9Ce2pdtCPYkbtPE6qyAEYW0ifU9EfWbOfwyhFdXWAuq6S29yJzKJ8nWiPk7YI/YztaKFTKN+5xeXeOzsOZ44f55LF85zeX6Ra0srLK2usdLu0un26Ad94uIDyS1ACoHve9QrFSabdWYmJ5jdsZudu3axb+8eDuzfz7FDBznhd3Ezd4LYrdDedjDXlhZOLoJXeRWWDn0OU5cfxkuckF5vHS3dxGU6eFCQRNUmXnctiaAWIB1W9p5kx2PvRQBBbTp3Lifs5l4rx0O5Q7FbA3HmflwRDjvdes6RvRD3cBF4wkED/9i5nBO/YVCCZTjuNUIcJfASR7YGPOEgtEprdsvMQ8bhl97DK9/yvbi+m7RUiFFHjzyLSQTSdTcVvMdRnZrgNb/3X6hMNCh+Y4pPFwKBRKf7iWRbEY1ZDOAi6I+0mt9vTQVUMw76CE1Xx9TFcFtdeiVHl+Mg0rjzdb/C/bO7+JxFc02UdAka08a5nHZC44Q93H57OOayxJpHPoia2oZz36u33JenAx3HdM48OH4HpXAl0FrZuJ2s+LzVcyd/jjwpZleJpoKyMos/pJvGf8s4MG7mZH/l+AjdNz/nmZaLQnTsVljfeYyoOvw9K8MejYVz+GniQ9mz8jjBm5tyeLthDxn1czW4s79nxlL8vmkFyZjH9aFYa743sZ0ouc+0hGTi2mPpsQLM79BMXLxQMaI+iV6d37x/WeJoRMQewfFgYm5kc+O2Z9O/8gS6JFrfmZimtu/YjfXFYrFYPguxYrfFYrFYLBaLJcfc3AyXLm1tMlAKgUzipMehtCaItBGvBWlUuTk+cVoXHMxKg8xMWA4E3YHTOU39E+WO2iJhRgTu9DUygFoFvMRVXCZ2g6lL7o6J5c4Sx5peqGlUtyLOSn7+F36RP/3TP+aH3/IWoqT4+R/8wf/kAx/4AO/+rd9m27ahKCCFINaaKB51QTtSpOPX2ojzgzJ7xf4FoRmL747W1AbjqI6Sa+DKQf1p81ppTRiaGtWuOxShlcobfAbH90PjaHak+ZzCGPrR6HdEA62OZqI+ENuHY+n1NY7UeK7YME7e1ATXqSA/0C+UNoK3IzW1ytYE5c0WLGitU4d6cb8gieXPLqTwHDP+blD+8yGFYPvc1Jb6ZrFYLM80tNacP3uaoF+o6SsEUaWJRqJcLxcbPn3pQfzeWvq6tn6dq6HLqQsXOX3+IhcuX+Pi/ALXVtZYWlpmbX2NdrtDv98njrcSy3xjCCHwPZdatcpEs8HM5CTbZmfYtWM7uw4c4uChQxw+dJiDB/bjSWgsnMuJJpFbpTe9O9dmtHoNt72Y3jydqA9KmWjeNDZ69KFEeRVW997J7Ln7TS1b6SSRvjIVwYSOQQhit4IbdomSuttxpUFQnwYhU9EHQMRRKmQCRNIlqE+n9YT7gBAOAYpQKQSCOVnFybgmFZo5p4KXqe38Rc2DfKw3z0f6G4tFMcYl6mVkK1dIYq1RaF79y2/loT/8Kw7c+xxmDuzOicdlLtCiADb4+80I3gOhuzph0lecpL+DdqWQI8+/A8F7KxHnwQZC94Ay13dc+G6U1ecenD/bBxeJO6g3lFy8/3PoTqaDHkfWl+k3pvP1qcF8l/waQsW44cYLYfWH/px41xGcw3dtOq6ni2htCb1J/eVgdYnqhntsjVFx2ziptY5zQqvWCsg8TCeCdyQ9olozcRwrlHCQKkSi098xSjoInXVoJ8+yyQIYJR1W996JcvPlcpRXZX3nbUxdeSQfIz7CGMFb36yzvfDvmEK999jxiKoT+N3V4Xgwv6d08vtORqFJENAqXRQwbNCFu15C//zjyLBP7PoEjVnijNs6rE8R+/VNxg368qkbH55fRdz1EvSH/3xsnW9x/B5EddT97U5MM/O5X8r6J99PuHQt2VlQ2X2Iybs/F+FufVGLxWKxfLYi9EYzkxaLxWKxWCyWzzq01jxx7jxra+ub77wFgkjnIqy1NgK1I8mJmFqPTg0OhNyyiPOiU3kcShkhOiiks/su1KvDyaFBzHmRQSk3b4OY9uX1mFhBrSKoV8SW3eDXr1/nO779W7l4cVjbzXVd3vpjP8GXfumXpjWpg9BMZNYqYkxt6OzfdRrvrlTixs44w7PCb/a4MNLExZh4NermdqSJfh8gkm0aI2pniWKd1gavJMtsi/uAubbNmkyd6ll8T4w4psswNd81vZIU/kZ1889ksGChssH5+oEiSNJf0/nigVghTWJA0Y3eCxTr3fJ/ch0+sJOjB3dt2C+LxWJ5prK+usKFJ86Wvre2tsbp02c4e+4cFy5e5MqVK1yfn2dl/jprK8u0en26QUj0FDiwhRB4iYDdbDSYq/vsmJpg1+wMB3bOcXDXDg7ecYIj+/fh+8Z5qMEIRpnf8bHjETZmcm17nRUq6ws5d2Vnek/Oaeh212gsnc+tFlvffoTYryPiwMhLQuZrh2udvtdYOEd95TKru4/Tmd1vxhSHyDjCTVzaIo5wwh7dqZ2pEDZx5VHa2w6hPCN8OY5DtVZlbeEKQmv6boW249IhJtAxGo2LRCJQmVubACakT3MLjuJ/6FzmoWBp0/2qOLn7dJRxd2fPmxW7dYnI6yJz92GlNVE2BjyKtiR4D2p01ycaCIbPEIOUm+w5bnZaVWdc4ONwENSFS4wR/wWCA26DRdVnOe6jks8oRm+pT44QuIV4ZwF88ZXz3LeymN+5WCqgvbxpbLYWEvnir8L5nC/YZM+nh3B1kaX3/L8b7tO443n4H/4TWLycrrIdie1WMWIDd3Ma9w7DhSvCyazazdf8TpdQGPXbnEK6KMdLUy0Ke2Y2lcV8a4SK6E7tplNIjcjit5aYmD8z9v3sOfOb1A0725VwWN91O2F9Ku3jzIWP42QWUaxvP0p/cjuV9XmaC0+ghEwXYGghEUrlyzBkUy0AEMRf+XqWP/GBDftSW7pIfbXwO6BQh13c8yXos5+E+QtbHqN49iuQr/wm9JmPo/7oHRAX/lGy4wDya74PUd24JELUXkP1uzj1CZwSYdxisVgs5Vix22KxWCwWi8UygtaaldVVFhaW6HQ2Xvm+Gf1QjcQ+SzF0VQ9o9RS+I0a2Q2liIlJuHHOttYnk1tqIxUE0us9UIy+CKm3E1rK59TIhE4xIvNrORN8BjZqg6m89nvpHfvTH+L//5w9y217y0lfwEz/1X5By2I7nQKWk3bIn+lhp+uHoG0UxfnBsPxqNio/j0W2OMyYaXDMyaau1Zr1jYsmn6uaYXjisVw3ms616goonzPkKbUjJlq/lIK6+iO8KfG+0z4PY9jjWubrjFa/8fK2OGumfEdI3XnjRDzXtnkq/V1qD43i84nPv3NK4LBaL5ZlAq9Xi4Ycf5uGHH+bMmTM8/NBDXLhwnqWlJVZX12i12/R7PcKo5Ib8JDGlVVyqiYA9NT3Ftukp9k1U2b99hkO7d3Js7y4OHTwAe2/LRTXLsMfktcdzQkfk1wlr+eSN0K8jsk5CrUFF9KZ2pYKMiAK83jp+ZzkVg7qTu1Cub2rICoHXWaGxfNFUQZYSjWBt93G04yLi0Lg4pZt32ao4FXm8zgqNpYssHH5Buo+MAtx+O+cMDyvNfBvZuGTA8yuEUtDPrAaMtWIp7tPWeZHGQeTc3AAzskJNbhwYuRYH/N76+Dq0Ayo4uWesWKsR5/NWxG4JOEks+qCdoqi8meA9ELqrEw2zoE9s/AzyVIrdQ3d2/hlj9GkkiWwvPIuU9c1D5J4tp8KA1519hInMz6URa0Xu++K3lhEFkbaI+Y5L3H/5o4jpHRvs+fSgtWbhr38f1WmN3ac6sx3/sX9C9tqZAxVCRWbsA5Fba7M92/7gL9nYo/QzyLihtQb0yLHFa6sxZQXIfQe3KHirmPXdd4z8HivuM3fuY+PfL5xzeJy6qbrdAJ3p3XRmD9BYPEdt9appXUjacwfpTe1M92vMn8HvDlM+SB3r5Lfp/D8y1Qu/jKWFjRMl6ksX0nMP28n/NMpv+EFor6H+6JfZkot952Hk17wJUTGx83plHv2J96CvnAa3grjj+Yjj91qHtsVisTyFWLHbYrFYLBaLxTKWMAx56OFHn1QbRWf3AD8T9xyEmlYiUjaqIueijpVOalKPTq+VubuV0qN1q5WmU0hRBSNslrl+y0Rit+BoHtALFK2Cc9dzYKrpjOw7jlZX8cEPfoA3/8Dr6Wfqpc/MzPJLv/IbHDx4OJ3HalRHY73LTR2m/nX2raonSscAZszF62bc0sPXUpK6nosBhlqXTwX1QzOZV/PzjqOB8Jv9DMs+OzBitVuyCKKMbl+VLlaoV0avW9l3U0pznYrfCa31yOcMUK+Oc9uPRqLHynwmV5dMB1/14uNMNm9FWKbFYrE8NfR6PR566CEeffRRHn/8cc6fP8/Fixe5fv06i4uLrK2t0el0CMPwpkW/jfBch2qlQqM5wdTUJLOzs+zYvoM9e3azf98+jhw+xJEjR2jUy91vbq/FxPV8HG2/Nk1/Ki/E+a0l6iuXUwFHI1jffgQ36KTiSlhpElYn8Dsr6X5ubw3lVujM7AMhEFGAG3Zxgq6pqY2gO7MXhEQJEzdcXzyP31tL3Z/9xizd2X3mJCpGqNi4ulOxTBkRPOmHDLqE9WlkFOBEfZR0EXGEzNyFlZTEXm00lrqABiIhjINysE1rrsUdegURycuIyGBc1DvcGpvxe2uPsaZG69BmKYrdZc5uyAveHgItINCjoribhIkPrshWBe+s0D3AYfN0mLLvvk6/S0PR2kmc8mAEa+M631jAL457o/2KfR33M+kKaVzeSvG9Zx5mWzD6kFwUvI3YrSiKtLn9B4svnv9FOC96dem5n2665x9j7WN/v+E+MurTvH4aGWcW5mTSFVJXc4nrWyc/5+nnqoffwvyOo4J3GRpRUtu65LjiZ601a7tuJ6pNjm9cKebOfXST8xfE9RKR/0aJvGouFl8JyfKhz8ktQnK7ayOuc5E46oedGxW7xctew8K1KxvG1U9dfCBNwTAdKIj3B+7E+Zo3mbce/if0e/8XtJaTE0g4eCc0Z2DhIvg1E01uhWyLxWJ52rE1uy0Wi8VisVgsY/E8j1qtSre7cX27jXClpiRZmjACL6mHnRWXe4GmLwRSmOkVraFZK59SURqK2q0oqrCYuHTP0SUx2+VOCkfm3d1SDGOri4iSE4axcQ1vJX7b9A9ecM99/N8/+Tv+3Xd/B489+jAAy8tLfMtrvorv/rdv4Ou/4V8C5vrUS2qDF8VVIQSeawTdwRjGCd3jEEIg5TBaPHsNfE+kMekCc93DeNQVX/EEuqBgCyFwS+bfpQQdj4rmYaS3LHZXPEG3PzoJHMVQNIi7jvkeDvtVLnQP+lwm5wehplYZ3b/V1fguVBKRXyWu84XV4QXq9gIrdlsslk85QRDw2GOP8dBDD3H69GnOnj3LpUuXuHbtGouLi6yurtLpdAiC4CkRsF3XpVKp0GjUmZqcYnZ2hh3bt7N7927279vLsZ1z3D3jM93M1FmtNGhvO1RwOG5OVG3SmdxJbe1aeq/3u6sov0pYnUiFvN7kDqJqk8mrjyGSOtLa8QgrTfx+4gIVAu16RJU6Xr9t4om1xgl7OEGHuNJAJrG1sVfB7a2bmtlJn4UGGbTxkprkAgi9Kt1sTW8h0I5nBDOSCOU4REvHuGYBVZE058/mapsr6dKb2IbyjPgslUL028R+HVxv7OcoAFdrAoaubyEE07LC1Tif7KPQOJknpghFrDXOJkKw2uQ7NHQvGzQaCbgIoqKQmPzfEzLnuM4K3jrpm8y0KgpL9AY1vP/6h/8r597/UbSGnSdv4wt/+vtyQvc4yq6nyMjRGk32kXOwd1aMdhBILQgzPu1BP4utD5dgiA33i9E4euO0GQ2EWiGQ3L26VCp0m3Mk4xQiWWyhhzHcZf3LLphY3zy6/umiduB2tFa0H/4wqt8t3Ue5FbrTe6gtXyJozBIlqQ5+a4FKazHzOef/HZE8cZP7RqeLVoZ7pNuL20oQGHH5Rn/3IR382V3ErTWcsIuWLrGfX5zidVdHEh+yDGXu5Hlf66Gz/UlQrP8utcLrrhFkykIU64xvDYE4fBeNie20Hvrn0j289nJe6BYSBj+tQiJufwHi879l2LcT96LveAFcehzCPmzfj5iYvYm+WSwWi+WpxordFovFYrFYLJaxdLpd+v2N3TgbMRBgfXc0RlxjxNGql6/JPRCwB9vqFYHvinLXb8n80DhR0k9SAMNoOE/nSErV7qLY7RTqdWcj0lWZFRlY7yimGnLETVyGK40YW6/Xede7f593/8Y7+c13vcOcRyl+6Rf/C//wd3/Lz/3ir1CtVUeE7VhpwgiqBeOH65iI7TDSGwrdUaw5fSVk26TDRD0/mSalwJF6ZH5TKT0yNs8xsefFS7KVazDYTwhTpzx7rlhpYqXL49NL2qhVzZgH7Zj68CX7CoGfWRBgrlf+HFES5R4p00axpngUG/d6NqkAAAEXF+Ik/t5874rXpVG7mYk8y9NNVuTYzO1nsXyqiKKIxx9/nEceeYTHH3+cJ554ggsXLuQE7Ha7TRAEqOIvslvAIEJ8YmKCmZkZduzYwe7du5mZnmTHtm0cPnSIo0eOMDMzs3ljgN9eguVL6Wuv38ZvLRJMbM/vGIfgbOym687sJa40ac6fToRVjdvvgNbD+rFAWJ+mO7WL+uoVlHSNuOw6qNBBqpgoEYpir4bbb+NEQ7e1G3RQbgUxqCcrJLFXJaxPp+3LqEdz8RyxV0M7HiLq053ZS33lMl5nBYCgPkNneg864+TUjpOP73Uk7bkDyPkzuIERpKWKqK1eozu9J3WBCsCL+uy9/QRnTz8+9voIQKLJejWr0oXCAsFxjuONWI77BCMOcYHCCLNgXNhpTeyBvCYELgK0GhG8HfJ1p10hCXU+2HtcX7PbpevyBT/5xtJ+J8sT0ImD1kWk4nmMHunToP3BOAQCL6kXnt0zIKaihy52IQSelrnI9q0K3uNQgCxJlykSacXtrbUN9xGAVgo3JwqXPWeLnGAqJuc2bPfppn7wODoMaD34wbH7hLUpsyAm4zYOGzP0J3cydeWRfEmDAdn48pH3xi8U2OznSGiNvtHHjdld1KIOtXMfTSO6I79Oe+6g+b2nNfWVy2aVKXJETE97KpL/aY3WatO67TdN4drIOBh9f8S9Xkh1uOP5iJmdNGZ2olVM5/FPoAd1s4WgMr2Npowg2g21JvLEvXDb5yAun4YogF2HS4VsIR3Yf/xJD9FisVgsTy1W7LZYLBaLxWKxjOXChUu3ZFLcdYxTO4yN4CeSbW4iImfFZSOWaqQw03mVZA5bSmEme4b2l7GTQ04iSmanREQibHqOEW6lGI21zu9r+quVRpZMAA3qTnuOoFljJOI6VrDcMoL3Rg5vpXTidNZpbfNv+47v4kUvfilv+N5/xfq6mYj8xCc+xpd/6Sv42Z97Oy94wfPw3MH1MnWxB3NAVT8vwDlS4PjlCwAGXF+JCUK4vBgz09dMNyW+J5LPycSICyHo9IdtRDF4YtRN7rtJHeyBGzz5nMqixbMMmhk40gex4QPxvOKPF7uL4r8UpgZ4ZQtpgp5rBPYgShY/FIiS76wjoeJDNxgVvINQgx66uAGaVcGCzDvHs2ybbdJsWLH7mcZv//Zv8/3f//1cv36dL/zCL+Qd73gHhw8ffrq7ZfkMRSnF6dOnefjhh3MC9tWrV1lcXGRlZYV2u02/339KBGzHcVIBe3p6mu3bt7Nnzx7279/PkSNHuP322zl58iS7du3acAzXr1xmaXGhvObGgIK7MKjP4LWW8DIOvNrqVYTW9CeHEeROFEAUEFc2duMGzVn6vTWq6/Np7Wwn7BHFDbTjopPa073JHdRXr9BvzKT9UY6PcjTKS5I4pDSx4dHQnShUhBO0TeyxVmghCWozuP02MkpEGxWxvuMIcaWZHuf21qm0FnESp6PXb1Nbu8byvruGYxISLQUMagYDSIf23AEmrzySbhNovO4q/cyCAK1i2qubu2xFQXErdy6Pvg50TFWUTy1qrXkkWGbKqdBVES0dGtFYSCOYaeO+djdwrDol7u645HmmbL+bQZDUtC70KevIlhghvq/zPVFoZMZVLYTA0TKJKh8SEuNrJ7ef0Jv5ew1bFbzHCaj5/m4Nt99KEguSo7VOf4ZS4Tu32E8gT37uFlt/+lDd9sY7CAFiNIYoqk3SnjtAc+GJsoM2OWvheXyMAF5k1Es9XIjBoEUh03hxDbB0Db10LSdOu0GHySuPsLbrNqrrC3i99WELX/49qL/+LcjWM8+edhDPrm/9vUYLQVibyG3zW4XfW6WO8uTaCYk4/kLEq/5l+k7zjudRP/IsgvlLoBTe3E6cWnOkBQAO3/Wk+m+xWCyWTw9szW6LxWKxWCwWSymdTpfHT51+Um2Mjc0s1sgONKudwup8AZ4L042t177OEitNt28ct0VRe1wN8OLxA7F1ujk6EdsLdE5cDkJNp69SwdpzoFaV+JvEbw+cw2CE70gl7iAJUse8/t9/Lx/4wPtzx3zjN30rb/q+N+FIc96s0C4wdaR9bzCJuuHpAXjwXDAiyj7nqDdyjXrBqLveTVzT4xxEOlmgEKvx83lyjMO+1TXXs1EV1Crlk+Gx0iyvK3wXJm/iu6KSuuRKm8+s+F2JYiOEVz3zntbGRR8mn5sUJtK9bEFDp6e4uqxGxl2teLzknmNW7H6G8ba3vY0f/MEfzG3bu3cv73nPezh27NjT1CvLMw2lFBcuXODBBx/k8ccf58yZM1y8eJErV66wsLCQCti9Xu8pE7ArlQrNZjMVsHft2sWBAwc4fPgwt99+OydOnGDfvn3IcfU7boILH/oH3CuncKIeUaVJa+5grpas213DDTr0pobCudNvUVlfwE8FGUNvYge9qZ3JPm2cqE9UaZTG3mowQrYQOP0205cfInarKM/sG1abhNXJ9DXA5KUH6czuHzodVUxUmzRRzipGS4fq8kXi6gTKrQIaoWLc3jpO4uwexv/mHa9KOvSmdpqa3AkyCpi+8AmkGt6Iw0qD5YPPyw9GxciC0NS8fhqvPxSnlJB05g7m9pnZc4Dryysj1yZLiEBlPu/FuMflqM2EHPZzSvhE6CR2e1gDe1J4TDn5ax+omPv7C1yIhn1rxSFKZG6IiUZarEVdJNCq4I+GuswL7IGKiQrin1N4qFBj6lyXUSnUJ4fRetixVqX1wotCeaTjEWFZAH6mTnmkVU7EH1eTe4BMxM5yB/tAlM9Ttu/nrS7z6ivnx59IKbzeGjJTMz79mRqpB28e5ORLvxbn2S/foPefHrRPf5LWA/90cwermNknPjLy86iFs/GDtx4En2e3bVz/OnYrrG8/TH3lCk7YM0cn116oOGlPDoVzHScOc5meU0a9QqmAksUr934Z8Yf+bIOemL7Kp+C+1J3cSXv7cOGg11mlsXA2MZVLxK5DoGLE2iI0Z8xiiiN3wflHzPXbf9xGi1ssFovFOrstFovFYrFYLOUE4c3Hl98ovmdqJfcytbtNRPiNtRMrI0CGkU7F21iNRlgbF/RoxGOsNL1AEytS0XqwvSj8eq5pe9CG7wl8z0kF/mLseZkYPBCCB0gp8E1qarK/5B2/8k7+9//6A37yJ/8TcWw69Xu/+1u8//3v5Vd+9TdpTkzn28SMP+syhoGDvFyUjuORTay1NTMTw32j2DjI69V8G5ECqUmd5uNwpBGUdcZxL6XZLoQgikenYSueIFaaamEsUazpB8Z5303c5krBRH3z2M4BYZS44TPblB6dHHbkQNAfOrB8j3QxQZFBKgFAvSrZt12w2lb0+qZvh/dv58jB7VS3Yju3fNpQJnQDXLp0iZe97GVW8P4sRynF5cuXefjhh3n00Uc5e/Ys58+f5+rVq8zPz7OyskKr1aLX66W/x28lUsqcgL1t2zZ27drFvn37OHLkCMeOHePkyZMcPHjwlgrYW0FrTe8Df8zU4x8dblyfp7FwltU9J2ntOGr2czwmrp8GrehN70kONi5KJwpwomFd4Uprgd7ENhAyrZEtw355jVcxFJtjr4qSbhrzDaCFzL1GxXSm9+IGXUQcghBEXpXa8iWc5FwaiL06YXUyJ/jFboXa+vVMvHEiR+phtLFUMZXWYk7UV65Pb2on9UJsu9tdJ8q6HUtclcqtQEbsLrsz+fU6frdH0OuVvAtoTa2zQr/aIPKqKK35WG+ea3GXw94Ee9wGTeHhSomLSbwJMnfPNR1S1S6VjAtWC7gU5Z2zFenQ1ZmVdTcYyywyfyqtc+K1QuNmxOjBs1gutjwRiLfyaBmi8MmLuUWB0BESnUS0ZwV7h3wCvKnlnRemdXKOSnKOgUt3q2L8ZkL3OBrCZVL6SCEIteLyTI31hetMZGsoZ5+jHIewPo3bW0/rLAtMkoGCguAtkC//Rpy7XrzFUTy91PYdo/XQh0DdxO9k6aC8CjLIxLt7VajU0J3h4pzip6GL2zepf62FoLX9MFF9mvVKk+bVR82CmsH3XDqg1PDZVwigILgLgZZOIoyX9wtAr8yDVzF1qcd2aIPO3gxCEB84SX/2AKLXwak3qR08TnV2J/riI6BBHthAyD5x7y3ukMVisVieyVix22KxWCwWi8VSiu/5m++UIY51zuE7qGtdZqAuir9CCCbq4IfQDYzTVkqo+WKsUFxGEOoRh3IY6Yx4nOmvMqJyFimG8eRp38acy0nqSxcpnkdrI55LMVrjehyFNFe++mu+lnvvvY9v//Zv4/r1awA8cfYMX/Yln8+PvPWnedHnvSJ3fBDla2oPPgs0Sf3tfD+qfj6iHODqcsxUYxj1vt41E6tRbOK8swsRjJlknKA//LvMzMEV95VitKa15wrqjO6rFKx18jurZHGEs0Vztyg5X9nXzMSqb212Lwg1UaypVTKLIFzB9inTqQMH9jEzPb21Dlo+bRgndA+wgvdnLtevX+eBBx7g8ccf5/Tp01y4cIHLly8zPz/P8vJyKmBH0Zh6BU+CgYBdr9eZnp5mbm6O3bt3s3fv3lTAvvPOOzl8+DCu++k7tROeup8wK3QnCGDq8oP0m3OE9WlkIqQ1li7Qm9xlopATcTmqNHJit9AKr9ci9ippLVqhRwUrjUALBxFHDNzXYXWCsDZp6mtrReRVCsKQiStxgi4iUXacKL/4TwBu2EWsR/Qmdw6FJ9en35il2lrI7asLMqkT9hFRiHaHi56C+kxO7Db7dfNidwmiUNdWC4mIw5xz/NqZx+l6VRxZ9DoDWuP2WjhaUeuus6IV74tWuBYbEe9suM5+t0klI2pWhEO/ILq3VEjFye8z51SZj4di4LhlFlnZVhf+HDxE5IRsGIksH7ipB1c6fW7QeVG4THguQwEekjAjjRc/x0F7MRqZiRYXQiD1UFTXyX7Fsyo0So+K3Ju5ugdtFhEl74jMdXMRzDgV6jK/2O7Pjzybl59/iG3d9XEPQkTVCWQcIrOCqYoyceZJv66egWeI2C0rNSbv/lzW7n8vI1dUxSXO9TyisHApvuMe6LbRFx5OXdZCK0QcDT/jzL+RRJnLO9sFIVndc4K4an4HaMelP7Wb+krm90RmMU9u2+hoyS/BKBlPfQJ5xwtRD/zD+H1uJMJcCNh5CPpdaK/C9A7E3S+FfbcZR7aQiMPPwpncRmmF9ztftPVzWSwWi8WCFbstFovFYrFYLGOo1aq4rrvlSXzjqCYVgLVOHNVj9N2iA1oIQdUXVG9MY8/hOYIwyrrDk1jwQFOrlDuri6J7xdM5wbtRE5tGnm/EoJZ2nLjJswsChCifdDWO8Xzf9u7bx//8P3/Oj//oW/ibv/pjAMIw4Ife/AZe+flfwg/+0H/KOfZaXU2zbupXF0XdItunJOeu5yfBOn3N6SsRB3e4OM6w9nQUQ9MRaDnqYH8yCEFpzcqyGHgTG5533081jCxRJrqXbZMyX0fcuMzHubUxE9kbjFVrTZB89zp9jecaRzjCOOc1kqnJqbHHWz492UzoHmAF72cOS0tLPPTQQzzyyCOcOXOGc+fOceXKFa5fv87y8jLr6+t0u92nRMAWQqQC9tTUFHNzc+zcuZP9+/dz8OBBbrvtNo4fP85tt92G7z+Jm+GnEcGjHx77ngCaC2dZPvBcamtmIZeMI7zuKrFfS8Vm5YxOXcmoDzo2YhughECoCLdn6gtrIYi8Oo4KTR1tzP2l35wztbDH/T4Xgqg2iXI8UyN8g7E5cYgTdHL1wmOvhhIOMie+j96EpQqJGYqOuqQ/Occ5GAEusxpORGGm5i6gNU7QpTl/lu70HqJqMz2u2m/TqzSQQuKoGC0EMo5wwl4qYApA99a4QCt32otRm+lMTLkUAkeLXOx2XCKCCZLFdsl+sTbibpzIuQKBRCAppOHkGjH1sbNPSqJsv8w1oPBcVyypI5NvVjYaXSbbsyK6IyQuMu9GLzBoYyCDD5Jd0j7qfL+LfVYj0vZ4oVtk2ijbpyjFq2Rcg20Rmitxh900cjHwy5Uqf3zb8/m6h99PPRqT6iQEsVdDFlIERhYArFwf0/tPT2oH78BpTtE58wDh0nWE41Ldexh/+16W3/cnY4/zuqs4mYUmSjqsrLeRKqLhuOZnSpjFNloIRJTEwA//t2l8udQKGUc5iTqoT+XFbhjGl2/I5os2xZ33IRrTqPMPwtri6A4q018hYPsB6KxBdx1mdyOe/XLYeRAuPgbSQRx9NmJyW/nJZvds2h+LxWKxWG4UK3ZbLBaLxWKxWEq5dOkKYaJwbkXPlHI4Dzs4xnVGJxmz3CqhdIDjkBNBByJvEEGsFL4rcOQg6ts4movx2/WKidQ2bmxTxzmLUsYlrRIR23c3FkGzQrPS5hq5jk4nYKOCI35AFIOUGplxQTeqDq//Dz/OfZ/3Sn76x3+AMIma/5u/+lM+fv+H+a9vfze7du9Nj19taSbro/0plpeemXBo9zULq/nJ6rWOZrmlcjXLY2Xc8t4mtchhGNNevDzmKzG60EBKs7/SQzd6GEG9MlpLe6ohWVoz08yeQ9qfWJFOi2s9rIlerxad5ALX0el3xSmxnPUClS5WGAjs48gK71obl3d+yjhmbb3F9NTGLj3Lpw9bFboHWMH76WNtbY0HH3yQxx57jFOnTnH+/HkuXbrE9evXWVpaSgXsMAw3b+wGEULg+z71ep3JyclUwN67dy+HDh3i2LFjnDhxgttvv51qtXrLz//pjtpE/PJ661RXr+G3huKKjHqARgvjl3VUHxFHpnZwFKClQ786STCzFz0QwrXC667hdVdTQcbrt1HSMXW1hfHdulHfOLoz9cJL++3XiP0abjamuAQ36ObEboQwfYo2dlFqkb+hCBWhpJMKz7FbIfIbQ/FWa5y4b5zKiWu7sXwhH4esonSBQG31Muv+0WFtX8APeygh8TcY0ywOU0hWM47mthr/czM4vxSCjopYiLv0dYyDZDnu0dbh0K2tdRIjPhCIzd8lAldnFgIyKs2VLQ0s20+TlBMhu7BwVAsUGHE7K1YbEZ9UxJcInIywX4wIj/VQLh/8OfDOCyFA5etwlxGhcuMY/CkLY86eeyAyl3lsRwVvjdD5Z8xl1aMum/kDVTxe6B60vZXonE2SCD4d8ed24c/tGtleP3Y3nVOfGNkuVEx9cVjnXEmXtV23o12PGI/O7H6aC09kDpDm5zC7AGaL//5xgw5hYybX1ki+wGZCt9a5CPMyxLNfgdhx0Jzz6/4j6iN/jnrkg9Brw9xenGe/DKa2w5XT4PqIo89FTI0Rsnce2mRUFovFYrE8NVix22KxWCwWi8UyQr8fsLC4lL7OCtjjkDKJbUxm3wbiYZmrZrD9ViOEoFaBfqgJw7zQHCsTkT7Yz0nqRRfFWCEEk/VhFHhpjetkjL67hXGUzEENBOcg0sbxrUbjxbWGKCnL5yfmL88V1CqCF973Mt79+3/Bm9/0nZx74jQAC/PX+eZv+DL+3Rt+kC//iq/Fc6FWETiOqXs96Me4euX7trnMNhVL64ow1lQ8wdykQ8Ub/fxaXSOiO0XVPGEgMA9i7Mt2Gyd4G4e3Zrk1bCsINbOT+UlW3xNsm5a0unokKl8nx0WZxRdBqEfqbDvSTCUbgbwEPUwoULq8dnv2nJsRxzcQ/2h5WtlM6D527BinTp0a2W4F71tHp9NJHdinT5/miSee4PLly1y7do2lpSXW1tZSAXujRVU3gxACz/Oo1+tMTEwwNzfHjh072Lt3LwcPHuTYsWPccccd3HnnndTr9c0b/CxGVOvo9trI9tjxTIxtFNCYP0Ps11HSQWiFkj5BYzYVdWXYp9JepNkePpdsO/9RWu0llg88J4kGkYT1abR0qbQzwrmK0XGIzriknTgkLkR9lxFVGpuK3WW//YvCknIqCBVnnOoeysvXF49qUyzvfzZTVx7BCXu0th8xzyZJVLSMgiT22Ixp79HbaV/8BDqOGdyssncnoTV+d40gI5Q5KkZtIalmsPbLTf7mCwcJuEIagVib+tguInUya625FLdYzwjj+7wJarGb1u4WiUsbrXIOaoUmxsRsp/3HiNa5Z4SMlzi7X+61EKkInW2vTBk3yTdDYXsw9hjwkTjJuT0hiXWcF5G1ppcRL0Wy3+BagBGyy1zYRSF7oyeDcTW4jSt+a/XHi+JoT8dEWuGK4Sq/SAgC6eBvJIqq/NnM2PI9VFdOE3/8PUYcfYYzcfKFuM0p2qcfIF5fBiGo7DpEdXY7wepVwtoksVen35xLoqwMUXWC2K3kSi9oKUdiz7fiyNaFKHUn7N6Y0A25RTAIYVzVawumNvfcXsRzX4m8+6XD/RuTOC/5OpyXfN1oY/uPb3o+i8VisVieLoS+1f8qtFgsFovFYrE847l+fYHLV66ObN+KPq2UTuthbyYEa61Z6yimGlsstHwDaK1ZaanSCG8hBBM1gVtQYbeqvwehcWMXjy9jIPwWcaSmWzDRCEE6uZrF94bXUmnN8rqi09NUfcFv/Nov8N9/5925/V/4wnv5b7/09jQGV2UWIQwwjvGtLzpoddVIPXM/EdSL12HgjBcZZ3zxGuhMZHnZdVzrKMJI005qhTdrgqmGLN134LbPt2/i6LPndRMH+GAhxsC1DYxx1xuh3cl8lwVmkUTRaR7HOl1MMY7nP+c4lcpnRjTxZzKbCd2/8iu/wmte8xq+8Au/kH/6p38q3Wfv3r1W8C6h1+vxyCOP8Oijj/L4449z7tw5Ll68yPXr11lcXGRtbY1Op0MQBLdcwAbwPI9arcbk5CQzMzPs3LmTPXv2cPDgQY4ePcrx48c5ceIEk5Mbu34tW6f30b8h+OQ/Dl83t9HafoSwNgWADHu4/TZu2Mkf19xGf3JnbtvklUeYuZh3Wi7tfw7t7Ydz22orl9N632AEudiv527ykVfNO7JLcHstquvzG+7Tr08RVidz0dpu2MNvLxqhXQg6M/sBqK5eQ6iY3tQOlFfu8hdxiIhCVCWziELFSJWP0t6xczfhh/9iw74FtSl6U3nHas+rUu+1xhwBAfAnsoeQIhVDPSQHvQl2u/mFHR0VjUR8r8YBqyr/cHM+XGdFZYQ/remXyLQuAicrwA5E68w2CSMR5JBxRicx6YP2hBi6t7OHZJ+pFBovU9s60oppWUn7EmpFWKgJ39VGrk9FciHSvycdIUaP1BYfjCErEY9zaRf3K0ONiT0Xhb9nryvAAXciFedJxvHSS49zsLOOlg5CxbhBJ1ejWwNer4UbmJ/V2PFRXgURR0id/0TkPV+Ce++/2LDvzyRUFCKkREiH7vnHWPvY32+4f33pAn5nZbhBa2Sc/7kQKk4XsJShESwdel5uUU598Tx+dzXXbtqGEDC9E1bnQcWIud3Iu16KrFTQ185DpYa44wWIqe3mUBUjNqlLbrFYLBbLMwkrdlssFovFYrFYRrh67TpXr45Gj95qM/byunES75yRNGslOdJPEiPQjj7uOpJSgb1sfGUuaJUotUXBswylNUUzx6DdsGS7UyJAZ8XuAVGs6fTMJOeDn/w43/fGf0On3U7fn5iY4Fd/9V2cuPNOEwmuyt3HWxHsB/1dWlcUPdA1H+pVObJvEBmhe3CNBpHmenTOGadEaA4jc75eQUCenRBM1POfndaaMtN0FOu01nixz6Miv8YpyTIPQjXyxTAifn6b1sPPo4y52SmO33ZwzLuWTxe2InR/13d9F2Cis63gDUEQ8Nhjj/HII4/kBOyrV6+ytLTE6uoqnU6Hfr//lAjYrutSq9WYmJhgdnaW7du3s2fPHg4cOMDRo0dTB/bs7OwtP7dlc3S/S/vPfgO1ukB3Ygcr++4uvdl6nRW8/npuW2dmXyqKm8YUez/xJzm3dVid4OqdrxppKycIgYkEz5w3divDmtYwGvMC+K2lXCx65FWIKhNU2ksIrdBC0p7dZ2KKB6KgdExkehxSXb1Kf2J7KmyLOAKtci7zLVEilM1s2wEf+xuKd3YNRhzTirA2TX9iGDWshOSC57Gr16Y25kexV2nQ92ucCde4FLdz7x3xJtjr5uOv1+KAMCPVKq25GLZy17KtQk6FKznhNtTlEd8OQ5E9SvZxkamDfHCXLh47eDUQrwf7SiHye6a64FDsdsg/E9RwcYVM21Fa0UflBOmyZ8MBorBfUCJlO4VnqTLR+qkSu10EB9yJXP/vWlvh7tWFEdew113FCzqmpEBS59vrLONEAbFbST9nEYd54dbx8L7jPyFqhbj0zwB6l8+w+qG/2XCf+sI5/F4m0aK4YEUpxCY1u9uz++jO7EtfV4WmevFBI3DP7kbe9XkIx0UvXEZU68jbn4+Y2oZWMcQxwrOLKy0Wi8Xy2YUVuy0Wi8VisVgsI6yvtzh95onS926V4K215ty1mFhBoyrYNTsqYOotCsrjiGLNant0ktFzGBFMB2THpxK7cFkfNproLBLH5c7jMrFbCtJJXQDXHb4unq4XDN3W/V6P73/jv+Hj9380MxbBv/7Xr+PffPd3p9cz2w8hyNUE34yltZhuoFOBXCkzjt1zzuiCAKVLneNRXOJyEuXXeHEtptXN71/1BTtnRj+7OC6f8O32R7f6bl7kV0rTj5LY96JjW5UL6V7G7a21JgjNn1HJvtWKz7OfdRvuRkW/LU87NyJ0D/hMFbyjKOL06dM89NBDnDp1irNnz3Lp0iWuXLnC4uIiq6urtNttgiBAFWMjbgGu61KtVpmYmGB6epodO3awe/duDhw4wJEjR1IBe8eOHbf83JZbj+p16H/yvVwKPeIxjma0orZ6BaGH36fIq9HefiS328z5+5m89lhu24XnvDoXI+x216h0lodNA3FB7A79GsofOpVFFCJVSOzVzH4qprp2HaFi4xIXku70LpRbQUYBldVr9CeHQnZpvZcSAf2m0BoRmxhzGQdoIdl24CjxEw/R6gdox8UJe4goJKxPDZ2gWhkhPmHedTlDiK81d4SKZub2qIHAr9HPLAC4v7/AWsalLYEXVHbgZ9ygSmvWVUiUEXTPhesESlFJ9ou14hPBYlonG8aL3WAixIUQBDpOI7g94eSOj0e83cniwsxWQSJ262Hda520qFNBXFARDk7i7M4+22U/uXiMaF1G8ROPSsa6FXd3drzj2IrYTdLO4FlyTlaZdoYx+nt6HV4xf7n8BFrjt5eNw3vwXdYKt7eeP4dSI+kDzqu+BefO+zbs/zMRHYXM/8XvocfUOBcqYvLyI2SXWQx+foevo/GfrJTw0tfQn9pJtL6CrFSp7r8NtzFpzhnHiErtFo7IYrFYLJbPDGzNbovFYrFYLBbLCM1mg2q1Sq/XG3lvK/W7t0IYDWtfd/oapXRO8FxpmwjymabMib83gusImjVJu5ufFN1K6eSBOAxGSC3GXN9IzXHHEYiBuzpp05GCSI1GnCttpmEH9as3GrvvitS5XqlW+a+//Jv8r//5u7z9v/4sSim01rzzne/g7//+73jXr/8mzWZzJDIxjI34W0ZRsK5XBetdnROspxqSKAav0IaU42q156PFxRih24xvdFsv0ISRxnPzxwzqahdPKeVImUnCOF8jfbDooNvXeK7Gc0TaJylM/c4ikQI3aWPQvhACV5qJ5+zPiSMpdY1bPn24GaEbYHJykr/4i78YK3h/OtXwVkpx9uxZHn74YR577DGeeOIJLly4wNWrV1lYWGB1dZVWq0W/339KBGzHcXIC9rZt29i9ezf79+/n6NGj3HbbbZw8eZJdu3Yhpf15+UxCVuvo4/cSP/Lg+J2EJPZquMHQTeyEo88gysnfGFTipM41VRDdtJAIHaMx+2pAxhEEHZRXAzRu2DFOSxUReXUqnWUjVklJLKv0m3OpI1u5Pt3Zffnzlt2rb93qQGorl2ksXUrrAMcLZ1md2U84vTu3nxN0h6JjRugWzSnO9lYACITgk77DpNI0lSYWsCYlhyuNnAB33JvmoWCZljar6hTwsf4Ct/vTzCRiqRSCKemzroJUDBYIWjrE0calPYjyNjWeTZXnUal6iEIjMqVOBn/m3coiJ/MO4ssFw9reCiOAZ/Yq/Gkc4oGOqQnzvco+22VrXTtC4Gu5JcG7WCNbIkqd6Df67XCS6zYchS4rRZ5rf/BenFzTI805/FATacVsrclzdh5g50MfHn9SIYgqdfxs9H3i8s79nJV918P+6LbPAITr0TzxOax/8gOl71dXr+WF7loTsb5oXszuRj7rxfC+P4RMQkUOpRC+T/3IyZJz+3Ym32KxWCyWMdhbpMVisVgsFotlBCEERw4f4MyZc/T6T81kVdH8tLSu2DZlXEBBpFPH8uKaol4R1HxxUy7viifwXUk/NO7bgfg4zpmdxmwXRWgFQuhMLPfoODZCCoF0hm5xMGJusQ42QJyopcYIPP4EUgpqlbx7+Wu+7pu454Uv4t99z2tZXjKTa4888giveuXL+bmf+wVe9Lmfm+7bC3QiEGt8Nz/JG0aadt/0oVk126u+pOIN3eQVT+B7gjA2E8qus7lTXIpkfJnXubHHmn5k4sfb3fLJ8OsrMTtnnJw7WwiBI/KLFMDQ52RQAAEAAElEQVQ4sPuFuWmtzXX3XI0Uebd7GBn3eaMq0nalKHPmQxSD4+iCWz7xamXGFQQhQRDaet2fptys0D3g6RS8lVJcvHiRBx98kFOnTnHmzBkuXLjAlStXWFhYYGVlJRWw47J6Ck8Sx3GoVCo0m80RAfvIkSMcO3aMkydPsm/fPitgf5ajtvD904V7hy75zri9fLR2Z2bfyI04bMyi3AqV1oLZIB3jGNcaJV2U64EQSBUjgg5SRamjXKqYSlJvO9OTnHAM3JiQXVzhdaNISXdmH5XWcip2O6vXmV2bZ+nAcwkbM2nbsV9D9Fu5hW2O5xFv346+sJJrdk0K1jI34baOaIphfeCqdHl2ZRsPBItpHe4YzePhCneJOWpyKBA3pEeQ1OVuK/OQ0NURE8JnKc4vWsgL0KMoKISGGyd0Q3hUhYMGVlWfkKxjG7zkGiQXA4dRt3cZEZpeRvAeh3Fjl4vLG3GzSx6yiwMA9ntNJmWF08EqbR2m2+WYmt/Ffk5X67zpuV8AQKwUTvLztfihv9lQwh/El+dIr3M2HkDnX9cnNmj1mU39yLMQXoX2Y/cTt1YAcJrTNPYfw1vei15fRDRncE68EDG1Hd1eBa0QzRn06jzq7/77xie4fBpOvvipH4jFYrFYLJ9B2Bhzi8VisVgsFstYtNasra9z6dIVgsBMXt7Kut0XrkcEGWPIRF0w05R0A02nED89URM0qpuLJUoZB7VbcP5qrekliYOey0hcdZGiaDrAccTI9hu5JgOxe+CYjpVxKg/c5oO61hpwHaj5+TGXnUspTZC0IQDPFUih+IH/8H389V//dW7fr/rqr+GHf/hHUJnrMUSnIu5AwBUCpupiWN9SaRbXFJ2+ZrIhqXj5DlU8c22V0qx1FFMNOSJ+a61TF3axZngYaa6vmIsxOyFRSrOwNjoNKwTsnnVGHN6Dazg4z6DNoKR2t+sY53dZXe96Jb+4oizO3JFmrGGkR9zjRZ5z93F839t4J8unnCcrdGe5VZHmSimuXr3Kww8/zKOPPsrZs2c5d+4cV69eZX5+npWVFdbX1+n1ek+JgC2lTAXsqakptm3bxq5du9i/fz+HDh3i9ttv58SJExw+fNgK2JYtE/b7nPnER8yLMfHefmsRN+ykr/uNWXpTQ+eyiCMq6wvUVq8wcf1xlFvh2h0vJa40Ss/pdtfw+vn60ZFbGcZ8J30ROi5EMsc4hYjifn0G5ZdHB5c5j9NxqtiI6okjVwuJdtxR8XwLiDhi+6n3m1j1hLDSZPHoC/P7RYGJNc92xXF4gIjOBs8r+90mk87ooqy2CvlIfx4AL4n73unUOORNmvMlZ1qN+yzGPU6HplaxRFAVDo+HK0PBWZOr8T0OiUjrcwsEO5wa29zh9ddas6z6XI/z7lhdEusdZ+p4b0RTeCNpOsXL1dfxlsLMReHvPT36uzobZb6RIC+BXU6DfZ6JmI+04oH+Yu6Yshj0Mt78nC/i4MRsbtvSX/wO8frymCNMPe5KZzW3ze2uIbJn1BoRR8jCOOWzX4586dffUBrSM424sw6As0VxX7dWUL/6pg33Ec99JfLl3/ik+2axWCwWy2cTVuy2WCwWi8VisWzKxUuXWVxcym1LayA+iQmsdk9xdWl0eq7qG1E5i+fC3MRozeOBQ1trTRRDPzSCbbMmRvoWRBoVQ8UnOaa8X0IYUbfsfaPtlI95K5diXC3yfqhKXd7N6ug4tnougD//8z/jh/6fNxNFQ0V37969vOs3foupmXy9W6X1iPDrSLPQoKz2dhCOChauY+LVV9uKXqDxXJisyxFReyOuL8cIAdunzefdD4xw3gs0CCNET9ZlqdANo2L3YGxRZFzlA3f/4HtTJna7jnGy59vVOVEjuwCgrI0BjXqNk3c+s2o2fzZwK4XuAZsJ3nNzc7zhDW9gbW2NCxcucPnyZebn51leXk4F7OzP6q1CSonv+zQaDaamppibm2P37t3s3buXw4cPc+zYMe68806OHj2K69oAOMutJ2qtsvChv0WsXAetiP06vYlthHXjStZCoNwKfmeJSmsRJV1a24+kwrRQ8bB2MOC1F+lO7xkrdJtGlam7nREFlXRMXe4MIhGjhzup1EE9iIPuN+ZQjofQMWiNlg5auuhBjLrWxrmpVf4JQStkFOba15go9JsRvL32CtMXP4kTD8X4tV230Z3aY0R0SMV6EYe5voRoPu5APOZ2fLs/jTemTx/rzdPSYfp+XbjcVZkDhoLtfNThk/2lVITVWnMpahGllbI3FnWzSMAp9GVWVtjl5j/v61GHJZVPICoK21rrNEp9I+rCxS2c80bFbp0I64Ma4AA7nBpSCC6H7RGhv8QfPUJTeNxZyQvUF8MW1+JObttWru3rn/UKTszsSvsqhKD1wAfoPfiBJN1AoBwPBnXZhYA4wuu10p8JEfZwo9ESA2AWZBRrd8uXfj3Oc16xad8+m4h//6fg8qmx78uv+wHEvts/hT2yWCwWi+WZjxW7LRaLxWKxWCyb0ul0efzU6fT1wJkLmzukN6PVVSytqbRushDQqIrSKbvppqRacBJrrWn3RoXpqi9GxNCBID5OJM0yTuyG8YL3VgXosgh1pTStXv6EvgsVb/xk+FbPt7i4wLd/27dx/vy5dJvrurz5h36ML/qSf5HbN4jy456qj4+PD0JNVDLrW3E1C2v5sVQ8mG6OX6yQpR9qokjTqN28a1QVc8cxWkRc8pkqZb4XRaq+2JJIPxDMx31fbj92kOnpyU3bsXzq+MVf/EVe//rXj33/ZoTu3/7t3+Yv//IvuXDhAh/60IfodsfU47xFCCFSAXtycpK5uTl27tzJ/v37OXjwILfddhvHjx/n9ttvx/dthL7l6SNaW2L5H/4QHYyWRelO7qQ7tRvlDcXfCUL8yWmWllYAkHE46lQWgqA+vemNsNJayDmhlXCI/aLYHYGQRuRDIKKeqSHuN4yArJQRreOg0AdJ5DcGDwXJRo1QUYngXTgWUF411w+3s0pcbRoBfQwagYxDtp3+p1R8bG07RFRp0JvcmazWi3HiEJQaER7PSc3VklvrpPTZnziHy3iwv8iaCtL7dUO4nPRnWVUhHR3hIXk4WOJy1KalTMC4hC2JzONwECNO6yPuJNVMrHaoFafDvOu4zN0d6c293ZuJ3VprQvKx6IO9B49CkVap2O4jmXEqTCX1zQMd80S4vkkvynluZRueGH4vluMeZxIH/YDNxG5HSP79yZfxkWtP8MjyVZRW3CM8XnzhcWSmvvbgu6ncSu54t7uOJzTO6rU09n8ErRFRgMz2ZWo77rf++Ge0u/tG0ecfQf2/Pweq5OHz8N04X/nvP/WdslgsFovlGY4Vuy0Wi8VisVgsW+LylavMz5v6l0oNJxLLxG6l9A3V19baxEwrBb5n6jjPr6nSaOhdM6OTwO1eft9BQmqZu3tcre7iPqpQejDLIIK8bPuTodNXqegqxNDVvZEDfSsM3OQ//baf5H/8j9/Pvffiz3sZP/nTP5e6OQefBRg3fXOD6HilNL0SN7pSZgFCrq/A9ul8pHmsNP1QU6+MniNW+kktpBgXQx+r/MfqSPN96wWjMeVl7u6NzhfFjHxnd+yY4dCBfTfWectTyvnz57n99tvp90eFN4Cf+qmf4ujRo9x///1cuXKF17/+9dx9990btvmGN7yBX/iFX3jSfRsI2LVajampKWZnZ9m5cyd79+7l0KFDHD16lBMnTnD8+HGq1ermDVosnwasvO+PCa5dKH1PA8v7n52LCPf9CpOeZP3apQ3bDepTGwrDAJX1eZyggxP0AE1QnSBszqEcf+jIRg+drBuhFXJEdJdElWbuhiziiJEle4njNd1La7z2Er2pXem5K60FKuvzrO+4bejSLnZBCLR0qa1cZubCJ9BCsr7jKEiHfn2auNIwwnpSo7zo7m45kgdFXmCrC5cD3gROZgxaa67GHVZVQA2HK3GbhbhPOxGypx2fuvByanCsFVejTlrf+1bgkn+OK3N3nwlWCTKO6TKxOxwnzmao4eCK0dIrYIY5ELFVInoLTNw6JM9OqJyrfEJ67C709XLYpqVLHpw24S5/WCMdYDHu8URG7N5KjPmzpnez0F4lSh5UJqKQ77h4Fn/MQ2bk1/OR/0Iw85IvJ/of/3njEymNVGFOEHf/1c8iPoNreN8M+tyDqH/4A5hPfjd6FcSzXoz4vK9FuLbsjcVisVgsN4rNJ7NYLBaLxWKxbIk9u3fRqNdZWFxkda2Vbi+Kx0GkCQJNvToa1T0OIQSVwrzObFOy3FI5AdLUk9YjblvfFSbierBfsm+rp6n5w7rQW13nme4lGBG8jdA95rjyMqRbpuYLuoERTX13OME7aHPQ/c3OMS5i/gf+45t5+StexRte/29T1+k/vvc9fPmXvJJf+pVf58iRY0ZsczVCgLvJ5yel2bdYD/vjH/8oFy9e4/idd7Fr917TJ6AbaOqVYZvt3kBgVlT9vIPrySYGDCLKR/os8u5umSxcqFUEcazpR5o4Nv0NI6h4my+OGJzPc/MiuxDQ75VHfVo+tZw/f54PfOAD3H///fzDP/zDWKEbGIk2/83f/E2uX7/O9u3bxx6ztLQ09r0yarUaX//1X8/Bgwc5duwYd9xxBydOnKDZHO+stFieiaheZ6zQDeY2W2kt0p0dLgoKgj7ar2/a9shveK3xuqt4vXVEHKGlg9tv43VXU0220lkh6K2zvvM2tJA3dtNO3N9OxikutELEoREFk7a0kPjr84SN6WFUuXRQwriyBYAQuGGP+splOrP7k/4r3LBHbfXKcFtxiEl73cldTMkHCauTqVjuhH1irwoDkVEIig8yOydnUMLh7No8AYop6TMtK5wKV1iIe2g0deFyLmyxXIgHd5GpIL4Y91mkz5xToS7NA5wjJHvcBlGoaOtbX44Byp3ixS0jr7UeeZxzkuUIA3HaQRALUCh8XRS880KyFAJX59sTQoycuKXCkWfkmnRpxVsTu2USEC+ASCkuxOvpdVWFMQkEcgPB+/DEHGEYpkI3wHPWVsYK3QAy7BFLZ/gd1pr+xdNsuixECLT0YCB4CwFWvB1BHDyJ8y0n0UtXIOjB7C5EIXXCYrFYLBbL1rFit8VisVgsFotly0xNTTI1NcmDDz1KPzDOHaVBMqybHQTGUdPuaXxX47njY7A3wnUE2yYl/RBW2sa5rbWJzi6K3Z5r3M+Det0DlDL9cKWmVhnWVxZitCb4AK2LM5jJH4JUjN1IM49jM/4bqVGdnkoIar4R9Mvm37cyJ68St3SsjLN90C6Ya3PPPffwV3/9d7zuu76TBx54AICVlWW+5TVfzXd/7+v5ln/57bju1uK7wYxTSiPQr6z1+Mkf/yHe87d/CYDn+fzr734jX/6V3wDAesd8Fr4nCOOhk7ofms+uVtFUk9j2wUTuOKF5KwsLUtNeYZuD+d5ScOg7jsAHOokaXquU10s359dpH7L7CCFy/dpIVLU8Oc6ePcsHPvABPv7xj3Pq1CkuXLjA/Pw8q6urdLtdwjAkjksiQm8Cx9l4ev+d73wne/fu5eLFixw8eJCDBw/yu7/7u7znPe8p3f9lL3sZv/mbv3lL+maxfDqjgs0X/MgS8a85t53W1Yvpaw3EXhXl+mgpzS/3Eje2lk7qZhYqQnkVQjGN11lJBW+/s0Lz+inWd92RP5ayAiWF9h2PWDo5h7eMQ5SQw/rdUuKGPWR7iX5z2/DgZB+hYoSKQSucsIcTdIj9On57xfSvvURnZt/ITU6n0icgJWFtmv7EXG4PmXVyD1zrGc6FPR4M11mNzYK3K0nd56wjuadjGtKlqyN6evg7NEIhtMwtTFuK+1SFm24TQjDn1mjfZFz3Znjk01b6Ks7Fdxdd3QNBWCJS97NM3OLCHIBgWB9cY+LA3dw3YXTlowSKdxeJyF3HwdXPy+ZbW3TpIZCZSPUz8Vo+1l1ABYcgE5s+TvCuOR5ff+h5vOuh9+a27+1tXGpDaIWIArOQI/lZ09IF14doE/e+EGjhmDYOPgvh2ySScYjZ3U93FywWi8Vi+YzAit0Wi8VisVgslhtmcnKC+YXF9PVA8C5GRAeRiaOuV2/OpSuEoOqD14NeDFWfVLQu4nuCfqgJIj1SkztSQ7ezcSFrKuQFb62No9ccP+pK15kZy6yIqtEIRBpjHURmOtqt3ViM++AcGnPuG7liWutU6M864cdFgdfrdX7nd/8773rXu3j7L/3XRLjVvP2//Tzv/Ye/5Z3v/FXcWn2sQ7yIFAId93nzD7yBD//z+9LtYRjw9l98G1EU8VVf+80ALLcUU41yETmMoOoNI8EF4Dqjzur02m8ieGdF/vx2cGX5uJzE6OfI0QULWaf4VotBeZ79J9eNcPbsWd73vvfxiU98gscff5yLFy+ysLDA6uoqnU6HMAxRZfUNbjG+79NsNpmenuYtb3kLs7OzG+5frVb5yZ/8SQDCMOQ1r3nNWKF7YmKCn/mZn7nVXbZYPi2RtSY4LsR5p2/kVYmqE6AVUSXv4q43mjSmZ2nMbqe9NG+SNmoThUjlkpMJkbSpqbYW0s3K9Ym9Km44FN799jJea5GwOZdrQglpBLoNxqTcChqBG3bT8wo0WisQA7Fd44R9Ixa6fnqsFg4Q4/Za6TmcfgcZBXhB21wzrRAqzkWZaxIhX0UIrdAIepM7cnHp2slLtBTG0UbzUGcVjTZO5syxRTlXCsGcU+FS1MmNPUan0d2DfnV1REMMP5uGuDX3vapwaEovjUXXWnMt7hCj2O2YePAV1ccXklgrAgp1uXVe+BUIHPL3fiN8589rxO6bQQ/bxAjioVZ0VESQfBZ9HSdyffYalsSuo/G0zi0siNEIPey/EAIfmVuQIEi+i5m2unHIQytXRnobbyW1BiAO0xQEd2Y7zh0vIH7wfeUH5FYaSLTr4d77ZZuex2KxWCwWi+XJYmdeLBaLxWKxWCw3hFKKtfXOiNCotBFXi8Rqa3WyN6JRlfQCxWQ9Hy2plBHYo1jT7mvCaLxAGsYmsnpAP9SISOPIbD8H7YIsKdWcHUcaLa5Mre3syDXG4T3OPT7abnkM541ct2z/c40kDBzHWcH2O7/zO3npS1/Cd772tayurgDwiY9/nFe+4uX80tt/maN3PBdHDh3i4+j3+7zxDf8+J3RneefbfxaAr3/NN1OvSKq+IIhGvytRPHTGD7pvPrfB53Rzbvni1d3omg4WWJSZr8prgI8mDWSZnZnZYk8/czl9+nQqYJ86dSonYA8c2E+1gO04Dr7vU6/XmZqaYseOHVy7do2zZ8+OPeZ3fud3+OIv/uIbOs9A6P7f//t/l74/MTHBn//5n3Py5MkbatdieaYiPZ/q/tvpPfEQAEo6tHYcJWhkFpDo3M2K7buM03HnHc9i8dwplhYX8kJ3kcJNO6pOoNrLyIwIGPt1nEEta8zdpLF8kV4cmrrZaYcdtCJXb7gM7XjoqAdap3XDjQjt4HWHrmYn7BMV6h7LoIPbG9ZbdoM2lfYyKhEUtRajtci1wu2s4OTGVMUJewitUdIxdcgHpwFQZl+NZgnNo1KhhRFEa7i52tEikbtzUd9CUhMO3cw5VcnNMdrq6q8Cxbvz4E462HbAnWDaqTAfd7kQrhMn/ZuPeygNvpB0k1hvR0hzHQrO6i11osC444rbY62JC3W6K8icI/t63MXJ1B13hcTBo6uHgexl1x6Mk94vhIZ7wkGhUhFfCMGsqLCqgnTxwuhTD0gpR7Y/1pjgUK/DOAaR+QLQWiFrE1T2HIGdB1DLV9GXTxcOIN0/6RzOV70BsfPg2HNYLBaLxWKx3CqE3mrhQovFYrFYLBaLBbhw6SqXr8wjBRSTfbXWdEtSmz0Xqn6JenwDrLYUU818G1GsmV8dnZCuj3N/O1ub/HQkuG55G0WntNaaTj/vHjaCu3Gbb0Ws1lpTXCcwqCW9VYLE1T6g4okRh/s4oiji9a//d/zje/MRl1/5Nd/Md33P97FjWpY43Y0QPxC63/e+MS6fDN/3/f+Bb/7mb0mPX2mX19Quc+87kpzDacCTqZG+EWULDbL1uMEstlhpa5o1Ufr9rlWrHD16eNMI7GcacRxz+vRp3v/+9/OJT3yC06dPpwL22tra0yJgT09Ps3PnTvbv388dd9zBc57zHO677z527do19nilFK973ev4tV/7tdL3fd/nD//wD7cseG9V6H7Ri160pfYsls8UVNhn5R//mGj5Oqu7TxDWp0r3c1yXvQcO0pyYTLdprTl7/z/D+hJCxSjHI6xNobxKuk9t6SKVzjIr++5Kt1VXr+EmTmnTiRg/qeU9ELIjv45yfToze4mqE2iEcVNrbRzUZWMRMo10lkEXoWO0a/qiAScKqKzPp8cG1QnjNs/0o758kbA2RexVEWi89jJuv43IRmn7NXqTO3PubpTCDVqI7I1IKxq1GnJqG/1uFyEdJmbn6Pge//jY/XgI2mj6JYNpZQRSc95RwXUp7tNS+Zj5isjf02ZlhUZG0F+PAy5GrQ2ftwYCsEoEasnwmUciOOROMOMMo68fCZZZU/no7Enh5e7TkVb0CyHeZVOexXv7IM7cxI4b13tVZr1BOo0kzxJrRU/Hue0C8HFGnleygnfaV50PQi9bSCAw0e2DY6vC4ZA3wblwPa1fPiE8HCG4FnVQSW+Ld9833fVK3n/5cR5fuZ5u85Timy+fY1s4GkmuAeV4ab1u7VWZetlX4c2ae6pWiugf/oD4wffnjkE6aOmaRRWNKSpf9O04c3tG2rdYLBaLxWK51Vix22KxWCwWi8WyZbTWfPTjjxBFEUIYQTX7OCmEoNdXhCVlcj3XiL9lguWTYX41Jsqcr1kTNCqCVm80vlom8dQbIQVUfNPHEqN6qQgdRiZGfMAgIlsII3pvpWa5UsNJZsHWjsmitaYXDOtgN6rjhXaVDKx4jj/8w//Dj//YW3N1jvfvP8S7fvO32Ll96MIzixo0koA3vfH1WxK6BwwE75VWTDfQVEoWBFT90UUFJnrcbPvN3/h1fuM33sXOnbv4n3/wvz5lYnJR7G71FL1g0GdBzRe4jnHZ9wLNof172LtnW3ljn2bEccxjjz3GBz/4Qe6//35Onz7NpUuXWFhYYH19/VMmYLuui+d5NBqNVMA+cOAAd9xxB8997nO577772L59+y07360SvK3QbbFsjFYxq088xuXVNk7URwuJ8vJ1fB3X5bYTJ5GJS1trzeInP0j32oV8W0C/uY2wPg2Av77A4X/+fa7d8dJU8K6uXsUNhq5VEYd4/bYRspMa4WFtEoQkqjTozO5HCSd1iJu48PxDgE7qEA9WWYmoj0DgdVeRcURYaeB114iqE8ReBaGVaVNk7nODNgv3PRkF1JYu5dzoyvFoz+1PBcfBOLLjApjbf5jZvXn37GMLl/mHsw+zER0VEmZk0TKxez7q5pzdWms8IYc1rrU5atapMuH4KK25GLXoqQhVIrqCEbOzz4JKq9xzgIvgLn9bbp/FuMfpcDXXTl24eJlro7SmW6iknZZjScdIWq9bZI6LCiN3EdQytcgH16c4HqU1HZ2P6JdApRDlrtG45NOJWol4PyhcU3b9B30fCN414XCbP01LhVyIWgBMSx9XSFbiPusqRBXa2V2f4kc/50tZ7Xf59Qffy2Kvlb5XjyO+dP4KB7udzDUSKMfNfe8aL/gCqkeelR9T0CP4/Z+G9SUjjnuV0UQCIfBf9Gq8Ey8sGZnFYrFYLBbLrcPGmFssFovFYrFYtkwcK6LITOppbUTTrGAqBdSrgnZP5wRocyywQQrpzTJRkyy3klhSAc1E5G3WIAiNEK21mb/ein7suiLjLkpqaSfvCUzUdrEMs+cKtB7W6x4cr7WpQy3laB3xIoP5z+I13SqD+O1eoIljnTrEimitafc0QkC9mndLf8VXfCXPf/4Lee1rv41rV019xwsXnuBffPGr+Km3/TSvetXnA+Yc6+0+P/zmN/DBf9q60A3wsz/zn4mV5hVf/I1pfzx3WB/bc8oXJGgNZ584y2u//dtYXl4CoNU6xT//8z9z3333mZrrSZR7pKDilTvBnwzZGuBaa4KM2a0XmMUGWa4trj6tYnccxzz88MN88IMfTB3Yly5dYnFxMXVgR1H0lArYQohSB/bBgwc5fvw4z33uc3nRi160aU3spwopJb/yK78CUCp4B0HAV3zFV2woeFuh22LZGr3Fa0zNX0yd1bFboTu1i6hmnNxxFNHrdqk3TD3m1oXTI0I3mHtxpbVA7NVQXgW/a0TQubMfYmXPnSY+eVBPO8GJkpVJQoAQJvI7uU/KKEAn28dhnL2mnvdgJZzXWWXu3Efweya2XAtJe+4AS1PPzceuawUqNmLiuEVork9/chu11WvpNhmHeN31nBPeuGZFTohvryyOiN1NP7+QoPScBWk1VAohSIXsSKsRoTtCEWpFFQcXSZy0Mh93UWhaKqSvY4QQSD3erZx7XbgmEUZAbmbqgFc2eKYZxJuTCO9ZsddB4CLSaPGB+J2PazfXMyv8D/rQwB2Wr8HspzPdlULgapETyxUQ6DjnyDZCfEQt055M66brVPAuHSPmOjoIJqWJqm8IFw9pRPRkbDXhskaQG9uEV+U7j5t7z1Slxvc8+xX890f+iQur80zgEDoO//+dB/jm61epCwctBFJFpt78IPK/UqNy8MRIv4RfxX/19xD+1W8TL1weFbrNBSd4///F2XMUOfXMWPxnsVgsFovlmYkVuy0Wi8VisVgsW0ZKiZQyFcfCGHxRrGMtaNYEUawJQjPh6DoCR95YLPdWqfqC2aZkravwnIxQnYi/nksqvLsORNHQ/Tw6vnyt7uEEp6HdU7Q6mpkJie/lx+K5sN7VCDRuwWmstli3PIogiKDmj0bEj2PQbqw0vb6JVN/IvR7GyTy9hlZH43tGXNfaRKFXJ3by//v9P+Fnf/qt/OWf/V9zTBjyfW96I1/whV/IT/3UT7PeCnjLm9/AP48RuicnJ/mKr/wqfvu33l36/s//l59hvaN59Vd/E7GCONBMNQQTSW3wTl/n6q7Hccx//P438vd//3e5dqSU3HXXMLY2SMxVrnPrhe4sQfI5lTn/s0TRrReR4zjmwQcfTAXsM2fOpAL2wIH9qRSwsw7sQ4cOcccdd/C85z2Pe++992kTsG+UJyN4W6HbYtkayx97L+r6+Zyk50R9GovnaG87lI/6TmhdPDW2PQF43VX63g6mLz0IgBt0qK1eJfLrOTFYhn1kPFydpByP2KuihUQLQex4oBSV7jIycZ1HlQbKq+XEaaHjXP+jxgwr++5m++kPILRCaEVz4Qncfptrd7xseKyQaKE3rQMeVZooMY/M7Of22/nYdyHQQiKyEdgl96IdjSm2+XVkbBbh9XRMS4VpbPkggttJXNZKa9aSWPNJ6eMJyVLcT+s8D4Tuwal6OqZC/rlmIe7mnM8bCd6bo1Fa09YhaHO+IqGO6WzS9kAI95NnpWF/8+5nKQSOFrlY9xgjgGfrZgtMre7swkZHSKKSSPIQhaeHgneMpq9jqsI15WsKfd9oJDGaCoK5JNpdCEFFyFToBqg4Lq/cdYLzrSU0mjtndvPinUeZyCx8cDW8wpul7Sic5NscR328eh8V9ZNz+cReDa+3jtSK5j1fiBjzUCqmtuF99esJf+cnoN8t3QetiR79EP49WysJYrFYLBaLxXIzWLHbYrFYLBaLxbJlpBRsm53m+oJx1moN/RBcR+M6kPXruI5IRdSnGs+FiaoEUV4DevCnIwXSM27vrPNcSvBdsaGjWmtNu2smR5fWFVXfiOlCCIJQ0+qa+HbXgUaJoUqpcgE7CBVKk+tPPGbfMqIYVttx7jrHytQzH7ilc/tn6nprzOcXxSp3vJSS7/uBt/Lil7yKn/iR7yMIzAToX/7FX/CRD3+EvfsP8In7P1ran8nJSd7xzl/jzhMn2LVzF//5P7+tdL93veNnAXj1V38TAP1QM1mX9EPz2cQKPFfzt3/zl/zoW95MGOZrhu4/cIDf+Z3fo9lsAokAK81CBu8pSDXvhzpx6g/rqwvBht/viWZtS23HccwnP/lJPvjBD/LAAw9w6tQpLl++nArYvV7vUypgN5vNVMA+fPgwx48fTwXsqanyWrvPdG5G8LZCt8WyNYKVBXpXz5e+JzCR463qBK7rUqvX0/ei9vqG7co4YOb8/TSWhm03PUl37ZpxVmuNG3SQWhF5NbR0TLS4dIkr9dSJqoH68kVkHKZPMX5vnchv0JvcYWLIx/ShP7mD1d3Hmb78ULqtuj5Pde0avaldmYFKtFYb+HcxQrbjQSI6kvausFvhxlOfmsm9DsKQj5x+hKZ2TKY2UMNlSvpci7t0VcR6Uoc7RhNrzXo8rN+9pgIirVK3cip4F/oRo3EzIxLpnpm+bjTczAgdBJ6QyGTrStzndLyac0wXWw+3KKIrjFDv5URrMRIa7gqJozVBRrIPtcYRSU3xpO52MRp9HINrJiC9tiGKStaNno5p47E4CI54U0gEoVZITKR5jHHgAxye3M6XHXwWFac8RkkrxaVHHqDXXk+FbgDHrdCd2k1t5TJOPExACOtTbLvnVfjbNqm5HfTHC90JanVh4zYsFovFYrFYniRW7LZYLBaLxWKx3BD79u5gaWWVKKPODv5adBSPTnsOKXM6b8X9PCBWGqWMiJyKjyVTjwMRdKBjCyHwPYHnGvFSFGpwD7YVCQtO3l6g6fQ0RfNuFJdHkUexiTMvjq8odENSt1FvzQnvlgi7QkC3r2jW5JbakALizNgG1+De+z6P3/vff8X3//vv5OyZxwBYXFxgcbF80nIiEbqPHz+B0vANr/lGYqX4Lz/7n0v3zwrevUATRCYNAGB9fZ3XvfabuHDhXO4Yx3V54w/8OF/zlV9KpcRdL6KtXbd0snqL37cg1CNObldSWp8eQMUx89fO8Z6//iMefPDBVMBeWlr6lAvYlUqFRqPBzMxMKmCfOHGC5z3vedx3333pgoHPdm5E8H7Vq15lhW6LZYv0rp7b8H037CGjgLk9e3O/k6VfQQX9scdV164zffGTzB+5l7A+iRv28A+eJLh8gThxvIo4wg06uEmseVqWRMVoIVMhW7s+Sohh3DngBm287mpaG3wc7blDTF1+GJF54qkvXyqI3Vu71wiVv6nIKECoCC3dtP9hpYnbbyG1QjouUzvzYuQjF5+g3RsVH6UQbHeqfDJazDmYAx3nIrwH5ykeW9y40fPdAJURzAfPhAJTEzv7zOYKkXMpd4lxC45piRipR71VIoyzPnsOmQje2fZ8YeT2fsZdnxWtszHoabJOiWN/MLYYDZq8Y1xreuTrfG82pqbwaKuQRUYfOgZX8czqPG//2N/wzXe+iB31yZH9WsuL9MYtIBGSoD5DbX0Yo4/WhO21zcVuzzf/hcHYXUR9NLnBYrFYLBaL5VZixW6LxWKxWCwWyw3heR47d8xx6fL13PayqG4hBpODo+0onbiTkt0Hf72R9OkRkbikjjiU14A2cZajx6d9Kb5Xcv6yvs5OSCq+IIxG3ytzd3uuiXzP9rXibZBDPtIHQa0i6PTybcRKEMbG5Swy19hxBGGsC22Uu5SlhIN7pnn37/wB7/iln+f3f+/dY/sxMTHJL/3yr3L8+LCuowZe/VXfRKsH7/ylzQXv+ZWYZk3yS7/4M/zB//idkX3vuffz+OGf+AVc18nFzaf9FQLX3do0+ODz8bdYR953Be1exKOPPsQjDz3IubOnuHLlEtevX2dtdZVut0MQ9InjODfRf6vJCtjNZjMVsI8cOcLx48d5/vOfzz333GMF7Jtkq4L3fffdx9///d+XtmGFboslj47HrArKMDc3x9z2Hbltjd2HWD/36NhjhFKcve9b8vVHFpcQro+MzS957biEtUm0dPD6rXQ3mYjd2hlOi5l62GHOOe111zYVu5VXQbk+TsaRLYqx21u5L2hNf2IblfV5pIoRKmLy+imaC2dZOPJCokrDiN5CEMppanGXvbedwPUraRP9MGB+dXnsKVwhmZI+S2rYV4/RG+pWHsV0EjUeJ5KxwNSrLo5UQOrYHgjesda4mYeoSGu0VniZz9KXDpHSqXM5e/zNEKLQWuOJjR3eHpIgkemdQc1tQKBzSwKG8e7j3eyavFMcoEuEZHhN8gsChgJ8ttUVHbAehcw51ZxgP+jH4JytsM//fPSf+Z7nvHJkMd/60sbu6tiv59oCiFqrpftqrYnbawgpceoTiIPPonflnElPUKbWvFTDB2H3ts/Z8NwWi8VisVgsTxYrdlssFovFYrFYbpipySZXrubF7lZXEUSCqUZ+ck0mZqCiKzadsMxsvxGhW5YItEbkBYTO1WwWQiSx3ltvf9DuoBnPGZ1kzUZnwyDCXCTucU0cQxib9wfx13OT+U44UuC7ECTx4p5747Wm6xUTF9/t65xTPY41npOPkvcc6Beu22AcSpvtWdEfoOqGXDj3+Njz12p1fu6//iq33X5i5L2qD6/+qm8ENhe8j5+8mx/+ge+m027l3p+cmuZnfvE3OHDwiHldF3glEe2wtVrdsRp+ZuvtPqcef5iHH3yAM2fOcPHSRRbm51ldXaXdbhMEwadMwK5Wq6kDe/fu3Rw6dIiTJ0/yOZ/zObzwhS+kVttaLLrlybEVwdsK3RbL1vFnttN+4pGx70u/yrYDh0e2Txy6g+7C5dI4c6e3ztKh54EYFWq146GVytXIjvw6btDJbZMqIs6I3QiBli4iU99bqgi0Kj1PSiJMZ+k1txd7tbmALARRtUnsVWhcP0Nj+ZJxb4c9Zs/fz7U7Xjp8KJGS+vYDVJt5B2+n399UDK5KFzJi9+CZISv6FttQJfdABSNCbhkaI+jKzBVQiVCevWfHaKRSOFnBW8iC2F0mT2+dCI1bXJiZ9FEyvBaeloSoXNy3Lji0Nbq0lrjMuNZjVPKafAR6JhrfQSQ1vLNjTBYTZNqN0SzHfba7Gz8LLPXanFq5zm0zO3Pb9WZJMiLrv0/G4o/W5emceZD2qU+guuZZTfhVdNCDTG35sDaN31rE763h3nkfzo79G5/bYrFYLBaL5UlixW6LxWKxWCwWyw0z0WxQr9fodExMZhRrVtvGhxIrmGoInMRdnRVPsxSFalmIE98MIUwUeRAO2xscHsdmIrUXaoIIOj2F7wl2TI9XuzfTMjUgHdN2FkeaiVeloVYR6RiEELgudPqa1Y6ZYJxpylLnue8JpNT0w3IX+mYIIWhUTYx3PxguLAhCqHhFt72gWTX9ilWhjYoR3pfWVNrG8lqXt/7QG3nf+9439vzdbof3vffvuPtZd4685zimb1sVvIvj+tbveB3f9h3fRRCZhQxCQM0f/z2JlSYIAh55+CEeevABTp85w6VLF1mYX2B1dYVOp/MpE7Bd1805sLMC9vOf/3xe8IIXWAH705TNBO8yrNBtsZRT3XUQp/Yx4m6r9P3GoeMIOXp/dvwKO57/ctafeJT2lSdQQR+3PkFz/1HWOj3ol0SoJCjHzUWSIwSxW0njzIHSG39xi04DuDdCsLrnTqYuP4RUMZFXozOXEfe0Hokn3wjteGYRVMYp7ndX8TvLBI3ZdNva2hq7d+/OHeu7m0/zhVoR6JiOilIROtIKnRlmUU6WQuBrSYROncg3QpngbepoS7Jx5l0dU1EaL/k+yM2XCNwwxVrjA7LCthCCajJlqpMH2TAZQ5x8K+IS0V0m7QyeuxycXFR6rmwOw2+WEAKp8+J2mbAfYj47X2y8evN6Z21E7K5NTNJeWRp/UJJ2MEgl0MBCKJDr6zQmTAx56+EP037sY7nDdNAbbUsIgok5qne/mMrdn7dhXy0Wi8VisVhuBVbstlgsFovFYrHcFLcdOchjp56g2+vRzkRoL60rlluwa0ZS9ccrt0IIJKN1kG8ERwoqviaKR+esNaau9mpbp47rKNK4Jc7pTl/RD2C6WeIQSyLNW11T91uLUZd6xRdMN8rHWqsIVjvGfe17gkiBg07Ffa1N7fE4FjcsdGudRF3qgRBsFgD0w+E16PQ19QoZET4RvGvG7T4QkE3cudnH94Spod3v86M/9EY+9M/jhe4B7/6Nd/L5r3wltx2/I13oMKBZEzgOfPXXfiNVD37x58sF7yzHbruDX/qV30rFYKEDHnv4AR596AGuXD7LpUuXWJhfYG1t9VMqYDuOg+f71Gt1JienmNu2jd179nL48BFOnryL4ydO4vs+O3fMcvjg3qesL5annhsRvK3QbbGMR0jJ3D2vZPFDf0vcybu06/uP0Tx219hjHb/C9O13M3373blSKfOPPQKMF7tLHd9bWVBX2EfGAbXVK3Sndo13d0tJa8cxgvoMM+c/xsKxF6U1ttEKoeIblmy7U7uZvH4qt83rruXEblXi1G1Ua0xXa6heH4kgRNPJyNOxUjwerNDWo9dO6mE6Sqn4KgSuhvAmndVmSaTOidtGAGdE8JZa4AhpBOGMI3rQzpNhNGZd4GhNJDSxUmmceEg8ElG+GQojSHtaDp+7Up/2xoiSejJlse2hVpuK3VU3X6NFa03guMnVL+9JXKmztvs4jaXzeL11+hM76IUx586cYv/hI9R9j/apj+fHKxyCxoxZXBL2QCn6U7sIq03Qmk4cs7vbpWoX9lksFovFYnmKsWK3xWKxWCwWi+Wm8H2PkyeOsbq2zv0PX4Lu0IGktRFZq37+mDjWSJkVXgWOGK31fSNIYdzIcTwqnDeqgtW2plkTSGFqWMdK4zhDgbjdU/QS89dEXY8ItWAiyAdisuua/kphIsd9V2wYPe65gkZVUPEyUZ0KYkx98SKxYstx6yoZQ+56yLxrPophvavxXZLPY9gP1xGl56pVBGvrvQ2F7snJSX7sx36Cn/iJH2NhwdSBrDQm6Yfguxon8zmDEfubVck3ftM3I6Xg5//LT48dl+9XuHTxAl/6BS9GqU+NgO37PvV6nWp9iumZbezYtYd9+49w4uRJXv6iu/H9/Jc5CDeecJ+emtzgXcszha0I3lbotlg2x21OseOlr6Z37QLh6gLC8ajuPojXnNr84ITsPUU6m90oR39Dy6zTGwgrTZRXwQk6RlQUkrA+gxP28LqrCK1wwy5e0MEJOrS2H92w3krQnOPKyS8wMTDDXm9hZCW9T6K8NaBcHxFHKNdHhj28Xgu0xp+YQsUR0hk6kC+dP0e9H0FGDJ3QkiViAjQf6y+UCt2Q1KXOPI8JIXAx9bTT0QiB1CIX531D40r+XyZ4o4f1qwOtqAlJmESYDwTvmw0wHwjYZXHyWmv6qNw4nwwDF7tzE5/9VmqSi03alQi8TkCn16VeNSLzxcuXWVhaRFbqVPodZCGyXrk+2jECeXvuIG5vjag2ne5z/cpldvsaMgsses1ttGf357/vgxWiyWC6OJw99RgHDx+l3mxuNnyLxWKxWCyWm8aK3RaLxWKxWCyWm0YIwfTUJHMz66yszefeW+9qphvDyG6ljBitYhO3XWznSfdFYhTkDK4jmG4KqpnYa6UhDjXLrdHpxG7fCONFokK7A9G7UR3vBM8y05RpTe6tsFXxX4qRIeM5AqdqnOjZPvVDjeeWi9tFXEfw9l/8iQ2F7l/91Xdx/MQJXvLSl/KXf/kXbNuxm527TJxqEJkJ26o/jGVPIz0lNDeZ8AyC/obvb0ZewG4wNTXF9h3b2bd3H0eOHOXEnSc5cuzEiIAdx5oLCyX1NwuiitYbT0Y3GzWmp+yk7mcKGwneVui2WLaOkJLa7oPUdh+8qeMHcdJCSianZui0ymPRk7OhpINM4sNl1Mfvr6Okg5YeynEJG9No6aIcF6/XIvJqJu7crxlH99o1RCKA+r11vN4aYW1jcV7oghxbUgc5MyDSMGshcIIOXncNoRUi7LO2/SjtbQdRXhWUQsYhtdVrpo44QG+NSx+4zo6776UyOc3i9WusrSyPnEYKwRwus/v28Z5TV0YfHDJEWuOSreMNu906i3GPIBGeJTcvdg/aLAuHz7YYa0WsFWHGW16sYT3AQ+IKiUIT6HhsjWyDAJ2tpW0ixz0cROF8TwYjdg/ZaqXxLV1Vna937ibjHbjQj/qTtNdbPNB+jJNHb8cRgoWlRdMvx6Vbm6AS9ZFKoYVAO24+tUDInNAN0O/16Gf2CWqTtOcOjj7wljy7aqW4cukiR+84vpXRWSwWi8VisdwUVuy2WCwWi8VisTxpDuyZ5fS5vNitFFxbUeyclkgpcq7rJ+PkHsuYGcLJuiQsCM1CCHzX1PMeIAUEoSbyNa4jCvuPthtG5CYbN9pXCGEi0Ee25xMrncSVHcbgyHzUeawYcUsLIXDksPa2ECClQAKTdSNwD4R6zxUIka0QOZ6zZ8/wp3/yR6XvZYVuMELgF33RF9Ppq5zLXGMWFriFC9LqKt7+335h0z4UGQrYFWr1OtPTU+zcsYO9e/dz9NhRTp58FvsO3gYyL2A70nwHBiit6QfF1pNzyHJJYqWl2DY1nLaO1OhnN0BKwR23Hbz132/L08pA8N69ezdve9vbCIKAEydO8O53v5t77rnn6e6exfIZhY5julfPEbVWkX4VObuLpZUV1ldX0VrjVyqEYbhxI0KgXR8VRzj9NtX16wBIFRO6VbpTu9OoceXVCDW5eOeo0gR9Ldek317eVOzODyTjiFYxIo4AjRYOMurjhj2ENl5moSIqnRWEHt5IY8cjvWdLiZIVulM7c4K3CvrMf+Kf2H3vq1hcyD+H5S4HsLa8RC/a5LphXNUeMn2+cRDsdhtcCNdR3HyMePGumH2ttM4J6Bpoq3yIuAJ84aT1tjXgComXEWHr2iVI6lrDmMWUYhCpnu+DKySxVrdE7t7KNSp7FnaEIM58b9zEgz0Q4X0hiYSmrUMaeHhi+Dl5CG73ptnjNQCIVcyFq5dYJeKj3ausqD4ekh1Ojef7M6gtpggNkI3p9O/dyV0bphwU6fe69LodqrX6jZ3UYrFYLBaLZYtYsdtisVgsFovF8qSZmqhx+5GdPHYmPzHcCzSXl2L2zDo5YVBpcG6hFjioXb2RAFncXvMFYTT02XiumRRd72gqnk7EYSM8d3oqrXWdpd3TNKv5etj5fg3/Xta3wf6D7WnyoyAV4rNeICFGr5uJXdeEkc7FqUspqFWyjnbNegca1VExv8jq6trY955113M4cvTYyPayFsNI52qBd/qKVlfzA2/+KX7g+/71hn1wXY+f/vl3c8fxO5homGhNrYcLFBxJGg8vhDAidqjTSPoBsTLfw4G7v+jSB5JFBeA7gsmGib7Psriu8T3FZF2SGAvNmEs+U6017U6P6al8vUzLMx8pJW9961v53u/9XlZXVzl48CCeZz9ni+VGUEqxvrpKEPRxXZfJ6RmcTHpGf+k6yx99D6rfS7dpBP2pneiJ7QAE/a2nf2jHpdJeSB3eAE7UR0tnZD8RD4VgLR2U6+Fkos9Fpo1sjIuII2RybOx4CB0jozC9fwutESrK3CdDsyJw4DoGkC79+gyVznIqeDtxSGPxHOs7bxs+IEiHoD5FtbWYthYHfc4/8BFiUagdU6DTbvMFjf38dfsCXV1u705re2uFFCaI2xMOUggmpM+qCrgVcrBIqnerxN0+aHEr3meRiNsC46COtMIdbBOCCg5Ka6JN+qmSSPNsLLiDvEXjG30q8pIa6mCeFWI0sdbGmS0EDgIpJE7WoS5MS35SA9wTEj8Za6hjKtLJXbNl1WOHrqXX4yOLFzkVrqbvByjORus815vGuQGxWghBc+deoqk5otVFourEDV+TKIzAlu62WCwWi8XyFCH0U1kAz2KxWCwWi8XyWcWV66ucOT/P0koLIaBZFUw2JI4URFE+wNF1xjhuCoxGUI6iVL5trYcCJsB6R5fW1Y5iTadvnNFVL/++Upp+Iqw2aybau19iiJICmjWBI8VYsVtrjdZG5C97+DZxm3mxPIzy+zrJ+wP3dxoxqjWtrubacsz2aclUo9yq0+mrtP81X+B7jLjSB/R6Pb7yK76cK1eulL7/+V/wJfzIW3+cWtUzjnUNkdKl18d1zLUVQnB9JSJI9lmYv8a/e903sLa6UnoOANd1ef4LX8Kb/uOPsm120pynMD/vu1CvDia+Nd1gtI45gOdA1RdE0ehnUPFI4/bDSHPuWkRYogPsmJZM1SXRJvPgB/fvZtfObRvvZLFYLJ9ltFvrXDz3BHE0jFURUrJrzz5m5uaI+12uv+cP0WPcx+25AzfmrE6otBaoruddz2s7jqU1imEgWOdXS03Mn0ZJj7A2CYCSDl5vncbSJZyoR+xW6E1spzu5M1e3WAuJcv38TX1E8AaUwonywr0M+/i91dy29uyBtA+DtmrLl0zcebIprDQJmrMbXocemq6As8EaH+xdK90nzjjLfSGZdCrMOVUAWirkSti+ZVHfN0tFOKmYO8BH5p4TY63ojKlNnsVJoswHRFuIMi9LgJGQO8rNOOMFUBEycY5r2iokzi5kBKrCTcV7MJHtsQaVSO8CqAuXGVlBDuq5Z+urZ87dFB7PqW4j0DHv614tHcM9/hwH3caG48wyPTvHnv0HiDvrLH/gz7g+exTkaCmfjTh2/E78SuWGjrFYLBaLxWLZKjf2ZGKxWCwWi8VisWzA7h1TfO7zj3H7gQb7t7vMTDiJ8zhfDhCMaBnHmo3WXmqtafc03f4m+xVeD0pkCiFodTXtvqbTVyNtuI5g26Rkrjkq+gphJg8dacTsWkVQqxhxe4AjoV4RuM6o0F3Wnkz+G9SqlAJcaSLGncL1ydbWHojhYITcKIa1dsz1lZhz1yKuLpvwz05//DUKMtpBN9Aj7uUs1WqV//STP0W1Wm7B+au//FPe+iNvodMLUwHfkaNjANPXTmA+vzCZd16Yv8YPvulfbSh0A0RRxD+972/52i97CV/z6s/nz//0/5a2r7VxZ3mupFkTeAW9Xyeu75WWIlaj486K154rOLTLZXZCJgsyoFYR7JlzmJt0tjS367o2QMtisViyhEHAhbNnckI3JPV8L56nvb5O5/zjY4VugMr6wk2dW4uyRWDCCNxBDxn20HGEki6xVyX2asRuhbUdt7G2+zjd6T10p/fQn9xJWJtCKNNHJ+rTWL7I1JVHIOP6Floho0LMiBCj/ZCSuODMjf0qrblD6MxDkxN0RtoydTeG++jiQ1YJgx4d8Jo4Jc7j4jNSRTjMyqE4qbROheCns1BHqEfF6GINcUfIm+rjVupqT0ufCTlcKOEi8YSDl0yxGof28OwDodv0y7izcws0gUDH9HREiBHbI62JMx5zDbR1xLzqJW748YtAWzrkiXCNy1F77BgeClfpj3H3F2k0m+zau8/0vz7B3Mu/hkbtxkTr5sSkFbotFovFYrE8pVhnt8VisVgsFovllnPlylWuz+cnpQd1p8uivMfFageREbrBGEgqrkjjxrMUnd1p22jmV3VaL1wAFR8aFWmEZzmsib3SKhFBY021ImjWhucbuLRNvezNp1JVibg6GHdxHEUhNnWD67zIDrDaViy38hO+YaQ5sttLI7uzfV4pEbcnamLDSPMPf/hDfO/3fA+9Xrf0/c//gi/hx3/ix/nzP/tTfvnt/40v+qIv4Xv+7RsIM5+z54DvmYnfK4sR164ZofvK5Qulbc5u2wVolhbKXWdSSu5+zvP5/jf/ONu37wTMgoNaJf95xEqz1lYjLm/fFaUu/6y7eyO01nSD0VrtAxxH8ty7T+CUKf8Wi8XyWcq1y5dYnL8+9v3mxCSNhbP05y9v2M7K3mdtrVZw5mHDX18w5UFqU0lceYRQCifs5gTR2PGIK41N26+uXmH2widy21qzB+hN7cptC71qGkMNSZ1oIXGi/vC8SoFSSBWmjuHu9B687ioTC2cB6E7uoD+xI21XxBHVtWumDRUjgO7ULuMmH0OApp0Z1gfjRc60FtNnIJ2JEgfzvHTQm2BVBbQTR3qMItIq54QuHvepoi7c3DOUg8i5vbXWtPTm9cld8sf02FgAnhAelcTF31cxXR0bB7w0134l7tN0POZkFV84BFrRViFdwvS6aa3p6Zh2ifNckn821Hr0+k5JnylnVDjOfmtdBFPS52pc/vxmxuLyudUdNHEQSa1wUfHZu2MX3U4bISQTU9P4vs/Swjzt9XUQyc9qc4IL586i1eafvu9XOHjsGJ63ccy+xWKxWCwWy5PBit0Wi8VisVgslluKUoozZ5+g3e6MvKe1EZ6zc2NSDiLHRyeX2z01Eltdr4yKlePE7ijWLK3n35ECtk8V4i6VZnFN4ZUIv9UKI+KxaWdrnqGBOF6kKHYP9ouVHhFdjWA+KoxfnB96mZTStHrge3DHPg/fzbddJnZ7DjRrG4uymwnez37O8/jExz+G1pqJiQn+7j3vTSI2dRq1OeCx05f599/7nWOF7n0Hb+ONb3kHE5Mz+PT4/d96G3/zV39JEJTXZ52cnOLrvvHb+LrXfDtzk3Jk8cF6R9EP8+NuVkVSpTOPFFAp+ZyLzK/ErHc1u2Zl6XfgyKF9bN82s2k7FovF8tnE2ccfo9sZ7zQVUrKzv0TvWvn9AUzt7tW9J5FRgBP20EIQVRq5CPHSG26mvnZWyBZRgNtv5wVv1zeCd+54lY+n0ZqpSw/SWLmUbgqrEyweeF5OQI/8GtrxEPFQyFZeFRGFuFFSkzx5IBJxhNQxynHpTZqFXJNXHsYJe6zvuA3lDcVNr7OC12+nfYu8GsHE+NIZIZp1NItxj76OmfSq3HbwEP/tk+8ZjjupfV0Wz118VinydAjem4ndoY7pqCh3n/YQKIYu8IEDW2szLlONfPwUaQ2HinSIksUBAsGcU+GwP5WeW2lNqNWIa3pdBcwXhOeeimgVBG+T+lN43itccwfBXq850r/iE8nR2gyPdBZH9hsgEbygsp0pp0JVOigNM9NTHNizL02o6bTbnD9zClUQtaXjsHP3HpYXFnLPh43mBJVajV63g0AwMTXF9Mws0ikvsWOxWCwWi8Vyq7Bit8VisVgsFovllnLt2nWuXhvv3iqilHF8l7lty8Ruz4V6Je/EGbh3i9pjHGsW10cfd6cbMidgX12K6fQ1jYrAL9TurlXKRVATLb65OBrFxppd5hoeCN7ZR3ITt26uhxAQx8bhXvPFyPnaPcX8qhl8L9AEyZzp3ISgXpX4rpnj7/Q1VV+U9sF3zQKCjcZiBO/vptfrbTjWf/1dr+N1r/vu3NgGXLh4he/8zu/g2pWLpcdmhe4Bt+9zcB3B/R/7CP/5bT/OuSfOlh777Oc8n1/79d/ICfxgnO6r7eEEbdUXNGsSpcy1yv5LSAjj7t7oOkSx5rELERqz73RT0qia/bt9TaRcPv8lJ8ceb7FYLJ+tPHHqcTrt1tj3peNwYLrB6sf+HqFiQBC7FYLGNFF10sR0qxgZ9fF76+lxGgjr0wTNuXyD46a6Cr/jnV4LJx46gDUQ1Kdz9wIR9XGigKg6kTu2vnie6SsPAxC7Fa4dfxky7OEGRvyL/DrKqyCiAKkVWgiUWwGtjciuMzEoWuHEIUF92gj4QG35IjKO6M7sHfa338HvLKfCZuz49Ca2ZcT40eVcizrifd2rrOnsODVBQdweOI5vRvBWWwoAv3Vk63brJF7dFw4V4aC1Zl0FRGgkJtLcReIkY4iSGPSsqNxT0ZYEexNZnl/It9utc8TP15Lvq3hE8L4edXJuc601y6o/cl6n8B1VevTa7nebI88r2VcV6fJ1d7yAP3r0o1SFicpvqZA1FaSC/jFvirsqcyPiuuu6HD58GN/3OfXIQ4RBIZJ/cI5KlaPHT9DrdomiEL9Sxfete9tisVgsFsvTg83Ws1gsFovFYrHcUhaXlre876COs1JGmCxOoJbFhIeREbEHZJO/tc7Pb7uuyNW+HrDWUUaExgjJg1rX7b5mraNQWlP1Ta3uiifKjWKUT/gOaPcU611Fp69HorTz/c234TmCfgitrma9Y/rW6pra5UUaVcmeOYepRr6PvdCI32sdzXpXU/EEsxNypJY1QD/ULKwq1jvjp3mf+7zn89af+iUq1erYffbs2ctrX/uvSsd27dpV/vW/eu1YofvAoVGhG+DKkqmz/pznfg6//z//kA99+GN80zd9C/V6Pbff2TOPl47Nc0UqRgPUkkULUgqqvsD3zOIJ3yNdGLARq+2hMNAP4dqy4syVmDNXYq4sKeZXApZXRxMNLBaL5bOdiam8GIjWRhjuruN21/D7bVqnH8DrtXCDLm7Qwe+uIuMQ5fpox0V7FeLaJGFGdBaA31nB66zk2y9buKRi3MJ+caVB7A5d0wIQWqOygqaQeL113IzIDtCZO0BvYjsAUcU4bZVbQSOMi9s1dZ21dHN/IgTacQudE0R+ncgf3t+iSpPu9J5c/73eOmF9iu7EdnoT2+g359DSNdfHcdGOh8rUAVdA06nw4voe6sLNnE3gF6YEhRD4JfXNi7fGskVhT2UNbx8xUmO8r2MCHaO1ZiBTBzqmpyLWVUiU9FphPk+NpqciuipKxe4sFeHgJkHj2f+KRKiRmuFXog5LcX4xoF9SQ31C5oVgIQReaT35jXEYXaDoFXq7x6nzxBPn2OZUqUqXmnTZ7tbY7zVxETSlx8nKbGlCTRRFXLp0iXZrfazQDdDv9+i0W1RrNVOT2wrdFovFYrFYnkas2G2xWCwWi8ViuWUopQjDzWskDvfP/z0IIYoydTa98uPaPU2QiONlAqUURijXmlIRVGlYXFd0A0UvyDcQKyOo16sSzyWtM152njDWrLbj0rrcQphjXMdMaJbVKy/DcwXZcs9RbBYErLaNSznKCP1CmFju3bMutcpwwrLb17n631MNE9veqJr/HGkc9VFsHM6RMu7vceJ9t6+569nP58c2ELwvX77Ej/7IW4iiYSSn1nD16hVe+9rvGBtdvv/gbfzHH3sHO0qiv9c7mnPXTBS5lOA4Dm/6vu/nH9/3T/z+//gD7rzzJDt37uTtv/yOsY7sWkUy3ZTUfIFTiKl3pKlZPviuqJLFB1nGLVrIEoQb1/u0WCyWzzbCIGBtZWVku1AKoRVCa+Kgz6o/Ra85jOMWWtFYukhlfT53XFSbRBXEYq+zsuHvbwCkw9Tlh2jMZ1JChCCu1Imz9a6F2XfgkRaxua+5/ZaJNM/Qntln/pzdn7anHRflVYduayGMAJ2NWx/U6o76yLBnFtBJh5kL97Pzkb9j+2P/SKW1mD+fkPQmdxBVmmjXNy5xKRE6LkSVSLR0iRGESR8a0uN51e25vgsxKiI7QoyIvJ9Kx3ZRZPaQSGHc1LLQs0FcuNIapTVx4kyPUcbRnYjkEWZ7hDZx7cnrrGgthMCXzsj1GCd4F79rV6P8Qjch8rHqwIgjfFz7RYrC+bMr23hOZVtab9yI1z4TwkjeU9LnmDdFU3oc8CZy5/CFw8mJnXzr7feO9C9Lp9Oh0x5fdmDARmK4xWKxWCwWy6eS4lJSi8VisVgsFovlphFC4DiSeCuqIOUTqNn5QykEjSp0evkIR40RxUXiwinOFg7Kc/YCjesIar6mHw5d4EKY6O6aL3Iu8QH/H3t/HjdLcpd3ot+IyKX2qnc7++nT5/QuCQkaLYAAA4MBY3t8L/b1vdfjhTseG4NZhHc2g0C2wJZtMB4w9vWMzTVggzfsAQwDDGBABoRYJHW3el/Ofs6715ZbxP0jsqoys7Le9+1Wd4Ok+Orzqs+blRkZkVl9MjueeJ7fOLJC8Ew/nYndVsC2dcejxDDN5/iaAQSVOcPAE6SZQRXayEwuxBfmu6sx5gDdpmA4NaSZFd5nDCfW5X1uw8awFwXeta7kYGyFVm1gb2hoN6DdWETECyEIPNuHOxWnuB0TNGqMObM+fMpb3so3fev7+NZv/JpaUeGnfuonAXj3t78Hz/Pmju6rL60Wuv/Gu7+fM6fW81tomBTmTYWAdkPQby1PBz/44EP86x/6kdpo9iqeEnjN1fuZQkRopkFgEHK5bmZd7fYiQkCvs9r97nA4HJ9sGK154dmniaOo/EEuMhONkNniQTfpn8Wf7JeixZu714ibA4y3WAEXdbcIRruoxDpqpc4QOsN4PsIUHvZQerEQxtC//hGizgZpszffnvlNZBpbYVrZB6ERVkj24vH8WJnGVsieHRc0GW5cYto/vdjmBRjp5SK5weTuXX+8Z7cJgUhj/OkBStvntgH8ySGN4Z15/5uHt+lsv8Cd+z4Do/x6tzr5K5DJMAXnNkKQyfKLyRnVoik8JoU60RJBNbhcIF52KLnMj/lYhHGRn1tir4cCGnk0uRCCWGccmKRUVzvLlyQUJfqqXG/bXK4rnhg9r9s9wxeSzBy/aE1jSsL4VKdL+1TvVrX2NkBTeEwL5+sJHyUkB8a+DAVI+iokNhm7WcQp1eTTGlv4QtISHh+Y3p479pWQnJEtPiXcQOVCdigUPRmwrxcvV5NoShxX/n2s5fj3K6U8Dm5dY3j3NkZnNLoDemcv4IfuXcjhcDgcDsfrixO7HQ6Hw+FwOByvGkII1gZr3N3ePtn+Ndu0sfUJZ5OPnhJ0W1ZwTTI7qanUQog0Ne1oAzrT8/ltT4ncYW0IPDl3WwO0Gvb46hTk7T3NVr88UWwMHIyXY8nj1CzV+vaUoFHjTNcGvMqEdZzCcKJZ79rzSSnotaxYHsXLk6OTyNAs1C3X2jCeaKRYCPrawOHEkGSC85vl42fXo1gPXQjbB9+TS/HxQthG0zThP/37HzrSPTcTvP/yV38tX/mX/gIvrRC677nXOrr7/bX5vew0Ba3Q4PuCViDoNEVtLfcixpgT1U4/at/qcMzs/yq7dpsC3ysvQChy8eyAZt1Ndzgcjk9SDvb3loXuAtoLkWmyEHKF4HDrPjo7L85FZpUlNPeuMe2dRgdNwArRUWeT8PAOKo3mxxqhwKS17xcymRKM9xBAe/tF9i+8qfChxEhF5jcLfQFvcrhov4bUazBeu0DvxhN40RCtfKadLbTfzMPM88eJTu1Pcex+AxmN5m7mtNllohStvRvzfYLxHv0bT7B34VNW9sGepLAqbzakipAthKAlPSbZiofYrKnKG5HK5eOjhOxAWOnXOqtPLnmX6kwjbTv5GARWDJ45kEOlaBufbT0tCcSzq1wVuYuP8VWCd2p0KbpdCIE0nKh+d5G6OPKmUCX3+OWgy7oO+XC0jQHawuds0GY3i3gy3sVH0pWBdYUbyVDH8+jzQCgeDAZ8TvPc/HoMVMhFr8OOXnw/pyZDYxcKzOhKvyR2GyBZ9R5nDLMr1241iXdfIti+ijCaqLPBcPPe+WKPwPfZfeYx4vFwcf6DPfZvvMiZh99Ca23j5VxCh8PhcDgcjo8JF2PucDgcDofD4XhVOX16i/CEdfvkirfRNCnHSQshCHxB4Fnxs+jCWaVzZrXGHFESumd0a5zDk8iQpMuTgUFFfFUSWo36TtTVCweWYs8/+lLCM9dTdg/L06ueErXjs4L7oo2dQ804gqYPYUVrzTJTij6f0WtVanViBfLh1I4702YedW5jvg3f875388EPvB+AZqu1sj7jT/3UT/LHv+yPHSl0f+N7/imDwTpeJVpcSkHDF6x1ZUnojpP6cdTVPa9Da+vuP8m+q9oVQnBxyyvFzM/od0Le9uaLJ2rb4XA4PlkYHh4e+blRnhVXC3/fGuUx3LxE6jfn2wQQjnZAl1dpJS1bC1wr38Z6C4GpxjPnD9Lu7afnArQXL0c0p36LLGjOhWOZRKh4QtzsEbXXiZuDuet7jpSEh7do7bxIONqheXCLtesfpnvn6fmYBID0MLL8gDbKJ/PLDtgsaJFWtrV2rpbHXcNJa2ZPKg7kqrCtjSnFhVvBWdFElSYQi4J0KBYe57Bw7YuR5ALm0eKy9OfFT4IpubYNMDYpWUEwlkKwIRtLk5knebIvB7SvErWPv5rVSPU3BuusyUXt974MeCRc5z7fpgd0pc8p1eKhYI23N07TFj6nPVuffU2FXPH7bKnm/LqGQjFQYel9d6STpZ6tq/J3xWBrl5dHU1wAYUc36PVQxZghYxCZXZAhdYbUKTcf+y2aN56keXCTxuFt+jce5+xjP0sw2kFKSZO0JHTPm9KaWx/9ELr+RdzhcDgcDofjNcGJ3Q6Hw+FwOByOVxXP87j//iuc2tosT6TVIISoFYRnvpIqVXFcCCsInyDJ2rZrynWXjbEu7X5H0u+IUvt1giZYMbl4vnZDLMVdF/tXJ66m2WL7/kgzjmw0+pPXUj70XMLVOylX72Y89kLCzZ3lycJMw43tbC7+7g31/ITtULDWsdHfa21BryUZT5enc0NfsN7NXe4sFg1kmSHV1m0epZBkVsz/4X/1ffzcz/wfAPh+wLe/93/lO77r+2isqOEdrXDyzYTuXm9tfo2qjKdlMT/ThnEMo6l19xc5qX9sVko7Smwd9Nn1n8XS12ngdTW8m6HggQseZ9Yl3Zag3xZc2FLcfzEgDFxwlsPhcLxc7GNAL9WdnvZsjWktPYzyEBi8eIwpHuWFaCGJOhsld3iVzu1naG+/YEVx5ZN5YelzA2jPz8U++4NURN0tsrCD9hs2dr36IiIVo637ODj7SGlzMN4lPLy1tK+pyJXaC5aeY2nYLh+mU1RyTOx03UPMlK/pzXTMgY5Lzz/DYmLQGFvTWgqBl4vSLeHNexwg7TF5jezZu1pmNDH2J8Hkx4r5/2Z/nt0zMf99mYnJlp6704p4K4WgJZZTVF5JiHptAsAxx3hIlFzI3ee9NvcHfTZUg03ZoCd9zigrZG96TR4KBtzn9+fvihf9LleCXundcV2FSwsxq9doVmu8rv+m8L9qLe6hjgmFpCUUTenRkh6P33iRjVNb9pzG5KkD5W9n1Oxz58HPIQ0W30eZJWw9/wEu3nuJ6d7qFCedpQzv3lz5ucPhcDgcDserjRO7HQ6Hw+FwOByvOp7ncfbsGa5cvnTsvkrZaOiigCzliglIUZ7DngnSUor5n+PUECXl2s9FprGZ1+kuGqx7Lcm5DcnZdcn5TcWl06okSs8QQtg461ykD/3VSvvdA80TV9NawTtJrUi9fVCeuBxHhmvbmmt3M0ZTQ79d/8oeJfD09ZRnbiREi9KmZNpOBHtKIKUg8GESw2iqa8bCklqcZmXnuZLwH//9j/FDP/jP5+P/69/0d3njp3wajz76Vv7Bd/+vKwXvKvff/yD/6B//M05trqEkBF799TPA3X0978dsfAYreB+MDaleTGsfZdaeT8oX9kkz22acGJLUHl+3YMIY0NouACheOyUFGz3FPac8Lmx59NuS6WRK5lxMDofDUaLT7R75uciKItts5VFeOiPsYIQkbXTm+8ssAcovA9PuFkmzb93POoNciNVCooXCGIM/3mW8dmH+k/lN/NHuoh+ArErRQtSvyKphvHah5EQHaBzeWdrPyMoKPzHz2pY2lo8REu2VHeVqOrQPqJzw8DYbz/06Kp7kBxmU0QS54D3RKR+Y3sJgRVNtNCkmF69BaENaiTz3hCRFM81/4jwqXLNYlKiBmPIzUgixcrLxJHJ0Wtkrq7QPEFTd+yegTgy3qTaL7SGKLa9FJxfTq0coxPzcQgiu+D2+oHVhLlz3VcA51S4J2X0ZLC2K7MvyYgsl5MprJmG++MCvjDsx2bxW+uzn+eRg7u6OdcbUZHhClsT0Wwe7/NaN5zh/z0WajXCll117AQenHyj3Jxohrj599MsXEI/HR37ucDgcDofD8WrirAcOh8PhcDgcjteMZrOJ53mk6dH1IaUUKyPNiwghUDJ34upyHPnsszgXRpuhdY1Popqa17HBVwaxVJvaisOeEoymmp1DTejDelciZfFc9p+2PGb9FKHWhsdfTEhSeEynXDql6DTtIKPEcGs349aethPsK8bebojSecEKr9pYUX/mVg68RQ3zNAMpDFLaCPRZ/e3hxDCeGkLfbk8Kx1eHMI4MzcAuRPjlX/q/+Lt/9+/MP/trf/1v8Ie/5Avn1+utn/5W/tH3fB9f/3VfxXQ6rR8IcP8DD/K93/fPGQzWSFLD4djel2Zg+zyu3KcogRs7mjNrqjifb6+tsTH1Rfd9XT1uYwy7Q1u7vd1Yvsiz8qazdIGqw9sYY93tKbRC+91wOBwOx8np9QfcCW+urNutkknht6JnGxCCuNknCxpWJDagRR5HUqjUbPwG/mQfkcddayHJghbk6TJGBmzf95k0967PBWipU1p715nojLi7+bEPVAimvVN0tl9YjC2NlupoL1EQ92ekfiOXle32JOwQDu8y7W6BVMg0onfrSbQXcnD6QYTJGFx/HC8eE0wOuPng54KUCGMQOiPF8F8n1xiaZB4TniJIc0f2vL9G2Prchf5Wc2GkEAhTJ0iXJxiFEAjzSrzWufhcuWTF+tu2X8e3HCDRmHkN8eoRs2UGGgPGRoc38trbXRXw9s3LHCYRv7XzEgJQyCXR+lAn5dI6+WKA4pKGmXu6fO78nc1oMmPd8CC44LXZUCEauJWOiNHWXS8EGOvOP+e15+7ts36Hngr5SLRDkt+tu9mUoU54tH2afZEidf33b5rEXDvYoX3Mgo7J4By89NulbWK8d+QxAN4JSxo5HA6Hw+FwvBo4sdvhcDgcDofD8ZohhOD0qS2uXb/xqrapZsUfaz7zPUOWLRzDrdBGX6dpPlkqrIvXIDB6WWieRVcfjOykYZTAzR1NMxQ0AoE2VlCfTVsmqSnVlp5xZ1+T5Br/zqEVzlsh+J4oObEN9UIt1Lueh5FZMtNkGopmsTgFJU0uzhYmrY0V+qvYWG8I8vMZY8XnJx7/Hb7hG/4mOleb/+yf+3L+p//pTxMnOhfV7TV/9BjBuyh0gxWXZy5938ud/RKmkY1QBxudPmhLfF8wTc3SjHucUhKfZzW2jYEoNaSZdbNn2l6BVlgjhmMF89l2lcfOT2N7fDHyPsnM/PrU0Wo1j43tdzgcjk82hJRcuu9+rj73HJNJwelpNCoeI7Kk4Ke2wnDqNUAIRJYy6Z8mafYxM2ez1giTIub1sG0EcxFpNDIakpo22s8dtEIwWTuPisf40aJed+PwDnF7rfwQfYVUa4VrqZaEbpnGJcd4Gtg64Y2D2wijyVTA8OwjjDbvZevZXwNjmHa38KeHyDQi6mzSufMcwhhUPKF/4zEah3etsA548Zje7aeRWUJ75yVklpB5AZ/T7fOTgz7p/KXHLAnGWb7NNwsXcE0AjHVum2XBWRtTEX5PXmrkOExl0cBEZ6X2AyHxkcRGk+VR6r60rv7YZCSV3s5qhs/GqTELUTknSmJGaUQgVn83dvXqePl5XHxhEccsmnysE56MdtnVkX0XQfBQMOCN4frcvX3J7zLUCc8k+7b3Arb1lHGS8qA/mF/rtvS5P+jzeLxIKpiaDDNoExxkTJIVUUfAjb1t7gs6Kz+HmjQCQLX7eIFkMo1ASEQetT9boIEQdLbOHNmuw+FwOBwOx6uJizF3OBwOh8PhcLymbG5u0Gg0Ko7ZY9MPXzHNoOzAlVIQ+pLAt9HeSi4mN1f1YxZzPe8vVvwdRZqoIHQbY5ZiyGdESZ2jvNwuWAd41bk8o85sU1cWOtPLceuZtuM4DmOsy/pwbEp9vnb1Bb7lb34dUS5ef8kf+kO8611fD1jne7F/Anj009/Kd3/Pcg3vBx4sC932OEGrYUXuGaEv6Hck5zcll04rTg3UXFwOaxYTZNpG0lc/0cawc6g5GOu5WG0XFNSPfyk8VtjvR1a5J8fVhT99auvoHRwOh+OTFN8PuPzgQzSFRqQxIo2R8QSDIGn2SdprJK2B/XNrgA6atkZ2o0Pc3VoI3QBSYqRfFpaFwNTUw1bJeOkv/6hb/rtaGI0XDV+VcdqI9QWTwTnSoDl/ZxBZQjDexZ8egjFooUiaPeL2OqONe0i9kNHGPSAESXuN7Xsf5XDzEkmrR9ReJw3atO6+QGvvGp27z9G9+yzd28+gouFinMbQvfUU3TvPzvuj0ph37N7h/3PjGsosHm5SWCd3EQNzJ/T8GtWN9WO5UMeQockK/UyMZsdERHk091inZMLktcBtDW0fK9AHQuY/VqAVQuALVSu6VxfAxZV62DdH+7S8eneyRBAga+PUDYY0j4lPMWQsxHUl7M8D4YB3ts7OHd4ZhsfiXX5y+DxZ4TvbkT4XvbIYPTEpO7q8sHBNhnNX+oynd26hzYoXzJxUZzTbR4vd4ahSm1v53PH7jLTM/10NycI2cXuNTNkX8PV77sMLwprWHA6Hw+FwOF4bnLPb4XA4HA6Hw/Ga0+12mEymS4LjcemerwQrbi9vV7Ls1C3MCwPlfswc4EsO6gxk4Q16NDWMIxAi49SgXA+xTpS2NaDNPJrc1pO2jmshTC60LvaNEkMrLF+g0BPE6bK7WxtoeFhndOG6Vp1WVeJkUbt871CjFEyGO3zjX/3L7O9bl9Db3vZ2vv3b34PMHWFSCgKvXPN8Jnj/6x/6Ef7JP/nH3Lp5k7e+9W38+f/lK8BbnkgNfFE7gZ5plpzyvge+Yh67PiNJbQx6EZX3LS4Y/QZtSTMUxOnyPa2bAA98mBaMUJ6CZrh6an9zY51er7fyc4fD4fhk5+a1q0yMhFw8NFURUQg4wkFb3ddID7K4FHlupEToxYNCGIPIUoy3eCnI/PKCLACxasVZARlP0cHysUUOzr2BuL3B4OrvkgUNhltX0F6IkQp/tEMw3LHu3ixBpjGTjTN2HEKQhh2Gm/cSREPUaAeMxkiPyeA8abM3f6jH3U102GLj+d+w/dIpUqdomaK9BmCQK1Z33Tud8GmHh3yg11+MvWa/k0SEnwQlJMYsWiuGms/eAET+p+I5NTAxGU3K4vu+jgmQTLD3WORifUjBiS4E3rxVixQCZURJxK+748VRCyBUPo9u3cNju4t0op4MeEu4wUWvixJiSSCvtlM8n8GgCuVv7vV7vLN5ll+aXJ/vdyMb81xywP3B4h4NZMg1hqXo+N0sYlMtasQLIWgJn2mhP4lOWettcjgtlgooE/oB/fU1du/eWVo0OaN76+nS7+lDn8H+cLS8oxCkzS5nzp6ld+rsynM6HA6Hw+FwvBY4sdvhcDgcDofD8Zoz6Pe4ffvu0vZXW+hetLvcsK0Lvuyinrm7pSxv8z3m9b9npBlIaVBSYIxhkguit/c0u0NNv22d49PYsHOYISVL54tTCDwreBfFYm3yePWCCD+cGJpBOX5bSkGnYePIi87tNI9kD1Uh5jM2xEPDerf+QieZIU4Lk88ChsMx7/3bX8etm1cBuHjpfr7p3f+AoFJ7USrQNaXYr1y5j+/+7n+cj8Fwe0+TTu0Ud+iX741Sy9cnKVyfRb8EnaYdT5QsrpGU9RHwvZZk+8BOnUtha58LIQg8e/8zncfZy3Ld7/nYhKDdsIsZgCPjywGmK2rROhwOhwN2t++yc/fOq9uosKHQJWmx9qWi4lLWy+JkFjSXthXxJgcMrj/GtHuK4dblI19epv3T7MhPI212yfI49sxvEKQx2vNJvbbttzHINCZtFgR0IcnSGGVGVhTXKTJOEUaTtBfpKKPNe1FpxNpLvzPfJnWG0RnmmBerTzs8KIvdNbW1X4nUbTBoQBTE3Iteh7b0eTreZ2LSedsGkFhn9mwxXl0s+tRkqIpzekq9uHzc66SofFdm357TqkVH+iRGk2hNR/o08zhzX3g0jeSB/ime2r9NXwZ8cfsewsKijKMizuv6We3rI+Ea75/cnNfbBng62SuJ3VIImsLj0CxeSusWJGQVCX8QNLm8cZaXtu9QVz3dGMPN4T4/+dHf5p3n7mPv1i10VlgsAqyPbtMYbQMCdfoe/De9k+dHGcSrotEFkXmNXu4dDofD4XA4jsCJ3Q6Hw+FwOByO1xStNVevXV/aftR87HFu5OOYxgYlaxzCClJYiqi2/VxMg8aJ4YVbKacGClXJr7YCuF6KQE9SuLOn5wJ2uyEJPcONXb3kJo5T8FV56lGb5VjQJIPdoWHQpiL+MhdtZ2KtMbbdmatdazMXa7XR9FqCIL8embaR5Wlm3eozsizhn7zvb/Hc048BsL5xmr/xrd/LOG3z/M2Uta6k25y1sXwNwS4I8HOXepQsotTHU8Mkgm7T0AgkQkAmIK5pZxwZmiGlay+EoBUKmoEhzuPWhRC16QCBJ9jsSQ6nZl5XfLa/UnnN8FwoTzJb81VW7rPvCbpNQ5SCd0xe63TqxG6Hw+FYxfadV1nonlEtCl2T3FGto+1FI7TykJkVX5Owg65xe8/3nw7p3XoKgMbhbdKgyXRwtGs16m7a8xZqHY+3ruCP9wjHeV1lIWgM7xJnMXFnc74tbfYQJiOYHCz6kEzIktai/jhwuHWF/rWPIAurzoROMKo+dntGs0bsr1L39lW91EoIpBGlWtgGSDF4Bk57LdaVva4PBn1+J9peulWycG9Wie7VBW11dcCPEucFszIvho7wCYTM3x0Ml/0ep73Woh1jmJiMcS7MJ2nKr77wUT719EUudTcwu4clofuVoHORf0YgFOsq5Fa2cF8nNdHj1Wj5lihP5xpj2FQNxjqdC+fhNOPZl17gzRcu8+Hrz5MVVhcaY4hMRoZhksT86vVn+aNvfCujgwOiKMLzPPpra3ieD5/1xRijEUKSpSnJRz505Bink9VOcofD4XA4HI7XCid2OxwOh8PhcDheU3Z395hMprWx4HVk2ljR1lsWIE9Cpg23dq2r+vSamgu8kNdu9MAzZYdwledvpYwjuL6dsdGTNAMxnxydxoaDiT2wVYm2FvkgPQm+EvhKcHFTsD/SHE7M3L1th1Wesi1GnBf7NYntOZuhjWfPdDmiuyj2TmKDEFbUL9YGn0SGSWRohdalXGxfSCCzE5//+/e/l9/94K/YsbU6/M1v+142Nk8DVoAeRxlXziqkEHYcqiyWz0hS8JQhScsXeCbItxt2rFHBGFSKkTdWHPeUoRGI8kS3ELlQTS5k10fR+55gY4WjfVbDW+cLFgxgtCnV5TZ5g9aNXtvMHKU+tslvh8Ph+EQlyzLiaHr8ji8XYyBLS4KyVh5gkLmga6SHwGB0BlIhkwg/GqKDJiQRWigma+ePPEdz+0Umg7NE7Q2MlKh4emwNFoGtBa41i/7ldbilTm3N7pxgckAadktCdtro4U8OSqKziselfYzyiVsDGsNyak7c6BBOV9cgv1Wpo1wXXW2w9atndbBnDmxjbA1q64q2ZVd8I4kqbuu28DlfKF/iC8WmanC7IOjWC9mi1oFcRWCjvUOhSIxmqhMCofDyJYMZhsTouQwvhKAtfFvju7D47fn0kAzDOa8939YSHpnWRAXB+bFbL/Flb3g7zx88d2zfXglxRdwuxpMDTHTKThYRikVce3UfIQRnvDYDGfKhaJuzfpu29JnGEbs7u3zBw5/GTz72AYzWaCA1ZW/4OIm4ur/D5Y3TtX0U+cIEIWV9nZ8Cqi4yx+FwOBwOh+M1xondDofD4XA4HI7XlN29/fmfjxMNjTEkuZBrHbUGpXhZLu+ZqKwzuHY3oxUK1ruy5PIWQqBkOQZ8RpoZdg7txGOcwo0djadsFHamy/N7xfrbM6QoO8p9T7DZV0ihGU6PnsTN9MzVXo77Nlix2cZvF+tQwmbfRnbPGEf2eG3g//yJH+bx3/01/h9/9l2cPX/ZOsor/wUwnmqEEPznH/0BfuFnfxwAz/P5K9/0D7lwz31LfRxODL2WdUgLYaemi9dFYOf2Z7HxVaaxXZCQViLQZ9rB7MeO20a9q8rtV9I6xuu+FrNtpetXE3VuzHIN96xGNC/2bRVra4PVHzocDscnMa8opaVuBVMFf7JPa/ca094WSbNvJVjpoZUPyRShM7TfmAvPcjqmMbyL9gK09BB+g6i1DuqIaTEhODz3SKkfadNfvX/1cKMxRpaOj1sDvOlhScj2okPiopAtFVr5qCwptbXcfvklZnvtPHfXzvPgC7+9sk8f6K+hWNSvtpHiYh5DPu8DkKAJjZq/5wghUJXHel097AMTkxqNV3Bud6RfErtn5xCV302hX7CIG5/97iG4x+syUIvrpY1hT0dzR7aHreUdm6xU51pjV7cVv5NX0yGbqlGKI28Kj8iUY7qf2r7Bye/8aqrf6JFO6EqffR3PXd9vCBaR9cYYnk0OSNBkRtPG45Lfoynrv7cN6fHmxibKGAIDCtDTKTeuXyPK0iOXEmyPDlaK3TOklPR6fQ7291bu0xusH9mGw+FwOBwOx2uBE7sdDofD4XA4HK8puiYys058tNvLcZSptqJtWDPDuKqNKC5P5Y0jQys0S5HmSrEkdgsgTs2SYSXNIEmXz5dkhqAiTAshaufnmw2xJHbXuZhmoquSy+fLtI3gnnHptGKzJxlPNeNoMZ+uDVy/9hL/9l/+AwC2Tl/g//0//3UbW67NPB48Tg3TBH7l5/8j/+Hf/LN5u1/59d/OQ2/89FqhefdQ022JucvHitoLd1ixz42gLnAU9oYm/6yMNQxVxpwt19WWUqDq3GiGpcUHaWbrdAeV79DM3X0S6hxoMxqNBpsbbmLX4XA46hBS0u0PODxCHKsiswSZTMmCJkYtvwCoaERr7zoCQ+PgNpnXIG105w9B7YWINKa1e5VgvAfGkIRtpt0tsmZv0dBJHgIfQ0kVAWA0piCkGuVbx3kpfnz5PUlU+mZkOUFERUOCw7s2nkUIDDA68zBpe8CN8R5n7zy/1OZPb2zxYrNl/c+mHJctat5IbAz88piqV01SFrsN1l1dnHCclXjx8jPp3CFuSscZqpJ+ikEWBOoUw7PpAZfpsZYL3lII1mRImmnivAUhBAGK1JRX1lVjxA2wnU05m7u7gZJIP++H1jQ9j7S6Uq+4T0Xgr6N0bmO4mY655PcYyAZPJDt8Xvsi/Xxc+1nEC+mQkY45Le22pvA5O53QHF5F5XXgJ+11pu31+Xe1Zex1XpwTooMD7ldtns5GKwVv76iFHwW2zpxlODws1fee0e316XS7J2rH4XA4HA6H49XEid0Oh8PhcDgcjteUZrPJZLKIMDXGMJ7amsxVYbJuAs5GTZeFxjgxpJltoypA1s1LH0403VZ5AlIKQeCZUiQ4QOiJ2oTGJIPAKx4PxgiSzEZ2zyZiZ+70oCKuN3z7My3EiyNAmPrYzqrjCazoLoV1k3sKNro20rLfVuyPs3mstzbwod96//y4wfrW/M+jKbQbVvCOYsOHf+uX+eH/73vnn//JP/f1fOrbv4gogX7Ljq96HfZHhlOD8vY6IVhJQa8lOBiXx2cd5st12bW2ixAKl8dOmhcE+hlS2v2rFL8rxti65bNFFIFXXZhQr3XUOblnNdU9T5FlGUop1tcGnD59ysWYOxwOxxFsnTnD6PAAXfeXdgWRpchkigBUPCENy7Wv0RnN3WtMu1skje78mNJf2kIgsPW5VWLfP1QaEY53OTz1AEmrP9/vtafuzaYqZFem5rRGKx+h0/lzUAuJTCK0F4AQrL30uyijMcagpeLOvZ9O3NkgBO6efxO/0+5ybvc6nTRh3w/4QLfP1cLKQSkEorLAsE7I1saUXkZmJV3qEPMfgdGaHRKi3H0+NSldUa4LYowhLsjksz5llbcijUGY8vP7pfSQvgzm7xFCCLoyYFsv3jeFEHhGUPUzV98p04prvm58HT+koTXDFWJ3ZgxPx/t0pM95r13/TlSIUU+N5vnkkIlO6QuPvufx2efu59b+NqNkQgOJJONe2WDd66MK7zXBdIcgGtrbksUE0YjGeJ+9rcv2e1/bQ+hKj1Mm5JaOaj+/t/CueBRho8Hl+x/k9s3rHO7b9CbP81jb2GTz9JkTteFwOBwOh8PxauPEbofD4XA4HA7Ha4vwSxOLUWIF02xiaDXAK1iHV5XoLgrNxhjivBb0ODIEnnU7z9pvhVbQLRIlsD/S9NtlwVspQUMassyKmUJAGFiBdn9UnuxMUhDC4KvFxCpYwTXW9jPbP+tEboZlMVcIweZAsjc0jCaFidxc8C5dMsCTCydUkTiPd++15HyxwEZP8uKdzO6fLw547EO/Pj/mkU95x/zPxsDh2IAwPPvkR/jn3/235u77L/zDf4ov+iN/GgN0W4J2UxIltt53kWlcP9FdR7clkVIznCxi40V+3SpGNStKF74rs9KQxXj3quhdRWuQuSs+SRdi9iQyTGP7/Zi5/KVYRJdXqRO8L144x/r6GlprpJS1k9kOh8PhKNNoNLl03wPcvnGN0XB1PWmMRsQTjPLQuRta6hQtClHgUjE8/UD5L+ia9BfthxycfoD+9cfwcsFbGEPnzrPs3vMW64h+HTDVZWs6Q6sAqSf555AGLYTOMPk4hdEk7TV0HOKN9zB+AyEVQqfIKGFw9Xfp3rX1owWGnXOPsHfmofkpmkJxNQz56OmL822Z0VCJ5q46skWt3G2fyzMBWuQu65mwDfZZ6hlReiY+me7TkwF+fp0DofClZGSyUi3twKiS4D2LSq8K1BqDKlzLFMO+jufuboBQLC88qxtT9dndqiw2CIRiTYbs5qKwQhBv75Ot+M5oY7iaDMnyPqlMlJzith/l+HRlYB2Pda+5WCy5s8cFPPLS47RqpmyFEMSdDfv53vXF2KcHNIfbJO2jk2Y2ZVArdl/ZOMOg2ak5op6w0eDivVfIsgytNZ7nuXcih8PhcDgcv6e8Pm/3DofD4XA4HI5PSnb3hjz13A2GUzN3ysSJ/ac2tv7zwaji9Kpx1GR6Fi9errNtDETJQvw2xk4rV2OvAXYONbd3M7RenvT0PEHgC3xPcGtHM42Xpqfzvtu+1H1mhVo7/x54tjb10rmAXkuw3rfR36vwPCv0Krl8LiEWbucZjUBwdn3RYJqmPPmR3wCg3elz/p4H0cagjXXEJxlcv3aV7/2udxFHVgR49DO+kD/xZ941b6Md2jOHvqDfFrQagk5TMOhIOg1h3V4npN2QnF5TtBvgK1s3vNWonxTNssV1K86bzmpsz75HM7d2XS+yzHA40kuivDE2en6GEGLlAgshmDvlZf4zmU7tRLxSblLX4XA4XgbNVov1zVNH7yQkutG2dbelzFc8SRv5XXzmnPTvX6mY9stOU6lTG23+anCC56AwGmYx5cYgjCHubhK3Bhggbq+B8hBGI3SWu7ltu1nQImkN0F5YaNHQ2rtROkdn93rpdyEEm16ztE3WvrnY6HAbH24WIjR2slDmn09MSmQyYpMRkRHl0eC2bIvAF4pQqNIZMmwd7cyUn7nNiiAthEBVpiZFLqaX+7lMWgk9r0/JKW8byIA1WRbI3xRs0JPBfOwbXoPLQY8LXhuJ4IrfQx2xOOJaOmRoFrE9u1m09I5koHQtJIZNFZQXRa64R3XE7XV0RaRvDrfn351VhEKy1V5E+Tc8nzefu5d3XHqQ0fCQg/09omh6RAtllFL4vu/eiRwOh8PhcPye45zdDofD4XA4HI7XjBev3QaswL2bGkJPLLmVtVnEVE9jQ1Zw5pb202BU/dxymtm63kkGqRZ0WzCeliPKAx96bbkUnV4+h+HFO6l1G/m2L1k+l6qkjSb3qkWsK3hyFvMJk9jW3p6J75m2E56zCPV5pHnBeCRgLoQLYWO96+b4D0aGODEEvt1w6ZQi9AXXtzOeeuJxJmPrnnvoTW9HI9GFlNfDg13+yXd+DcODXQAeeORRvvyr3o1BkmaGwC9HzAshCDx7jYUQdPI59Lo61pmexdQvX6vQFySpodUQtBuSwLP76sr4GoEVodPamHKA8jEm/0AI+x06GGumiY2Nb4blCeokARMU3eMCYczcFc9c5Bbz+zFjOBwRxzFBECx3zOFwOBxHkqbJ8TsJiZEC8ghvyP8e1mlt/e7jiJv9pW0yjWv2PBoZTxAYsqBlNxhN4+A2adghbax2xAqs4K21dWHPxMi00SX1G1Aak43rLmK8EJKC+Cgk0+4W7d2X5pv8eLR03llSSjKTsI11IOuZQxvI0Es1sud9zq/+bN9yrDhMTEqLhZvXRoZLkkKLBhtf3haLMSohkIbSeVcJ8cdRdXJHJiv1VQCbqsmhSRjpBIXg/mBAW/q8kBxyMx3zmY0z+FIxyCX3UHgEebunvBbrqnFsHe7zXgeVjudO8HNee6lMC1h3OgYUgDk+0v9IhCBtdEoLN1QWzyuhryIIQ7744TcwjiNSndEJGowOD3n2icdJksW/F+1ul3MXL+H7L//fOYfD4XA4HI7fC5zY7XA4HA6Hw+F4zdjdX8SVGgPTxJSExBlRbGgEC2HZlvU0KGVjq5VcCJBS1kVsQpKauWtcCutC1trQCARKiVIN7TqRFmBvpBdR28LWxfY95tHlJ6Hq2LYR3MtGNE8BlfrdtYW6qTexaQMv3km5/5w/7+/ZdcWZNcn/8e8XEeYPv+ntpePiaMr3//2v585NO1F+7sIVvuKvvg8/sE4nAyX3fPWcobeInjfYa6n1wjUd5WNKUrMkdjcCwXhqaOWucd8T9No2It4ucsjd7LMB1+S4z/arsjc2HI7Lk8dxCo2gfK8NMJoa2g1Kk/QnucVRFPH4E0/S7/e4eOG8q9XtcDgcL4MgbJxsRyFszHhBEBSAMfpViR/X3stcsGQMrb3rqHjMpH+WuLNBMNpF6oxgso8RgixsH9mEMHr58V4R72tTY1ZsNVjntxGCJGhxJ53weLzLdjYlEJKhTpiYchi4Kfic7cI7iTCmJjLcOo9ngrdAIDElgdoACZqAxXOwrg54bDTVKyMRcxf5Sane9VAoWwN81mdjHeheHs1ugLb0UUIyICQQknu9Hl3p4wvJ/X6fNwfrtNXiu9BTIVWOE7rBjvuc38YkhpFO6cvV3y+NQZn6u/pyqV7BTAVkQqCOSBwYrOcR6Pk732h4yEvPP7u03+jwkBefeZrLDz6EPCqKyOFwOBwOh+P3CU7sdjgcDofD4XC8ZlgxsRobvrxfnMKSnQk78VsUqYG58F3VQaPE5CL5Aimtu9ivCN1xbAiCZdG9erzdf7U4flKq9Z/TzKCNQEkbKz5vW8xiuo8+12we89auBpNwYcujEYi8bfjwb//afN+HC/W60zTlX/zjb+D5pz8MwGBti6//pu/l7NaAaWKFfimh4duFAlUXfJJCu0arsFHy5W11QrMQgn5HlkRwIQS+Z+tXlsdor01VMDfY+1S9HQ1fcFjzXUszu2ChyCox/6Ts7x+QZRn3Xbn8sTXkcDgcn0S0Ox3CsHGimGSTC6fljRz3eFxCpjFa+cjMrsTS0iNuDU7eQJbQ3r2GF48BaO7fQKVRqRv+9NA6vo94T/gY3iAwQqKVh8nF6bg5IPNCUF6+B8ibj/NCp0FS04eFQ96+kxUv66xGdlZ5fp7kUmfGvKKBVYXutvQQxjqzZ/3tCJ+JSedCvJfL3QYrll/2uvP3i9RkHOgYAQxUSGI02hhOqRZbqokSgolO2VAN2tKfu66LTvdXgy2vicymx74vvirnM2aeEzA7Wxq28dOIVPp4NV1od7qsb26Vtt29dXPlKaJoysH+HoO1o+uAOxwOh8PhcPx+wIndDofD4XA4HI7XjM31Hrfu7M1/9xR0moLRdFlYTtLlWttptiw0CyFoBDCJzVKked0EYpQYPLUQtpPUkBmYxjauWxUE3faqOtI6d2KvYFZHOjNg4vp2ioJ3kgvDnrS1vaUwc2e3NuDlse4n4fa+5s5BQisUCAE7eyOeeuJ3Adg6fZGNrXPzPv7ov/x7fOiD/w2ARrPN133j9zLYOIOnoO8vBtgIYLMn2RnWO6urBB5LYnfg2/vnqfL985SouacsucGmsZnf/+L9W0UjEKV+CGHvbZzaCW1fLaLZPbW8AOHlMhyOGI5GdNpHu/kcDofDseD8pXt54dmnydL0mD3rYk7Kv8p4ilEeJhd9VTxm45n/zv6FNxN1N+1f9FJyeOo+WjtX8eIRw63Lc3e4VIpGs8l4OKyeaXEOneFPD0td8KIxWdgq7SOyBPNyHeMnQUgyvzF/YBlg75634E/26d56Oo9Gh0+JE9qHmh/uHeMwRyzJuyd5FM6E8uOo7rGmQjzEXLRWCM54LbaziMhkKISNAUfwXHrAgY4JUUghaOExNikCgRKSQEhSY7jP73HGazFQIRLBgY65KDq2nfzeJibLx5pT8w43c6Jnr5LgHQiFv+RBXybstEkOD1de99JihFWNCMF0/QJps097+wWyoEna7OFlCcJowsEWnoAkivB8j/7aBoP19dK7lNaa0RHffYDh/r4Tux0Oh8PhcHxc4MRuh8PhcDgcDsdrxqULp7izfYDOle1WKFFS0Gkaoti6gY2xTm1fWbG4yjSPOC9O0EkpaIVWTI3ThehdNxWb6UUbsHD1GmPj04UwuQBL3kfBOKpEehrrxi5FbBdI89rexhimGYR+jSM5d4hrs3Cly6JLPd+mJGgt8th2ltr46Ec+wGO/8356gw0+5wu/jCBoAIaxLRXJk499kCyzIsJDhQjzn/7x/41f/rn/YM+hPL7qr72PC5ceAOyCgFm0OMCpNUXgCTakjQafC8jYuubV6VelBL5nFiK+spPI2swWMRhk4dotwlEXCLFwrGtjSPL7NKub7itbn3wWFlCTcM5mX7JzYOt1F9cKpJn92ehCmDvgo8TMa5BXmS1eOE5gPzw4dGK3w+FwvAwazSb3PfQwLzzzNNH0KIe3KblW87+VFx9rTfPgJkJnTAbn0J7P+vO/STjZZ/PpX+HOA59NGrQQxoCQjNcvYIQqidRh2KDROFrs1n6DTPmobFF3RJgV8SBG401tW2mj86pErq9alZU0+0z6Z2jt35hvu5JkXExSXqrEmVSf2tV3JVF8AK+gTg7uSh/NwqktgAaKmAwNBEgu+z0kgmvpkMhk82jxU6rJbjbllGoRCImH5LLX4+l4l/N+lwteByngVjphpBP6KkQKu1iuKT3Oem2a0o5zkMePF98sfKFsQkyl31leF71YxkTWONtfKZudPkyi0vdWJVOao228JEZ7Pv3ug9yRElMXJwR53XplV4XmdchXkTa7jDYvYYScf1eUzjh7aotWt3d0Z4+557b/r5bv3eFwOBwOh+O1xYndDofD4XA4HI7XjE67yae+8TIffeYak8l0HicuhaAZChpB2Z0dp2YpYjrTMImsWF2M1Z7FX2szcwCv9hzFKaTaENQ4e4yZCbiwc6gZtAWZXtSeXpzPCqVZtuxuVgIy7LykNradbkvQ8AUin5w1xorixfHOXOpFcX3mbp9Fis+GbIzhx37wH/LzP/Uj831/4Wd+jK//5u9nffPMfD78sd9dRJi/8S3vQEn4lV/4L/yXH/3++fY/95XfxsNvetv89ygBIQwNH5rhor556AvCviKKNdPYIAQkmXXH+5WMzGZg+zqNy650gx23XxDvZ/eqOIcvhK3JeTjRJGl97XMl7bVcMT2MkoK1rmR/qElrdopTaISCKNZz13jol79XmTZM8vvRab4OUaQOh8PxSYbn+Zy7eA/PPfXk6p2ExEgB2q6iMlItHhpZQnP/1jyavLl7lfb2CwS5A1saTf/6Y+xeerTUnvbKNbIn4xFBuFynebkv1iGc+Y28drhBZCkyjRBGY4SimV6ntX8dlca2i8pnvH6R8cY9J7omr4Sou1USuwEeiJfF7uMwNaKnh6g8a8uecB/JOc8u9rqRjknQSOw7T8PYfz4UDPBzwf+c12Y7i9hSDdaUvY5DnRAIRTePFjfG8EDQpyuDedT4Jb9HYjTPJPtMTYYQgqnJeDrZ5wG/T0MuxlonZNdFtGvKRm8phI1kP4ZWs8l4Mln5uRCCs90+25Pbi3rzOqMxvEtjuD3fL/7I+2m0N5isnSsdb2wjVrgG+yKkTal2fR1p2EYm05IoPtzbPlbslkrRbLWYjMcr92l3jhHMHQ6Hw+FwOH6f8CosM3U4HA6Hw+FwOFYz6Hd4x6MP8aaHLx25nxBWXK3O0Qps9HW1fvSMmYN6VSy1YFHnuy6CG+xcYpzOBGbBVl+x1Zc0QxvH3W4I2g2BkmJJhAV7TLF9bWB/ZLi9r4lTTZIxF19tHxeTqr4naIViLmyXIyYXjvEf/VfvKwndAHduvsQ//PavYOfuTbQ2GGN4/EO/lp9H8vCb3sbjv/t+fuifv2d+zP/9T30Nb//sL1mKSd8/HPOTP/HjfNd7/hb/7sd+tPSZ79nrr40V5u8eaKJkub7nJDLsDU3tda46sWcO99kke5wYrt1N+ehLKdfuLsfbztz1s2aqNdDjxDCaaA7HJr8fy1+G0dSQZbrkGh9HhvFUM4k0o6lmNF2473WdfbxAt9M58nOHw+Fw1NNstblw6TJKHVEjRAiM9DDSK7mkvXiClyxERwEgyu2Ew7tL9VJEjZO21WozC1eZ/Y2v4jHN3Wu07z5Pc+cqadDk4OzDDE8/wOHpBxhtXkYrhUojZJag0ilBdGgF+VkbWUL3zrO07zx7wivy8tFesBBGc04yyWcX4C2ebwJRit+WQEf6dKVfcoGL3DvdQHI56CFyQXxTNVAIOiLglGpy2mtxXrVoFu6JJySX/S4PBAPOeC1Oey3uC/qc99qogjgthGBkEnShf76wDvEiGYZb2bLwXH1q1785vvylalrA1vmztJrNlfsInbF962ZZnJaK6eAck96p0r7haBt/vLfcM6FKLzjV+1t/4uV9zDHvLzM2Tp1e+Znn+wzW1k7UjsPhcDgcDsfvNc7Z7XA4HA6Hw+F4XVhb63HjhpxHmsNM2DW5UL1wEweemc9RyxXR4TOUFCi5EFiLu9bGjte4d2ykeXkSPPQFQsglh7fd3yy16yuoBrIaY53QhXLYGGPIMpBy0YbvCXxP2Hrilbl4rQ0/9v97H7/w0/92uSPA3dvX+Iff/hX8lb/9Ayjlcf2lZwC4dN8j3L19jX/6D/4GOrPq7ud98Z/ki/7on8VXszhvw9NPPc0v/ux/4L//0k8wGdv41f/2Cz/NH/0f/xhh7niTUuApM3egaw139zW+B54Uc/f9bG41TszcHT4j03bMRRHaGDicGJ65npTGHSVWwK5GwU/ictz6rKlZJH4RX0FU2aYN7AwNzWC5b9VvhTGG8RQ6rfrvXqvZpNNxEeYOh8PxSukNBoSNBs989PHVO9WVDml04OBWaVvmh1DQPgUg0BgDXjTCCEnWGpSOkUoRJQlGFRzfaUIw3CYsCJEG0H6TqLtlf/d8JmsXMEKWHLtZ0EJkaSnyvL1zlfH6xfI5XiVEli65fp/z1NI7SvEKltJR8v2kyIVsI8kwdOSir02hGOVR2iL//4bwuJ2M2TcxBpAI1mXIaa+JVxBeJyajkdffBhiblBeTQy753Xlt7Vlt7pFZPLANEJuMhlhMWYZC0ZM+B3pxbfd0xCW6pfGXw+9PGNFe8/kz8T7rqsFaHpH+VLTL//k7v8DnX3yYNdFiVHVDG4N3xHmi7hbh4TayEIEfDrdJCt9JmxqglxZurOx34dwG0CpYLLjww9p31Sq9/oAz5y9y+8a10vt52Ghw4dJl5FGLURwOh8PhcDh+H+HEbofD4XA4HA7H64J1AHlAXN4+K8Jc2VY3v7Y3zGiGktAvT96FviBOa0RsKnUqhRXAq1Hpsx5W++ErSmK3MWbhaK5OJguBEGZpTnUaG/xCHHaa2bPYWO5FG8bYutZF0dcYw7/7wffxiz9TL3TPmAneX/CH/p/zbffe90a+971fRxTZ2f9Pfdvn8yf/3F+1sepZxC/9/M/yiz/zH/jo47+z1N4XfuEX4fvliflGINirlDVNUphky2PeH+ncrV6+T2kGQeW/QIri9YxuSxD4omrKs1HwNSJ4ULn/UkC3LZhGVkwv9TmBhl+9d8tz4UkKsTEIoWk1RNlxbySXL186dhLZ4XA4HEeTJPHxOy0h5k9rIxXCGIROScIO094ptPIRWUrn9rP0bn507gKfdjbYufQok7ULAOgsY/v2TSsu5rEtxvMZbV2Bu88Tjnbys0Fz/yZp0CILF4ucot5pwtGOrQueo/1Gpb63JhxuM+2feXlDXBVXU6C1/SLBaI+k1QMhuakkT/oSg0GZ5cV+xhgyzDyM3ACeAY1A5xK4j2RqUqJcRBf5j0TO2xuToc0iaUVjuKunjOOUR4K1uZBtgMjoksM7QbObRWx6C4e0EhJlRCluPEHTqIy3KTwOWFxbQ93iw+UxV9GAMIvFd7ry7ncrHbOjI3Z0xL2my8ikPJfYiPyff+kJ/swb3wm3KQnes+u0EiFJm12CwiIKlRxVs341hjzWHzF/gcmUX/q+3NnZZTSNuHTp0tHpCcD65iaDtTUOD/bJ0oyw2aDd6R55jMPhcDgcDsfvN5zY7XA4HA6Hw+F4XXjsqWtcuz1hoydpVJy1JxENp7HmYGwYTjLWu5JmuBAgZ1Hf1Xa0BlEQlL3c6e0L66DWBTd4qwmjqHxOIQShv6jfnRRE8tkk62yOVJt6IT1JYRzpuZu4mCypbSOl/aVYxHufROiecff2NX783y7qcv/OB36Rg33rOLvvobfw57/2O7h1/Xl++ef+I+//pZ9gPDosHR+GDf7AF3wRX/pH/gRv+pRPoTptO1uAUK2FLSVkhTFrbR3ed/Y0m32JKgjTxizfJykFWwPJzZ18Yl3A2XWFkrY+qC64rsXy5QLA9+xPkhvDwsDGmLcadvskMqTaXttmaL1p1YTP4lIHGwlv/zyODJPYOtWFIHffZ0ymCd2O+88ph8Ph+FhQ6mR/jxpmkc4CmUUkjS5Z2LIR50DUGiCERBSdzjqjuX9zLnY3htuc/cjPcvORL5jX0raVRTKMESWxcDw4RzDaKT0Jw9EO44LYbaQiDTv408XzVMtlYVFUay7XCdlZCoVrER7eRmYpk8HZ2phqb3pI7+aTqCxG6JRn+lv8aLeBKQi40szi2WfitinFtQPElS0ZWWmHRcS7xjMLwVsKgWckaaGy99ik3MkmnPEW10hj0Kac6nKgYzYpx4FLymJ3nUc6rbwAtIRXep8wxvBSOmTLa9LO3enVet2Lcc6i3Be1yY0xXEtH3MgWIvazyQG7uvxy+Js3n+MB3SptO8nSt1kkuRESIyRaCNAZwWQfFU8wQhK118ka5RIpOv9ez84hALReuLhXvEOPx2Nu3LjBhQsXju2bVIr+2voJRuFwOBwOh8Px+xM3O+NwOBwOh8PheM2J4oSr161DavtAE/rQbco8SnvhvDlK9B7mDl1t4O6BRkkIPIHBECfQbgpUzeG6EJ89a14IgacAZQXQfCvthq3ZXCTwBFJYwbuuhvNskzELZ091r2kM2hgaFUd6db7bk/ZnGht+7GUI3TOi6WQ+vt1tG/F66uxF3vHZf4jvec9f5umPLru477n3fv7oH/sTfOEXfSntTg9j7OKB7QNNMxTzOPJJbIji5Ql6KcCIxXWY/XOaGK7ezWiFglODxeR/1W0PVtzOtBXIu00xF8jlrEZ67noHlmqNz8bbadrrHMWm5B6fRcTb/fI+arMUTz8LGMi0qXWUV2uUHw4ndDura3c6HA6Hox5bziNDSkmz1cL3g5UO74WD25v/Ja6DJpO1C6h4hNTZfBvGoNJ4IS5Lxfa9n86Zx39+LngLDBvPf2AudtttgNG2XvLsfF5ghexoEWlS58St1lReEraBuFGuNz1rJ/MbIAQiS/CjEVr5pEELmUxp7N9CmgyZTBmduq948fDHe2w9/X5UMkHqFJlM+Uivy1R1aWAXAmpjSIwuidEfCwYrXKtiRHjNftvZtCR2gxWWZWHvqpO6Dru4rZx+05M+I5MwzaPAt1T5GXw3m7KnY/bjmCt+j5b0jzyTno8sP6cQ+NUa6ELgURb1b48PeLhddj7rvCVbF95AzaIHLSSHW/eRNHv5fU8JD2/TPLg1vzqN0TZRa43RxiX7fRcChMIYgdCLlYUCs/SdrWN/f58zZ87geW761+FwOBwOxyc27m3H4XA4HA6Hw/Gas7M7QhccOVFivTRhYGtLppmdz/OOmLNLsvKUZaatKCxyt27oSzK9HKltsO2u0tFngrMQsNGTKKk5nCza0cY6lW3t8OXjZxHYmZ6J6HZ/rQFhxeAgF1zr4jSL5xfC7vMf/vVqoVsqxZ/5i9/Mz//Uj/DS80+uGJM9TxA0ONzf5Yf/xXeWPveDkM/47C/i87/oy3jg4TfTCARhszw4bWA0Neyleu6cn8YQBssx4kqByQxRPE+CnTOODJm2x0hJyd21uIaCi1sep9cM46hmYj5fqGC/I/YaLTmzcyd3uyGW6p5XUUrQEIYkXcTGa23d/nasRx8P4B31ZXU4HA7HEsYYtu/cZufuHdIksc9MzyNJkpXHzJ8YOi0J3ghBFrQR08NFqLkQZMrHSwtOXKkYbVyif/OJ+aZgsk8w3CHuFJysdc/nivC55No2BhWXazd70Rgx6ytYp27YnrcvdIaKJ3ZxnM7I/AZeZNuQWUI4vEu4d4MsbBMFTYTO8MZ7+NHQRmAbjVY+YPDj0fy8f/LaM9wzHfFfzl22bQlBKBTSCGJTW7vlZWPF7gVCCIShJCjXOamrT/1iLW6A1GieiPc477Vo5NdtpBNGJGyoBr5QCCHoq5CO9Hkq2acvg3k9bWMM19MRe9oumDDA9XTElaD/ssfYlsu11av9D5VPv9dnMpnkdcwNMpnQ2ruFHx0igMwLiDobJO3FdywanC19p4zymA7Oob2Qzs6Li/bHu2R+yLR/ttAJiUEXAvyx9drNipfT2S7GEEWRE7sdDofD4XB8wuPedhwOh8PhcDgcrz0183DTxLpoYRZvDYkxKLkQfosoIUgqk6gzl/DMIa6kFUKNsSKzkIvo8lUY8n3zfda6in7bupIncVk895UgzeoF6/lQhXWYe3LRr+JnRpuleclZf40x/PD/9vf5uZ9aLXT/z1/7nbztMz6fN3/65/Dd7/mqlYI3QBxPSyXSz1+8wud/0ZfxB77wD9NsLSaBo8Q6l9uN5RraKq8jnmRWAJ9EEPoG31uI81FsnffaQKe5fL0Px5q1rqLGlF0i8ARKSuJ0+TNj7DWFxTU2ec3QebSnmDm4lxc9zNqYifFSCsLAOsGrbv7j8D3FxrqrZ+lwOBwvh2svPs/B3t78d2PMkUJ3ERvdnGGKsedCoD0flRYedFJiECVRMGkui54yO+a8xiArTu6kNSj97k8OSvW5ZRrjxWNbgsNA1Nlg/+zDi+5mCf7kEC8eodIYIxRx2MLLEmQaAwYjPSbrF0naa4W+aFQazV3jKksYb1wk80Pae9fn1+czt2+y54f8t1PnF30UktToE7mpXw3CitNYITijWuzqaC6Ez0TqGU/H+9zKxuxkU94UrCHFItL8bjbltGrNF8opIXnAH6AK7xn2naC8MGFiMmKTERzjfK6S5XHhPRkQCEVqMg6zcurAm3qn2bl7Fy8/p4rGdG8/U6rdrtKY1t4NojQu1WsXJr8ThX7FnQ3Swzvz9AGAxuFdpr0zJSHbCFE6R12SUB1KKUbDQw4PDsAY2t0unW7vRCWEHA6Hw+FwOD5ecGK3w+FwOBwOh+M1Z2Otg5RiKQZ8b6jptQouF2NrXtc5sdtNwTRZntaruoVF7gIOKm+62hiyjHmkdZFqtLaUgmYoGEeF+pHG1m7WhpJoO3Mc17WptUEWdo4TQ5QamsGyIKy14d/8q/cdKXR/+Vd/J5/3eV9gFwl0B7zrm7/vWMHb83zeMXdxv4XQF0gpSNLlSdI4NUtit40SN6Va5FYchyjWSw7rNLN1sovsjwzdlsH3luuOLlFT1xus0F69zkKI2hhVKaBmTUIt1b7ado92d99/5SyqamF3OBwOx0pGw8OS0P3KMEv1P2pjnCsqoNBlYVtLRdwe1LSt5/WxVTIhaa9hpof48Zg0aBEXxG5vOqS1e3X+u4wnBOM9W4tZSjCG/dMP5lHlct6tYLxDY7g9Py48hCxskwWtvK8pjbxWeDwTvIUk6p1GpgnheGd+bNQ7RTjawSuI8p919wa/snXO1oOe9VXIV8XdvfTENaAqEd8AV9MhZ1QLT0jOeW02vCZdE/Bicsi6aszd09oYPhRtz2tkJ2ieSw+56C9qVmsME5PSFgvHtap56WqK5Yd5NqsvUyA1mqvpkLFOaQjFRb+DX/gOhcLjYX8NUzhuS7V4PjngRjbmYntAeBiV0opau9dKInSRYLhN1F7HeMF8mzAaU3Fkx+01vL2F2C11isxitFdcGPDyxekwDLl59SXGo0Uc/87dOzQaTS5euQ/fX3ayOxwOh8PhcHw84mZoHA6Hw+FwOByvOYHvcen85tL2aQxJuroOdpFWKGgENUL1ClGy2sZwYjgcm/rz1cReD9qyJK5Gsf1JkpNHXafZIlLcGMM0sY7jOLHnnDnaM234kf/9aKH7z37Vd/IZ7/x862CSgtCHwWDAX/3b38fFex9c2Yf+2iZ//E99JQ888qlIIebie51WGyf118dXK8ZbuR1SQOjXLybYHx1fN9QYw+5wFiN/tIP+KIQQteOrQ+bXcrkN+0+/EFfe6zR58xvu5fyZjZM17nA4HA4A9nd3P+Y2TiT1GbP0UJ/0zzIenJv/fnjq/oqIaNuWOgNt62T7430QgrTZY9LdYrh5eS5aYwzh/g0m/TPsn32Y/bOPcHj6fqa9U2RBE+2FaL/B2rUP0Ti8M18VZ7yAg7OPMCk6fQEvGiGTqNSfYLSDqLjPo+7W8iK1Qkw2QD+NWY/KjvSTXLfqPgIIK1OGPrK0RQjrHA/zcPO28PBzYf12NuZev8uWZ+tqB0Jx2e+xrhrz46UQS47zfR2XhGTgREK9xiCBNRlyWjVZlyGhUCgEXv6TGs2vT27xwekdnoh3+e3oLj85fIEXk8N5Ow2paEsPv3BFpBBcCfq8beMiX7B1X+n9RKYRXiXKvojAxuZXt1WpLtowNdu8Qv14AJHG+JN9u0ij7txC4ElRErpnTKcTrr7w3Mp+OxwOh8PhcHy84cRuh8PhcDgcDsfrwsP3n+XyPVslpzNQW19Za5bETiEEW33JoCPntb2VtDWa68iyhTiaZmbuZD4YGw7GmtFUM5xo7u5rrt1Zzs32PcH5jUX09qTg8k5TK1inmf2Z1fReGoeBJLXupaIzWhv7k2nbtx/9l+/jF366XuhWSvEV7/ou3vFZnz8XkoUQSCHwlGBtbY2/9e7vp9Xq1B6/fecG7/2Wr+DOrRulKeVqpPgs/n1vqGsF7zr3erVsdath++TXOPOncb2AXSRKIE7tvdsfGaaRPUaKo+uu1yGFQEk7TilmCQD1gnmrUS94d1oBn/2ON/C5n/lGPvcz38jbH32QU5svvwaow+FwfLKTZR+7s9jA0l/iXjwpidsqmdoo8cw+1zMvYDI4x7U3fymHW1cYr51n+/LbV55D5jWy07BN1F4naq8TtzfKD3khGJ26n7izgVE+Rnkk7XX2Lr6ZaWej1FbvxhMEo93SsYdbV9Cy7ESu1v4WgD8ti5TaD+e1wOfb1LKjOa084KuCssAK10U2VIOBDOZCbEt4tJVPN3dh+0ikEAgEMm9D5ntLIegIj2ahb1OTkVZE2GrUOCxHmhuW634LbMmUqU4Z64TIZEvvEy2heEO4zqWgy1m/zT1Bl0Dkfc5/mtLjc1rnOO+158dlGH5zepvtbLFAQOT1zquckk3iaXlRgtDHf6+r+9SuHaxEpadhG1OImRFpzMXf/i+cfvz/st9tY/AnBwSTfRoHt5f+vVBKceHCBaYHe6hojIrGUOnHZDRiMl4t1DscDofD4XB8POFizB0Oh8PhcDgcrwtCCB65/xz3XzrF40+9xO7eAZ5a1KquxlYnKXiqHAMuhKDXEqXoc7CCcbXOs8HWmVbStlVte5QaosTGh9/YyTBCcO/p8utxpyk5v2F45mZGWiPKz9JU5SzK3Cw7ynXu3jZL2+yWf/eD7+MXf2a10P3Vf/27+AOf9z8Q+oLDiZ4vDpBysVCg0xvw3f/8x/m73/JVPP/sR5fauXPrGt/1t7+Cv/UdP8DFC9bdJvK64tVxaQM7h5rAW0S+RwlL8e1ga6T7nl1IUIyOF0LkbvDFqL283nldjPyMaVyMjYdJbAh8UesWPwmzSPsZmTbz+1DcLoSg1bC1vmeLEmwKbYoxmqAu69zhcDgcJ6bRbHK4v/cxtSEATGZ1PSGRSYRKI1s2BB+pU7xoZIXYNCIK23m9bvsQvvnQ5yGzBD8aIVMrWmovtMKimj/ASNvr5ah0WReVXvNcEpLhqfsJR7vz+toCaO28uIgkB5CKae8UrbzeNtjY6mpEu9DLC/GqoqZMyyLp1WabvaBR2N0sic6hUHhCooxgajJ6MsATcl6DOkXPa137QtIRHkWZVCwHmlPnLb6TTTjltWo+WZAZg0RwWjUJhMojyz0GKiQUHmD7v6cj0tkT3FjnTjevqw0QSs9+D4yZl7apq0ktheDTG6e4Pnxu/j5ggKfjPTaaBce9EHhGLM4JHIyGDAbllKLMCzFCzu937Rj9RmVLpf6NMda1rzxau9dACKa900ij7fux0Zx57OdQaUR79yqbz7yfg7MPI3RG6jcRGNT0gMZol/bd5/GSCWnQZnrrHA2j5tfBAGnQJmn15+efjEc0W0ffI4fD4XA4HI6PB9ysjcPhcDgcDofjdcX3Pc5s9RkNF7GR2oBkWfDe3Npia2PAR598+sg2PWWV5mod6llzdS4aX1kR93BiBc5nrqccjDQXthTdpiTVsHOQcXtP17rPwZrJlFrU7fa83LWt7QS3yB3FQghMpRdxYvjPP/IPjhC6Pf7GN/89Pvtzv6AwzoXAbePMjTW0Cej31/jm93w/7/nmr6wXvG9f4zu/5Sv4lvf+AGfOWMFbSvBF7jCvjDFObQ3vmWCsVlxLTwkCz2AQS/ev+HuvJYgSKygrWT8JXXefJpGhXZ0nfgUYs7gDs/h4kwsg1mEPIEpuda0Nk0lEt+v+s8nhcDg+FtbWN7h76+axCR/HIQB0hkgn+NMhMp0idWad0sYQt9ZycdH+RS9MhijW78Ygs9hGlgMyHqPiCVGnUFf55cSIVDDKI+ps2PjynGC0t7SfVuU4kbqrolVQ+l0mE5DKxp+AFUlbawgDjYObGODnTt8zL1lujLEu6EIbjVzoBlvLeyAUjYIjOxRq7tie4QlJdoSYu6r/qiZMcieb8mxywG42RQpBQ3h8ZuM03cpYvfk7hUAJyaZQbGdTklxW18CBjlmTYckxnmEQpv4dY0ZTepz12lxPR/Ntd7Pp0n6iUvxdSkmv1+Pg4GCxj84QOiUc74HRGOmR+g10LnBrqUiavdJ1Ki2eMMa2ASStNUZCYpRPGrSYBZ6vP/NrCKPZufBmtOcj4ylGSKLe5uK7qjO8eEw42rbR+PEYhneQ7XVGG/eCsKPx4xEISPL68/KkNV8cDofD4XA4fp/j3mocDofD4XA4HK873U6ramoh09Z5q7Wh0Qh50xse4OL5MzQaDZqN49VOTwkagRWxpbSObiuqQp0xVwgbXT2aLiZw7+xrfuvphA8+HfOR5xNu7CyE7mpkd7HvxbHMIrc9T6DUQgCWwvbHHmP4jz90tND9176pLHQbY6imwAphzzEToru9Ad/8nu/n3isP1bZ75/Y1vv0bvoLbt64X2mDusF+FkjPRfrHf7M++At+TBJ5YWVM79Jk79KexYRwZsmx557DmPsVp2fF9HKuElLrNWWYXPKRHpJCqVTfe4XA4HCfG830uXLp8pAhZwhiaezfo3HkWf1yu9y0AlSU092/Q2r9J4/AOrf0bBNMDtOdjPB/jBRg/XHIgG+UTtTcwBYFUYAjGe/UPileA9srCbV2RZpWWxdW00SENFw5bIwRJo1CexBj86ZC00SUN2guRVEiizgY7g3P80L0P82RvbX7K2GRLkeBVIbsqYQshlvZZdccE0JcB6yqkKRSbqsFnNM7wpe17+eL2PdwXLJf9UEiGOiZGMzUZezriv09vMtSVGG/KpU+kEPQrgrgBJjX1vE9yF6sx5apmlNX49wjNoUloNm0dcplGbD7/GzRGOwij87rvKUE0xIuGaKEYb9wzr/XuBwEbm6cgS5HxBBVPEFmCKJwnafZJgg5Gehhlf+4+8FncufIOklafLGiRdNbxp4fleHypODz9AAdnyu9/4WgHf7JX2uZFI7tgRAg6PVeaxeFwOBwOxycGTux2OBwOh8PhcLyuZFnGc8+/QFATTW0MNBohjzx8H2EYkKYpxhj8IKhpaRkr/hZixXOiBJIacTVYEaldJ36uFIRXzKoWJ2lnfw4D28av/eJ/4pd/drXQ/bV/87v4tLd9XqmNOLWucV9agbnct0XHjhO8796+xt9/z19nEmXofHFBnNqfVeMoCtwiF+0DT+B7ohQzn1Uz3Gv6Z9uEtGbfwK+/xruHRzvKZqSZYTg5vjb4DHXMfw21W01azVfBVu5wOBwOuv0+9z/yRnz/6Ge6P9rh0q/9G+75zX/P+d/9Sa68/4e48MH/hFeoYZ2FbYan7ycrCKBePKZ366l5ve6VSEkatsubdIas1E1+pcikXNc5bg3KfTKG0dpFJr3T9lcEo41LTAbniNprGGyMNTMHsM4Ih9uoPLJc+w0MElF41qXtNZ7pFKLSYe7gLlIVcKupMzMUgnNem3u8Lh3pEwjJumpwxmtxymtySjV5JFjj3qDHRb/Lg+Ea570Op7wmLenRlQF+zfn7KuAdjTMlcTlG85Fop6avZQKh8CqidFIjdp+EoU5Kv5/z2kv7NIWa1zbPjOFWdMgvPfsRhg3J2toa3TvP2prxBTLlE7XW0F7AaHCGLFgsYEjjmPHdGzRGO4STA4LJAeF4D5kU6oUDEg1FJ71UxN1N4tyNPcOfHiAr5x9uXUFXYvfDw7ul3wWg0ojNU6fxPJdc43A4HA6H4xMDJ3Y7HA6Hw+FwOF5Xdnf3SJIEJQXN0AqmMxd24AuaDY+rL13jQx9+jI889gQf+sgTbO/srxRSq0hRriWZacPOgSZOIEnLQmimTa24GiUGXRFMhRCEgXWJF4X0WU3uOqqiqxSCZgi/9DM/XLv/TOh+22d8PtrYCO9ZGzMxWmMjwdc6tn75oC3otUVpHMcJ3i88+zgf+t0PMpzCcGrPM5qa2gUBq6iOLU5zx3bNfaq7Pmm6vCBAazumqghtsJHixzGJDJm20fTVe11bXlUsn6v42b33nD32nA6Hw+E4OZ7nkSRHi8pJe50bn/LFpH5zvq29e5WLH/yPiGwhUmovZLxxsXSszBLCYVncqyPzw6VtQr8y4bTKcOsy0+4WYB3a0+5pVDy29bVzRzbKY7R1mdHgHAdnHyJtdAGI2+sM1y8ui/FpWUDPgmbp99DA+bQs8i9X1s7bAtZlyKZq0Kg4nI0xXPF7/JHOZT67eY7PaFqn9h9sX5zX9g6EIpCKkUlL70ojk/JMcnDsgrOm9DjvdUrb7uop40qN8johXi0J6MevQryZjtjLFtfPGMPbG6e5mPchFJL7g8FSK0IIGlJhjOFONiazSwz4yM0XaA96tA5uzffVUrF/9mHu3vcZ7F18M7v3fBq6EF8+69XUSLS3+O4JY/Cj8dICCWn00stT3FpbuiJ+NCz9bpRP3F4vt1WziGOwvsHWGfeO43A4HA6H4xMHt4TP4XA4HA6Hw/G6cnC4qNUthMgjxheTlZPJhMnEOlWMMSSxnfzUGow2CAnqqMxtrAs7yeesR9OyOzpOYTjJmMRW4K2bkzUGRhNDMyy7kmf99ZRhWpg7zPTqmHOtTUloFUJgVtS+VMqj3e7Of08yGB1otIZmKOZ9SzLrrJ4JtaNp1asFfhDSbC07leb9KmSip5mt2X0wNrRDGzs+i5o1xo5BVq55pkFJk49n4QwfTg2BZ/L+2WOixNBqVNzd+fbZuRZx8YJB245RG1srvBEKuzDhiPueaTNvQ2t73z0FnaY9RgjBcuV08D2ByAxCKJLc0j/odbh44TS97urr53A4HI6XjxBi/tw4iri9zu0HP4dzH/mZ+bZgsk/v5kfZP/+m+bak0SNTAaog6PmTA6b9My+7b6biiFXRCKO8kjh5ona8gMPTD2CEtP0LW9axm0wxGERBsJ1s3LPcgFeu541UaOWjCkJ/ta+wkHhnrukMjUIQCInKw7LXZYOHwjXC/HhjDLs64oXkEI3hgtfh0capUrtCCDZVk08NFR+Ibs+3ZxjGJqUjFv2NTMaejllTR1+zLdXgxfSwtC0yKa1jpikTnZX07bDGPZ7ZgSGFYKpTPhTtEJuMTw03Oee1STGEUvHWxikakeKS36MlvVKt8xRDkr+rSWy0ewM1fzd6/+O/xdtzt74B9s6/aV4He05N3xCCNGwhswRReBf04gmxF5RW5gmjMYXFCEZ5aL+BKjrBa1IMTDWqXlVj9SWbF68s983hcDgcDofj4xjn7HY4HA6Hw+FwfNxgHb7H7yeEwFfWLV6tcw1W3LVx13nkeU0b2thY7DpHsZ2sL/TL2PMU5+6tSLz4KfK5X/hltf2O4yl/79u/lg//zm8Qp4b9kWb7QLM71CXH9Hi6cFDPRF4hFnW1x+Mx7/3Wr+HxD3+w9jxnzl/myoOPzsWGoqN7FBl2h9YZnWnIzGLhQJVMgzYLkXk+jhSmyaLNta6sXQyQZtaNrXV50YEQgsATdBqCdlOSpIb9kSFOVosjdd8Le08KNT9l/b1e63d466c9wtsefQPv+PQ38sZHrjih2+FwOF4jTlon+PDUfaR+uZRE5+7z5Z2EWK6RfZKqzUaX6nYbQE1HiDQXlHVGa/cq3ZtP4U0OTtTfar+GW1dIm4sFbAKQdS8lJ8QAmReQeSEYjUymhMO7NPZv4h/eoR9NaKFoSI9GHiU+UCGBUCgh8YTkwMQ8Fe/NHdlCCNZVg/uDPm9aP8+bm1srz99XAeuyLGJHJltauHCoj4+Dr94hATTFstBdbHs/i7iaDpnmDnCJoFFzDFghfjed8v7JTSY6JTaa35reYaJTIp1xmMUMdcL9wYC+DPAQeELiC4kUgtRoMgwZBiNgSzUJCsLzRAhiZc8dtwbLQvdRCLGULCCMXk4WqFkQUt1SXfQgspRwVI6Ej7qbpd+75y6hTlgeyOFwOBwOh+PjBSd2OxwOh8PhcDheV7rdzvE7HcNJIq1tRLWoFVm7TStWi/m+9s8CWw878KDdWNT0rnOgzepmz0RvK47beO4sy53o+WHVw7/gD/2/ePs7v6S233E05X3f8XX82q/9BuNoceC08GdtrAt7HOmlWttRNOG73v21PPGReqG719/gL37930N5nu1vZpaEYoN1es9ItY0pr14HgxW86+pvp7nQ3AwEnaYk9K2AXVwkoCSEgVjp2M60bWOcu/MPxpqDUUZSU19c1vyXjQHiQllOW9PdOuKlsD9KQpYmVmD3PbxVFn2Hw+FwvCpsnjo9d8geiVTzeO85NckoMivXX04avaV9qhgvZNrbIlO+dfNKhTQaf7KPjMZ07j6PSmMEhvbOS/BKIs6lrJHd699fDNaRa3IHdvlDTRK0mfTPEnW3iLqbjDcuEXW3UPEYlcUEyYQvu/EC/+ON5+e1vIVYCLhF9nTEtbQcf92VAZ976j7CY6YJN1VjadtxaxDr3qEUgrAgHp9STRqyLFwbIMWWlYl0xrPJASmGO9mERhhyvrOGPOJ7lKC5k03Z1lP2dMQdPeVnxi9xIxuRoEnQTEzKjp6SFEbhCUlX+qW64kIIujJYbBGCGz0rIkedjWOuQM01qXHmH3+QXvr6BMMdGvu35i+anbvPIQtx8FF7g6Q5yPss6Z6/l/X7Hnn553Y4HA6Hw+H4fY4Tux0Oh8PhcDgcryvra2v4/sdWTWcmgp6EbnP5lVcpwVavLLwKYX9CH0JflCZQW+HyZKpSYqXAurxv2VGslMeX/+VvWy14x1P+xT96F08//pt2fwmIao1rmMaU4tSn0wl/929/zUqhu9tf5+u++fs5e/5yqZ06oqQsbicZjGPrAjeVca5KF58mphQjHviCVmh/2g1BM5TzqPO6NoyBODEUtXQbQ18jdoj6NibxsjtfCCuwS2njdOMkYTQa1w/C4XA4HK8qzVaLe67cj/KOeRcwBhWX/26O2utl4dkYRusXrdsZWzu56mRdiZDE7TW09OaR0wIIR9t4hfMKownG+ydrc/kk9pkphP1B4I936V1/jLUXf4vujcfxJocY6WFU/iO9kuscIdGNdmlVl1Eeh2ceZO/Cm0tne/hwjzfvlWuWy5rq3TfT5WfeneHLH6NgeWKxL8uu4X0d81x8QFS4b+e8Nl/QvEBP+rSExxuD1YJxZDI+FN2lLTwu+z3u9Xt4StXU7y6zphp8SfueUn92dcR/n9xipAuR8MB+FpfeeYQQNCuCtBRlgf7FtXPsNbv1ceXHUVllaISoEcBN6bsujCEanLH/DgAijVE6oXF4m+b+TfoerGVDRLuPOnMvzc/946z90f+FzTc8ytYbHuXiZ/4PbDzwJkTdy6vD4XA4HA7HxznCnHSW0OFwOBwOh8PheJWYTiNefPElJtNF3UGlZB79XZ4A1Ho5JhvsnO9xtbtnbB9k7I8qrmRjePH2slMr8Gwd5xlrXclaR3Bn35Tqf4N1Rac1Zi/BwvE9E9Dt/mWROMtS/sX3fiu/+f6fru13EDT481//3Xzqo2/FU4LAs0K8zs09Incmw0LoXhVd3u2v89Xf8E85fe7yXBg2WJf4KqN8I4DQL0+KCgHNoFJ/2+QieE07D5zzaDWOn1g1xpCmy4sFsswwipYbHnRkqZ76JNJEydJuADQDCIPVfTB5FHu71eTSPRdoNpedaw6Hw+F4dUmThCcf+/DqHYyhc+dZTj35S/jRiEz5bF95O1nQYrh5b6mWtsgSOrefZbx+kSxsvax+eJMDVFpYOWYMjYObJYF42tlkOjj7stq1NU5SUN78pUBkCZ07z9Lau17a9XDzMsPTD5SP1xmyxslePofm3Id/ulTH+VbY5Acvl927ic7IKk/YdzbPlhz2958+jzmcEMerY8hfSg55OjlA522dVS0ueB1eSockaJpC8cbAirEp1pH9fO7I9hDcH/RLgnFkMjSGQChkfsU1Zi7Qz+q7Z5jl6PMT1H4HOMhi/vPoudK2C16HN4dlgb0vg5K73NYzL1+LiU4ZmcXLhjCaRxKDbnSRaVwbqy+yBJEl6KDwvdQZXjyZf+/SoEkWNGv7r2cLMYyefyebO1cJx7uFkwhOf8EfRzVe3nff4XA4HA6H4xMFt5zP4XA4HA6Hw/G602iEPPjg/dx/3xXOnjvLxQvneeThhwhraghaB+7Hdr6NnmKrLwl8O3mpteFwUj9BGqeLmHQhoN+27t9TA8nZdUkzyOtxzw+vDymdzb96albjO3cTi4UL2fc8vvyr3s2nfcYX1/el4vBONVb09sU8FlwKcWKh+0zu6NbGtpXp1c5ugCRd3mYMpfrhxtgftaL2eXREne0iQgg8b9mdrRTUpZSOpno+ya21IU7L+2ltyDJDlBj2Rkf3YXYNRuMJTz79LHG8QjV3OBwOx6uG5/ucOXdh9Q5CMDx1Hy99+h8nag3Yu/gWjPKRWUJr56XSrkb5HJ558GUL3VATKZ0/TAyCzAvJVIBRHv5ol971xxm8+Dt0bj2NiidHNywEeH7p4WT7+RDjtfOlXbt3nyMY3q0cXxeDXj2HZNI7U9q0FkfHHYWPXIqS35uOlxYcVrnod3l74xQBkpbwuD/o01OB/af0eTAY2BInGFKd8XS8z91syrV0yIvpIc8k+6RGk2JIMSghbU1x7PuMzKPXZf7eBIs4do/qQruTvV/0VMBZVf5e3ExHS/ullYUFxesj8x+NIURySgScEyGnVANpNN2bT9K9/TTdW0/RufV0qc57585zbD776zR3ry0al4q00SH1QlK/sVLoBityy4LQDSzXCDeG6e2rK9twOBwOh8Ph+ETnY8uPdDgcDofD4XA4XiF7+0NeuHqL/QM74dht+0jqa2IqKZBi4RyezT8aY1bW/ax+1m1Jui3Jrz8RzYXuVcbwSQyBZyO4i+7xRiAYdCSjyAqtSWYwGoRY7ocGRGUe1u5SmPQ20Ah9vvyr3g3Ab/33ZYd3HE/5nvd+HV/3Dd/Dw296K0lq5s5zY6yj+71HCN29/gZf843fz6lzl2s/n/WoqN3P/pzkwn+1pnacQsMvj1kIWx/dXnd7bT0liOKTB0nNBO/iBHaqBZMoo1FxZicpHIw07aYsOf9nXUo1THJHuO/BNDY0guUbbkw5Jj1NM27f2ebC+TNL+zocDofj1WV9a4ugEXLj6kskKxzFSbPHzTd8IY2CGOwlU1Q8Jiu6ZU9SB7wGYQxaeTYKXUhkGjHpnyFprWGUnTaT8YT+zY8SDrftQcO7tLdfZP/cIy/f8Q0MN+6luXcDURBY2ztXiTuFCPZZfZVjRF1TGffI85f2GciQbb1wfw9UyFgnNIWHEIKxTvjF28/QlwFvbZxaqvM9QxtDKBSfFm4SCMVeFrGvYySCddXgMEsYG7tSTgCRSbmejeZO8J0o4sVkyOe2zhHkDu9ZbW7PsPKdzl4OgTTm2BrhdQxUyI1sEd2ua5YRVOt/x1lKaKAlxLx+d0/4eJUVmGmzRzodEkxsDLxKI1o7LzEZnCOY7M9d/N1bT5E0uqTNRU35LGwd+72t+zTzw6VtJnsFdeUdDofD4XA4PkFwzm6Hw+FwOBwOx+vO9s4BH3r82bnQDSBMjY24QLHOMiwcxXXOHmPMys82enkcpFg9v6ikdRTXzTA2AoHv5fHfehEFbs9ZrmddrW1dbK7YtVbD5y98zbt562etcHhHVvB+4sMfYDQ1pJk9eDqd8He+5at57Aih+13f8k85d2EhdK8asyj0b+7Wllbsrl5HY+yCgLQmulwIgScFjUDie9aVP6qpsQ0Qp4bhRC+1P3PCCyG4vp0xnFrheul+itw5X9O2nxv1VB53vz/SDCd67kqfOfzrIvL39w+WNzocDofjNaHT7R0pcgLEzf7SNpUc72AG69DWQqKFwtS4pdOgRdIaoIMm2g9Jmz3i7tZc6AbQQZPdi29h2llEXwsM/euPo6Jll/CxffIC4oo714uGJzhw+b1G6LLIqTcv86neYD7htyZD3t46zdsap5AIGkKxpRokRjPSCYdZzIvJEGMMe1nEE/Hu0jkSk3EtHfFkssdTyT7XszEfiXd4ItnjRjbmWjbiQ/E2TyV76LyPBjjnd/iUYKP0nN7WU35zenvpHCcRsWXNE99T1VrXy0SmfI1C4ZEUFhoYY7iRjku1vBOT0hVyLnQDeHWLAIRksnaerBBfLoDWzlXad58vb6vE17/iBRp6WdgON06/orYcDofD4XA4PhFwYrfD4XA4HA6H43XFGMMzz18vzdfOor5fWXsLQXYmYB5lgjq/6eHJhUA6E71lXlu7EUIYWKF1mgu6VbZ6kqyyXRtq40aLNb1n56kbqu/7/Pmvfjdv/awvqe33TPB+/MMf4HBiuLs74j0nELrPnr+8VJP7KKG/uL0R5DGuennhgK0VLmrrfaf5/n5+X8eRYfcwYxpr0syQ5CL3aGKse3zF/ZrGZu7OHkWGnaFBa+g0BetdyXpXoaRdfFBFSkHoL2qaA4ymhrv7mijRZHr1eU8ajepwOByOVwdzTHz2rJ6JAbTyMUKiq/Hj1TZnP1KBVCAlRiqM9DBF0fSktVLyWPXSJgytYjz1y8BUhNOsUusZs/w+Ex7cJjy4XRK9d+/9dO5efjsGQdRaY7J1Pw/7Pd4ZbLImQ94Y2hram16TTw03ueL3WVMNTqsW66rBfhYTmYwETYLmheSQZ+K90rPQF4qO8OfvORmGhvToyXKfRyblji7Huw9UyKYqx3S/lA6Z6PIix+Wq3Cfjwrnz+P6ym73IZb/HQC7c0DvZlJ8YPs+d1Pb1UCcc6oSn432GWcxOOqHzcqZMhSBur5e3SYmR5RcUb3qCBQ0nIBiVFyQEG2fwe+sr9nY4HA6Hw+H4xMfFmDscDofD4XA4XlcODsdMo/qo0pNSp0XWbcsyUKoct90IBA9d9Hjipeokq53vXqphOdRs9ssT6s1Q0AwEw+my43lJRDZWMPfUrPZk7qKWLLmKPc/nz37ltwHwgV/9r0vjmQnef+mvfCf/9cd/kCcfO5nQbfKgcq2Xhe66PktRvhbGWNHeV4sI9WNdeCm0Govf0wwOxwYllyPfk9SgaiLGp/Hy9Y1SQ7tRvh9KCjxpSCvXsxnKpTbs+UAtl4ef0+22V3/ocDgcjledZrtNsre3eocsYdQ/S9zZwCh/HkEiTFab7gGF1A+dWtFx9uwRwgrgOl157CrSRpc0aOHFi0hs7xU4uzEGlUxLm6a906AzK8zn/UR5aK0RJsOLRjSG2wgMMkuYFOp+T9bOc9sLSJqDuSP9vGrRUAHprPY1gjNeC19IWnIhDp9STZ5PDvlQbCPaNYaPxLvs64RHG1vz/foqICHjTrbodygUAZK44Ms+0DGbsoEqiPmnVZM72UIEN8CejmgWxOCTSN11++wd7HPm1CmuXr9eu1hNIrjH73Laa/GTh89zK5uQYcgw/PLkBu9sniVj4UZ/LjnkrGog5MubMs38xtK2asS8Vh/7NKyKJ4Sjnfnvwfop1h/93I+5XYfD4XA4HI6PZ5zY7XA4HA6Hw+F4XUlragqm2dH1t18JWkOcgWfA98ptDzoKWI5Nz7R1mRfZHxmEyBh05Lx+tzZmpRGsOA6BnavOMls3ujgHK4WN7KxOy4aBx5/+S98GrBa8//F737Vy3IO1Db7l7/wA7fV7c9e73S6EsNGiplyjW9Vc8pkDvUpmIKjcIy+/DlWXdDYbXKWdqrjuKQj9+vted41HU0OcGAJ/IcRrA82GYDxdjiVXNYsKprEh9OsFeyEEp7Y2l7Y7HA6H47VjffMUB0eI3TrskIWdhVM2X7lljDhWtBYAOivFktvjJZiXXwHaVBzlJxEwVTTGSIXOay2rZMp44xLh4R0ah7eJWwOm/TNIozG6cg4p8Ub7tLdfRCsPIxVePEbGY3ShZnmp3ndOA8mh0ciZ8CwECYaJTudCsxCCy0GPsUl4JlmU8biaDrk367KuFiLuQIbczaald5dQKOJiJDgQG02zIHarGpe0V9l23BugMaa21vbe/j7D0YhLFy5y5+5dRpPxvD2JmNfiDoXiLY1NfmL0wvzYBM2L6SHnvc58W1b2/Z+YpWhxY5AV9/q09/Kixv0gQGtNlqYoz2NtfYNeKyRZ64LRhBtnCdZPvYLeOhwOh8PhcHxi4cRuh8PhcDgcDsfrSru17HwBiBIbm30ShKh3cheZuXxTDVkCStpI7DQz7A41nipHjIN1/Aph5qL2bLJzb2jYH2UEno3tHkemNt4cZv2yE6Xz+uL5/6uCgmxWxJ5LIWiFHn/uK78NIeA3fmVZ8F7FYG2Dd3/nP+PCPVfIMs3hxJTGKEU5bt06uMW8vuZxaA2ZLlwfAb4nMMaKzEVRWQj7e1Ww1gZEYUFAMxQl0XlWb10b8KSpvddX72ZcOm0jzBdjEXSagjSzYxaA50GaCvZGZTEj03A4MXQai3s049I952k267+jDofD4XhtaLXbnLt4DzeuvrSylIQVrWtc2kIhzPJCujJmabWVQbx8UVNniDQpbZr2zxx5iEgTZBohgDTvgzc9BCDqbhE3e4wH50AoOx4MIp7SGG3jTw/BGDIvIA3bGG/hyA7GeyRGk4W5UFvzwJwtbtPGzEVfgBhNYAyqsO2y3y+J3WAF76LY7QlJICRRQdwWQiy90MjKYrKhKV+ztvDYVOVnrTrmbkjPI61c+xlpmnJweEin1SKaTBb9qnCv31tyog/1cpvTY79PywTj/dLvKp0iCvcjbvaZ9hdit+f76CxDa43yPAbrG7Q7XcYjG3Xe6XZpte29rS4IbfQXteMdDofD4XA4HE7sdjgcDofD4XC8zvieotnwmEzLbpcosROCqxy3L5ei03gWw33tbobOY8V9T9QK1nECgQeq4vA2ucid5POfQoijaztXhpCkdmwz0qxetJ+1GQYef+Frvg1fCX71l37quOHSH2zwre/9Ac5duEyU2FrYSgmkXLidpQSTlcVu+087lmJXbJ3u5YjzKDaEwSw6fHEtPGUXFMzc7FIK2g1BvGygJ9PWcS0l83j3xfhhkkePe0qw1Zfc3iuL1ZPY8PT1lPMbimYoKF5sT4mSO18F0Ept3fAiSQrTGDqFMqJCQJrUT6Q7HA6H47VlsL5Bs93hmY8+vnJFmxVvK7EhQtjn1RFtFxNNFryCGtFScff+z6R38wlaezeYdjaJahzV892TyDqwvQAjFSLLEOmUpNFFeyEI6wg2KiitDjOzkiG5qOylkRWtBTbGPR9TMDkgkgrtN2uvWTxfbrcctZKYDCUW04It6dEUHhOTFvZZdr5Xk1yq110AU5PiI5F5qsz1dFT6/C3hZlm89QOy1J632Wyyvr5OmqYkSYLv+wwGA67fusnO7i6r2N3fY6M/OPIdUgqBX3Gi14nsQ5MRG00gTla3W02HeNPFQgEvCPAmVvwWYZPw8psILr0BObZCfLfXp9Xp5Av8rJA963en211q/9VMPnI4HA6Hw+H4RMSJ3Q6Hw+FwOByO15UXX7yKJzOkXERsz4hTK0LXRWsXsZN+pnYu3Cab1k9rd5qC/ZEmzaxY2wrtOWfuZynBVwKl6q3jUpQnzIuCt8j/T4r6Sck0Ayns+Iru6oXgXTMe4fEXv+7bAI4UvPuDDb7pPT/A+qnLjCqibuDBJF70Vyljz6/L/RR5R2ZHh4FYrj+ej30aGzxp8JuVCFIhckc79FqCfkcxjTXDcVlIlwLe9Mglmg2fZ555ttSGlAIp7LUIPEHYtfHx2wfZXDj3Pei3JAZBktrfj6LbkoS+dfZn2iCloBmKUny6MfZ7sL13yMbmBl51tYPD4XA4XnOyND02ukUYgyk+n04iBGoN6NJKNnHMeVYiJQdnHyFuDpgOzpTOL6Mxrf3rc5dv3OgxWr9A1uwtjjcGoTNm2SRGSYTJbKL6TPCWisngHDJL5vXBBSDTmKzobAe86YjYL6zcyskwTApP36o7uC7APats7cpy5I42hq702dHRvE9vCNbY1zFPxHtoDB6SfR0zIeWUanGdyVxAv9BZ4w+cuZ9NExAnCWEQsrG2hu/7pLnY7Xn1D/WspgxOEWMMYRgeuc9IJ4wrLvMtVb52HlZ4vqqnXJQN/Irg7XnevK/K8xisrdMR6yTdBkJIGqcvEq6fwmiNSWOEFyDy+9odlPtTFLkdDofD4XA4HK8cJ3Y7HA6Hw+FwOF43JpMpB4eHNnK6AUkGabpw8freyd0rdoKQJXf17Pi6Ws2DjuRgvNgopaARiJWR4svntMJq0a08O58VuZf3LxKnkGQmdx6L0n6rhXuPr3jXu4F6wXsmdJ+/eIVMLwvmDT+/zgVHuiqboUtjMXk98llU+fL1nQn+gjRbrnFusGPpte3EbiOwQnMUGzJj70voC4RJabd6pUnjGb4n0HoxKd9vS/ptyXiqSXXZDZ5p8DmewBfzOt9VprFmPLWLAPZHQ25vP8b5sxvcd+/ZpShWh8PhcLx2yGrtixqWHpdmucayN94nC1tzF3Tj8DbBeJfh5mXSRhe0RrxcZ7fOUGmMyOswx+01lgzTSiGTGJlZQbUx2iYc77J/7g12f7BOdKlKtcYFgMlsDfJCRHvU2cDbGc+bF4DQ6XxcACqLrZhfEbJ3OFocVpXn291sUnI8SwT3eGWXsRSC016Ltva5mg4557XxhWJTNXnQNzyTHMzbjdGcPXOaLz17mf14ghSCXrAsys9YJXLPaDYa7B8crPw88H3W1ta4e/cuurqaMufD0Xbprm/IBn21EMjbfoiZvZN4Cm99nTPNLtPxGCkl3f6AdqeD1hqdZSjPW7y3nr1UOpeQEhG4sigOh8PhcDgcrwdO7HY4HA6Hw+FwvG4cHh7O/yyEIPCse7dKnJjaiOs6VonjnloWuz0l6Lcl07h+ErSIn/crScuT4VV394xq5LcUC9G22A9jIE1tPenqOKrCspJ57WqlrMNbwK/+4kLwHqxt8o3f8U85f/HK/JzFeFFbk1vSCjQHk2OHbPsBeIU61rPrO4snL5JkhkaNai5E+d4JIWiE5f3G4wmbm4LNzQ1u3rxV+sxTAl1zWwNfQCUW/XCsMUbQDE8WNVplGmuGk/J1zzLNi1fvkCQpb3jwnlfUrsPhcDhePo1mEz8ISeKofgdjCEfbxK0BxrOuY1GJ2lbRiCAaYqIRUXcTFY0Ih3cRQPfOs+yffhCjXtl0mNDZ3BGusgSZJVZUl7Y97YUcnH2ItasfQiXTef+6t55i+/Lbjqw1LsgXmBUetmnQrr0GpV+BWMh8cZbBIDgwWelx6SHwhCIpOLcDFs9NbQxPRHvz35UQvLVxioasTznpSJ/7/T5ewfW8pZpcT0eletjP7d7m0XNXGISt2nZeDhtr69y6c2dlCZnNjU183+eee+7hxRdfXBK8b5kpH5jetv33Qt555gqPtDbZHQ/xpOLe9VOc6g5IspQky2j4PnI2vkqJbCnliRZmOBwOh8PhcDheH5zY7XA4HA6Hw+F4/TiBS1Zrw5PXEjwluP+cV1PT2ZzI/a2kIPQMcVoWpjsNwa3KvlVndVGsFcK6z2eCtY0gX659OXM0z7qm8jlQpQSBbyOytbECtKfI64WX2yj2YxHHbg1bSnn8pXd9B4++/Q/wux98P/3BBn/4//an6fYGheMFXl6j27Coye0pgaAcJR740AkFO8MaZ/yK+PJqamy3KVYK/8fdJ5lfoFNbmyRJwvb2TunzVBsCWT5eyfJCgzgxRPlPr23vrZTHfzcW/TSMp6udfTdu7XLvxdO0mkfHojocDofj1eHOrZurhW7Anx4QjnfxJ/uMN+5BS9/W5QAwBm9yiBcdknkhRkiC4TZ+NGIyOE8atMBoZJagX4nYLRVp2MKbjuaucAGoeEra6JT2m/RO09l+Yb5JpRHBeG/h7ob8oV89ydITdbkflVjtzG8gpCSbvTMYQ2zKru6W9PGEJDIZkdG0pYfIn+rNRhPRbXBxmLGVJpxp93n01CWuvfAi02j1vfDEcimTrgzY1tP5tnESrzz+5RIEAfdevIfnX3pxSfAe9Puc2rS10zudDg8++CC7u7tMp1OklAwGA97UbvP2+E1Ms4S1sIW3Qsj3lYf/ChdDOBwOh8PhcDh+b3Bvbw6Hw+FwOByO141et8ONG0fvs3OoiRKIEsNHXkjY7Ek2+2ru1JYsu6JXoZSgIW089ayWdMOXeCqbx3rPKIqoqjB/q6RABYLRVFvh3JhctF4Wc7UBYex55DwGPHexF7K248SQpqBUuY2Zu9uYhVA9a2P2+Tve+Qd5+2f9wfmYqqKyECKvYW1Kx4WBYVqYc97sSSuCS83+0JAW3ecaqJkDLor5Db8YdV52lBtgEhta4WrhedDvz/t24fw5tjY3eOq5mzzz4i77Y814qvmMR8KlsYWBIUrsOaNk0emDkeZgBKcHCn9FXHmV2QKEo7izvc+lC6dO1J7D4XA4Xjl7O9vcubniJcEY/NEO/mQfLT1AEO7fIm32aRzcwotGGClJww6T/pm56xtgWo1e+VgQEu0FqHQhAgujbbS4XLycJK0BFMRuAJmuFo7nVERcf3pY/pg8Ar3wexp28Y0mRZAJyUgvalIrxFzoBgiF4sFLl+l3ukRxhJSKRl7n+iEuls71wjE1suvQFXF+0Khxpn8MDPp93tB6iO2dHSbTKZ7yWBsM6HY6pf08z2Nra2vp+G7QoIuLFnc4HA6Hw+H4RMOJ3Q6Hw+FwOByO141Go0G/32N/v77mYpoZ9gs1tdMMbu5qlBIM2tI6qE5SoLnArEa11WUNz9xMbT3vrOyXmteirgjNM3wliNOFO1obkCwL3lIuz6lnelHbWhtDki7Gp6SZ718UjYt9M1h39ywxs7hPqq3wrmQhclwAiNKceSuwkepxaoXqmXO93ZC0QsPeSDOcLMaw7OXO+5RrBqFfFKGhmji/d6hpBKK25nWv26XTKU+Ah2HIYG2dZ37tDlLA2x8Kap3hUggavl1wcFAjVEepObHYfRL0cWq4w+FwOF4V7t6+XfpdphH+5ACZxhghwRiysAszsdcYwuE24WhnHmXuRyP8yT4HZx9e1LV+tYTuHKM8qArXS9Hay8+OzK+IrJX4dW9ywD0f+PfcfvCzOTj3BtAZ4fDuYgchyLxwPh6tfJJmD+PZcXrGcPnyvTz70ktEaYIElFiO2j48OGS9P6DVPDpaPAwC0jQ9cp/S+IzhQJed3G88deHEx5+UwA84e/rMq96uw+FwOBwOh+PjFyd2OxwOh8PhcDheV+65eIGr8jq7u3vzbVobDieaw4lhEi1PEO+PNIO2xPNW1+g+DgMMJ9bdLIUg9G3cd6rLc9RS1sxZA74HMoGsMO+r8+xy3xNLNa21MXOhV2tbanomsheZxaPXCeRWCJ/Fktp58brhawOeWP6sHIsu6DYFaWaolpkUQtAKJaOpRghyF7pYqnkO0AyhFYq6pPMScQq3djLWuopGMNtbsLW1wZnT9U7p86c6rPUaNP2EdnN1LczZAgbfE3kc/ILhRNNuiJNF3av6+utFBr1X15XmcDgcn4wYrUl3bkKWotZOIYOy8JsmCXG0iL/2poeEh3eXnjU6S8nC9qzWB1nYZiLP0dy7Ot/XS6a0t19ieOrKazWa5S0VUTkY7ZV+T4OmdXvPDzClWuMyiTj34Z/Gj0ec+/BPo5odwvP3o+M1K3qvb9E6f4VnnnwSkggj5ULMLzA82EdnGX6NyD0jSZOVnxXZXN9gNB6faF+Am9mIrHBt3njqIlfWT5/4eIfD4XA4HA6H45XixG6Hw+FwOBwOx+uKlJJ7Ll7g7JnTfOjx59k9GBMli8jtwBdESVXANAzHmo3+6snbInX1oo2Bw/GiXSEEnrL1t6uibqbLTunZ/p3QsFtjchI1Dm9M7o3ON2u9+DkpRUf4bAzFmt5H7QvWoZ4aQ1Ga9pRAiuWJ+tCfxZ8vxq2kHUPo5TXQC9HlJyFK4OZOhpLQCD3e+db7aR5R/1oIwRe/814++tSzJ2q/3RBLiyPSLF8c0amvxVlECkEjEEzierm712myNujUfuZwOByOkzF97iNMPvSr6MnQblAe4eU30v7Uz0XktZFLz9ssrRW6AaTJMMkUHTTn27QfkgUtvHghzAbjHUR2j3Vhv8qIrPwiYIRcuM0BkSU09m8uPlc+B2cemv8ehiHt6IBo7yZGSFo7LzG49mH8aGSPB8689EHU53wpXHlwflyWpmgAf/VzNE0SfN8nScqCdmY0wzzevKf6Jxrn2mDA4WjIzu7u0mezsisASima3Q7tWHA28Wn7DR7eOs/53vqJzuNwOBwOh8PhcHysOLHb4XA4HA6Hw/F7gu/7dDodbtwdlbZv9QRRbOO2i9zYzdgcHC9gamPQFVf0UShJSew2xorfUWII/fIEvFISUfItWapCc1Eor5YKXeUirispmmkrpMuCwGzDxZfHluVx5rIiRgsgyQxSLFzMiYEwMEsR4xtdyV4hRn4W7d7wBb73ymNg19e6vOWRC0cK3TPOnepwsNcmmk6O3bcRSNoNw2havqrTFeJ1Ha2GQBuWFliEgeLNb7x84nYcDofDsUz0/OOMfv1nyhuzlOjp38FMx3Tf+UcAUJ5Hq91hPBriTQ+PTA+RWYw2jdJDMw3aJbFbGIPMErKjxO5XUsvbaGTBGW0QpAXh3fd9NrwEulZQDk5fpHnljfSFRxzH+L5Ps9lE/9d/gXnsV1ef5+ZzmMkQ0VwsuJJKIZVCH1FL2/cDNpttbty+lQ/RcCMdczubzOtpP397yLaIeeuF+2tLjcwQQnDpwkUG/T47O7vESUIQ+Gyub9Buteau73arhZSSB464bC+X0WhEkqaEQUCz2Tz+AIfD4XA4HA7HJzVO7HY4HA6Hw+Fw/J5x8dwGz7xwG527g0JfsNZVNEPDczdTxgXXbqZnjuvVE7MmF7pn+0th8qRTgTaGZrB8jBQCJRfu7plzWhuYxAZPWWe0AdLUlKLBi30TYtG3ag9L+x+hw9a5tnXlGGMMcQatYFnwTjJQxsaUq/yz2eUqlp72FaQp+F65DU8JfLUcXx6l5mWJ3Z/y8HlOb/aYTBNazYBW3YU/gkG/y60TiN1AHpOuGU0N09jM666nmZnXJT8KIQTdlqCZGeLU2vF9z7rcX90qrw6Hw/HJhTGG8Yffv/Lz+OpTpLt38Na2ANg6c4YXnnkamR1dJzpfSkbpb+mlcBWBrsR8hwd3iNuDefx3a+dF1l/4ILce+jyS9tqx4/GDAE9nJJHI2/fQXgCFyPBmu836pTfx/2/vTp4jSc88v//e15fYA4Edidyrsjbu7Gazmz3do+k209hoOUgmXXTQX6GbrvordJPppot0kmkdM416RprhqDnVJKtYrKqsyqzcsAOxL768OjgCiBVLFrISIL8fs7JMeLh7vO5JI4D4+fM8+v7Px471JOXzI63bZ81LmTSxjzFGtaUlHezuzj1kcXlZQZhTs91Sq93Wy7it7WT8+2niUv1m6xulzukv7r0/50ynFipVLVSqU9sr5avvfNJqt/XNi+fq909nohcLRd2/e0f5XP6MIwEAAPDH7GJ9IAEAAIA3oJAP9ePv3TsJXMv57M98aPTRvUAf3PF1e9nTvVVPH97xdVYH7VmfG6cuC4D7kVMUZ3+fVcQUeEaBd3rMqDjJKoV7A5cdP+f940QaxO64UGz2Xs65qfNPXkMyMUPcTQTPUZK1Qu/0s/B/UpKOzxU3xsgb+anfKGtFnrpsrnaSODnnjivanfwZvyEM4unK57OkqVOpmNPKUvnSQbck9aP05AGImeefeK2Qs1pZ8BT6Rr5vlAuzVu1uzjn6UapoYta372Vzy4t5exLsd7sXC9wBANOSoz2l7fqZ+wxefHny91K5orsP35ENzv6+kf2/9/j32dT6ciPfewfF2lgLc6/f0cpX/682fvfP5fVb8vptrf/+/1bp8IXu/ep/ktcf7zIzS7lSlc0XFefLivNlpUF+LOiWpGajce55JEn3v3/262v3ZYqVqc2r67eUn1PpvHZrU7l8QdZavfvgoTY2NrSb9GbuK0m/23mubtSf+/p3rdvr6fHXX40F3ZLU6Xb05VdfKY7PfggCAAAAf7wIuwEAAPBWba4v6p/8xYd69/6a8uF4m/JywWq5arVQsgoDM7eqe5hpzso2h0cMYqfDVirf01Ro7pyT03H78RnnH35+PgyyPTO9n5Ekp6mq6FnrHJW67L8kPQ3ax8JuZaH2aSB9elynr7Hqd6PTVuWjgXDgmZMQezT4dscPAwzi0xD9zoqncEb/p3bfqdNPz3zgYGj/sHX+TnMcHDX15ZNtNTrpVJifpk5bh4m+fBHPDMNzYba4atGMtJE/3S9OnI7aiXbrqZqd84enT7aEBwBcQjq/3fbkPmmnoeRwW+VCXrd/8NMzD/EGXeUbWzLHxzpj1V28rfrm95V6gRIvUGfp7sn+fqeu1S//pWyayB90tf7Zv9CDX/4PCrtZEO8POlp89utzl9qsH819iGrovNeHzPs/k2rrc1+3P/8PZ273PE8P3n1P65u3lS8UFYY5VRYWdP/dR1pZOz2ftVY9z520Lp8ldU7P6wcXWu93YWd3d+6DblEca+/g+qwVAAAA1wttzAEAAPDWFQs5ffjupj7/vKNub7wKybNZ1bTvZaHzMKtN3cW6gBojGSe1uunJ176fHdsbZJXYo6exdjqwNma8wnoYeE8eK2Xb0nR6drY0p4P5jHOkLlvzaMiezLnWrBJ8fP62U3bPRkNr38vatc9cwvF71cpG5YLVo1tGLw4S1dun+xdzRqsLVoEnHTTPvvHWvv4ztd+8yNqzxol02EoV+tIgyr5udNOTNvXdvlMpP36PS/msXf3kQxHtbqJG1439u2b/9vPnuvu+p1Kp9NrXAQB/7LzaikyYlxvMry62hZI6/+t/p+TV15Kc5IcK3v2RqnffVePZ4+kD0kRBvyXjUtm4r9bKQ0WFimSMkrCg+sYHctaX809bmJcOnykYqdz2koFsEo2dtrz7WHuPfnHm9TjnVKpU1GnPf6CrdMHW3sYPZP/z/0rp//zfSq9GrjNXlPmr/ywLw+ewnqfl1TUtr66ds97z13HRcP67UG+eXRXfaDa0sXb2NQMAAOCPE2E3AAAAro3qQmUq7LbWyNNpKDnMJq1mB8Cz5nobI0UT3S+NyYLteKLwzJsTdlsrJRcoUvOsTsu8LzD1edYM8HkFxfM+k45iKTc+mjR7GGBiBfOC3eG5K4UspA58owdrvqI4VbObPWgwOv868LKW7vPcWluY/+I5Gs3O2NeDOAu9J/9N0hkt3H3PnFzDqMA3U1XiTlKr51QpzL4nG+vr3yq0B4A/dsbzlX/vJ+p+8q9nvu5VFjX45f8iMxqGxwNFv///FKxta/lP/5nqn/07xdFAck5e1JM/6MgcP33mxQPZZCDZ064waTjd4rtb21R1+4uxban1xwJvc4Eq9GK5osWlZR3s7iiZ8wPByur8au1Jpros77/4r+W2nsjtfiOTK0oPfygT5C58jrNsVGoyxswNtI2kW9XzZ5V/Z87J3a9RLg8AAIBrhrAbAAAA10IUxTo4OJz52rz25ZNaXac4lUr58cDbmPH23UOBNx12G2MU+E5xPP6569z25hOV2f5IJ/ZhS/Eha6YD+mHluRv9es7lGjN9Tknqx5K1ToFnxl5LnVPONycfEA/PO3nNUvYh8nBW9VDgWxVz43PGk9TNPH5ooVLQ5npt/g7n8DyraOIN8qFRu3e6iKWKVaXoTR4qafaDAoFvlAukfjS+X7vn5FyqUv60RX6cOPlhQcvLS699DQCATOH7f6G031X/8a/H0kpvcV2Bb5XOqfpOd54p360raO7KjwZzz59rHahfPTtgdmb6+4Vx409QdRdvn3kOSVpeXZMfBLr3ziM9f/q1osHpuqz1tHH7tkqV6Tnb5zEbD2Q2Hlz6OEnq9/tyzimXy6ne7+jjnW+0322pFOT0g9U7em/5lj7feznz2HeW1lXJzZ7//TZUymUdNebPeK9csGoeAAAAf3wIuwEAAHAtbO/sKJosvx4xbLU9NKy2Hra1jpPTauNWVwp9p9DXcVWTVMiZsfnWUlY1HvpOg4m3tcYoDLLq4X40HkRPVhaNBt7Wjq/RWo0FzZ7NAtdZleMn16jZr0nZtc4rbOoOpMRzCnyjYUFyHEs5f3z2tDWSNdPXLB0Hvd74CnxPY/u2e27uGoyRfv6TB99q1vXK0oKev9ob25YPj+eKH69jsTz+5EKSOHX6TlHi1O07rdXs1HUsla0OWqn60fCBguz1Tj871rfD+eiSNR3FcSLfnx2oAwAuxhij8p/+rQof/kyD519KSSx/ZVP+6qZa//1/c+ax8ZNP5M5pqTIZWs+Sa++PH5PGsnH/5GtnrA7v/nju8dZa3bpzV8Xj0RaFYlGPPvyeWs2GBv2+fN9Xpbog63133zOO6nW92t5Sr398Hdbo991DPYlPW4F/vPONfrR6V+8srevrg+2x790PF9f0Vw8++s7WexFrq6tzw27PelpZXv6OVwQAAICbgrAbAAAAb51zToeHR+fsM13xbI1krNSPnAbxeAQ7iLNW3sO51QtFo/7AqNUb3y/wjYxxY1W/J+e3p2XXxmTBb5zMDry9iYrs1El2ZCa0NVIYWPm+U6c3Xh09DMKtMYpHSr9Hg3LnsiB2VmW3HR5vTfa+w+OV3ZtckAUOw6pxY4xyQTbDOvCz9t+FnJkTdmdzsOMkC//PeB5Bzkm7+y3dv/N6LVijKFa71Zq6RmOMqsUs7HbOTVWgGyPVO1ngkfONun2pVBifY26t0UrV0yByU/O7JSke+Tp1Tv0oJuwGgCvilaoqfPAnJ1+7JJbOaR3uooGCpXUN9l7JWU8mTWQmvgMO8udUUqeJyrtfjZzUKejUTx4sc2Fehz/9jzSorMlIKlUqWl5ZVZIkWZAdBKou1KaCbGOMKtXXH9kRRdkPHUEQaDDo62h/X1E0UBCEqi0tK8zN/z56cHSop8+eTVyn0we5mkJj9Xl0dLL517vP9M8e/lA/u/Ountf35ZzT7YVlLeSLr732N6VULOrhvft69uK54pGHHMIg0IN79xUGwRlHAwAA4I8ZYTcAAADeujRNlaZnV2c5ZQGy0WgltFO97fTqIFE+NCrlJyt+JXdc7ex5VhtLRkftVPV2ehKcxkkWYFsjzRgDLd/LQtbh+/reafAsnW6f1Xo8SSXPZoH3MDe1xqhcyGZId0aC95OZ5BoPeoeB96yW6tZMtx53bvzBgCjJwtvAHwb/w9nn2ZoqRaNcYDSInPbqTqs1p1wwfs7Qzyrgu4NZUfu451uHWl4qq1y8fOD97MW2BoOB8qHRIB4PpPOh1XLFzKwat9aoEBr1oyysT1Kp2ZFygVMYmLHW5rnQqpCkUw89TJ4vF/CrEgC8KcbzZZc2lB5szd9p9Y46pXU1yptyni+Txso191Q8eC6bxkqNp+7infnvIWm18UxBvy0ZK+/Oewq/9xeyh6+kxr5UWZb94M+0GuS0evWXOFP98FB7O1vq97L27X4QKI7Gn7bb29nW+q1NLa9Nt2d3zunl1vx7dj+o6GncVN+dhsV/v/1EP1m/r4/W5t+r66K2sKBqpaJ6s6E4ipXL5VQpl09+RgIAAABm4RMcAAAAvHXWWgWBf2Ybc+k4yJXUaidqdrP208MK6SieDi+dsiA7H2ZfG2O0WPa0WPb0yZPBdDtxTUe5vpXSkQz9tDp6usJ75vunWdvwyQ9qPZuFzaNrcMM+5hPnHQbYk1KXHTN67tA/DuhHCuaSVEoG2RxzO1Gs3Btk4fawPfnuUTbDulwwx1Xvw6pxK2POuWBJewct/fN/+TvdubWon3z/rjw7Y1j6DGmaam//SFL2QEA+yG5wEGRt2UertNPUTYXeCyWrw+bpzXRO6g2y25nPje9byE1X+I/aWK1R1Q0Ab1j4/b9U7+/+x5mvpUFeu4V19bp9ycs+unLWV29hQ1GhqoWtz9W+8z3pjO8xiysrWvnxT+X+8X8i6fShMm2+eyXrHwwGqh8eKI4ihbmcaotL8vz5H7Md7O1q68XzsW2TQffQ9quXyhWKKk/MAG93OidV4bNYY7TuFfRN3DrZtttpXuRyrg1rrRYXam97GQAAALhBLvbJEwAAAPAGGWO0vLR04f2djBqd8VbgueC0enpUlGh6ELakSnH8R2FrpFJBmiwcNsbIu+BPzZ7N3mryHKmbXQ89q3j4ssVLo2G5URZ2e9aomJOCkfvhe9PrkqRBJHV66cm9dJJaPaf9ZqowMMczwM3xeo3y4cUW+PzVoX772YsLX0ccJ9PV/WY66G51U/32SaR0Iv33PaNibnptk+3tpez+VIuzr6NYyOn9d25deN0AgNcTPPqJwh/9taa+SYd5DX7xn57Oo56QhEXZn/1T+dWzZzg3jrL5z9kYj6utDN7b3tKXv/tEu1uvdLi/p+2XL/T57z5Ro340c/80TbWz9epS73GwtzvzPOfxJq4179H+GwAAAH/YqOwGAADAtbC6uqJ2p6NmszW2fbJyWZLKBXMyP1vKQubNZU8yUqs7PVc6SSQ78ZPv6oJVvZ2eVEznAiPfGpULTr2B02DkHJ7VdBX4SSv14691WjW2VDWKY6kXuayyODTyrdSfWJfvZe3BB8ct1d2cc0uS52U/vA8mry2VJCfPSkFw+oG+NUal/MU+3G/3prdFsTSIsjbgQ6mTlqpWWweJLvB5u755eaAPH91SLjz/1w7f9+RZq2TixHFyOnddkj59GqnZdfqHx5Ee3fZVKWRPIjjnZhb4Jen0dUhSMWfle07WL6rdHcj3rTZWF3V3c1kBVd0A8J3I/em/r+C9P1X01T/I9TqytTUF7/5Ie0+enHlco96QPadzSHLOTPDX1awfzQyuXZrqxdMnyn3woXK5/NhrrUZDaXK59fS6nalthUJBxpisE8wc9WQw9vX3V29f6n0BAACAm4awGwAAANeCtVYPH9xXvdHQ7u6+Wq22nJPSVPL98cDbGKPNZU/P97LQtVa2J9XH1aJRnDh1+06py6qZB7Gbmm1dyFk9WPf1fC9WFGtspnYxZxT6qVonIbCRkZuqzh4NpUfz+EEkVYtW5cLwdacodjPngoeBkbVO/WhkDriZPmetZBV40m4jnQ7zh/nwyLmT5HRe+Os6aKZaX7THH6xnawr97N432qlaXTdzzvlQmjodHLV0a6127ntZa7WyUtP2zsHY9iSRYjl5ntTsOjW77mRtv/xsoM1lq4cbgZzLgnGn6UL+di+b/50LT6vEk9Rpeammdx7cvcQdAQBcNVtdUu4nfzO2LTknGE6TWKXywsxAeKhQKFzJ+ibt705XXA8553S4t6eN2+Pzsc+7nlk8b/rBq8D3tVir6eDwcOYxjWSgg/S0Ir4aFvSLzUeXfm8AAADgJqGNOQAAAK4NY4xqCwu6vXlLcZKFuO1+FqpOKuSsHm74WlmwKk5UMGcV01lFtnNSP5K6g+lzlAtGSxWr0NPMmdrDorEkPZ7TPWPN1mTtwkcLzDo9p2QkBU7T7PzDedpGx5XczilOssD4rGJi38sqz601WluwWq5YBX62Jns8U9sYjb2nU1adfVb113naPaftw1RRPB70+57RUtXTYuX8XycuE7bfvb2hYiE/tX0QOz3fS/Ryb3qm+34jVZpm9zIaacU+dY7Iqd116vRStXupuv0siAcAXD/5c4LqXKGgxeXVM/dZWjn79dfV7bQv/XqhePngvVpbnLn9zuZtVcrlqe2pNfo8yVq3B9bTj9fu6b/8wV+qHE5/XwUAAAD+kFDZDQAAgGunWCwon8+p1e4dt+12SlyiUs6OVWj7ntFydXZKHPhGUeJOqp67fZe1s/alOJWi2KneSjWIJWPNVLt0Y4xyvtTpu5Ovs4rr0yh1tHW5RuZyp07aq6daLFuFgTmpfjbGKPAk3zo1uuPrzWaDu6nqbknK+ePrKuQk54waEw8BTFZZp8dBv2ddFrK/RpV3u+fU7iWqlY1q5fF7XZgxI3uU71utLE5/ID9/f0/f/+gd7ewe6uXWvlqdvvoDp4NWFk7HyXSM3Y+yKu/qxAx2p+xBgOEDAcNLH71H/X504bUBAL47S8urahwdzX99ZVX5QkGbd+/p5fNn43M/JK2src8Ni78t63lK4umHr05et9M/l+QLRRVLZXXaF3vIKszltLS8MvM1z1o9eviOWu226o26nHMql8paqFb1J5L6SazAZqNBAAAAgD8GhN0AAAC4lu7e2dCvP/n65OtBJA2iVNWiUT48/wNca40Cf3z2dlYp7rRfH58LnVUFG02Ols4FRr2B02jz0WFgPBnzJqmTzGibbGmvkcr3pMXy+HqNMfKtUzyyDM9KpZLRYcuNhOPDA6avLx+Oh91G0lLZypjZc709b3Zl+kV1ek61idza94wqRaNmZ3b1+KMHa/IvOf/a8zzd2liRszn9b3/3xdT7jT4QMPTly1g/eBCctLIfMsdV7/Pkc+Gl1gYA+G4Uy2Wtb97W9ssXU6+trm+oUl2QJNWWllWqVHR0cKBBvyffD1RbWlYu/+aqmasLNR3u781/vVabuf32/Qf65qsv1e/1xrZ7nqckTSXnZKzVQm1Raxu35Plnf2RXLpVULpWmtuf94PyLAAAAAP6AEHYDAADgWqotVFWulNU/HK+CGsRS/oIZZeAZTTa1tsftxEcD4TiVkuOZ2r432RJdJ+2xR43Ohk5Tp8HxPpX8+P5Jkr0+GcTmAqO4f7q2QmjkWaOlilO759QbZK3DPTu8jnHWGlUK5mSGdT408o73ywVZIJym2SI9++2Cbim7X72BUz4cP9NSxcqYVM32eKvzWrWoD97ZeO33W18pKRd66g/Gb34xZ9Tqjr9XkmbzvBdK42tL07PD7vXVpddeHwDgzVpeXVO5WtXR/r6iwUB+mAXZ+fx4S/AgCLW6/vrfby5rZW1djfrRzOrufKGghcXZ31uCINA773+oZv1IrWZTklSuVFVZWJBzTkkcy/N9WSqyAQAAgEsh7AYAAMC1tbhQ1v5E2N0bOJVy7iTYncc5dzJre3JsdalgFbVSOXe6n5RVfQeek3ccTEexU6fvjudxT7/fMPAerdCuFI2ck+Ike+/Ql3qRUyGcDNGNimE2SzyrQM5e96xRtWhUKZy2T5ekhUpB9eZ47/NS3srznIwN5JLTltzGmGwG+OWKqs+1e5RofdFTGIy3VS/lrZrt8VC62e4pjpNLV3YP7R+0lPNT9Qfj27NqcqlULKjR7iuOEy1VPC1V7FTFt9NxVfuM3KBaKWrz1uwWsQCA6yGXy2t98/bbXsaYIAz14NF72n75Uq1GNiPbGKOFxSWt39o8M6w2xqhaW5xqsW6MkQ3pNgIAAAC8DsJuAAAAXFtLiyWZJ5O12dJhO9VCcXx+96h2L9VxV3EVQqnTH3/d94xqZat2N1V3IkyNEqk3SDUc5zysZJ4MUqUsKHdOGh0l3e45VYtWw4y31U1V7zjVSqlK+fEPwLM52tNhvDQ9X3t1paLFhaK+eXmg9LjPeeB7+v7763r0YE2//Phrvdqpz7wf55mcVz5Pkkpbh6l+/OGGDg7rarZ66g6cuv3pC0iSVM12T4sL0y1Wz32fJNXHnz5VPsweHGj3XValrux+rS/l9B//7Ufa2dnV1vbOyTU0OtMtzpOsM6zCIPvTmKxSfm1lgeo5AMBryeXyuvfwHcVxpCSO5QehPO+KnzADAAAAcCGE3QAAALiWoijW82fPVClaNTrjCWaaSq1eqlrJzgxpPSuliZQLjQLPyJisQnsyVLbWyPfcVJvyYQbq2dO25sa4k+DUHZ9oeL7RZunNrlMhdAp8I+ecmr3slaO2U7ufqJQz8j2j1GUV38MA9rzAuVYp6PbGoj58dEuHR21Za7S8WJZ3XLa8tlJ9rbC7N3CKEqdKYfZ7B75OguZizmhtOa97d9bV7qV6+qpz5rk//vSZ/vGfvy/vkqHy1m5d0fE/SiFnlA+zSnnp+AEBxWp3+6pWqydhtzFZxXe3704eVBjuXzy+56MajabW11YvtS4AAEb5fiCfGdkAAADAW0XYDQAAgGtpf39fcZwoHxoFnlV34BQnWSCcD4zCYLr6eSjwjeLEyT/OWHNBNqe71XVqdNJsjvZxOu3PmOttjFEYOJmR1uWeNfKs1B+kU6G5GZngnTppp56qUjBjQbEkRbFUj53yufHjnctmYufmfF6ezwW6tVbLriX0tbG2MLXPnVuL+uLrbXUmS9XPkDqnejuVk+RcqlLenLRTt1aqlaxqZTN+n9NI/X5fm+s1ff7V9pnnbzR7evHqSPduX242drc3fg3GZPdybJ/uQFbR2IMG1hiV8kaFXFYJbo2mZqUPuXRGqT4AAAAAAABuFPr2AQAA4FpqNE9ndXueUblgVSt7WihZ5cLTADZJpltoe9aoEI6HtMYY5UOjKD4NuqUsIA1nPALqe2bmrOfJ8NS5rJI4HTlp6qR6x2mvMb22bI709PZOPwvzJwW+pz/78YO5oe3peq1+9qP7Z+4zqTdwJ0Fxp++0W08V+tLtFU8P1j0tVmZXzsdxot989vxC7/Fy++hSa5KycP88npVevXqlWc87WJNVcp91z4ql4qXXBQAAAAAAgOuFym4AAABcUzMGWU9Ikqw9eS6QwmA82PS86aAz8LPAuzcYP3c+yOqDB/H4/rOCVN87baktZRXZqcvapgfGHR9nTluda7oCPYolG4y3LXeSGl2n9+/XFHhZeL68WNK928vKzUrjZ6iWC7LWjAXvZ0mS6W2dvjuZUz6LtVb7R13tH7Yv9B7xrDc5x9pK9czrqC0U1e9l72+mC/PPZYzRyvLlqs0BAAAAAABw/RB2AwAA4FqqlMvqdntn7tOP3MmfcZLNyR6fzTw9B3tlwWrrIBkLrI3JKsFzvlMvymZzG0lGRpPNro0xygXSIM7mbY/O+07T0/nbUnYO65mptufOSf1ICjwna7Nzps4p8D394qfnV3HP43lWy4tl7e43L7T/rFHa+81U/cgpF8xew+Liop68OrrwmhYXShfed+izL54p8KT+jE7jvm/1ww/v6nB/52Rbds8vdm7npHt3byufz196XQAAAAAAALheaGMOAACAa2l5eUnerD7ix5zLQumhJD1uy32ceg5ip07v9Osh3zPaXPZUypupym1rjQLfyJqsBbrvZ5Xck6zNZlsn6XjIOhm4hsGwnfasC8jWHCdSFDslidTrJ3qx05h7zefZ2qmfG3QnqVMUO/UG4/dv9Bo+fRqdPEgwyg/zWl9fVxRdrFrbWqOHd5cvtO/Q4VFTB4dN+V5Whe/Z4wcPTPZvsbpUUrVckO+fPrd71qMB/cip00vVGzi1e6mOWqm6/ctXmwMAAAAAAOD6IewGAADAtRSGoR4+fKAwDC91XJwcz9E+DnM7vSzcHYbeUezU6KRKneTP+Gl4uM2zWcDqWSn0sz/jJDtXp5+ehMGjRdipO50HbszpfG/PGvleVkltj8/peadt0o2RijmjhaLVV092tL3XmArpz+Oc028/f3mB/aRelFWk+15W0T6p03f6+y8G+nor0m490fZRot8/j/R0O5W1VgvV8+dd+57Vz3/8UMVC7lLXsbNXP/m7Z43yoVUxb1XMWeUCq0ajrThOVK1WT/YzJruv2f10J4F+q5uq08tmqnf7ToMo2+/oqHnp+wsAAAAAAIDrhzbmAAAAuLZKxaI+/OA9NZstff3k6dhrxhhZ65ROVCcP24sPJWkWdEaJG2tdLmWB82SRsjFG+cApTke3ZVXFzY7T5BjpyZnRaZp9GfiT+xlZuaky5MCXaiUre5x8HzXa+te/+kqryxX9+U8enlndPuqo0VW70z93v2GIL5cFv7kgq57uRdn9yVqvZ9d72HI6bJ3eoHavpdQ5lYtnB9h3N5f0ww9vK5hVFn+OZFa5+YRBFOnFyy2l7vRhA2OytadOarSng+zAlwqhkecZRYOWPvvsc62urWhl+XKV5wAAAAAAALg+qOwGAADAtWaMUbVaURgGY9udc5qVAzsnDeLp7d6MXteeZzRx2pPtky3OJSk3sW+czGkFLs3cPjk/3EiqFU+D7lG7+0397stX0yeZI5pM8ufIwvzxinTfMyrnrUp5o3zOKDxu5T59rHRU7+iTMyrI799e0p/84N5rBd2SVK2cXTWez4VqNhrq9/ty7vjhAnf6n4xRIT/+DxX6Urlg5Y38j2AQRXrx4pW2tncEAAAAAACAm4mwGwAAADdCsVAY+zpJszbhF81UrTVjAa/RaZvsfDj+mqSpryUpnzNjAfuwKjw712l18fDP8+RDc9LqfJZvXhxcqNJZkqrl/MyAfhbfM/JmzSI/5/i7Gwt6/HTnzBbgucknAi5pY21R/hn/qLc3l3VUP51r7nTaPj49Drw9M/60QyE3/8J2dnYVxzOejgAAAAAAAMC1R9gNAACAa+/o6EiNxkjA6U7biQ+rs30va8ldyBmV8poZ/Ib+SNvrkZ+Ew8CoXLRjQbad8ZOyNUbVolEuyNYwzHydsnDbt0a+Z+Rbo1rZqlqcVR2dbcsHZqpSfFIUJ+r0BmfvdCyfC3R7ffFC+2bXMnvbvFjYWqMfvL+h3f3Wmefd3W9eeA2z+L6nH370YGZl+ObGsu7cWlGanF3FHvhG5UL2YEI2K31+2O2cU73x7dYMAAAAAACAt4OZ3QAAALjWnHPa2dmRMadPasZTc7OzSuXAG4bJRsWcU6fnRsdpy5gsYDbWKYqnA1DfN0oG2RHWGPl2fHa3lAWntbJRkjh9s3v6YupOW6V7VqoWTTanuyR1+u6ktXrgS6WcVehfrAz7Mu3Af/TRHbW7fR3WO+fu63vTrdaNMQq87JpHZ5MbI/30o1taWSxdrGT9W1qolvQXP/tI27uHarV78n1P66s1lYp5SVKhWNCgHp15jsA3Cvzs3+k8aXqxFvAAAAAAAAC4Xgi7AQAAcK31+30NBll1sxkJk2eNqHZuZB/PqFSUokiK4iz0tsNW48bKOTd1jtCX+iOF1NYaBSar4B5Wb2fHG5njcH3Yyjw97qdtjVTK25MK7tDPZmAPW39Pzu0+y+pSWflLtAUPAk9//fP3tL3X0O8fb+mo0Z27rzFGge8UxdPbc352nenx/fSsUaOZBejrK1U9f3U497wbqwsXXu9ZPM9qc2N55mv92Jdz7kL30ps1rH1CsXD2nHAAAAAAAABcT7QxBwAAwI1jjZnZpjxONTZP2hqjXGgUhka+n83HHgaks2ZWG2N0XDw8ts1aI8+OH29M1qp8VOo0VQk+ep7LBN2eZ/W99zcvvP/o+2ysLujBnZXz38Nmle6+l4Xa1mR/9zxzPA89u24j6bDe0cFRW+89WJM3py14Lufr/p3ZAfVVebFd18efbeuwdbFZ5ucpFgsqlQi7AQAAAAAAbiLCbgAAAFxruVxOvj/dkCiY0907ndG12pszfzuY0edoXpA7S7VotVSxU8F76s5vnX2e2xs11aqvH8LeWluQvUC4bszxnHHPyPPGA3mjLAC3VoqiWH/3yy/07z55pp98/65KxdzYeWrVov7Rzx4pF77Z5lG/+3JbktTofPt77Hme7t+7+63PAwAAAAAAgLeDNuYAAAC41owxWllZ0dbW1th2zxqFvlPqrOLj4dNhEGihWlK9Xp/a17Nuaka172UV35VyRb1+lM2GXqnp2au6Xm4fXWh9i2WratGo03NKnZQLjPLhtx9svbPXvNT+7U5fT57t6ajZle97iqL4UqG7MVkb+JOvlYXck44aHX32eEv/5Bcf6KjeUaPVV7kYam2leqn1vo44SbV/1JYk9QZOUewUXHD2+SxpmsqbVeIPAAAAAACAG4GwGwAAANfe8vKy4jjW/v7+WJvycqmoe/fuSZLS1CkMs/nWv/99V/3BYOwcgTec5+0pTrJB24u1qu7eXlexMN67vFwqau+gqUE0PRg8H2ahcD863eZZo0rx2wfco/qD+Pydjr3cPtLf//rpt6ooN8rmkp98fcbltDsD/cMnz7R/1Fa3l92IpVpJH767odXlymuv4SJrHLVXT3Rr+fV/pXHOqdvtqlwuf7uFAQAAAAAA4K0wzl1Bj0UAAADgOxBFkZrNptI0VbFYVLE4u833YDDQ06fP1Ol2T7ZZa7WxvqaVlWVFcSzP2jOreludvn7/eEsvt46UOiffkxZKVgslo95Aerk/HYRfpUo5r7/9yw/P3a/fj/S//92nSmf1b78k57LA27nZrd/PY4z05z99R+tvsMr7X/zyS23tnla9V4tGKwuewtes8H707kOVSqWrWh4AAAAAAAC+Q4TdAAAA+IPV7nTU7XTleZ6q1cprtayu1xt68vSprNHJPGvnnL7ZSRS/wbz7Rx/e0cN7K+fu98XX2/r0i1dvbiGXVC3n9TcXCOlf1+5BS//Xv/5yqop9rWa1VLncv6/v+/reRx+MzSkHAAAAAADAzfEa9RoAAADAzVAqFrWysqzFxdprz2Yul0sKfG8sEDXGaLn65n6Uvr1R04O7yxfat9nuv7F1vI5Gq6dGq3v+jq9pdamsf/SnD1UqhmPbg7Bw6XNtrK8RdAMAAAAAANxgzOwGAAAAzuB5npaWlrS3tze2vVywOmqm6l98tPZMudDXylJFvf5AuTDQvc0lra1ULhzC5sLr9yN9HKdv9Pyb6wu6tVbVzn5LrU5fC5W8KsVAv//8S120cVW5XNLy8tIbXScAAAAAAADerOv3yRgAAABwzayvrytNUx0cHIxtL+SN+q3LTQUKfE9RnMizRrc3FvXhow0V8uH5B85xd3NRXz7ZufD+xmQzud8Uz1pVSrk39waS0tTpi6+39M3LfUVRIiPp9qono2zm+EV0uz0556jsBgAAAAAAuMEIuwEAAIBzGGO0ubmp1dVVvXz5Us1mU5JULVodtS4+uPv9h+v68NGGoiiR71tZ++1boVfLBb17f1WPn+5OvRYGnm7fWlSvF8n3re5sLOrrZ3va2m1c+Px//pOHqje7+uzx1oX2v7u5qCB4s79m/Oq3T7Szd3oNxbyRPc6sh3c0PSf1TpJEcZIo8PmVCAAAAAAA4Kbikx0AAADggoIgUK1WOwm7A99orWa1c3Sxtt2tTl/GGIVX3Hr8Bx/cVrVS0FdPd1VvduV7VrdvLer9h2sqFk6rrHf2m5cKuiUplwt0p5y/UNi9ulzR9z+4fen1X9TeQV2Pn7zS/tH4nPJccPr3YaG2cWdXeVtj5F3BwwYAAAAAAAB4ewi7AQAAgEuoVCryPE9JklV0V4pW+dCo0UlVb7kzA9ZGs/vG1nVvc0n3NpfObM39ye9fXPq823sNPbq/qlzOV3/OgPLAt/qzHz/U6nLl0uefZxDFevZyX7v72YMFxbyvo3pD/cHFGpVn/xLzW5TXarUrqawHAAAAAADA20PYDQAAAFyCtVZ3797VkydPTrYFvtFy1VO7FyuanQdn+wXeG1+fMUZ7By09e3WgwSBWuZjT/TsrStNUjVbv0uf7/eMtff3NngZzLsz3rP7q5++pWi5826WfaLZ7+je/+lL9wel79gtGxpiZDxN0+k6jb5+mTi/2EpUKVrXSdKAdBIE2NtaubL0AAAAAAAB4Owi7AQAAgEsql8sKgkBRFI1trxSsDprzW5rfubU4c3uaOhmjuRXZF+Wc08efPNM3Lw/Gtj/+Zlfv3n/9cHde0C1JMlJppFX6Vfj4t0/Ggm7fO703npXiiTHpvYHUj5xyQbZPo+M0iKVBM9UgcqoWrUI/m+Pd6jqtrVUUBIEAAAAAAABwsxF2AwAAAK+hUqno4GA8VK6WjJpdzazurlULund7eWzby60jffl0R4f1joyRNlYX9MG7G1qovF6V9NPn+1NBtyQ5J335ZEfWGKXuYm3ALyqOUx3W21pZupoW5of19lQF+ugjAHEipc7JTjwYsHOUaqliVMwZNbunDxy0e07t3ng6HqV1ffRo80rWCwAAAAAAgLeHsBsAAAB4DcvLyzo6OlKangarnjW6veLpsOnU7klxkirwPd27vaQP3t2Q75221P7i6219+sWrk6+dk17t1LWz19Rf/uxdLdVKl17TV8/2znzdWqM0udqw+6q12tOt1odLjhOn3Xoiz2Sz0q09DbzdcdW2nJTML66XJEWTpeEAAAAAAAC4kQi7AQAAgNeQy+V0//59PX/+fKydeT4X6s/evaNCoag4TuT73lgoK0m9fqTffbk187xJmuo3n73Qv/cX719qPc45Nc+ZyR3PSYE9K60vWTXbTs3u5cLwwPe0uHD5YH6eXDjdXjxNpSRxanZSOSfFTjpspcoFRrWyle9JucDI97L77HtG8Rmhfq16dfPFAQAAAAAA8PYQdgMAAACvqVQq6f3331er1VIURQrDUKVS6WS+dBB4arVaajQacs6pVCppYWFBL7aO5M5oJ37U6KjZ7qlczOnJ8309ebanZrunMPR199aS3nu4pjAY/1HeGKMw8DSILla1HPhZQJwPjSoFk1V9p+mlw+53H6zKG6lY/7ZWlirKhf7YzG5J6g6ceoPxtfUjJ9+TSvnx968WzNS+o965t3pl6wUAAAAAAMDbY9xZn7IBAAAAeC1Jkujp06fqdDpj24MgUOSKevzN/pnHr69U5Jy0s9+ceq1czOmvf/6ewnA88P7Vb57q2avDC62vXDBaX/TGtjnn9Gwn0UXycs8avXN/TR892jgJ96/K1m5dv/rN15r8TaXRThVPFKeXC0aby6f3wVopH0iNjtNufbqS/cN31vXho1tXul4AAAAAAAC8HYTdAAAAwBvw7Nkz1ev1ma/1Ik8vdvvf6vzv3l/VDz64ffJ1o9nV3/3yi7mtyicZI91f9+RNtFjvR06v9pOpudeVcl4/+d5dtTp9WWO0tlKZqi6/Sof1th4/2db2XkMuG8Wtbt+pH03/+rK57KlcyKq784HkHbczj2KnRidVnEieJ1WLVvfu3NLKysobWzcAAAAAAAC+O4TdAAAAwBWLokiff/753FblUZzq2W46Vbl8GWHg6T/4mx+efP3//P1j7c6oAh8yRlPvVykYrdbsVGW2c5KXq6nZiWSN0cZaVbfXa7L26tqVX9Rvf/9Cj5/uHq/LqdVzM+9brWy1VvNUzOnMSvNyuawHDx68odUCAAAAAADgu8TMbgAAAOCK9Xq9uUF3nKR6sfftgm5JGkSJnHMyxqjXj84MuiVpoVLQUaM7tq3ZdYrTVJsrOcllM7IrlYpWV1dVLBa/3QKvyNpK9STsNsaolMvmd49WnhdCo5WqVT682nbqAAAAAAAAuN4IuwEAAIAr5nne1DbnnPYbqertq2msVCqEJxXMg0F87v5RlGh1uaL9w5bS1B2v0+rO5qo+erRxst9Vz99+HfuHLTVafeVCT76NlQukfpS9Zq1RKW+Upk4rC1ZBYFQITyvOhw8AzFOtVt/08gEAAAAAAPAdIewGAAAArlihUJDn+UqS0xB6t56q2bm6CUIP7p7OnS4UQnnWKknnz+tudwdqdwcqFUI9erimXBhoZamswJ8O5t+WZqunX/7DE9WbPUlS6Et3Vj2tLXp6tpOM7WutUS60ygWnwXYUO33xPNL3HwSydjrwDsNQCwsLb/YiAAAAAAAA8J357ofuAQAAAH/gXm4f6cVu/6SVeRS7Kw2611cqeufeqpxzcs7J96xKxfBCx7a7Az1/eahbawtqtnr65sWBdvYac9uuf1cGUay/+7ePT4JuSaqWsnninjWalck32uPh/hcvYr06TPXvHkdq98ZfO2ymun3n3syqewAAAAAAANxMVHYDAAAAVyhOUv3Dp88VxU6vDlItVax6g9cPkq2RCjmjJHXyrFGlYLS5GurZs2/UbGZzuhtdq0ZrcOFz7h+19X/+y0/V7pweU8gH+vH37mp95e20+f7mxYF6w17lx0L/tDq7EBo1u+P3sd1zCtupFkpWUey0fZhVf+83Uv2rTwaqlYwC36jdc+r0nRaWm/rR+/k3fzEAAAAAAAD4ThB2AwAAAFdoa6euKM5C127f6UU/0euMwTaSSgWjpYpV4I+foF6vn/w9SZ32ji4edA+NBt2S1O1F+uXHX+uvf/6eatXi5Rf8LW3vNae2JamTZDSInLr92Q8MHDZTFUsl5Uu+Urc79tpR20k6PW5rt6kfvb96lcsGAAAAAADAW0QbcwAAAOAKTVYnS9JlO4TfWbV6cMvT+qJ3EnTHidN+I1EUj5+s23eXPv88aer05ZOdqznZZc14ImBYyV1vp5KRPJtVuo+yRnr0YEP379w69y26nYZa7faVLBcAAAAAAABvH2E3AAAAcIVKxdzUtiR1x1XKFzOIJDsS/saJ04u9RL2Bm6ryvmrbe403ev55NlYqU9s6PadmJ1E/yu6dMZK1ku+d/met9Gq7rkop1Pry/Ip0I2lj0dOrV9tv6hIAAAAAAADwHSPsBgAAAK7QUq0kb6T82DmnfiT1o+zvF3HUTsf23W+kihONnXcoH77Z8PtNcc6p0Wxqf/9AzWZTOW8g35veb/fo/HsWx4mevDiQS3ry5vyG8/CWr3xo1Ol0NBhMV98DAAAAAADg5mFmNwAAAHBFnHP6tx9/PVbFfTy+P65FggAAC7ZJREFU+/j1md26pwwiaesw1dqClTFS+7id9yCeDn6TrMO3rqiTudaWq1d0pnHOOSVJIs/z1G639c2zF4qi09DZs9KdVU9bB4l6I+PEL3K/yqW8Pv70hQLf6IM7vg5bTjtHiZJUWigZ3V31tb54mqSnaSIpuMKrAwAAAAAAwNtA2A0AAABckZ39pvaPxmdCj3Yvj1MpvGBvpU7P6dBLVSvbkyA7iqVuP1Uhl53EOadX+8mVBd3WGD16sHZFZ8skSaKt7R0dHh4qSVIZY6Yq3IcF66FvdG/NV2/gdNBMZaSTau9Of/ZVBr4nP/DVH8SSstD/e/cDfe9+IOeczERa7nmewjC8yksEAAAAAADAW0LYDQAAAFyRrZ361LbRqDVOJN862RntyIv5QNVKQUf1hnzPqFq0KuSyYNia09B85yjV5rJR4Bu1e05JejVrz+cC/eR7d7W4MH/u9WUlaarHj79Wt9c72XaRVu750KiYM4oTqZAzygVS6lL1BuPHetboZz9+qEbrtBS82XGKa06+Z6aCbklaXl6StUxzAgAAAAAA+ENA2A0AAABckTSdDnI9L6voHupFUuA5+Z5OqpyNMfrhR3e0tlzRp59+Ona8MUaVolG9nZ07TqRnu4kqBTPWLv2y7t9e1p3NRXU6feVygdaWKzPD4df1+Om+nr/cUq30emsshEatrlMuyO7ByoKn/sCp00/lnBQGWSBeKgQyI+G1k/RsN9bdVV++N349+XxRG+tXW7kOAAAAAACAt4ewGwAAALgiy4tlffPyYGybZ42sdUpHAu8oyf6TnPJBNpf61U5dG6sLqlQqajabY+dYqli1uslJFbdzUqPzeiFyqRDqpz+4p+XFcrZh+OcV+re/fqbPvtrVo01f0vlV1Gnq5E0E07nQKJloQ54LjXKhN7ZfvdHU2uqKVhZL2jvMWsj3I+nxq1jVolE+NHIuq/heqKb64AoDfQAAAAAAALxd9O8DAAAArsjtjZoK+WBqe84/nT09ZI2UC3TS0rzfz2ZOr6+vT7XZttaoWvz2IW2lnNdf//n7p0H3G3Bw1NFnX+1K0lSAPUuauqwdezId3hcuMOD833z8XP/Hv/pS7z9ckzfSHt45qd522j5MtXOUtUDf3W9d4koAAAAAAABw3VHZDQAAAFwRz7P6xZ++q19+/LVa7f7JdmOMQj9rX+6cJCPZiQrjciknScrn83r48KG2t7fVap2Gs8W81WErufBajKRb6wvq9WN51mhzvaY7m0vyvTf7vOvjZ6eV7b2BUy44O/AexE5OUquXVbkHQXZvnDudUz6Pc071Tqq9RkOvdppaX87rqNmb2m+4AjNjVjoAAAAAAABuLsJuAAAA4ApVSnn97V9+qN39pn7122/UH8QnrxljNK+L9v07yyd/LxQKevDggY6OjvT8+XNJUj7MWnL3BrMT4DDwNMh6o2t1uaIP393QUq10RVd1cf1+dPL33sBp4YwlOOcUj+T3vcipH0mlwsVC6f1Gquj49iapU7ub6Kwjb68vXOi8AAAAAAAAuBkIuwEAAIArZozR2kpViwtFbe02zt3/Rx/dUaWUn9peLpdljJFzWcC9sWS1c5iq0z8NvI0xevf+qj56tKEoSmStVRB4U+f6rlTL2XWUC0ZrtctXkTtlwbV3RhV2mjrt1VM93xuvdK+3Blqpher2oqljPM/qw3fXL70eAAAAAAAAXF+E3QAAAMAbcv/28plh9/JiST/88I4WKoWZr/u+r8XFRR0cZK3BPWt0a9nTIHLqDpzyuVA/+N4j5cLsx/pc7s22KL+IR/eX9ZvPt7RW82TmlbGPMMoC7lFR7OSF08fu1RPV26laXacknX2+H390W0+e72trt3mybaGS15/84K5q1dn3GQAAAAAAADcTYTcAAADwhmysLej+nWU9fb4/9dqttQX92Y8fnBsIb2xsKEkS1ev1k21hYFRbKOnevXvy/ev1I32xEOoXP72n5uGrc/c1xijws7ndo+JEiuJUgT8e3lsr1dvzB3l71mhtuaJ7m4tqdfpqtvrK53wtLhRf72IAAAAAAABwrRk37IkIAAAA4I14tVPX0+f7anf6yucD3bu9pDsbixeqfB7q9/tqNBpyzqlcLqtYvL4BrnNOv/7NJxfetzeYrtQOfKNcMH5/Uuf0ydeRovHu5Sce3V/SX//swWusGAAAAAAAADcRYTcAAACAK/f4q6/VarUvtK9zTvlCScb6SuJExWJeqys1PX78lSZ/XWn3Un35Ip4Kx1eXSvqnf/VInpXSNJXv+5d6mAAAAAAAAAA3D2E3AAAAgCvXarX0+KsnM1+zNguh09QpDEOtrCxpZXl5Kpze29vXi5fT7dBTZyR/QYfNgTxr9OD2olaXctrd2VGzmc3q9n1fS0tLWl1dJfQGAAAAAAD4A0XYDQAAAOCNOKrX9fLlK0VRfLKtVCzq3r07CoJAzjlZa884g9RoNLWzu6d2uy1jjBYWqlpbW1Uhnz/Zp9fr6auvvlKaplPHLyws6O7du1d3UQAAAAAAALg2CLsBAAAAvDHOObVaLcVxonw+r0Ihf/5Bc84zr0L76dOnJxXds7zzzjvXesY5AAAAAAAAXo//thcAAAAA4A+XMUaVSuVKzjNLkiRnBt2SdHR0RNgNAAAAAADwB+jsnoEAAAAAcI3Nal3+OvsAAAAAAADg5iHsBgAAAHBj+b4v3z+7YVU+/3qt0wEAAAAAAHC9EXYDAAAAuLGMMVpaWpr7urVWi4uL3+GKAAAAAAAA8F0h7AYAAABwo62urqparU5tt9bq3r178jzvLawKAAAAAAAAb5pxzrm3vQgAAAAA+Lba7bbq9bqSJFGhUFCtVju3xTkAAAAAAABuLsJuAAAAAAAAAAAAAMCNQxtzAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCNQ9gNAAAAAAAAAAAAALhxCLsBAAAAAAAAAAAAADcOYTcAAAAAAAAAAAAA4MYh7AYAAAAAAAAAAAAA3DiE3QAAAAAAAAAAAACAG4ewGwAAAAAAAAAAAABw4xB2AwAAAAAAAAAAAABuHMJuAAAAAAAAAAAAAMCN8/8DvR3UyZamgoMAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# plot clones in space with the phylogeography\n", + "\n", + "fig = calicost.utils_plotting.plot_individual_spots_in_space(full_adj_coords, coords.clone_label, coords.tumor_proportion, base_width=10, base_height=5)\n", + "axes = plt.gca()\n", + "\n", + "# clone centers + ancestors\n", + "for node in t.traverse():\n", + " axes.scatter( node.x, -node.y, marker=\"D\", linewidth=2, edgecolor='black', facecolor=\"None\", s=50)\n", + "\n", + "# edges\n", + "for node in t.iter_leaves():\n", + " while not node.is_root():\n", + " p = node.up\n", + " if np.abs(node.x - p.x) + np.abs(node.y - p.y) > 1:\n", + " axes.annotate(\"\", xy=(node.x, -node.y), xytext=(p.x, -p.y), arrowprops=dict(mutation_scale=15, lw=1, arrowstyle=\"->\", color=\"black\"))\n", + " node = p\n", + " \n", + "axes.invert_yaxis()\n", + "fig.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30948782-8a89-4eee-8ce5-c244747c0ac9", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/notebooks/tutorials/simulated_data_tutorial.ipynb b/docs/notebooks/tutorials/simulated_data_tutorial.ipynb new file mode 100644 index 0000000..5b86caf --- /dev/null +++ b/docs/notebooks/tutorials/simulated_data_tutorial.ipynb @@ -0,0 +1,745 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a2a37765-769d-4571-9d15-1870f1d45903", + "metadata": {}, + "source": [ + "# Run CalicoST on a simulated data" + ] + }, + { + "cell_type": "markdown", + "id": "26467326-42cc-4d7f-8ffa-7e6cc371db3f", + "metadata": {}, + "source": [ + "## Download the data" + ] + }, + { + "cell_type": "markdown", + "id": "e527d832-c883-4bd8-a9d4-cc17873d3cd0", + "metadata": {}, + "source": [ + "We applied CalicoST on a small simulated data provided by [examples/simulated_example.tar.gz](https://github.com/raphael-group/CalicoST/blob/main/examples/simulated_example.tar.gz) from the github, which contains the following files/directories:\n", + "- simulated_example\n", + " - outs: simulated transcript count matrix and spatial coordinates\n", + " - snpinfo: parsed allele count matrix\n", + "\n", + "Untar the data by\n", + "```\n", + "tar -xzvf /examples/simulated_example.tar.gz\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "26cf31fe-425f-44bd-bcfb-7c26d9f8e54c", + "metadata": {}, + "source": [ + "## Run CalicoST to infer CNAs and cancer clones assuming spots are purely tumor or purely normal" + ] + }, + { + "cell_type": "markdown", + "id": "0cca3442-eee9-4a99-b5af-79076753195b", + "metadata": {}, + "source": [ + "To run CalicoST, we first copy `configuration_cna` file provided by CalicoST github to the example directory.\n", + "```\n", + "cd simulated_example\n", + "cp /configuration_cna ./\n", + "```\n", + "\n", + "Then we modify the following paths in the copied `configuration_cna` file:\n", + "- `spaceranger_dir` is path to the `outs` directory of the downloaded data.\n", + "- `snp_dir` is the path to the `snp_info` directory of the downloaded data.\n", + "- `output_dir` is the output directory for CalicoST to write the inferred clones and CNAs. It must be an existing directory.\n", + "\n", + "\n", + "We keep the default values for other parameters in `configuration_cna` file, while refer to this [parameter specification](https://calicost.readthedocs.io/en/latest/parameters.html) for more details if parameter tuning is needed for other samples.\n", + "\n", + "Now we use CalicoST to infer clones and allele-specific CNAs by running the following command in terminal\n", + "```\n", + "OMP_NUM_THREADS=1 python /src/calicost/calicost_main.py -c configuration_cna\n", + "```\n", + "\n", + "It takes about 2h to run on this simulated data. When finished, the CalicoST output directory will contain the following files:\n", + "- `/clone3_rectangle0_w1.0/clone_labels.tsv` store the inferred cancer clones;\n", + "- `/clone3_rectangle0_w1.0/cnv_seglevel.tsv` store the inferred allele-specific copy number profile per genomic segment;\n", + "- `/clone3_rectangle0_w1.0/cnv_genelevel.tsv` store the inferred allele-specific copy numbers projected to expressed genes;\n", + "- `/clone3_rectangle0_w1.0/cnv_diploid*`, `calicost/clone3_rectangle0_w1.0/cnv_triploid*`, `calicost/clone3_rectangle0_w1.0/cnv_tetraploid*` store an additional version of integer allele-specific copy numbers when enforcing the ploidy to be diploid, triploid, and tetraploid. Experienced users can decide which ploidy to use based on prior knowledge or based on the rdr-baf plots.\n", + "- `/clone3_rectangle0_w1.0/plots/` store the plots corresponding to the spatial organization of inferred cancer clones and allele-specific copy numbers along the genome for each clone." + ] + }, + { + "cell_type": "markdown", + "id": "70aad0dd-d0aa-4faf-81df-0e16322cd12c", + "metadata": {}, + "source": [ + "## Load the results of CalicoST" + ] + }, + { + "cell_type": "markdown", + "id": "fcb0e496-d9ca-4b13-a2fa-37cdd56fc10e", + "metadata": {}, + "source": [ + "Load the inferred cancer clones `/clone3_rectangle0_w1.0/clone_labels.tsv` by pandas." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f757e7f8-5946-48b6-b3da-089aa7b73f5f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
clone_label
BARCODES
spot_02
spot_12
spot_22
spot_32
spot_42
......
spot_17951
spot_17961
spot_17971
spot_17981
spot_17991
\n", + "

1800 rows × 1 columns

\n", + "
" + ], + "text/plain": [ + " clone_label\n", + "BARCODES \n", + "spot_0 2\n", + "spot_1 2\n", + "spot_2 2\n", + "spot_3 2\n", + "spot_4 2\n", + "... ...\n", + "spot_1795 1\n", + "spot_1796 1\n", + "spot_1797 1\n", + "spot_1798 1\n", + "spot_1799 1\n", + "\n", + "[1800 rows x 1 columns]" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "output_dir = \".\"\n", + "df_clones = pd.read_csv(f\"{output_dir}/clone3_rectangle0_w1.0/clone_labels.tsv\", header=0, index_col=0, sep='\\t')\n", + "df_clones" + ] + }, + { + "cell_type": "markdown", + "id": "18927baa", + "metadata": {}, + "source": [ + "Load the inferred allele-specific copy numbers for each genomic bin `/clone3_rectangle0_w1.0/cnv_seglevel.tsv`." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "72379207", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
STARTENDclone0 Aclone0 Bclone1 Aclone1 Bclone2 Aclone2 B
CHR
110011381616548111111
116352272384877111111
123917756101016111111
161850206653223111111
167854547780639111111
...........................
224352874445187923111111
224519033845828198111111
224605386946687116111111
224676261750199494111111
225020097950783663111111
\n", + "

1299 rows × 8 columns

\n", + "
" + ], + "text/plain": [ + " START END clone0 A clone0 B clone1 A clone1 B clone2 A \\\n", + "CHR \n", + "1 1001138 1616548 1 1 1 1 1 \n", + "1 1635227 2384877 1 1 1 1 1 \n", + "1 2391775 6101016 1 1 1 1 1 \n", + "1 6185020 6653223 1 1 1 1 1 \n", + "1 6785454 7780639 1 1 1 1 1 \n", + ".. ... ... ... ... ... ... ... \n", + "22 43528744 45187923 1 1 1 1 1 \n", + "22 45190338 45828198 1 1 1 1 1 \n", + "22 46053869 46687116 1 1 1 1 1 \n", + "22 46762617 50199494 1 1 1 1 1 \n", + "22 50200979 50783663 1 1 1 1 1 \n", + "\n", + " clone2 B \n", + "CHR \n", + "1 1 \n", + "1 1 \n", + "1 1 \n", + "1 1 \n", + "1 1 \n", + ".. ... \n", + "22 1 \n", + "22 1 \n", + "22 1 \n", + "22 1 \n", + "22 1 \n", + "\n", + "[1299 rows x 8 columns]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_cna = pd.read_csv(f\"{output_dir}/clone3_rectangle0_w1.0/cnv_seglevel.tsv\", header=0, index_col=0, sep='\\t')\n", + "df_cna" + ] + }, + { + "cell_type": "markdown", + "id": "565f6ddb", + "metadata": {}, + "source": [ + "Load the inferred allele-specific copy numbers for each gene `/clone3_rectangle0_w1.0/cnv_genelevel.tsv`." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7a1d1ff0-dca4-4c30-92c6-5a219846301a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
clone0 Aclone0 Bclone1 Aclone1 Bclone2 Aclone2 B
gene
ISG15111111
C1orf159111111
SDF4111111
UBE2J2111111
INTS11111111
.....................
CPT1B111111
CHKB111111
CHKB-DT111111
SHANK3111111
RABL2B111111
\n", + "

9000 rows × 6 columns

\n", + "
" + ], + "text/plain": [ + " clone0 A clone0 B clone1 A clone1 B clone2 A clone2 B\n", + "gene \n", + "ISG15 1 1 1 1 1 1\n", + "C1orf159 1 1 1 1 1 1\n", + "SDF4 1 1 1 1 1 1\n", + "UBE2J2 1 1 1 1 1 1\n", + "INTS11 1 1 1 1 1 1\n", + "... ... ... ... ... ... ...\n", + "CPT1B 1 1 1 1 1 1\n", + "CHKB 1 1 1 1 1 1\n", + "CHKB-DT 1 1 1 1 1 1\n", + "SHANK3 1 1 1 1 1 1\n", + "RABL2B 1 1 1 1 1 1\n", + "\n", + "[9000 rows x 6 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_cna = pd.read_csv(f\"{output_dir}/clone3_rectangle0_w1.0/cnv_genelevel.tsv\", header=0, index_col=0, sep='\\t')\n", + "df_cna" + ] + }, + { + "cell_type": "markdown", + "id": "1d9ed8e1-88f3-4b49-a75b-11a2fc2168e1", + "metadata": {}, + "source": [ + "The plots generated by CalicoST are in PDF format and can be directly viewed. Below, we load the PDF plots in this notebook for easy visualization.\n", + "\n", + "Firstly, `/clone3_rectangle0_w1.0/plots/clone_spatial.pdf` shows the inferred cancer clone in space. " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "1be9a3d1-2021-4b9b-bb13-4db1a17cb6c2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from wand.image import Image as WImage\n", + "img = WImage(filename=f\"{output_dir}/clone3_rectangle0_w1.0/plots/clone_spatial.pdf\", resolution=100)\n", + "img" + ] + }, + { + "cell_type": "markdown", + "id": "ef996ccb", + "metadata": {}, + "source": [ + "Secondly, `/clone3_rectangle0_w1.0/plots/acn_genome.pdf` shows the allele-specific copy numbers per clone along the genome. The color scheme follows" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "1ca3ec13-50bb-4276-bd30-d1c58366a13b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# allele-specific copy numbers of each clone (the color scheme is the same as Fig2c\n", + "img = WImage(filename=f\"{output_dir}/clone3_rectangle0_w1.0/plots/acn_genome.pdf\", resolution=120)\n", + "img" + ] + }, + { + "cell_type": "markdown", + "id": "5786d757", + "metadata": {}, + "source": [ + "Thirdly, `/clone3_rectangle0_w1.0/plots/rdr_baf_defaultcolor.pdf` shows RDR-BAF along the genome for each clone. Here, each color indicates a HMM state, while different colors may correspond to the same allele-specific copy numbers." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "28fc9487-b4f5-4e82-9c7f-ebf115078305", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# RDR-BAF plot along the genome for each clone\n", + "img = WImage(filename=f\"{output_dir}/clone3_rectangle0_w1.0/plots/rdr_baf_defaultcolor.pdf\", resolution=120)\n", + "img\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dcc3518a-a57e-4a96-9d21-44da42cb839d", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/parameters.rst b/docs/parameters.rst new file mode 100644 index 0000000..0669548 --- /dev/null +++ b/docs/parameters.rst @@ -0,0 +1,76 @@ +Specification of running parameters of CalicoST +=============================================== + +Supporting reference files +-------------------------- +geneticmap_file: str + The path to genetic map file. + +hgtable_file: str + The path to the location of genes in the genome. This file should be a tab-delimited file with the following columns: gene_name, chrom, cdsStart, cdsEnd. + +normalidx_file: str, optional + The path to the file containing the indices of normal spots in the spatial transcriptomics data. Each line is a single index without header. + +tumorprop_file: str, optional + The path to inferred tumor proportions per spot. This file should be a tab-delimited file with the following columns names: barcode, Tumor. + +filtergenelist_file: str, optional + The file to a list of genes to exclude from CNA inference, based on prior knowledge. + +filterregion_file: str, optional + The file to a list of genomic regions to exclude from CNA inference in BED format. E.g., HLA regions. + + +Phasing parameters +------------------ +logphase_shift: float, optional + Adjustment to the strength of Markov Model self-transition in phasing. The higher the value, the higher self-transition probability. Default is -2.0. + +secondary_min_umi: int, optional + The minimum UMI count a genome segment has in pseudobulk of spots in the step of genome segmentation. Default is 300. + + +Clone inference parameters +-------------------------- +n_clones: int + The number of clones to infer using only BAF signals. Default is 3. + +n_clones_rdr: int, optional + The number of clones to refine for each BAF-identified clone using RDR and BAF signals. Default is 2. + +min_spots_per_clone: int, optional + The minimum number of spots required to call a clone should have. Default is 100. + +min_avgumi_per_clone: int, optional + The minimum average UMI count required for a clone. Default is 10. + +nodepotential: str, optional + One of the following two options: "max" or "weighted_sum". "max" refers to using the MLE decoding of HMM in evaluating the probability of spots being in each clone. "weighted_sum" refers to using the full HMM posterior probabilities to evaluate the probability of spots being in each clone. Default is "weighted_sum". + +spatial_weight: float, optional + The strength of spatial coherence in HMRF. The higher the value, the stronger the spatial coherence. Default is 1.0. + + +CNA inference parameters +------------------------ +n_states: int + The number of allele-specific copy number states in the HMM for CNA inference. + +t: float, optional + The self-transition probability of HMM. The higher the value, the higher probability that adjacent genome segments are in the same CNA state. Default is 1-1e-5. + +max_iter: int, optional + The number of Baum-Welch steps to perform in HMM. Default is 30. + +tol: float, optional + The convergence threshold to terminate Baum-Welch steps. Default is 1e-4. + + +Merging clones with similar CNAs +-------------------------------- +np_threshold: float, optional + The threshold of Neyman Pearson statistics to decide two clones have distinct CNA events. The higher the value, the two clones are merged more easily. Default is 1.0. + +np_eventminlen: int, optional + The minimum number of consecutive genome segments to be considered as a CN event. Default is 10. diff --git a/docs/references.rst b/docs/references.rst new file mode 100644 index 0000000..e69de29 diff --git a/docs/tutorials.rst b/docs/tutorials.rst new file mode 100644 index 0000000..2720dc2 --- /dev/null +++ b/docs/tutorials.rst @@ -0,0 +1,11 @@ +.. toctree:: + :maxdepth: 0 + :caption: Contents: + + Allele-specific CNAs and cancer clones on a simulated data + --------------------------------------------------------- + notebooks/tutorials/simulated_data_tutorial.ipynb + + Cancer clones and phylogeography of a five-slice prostate cancer + ---------------------------------------------------------------- + notebooks/tutorials/prostate_tutorial.ipynb \ No newline at end of file diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..01058c9 --- /dev/null +++ b/environment.yml @@ -0,0 +1,12 @@ +name: calicost_env +channels: + - conda-forge + - bioconda + - defaults +dependencies: + - python==3.10 + - samtools==1.18 + - bcftools==1.18 + - cellsnp-lite + - snakemake + - lemon \ No newline at end of file diff --git a/examples/CalicoST_example.tar.gz b/examples/CalicoST_example.tar.gz new file mode 100644 index 0000000..2131300 Binary files /dev/null and b/examples/CalicoST_example.tar.gz differ diff --git a/examples/example_input_filelist b/examples/example_input_filelist new file mode 100644 index 0000000..aaf55d1 --- /dev/null +++ b/examples/example_input_filelist @@ -0,0 +1,5 @@ +/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_2_visium/outs/possorted_genome_bam.bam H12 /u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_2_visium/outs/ +/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_4_visium/outs/possorted_genome_bam.bam H14 /u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_4_visium/outs/ +/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_5_visium/outs/possorted_genome_bam.bam H15 /u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H1_5_visium/outs/ +/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H2_1_visium/outs/possorted_genome_bam.bam H21 /u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H2_1_visium/outs/ +/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H2_5_visium/outs/possorted_genome_bam.bam H25 /u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_spaceranger/P1_H2_5_visium/outs/ diff --git a/examples/prostate_example.tar.gz b/examples/prostate_example.tar.gz new file mode 100644 index 0000000..4217a8b Binary files /dev/null and b/examples/prostate_example.tar.gz differ diff --git a/examples/simulated_example.tar.gz b/examples/simulated_example.tar.gz new file mode 100644 index 0000000..bd79ef5 Binary files /dev/null and b/examples/simulated_example.tar.gz differ diff --git a/examples/tutorial.tar.gz b/examples/tutorial.tar.gz new file mode 100644 index 0000000..34445d8 Binary files /dev/null and b/examples/tutorial.tar.gz differ diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..15a4bce --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,61 @@ +[build-system] +requires = ["setuptools>=61.0"] +build-backend = "setuptools.build_meta" + +[project] +name = "CalicoST" +version = "1.0.0" +authors = [ + { name="Cong Ma", email="congma@princeton.edu" }, + { name="Metin Balaban", email="metin@princeton.edu" }, + { name="Jingxian Liu", email="jingxian.liu@wustl.edu" }, + { name="Siqi Chen", email="siqichen@wustl.edu" }, + { name="Li Ding", email="lding@wustl.edu" }, + { name="Ben Raphael", email="braphael@cs.princeton.edu" }, +] +description = "Inferring allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics" +readme = "README.md" +requires-python = ">=3.8" +classifiers = [ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: BSD License", + "Operating System :: OS Independent", +] +dependencies = [ + 'numpy', + 'scipy', + 'pandas', + 'scikit-learn', + 'scanpy', + 'anndata', + 'numba', + 'tqdm', + 'statsmodels', + 'networkx', + 'matplotlib', + 'seaborn', + 'pysam', + 'ete3' +] + +[project.optional-dependencies] +docs = [ + "ipython", + "ipywidgets>=8.0.0", + "sphinx>=5.3", + "sphinx-autodoc-annotation", + "sphinx-autodoc-typehints>=1.10.3", + "sphinx_rtd_theme", + "sphinxcontrib-bibtex>=2.3.0", + "sphinxcontrib-spelling>=7.6.2", + "nbsphinx>=0.8.1", + "myst-nb>=0.17.1", + "sphinx_copybutton>=0.5.0", +] + +[project.urls] +"Homepage" = "https://github.com/raphael-group/CalicoST" + +[tool.setuptools.packages.find] +where = ["src"] +include = ["calicost*"] \ No newline at end of file diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..6941a67 --- /dev/null +++ b/setup.py @@ -0,0 +1,33 @@ +import setuptools + +setuptools.setup( + name='calicost', + version='v1.0.0', + python_requires='>=3.8', + packages=['calicost'], + package_dir={'': 'src'}, + author='Cong Ma', + author_email='congma@princeton.edu', + description='Allele-specific CNAs and spatial cancer clone inference', + long_description='CalicoST infers allele-specific copy number aberrations and cancer clones in spatially resolved transcriptomics data', + url='https://github.com/raphael-group/CalicoST', + install_requires=[ + 'numpy', + 'scipy', + 'pandas', + 'scikit-learn', + 'scanpy', + 'anndata', + 'numba', + 'tqdm', + 'statsmodels', + 'networkx', + 'matplotlib', + 'seaborn', + 'pysam', + 'ete3', + 'ipykernel' + ], + include_package_data=True +) + diff --git a/src/calicost/__init__.py b/src/calicost/__init__.py new file mode 100644 index 0000000..4957a9c --- /dev/null +++ b/src/calicost/__init__.py @@ -0,0 +1 @@ +__version__ = 'v1.0.0' diff --git a/src/calicost/allele_starch_generateconfig.py b/src/calicost/allele_starch_generateconfig.py new file mode 100644 index 0000000..3444c14 --- /dev/null +++ b/src/calicost/allele_starch_generateconfig.py @@ -0,0 +1,241 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +import scanpy as sc +import anndata +import logging +import copy +from pathlib import Path +import subprocess +from hmm_NB_BB_phaseswitch import * +from utils_distribution_fitting import * +from hmrf import * +from utils_IO import * + + +def read_configuration_file(filename): + ##### [Default settings] ##### + config = { + "spaceranger_dir" : None, + "snp_dir" : None, + "output_dir" : None, + # supporting files and preprocessing arguments + "hgtable_file" : None, + "normalidx_file" : None, + "tumorprop_file" : None, + "supervision_clone_file" : None, + "filtergenelist_file" : None, + "filterregion_file" : None, + "binsize" : 1, + "rdrbinsize" : 1, + # "secondbinning_min_umi" : 500, + "max_nbins" : 1200, + "avg_umi_perbinspot" : 1.5, + "bafonly" : True, + # phase switch probability + "nu" : 1, + "logphase_shift" : 1, + "npart_phasing" : 2, + # HMRF configurations + "n_clones" : None, + "n_clones_rdr" : 2, + "min_spots_per_clone" : 100, + "min_avgumi_per_clone" : 10, + "maxspots_pooling" : 7, + "tumorprop_threshold" : 0.5, + "max_iter_outer" : 20, + "nodepotential" : "max", # max or weighted_sum + "initialization_method" : "rectangle", # rectangle or datadrive + "num_hmrf_initialization_start" : 0, + "num_hmrf_initialization_end" : 10, + "spatial_weight" : 2.0, + "construct_adjacency_method" : "hexagon", + "construct_adjacency_w" : 1.0, + # HMM configurations + "n_states" : None, + "params" : None, + "t" : None, + "t_phaseing" : 1-1e-4, + "fix_NB_dispersion" : False, + "shared_NB_dispersion" : True, + "fix_BB_dispersion" : False, + "shared_BB_dispersion" : True, + "max_iter" : 30, + "tol" : 1e-3, + "gmm_random_state" : 0, + "np_threshold" : 2.0, + "np_eventminlen" : 10 + } + + argument_type = { + "spaceranger_dir" : "str", + "snp_dir" : "str", + "output_dir" : "str", + # supporting files and preprocessing arguments + "hgtable_file" : "str", + "normalidx_file" : "str", + "tumorprop_file" : "str", + "supervision_clone_file" : "str", + "filtergenelist_file" : "str", + "filterregion_file" : "str", + "binsize" : "int", + "rdrbinsize" : "int", + # "secondbinning_min_umi" : "int", + "max_nbins" : "int", + "avg_umi_perbinspot" : "float", + "bafonly" : "bool", + # phase switch probability + "nu" : "float", + "logphase_shift" : "float", + "npart_phasing" : "int", + # HMRF configurations + "n_clones" : "int", + "n_clones_rdr" : "int", + "min_spots_per_clone" : "int", + "min_avgumi_per_clone" : "int", + "maxspots_pooling" : "int", + "tumorprop_threshold" : "float", + "max_iter_outer" : "int", + "nodepotential" : "str", + "initialization_method" : "str", + "num_hmrf_initialization_start" : "int", + "num_hmrf_initialization_end" : "int", + "spatial_weight" : "float", + "construct_adjacency_method" : "str", + "construct_adjacency_w" : "float", + # HMM configurations + "n_states" : "int", + "params" : "str", + "t" : "eval", + "t_phaseing" : "eval", + "fix_NB_dispersion" : "bool", + "shared_NB_dispersion" : "bool", + "fix_BB_dispersion" : "bool", + "shared_BB_dispersion" : "bool", + "max_iter" : "int", + "tol" : "float", + "gmm_random_state" : "int", + "np_threshold" : "float", + "np_eventminlen" : "int" + } + + ##### [ read configuration file to update settings ] ##### + with open(filename, 'r') as fp: + for line in fp: + if line.strip() == "" or line[0] == "#": + continue + # strs = [x.replace(" ", "") for x in line.strip().split(":") if x != ""] + strs = [x.strip() for x in line.strip().split(":") if x != ""] + assert strs[0] in config.keys(), f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}" + if strs[1].upper() == "NONE": + config[strs[0]] = None + elif argument_type[strs[0]] == "str": + config[strs[0]] = strs[1] + elif argument_type[strs[0]] == "int": + config[strs[0]] = int(strs[1]) + elif argument_type[strs[0]] == "float": + config[strs[0]] = float(strs[1]) + elif argument_type[strs[0]] == "eval": + config[strs[0]] = eval(strs[1]) + elif argument_type[strs[0]] == "bool": + config[strs[0]] = (strs[1].upper() == "TRUE") + elif argument_type[strs[0]] == "list_str": + config[strs[0]] = strs[1].split(" ") + # assertions + assert not config["spaceranger_dir"] is None, "No spaceranger directory!" + assert not config["snp_dir"] is None, "No SNP directory!" + assert not config["output_dir"] is None, "No output directory!" + + return config + + +def write_config_file(outputfilename, config): + list_argument_io = ["spaceranger_dir", + "snp_dir", + "output_dir"] + list_argument_sup = ["hgtable_file", + "normalidx_file", + "tumorprop_file", + "supervision_clone_file", + "filtergenelist_file", + "filterregion_file", + "binsize", + "rdrbinsize", + # "secondbinning_min_umi", + "max_nbins", + "avg_umi_perbinspot", + "bafonly"] + list_argument_phase = ["nu", + "logphase_shift", + "npart_phasing"] + list_argument_hmrf = ["n_clones", + "n_clones_rdr", + "min_spots_per_clone", + "min_avgumi_per_clone", + "maxspots_pooling", + "tumorprop_threshold", + "max_iter_outer", + "nodepotential", + "initialization_method", + "num_hmrf_initialization_start", + "num_hmrf_initialization_end", + "spatial_weight", + "construct_adjacency_method", + "construct_adjacency_w"] + list_argument_hmm = ["n_states", + "params", + "t", + "t_phaseing", + "fix_NB_dispersion", + "shared_NB_dispersion", + "fix_BB_dispersion", + "shared_BB_dispersion", + "max_iter", + "tol", + "gmm_random_state", + "np_threshold", + "np_eventminlen"] + with open(outputfilename, 'w') as fp: + # + for k in list_argument_io: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# supporting files and preprocessing arguments\n") + for k in list_argument_sup: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# phase switch probability\n") + for k in list_argument_phase: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# HMRF configurations\n") + for k in list_argument_hmrf: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# HMM configurations\n") + for k in list_argument_hmm: + fp.write(f"{k} : {config[k]}\n") + + +def main(argv): + template_configuration_file = argv[1] + outputdir = argv[2] + hmrf_seed_s = int(argv[3]) + hmrf_seed_t = int(argv[4]) + config = read_configuration_file(template_configuration_file) + for r in range(hmrf_seed_s, hmrf_seed_t): + config["num_hmrf_initialization_start"] = r + config["num_hmrf_initialization_end"] = r+1 + write_config_file(f"{outputdir}/configfile{r}", config) + + +if __name__ == "__main__": + if len(sys.argv) > 1: + main(sys.argv) \ No newline at end of file diff --git a/src/calicost/arg_parse.py b/src/calicost/arg_parse.py new file mode 100644 index 0000000..32f5570 --- /dev/null +++ b/src/calicost/arg_parse.py @@ -0,0 +1,268 @@ +import sys +import numpy as np +import scipy +import pandas as pd +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() + + +def load_default_config(): + config_joint = { + "input_filelist" : None, + "alignment_files" : [] + } + config_single = { + "spaceranger_dir" : None + } + config_shared = { + "snp_dir" : None, + "output_dir" : None, + # supporting files and preprocessing arguments + "geneticmap_file" : None, + "hgtable_file" : None, + "normalidx_file" : None, + "tumorprop_file" : None, + "supervision_clone_file" : None, + "filtergenelist_file" : None, + "filterregion_file" : None, + "secondary_min_umi" : 300, + "min_snpumi_perspot" : 50, + 'min_percent_expressed_spots' : 0.005, + "bafonly" : False, + # phase switch probability + "nu" : 1.0, + "logphase_shift" : -2.0, + "npart_phasing" : 3, + # HMRF configurations + "n_clones" : None, + "n_clones_rdr" : 2, + "min_spots_per_clone" : 100, + "min_avgumi_per_clone" : 10, + "maxspots_pooling" : 7, + "tumorprop_threshold" : 0.5, + "max_iter_outer" : 20, + "nodepotential" : "weighted_sum", # max or weighted_sum + "initialization_method" : "rectangle", # rectangle or datadrive + "num_hmrf_initialization_start" : 0, + "num_hmrf_initialization_end" : 10, + "spatial_weight" : 1.0, + "construct_adjacency_method" : "hexagon", + "construct_adjacency_w" : 1.0, + # HMM configurations + "n_states" : None, + "params" : "smp", + "t" : 1-1e-5, + "t_phaseing" : 1-1e-4, + "fix_NB_dispersion" : False, + "shared_NB_dispersion" : True, + "fix_BB_dispersion" : False, + "shared_BB_dispersion" : True, + "max_iter" : 30, + "tol" : 1e-4, + "gmm_random_state" : 0, + "np_threshold" : 1.0, + "np_eventminlen" : 10, + # integer copy number + "nonbalance_bafdist" : 1.0, + "nondiploid_rdrdist" : 10.0 + } + + argtype_joint = { + "input_filelist" : "str", + "alignment_files" : "list_str" + } + argtype_single = { + "spaceranger_dir" : "str" + } + argtype_shared = { + "snp_dir" : "str", + "output_dir" : "str", + # supporting files and preprocessing arguments + "geneticmap_file" : "str", + "hgtable_file" : "str", + "normalidx_file" : "str", + "tumorprop_file" : "str", + "supervision_clone_file" : "str", + "filtergenelist_file" : "str", + "filterregion_file" : "str", + "secondary_min_umi" : "int", + "min_snpumi_perspot" : "int", + 'min_percent_expressed_spots' : "float", + "bafonly" : "bool", + # phase switch probability + "nu" : "float", + "logphase_shift" : "float", + "npart_phasing" : "int", + # HMRF configurations + "n_clones" : "int", + "n_clones_rdr" : "int", + "min_spots_per_clone" : "int", + "min_avgumi_per_clone" : "int", + "maxspots_pooling" : "int", + "tumorprop_threshold" : "float", + "max_iter_outer" : "int", + "nodepotential" : "str", + "initialization_method" : "str", + "num_hmrf_initialization_start" : "int", + "num_hmrf_initialization_end" : "int", + "spatial_weight" : "float", + "construct_adjacency_method" : "str", + "construct_adjacency_w" : "float", + # HMM configurations + "n_states" : "int", + "params" : "str", + "t" : "eval", + "t_phaseing" : "eval", + "fix_NB_dispersion" : "bool", + "shared_NB_dispersion" : "bool", + "fix_BB_dispersion" : "bool", + "shared_BB_dispersion" : "bool", + "max_iter" : "int", + "tol" : "float", + "gmm_random_state" : "int", + "np_threshold" : "float", + "np_eventminlen" : "int", + # integer copy number + "nonbalance_bafdist" : "float", + "nondiploid_rdrdist" : "float" + } + + category_names = ["", "# supporting files and preprocessing arguments", "# phase switch probability", "# HMRF configurations", "# HMM configurations", "# integer copy number"] + category_elements = [["input_filelist", "spaceranger_dir", "snp_dir", "output_dir"], \ + ["geneticmap_file", "hgtable_file", "normalidx_file", "tumorprop_file", "alignment_files", "supervision_clone_file", "filtergenelist_file", "filterregion_file", "secondary_min_umi", "min_snpumi_perspot", "min_percent_expressed_spots", "bafonly"], \ + ["nu", "logphase_shift", "npart_phasing"], \ + ["n_clones", "n_clones_rdr", "min_spots_per_clone", "min_avgumi_per_clone", "maxspots_pooling", "tumorprop_threshold", "max_iter_outer", "nodepotential", "initialization_method", "num_hmrf_initialization_start", "num_hmrf_initialization_end", "spatial_weight", "construct_adjacency_method", "construct_adjacency_w"], \ + ["n_states", "params", "t", "t_phaseing", "fix_NB_dispersion", "shared_NB_dispersion", "fix_BB_dispersion", "shared_BB_dispersion", "max_iter", "tol", "gmm_random_state", "np_threshold", "np_eventminlen"], \ + ["nonbalance_bafdist", "nondiploid_rdrdist"]] + return config_shared, config_joint, config_single, argtype_shared, argtype_joint, argtype_single, category_names, category_elements + + +def read_configuration_file(filename): + ##### [Default settings] ##### + config_shared, config_joint, config_single, argtype_shared, argtype_joint, argtype_single, _, _ = load_default_config() + config = {**config_shared, **config_single} + argument_type = {**argtype_shared, **argtype_single} + + ##### [ read configuration file to update settings ] ##### + with open(filename, 'r') as fp: + for line in fp: + if line.strip() == "" or line[0] == "#": + continue + strs = [x.strip() for x in line.strip().split(":") if x != ""] + # assert strs[0] in config.keys(), f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}" + if (not strs[0] in config.keys()) and (not strs[0] in config_joint.keys()): + # warning that the argument is not a valid configuration parameter and continue + logger.warning(f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}") + continue + if len(strs) == 1: + config[strs[0]] = [] + elif strs[1].upper() == "NONE": + config[strs[0]] = None + elif argument_type[strs[0]] == "str": + config[strs[0]] = strs[1] + elif argument_type[strs[0]] == "int": + config[strs[0]] = int(strs[1]) + elif argument_type[strs[0]] == "float": + config[strs[0]] = float(strs[1]) + elif argument_type[strs[0]] == "eval": + config[strs[0]] = eval(strs[1]) + elif argument_type[strs[0]] == "bool": + config[strs[0]] = (strs[1].upper() == "TRUE") + elif argument_type[strs[0]] == "list_str": + config[strs[0]] = strs[1].split(" ") + # assertions + assert not config["spaceranger_dir"] is None, "No spaceranger directory!" + assert not config["snp_dir"] is None, "No SNP directory!" + assert not config["output_dir"] is None, "No output directory!" + + return config + + +def read_joint_configuration_file(filename): + ##### [Default settings] ##### + config_shared, config_joint, config_single, argtype_shared, argtype_joint, argtype_single, _, _ = load_default_config() + config = {**config_shared, **config_joint} + argument_type = {**argtype_shared, **argtype_joint} + + ##### [ read configuration file to update settings ] ##### + with open(filename, 'r') as fp: + for line in fp: + if line.strip() == "" or line[0] == "#": + continue + strs = [x.strip() for x in line.strip().split(":") if x != ""] + # assert strs[0] in config.keys(), f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}" + if (not strs[0] in config.keys()) and (not strs[0] in config_single.keys()): + # warning that the argument is not a valid configuration parameter and continue + logger.warning(f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}") + continue + if len(strs) == 1: + config[strs[0]] = [] + elif strs[1].upper() == "NONE": + config[strs[0]] = None + elif argument_type[strs[0]] == "str": + config[strs[0]] = strs[1] + elif argument_type[strs[0]] == "int": + config[strs[0]] = int(strs[1]) + elif argument_type[strs[0]] == "float": + config[strs[0]] = float(strs[1]) + elif argument_type[strs[0]] == "eval": + config[strs[0]] = eval(strs[1]) + elif argument_type[strs[0]] == "bool": + config[strs[0]] = (strs[1].upper() == "TRUE") + elif argument_type[strs[0]] == "list_str": + config[strs[0]] = strs[1].split(" ") + # assertions + assert not config["input_filelist"] is None, "No input file list!" + assert not config["snp_dir"] is None, "No SNP directory!" + assert not config["output_dir"] is None, "No output directory!" + + return config + + +def write_config_file(outputfilename, config): + _,_,_, argtype_shared, argtype_joint, argtype_single, category_names, category_elements = load_default_config() + argument_type = {**argtype_shared, **argtype_joint, **argtype_single} + with open(outputfilename, 'w') as fp: + for i in range(len(category_names)): + fp.write(f"{category_names[i]}\n") + for k in category_elements[i]: + if k in config: + if argument_type[k] == "list_str": + fp.write(f"{k} : {' '.join(config[k])}\n") + else: + fp.write(f"{k} : {config[k]}\n") + fp.write("\n") + + +def get_default_config_single(): + config_shared, config_joint, config_single, argtype_shared, argtype_joint, argtype_single, _, _ = load_default_config() + config = {**config_shared, **config_single} + return config + + +def get_default_config_joint(): + config_shared, config_joint, config_single, argtype_shared, argtype_joint, argtype_single, _, _ = load_default_config() + config = {**config_shared, **config_joint} + return config + + +def main(argv): + template_configuration_file = argv[1] + outputdir = argv[2] + hmrf_seed_s = int(argv[3]) + hmrf_seed_t = int(argv[4]) + try: + config = read_configuration_file(template_configuration_file) + except: + config = read_joint_configuration_file(template_configuration_file) + + for r in range(hmrf_seed_s, hmrf_seed_t): + config["num_hmrf_initialization_start"] = r + config["num_hmrf_initialization_end"] = r+1 + write_config_file(f"{outputdir}/configfile{r}", config) + + +if __name__ == "__main__": + if len(sys.argv) > 1: + main(sys.argv) diff --git a/src/calicost/calicost_main.py b/src/calicost/calicost_main.py new file mode 100644 index 0000000..8990bc8 --- /dev/null +++ b/src/calicost/calicost_main.py @@ -0,0 +1,444 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +from sklearn.cluster import KMeans +import scanpy as sc +import anndata +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() +import copy +from pathlib import Path +import functools +import subprocess +from calicost.arg_parse import * +from calicost.hmm_NB_BB_phaseswitch import * +from calicost.utils_distribution_fitting import * +from calicost.utils_hmrf import * +from calicost.hmrf import * +from calicost.phasing import * +from calicost.utils_IO import * +from calicost.find_integer_copynumber import * +from calicost.parse_input import * +from calicost.utils_plotting import * + + +def main(configuration_file): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + print("Configurations:") + for k in sorted(list(config.keys())): + print(f"\t{k} : {config[k]}") + + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_bininfo, df_gene_snp, \ + barcodes, coords, single_tumor_prop, sample_list, sample_ids, adjacency_mat, smooth_mat, exp_counts = run_parse_n_load(config) + + copy_single_X_rdr = copy.copy(single_X[:,0,:]) + copy_single_base_nb_mean = copy.copy(single_base_nb_mean) + single_X[:,0,:] = 0 + single_base_nb_mean[:,:] = 0 + + # run HMRF + for r_hmrf_initialization in range(config["num_hmrf_initialization_start"], config["num_hmrf_initialization_end"]): + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + if config["tumorprop_file"] is None: + initial_clone_index = rectangle_initialize_initial_clone(coords, config["n_clones"], random_state=r_hmrf_initialization) + else: + initial_clone_index = rectangle_initialize_initial_clone_mix(coords, config["n_clones"], single_tumor_prop, threshold=config["tumorprop_threshold"], random_state=r_hmrf_initialization) + + # create directory + p = subprocess.Popen(f"mkdir -p {outdir}", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) + out,err = p.communicate() + # save clone initialization into npz file + prefix = "allspots" + if not Path(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz").exists(): + initial_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz", **allres) + + # run HMRF + HMM + if config["tumorprop_file"] is None: + hmrf_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat, adjacency_mat=adjacency_mat, sample_ids=sample_ids, max_iter_outer=config["max_iter_outer"], nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"]) + else: + hmrfmix_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat, adjacency_mat=adjacency_mat, sample_ids=sample_ids, max_iter_outer=config["max_iter_outer"], nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"], tumorprop_threshold=config["tumorprop_threshold"]) + + # merge by thresholding BAF profile similarity + res = load_hmrf_last_iteration(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz") + n_obs = single_X.shape[0] + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"]))]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"]))], single_tumor_prop, threshold=config["tumorprop_threshold"]) + tumor_prop = np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) + merging_groups, merged_res = similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, threshold=config["np_threshold"], minlength=config["np_eventminlen"], params="sp", tumor_prop=tumor_prop, hmmclass=hmm_nophasing_v2) + print(f"BAF clone merging after comparing similarity: {merging_groups}") + # + if config["tumorprop_file"] is None: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD, min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs) + else: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD, min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs, single_tumor_prop=single_tumor_prop, threshold=config["tumorprop_threshold"]) + print(f"BAF clone merging after requiring minimum # spots: {merging_groups}") + n_baf_clones = len(merging_groups) + np.savez(f"{outdir}/mergedallspots_nstates{config['n_states']}_sp.npz", **merged_res) + + # adjust phasing + n_obs = single_X.shape[0] + merged_res = dict(np.load(f"{outdir}/mergedallspots_nstates{config['n_states']}_sp.npz", allow_pickle=True)) + merged_baf_assignment = copy.copy(merged_res["new_assignment"]) + n_baf_clones = len(np.unique(merged_baf_assignment)) + pred = np.argmax(merged_res["log_gamma"], axis=0) + pred = np.array([ pred[(c*n_obs):(c*n_obs+n_obs)] for c in range(n_baf_clones) ]) + merged_baf_profiles = np.array([ np.where(pred[c,:] < config["n_states"], merged_res["new_p_binom"][pred[c,:]%config["n_states"], 0], 1-merged_res["new_p_binom"][pred[c,:]%config["n_states"], 0]) \ + for c in range(n_baf_clones) ]) + + # adding RDR information + if not config["bafonly"]: + # select normal spots + if (config["normalidx_file"] is None) and (config["tumorprop_file"] is None): + EPS_BAF = 0.05 + PERCENT_NORMAL = 40 + vec_stds = np.std(np.log1p(copy_single_X_rdr @ smooth_mat), axis=0) + id_nearnormal_clone = np.argmin(np.sum( np.maximum(np.abs(merged_baf_profiles - 0.5)-EPS_BAF, 0), axis=1)) + while True: + stdthreshold = np.percentile(vec_stds[merged_res["new_assignment"] == id_nearnormal_clone], PERCENT_NORMAL) + normal_candidate = (vec_stds < stdthreshold) & (merged_res["new_assignment"] == id_nearnormal_clone) + if np.sum(copy_single_X_rdr[:, (normal_candidate==True)]) > single_X.shape[0] * 200 or PERCENT_NORMAL == 100: + break + PERCENT_NORMAL += 10 + pd.Series(barcodes[normal_candidate==True].index).to_csv(f"{outdir}/normal_candidate_barcodes.txt", header=False, index=False) + + elif (not config["normalidx_file"] is None): + # single_base_nb_mean has already been added in loading data step. + if not config["tumorprop_file"] is None: + logger.warning(f"Mixed sources of information for normal spots! Using {config['normalidx_file']}") + else: + for prop_threshold in np.arange(0.05, 0.6, 0.05): + normal_candidate = (single_tumor_prop < prop_threshold) + if np.sum(copy_single_X_rdr[:, (normal_candidate==True)]) > single_X.shape[0] * 200: + break + # filter bins based on normal + index_normal = np.where(normal_candidate)[0] + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_gene_snp = bin_selection_basedon_normal(df_gene_snp, \ + single_X, single_base_nb_mean, single_total_bb_RD, config['nu'], config['logphase_shift'], index_normal, config['geneticmap_file']) + assert df_bininfo.shape[0] == copy_single_X_rdr.shape[0] + df_bininfo = genesnp_to_bininfo(df_gene_snp) + copy_single_X_rdr = copy.copy(single_X[:,0,:]) + # filter out high-UMI DE genes, which may bias RDR estimates + copy_single_X_rdr, _ = filter_de_genes_tri(exp_counts, df_bininfo, normal_candidate, sample_list=sample_list, sample_ids=sample_ids) + MIN_NORMAL_COUNT_PERBIN = 20 + bidx_inconfident = np.where( np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) < MIN_NORMAL_COUNT_PERBIN )[0] + rdr_normal = np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) + rdr_normal[bidx_inconfident] = 0 + rdr_normal = rdr_normal / np.sum(rdr_normal) + copy_single_X_rdr[bidx_inconfident, :] = 0 # avoid ill-defined distributions if normal has 0 count in that bin. + copy_single_base_nb_mean = rdr_normal.reshape(-1,1) @ np.sum(copy_single_X_rdr, axis=0).reshape(1,-1) + + # adding back RDR signal + single_X[:,0,:] = copy_single_X_rdr + single_base_nb_mean = copy_single_base_nb_mean + n_obs = single_X.shape[0] + + # save binned data + np.savez(f"{outdir}/binned_data.npz", lengths=lengths, single_X=single_X, single_base_nb_mean=single_base_nb_mean, single_total_bb_RD=single_total_bb_RD, log_sitewise_transmat=log_sitewise_transmat, single_tumor_prop=(None if config["tumorprop_file"] is None else single_tumor_prop)) + + # run HMRF on each clone individually to further split BAF clone by RDR+BAF signal + for bafc in range(n_baf_clones): + prefix = f"clone{bafc}" + idx_spots = np.where(merged_baf_assignment == bafc)[0] + if np.sum(single_total_bb_RD[:, idx_spots]) < single_X.shape[0] * 20: # put a minimum B allele read count on pseudobulk to split clones + continue + # initialize clone + if config["tumorprop_file"] is None: + initial_clone_index = rectangle_initialize_initial_clone(coords[idx_spots], config['n_clones_rdr'], random_state=r_hmrf_initialization) + else: + initial_clone_index = rectangle_initialize_initial_clone_mix(coords[idx_spots], config['n_clones_rdr'], single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"], random_state=r_hmrf_initialization) + if not Path(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz").exists(): + initial_assignment = np.zeros(len(idx_spots), dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"barcodes":barcodes[idx_spots], "num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz", **allres) + + # HMRF + HMM using RDR information + copy_slice_sample_ids = copy.copy(sample_ids[idx_spots]) + if config["tumorprop_file"] is None: + hmrf_concatenate_pipeline(outdir, prefix, single_X[:,:,idx_spots], lengths, single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat[np.ix_(idx_spots,idx_spots)], adjacency_mat=adjacency_mat[np.ix_(idx_spots,idx_spots)], sample_ids=copy_slice_sample_ids, max_iter_outer=10, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"]) + else: + hmrfmix_concatenate_pipeline(outdir, prefix, single_X[:,:,idx_spots], lengths, single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], single_tumor_prop[idx_spots], initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat[np.ix_(idx_spots,idx_spots)], adjacency_mat=adjacency_mat[np.ix_(idx_spots,idx_spots)], sample_ids=copy_slice_sample_ids, max_iter_outer=10, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"], tumorprop_threshold=config["tumorprop_threshold"]) + + ##### combine results across clones ##### + res_combine = {"prev_assignment":np.zeros(single_X.shape[2], dtype=int)} + offset_clone = 0 + for bafc in range(n_baf_clones): + prefix = f"clone{bafc}" + allres = dict( np.load(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + r = allres["num_iterations"] - 1 + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + idx_spots = np.where(barcodes.isin( allres["barcodes"] ))[0] + if len(np.unique(res["new_assignment"])) == 1: + n_merged_clones = 1 + c = res["new_assignment"][0] + merged_res = copy.copy(res) + merged_res["new_assignment"] = np.zeros(len(idx_spots), dtype=int) + try: + log_gamma = res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)].reshape((2*config["n_states"], n_obs, 1)) + except: + log_gamma = res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)].reshape((config["n_states"], n_obs, 1)) + pred_cnv = res["pred_cnv"][ (c*n_obs):(c*n_obs+n_obs) ].reshape((-1,1)) + else: + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"])) ]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"])) ], single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"]) + tumor_prop = np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) + merging_groups, merged_res = similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, threshold=config["np_threshold"], minlength=config["np_eventminlen"], params="smp", tumor_prop=tumor_prop, hmmclass=hmm_nophasing_v2) + print(f"part {bafc} merging_groups: {merging_groups}") + # + if config["tumorprop_file"] is None: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD[:,idx_spots], min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs) + else: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD[:,idx_spots], min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs, single_tumor_prop=single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"]) + print(f"part {bafc} merging after requiring minimum # spots: {merging_groups}") + # compute posterior using the newly merged pseudobulk + n_merged_clones = len(merging_groups) + tmp = copy.copy(merged_res["new_assignment"]) + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)], single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"]) + # + merged_res = pipeline_baum_welch(None, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), np.tile(lengths, X.shape[2]), config["n_states"], \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) if not tumor_prop is None else None, \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, init_log_mu=res["new_log_mu"], init_p_binom=res["new_p_binom"], init_alphas=res["new_alphas"], init_taus=res["new_taus"], max_iter=config["max_iter"], tol=config["tol"], lambd=np.sum(base_nb_mean,axis=1)/np.sum(base_nb_mean), sample_length=np.ones(X.shape[2],dtype=int)*X.shape[0]) + merged_res["new_assignment"] = copy.copy(tmp) + merged_res = combine_similar_states_across_clones(X, base_nb_mean, total_bb_RD, merged_res, params="smp", tumor_prop=np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) if not tumor_prop is None else None, hmmclass=hmm_nophasing_v2, merge_threshold=0.1) + log_gamma = np.stack([ merged_res["log_gamma"][:,(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ], axis=-1) + pred_cnv = np.vstack([ merged_res["pred_cnv"][(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ]).T + # + # add to res_combine + if len(res_combine) == 1: + res_combine.update({"new_log_mu":np.hstack([ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":log_gamma, "pred_cnv":pred_cnv}) + else: + res_combine.update({"new_log_mu":np.hstack([res_combine["new_log_mu"]] + [ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([res_combine["new_alphas"]] + [ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([res_combine["new_p_binom"]] + [ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([res_combine["new_taus"]] + [ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":np.dstack([res_combine["log_gamma"], log_gamma ]), "pred_cnv":np.hstack([res_combine["pred_cnv"], pred_cnv])}) + res_combine["prev_assignment"][idx_spots] = merged_res["new_assignment"] + offset_clone + offset_clone += n_merged_clones + # temp: make dispersions the same across all clones + res_combine["new_alphas"][:,:] = np.max(res_combine["new_alphas"]) + res_combine["new_taus"][:,:] = np.min(res_combine["new_taus"]) + # end temp + n_final_clones = len(np.unique(res_combine["prev_assignment"])) + # per-sample weights across clones + log_persample_weights = np.zeros((n_final_clones, len(sample_list))) + for sidx in range(len(sample_list)): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res_combine["prev_assignment"][index], minlength=n_final_clones) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + # final re-assignment across all clones using estimated RDR + BAF + if config["tumorprop_file"] is None: + if config["nodepotential"] == "max": + pred = np.vstack([ np.argmax(res_combine["log_gamma"][:,:,c], axis=0) for c in range(res_combine["log_gamma"].shape[2]) ]).T + new_assignment, single_llf, total_llf, posterior = aggr_hmrf_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, res_combine, pred, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + elif config["nodepotential"] == "weighted_sum": + new_assignment, single_llf, total_llf, posterior = hmrf_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, res_combine, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + else: + if config["nodepotential"] == "max": + pred = np.vstack([ np.argmax(res_combine["log_gamma"][:,:,c], axis=0) for c in range(res_combine["log_gamma"].shape[2]) ]).T + new_assignment, single_llf, total_llf, posterior = aggr_hmrfmix_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res_combine, pred, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + elif config["nodepotential"] == "weighted_sum": + new_assignment, single_llf, total_llf, posterior = hmrfmix_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res_combine, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + res_combine["total_llf"] = total_llf + res_combine["new_assignment"] = new_assignment + # re-order clones such that normal clones are always clone 0 + res_combine, posterior = reorder_results(res_combine, posterior, single_tumor_prop) + # save results + np.savez(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", **res_combine) + np.save(f"{outdir}/posterior_clone_probability.npy", posterior) + + ##### infer integer copy ##### + res_combine = dict(np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True)) + final_clone_ids = np.sort(np.unique(res_combine["new_assignment"])) + nonempty_clone_ids = copy.copy(final_clone_ids) + # add clone 0 as normal clone if it doesn't appear in final_clone_ids + if not (0 in final_clone_ids): + final_clone_ids = np.append(0, final_clone_ids) + # chr position + medfix = ["", "_diploid", "_triploid", "_tetraploid"] + for o,max_medploidy in enumerate([None, 2, 3, 4]): + # A/B copy number per bin + allele_specific_copy = [] + # A/B copy number per state + state_cnv = [] + + df_genelevel_cnv = None + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==cid)[0] for cid in final_clone_ids]) + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==cid)[0] for cid in final_clone_ids], single_tumor_prop, threshold=config["tumorprop_threshold"]) + + for s, cid in enumerate(final_clone_ids): + if np.sum(base_nb_mean[:,s]) == 0: + continue + # adjust log_mu such that sum_bin lambda * np.exp(log_mu) = 1 + lambd = base_nb_mean[:,s] / np.sum(base_nb_mean[:,s]) + this_pred_cnv = res_combine["pred_cnv"][:,s] + adjusted_log_mu = np.log( np.exp(res_combine["new_log_mu"][:,s]) / np.sum(np.exp(res_combine["new_log_mu"][this_pred_cnv,s]) * lambd) ) + if not max_medploidy is None: + best_integer_copies, _ = hill_climbing_integer_copynumber_oneclone(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, max_medploidy=max_medploidy) + else: + try: + best_integer_copies, _ = hill_climbing_integer_copynumber_fixdiploid(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, nonbalance_bafdist=config["nonbalance_bafdist"], nondiploid_rdrdist=config["nondiploid_rdrdist"]) + except: + try: + best_integer_copies, _ = hill_climbing_integer_copynumber_fixdiploid(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, nonbalance_bafdist=config["nonbalance_bafdist"], nondiploid_rdrdist=config["nondiploid_rdrdist"], min_prop_threshold=0.02) + except: + finding_distate_failed = True + continue + + print(f"max med ploidy = {max_medploidy}, clone {s}, integer copy inference loss = {_}") + # + allele_specific_copy.append( pd.DataFrame( best_integer_copies[res_combine["pred_cnv"][:,s], 0].reshape(1,-1), index=[f"clone{cid} A"], columns=np.arange(n_obs) ) ) + allele_specific_copy.append( pd.DataFrame( best_integer_copies[res_combine["pred_cnv"][:,s], 1].reshape(1,-1), index=[f"clone{cid} B"], columns=np.arange(n_obs) ) ) + # + state_cnv.append( pd.DataFrame( res_combine["new_log_mu"][:,s].reshape(-1,1), columns=[f"clone{cid} logmu"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( res_combine["new_p_binom"][:,s].reshape(-1,1), columns=[f"clone{cid} p"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( best_integer_copies[:,0].reshape(-1,1), columns=[f"clone{cid} A"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( best_integer_copies[:,1].reshape(-1,1), columns=[f"clone{cid} B"], index=np.arange(config['n_states']) ) ) + # + # tmpdf = get_genelevel_cnv_oneclone(best_integer_copies[res_combine["pred_cnv"][:,s], 0], best_integer_copies[res_combine["pred_cnv"][:,s], 1], x_gene_list) + # tmpdf.columns = [f"clone{s} A", f"clone{s} B"] + bin_Acopy_mappers = {i:x for i,x in enumerate(best_integer_copies[res_combine["pred_cnv"][:,s], 0])} + bin_Bcopy_mappers = {i:x for i,x in enumerate(best_integer_copies[res_combine["pred_cnv"][:,s], 1])} + tmpdf = pd.DataFrame({"gene":df_gene_snp[df_gene_snp.is_interval].gene, f"clone{s} A":df_gene_snp[df_gene_snp.is_interval]['bin_id'].map(bin_Acopy_mappers), \ + f"clone{s} B":df_gene_snp[df_gene_snp.is_interval]['bin_id'].map(bin_Bcopy_mappers)}).set_index('gene') + if df_genelevel_cnv is None: + df_genelevel_cnv = copy.copy( tmpdf[~tmpdf[f"clone{s} A"].isnull()].astype(int) ) + else: + df_genelevel_cnv = df_genelevel_cnv.join( tmpdf[~tmpdf[f"clone{s} A"].isnull()].astype(int) ) + if len(state_cnv) == 0: + continue + # output gene-level copy number + df_genelevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_genelevel.tsv", header=True, index=True, sep="\t") + # output segment-level copy number + allele_specific_copy = pd.concat(allele_specific_copy) + df_seglevel_cnv = pd.DataFrame({"CHR":df_bininfo.CHR.values, "START":df_bininfo.START.values, "END":df_bininfo.END.values }) + df_seglevel_cnv = df_seglevel_cnv.join( allele_specific_copy.T ) + df_seglevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_seglevel.tsv", header=True, index=False, sep="\t") + # output per-state copy number + state_cnv = functools.reduce(lambda left,right: pd.merge(left,right, left_index=True, right_index=True, how='inner'), state_cnv) + state_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_perstate.tsv", header=True, index=False, sep="\t") + # # + # # posterior using integer-copy numbers + # log_persample_weights = np.zeros((len(nonempty_clone_ids), len(sample_list))) + # for sidx in range(len(sample_list)): + # index = np.where(sample_ids == sidx)[0] + # this_persample_weight = np.array([ np.sum(res_combine["new_assignment"][index] == cid) for cid in nonempty_clone_ids]) / len(index) + # log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + # log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + # pred = np.vstack([ np.argmax(res_combine["log_gamma"][:,:,cid], axis=0) for cid in nonempty_clone_ids ]).T + # df_posterior = clonelabel_posterior_withinteger(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, state_cnv, res_combine, pred, \ + # smooth_mat, adjacency_mat, res_combine["new_assignment"], sample_ids, base_nb_mean, log_persample_weights, config["spatial_weight"], hmmclass=hmm_nophasing_v2) + # df_posterior.to_pickle(f"{outdir}/posterior{medfix[o]}.pkl") + + ##### output clone label ##### + df_clone_label = pd.DataFrame({"clone_label":res_combine["new_assignment"]}, index=barcodes) + if not config["tumorprop_file"] is None: + df_clone_label["tumor_proportion"] = single_tumor_prop + df_clone_label.to_csv(f"{outdir}/clone_labels.tsv", header=True, index=True, sep="\t") + + ##### plotting ##### + # make a directory for plots + p = subprocess.Popen(f"mkdir -p {outdir}/plots", shell=True) + out, err = p.communicate() + + # plot RDR and BAF + cn_file = f"{outdir}/cnv_diploid_seglevel.tsv" + fig = plot_rdr_baf(configuration_file, r_hmrf_initialization, cn_file, clone_ids=None, remove_xticks=True, rdr_ylim=5, chrtext_shift=-0.3, base_height=3.2, pointsize=30, palette="tab10") + fig.savefig(f"{outdir}/plots/rdr_baf_defaultcolor.pdf", transparent=True, bbox_inches="tight") + # plot allele-specific copy number + for o,max_medploidy in enumerate([None, 2, 3, 4]): + cn_file = f"{outdir}/cnv{medfix[o]}_seglevel.tsv" + if not Path(cn_file).exists(): + continue + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + df_cnv = expand_df_cnv(df_cnv) + df_cnv = df_cnv[~df_cnv.iloc[:,-1].isnull()] + fig, axes = plt.subplots(1, 1, figsize=(15, 0.9*len(final_clone_ids) + 0.6), dpi=200, facecolor="white") + axes = plot_acn_from_df_anotherscheme(df_cnv, axes, chrbar_pos='top', chrbar_thickness=0.3, add_legend=False, remove_xticks=True) + fig.tight_layout() + fig.savefig(f"{outdir}/plots/acn_genome{medfix[o]}.pdf", transparent=True, bbox_inches="tight") + # additionally plot the allele-specific copy number per region + if not config["supervision_clone_file"] is None: + fig, axes = plt.subplots(1, 1, figsize=(15, 0.6*len(unique_clone_ids) + 0.4), dpi=200, facecolor="white") + merged_df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + df_cnv = merged_df_cnv[["CHR", "START", "END"]] + df_cnv = df_cnv.join( pd.DataFrame({f"clone{x} A":merged_df_cnv[f"clone{res_combine['new_assignment'][i]} A"] for i,x in enumerate(unique_clone_ids)}) ) + df_cnv = df_cnv.join( pd.DataFrame({f"clone{x} B":merged_df_cnv[f"clone{res_combine['new_assignment'][i]} B"] for i,x in enumerate(unique_clone_ids)}) ) + df_cnv = expand_df_cnv(df_cnv) + clone_ids = np.concatenate([ unique_clone_ids[res_combine["new_assignment"]==c].astype(str) for c in final_clone_ids ]) + axes = plot_acn_from_df(df_cnv, axes, clone_ids=clone_ids, clone_names=[f"region {x}" for x in clone_ids], add_chrbar=True, add_arrow=False, chrbar_thickness=0.4/(0.6*len(unique_clone_ids) + 0.4), add_legend=True, remove_xticks=True) + fig.tight_layout() + fig.savefig(f"{outdir}/plots/acn_genome{medfix[o]}_per_region.pdf", transparent=True, bbox_inches="tight") + # plot clones in space + if not config["supervision_clone_file"] is None: + before_assignments = pd.Series([None] * before_coords.shape[0]) + for i,c in enumerate(unique_clone_ids): + before_assignments.iloc[before_df_clones.clone_id.isin([c])] = f"clone {res_combine['new_assignment'][i]}" + fig = plot_clones_in_space(before_coords, before_assignments, sample_list, before_sample_ids, palette="Set2", labels=unique_clone_ids, label_coords=coords, label_sample_ids=sample_ids) + fig.savefig(f"{outdir}/plots/clone_spatial.pdf", transparent=True, bbox_inches="tight") + else: + assignment = pd.Series([f"clone {x}" for x in res_combine["new_assignment"]]) + fig = plot_individual_spots_in_space(coords, assignment, single_tumor_prop, sample_list=sample_list, sample_ids=sample_ids) + fig.savefig(f"{outdir}/plots/clone_spatial.pdf", transparent=True, bbox_inches="tight") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--configfile", help="configuration file of CalicoST", required=True, type=str) + args = parser.parse_args() + + main(args.configfile) \ No newline at end of file diff --git a/src/calicost/calicost_supervised.py b/src/calicost/calicost_supervised.py new file mode 100644 index 0000000..d872cae --- /dev/null +++ b/src/calicost/calicost_supervised.py @@ -0,0 +1,493 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +from sklearn.cluster import KMeans +import scanpy as sc +import anndata +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() +import copy +from pathlib import Path +import functools +import subprocess +from arg_parse import * +from hmm_NB_BB_phaseswitch import * +from utils_distribution_fitting import * +from utils_hmrf import * +from hmrf import * +from phasing import * +from utils_IO import * +from find_integer_copynumber import * +from parse_input import * +from utils_plotting import * + +from matplotlib import pyplot as plt +from matplotlib.lines import Line2D +import matplotlib.patches as mpatches +import seaborn +plt.rcParams.update({'font.size': 14}) + +import mkl +mkl.set_num_threads(1) + + +def main(configuration_file): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + print("Configurations:") + for k in sorted(list(config.keys())): + print(f"\t{k} : {config[k]}") + + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_bininfo, x_gene_list, \ + barcodes, coords, single_tumor_prop, sample_list, sample_ids, adjacency_mat, smooth_mat, exp_counts = run_parse_n_load(config) + + # normal baseline expression if tumorprop_file is provided + if not config["tumorprop_file"] is None: + EXPECTED_NORMAL_PROP = 0.05 + q = np.sort(single_tumor_prop)[ int(EXPECTED_NORMAL_PROP * len(barcodes)) ] + normal_candidate = ( single_tumor_prop <= q ) + + # copy_single_X_rdr,_ = filter_de_genes(exp_counts, x_gene_list, normal_candidate, sample_list=sample_list, sample_ids=sample_ids) + copy_single_X_rdr, _ = filter_de_genes_tri(exp_counts, x_gene_list, normal_candidate, sample_list=sample_list, sample_ids=sample_ids) + MIN_NORMAL_COUNT_PERBIN = 20 + bidx_inconfident = np.where( np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) < MIN_NORMAL_COUNT_PERBIN )[0] + rdr_normal = np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) + rdr_normal[bidx_inconfident] = 0 + rdr_normal = rdr_normal / np.sum(rdr_normal) + copy_single_X_rdr[bidx_inconfident, :] = 0 # avoid ill-defined distributions if normal has 0 count in that bin. + copy_single_base_nb_mean = rdr_normal.reshape(-1,1) @ np.sum(copy_single_X_rdr, axis=0).reshape(1,-1) + # adding back RDR signal + single_X[:,0,:] = copy_single_X_rdr + single_base_nb_mean = copy_single_base_nb_mean + + # make each cluster in supervision_clone_file a pseudospot + if not config["supervision_clone_file"] is None: + tmp_df_clones = pd.read_csv(config["supervision_clone_file"], header=0, index_col=0, sep="\t") + df_clones = pd.DataFrame({"barcodes":barcodes.values}, index=barcodes.values).join(tmp_df_clones) + df_clones.columns = ["barcodes", "clone_id"] + + unique_clone_ids = np.unique( df_clones["clone_id"][~df_clones["clone_id"].isnull()].values ) + clone_index = [np.where(df_clones["clone_id"] == c)[0] for c in unique_clone_ids] + if config["tumorprop_file"] is None: + single_X, single_base_nb_mean, single_total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + single_tumor_prop = None + else: + single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop, threshold=config["tumorprop_threshold"]) + before_coords = copy.copy(coords) + before_df_clones = copy.copy(df_clones) + before_sample_ids = copy.copy(sample_ids) + coords = np.array([ np.mean(coords[idx,:],axis=0) for idx in clone_index ]) + smooth_mat = scipy.sparse.csr_matrix(np.eye(coords.shape[0])) + adjacency_mat = scipy.sparse.csr_matrix(np.eye(coords.shape[0])) + barcodes = pd.Series(unique_clone_ids) + sample_ids = np.array([sample_ids[idx][0] for idx in clone_index]) + + # clear values in RDR to first infer clones using BAF signal only + copy_single_X_rdr = copy.copy(single_X[:,0,:]) + copy_single_base_nb_mean = copy.copy(single_base_nb_mean) + single_X[:,0,:] = 0 + single_base_nb_mean[:,:] = 0 + + # run HMRF + for r_hmrf_initialization in range(config["num_hmrf_initialization_start"], config["num_hmrf_initialization_end"]): + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + if config["initialization_method"] == "rectangle": + if config["tumorprop_file"] is None: + initial_clone_index = rectangle_initialize_initial_clone(coords, min(coords.shape[0],config["n_clones"]), random_state=r_hmrf_initialization) + else: + initial_clone_index = rectangle_initialize_initial_clone_mix(coords, min(coords.shape[0],config["n_clones"]), single_tumor_prop, threshold=config["tumorprop_threshold"], random_state=r_hmrf_initialization) + else: + kmeans = KMeans(n_clusters = config["n_clones"], max_iter=1, init="random", random_state=config["num_hmrf_initialization_start"]).fit(coords) + initial_clone_index = [np.where(kmeans.labels_ == i)[0] for i in range(config["n_clones"])] + + # create directory + p = subprocess.Popen(f"mkdir -p {outdir}", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) + out,err = p.communicate() + # save clone initialization into npz file + prefix = "allspots" + if not Path(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz").exists(): + initial_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz", **allres) + + # run HMRF + HMM + if config["tumorprop_file"] is None: + hmrf_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat, adjacency_mat=adjacency_mat, sample_ids=sample_ids, max_iter_outer=config["max_iter_outer"], nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"]) + else: + hmrfmix_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat, adjacency_mat=adjacency_mat, sample_ids=sample_ids, max_iter_outer=config["max_iter_outer"], nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"], tumorprop_threshold=config["tumorprop_threshold"]) + + # merge by thresholding BAF profile similarity + res = load_hmrf_last_iteration(f"{outdir}/{prefix}_nstates{config['n_states']}_sp.npz") + n_obs = single_X.shape[0] + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"]))]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res["new_assignment"]==c)[0] for c in np.sort(np.unique(res["new_assignment"]))], single_tumor_prop, threshold=config["tumorprop_threshold"]) + tumor_prop = np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) + merging_groups, merged_res = similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, threshold=config["np_threshold"], minlength=config["np_eventminlen"], params="sp", tumor_prop=tumor_prop, hmmclass=hmm_nophasing_v2) + print(f"BAF clone merging after comparing similarity: {merging_groups}") + # + if config["tumorprop_file"] is None: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD, min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs) + else: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD, min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs, single_tumor_prop=single_tumor_prop) + print(f"BAF clone merging after requiring minimum # spots: {merging_groups}") + n_baf_clones = len(merging_groups) + np.savez(f"{outdir}/mergedallspots_nstates{config['n_states']}_sp.npz", **merged_res) + + # adjust phasing + n_obs = single_X.shape[0] + merged_res = dict(np.load(f"{outdir}/mergedallspots_nstates{config['n_states']}_sp.npz", allow_pickle=True)) + merged_baf_assignment = copy.copy(merged_res["new_assignment"]) + n_baf_clones = len(np.unique(merged_baf_assignment)) + pred = np.argmax(merged_res["log_gamma"], axis=0) + pred = np.array([ pred[(c*n_obs):(c*n_obs+n_obs)] for c in range(n_baf_clones) ]) + merged_baf_profiles = np.array([ np.where(pred[c,:] < config["n_states"], merged_res["new_p_binom"][pred[c,:]%config["n_states"], 0], 1-merged_res["new_p_binom"][pred[c,:]%config["n_states"], 0]) \ + for c in range(n_baf_clones) ]) + # EPS_BAF = 0.05 + # merged_baf_profiles[np.abs(merged_baf_profiles - 0.5) < EPS_BAF] = 0.5 + # population_baf = np.mean(merged_baf_profiles[merged_res["new_assignment"], :], axis=0) if config["tumorprop_file"] is None else np.mean(merged_baf_profiles[merged_res["new_assignment"][single_tumor_prop > config["tumorprop_threshold"]], :], axis=0) + # single_X[(population_baf > 0.5), 1, :] = single_total_bb_RD[(population_baf > 0.5), :] - single_X[(population_baf > 0.5), 1, :] + + # adding RDR information + if not config["bafonly"]: + # select normal spots + if (config["normalidx_file"] is None) and (config["tumorprop_file"] is None): + EPS_BAF = 0.05 + PERCENT_NORMAL = 40 + vec_stds = np.std(np.log1p(copy_single_X_rdr), axis=0) # TBD: whether to smooth by multiplying smooth_mat + id_nearnormal_clone = np.argmin(np.sum( np.maximum(np.abs(merged_baf_profiles - 0.5)-EPS_BAF, 0), axis=1)) + while True: + stdthreshold = np.percentile(vec_stds[merged_res["new_assignment"] == id_nearnormal_clone], PERCENT_NORMAL) + normal_candidate = (vec_stds < stdthreshold) & (merged_res["new_assignment"] == id_nearnormal_clone) + if np.sum(copy_single_X_rdr[:, (normal_candidate==True)]) > single_X.shape[0] * 200 or PERCENT_NORMAL == 100: + break + PERCENT_NORMAL += 10 + # copy_single_X_rdr, _ = filter_de_genes(exp_counts, x_gene_list, normal_candidate) + copy_single_X_rdr, _ = filter_de_genes_tri(exp_counts, x_gene_list, normal_candidate, sample_list=sample_list, sample_ids=sample_ids) + MIN_NORMAL_COUNT_PERBIN = 20 + bidx_inconfident = np.where( np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) < MIN_NORMAL_COUNT_PERBIN )[0] + rdr_normal = np.sum(copy_single_X_rdr[:, (normal_candidate==True)], axis=1) + rdr_normal[bidx_inconfident] = 0 + rdr_normal = rdr_normal / np.sum(rdr_normal) + copy_single_X_rdr[bidx_inconfident, :] = 0 # avoid ill-defined distributions if normal has 0 count in that bin. + copy_single_base_nb_mean = rdr_normal.reshape(-1,1) @ np.sum(copy_single_X_rdr, axis=0).reshape(1,-1) + pd.Series(barcodes[normal_candidate==True].index).to_csv(f"{outdir}/normal_candidate_barcodes.txt", header=False, index=False) + # + index_normal = np.where(normal_candidate)[0] + sorted_chr_pos = list(zip(df_bininfo.CHR.values, df_bininfo.START.values)) + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, sorted_chr_pos, _, x_gene_list, index_remaining = bin_selection_basedon_normal(single_X, \ + single_base_nb_mean, single_total_bb_RD, sorted_chr_pos, sorted_chr_pos, x_gene_list, config["nu"], config["logphase_shift"], index_normal) + assert df_bininfo.shape[0] == copy_single_X_rdr.shape[0] + df_bininfo = df_bininfo.iloc[index_remaining, :] + copy_single_X_rdr = copy_single_X_rdr[index_remaining, :] + copy_single_base_nb_mean = copy_single_base_nb_mean[index_remaining, :] + + elif (not config["normalidx_file"] is None): + # single_base_nb_mean has already been added in loading data step. + if not config["tumorprop_file"] is None: + logger.warning(f"Mixed sources of information for normal spots! Using {config['normalidx_file']}") + + # adding back RDR signal + single_X[:,0,:] = copy_single_X_rdr + single_base_nb_mean = copy_single_base_nb_mean + n_obs = single_X.shape[0] + + # save binned data + np.savez(f"{outdir}/binned_data.npz", lengths=lengths, single_X=single_X, single_base_nb_mean=single_base_nb_mean, single_total_bb_RD=single_total_bb_RD, log_sitewise_transmat=log_sitewise_transmat, single_tumor_prop=(None if config["tumorprop_file"] is None else single_tumor_prop)) + + # run HMRF on each clone individually to further split BAF clone by RDR+BAF signal + for bafc in range(n_baf_clones): + prefix = f"clone{bafc}" + idx_spots = np.where(merged_baf_assignment == bafc)[0] + if np.sum(single_total_bb_RD[:, idx_spots]) < single_X.shape[0] * 20: # put a minimum B allele read count on pseudobulk to split clones + continue + # initialize clone + if config["tumorprop_file"] is None: + initial_clone_index = rectangle_initialize_initial_clone(coords[idx_spots], min(len(idx_spots),config['n_clones_rdr']), random_state=r_hmrf_initialization) + else: + initial_clone_index = rectangle_initialize_initial_clone_mix(coords[idx_spots], min(len(idx_spots),config['n_clones_rdr']), single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"], random_state=r_hmrf_initialization) + if not Path(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz").exists(): + initial_assignment = np.zeros(len(idx_spots), dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"barcodes":barcodes[idx_spots], "num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz", **allres) + + # HMRF + HMM using RDR information + copy_slice_sample_ids = copy.copy(sample_ids[idx_spots]) + if config["tumorprop_file"] is None: + hmrf_concatenate_pipeline(outdir, prefix, single_X[:,:,idx_spots], lengths, single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat[np.ix_(idx_spots,idx_spots)], adjacency_mat=adjacency_mat[np.ix_(idx_spots,idx_spots)], sample_ids=copy_slice_sample_ids, max_iter_outer=10, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"]) + else: + hmrfmix_concatenate_pipeline(outdir, prefix, single_X[:,:,idx_spots], lengths, single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], single_tumor_prop[idx_spots], initial_clone_index, n_states=config["n_states"], \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat[np.ix_(idx_spots,idx_spots)], adjacency_mat=adjacency_mat[np.ix_(idx_spots,idx_spots)], sample_ids=copy_slice_sample_ids, max_iter_outer=10, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=config["max_iter"], tol=config["tol"], spatial_weight=config["spatial_weight"], tumorprop_threshold=config["tumorprop_threshold"]) + + ##### combine results across clones ##### + res_combine = {"prev_assignment":-1 * np.ones(single_X.shape[2], dtype=int)} + offset_clone = 0 + for bafc in range(n_baf_clones): + prefix = f"clone{bafc}" + if not Path(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz").exists(): + # we skipped the BAF clone in the previous step because of low SNP-covering UMI conuts. + continue + allres = dict( np.load(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + r = allres["num_iterations"] - 1 + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + idx_spots = np.where(barcodes.isin( allres["barcodes"] ))[0] + if len(np.unique(res["new_assignment"])) == 1: + n_merged_clones = 1 + c = res["new_assignment"][0] + merged_res = copy.copy(res) + merged_res["new_assignment"] = np.zeros(len(idx_spots), dtype=int) + try: + log_gamma = res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)].reshape((2*config["n_states"], n_obs, 1)) + except: + log_gamma = res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)].reshape((config["n_states"], n_obs, 1)) + pred_cnv = res["pred_cnv"][ (c*n_obs):(c*n_obs+n_obs) ].reshape((-1,1)) + else: + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in range(config['n_clones_rdr'])]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in range(config['n_clones_rdr'])], single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"]) + tumor_prop = np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) + merging_groups, merged_res = similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, threshold=config["np_threshold"], minlength=config["np_eventminlen"], params="smp", tumor_prop=tumor_prop, hmmclass=hmm_nophasing_v2) + print(f"part {bafc} merging_groups: {merging_groups}") + # + if config["tumorprop_file"] is None: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD[:,idx_spots], min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs) + else: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], merged_res, single_total_bb_RD[:,idx_spots], min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*n_obs, single_tumor_prop=single_tumor_prop[idx_spots]) + # compute posterior using the newly merged pseudobulk + n_merged_clones = len(merging_groups) + tmp = copy.copy(merged_res["new_assignment"]) + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)], single_tumor_prop[idx_spots], threshold=config["tumorprop_threshold"]) + # + merged_res = pipeline_baum_welch(None, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), np.tile(lengths, X.shape[2]), config["n_states"], \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) if not tumor_prop is None else None, \ + hmmclass=hmm_nophasing_v2, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, init_log_mu=res["new_log_mu"], init_p_binom=res["new_p_binom"], init_alphas=res["new_alphas"], init_taus=res["new_taus"], max_iter=config["max_iter"], tol=config["tol"], lambd=np.sum(base_nb_mean,axis=1)/np.sum(base_nb_mean), sample_length=np.ones(X.shape[2],dtype=int)*X.shape[0]) + merged_res["new_assignment"] = copy.copy(tmp) + merged_res = combine_similar_states_across_clones(X, base_nb_mean, total_bb_RD, merged_res, params="smp", tumor_prop=np.repeat(tumor_prop, X.shape[0]).reshape(-1,1) if not tumor_prop is None else None, hmmclass=hmm_nophasing_v2, merge_threshold=0.1) + log_gamma = np.stack([ merged_res["log_gamma"][:,(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ], axis=-1) + pred_cnv = np.vstack([ merged_res["pred_cnv"][(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ]).T + + # add to res_combine + if len(res_combine) == 1: + res_combine.update({"new_log_mu":np.hstack([ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":log_gamma, "pred_cnv":pred_cnv}) + else: + res_combine.update({"new_log_mu":np.hstack([res_combine["new_log_mu"]] + [ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([res_combine["new_alphas"]] + [ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([res_combine["new_p_binom"]] + [ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([res_combine["new_taus"]] + [ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":np.dstack([res_combine["log_gamma"], log_gamma ]), "pred_cnv":np.hstack([res_combine["pred_cnv"], pred_cnv])}) + res_combine["prev_assignment"][idx_spots] = merged_res["new_assignment"] + offset_clone + offset_clone += n_merged_clones + # assign un-assigned spots to the clone with smallest number of spots + unassigned_spots = np.where(res_combine["prev_assignment"] == -1)[0] + res_combine["prev_assignment"][unassigned_spots] = np.argmin(np.bincount(res_combine["prev_assignment"][res_combine["prev_assignment"]>=0])) + # temp: make dispersions the same across all clones + res_combine["new_alphas"][:,:] = np.max(res_combine["new_alphas"]) + res_combine["new_taus"][:,:] = np.min(res_combine["new_taus"]) + # end temp + n_final_clones = len(np.unique(res_combine["prev_assignment"])) + # compute HMRF log likelihood + log_persample_weights = np.zeros((n_final_clones, len(sample_list))) + for sidx in range(len(sample_list)): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res_combine["prev_assignment"][index], minlength=n_final_clones) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + # final re-assignment across all clones using estimated RDR + BAF + if config["tumorprop_file"] is None: + if config["nodepotential"] == "max": + pred = np.vstack([ np.argmax(res_combine["log_gamma"][:,:,c], axis=0) for c in range(res_combine["log_gamma"].shape[2]) ]).T + new_assignment, single_llf, total_llf, posterior = aggr_hmrf_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, res_combine, pred, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + elif config["nodepotential"] == "weighted_sum": + new_assignment, single_llf, total_llf, posterior = hmrf_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, res_combine, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + else: + if config["nodepotential"] == "max": + pred = np.vstack([ np.argmax(res_combine["log_gamma"][:,:,c], axis=0) for c in range(res_combine["log_gamma"].shape[2]) ]).T + new_assignment, single_llf, total_llf, posterior = aggr_hmrfmix_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res_combine, pred, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + elif config["nodepotential"] == "weighted_sum": + new_assignment, single_llf, total_llf, posterior = hmrfmix_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res_combine, \ + smooth_mat, adjacency_mat, res_combine["prev_assignment"], copy.copy(sample_ids), log_persample_weights, spatial_weight=config["spatial_weight"], hmmclass=hmm_nophasing_v2, return_posterior=True) + res_combine["total_llf"] = total_llf + res_combine["new_assignment"] = new_assignment + # res_combine = dict(np.load(f"{outdir}/original_rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True)) + # posterior = np.load(f"{outdir}/original_posterior_clone_probability.npy") + # re-order clones such that normal clones are always clone 0 + res_combine, posterior = reorder_results(res_combine, posterior, single_tumor_prop) + # save results + np.savez(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", **res_combine) + np.save(f"{outdir}/posterior_clone_probability.npy", posterior) + + ##### infer integer copy ##### + res_combine = dict(np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True)) + final_clone_ids = np.sort(np.unique(res_combine["new_assignment"])) + nonempty_clone_ids = copy.copy(final_clone_ids) + # add clone 0 as normal clone if it doesn't appear in final_clone_ids + if not (0 in final_clone_ids): + final_clone_ids = np.append(0, final_clone_ids) + # chr position + medfix = ["", "_diploid", "_triploid", "_tetraploid"] + for o,max_medploidy in enumerate([None, 2, 3, 4]): + # A/B copy number per bin + allele_specific_copy = [] + # A/B copy number per state + state_cnv = [] + + df_genelevel_cnv = None + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==cid)[0] for cid in final_clone_ids]) + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==cid)[0] for cid in final_clone_ids], single_tumor_prop, threshold=config["tumorprop_threshold"]) + + finding_distate_failed=False + for s, cid in enumerate(final_clone_ids): + if np.sum(base_nb_mean[:,s]) == 0: + continue + # adjust log_mu such that sum_bin lambda * np.exp(log_mu) = 1 + lambd = base_nb_mean[:,s] / np.sum(base_nb_mean[:,s]) + this_pred_cnv = res_combine["pred_cnv"][:,s] + adjusted_log_mu = np.log( np.exp(res_combine["new_log_mu"][:,s]) / np.sum(np.exp(res_combine["new_log_mu"][this_pred_cnv,s]) * lambd) ) + if not max_medploidy is None: + best_integer_copies, _ = hill_climbing_integer_copynumber_oneclone(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, max_medploidy=max_medploidy) + else: + try: + best_integer_copies, _ = hill_climbing_integer_copynumber_fixdiploid(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, nonbalance_bafdist=config["nonbalance_bafdist"], nondiploid_rdrdist=config["nondiploid_rdrdist"]) + except: + try: + best_integer_copies, _ = hill_climbing_integer_copynumber_fixdiploid(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, nonbalance_bafdist=config["nonbalance_bafdist"], nondiploid_rdrdist=config["nondiploid_rdrdist"], min_prop_threshold=0.05) + except: + finding_distate_failed = True + continue + + print(f"max med ploidy = {max_medploidy}, clone {s}, integer copy inference loss = {_}") + + allele_specific_copy.append( pd.DataFrame( best_integer_copies[res_combine["pred_cnv"][:,s], 0].reshape(1,-1), index=[f"clone{cid} A"], columns=np.arange(n_obs) ) ) + allele_specific_copy.append( pd.DataFrame( best_integer_copies[res_combine["pred_cnv"][:,s], 1].reshape(1,-1), index=[f"clone{cid} B"], columns=np.arange(n_obs) ) ) + # + state_cnv.append( pd.DataFrame( res_combine["new_log_mu"][:,s].reshape(-1,1), columns=[f"clone{cid} logmu"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( res_combine["new_p_binom"][:,s].reshape(-1,1), columns=[f"clone{cid} p"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( best_integer_copies[:,0].reshape(-1,1), columns=[f"clone{cid} A"], index=np.arange(config['n_states']) ) ) + state_cnv.append( pd.DataFrame( best_integer_copies[:,1].reshape(-1,1), columns=[f"clone{cid} B"], index=np.arange(config['n_states']) ) ) + # + tmpdf = get_genelevel_cnv_oneclone(best_integer_copies[res_combine["pred_cnv"][:,s], 0], best_integer_copies[res_combine["pred_cnv"][:,s], 1], x_gene_list) + tmpdf.columns = [f"clone{s} A", f"clone{s} B"] + if df_genelevel_cnv is None: + df_genelevel_cnv = copy.copy(tmpdf) + else: + df_genelevel_cnv = df_genelevel_cnv.join(tmpdf) + + if finding_distate_failed: + continue + + # output gene-level copy number + df_genelevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_genelevel.tsv", header=True, index=True, sep="\t") + # output segment-level copy number + allele_specific_copy = pd.concat(allele_specific_copy) + df_seglevel_cnv = pd.DataFrame({"CHR":df_bininfo.CHR.values, "START":df_bininfo.START.values, "END":df_bininfo.END.values }) + df_seglevel_cnv = df_seglevel_cnv.join( allele_specific_copy.T ) + df_seglevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_seglevel.tsv", header=True, index=False, sep="\t") + # output per-state copy number + state_cnv = functools.reduce(lambda left,right: pd.merge(left,right, left_index=True, right_index=True, how='inner'), state_cnv) + state_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_perstate.tsv", header=True, index=False, sep="\t") + # summarize to cna events + df_event = summary_events(f"{outdir}/cnv{medfix[o]}_seglevel.tsv", f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz") + df_event.to_csv(f"{outdir}/cnv{medfix[o]}_event.tsv", header=True, index=False, sep="\t") + + ##### output clone label ##### + df_clone_label = pd.DataFrame({"clone_label":res_combine["new_assignment"]}, index=barcodes) + if not config["tumorprop_file"] is None: + df_clone_label["tumor_proportion"] = single_tumor_prop + df_clone_label.to_csv(f"{outdir}/clone_labels.tsv", header=True, index=True, sep="\t") + + ##### plotting ##### + # make a directory for plots + p = subprocess.Popen(f"mkdir -p {outdir}/plots", shell=True) + out, err = p.communicate() + + # plot RDR and BAF + cn_file = f"{outdir}/cnv_diploid_seglevel.tsv" + fig = plot_rdr_baf(configuration_file, r_hmrf_initialization, cn_file, clone_ids=None, remove_xticks=True, rdr_ylim=5, chrtext_shift=-0.3, base_height=3.2, pointsize=30, palette="tab10") + fig.savefig(f"{outdir}/plots/rdr_baf_defaultcolor.pdf", transparent=True, bbox_inches="tight") + # plot allele-specific copy number + for o,max_medploidy in enumerate([None, 2, 3, 4]): + cn_file = f"{outdir}/cnv{medfix[o]}_seglevel.tsv" + if not Path(cn_file).exists(): + continue + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + df_cnv = expand_df_cnv(df_cnv) + fig, axes = plt.subplots(1, 1, figsize=(15, 0.9*len(final_clone_ids) + 0.6), dpi=200, facecolor="white") + axes = plot_acn_from_df(df_cnv, axes, add_chrbar=True, add_arrow=True, chrbar_thickness=0.4/(0.6*len(final_clone_ids) + 0.4), add_legend=True, remove_xticks=True) + fig.tight_layout() + fig.savefig(f"{outdir}/plots/acn_genome{medfix[o]}.pdf", transparent=True, bbox_inches="tight") + # additionally plot the allele-specific copy number per region + if not config["supervision_clone_file"] is None: + fig, axes = plt.subplots(1, 1, figsize=(15, 0.6*len(unique_clone_ids) + 0.4), dpi=200, facecolor="white") + merged_df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + df_cnv = merged_df_cnv[["CHR", "START", "END"]] + df_cnv = df_cnv.join( pd.DataFrame({f"clone{x} A":merged_df_cnv[f"clone{res_combine['new_assignment'][i]} A"] for i,x in enumerate(unique_clone_ids)}) ) + df_cnv = df_cnv.join( pd.DataFrame({f"clone{x} B":merged_df_cnv[f"clone{res_combine['new_assignment'][i]} B"] for i,x in enumerate(unique_clone_ids)}) ) + df_cnv = expand_df_cnv(df_cnv) + clone_ids = np.concatenate([ unique_clone_ids[res_combine["new_assignment"]==c].astype(str) for c in final_clone_ids ]) + axes = plot_acn_from_df(df_cnv, axes, clone_ids=clone_ids, clone_names=[f"region {x}" for x in clone_ids], add_chrbar=True, add_arrow=False, chrbar_thickness=0.4/(0.6*len(unique_clone_ids) + 0.4), add_legend=True, remove_xticks=True) + fig.tight_layout() + fig.savefig(f"{outdir}/plots/acn_genome{medfix[o]}_per_region.pdf", transparent=True, bbox_inches="tight") + # plot clones in space + if not config["supervision_clone_file"] is None: + before_assignments = pd.Series([None] * before_coords.shape[0]) + for i,c in enumerate(unique_clone_ids): + before_assignments.iloc[before_df_clones.clone_id.isin([c])] = f"clone {res_combine['new_assignment'][i]}" + fig = plot_clones_in_space(before_coords, before_assignments, sample_list, before_sample_ids, palette="Set2", labels=unique_clone_ids, label_coords=coords, label_sample_ids=sample_ids) + fig.savefig(f"{outdir}/plots/clone_spatial.pdf", transparent=True, bbox_inches="tight") + else: + assignment = pd.Series([f"clone {x}" for x in res_combine["new_assignment"]]) + fig = plot_clones_in_space(coords, assignment, axes, palette="Set2") + fig.savefig(f"{outdir}/plots/clone_spatial.pdf", transparent=True, bbox_inches="tight") + + +if __name__ == "__main__": + if len(sys.argv) > 1: + main(sys.argv[1]) \ No newline at end of file diff --git a/src/calicost/estimate_tumor_proportion.py b/src/calicost/estimate_tumor_proportion.py new file mode 100644 index 0000000..06d4caa --- /dev/null +++ b/src/calicost/estimate_tumor_proportion.py @@ -0,0 +1,120 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() +import copy +import functools +import subprocess +from calicost.arg_parse import * +from calicost.hmm_NB_BB_phaseswitch import * +from calicost.parse_input import * +from calicost.utils_hmrf import * +from calicost.hmrf import * + + +def main(configuration_file): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_bininfo, df_gene_snp, \ + barcodes, coords, single_tumor_prop, sample_list, sample_ids, adjacency_mat, smooth_mat, exp_counts = run_parse_n_load(config) + + single_base_nb_mean[:,:] = 0 + + n_states_for_tumorprop = 5 + n_clones_for_tumorprop = 3 + n_rdrclones_for_tumorprop = 3 #2 + max_outer_iter_for_tumorprop = 10 + max_iter_for_tumorprop = 20 + MIN_PROP_UNCERTAINTY = 0.05 + initial_clone_index = rectangle_initialize_initial_clone(coords, n_clones_for_tumorprop, random_state=0) + # save clone initialization into npz file + prefix = "initialhmm" + if not Path(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz").exists(): + initial_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz", **allres) + + hmrf_concatenate_pipeline(config['output_dir'], prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, initial_clone_index, n_states=n_states_for_tumorprop, \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat, adjacency_mat=adjacency_mat, sample_ids=sample_ids, max_iter_outer=max_outer_iter_for_tumorprop, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=max_iter_for_tumorprop, tol=config["tol"], spatial_weight=config["spatial_weight"]) + + res = load_hmrf_last_iteration(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz") + merging_groups, merged_res = merge_by_minspots(res["new_assignment"], res, single_total_bb_RD, min_spots_thresholds=config["min_spots_per_clone"], min_umicount_thresholds=config["min_avgumi_per_clone"]*single_X.shape[0]) + + # further refine clones + combined_assignment = copy.copy(merged_res['new_assignment']) + offset_clone = 0 + combined_p_binom = [] + offset_state = 0 + combined_pred_cnv = [] + for bafc in range(len(merging_groups)): + prefix = f"initialhmm_clone{bafc}" + idx_spots = np.where(merged_res['new_assignment'] == bafc)[0] + total_allele_count = np.sum(single_total_bb_RD[:, idx_spots]) + if total_allele_count < single_X.shape[0] * 50: # put a minimum B allele read count on pseudobulk to split clones + combined_assignment[idx_spots] = offset_clone + offset_clone += 1 + combined_p_binom.append(merged_res['new_p_binom']) + combined_pred_cnv.append(merged_res['pred_cnv'] + offset_state) + offset_state += merged_res['new_p_binom'].shape[0] + continue + # initialize clone + initial_clone_index = rectangle_initialize_initial_clone(coords[idx_spots], n_rdrclones_for_tumorprop, random_state=0) + # save clone initialization into npz file + if not Path(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz").exists(): + initial_assignment = np.zeros(len(idx_spots), dtype=int) + for c,idx in enumerate(initial_clone_index): + initial_assignment[idx] = c + allres = {"barcodes":barcodes[idx_spots], "num_iterations":0, "round-1_assignment":initial_assignment} + np.savez(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz", **allres) + + copy_slice_sample_ids = copy.copy(sample_ids[idx_spots]) + hmrf_concatenate_pipeline(config['output_dir'], prefix, single_X[:,:,idx_spots], lengths, single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], initial_clone_index, n_states=n_states_for_tumorprop, \ + log_sitewise_transmat=log_sitewise_transmat, smooth_mat=smooth_mat[np.ix_(idx_spots,idx_spots)], adjacency_mat=adjacency_mat[np.ix_(idx_spots,idx_spots)], sample_ids=copy_slice_sample_ids, max_iter_outer=10, nodepotential=config["nodepotential"], \ + hmmclass=hmm_nophasing_v2, params="sp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], \ + fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, max_iter=max_iter_for_tumorprop, tol=config["tol"], spatial_weight=config["spatial_weight"]) + + cloneres = load_hmrf_last_iteration(f"{config['output_dir']}/{prefix}_nstates{n_states_for_tumorprop}_sp.npz") + combined_assignment[idx_spots] = cloneres['new_assignment'] + offset_clone + offset_clone += np.max(cloneres['new_assignment']) + 1 + combined_p_binom.append(cloneres['new_p_binom']) + combined_pred_cnv.append(cloneres['pred_cnv'] + offset_state) + offset_state += cloneres['new_p_binom'].shape[0] + combined_p_binom = np.vstack(combined_p_binom) + combined_pred_cnv = np.concatenate(combined_pred_cnv) + + normal_candidate = identify_normal_spots(single_X, single_total_bb_RD, merged_res['new_assignment'], merged_res['pred_cnv'], merged_res['new_p_binom'], min_count=single_X.shape[0] * 200) + loh_states, is_B_lost, rdr_values, clones_hightumor = identify_loh_per_clone(single_X, combined_assignment, combined_pred_cnv, combined_p_binom, normal_candidate, single_total_bb_RD) + assignments = pd.DataFrame({'coarse':merged_res['new_assignment'], 'combined':combined_assignment}) + # pool across adjacency spot to increase the UMIs covering LOH region + _, tp_smooth_mat = multislice_adjacency(sample_ids, sample_list, coords, single_total_bb_RD, exp_counts, + across_slice_adjacency_mat=None, construct_adjacency_method=config['construct_adjacency_method'], + maxspots_pooling=7, construct_adjacency_w=config['construct_adjacency_w']) + single_tumor_prop, _ = estimator_tumor_proportion(single_X, single_total_bb_RD, assignments, combined_pred_cnv, loh_states, is_B_lost, rdr_values, clones_hightumor, smooth_mat=tp_smooth_mat) + # post-processing to remove negative tumor proportions + single_tumor_prop = np.where(single_tumor_prop < MIN_PROP_UNCERTAINTY, MIN_PROP_UNCERTAINTY, single_tumor_prop) + single_tumor_prop[normal_candidate] = 0 + # save single_tumor_prop to file + pd.DataFrame({"Tumor":single_tumor_prop}, index=barcodes).to_csv(f"{config['output_dir']}/loh_estimator_tumor_prop.tsv", header=True, sep="\t") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--configfile", help="configuration file of CalicoST", required=True, type=str) + args = parser.parse_args() + + main(args.configfile) \ No newline at end of file diff --git a/src/calicost/find_integer_copynumber.py b/src/calicost/find_integer_copynumber.py new file mode 100644 index 0000000..b1e41f6 --- /dev/null +++ b/src/calicost/find_integer_copynumber.py @@ -0,0 +1,680 @@ +# from cProfile import label +import numpy as np +import pandas as pd +import scipy +# import gurobipy as gp +# from gurobipy import GRB +import copy + + +# def hill_climbing_integer_copynumber_oneclone(new_log_mu, base_nb_mean, new_p_binom, pred_cnv, max_allele_copy=5, max_total_copy=6, max_medploidy=4): +# n_states = len(new_log_mu) +# lambd = base_nb_mean / np.sum(base_nb_mean) +# weight_per_state = np.array([ np.sum(lambd[pred_cnv == s]) for s in range(n_states)]) +# mu = np.exp(new_log_mu) +# def f(params, ploidy): +# # params of size (n_states, 2) +# if np.any( np.sum(params, axis=1) == 0 ): +# return len(pred_cnv) * 1e6 +# denom = weight_per_state.dot( np.sum(params, axis=1) ) +# frac_rdr = np.sum(params, axis=1) / denom +# frac_baf = params[:,0] / np.sum(params, axis=1) +# points_per_state = np.bincount(pred_cnv, minlength=params.shape[0] ) +# ### temp penalty ### +# mu_threshold = 0.3 +# crucial_ordered_pairs_1 = (mu[:,None] - mu[None,:] > mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] < 0) +# crucial_ordered_pairs_2 = (mu[:,None] - mu[None,:] < -mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] > 0) +# return np.square(0.3 * (mu - frac_rdr)).dot(points_per_state) + np.square(new_p_binom - frac_baf).dot(points_per_state) + \ +# np.sum(crucial_ordered_pairs_1) * len(pred_cnv) + np.sum(crucial_ordered_pairs_2) * len(pred_cnv) +# ### end temp penalty ### +# # return np.abs(mu - frac_rdr).dot(points_per_state) + 5 * np.abs(new_p_binom - frac_baf).dot(points_per_state) +# def hill_climb(initial_params, ploidy, idx_med, max_iter=10): +# best_obj = f(initial_params, ploidy) +# params = copy.copy(initial_params) +# increased = True +# for counter in range(max_iter): +# increased = False +# for k in range(params.shape[0]): +# this_best_obj = best_obj +# this_best_k = copy.copy(params[k,:]) +# for candi in candidates: +# if k == idx_med and np.sum(candi) != ploidy: +# continue +# params[k,:] = candi +# obj = f(params, ploidy) +# if obj < this_best_obj: +# # print(k, candi, obj, this_best_obj, ploidy+1, 0.1 * np.maximum(0, np.sum(params[k,:]) - ploidy-1) * np.sum(pred_cnv==k)) +# this_best_obj = obj +# this_best_k = candi +# increased = (increased | (this_best_obj < best_obj)) +# params[k,:] = this_best_k +# best_obj = this_best_obj +# if not increased: +# break +# return params, best_obj +# # candidate integer copy states +# candidates = np.array([ [i,j] for i in range(max_allele_copy + 1) for j in range(max_allele_copy) if (not (i == 0 and j == 0)) and (i + j <= max_total_copy)]) +# # find the best copy number states starting from various ploidy +# best_obj = np.inf +# best_integer_copies = np.zeros((n_states, 2), dtype=int) +# # fix the genomic bin with the median new_log_mu to have exactly ploidy genomes +# bidx_med = np.argsort(new_log_mu[pred_cnv])[ int(len(pred_cnv)/2) ] +# idx_med = pred_cnv[bidx_med] +# for ploidy in range(1, max_medploidy+1): +# initial_params = np.ones((n_states, 2), dtype=int) * int(ploidy / 2) +# initial_params[:, 1] = ploidy - initial_params[:, 0] +# params, obj = hill_climb(initial_params, ploidy, idx_med) +# if obj < best_obj: +# best_obj = obj +# best_integer_copies = copy.copy(params) +# return best_integer_copies, best_obj + + +def find_diploid_balanced_state(new_log_mu, new_p_binom, pred_cnv, min_prop_threshold, EPS_BAF): + n_states = len(new_log_mu) + # find candidate diploid balanced state under the criteria that (1) #bins in that state > 0.1 * total #bins and (2) BAF is close to 0.5 by EPS_BAF distance + candidate = np.where( (np.bincount(pred_cnv, minlength=n_states) >= min_prop_threshold*len(pred_cnv)) & (np.abs(new_p_binom - 0.5) <= EPS_BAF) )[0] + if len(candidate) == 0: + raise ValueError("No candidate diploid balanced state found!") + else: + # the diploid balanced states is the one in candidate with smallest new_log_mu + return candidate[ np.argmin(new_log_mu[candidate]) ] + + +def hill_climbing_integer_copynumber_fixdiploid(new_log_mu, base_nb_mean, new_p_binom, pred_cnv, max_allele_copy=5, max_total_copy=6, max_medploidy=4, \ + min_prop_threshold=0.1, EPS_BAF=0.05, nonbalance_bafdist=None, nondiploid_rdrdist=None, enforce_states={}): + n_states = len(new_log_mu) + lambd = base_nb_mean / np.sum(base_nb_mean) + weight_per_state = np.array([ np.sum(lambd[pred_cnv == s]) for s in range(n_states)]) + mu = np.exp(new_log_mu) + # + def is_nondiploidnormal(k): + if not nonbalance_bafdist is None: + if np.abs(new_p_binom[k] - 0.5) > nonbalance_bafdist: + return True + if not nondiploid_rdrdist is None: + if np.abs(mu[k] - 1) > nondiploid_rdrdist: + return True + return False + # + EPS_POINTS = 0.1 + def f(params, ploidy, scalefactor): + # params of size (n_states, 2) + if np.any( np.sum(params, axis=1) == 0 ): + return len(pred_cnv) * 1e6 + frac_rdr = np.sum(params, axis=1) / scalefactor + frac_baf = params[:,0] / np.sum(params, axis=1) + points_per_state = np.bincount(pred_cnv, minlength=params.shape[0] ) + EPS_POINTS + ### temp penalty ### + mu_threshold = 0.3 + crucial_ordered_pairs_1 = (mu[:,None] - mu[None,:] > mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] < 0) + crucial_ordered_pairs_2 = (mu[:,None] - mu[None,:] < -mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] > 0) + # penalty on ploidy + derived_ploidy = np.sum(params, axis=1).dot(points_per_state) / np.sum(points_per_state, axis=0) + return np.square(0.3 * (mu - frac_rdr)).dot(points_per_state) + np.square(new_p_binom - frac_baf).dot(points_per_state) + \ + np.sum(crucial_ordered_pairs_1) * len(pred_cnv) + np.sum(crucial_ordered_pairs_2) * len(pred_cnv) + np.sum(derived_ploidy > ploidy + 0.5) * len(pred_cnv) + # + def hill_climb(initial_params, ploidy, idx_diploid_normal, max_iter=10): + scalefactor = 2.0 / mu[idx_diploid_normal] + best_obj = f(initial_params, ploidy, scalefactor) + params = copy.copy(initial_params) + increased = True + for counter in range(max_iter): + increased = False + for k in range(params.shape[0]): + if k == idx_diploid_normal or k in enforce_states: + continue + this_best_obj = best_obj + this_best_k = copy.copy(params[k,:]) + for candi in candidates: + if is_nondiploidnormal(k) and candi[0] == 1 and candi[1] == 1: + continue + params[k,:] = candi + obj = f(params, ploidy, scalefactor) + if obj < this_best_obj: + this_best_obj = obj + this_best_k = candi + increased = (increased | (this_best_obj < best_obj)) + params[k,:] = this_best_k + best_obj = this_best_obj + if not increased: + break + return params, best_obj + # diploid normal state + idx_diploid_normal = find_diploid_balanced_state(new_log_mu, new_p_binom, pred_cnv, min_prop_threshold=min_prop_threshold, EPS_BAF=EPS_BAF) + # candidate integer copy states + candidates = np.array([ [i,j] for i in range(max_allele_copy + 1) for j in range(max_allele_copy+1) if (not (i == 0 and j == 0)) and (i + j <= max_total_copy)]) + # find the best copy number states starting from various ploidy + best_obj = np.inf + best_integer_copies = np.zeros((n_states, 2), dtype=int) + for ploidy in range(1, max_medploidy+1): + # initial_params = np.array([ [1,1] if not is_nondiploidnormal(k) else [1,0] for k in range(n_states)], dtype=int) + np.random.seed(0) + for r in range(20): + initial_params = candidates[ np.random.randint(low=0, high=candidates.shape[0], size=n_states), : ] + initial_params[idx_diploid_normal] = np.array([1,1]) + for k,v in enforce_states.items(): + initial_params[k] = v + params, obj = hill_climb(initial_params, ploidy, idx_diploid_normal) + if obj < best_obj: + best_obj = obj + best_integer_copies = copy.copy(params) + return best_integer_copies, best_obj + + +def hill_climbing_integer_copynumber_oneclone(new_log_mu, base_nb_mean, new_p_binom, pred_cnv, max_allele_copy=5, max_total_copy=6, max_medploidy=4, enforce_states={}, EPS_BAF=0.05): + n_states = len(new_log_mu) + lambd = base_nb_mean / np.sum(base_nb_mean) + weight_per_state = np.array([ np.sum(lambd[pred_cnv == s]) for s in range(n_states)]) + mu = np.exp(new_log_mu) + # + EPS_POINTS = 0.1 + def f(params, ploidy): + # params of size (n_states, 2) + if np.any( np.sum(params, axis=1) == 0 ): + return len(pred_cnv) * 1e6 + denom = weight_per_state.dot( np.sum(params, axis=1) ) + frac_rdr = np.sum(params, axis=1) / denom + frac_baf = params[:,0] / np.sum(params, axis=1) + points_per_state = np.bincount(pred_cnv, minlength=params.shape[0] ) + EPS_POINTS + ### temp penalty ### + mu_threshold = 0.3 + crucial_ordered_pairs_1 = (mu[:,None] - mu[None,:] > mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] < 0) + crucial_ordered_pairs_2 = (mu[:,None] - mu[None,:] < -mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] > 0) + # penalty on setting unbalanced states when BAF is close to 0.5 + if np.sum(params[:,0] == params[:,1]) > 0: + baf_threshold = max(EPS_BAF, np.max(np.abs(new_p_binom[(params[:,0]==params[:,1])] - 0.5))) + else: + baf_threshold = EPS_BAF + unbalanced_penalty = (params[:,0] != params[:,1]).dot(np.abs(new_p_binom - 0.5) < baf_threshold) + # penalty on ploidy + derived_ploidy = np.sum(params, axis=1).dot(points_per_state) / np.sum(points_per_state, axis=0) + return np.square(0.3 * (mu - frac_rdr)).dot(points_per_state) + np.square(new_p_binom - frac_baf).dot(points_per_state) + \ + np.sum(crucial_ordered_pairs_1) * len(pred_cnv) + np.sum(crucial_ordered_pairs_2) * len(pred_cnv) + np.sum(derived_ploidy > ploidy + 0.5) * len(pred_cnv) + \ + unbalanced_penalty * len(pred_cnv) + ### end temp penalty ### + # return np.abs(mu - frac_rdr).dot(points_per_state) + 5 * np.abs(new_p_binom - frac_baf).dot(points_per_state) + def hill_climb(initial_params, ploidy, max_iter=10): + best_obj = f(initial_params, ploidy) + params = copy.copy(initial_params) + increased = True + for counter in range(max_iter): + increased = False + for k in range(params.shape[0]): + if k in enforce_states: + continue + this_best_obj = best_obj + this_best_k = copy.copy(params[k,:]) + for candi in candidates: + params[k,:] = candi + obj = f(params, ploidy) + if obj < this_best_obj: + # print(k, candi, obj, this_best_obj, ploidy+1, 0.1 * np.maximum(0, np.sum(params[k,:]) - ploidy-1) * np.sum(pred_cnv==k)) + this_best_obj = obj + this_best_k = candi + increased = (increased | (this_best_obj < best_obj)) + params[k,:] = this_best_k + best_obj = this_best_obj + if not increased: + break + return params, best_obj + # candidate integer copy states + candidates = np.array([ [i,j] for i in range(max_allele_copy + 1) for j in range(max_allele_copy+1) if (not (i == 0 and j == 0)) and (i + j <= max_total_copy)]) + # find the best copy number states starting from various ploidy + best_obj = np.inf + best_integer_copies = np.zeros((n_states, 2), dtype=int) + for ploidy in range(1, max_medploidy+1): + initial_params = np.ones((n_states, 2), dtype=int) * int(ploidy / 2) + initial_params[:, 1] = ploidy - initial_params[:, 0] + for k,v in enforce_states.items(): + initial_params[k] = v + params, obj = hill_climb(initial_params, ploidy) + if obj < best_obj: + best_obj = obj + best_integer_copies = copy.copy(params) + return best_integer_copies, best_obj + + +def hill_climbing_integer_copynumber_joint(new_log_mu, base_nb_mean, new_p_binom, pred_cnv, max_allele_copy=5, max_total_copy=6, max_medploidy=4): + """ + Jointly infer copy numbers across multiple clones, given they share the same set of new_log_mu and new_p_binom parameters. + + Attributes: + ---------- + new_log_mu : array of size (n_states, n_clones) + Log mean of the negative binomial distribution, after adjusting to make weighted sum to be 1. + + base_nb_mean : array of size (n_obs, n_clones) + Baseline probability of gene expression across bins (n_obs) for each clone (n_clones). + + new_p_binom : array of size (n_states,) + BAF parameter in the Beta-binomial distribution. + + pred_cnv : array of size (n_obs, n_clones) + Copy unmber states across bins (n_obs) for each clone (n_clones). + """ + n_states = new_log_mu.shape[0] + n_clones = base_nb_mean.shape[1] + lambd = np.sum(base_nb_mean,axis=1) / np.sum(base_nb_mean) + weight_per_state = np.array([[ np.sum(lambd[pred_cnv[:,c] == s]) for s in range(n_states)] for c in range(n_clones)]).T # size of (n_states, n_clones) + mu = np.exp(new_log_mu) + def f(params, ploidy): + # params of size (n_states, 2) + if np.any( np.sum(params, axis=1) == 0 ): + return len(pred_cnv) * 1e6 + denom = weight_per_state.T.dot( np.sum(params, axis=1) ) # size of (n_clones,) + frac_rdr = np.sum(params, axis=1).reshape(-1,1) / denom.reshape(1,-1) # size of (n_states, n_clones) + frac_baf = params[:,0] / np.sum(params, axis=1) + points_per_state = np.vstack([ np.bincount(pred_cnv[:,c], minlength=params.shape[0]) for c in range(n_clones) ]).T # size of (n_states, n_clones) + ### temp penalty ### + mu_threshold = 0.3 + crucial_ordered_pairs_1 = (mu[:,0][:,None] - mu[:,0][None,:] > mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] < 0) + crucial_ordered_pairs_2 = (mu[:,0][:,None] - mu[:,0][None,:] < -mu_threshold) * (np.sum(params, axis=1)[:,None] - np.sum(params, axis=1)[None,:] > 0) + # penalty on ploidy + derived_ploidy = np.median(np.sum(params, axis=1).dot(points_per_state) / np.sum(points_per_state, axis=0)) + return np.sum(np.square(0.3 * (mu - frac_rdr) * points_per_state)) + np.sum(np.square((new_p_binom - frac_baf).reshape(-1,1) * points_per_state)) + \ + np.sum(crucial_ordered_pairs_1) * np.prod(pred_cnv.shape) + np.sum(crucial_ordered_pairs_2) * np.prod(pred_cnv.shape) + np.sum(derived_ploidy > ploidy + 0.5) * np.prod(pred_cnv.shape) + ### end temp penalty ### + # return np.abs(mu - frac_rdr).dot(points_per_state) + 5 * np.abs(new_p_binom - frac_baf).dot(points_per_state) + def hill_climb(initial_params, ploidy, max_iter=10): + best_obj = f(initial_params, ploidy) + params = copy.copy(initial_params) + increased = True + for counter in range(max_iter): + increased = False + for k in range(params.shape[0]): + this_best_obj = best_obj + this_best_k = copy.copy(params[k,:]) + for candi in candidates: + params[k,:] = candi + obj = f(params, ploidy) + if obj < this_best_obj: + # print(k, candi, obj, this_best_obj, ploidy+1, 0.1 * np.maximum(0, np.sum(params[k,:]) - ploidy-1) * np.sum(pred_cnv==k)) + this_best_obj = obj + this_best_k = candi + increased = (increased | (this_best_obj < best_obj)) + params[k,:] = this_best_k + best_obj = this_best_obj + if not increased: + break + return params, best_obj + # candidate integer copy states + candidates = np.array([ [i,j] for i in range(max_allele_copy + 1) for j in range(max_allele_copy+1) if (not (i == 0 and j == 0)) and (i + j <= max_total_copy)]) + # find the best copy number states starting from various ploidy + best_obj = np.inf + best_integer_copies = np.zeros((n_states, 2), dtype=int) + # fix the genomic bin with the median new_log_mu to have exactly ploidy genomes + # bidx_med = np.argsort(np.concatenate([ new_log_mu[pred_cnv[:,c],c] for c in range(n_clones) ]))[ int(len(pred_cnv.flatten())/2) ] + # idx_med = pred_cnv.flatten(order="F")[bidx_med] + for ploidy in range(1, max_medploidy+1): + initial_params = np.ones((n_states, 2), dtype=int) * int(ploidy / 2) + initial_params[:, 1] = ploidy - initial_params[:, 0] + params, obj = hill_climb(initial_params, ploidy) + if obj < best_obj: + best_obj = obj + best_integer_copies = copy.copy(params) + return best_integer_copies, best_obj + + +def get_genelevel_cnv_oneclone(A_copy, B_copy, x_gene_list): + map_gene_bin = {} + for i,x in enumerate(x_gene_list): + this_genes = [z for z in x.split(" ") if z != ""] + for g in this_genes: + map_gene_bin[g] = i + gene_list = np.sort(np.array(list(map_gene_bin.keys()))) + gene_level_copies = np.zeros( (len(gene_list), 2), dtype=int ) + for i,g in enumerate(gene_list): + idx = map_gene_bin[g] + gene_level_copies[i, 0] = A_copy[idx] + gene_level_copies[i, 1] = B_copy[idx] + return pd.DataFrame({"A":gene_level_copies[:,0], "B":gene_level_copies[:,1]}, index=gene_list) + + +def convert_copy_to_states(A_copy, B_copy): + tmp = A_copy + B_copy + tmp = tmp[~np.isnan(tmp)] + base_ploidy = np.median(tmp) + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy != B_copy) ] = "del" + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy == B_copy) ] = "bdel" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy != B_copy) ] = "amp" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy == B_copy) ] = "bamp" + coarse_states[ (A_copy + B_copy == base_ploidy) & (A_copy != B_copy) ] = "loh" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +""" +def optimize_integer_copynumber_oneclone(new_log_mu, base_nb_mean, total_bb_RD, new_p_binom, pred_cnv, max_copynumber=6): + ''' + For each single clone, input are all vectors instead of matrices + ''' + m = gp.Model("ilp") + ##### Create variables ##### + var_copies_1 = [] + var_copies_2 = [] + # allele-specific copy numbers + for k in range(len(new_log_mu)): + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}1") + var_copies_1.append( tmp ) + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}2") + var_copies_2.append( tmp ) + # absolute value of the expressions in objective function + var_abs_rdr = [] + var_abs_baf = [] + for k in range(len(new_log_mu)): + tmp = m.addVar(lb=0, name=f"rdr{k}") + var_abs_rdr.append( tmp ) + tmp = m.addVar(lb=0, name=f"baf{k}") + var_abs_baf.append( tmp ) + ##### Set objective ##### + obj = gp.LinExpr([np.sum((pred_cnv==k) & (base_nb_mean>0)) for k in range(len(new_log_mu))], var_abs_rdr) + obj.addTerms([np.sum((pred_cnv==k) & (total_bb_RD>0)) for k in range(len(new_p_binom))], var_abs_baf) + m.setObjective(obj, GRB.MINIMIZE) + ##### Add constraint ##### + # total copy >= 1 + for k in range(len(new_log_mu)): + m.addConstr(var_copies_1[k] + var_copies_2[k] >= 1, f"min_cn_{k}") + # total copy not exceeding max_copynumber + for k in range(len(new_log_mu)): + m.addConstr(var_copies_1[k] + var_copies_2[k] <= max_copynumber, f"max_cn_{k}") + # RDR + lambd = base_nb_mean / np.sum(base_nb_mean) + mu = np.exp(new_log_mu) + weight_total_copy = gp.LinExpr( np.append(lambd, lambd), [var_copies_1[pred_cnv[g]] for g in range(len(base_nb_mean))] + [var_copies_2[pred_cnv[g]] for g in range(len(base_nb_mean))]) + for k in range(len(new_log_mu)): + m.addConstr(mu[k] * weight_total_copy - var_copies_1[k] - var_copies_2[k] <= var_abs_rdr[k], f"const_rdr_{k}_1" ) + m.addConstr(-mu[k] * weight_total_copy + var_copies_1[k] + var_copies_2[k] <= var_abs_rdr[k], f"const_rdr_{k}_1" ) + # BAF + for k in range(len(new_log_mu)): + m.addConstr( (new_p_binom[k] - 1) * var_copies_1[k] + new_p_binom[k] * var_copies_2[k] <= var_abs_baf[k], f"const_baf_{k}_1" ) + m.addConstr( -(new_p_binom[k] - 1) * var_copies_1[k] - new_p_binom[k] * var_copies_2[k] <= var_abs_baf[k], f"const_baf_{k}_1" ) + ##### Optimize model ##### + m.Params.LogToConsole = 0 + m.optimize() + ##### get A allele and B allele integer copies corresponding to each HMM state ##### + B_copy = np.array([ m.getVarByName(f"c{k}1").X for k in range(len(new_log_mu)) ]).astype(int) + A_copy = np.array([ m.getVarByName(f"c{k}2").X for k in range(len(new_log_mu)) ]).astype(int) + # theoretical RDR and BAF per state + total_copy_per_locus = A_copy[pred_cnv] + B_copy[pred_cnv] + theoretical_mu = 1.0 * (A_copy + B_copy) / (lambd.dot(total_copy_per_locus)) + theoretical_p_binom = 1.0 * B_copy / (B_copy + A_copy) + return B_copy, A_copy, theoretical_mu, theoretical_p_binom, m.ObjVal + + +def optimize_integer_copynumber_oneclone_v2(new_log_mu, base_nb_mean, total_bb_RD, new_p_binom, pred_cnv, base_copynumber=4, max_copynumber=6): + ''' + For each single clone, input are all vectors instead of matrices + ''' + m = gp.Model("ilp") + ##### Create variables ##### + var_copies_1 = [] + var_copies_2 = [] + # allele-specific copy numbers + for k in range(len(new_log_mu)): + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}1") + var_copies_1.append( tmp ) + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}2") + var_copies_2.append( tmp ) + # absolute value of the expressions in objective function + var_abs_rdr = [] + var_abs_baf = [] + var_abs_total = [] + for k in range(len(new_log_mu)): + tmp = m.addVar(lb=0, name=f"rdr{k}") + var_abs_rdr.append( tmp ) + tmp = m.addVar(lb=0, name=f"baf{k}") + var_abs_baf.append( tmp ) + tmp = m.addVar(lb=0, name=f"total{k}") + var_abs_total.append( tmp ) + ##### Set objective ##### + obj = gp.LinExpr([np.sum((pred_cnv==k) & (base_nb_mean>0)) for k in range(len(new_log_mu))], var_abs_rdr) + obj.addTerms([np.sum((pred_cnv==k) & (total_bb_RD>0)) for k in range(len(new_p_binom))], var_abs_baf) + obj.addTerms([0.02 * np.sum((pred_cnv==k) & (base_nb_mean>0)) for k in range(len(new_log_mu))], var_abs_total) + obj.addTerms([0.02 * np.sum((pred_cnv==k) & (total_bb_RD>0)) for k in range(len(new_p_binom))], var_abs_total) + m.setObjective(obj, GRB.MINIMIZE) + ##### Add constraint ##### + # total copy >= 1 + for k in range(len(new_log_mu)): + m.addConstr(var_copies_1[k] + var_copies_2[k] >= 1, f"min_cn_{k}") + # total copy not exceeding max_copynumber + for k in range(len(new_log_mu)): + m.addConstr(var_copies_1[k] + var_copies_2[k] <= max_copynumber, f"max_cn_{k}") + # total copy similar to base_copynumber + for k in range(len(new_log_mu)): + m.addConstr(var_copies_1[k] + var_copies_2[k] - base_copynumber <= var_abs_total[k], f"total_cn_{k}_1") + m.addConstr(base_copynumber - var_copies_1[k] - var_copies_2[k] <= var_abs_total[k], f"total_cn_{k}_2") + # RDR + lambd = base_nb_mean / np.sum(base_nb_mean) + mu = np.exp(new_log_mu) + weight_total_copy = gp.LinExpr( np.append(lambd, lambd), [var_copies_1[pred_cnv[g]] for g in range(len(base_nb_mean))] + [var_copies_2[pred_cnv[g]] for g in range(len(base_nb_mean))]) + for k in range(len(new_log_mu)): + m.addConstr(mu[k] * weight_total_copy - var_copies_1[k] - var_copies_2[k] <= var_abs_rdr[k], f"const_rdr_{k}_1" ) + m.addConstr(-mu[k] * weight_total_copy + var_copies_1[k] + var_copies_2[k] <= var_abs_rdr[k], f"const_rdr_{k}_1" ) + # BAF + for k in range(len(new_log_mu)): + m.addConstr( (new_p_binom[k] - 1) * var_copies_1[k] + new_p_binom[k] * var_copies_2[k] <= var_abs_baf[k], f"const_baf_{k}_1" ) + m.addConstr( -(new_p_binom[k] - 1) * var_copies_1[k] - new_p_binom[k] * var_copies_2[k] <= var_abs_baf[k], f"const_baf_{k}_1" ) + ##### Optimize model ##### + m.Params.LogToConsole = 0 + m.optimize() + ##### get A allele and B allele integer copies corresponding to each HMM state ##### + B_copy = np.array([ m.getVarByName(f"c{k}1").X for k in range(len(new_log_mu)) ]).astype(int) + A_copy = np.array([ m.getVarByName(f"c{k}2").X for k in range(len(new_log_mu)) ]).astype(int) + # theoretical RDR and BAF per state + total_copy_per_locus = A_copy[pred_cnv] + B_copy[pred_cnv] + theoretical_mu = 1.0 * (A_copy + B_copy) / (lambd.dot(total_copy_per_locus)) + theoretical_p_binom = 1.0 * B_copy / (B_copy + A_copy) + return B_copy, A_copy, theoretical_mu, theoretical_p_binom, m.ObjVal + + +def get_integer_copynumber(new_log_mu, base_nb_mean, total_bb_RD, new_p_binom, pred_cnv, max_copynumber): + num_clones = new_p_binom.shape[1] + B_copy = np.ones(new_p_binom.shape, dtype=int) + A_copy = np.ones(new_p_binom.shape, dtype=int) + theoretical_mu = np.ones(new_p_binom.shape) + theoretical_p_binom = np.ones(new_p_binom.shape) + sum_objective = 0 + for c in range(num_clones): + tmp_B_copy, tmp_A_copy, tmp_theoretical_mu, tmp_theoretical_p_binom, tmp_obj = optimize_integer_copynumber_oneclone(new_log_mu[:,c], base_nb_mean[:,c], total_bb_RD[:,c], new_p_binom[:,c], pred_cnv, max_copynumber) + B_copy[:,c] = tmp_B_copy + A_copy[:,c] = tmp_A_copy + theoretical_mu[:,c] = tmp_theoretical_mu + theoretical_p_binom[:,c] = tmp_theoretical_p_binom + sum_objective += tmp_obj + return B_copy, A_copy, theoretical_mu, theoretical_p_binom, sum_objective + + +def eval_objective(new_log_mu, base_nb_mean, total_bb_RD, new_p_binom, pred_cnv, B_copy, A_copy): + num_clones = new_p_binom.shape[1] + objectives_rdr = [] + objectives_baf = [] + for c in range(num_clones): + # RDR + idx_nonzero = np.where(base_nb_mean[:,c] > 0)[0] + total_copy = (A_copy + B_copy)[pred_cnv, c] + lambd = base_nb_mean[:,c] / np.sum(base_nb_mean[:,c]) + weight_total_copy = lambd.dot(total_copy) + obj_rdr = np.sum(np.abs( np.exp(new_log_mu[pred_cnv,c][idx_nonzero]) * weight_total_copy - total_copy[idx_nonzero] )) + objectives_rdr.append( obj_rdr ) + # BAF + idx_nonzero = np.where(total_bb_RD[:,c] > 0)[0] + obj_baf = np.sum(np.abs( total_copy[idx_nonzero] * new_p_binom[pred_cnv, c][idx_nonzero] - B_copy[pred_cnv, c][idx_nonzero] )) + objectives_baf.append( obj_baf ) + return objectives_rdr, objectives_baf + + +def composite_hmm_optimize_integer_copynumber(base_nb_mean, total_bb_RD, new_log_mu, new_scalefactors, new_p_binom, state_tuples, pred_cnv, max_copynumber=6): + ''' + Attributes + ---------- + base_nb_mean : array, (n_obs, n_spots) + Expected read counts per bin (or SNP) under diploid genome assumption. + + total_bb_RD : array, (n_obs, n_spots) + Total SNP-covering reads per SNP. + + new_log_mu : array, (n_individual_states, ) + Log fold change of RDR for each copy number state + + new_scalefactors : array, (n_spots, ) + Log normalization factor due to total copy number change along the whole genome of that clone. + + new_p_binom : array, (n_individual_states, ) + BAF of each copy number state. + + state_tuples : array, (n_composite_states, n_spots) + Each composite state is a omposition of copy numnber states across all clones. + + pred_cnv : array, (n_obs, ) + Categorical variables to indicate the composite state each bin (or SNP) is in. + ''' + n_obs = base_nb_mean.shape[0] + n_spots = base_nb_mean.shape[1] + n_individual_states = int(len(new_log_mu) / 2) + n_composite_states = int(len(state_tuples) / 2) + # gurobi ILP to infer integer copy numbers + m = gp.Model("ilp") + ##### Create variables ##### + var_copies_1 = [] + var_copies_2 = [] + # allele-specific copy numbers + for k in range(n_individual_states): + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}1") + var_copies_1.append( tmp ) + tmp = m.addVar(lb=0, vtype=GRB.INTEGER, name=f"c{k}2") + var_copies_2.append( tmp ) + # absolute value of the expressions in objective function, per clone per individual copy number state + var_abs_rdr = [[] for c in range(n_spots)] + var_abs_baf_B = [[] for c in range(n_spots)] + var_abs_baf_A = [[] for c in range(n_spots)] + for c in range(n_spots): + for k in range(n_individual_states): + tmp = m.addVar(lb=0, name=f"rdr_{c}_{k}") + var_abs_rdr[c].append( tmp ) + tmp = m.addVar(lb=0, name=f"bafB_{c}_{k}") + var_abs_baf_B[c].append( tmp ) + tmp = m.addVar(lb=0, name=f"bafA_{c}_{k}") + var_abs_baf_A[c].append( tmp ) + ##### Set objective ##### + obj = gp.LinExpr(0) + for c in range(n_spots): + this_pred_cnv = state_tuples[pred_cnv, c] + # RDR + coef = [np.sum(((this_pred_cnv==k) | (this_pred_cnv==k+n_individual_states)) & (base_nb_mean[:,c]>0)) for k in range(n_individual_states)] + obj.addTerms(coef, var_abs_rdr[c]) + # BAF + coef = [np.sum((this_pred_cnv==k) & (total_bb_RD[:,c]>0)) for k in range(n_individual_states)] + obj.addTerms(coef, var_abs_baf_B[c]) + coef = [np.sum((this_pred_cnv==k+n_individual_states) & (total_bb_RD[:,c]>0)) for k in range(n_individual_states)] + obj.addTerms(coef, var_abs_baf_A[c]) + m.setObjective(obj, GRB.MINIMIZE) + ##### Add constraint ##### + # total copy >= 1 + for k in range(n_individual_states): + m.addConstr(var_copies_1[k] + var_copies_2[k] >= 1, f"min_cn_{k}") + # total copy not exceeding max_copynumber + for k in range(n_individual_states): + m.addConstr(var_copies_1[k] + var_copies_2[k] <= max_copynumber, f"max_cn_{k}") + # RDR + for c in range(n_spots): + this_pred_cnv = state_tuples[pred_cnv, c] + this_pred_cnv = this_pred_cnv % n_individual_states + lambd = base_nb_mean[:,c] / np.sum(base_nb_mean[:,c]) + mu = np.exp(new_log_mu[:n_individual_states]) if c==0 else np.exp(new_log_mu[:n_individual_states] + new_scalefactors[c-1]) + weight_total_copy = gp.LinExpr( np.append(lambd, lambd), [var_copies_1[this_pred_cnv[g]] for g in range(n_obs)] + [var_copies_2[this_pred_cnv[g]] for g in range(n_obs)]) + for k in range(n_individual_states): + m.addConstr(mu[k] * weight_total_copy - var_copies_1[k] - var_copies_2[k] <= var_abs_rdr[c][k], f"const_rdr__{c}_{k}_1" ) + m.addConstr(-mu[k] * weight_total_copy + var_copies_1[k] + var_copies_2[k] <= var_abs_rdr[c][k], f"const_rdr__{c}_{k}_2" ) + # BAF + for c in range(n_spots): + this_pred_cnv = state_tuples[pred_cnv, c] + # B allele + for k in range(n_individual_states): + m.addConstr( (new_p_binom[k] - 1) * var_copies_1[k] + new_p_binom[k] * var_copies_2[k] <= var_abs_baf_B[c][k], f"const_baf_{c}_{k}_1" ) + m.addConstr( -(new_p_binom[k] - 1) * var_copies_1[k] - new_p_binom[k] * var_copies_2[k] <= var_abs_baf_B[c][k], f"const_baf_{c}_{k}_2" ) + # A allele + for k in range(n_individual_states): + m.addConstr( new_p_binom[k] * var_copies_1[k] + (1-new_p_binom[k]) * var_copies_2[k] <= var_abs_baf_A[c][k], f"const_baf_A_{c}_{k}_1" ) + m.addConstr( -new_p_binom[k] * var_copies_1[k] - (1-new_p_binom[k]) * var_copies_2[k] <= var_abs_baf_A[c][k], f"const_baf_A_{c}_{k}_2" ) + ##### Optimize model ##### + m.Params.LogToConsole = 0 + m.optimize() + ##### get A allele and B allele integer copies corresponding to each HMM state ##### + B_copy = np.array([ m.getVarByName(f"c{k}1").X for k in range(n_individual_states) ]).astype(int).reshape(-1,1) + A_copy = np.array([ m.getVarByName(f"c{k}2").X for k in range(n_individual_states) ]).astype(int).reshape(-1,1) + # theoretical RDR and BAF per state + theoretical_mu = [] + theoretical_p_binom = [] + for c in range(n_spots): + this_pred_cnv = state_tuples[pred_cnv, c] + lambd = base_nb_mean[:,c] / np.sum(base_nb_mean[:,c]) + total_copy_per_locus = A_copy[this_pred_cnv % n_individual_states,0] + B_copy[this_pred_cnv % n_individual_states,0] + theoretical_mu.append( 1.0 * (A_copy + B_copy) / (lambd.dot(total_copy_per_locus)) ) + theoretical_p_binom.append( 1.0 * B_copy / (B_copy + A_copy) ) + theoretical_mu = np.hstack(theoretical_mu) + theoretical_p_binom = np.hstack(theoretical_p_binom) + return B_copy, A_copy, theoretical_mu, theoretical_p_binom, m.ObjVal + + +def composite_hmm_eval_objective(base_nb_mean, total_bb_RD, new_log_mu, new_scalefactors, new_p_binom, state_tuples, pred_cnv, B_copy, A_copy): + n_spots = base_nb_mean.shape[1] + n_individual_states = int(len(new_log_mu) / 2) + objectives_rdr = np.zeros( (n_individual_states, n_spots) ) + objectives_baf_B = np.zeros( (n_individual_states, n_spots) ) + objectives_baf_A = np.zeros( (n_individual_states, n_spots) ) + for c in range(n_spots): + this_pred_cnv = state_tuples[pred_cnv, c] + total_copy = (A_copy + B_copy)[this_pred_cnv % n_individual_states, 0] + # RDR + lambd = base_nb_mean[:,c] / np.sum(base_nb_mean[:,c]) + weight_total_copy = lambd.dot(total_copy) + for k in range(n_individual_states): + num_entries = np.sum( (base_nb_mean[:,c] > 0) & (this_pred_cnv % n_individual_states == k) ) + if c == 0: + objectives_rdr[k,c] = num_entries * np.abs( np.exp(new_log_mu[k]) * weight_total_copy - A_copy[k,0] - B_copy[k,0] ) + else: + objectives_rdr[k,c] = num_entries * np.abs( np.exp(new_log_mu[k] + new_scalefactors[c-1]) * weight_total_copy - A_copy[k,0] - B_copy[k,0] ) + # BAF + for k in range(n_individual_states): + num_entries = np.sum( (total_bb_RD[:,c] > 0) & (this_pred_cnv == k) ) + objectives_baf_B[k,c] = num_entries * np.abs( new_p_binom[k] * (A_copy[k,0] + B_copy[k,0]) - B_copy[k, 0] ) + num_entries = np.sum( (total_bb_RD[:,c] > 0) & (this_pred_cnv == k + n_individual_states) ) + objectives_baf_A[k,c] = num_entries * np.abs( new_p_binom[k] * (A_copy[k,0] + B_copy[k,0]) - A_copy[k, 0] ) + return objectives_rdr, objectives_baf_B, objectives_baf_A + +##### below are gurobi example ##### +# try: + +# # Create a new model +# m = gp.Model("mip1") + +# # Create variables +# x = m.addVar(vtype=GRB.BINARY, name="x") +# y = m.addVar(vtype=GRB.BINARY, name="y") +# z = m.addVar(vtype=GRB.BINARY, name="z") + +# # Set objective +# m.setObjective(x + y + 2 * z, GRB.MAXIMIZE) + +# # Add constraint: x + 2 y + 3 z <= 4 +# m.addConstr(x + 2 * y + 3 * z <= 4, "c0") + +# # Add constraint: x + y >= 1 +# m.addConstr(x + y >= 1, "c1") + +# # Optimize model +# m.optimize() + +# for v in m.getVars(): +# print('%s %g' % (v.VarName, v.X)) + +# print('Obj: %g' % m.ObjVal) + +# except gp.GurobiError as e: +# print('Error code ' + str(e.errno) + ': ' + str(e)) + +# except AttributeError: +# print('Encountered an attribute error') +""" \ No newline at end of file diff --git a/src/calicost/hmm_NB_BB_nophasing.py b/src/calicost/hmm_NB_BB_nophasing.py new file mode 100644 index 0000000..b6df5c1 --- /dev/null +++ b/src/calicost/hmm_NB_BB_nophasing.py @@ -0,0 +1,311 @@ +import logging +import numpy as np +from numba import njit +from scipy.stats import norm, multivariate_normal, poisson +import scipy.special +from scipy.optimize import minimize +from scipy.optimize import Bounds +from sklearn.mixture import GaussianMixture +from tqdm import trange +import statsmodels.api as sm +from statsmodels.base.model import GenericLikelihoodModel +import copy +from calicost.utils_distribution_fitting import * +from calicost.utils_hmm import * +import networkx as nx + + +############################################################ +# whole inference +############################################################ + +class hmm_nophasing(object): + def __init__(self, params="stmp", t=1-1e-4): + """ + Attributes + ---------- + params : str + Codes for parameters that need to be updated. The corresponding parameter can only be updated if it is included in this argument. "s" for start probability; "t" for transition probability; "m" for Negative Binomial RDR signal; "p" for Beta Binomial BAF signal. + + t : float + Determine initial self transition probability to be 1-t. + """ + self.params = params + self.t = t + # + @staticmethod + def compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + # AF from BetaBinom distribution + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + log_emission_baf[i, idx_nonzero_baf, s] = scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], p_binom[i, s] * taus[i, s], (1-p_binom[i, s]) * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + def compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop, **kwargs): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + # nb_mean = base_nb_mean[idx_nonzero_rdr,s] * (tumor_prop[s] * np.exp(log_mu[i, s]) + 1 - tumor_prop[s]) + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * (tumor_prop[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + 1 - tumor_prop[idx_nonzero_rdr,s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + # AF from BetaBinom distribution + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + # mix_p_A = p_binom[i, s] * tumor_prop[s] + 0.5 * (1 - tumor_prop[s]) + # mix_p_B = (1 - p_binom[i, s]) * tumor_prop[s] + 0.5 * (1 - tumor_prop[s]) + mix_p_A = p_binom[i, s] * tumor_prop[idx_nonzero_baf,s] + 0.5 * (1 - tumor_prop[idx_nonzero_baf,s]) + mix_p_B = (1 - p_binom[i, s]) * tumor_prop[idx_nonzero_baf,s] + 0.5 * (1 - tumor_prop[idx_nonzero_baf,s]) + log_emission_baf[i, idx_nonzero_baf, s] += scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], mix_p_A * taus[i, s], mix_p_B * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + @njit + def forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are n_states of paired states for (CNV, phasing) pairs. + Input + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output + log_alpha: size n_states * n_observations. log alpha[j, t] = log P(o_1, ... o_t, q_t = j | lambda). + ''' + n_obs = log_emission.shape[1] + n_states = log_emission.shape[0] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + # initialize log_alpha + log_alpha = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_alpha[:, cumlen] = log_startprob + np_sum_ax_squeeze(log_emission[:, cumlen, :], axis=1) + for t in np.arange(1, le): + for j in np.arange(log_emission.shape[0]): + for i in np.arange(log_emission.shape[0]): + buf[i] = log_alpha[i, (cumlen + t - 1)] + log_transmat[i, j] + log_alpha[j, (cumlen + t)] = mylogsumexp(buf) + np.sum(log_emission[j, (cumlen + t), :]) + cumlen += le + return log_alpha + # + @staticmethod + @njit + def backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are n_states of paired states for (CNV, phasing) pairs. + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output + log_beta: size 2*n_states * n_observations. log beta[i, t] = log P(o_{t+1}, ..., o_T | q_t = i, lambda). + ''' + n_obs = log_emission.shape[1] + n_states = log_emission.shape[0] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + # initialize log_beta + log_beta = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_beta[:, (cumlen + le - 1)] = 0 + for t in np.arange(le-2, -1, -1): + for i in np.arange(log_emission.shape[0]): + for j in np.arange(log_emission.shape[0]): + buf[j] = log_beta[j, (cumlen + t + 1)] + log_transmat[i, j] + np.sum(log_emission[j, (cumlen + t + 1), :]) + log_beta[i, (cumlen + t)] = mylogsumexp(buf) + cumlen += le + return log_beta + + # + def run_baum_welch_nb_bb(self, X, lengths, n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat=None, tumor_prop=None, tp_weight_by_mu=None, \ + fix_NB_dispersion=False, shared_NB_dispersion=False, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + is_diag=False, init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, max_iter=100, tol=1e-4, **kwargs): + ''' + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + base_nb_mean: size of n_observations * n_spots. + In NB-BetaBinom model, n_components = 2 + Intermediate + log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. + alpha: size of n_states. Dispersioon parameter of each HMM state. + ''' + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + assert n_comp == 2 + # initialize NB logmean shift and BetaBinom prob + log_mu = np.vstack([np.linspace(-0.1, 0.1, n_states) for r in range(n_spots)]).T if init_log_mu is None else init_log_mu + p_binom = np.vstack([np.linspace(0.05, 0.45, n_states) for r in range(n_spots)]).T if init_p_binom is None else init_p_binom + # initialize (inverse of) dispersion param in NB and BetaBinom + alphas = 0.1 * np.ones((n_states, n_spots)) if init_alphas is None else init_alphas + taus = 30 * np.ones((n_states, n_spots)) if init_taus is None else init_taus + # initialize start probability and emission probability + log_startprob = np.log( np.ones(n_states) / n_states ) + if n_states > 1: + transmat = np.ones((n_states, n_states)) * (1-self.t) / (n_states-1) + np.fill_diagonal(transmat, self.t) + log_transmat = np.log(transmat) + else: + log_transmat = np.zeros((1,1)) + # a trick to speed up BetaBinom optimization: taking only unique values of (B allele count, total SNP covering read count) + unique_values_nb, mapping_matrices_nb = construct_unique_matrix(X[:,0,:], base_nb_mean) + unique_values_bb, mapping_matrices_bb = construct_unique_matrix(X[:,1,:], total_bb_RD) + # EM algorithm + for r in trange(max_iter): + # E step + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmm_nophasing.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + else: + log_emission_rdr, log_emission_baf = hmm_nophasing.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmm_nophasing.forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_beta = hmm_nophasing.backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + log_xi = compute_posterior_transition_nophasing(log_alpha, log_beta, log_transmat, log_emission) + # M step + if "s" in self.params: + new_log_startprob = update_startprob_nophasing(lengths, log_gamma) + new_log_startprob = new_log_startprob.flatten() + else: + new_log_startprob = log_startprob + if "t" in self.params: + new_log_transmat = update_transition_nophasing(log_xi, is_diag=is_diag) + else: + new_log_transmat = log_transmat + if "m" in self.params: + if tumor_prop is None: + new_log_mu, new_alphas = update_emission_params_nb_nophasing_uniqvalues(unique_values_nb, mapping_matrices_nb, log_gamma, alphas, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu, new_alphas = update_emission_params_nb_nophasing_uniqvalues_mix(unique_values_nb, mapping_matrices_nb, log_gamma, alphas, tumor_prop, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu = log_mu + new_alphas = alphas + if "p" in self.params: + if tumor_prop is None: + new_p_binom, new_taus = update_emission_params_bb_nophasing_uniqvalues(unique_values_bb, mapping_matrices_bb, log_gamma, taus, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + new_p_binom, new_taus = update_emission_params_bb_nophasing_uniqvalues_mix(unique_values_bb, mapping_matrices_bb, log_gamma, taus, tumor_prop, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + new_p_binom = p_binom + new_taus = taus + # check convergence + print( np.mean(np.abs( np.exp(new_log_startprob) - np.exp(log_startprob) )), \ + np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )), \ + np.mean(np.abs(new_log_mu - log_mu)),\ + np.mean(np.abs(new_p_binom - p_binom)) ) + print( np.hstack([new_log_mu, new_p_binom]) ) + if np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )) < tol and \ + np.mean(np.abs(new_log_mu - log_mu)) < tol and np.mean(np.abs(new_p_binom - p_binom)) < tol: + break + log_startprob = new_log_startprob + log_transmat = new_log_transmat + log_mu = new_log_mu + alphas = new_alphas + p_binom = new_p_binom + taus = new_taus + return new_log_mu, new_alphas, new_p_binom, new_taus, new_log_startprob, new_log_transmat, log_gamma + + diff --git a/src/calicost/hmm_NB_BB_nophasing_v2.py b/src/calicost/hmm_NB_BB_nophasing_v2.py new file mode 100644 index 0000000..e5a6971 --- /dev/null +++ b/src/calicost/hmm_NB_BB_nophasing_v2.py @@ -0,0 +1,342 @@ +import logging +import numpy as np +from numba import njit +from scipy.stats import norm, multivariate_normal, poisson +import scipy.special +from scipy.optimize import minimize +from scipy.optimize import Bounds +from sklearn.mixture import GaussianMixture +from tqdm import trange +import statsmodels.api as sm +from statsmodels.base.model import GenericLikelihoodModel +import copy +from calicost.utils_distribution_fitting import * +from calicost.utils_hmm import * +import networkx as nx + +""" +Joint NB-BB HMM that accounts for tumor/normal genome proportions. Tumor genome proportion is weighted by mu in BB distribution. +""" + +############################################################ +# whole inference +############################################################ + +class hmm_nophasing_v2(object): + def __init__(self, params="stmp", t=1-1e-4): + """ + Attributes + ---------- + params : str + Codes for parameters that need to be updated. The corresponding parameter can only be updated if it is included in this argument. "s" for start probability; "t" for transition probability; "m" for Negative Binomial RDR signal; "p" for Beta Binomial BAF signal. + + t : float + Determine initial self transition probability to be 1-t. + """ + self.params = params + self.t = t + # + @staticmethod + def compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + # AF from BetaBinom distribution + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + log_emission_baf[i, idx_nonzero_baf, s] = scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], p_binom[i, s] * taus[i, s], (1-p_binom[i, s]) * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + def compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop, **kwargs): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + # nb_mean = base_nb_mean[idx_nonzero_rdr,s] * (tumor_prop[s] * np.exp(log_mu[i, s]) + 1 - tumor_prop[s]) + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * (tumor_prop[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + 1 - tumor_prop[idx_nonzero_rdr,s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + # AF from BetaBinom distribution + if ("logmu_shift" in kwargs) and ("sample_length" in kwargs): + this_weighted_tp = [] + for c in range(len(kwargs["sample_length"])): + range_s = np.sum(kwargs["sample_length"][:c]) + range_t = np.sum(kwargs["sample_length"][:(c+1)]) + this_weighted_tp.append( tumor_prop[range_s:range_t,s] * np.exp(log_mu[i, s] - kwargs["logmu_shift"][c,s]) / (tumor_prop[range_s:range_t,s] * np.exp(log_mu[i, s] - kwargs["logmu_shift"][c,s]) + 1 - tumor_prop[range_s:range_t,s]) ) + this_weighted_tp = np.concatenate(this_weighted_tp) + else: + this_weighted_tp = tumor_prop[:,s] + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + mix_p_A = p_binom[i, s] * this_weighted_tp[idx_nonzero_baf] + 0.5 * (1 - this_weighted_tp[idx_nonzero_baf]) + mix_p_B = (1 - p_binom[i, s]) * this_weighted_tp[idx_nonzero_baf] + 0.5 * (1 - this_weighted_tp[idx_nonzero_baf]) + log_emission_baf[i, idx_nonzero_baf, s] += scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], mix_p_A * taus[i, s], mix_p_B * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + @njit + def forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are n_states of paired states for (CNV, phasing) pairs. + Input + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output + log_alpha: size n_states * n_observations. log alpha[j, t] = log P(o_1, ... o_t, q_t = j | lambda). + ''' + n_obs = log_emission.shape[1] + n_states = log_emission.shape[0] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + # initialize log_alpha + log_alpha = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_alpha[:, cumlen] = log_startprob + np_sum_ax_squeeze(log_emission[:, cumlen, :], axis=1) + for t in np.arange(1, le): + for j in np.arange(log_emission.shape[0]): + for i in np.arange(log_emission.shape[0]): + buf[i] = log_alpha[i, (cumlen + t - 1)] + log_transmat[i, j] + log_alpha[j, (cumlen + t)] = mylogsumexp(buf) + np.sum(log_emission[j, (cumlen + t), :]) + cumlen += le + return log_alpha + # + @staticmethod + @njit + def backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are n_states of paired states for (CNV, phasing) pairs. + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output + log_beta: size 2*n_states * n_observations. log beta[i, t] = log P(o_{t+1}, ..., o_T | q_t = i, lambda). + ''' + n_obs = log_emission.shape[1] + n_states = log_emission.shape[0] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + # initialize log_beta + log_beta = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_beta[:, (cumlen + le - 1)] = 0 + for t in np.arange(le-2, -1, -1): + for i in np.arange(log_emission.shape[0]): + for j in np.arange(log_emission.shape[0]): + buf[j] = log_beta[j, (cumlen + t + 1)] + log_transmat[i, j] + np.sum(log_emission[j, (cumlen + t + 1), :]) + log_beta[i, (cumlen + t)] = mylogsumexp(buf) + cumlen += le + return log_beta + + # + def run_baum_welch_nb_bb(self, X, lengths, n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat=None, tumor_prop=None, \ + fix_NB_dispersion=False, shared_NB_dispersion=False, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + is_diag=False, init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, max_iter=100, tol=1e-4, **kwargs): + ''' + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + base_nb_mean: size of n_observations * n_spots. + In NB-BetaBinom model, n_components = 2 + Intermediate + log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. + alpha: size of n_states. Dispersioon parameter of each HMM state. + ''' + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + assert n_comp == 2 + # initialize NB logmean shift and BetaBinom prob + log_mu = np.vstack([np.linspace(-0.1, 0.1, n_states) for r in range(n_spots)]).T if init_log_mu is None else init_log_mu + p_binom = np.vstack([np.linspace(0.05, 0.45, n_states) for r in range(n_spots)]).T if init_p_binom is None else init_p_binom + # initialize (inverse of) dispersion param in NB and BetaBinom + alphas = 0.1 * np.ones((n_states, n_spots)) if init_alphas is None else init_alphas + taus = 30 * np.ones((n_states, n_spots)) if init_taus is None else init_taus + # initialize start probability and emission probability + log_startprob = np.log( np.ones(n_states) / n_states ) + if n_states > 1: + transmat = np.ones((n_states, n_states)) * (1-self.t) / (n_states-1) + np.fill_diagonal(transmat, self.t) + log_transmat = np.log(transmat) + else: + log_transmat = np.zeros((1,1)) + # initialize log_gamma + log_gamma = kwargs["log_gamma"] if "log_gamma" in kwargs else None + # a trick to speed up BetaBinom optimization: taking only unique values of (B allele count, total SNP covering read count) + unique_values_nb, mapping_matrices_nb = construct_unique_matrix(X[:,0,:], base_nb_mean) + unique_values_bb, mapping_matrices_bb = construct_unique_matrix(X[:,1,:], total_bb_RD) + # EM algorithm + for r in trange(max_iter): + # E step + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmm_nophasing_v2.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + else: + # compute mu as adjusted RDR + if ((not log_gamma is None) or (r > 0)) and ("m" in self.params): + logmu_shift = [] + for c in range(len(kwargs["sample_length"])): + this_pred_cnv = np.argmax(log_gamma[:,np.sum(kwargs["sample_length"][:c]):np.sum(kwargs["sample_length"][:(c+1)])], axis=0)%n_states + logmu_shift.append( scipy.special.logsumexp(log_mu[this_pred_cnv,:] + np.log(kwargs["lambd"]).reshape(-1,1), axis=0) ) + logmu_shift = np.vstack(logmu_shift) + log_emission_rdr, log_emission_baf = hmm_nophasing_v2.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop, logmu_shift=logmu_shift, sample_length=kwargs["sample_length"]) + else: + log_emission_rdr, log_emission_baf = hmm_nophasing_v2.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmm_nophasing_v2.forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_beta = hmm_nophasing_v2.backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + log_xi = compute_posterior_transition_nophasing(log_alpha, log_beta, log_transmat, log_emission) + # M step + if "s" in self.params: + new_log_startprob = update_startprob_nophasing(lengths, log_gamma) + new_log_startprob = new_log_startprob.flatten() + else: + new_log_startprob = log_startprob + if "t" in self.params: + new_log_transmat = update_transition_nophasing(log_xi, is_diag=is_diag) + else: + new_log_transmat = log_transmat + if "m" in self.params: + if tumor_prop is None: + new_log_mu, new_alphas = update_emission_params_nb_nophasing_uniqvalues(unique_values_nb, mapping_matrices_nb, log_gamma, alphas, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu, new_alphas = update_emission_params_nb_nophasing_uniqvalues_mix(unique_values_nb, mapping_matrices_nb, log_gamma, alphas, tumor_prop, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu = log_mu + new_alphas = alphas + if "p" in self.params: + if tumor_prop is None: + new_p_binom, new_taus = update_emission_params_bb_nophasing_uniqvalues(unique_values_bb, mapping_matrices_bb, log_gamma, taus, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + # compute mu as adjusted RDR + if ("m" in self.params): + mu = [] + for c in range(len(kwargs["sample_length"])): + this_pred_cnv = np.argmax(log_gamma[:,np.sum(kwargs["sample_length"][:c]):np.sum(kwargs["sample_length"][:(c+1)])], axis=0)%n_states + mu.append( np.exp(new_log_mu[this_pred_cnv,:]) / np.sum(np.exp(new_log_mu[this_pred_cnv,:]) * kwargs["lambd"].reshape(-1,1), axis=0, keepdims=True) ) + mu = np.vstack(mu) + weighted_tp = (tumor_prop * mu) / (tumor_prop * mu + 1 - tumor_prop) + else: + weighted_tp = tumor_prop + new_p_binom, new_taus = update_emission_params_bb_nophasing_uniqvalues_mix(unique_values_bb, mapping_matrices_bb, log_gamma, taus, weighted_tp, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + new_p_binom = p_binom + new_taus = taus + # check convergence + print( np.mean(np.abs( np.exp(new_log_startprob) - np.exp(log_startprob) )), \ + np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )), \ + np.mean(np.abs(new_log_mu - log_mu)),\ + np.mean(np.abs(new_p_binom - p_binom)) ) + print( np.hstack([new_log_mu, new_p_binom]) ) + if np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )) < tol and \ + np.mean(np.abs(new_log_mu - log_mu)) < tol and np.mean(np.abs(new_p_binom - p_binom)) < tol: + break + log_startprob = new_log_startprob + log_transmat = new_log_transmat + log_mu = new_log_mu + alphas = new_alphas + p_binom = new_p_binom + taus = new_taus + return new_log_mu, new_alphas, new_p_binom, new_taus, new_log_startprob, new_log_transmat, log_gamma + + diff --git a/src/calicost/hmm_NB_BB_phaseswitch.py b/src/calicost/hmm_NB_BB_phaseswitch.py new file mode 100644 index 0000000..109cd41 --- /dev/null +++ b/src/calicost/hmm_NB_BB_phaseswitch.py @@ -0,0 +1,870 @@ +import logging +import numpy as np +from numba import njit +from scipy.stats import norm, multivariate_normal, poisson +import scipy.special +from scipy.optimize import minimize +from scipy.optimize import Bounds +from sklearn.mixture import GaussianMixture +from tqdm import trange +import statsmodels.api as sm +from statsmodels.base.model import GenericLikelihoodModel +import copy +from calicost.utils_hmm import * +from calicost.utils_distribution_fitting import * +from calicost.hmm_NB_BB_nophasing import * +from calicost.hmm_NB_BB_nophasing_v2 import * +import networkx as nx + + +############################################################ +# whole inference +############################################################ + +class hmm_sitewise(object): + def __init__(self, params="stmp", t=1-1e-4): + """ + Attributes + ---------- + params : str + Codes for parameters that need to be updated. The corresponding parameter can only be updated if it is included in this argument. "s" for start probability; "t" for transition probability; "m" for Negative Binomial RDR signal; "p" for Beta Binomial BAF signal. + + t : float + Determine initial self transition probability to be 1-t. + """ + self.params = params + self.t = t + # + @staticmethod + def compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (2*n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((2 * n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((2 * n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + log_emission_rdr[i + n_states, idx_nonzero_rdr, s] = log_emission_rdr[i, idx_nonzero_rdr, s] + # AF from BetaBinom distribution + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + log_emission_baf[i, idx_nonzero_baf, s] = scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], p_binom[i, s] * taus[i, s], (1-p_binom[i, s]) * taus[i, s]) + log_emission_baf[i + n_states, idx_nonzero_baf, s] = scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], (1-p_binom[i, s]) * taus[i, s], p_binom[i, s] * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + def compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop, **kwargs): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + taus : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (2*n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_mu.shape[0] + # initialize log_emission + log_emission_rdr = np.zeros((2 * n_states, n_obs, n_spots)) + log_emission_baf = np.zeros((2 * n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from NB distribution + idx_nonzero_rdr = np.where(base_nb_mean[:,s] > 0)[0] + if len(idx_nonzero_rdr) > 0: + nb_mean = base_nb_mean[idx_nonzero_rdr,s] * (tumor_prop[idx_nonzero_rdr,s] * np.exp(log_mu[i, s]) + 1 - tumor_prop[idx_nonzero_rdr,s]) + # nb_std = np.sqrt(nb_mean + alphas[i, s] * nb_mean**2) + n, p = convert_params(nb_mean, alphas[i, s]) + log_emission_rdr[i, idx_nonzero_rdr, s] = scipy.stats.nbinom.logpmf(X[idx_nonzero_rdr, 0, s], n, p) + log_emission_rdr[i + n_states, idx_nonzero_rdr, s] = log_emission_rdr[i, idx_nonzero_rdr, s] + # AF from BetaBinom distribution + idx_nonzero_baf = np.where(total_bb_RD[:,s] > 0)[0] + if len(idx_nonzero_baf) > 0: + mix_p_A = p_binom[i, s] * tumor_prop[idx_nonzero_baf,s] + 0.5 * (1 - tumor_prop[idx_nonzero_baf,s]) + mix_p_B = (1 - p_binom[i, s]) * tumor_prop[idx_nonzero_baf,s] + 0.5 * (1 - tumor_prop[idx_nonzero_baf,s]) + log_emission_baf[i, idx_nonzero_baf, s] += scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], mix_p_A * taus[i, s], mix_p_B * taus[i, s]) + log_emission_baf[i + n_states, idx_nonzero_baf, s] += scipy.stats.betabinom.logpmf(X[idx_nonzero_baf,1,s], total_bb_RD[idx_nonzero_baf,s], mix_p_B * taus[i, s], mix_p_A * taus[i, s]) + return log_emission_rdr, log_emission_baf + # + @staticmethod + @njit + def forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are 2 * n_states of paired states for (CNV, phasing) pairs. + Input + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: 2*n_states * n_observations * n_spots. Log probability. + log_sitewise_transmat: n_observations, the log transition probability of phase switch. + Output + log_alpha: size 2n_states * n_observations. log alpha[j, t] = log P(o_1, ... o_t, q_t = j | lambda). + ''' + n_obs = log_emission.shape[1] + n_states = int(np.ceil(log_emission.shape[0] / 2)) + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) + # initialize log_alpha + log_alpha = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + combined_log_startprob = np.log(0.5) + np.append(log_startprob,log_startprob) + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_alpha[:, cumlen] = combined_log_startprob + np_sum_ax_squeeze(log_emission[:, cumlen, :], axis=1) + for t in np.arange(1, le): + phases_switch_mat = np.array([[log_sitewise_self_transmat[cumlen + t-1], log_sitewise_transmat[cumlen + t-1]], [log_sitewise_transmat[cumlen + t-1], log_sitewise_self_transmat[cumlen + t-1] ]]) + combined_transmat = np.kron( np.exp(phases_switch_mat), np.exp(log_transmat) ) + combined_transmat = np.log(combined_transmat) + for j in np.arange(log_emission.shape[0]): + for i in np.arange(log_emission.shape[0]): + buf[i] = log_alpha[i, (cumlen + t - 1)] + combined_transmat[i, j] + log_alpha[j, (cumlen + t)] = mylogsumexp(buf) + np.sum(log_emission[j, (cumlen + t), :]) + cumlen += le + return log_alpha + # + @staticmethod + @njit + def backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are 2 * n_states of paired states for (CNV, phasing) pairs. + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: 2*n_states * n_observations * n_spots. Log probability. + log_sitewise_transmat: n_observations, the log transition probability of phase switch. + Output + log_beta: size 2*n_states * n_observations. log beta[i, t] = log P(o_{t+1}, ..., o_T | q_t = i, lambda). + ''' + n_obs = log_emission.shape[1] + n_states = int(np.ceil(log_emission.shape[0] / 2)) + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) + # initialize log_beta + log_beta = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_beta[:, (cumlen + le - 1)] = 0 + for t in np.arange(le-2, -1, -1): + phases_switch_mat = np.array([[log_sitewise_self_transmat[cumlen + t], log_sitewise_transmat[cumlen + t]], [log_sitewise_transmat[cumlen + t], log_sitewise_self_transmat[cumlen + t] ]]) + combined_transmat = np.kron( np.exp(phases_switch_mat), np.exp(log_transmat) ) + combined_transmat = np.log(combined_transmat) + for i in np.arange(log_emission.shape[0]): + for j in np.arange(log_emission.shape[0]): + buf[j] = log_beta[j, (cumlen + t + 1)] + combined_transmat[i, j] + np.sum(log_emission[j, (cumlen + t + 1), :]) + log_beta[i, (cumlen + t)] = mylogsumexp(buf) + cumlen += le + return log_beta + # + def run_baum_welch_nb_bb(self, X, lengths, n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat, tumor_prop=None, \ + fix_NB_dispersion=False, shared_NB_dispersion=False, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + is_diag=False, init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, max_iter=100, tol=1e-4): + ''' + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + base_nb_mean: size of n_observations * n_spots. + In NB-BetaBinom model, n_components = 2 + Intermediate + log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. + alpha: size of n_states. Dispersioon parameter of each HMM state. + ''' + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + assert n_comp == 2 + # initialize NB logmean shift and BetaBinom prob + log_mu = np.vstack([np.linspace(-0.1, 0.1, n_states) for r in range(n_spots)]).T if init_log_mu is None else init_log_mu + p_binom = np.vstack([np.linspace(0.05, 0.45, n_states) for r in range(n_spots)]).T if init_p_binom is None else init_p_binom + # initialize (inverse of) dispersion param in NB and BetaBinom + alphas = 0.1 * np.ones((n_states, n_spots)) if init_alphas is None else init_alphas + taus = 30 * np.ones((n_states, n_spots)) if init_taus is None else init_taus + # initialize start probability and emission probability + log_startprob = np.log( np.ones(n_states) / n_states ) + if n_states > 1: + transmat = np.ones((n_states, n_states)) * (1-self.t) / (n_states-1) + np.fill_diagonal(transmat, self.t) + log_transmat = np.log(transmat) + else: + log_transmat = np.zeros((1,1)) + # a trick to speed up BetaBinom optimization: taking only unique values of (B allele count, total SNP covering read count) + unique_values_nb, mapping_matrices_nb = construct_unique_matrix(X[:,0,:], base_nb_mean) + unique_values_bb, mapping_matrices_bb = construct_unique_matrix(X[:,1,:], total_bb_RD) + # EM algorithm + for r in trange(max_iter): + # E step + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmm_sitewise.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + else: + log_emission_rdr, log_emission_baf = hmm_sitewise.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, tumor_prop) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmm_sitewise.forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_beta = hmm_sitewise.backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + log_xi = compute_posterior_transition_sitewise(log_alpha, log_beta, log_transmat, log_emission) + # M step + if "s" in self.params: + new_log_startprob = update_startprob_sitewise(lengths, log_gamma) + new_log_startprob = new_log_startprob.flatten() + else: + new_log_startprob = log_startprob + if "t" in self.params: + new_log_transmat = update_transition_sitewise(log_xi, is_diag=is_diag) + else: + new_log_transmat = log_transmat + if "m" in self.params: + # new_log_mu, new_alphas = update_emission_params_nb_sitewise(X[:,0,:], log_gamma, base_nb_mean, alphas, start_log_mu=log_mu, \ + # fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + if tumor_prop is None: + new_log_mu, new_alphas = update_emission_params_nb_sitewise_uniqvalues(unique_values_nb, mapping_matrices_nb, log_gamma, base_nb_mean, alphas, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu, new_alphas = update_emission_params_nb_sitewise_uniqvalues_mix(unique_values_nb, mapping_matrices_nb, log_gamma, base_nb_mean, alphas, tumor_prop, start_log_mu=log_mu, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion) + else: + new_log_mu = log_mu + new_alphas = alphas + if "p" in self.params: + if tumor_prop is None: + new_p_binom, new_taus = update_emission_params_bb_sitewise_uniqvalues(unique_values_bb, mapping_matrices_bb, log_gamma, total_bb_RD, taus, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + new_p_binom, new_taus = update_emission_params_bb_sitewise_uniqvalues_mix(unique_values_bb, mapping_matrices_bb, log_gamma, total_bb_RD, taus, tumor_prop, start_p_binom=p_binom, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion) + else: + new_p_binom = p_binom + new_taus = taus + # check convergence + print( np.mean(np.abs( np.exp(new_log_startprob) - np.exp(log_startprob) )), \ + np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )), \ + np.mean(np.abs(new_log_mu - log_mu)),\ + np.mean(np.abs(new_p_binom - p_binom)) ) + print( np.hstack([new_log_mu, new_p_binom]) ) + if np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )) < tol and \ + np.mean(np.abs(new_log_mu - log_mu)) < tol and np.mean(np.abs(new_p_binom - p_binom)) < tol: + break + log_startprob = new_log_startprob + log_transmat = new_log_transmat + log_mu = new_log_mu + alphas = new_alphas + p_binom = new_p_binom + taus = new_taus + return new_log_mu, new_alphas, new_p_binom, new_taus, new_log_startprob, new_log_transmat, log_gamma + + +def posterior_nb_bb_sitewise(X, lengths, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, log_startprob, log_transmat, log_sitewise_transmat): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + lengths : array, shape (n_chromosomes,) + Number genes (or bins) per chromosome, the sum of this vector should be equal to n_observations. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log read depth shift of each CNV states. + + alphas : array, shape (n_states, n_spots) + Inverse of dispersion in NB distribution of each state. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + MAF of each CNV states. + + taus : array, shape (n_states, n_spots) + Inverse of dispersion of Beta-Binomial distribution of each state. + + log_startprob : array, shape (n_states,) + Log of start probability. + + log_transmat : array, shape (n_states, n_states) + Log of transition probability across states. + + log_sitewise_transmat : array, shape (n_observations) + Log of phase switch probability of each gene (or bin). + """ + log_emission_rdr, log_emission_baf = hmm_sitewise.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmm_sitewise.forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_beta = hmm_sitewise.backward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + return log_gamma + + +def loglikelihood_nb_bb_sitewise(X, lengths, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, log_startprob, log_transmat, log_sitewise_transmat): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + lengths : array, shape (n_chromosomes,) + Number genes (or bins) per chromosome, the sum of this vector should be equal to n_observations. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log read depth shift of each CNV states. + + alphas : array, shape (n_states, n_spots) + Inverse of dispersion in NB distribution of each state. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_binom : array, shape (n_states, n_spots) + MAF of each CNV states. + + taus : array, shape (n_states, n_spots) + Inverse of dispersion of Beta-Binomial distribution of each state. + + log_startprob : array, shape (n_states,) + Log of start probability. + + log_transmat : array, shape (n_states, n_states) + Log of transition probability across states. + + log_sitewise_transmat : array, shape (n_observations) + Log of phase switch probability of each gene (or bin). + """ + log_emission_rdr, log_emission_baf = hmm_sitewise.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmm_sitewise.forward_lattice(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + return np.sum(scipy.special.logsumexp(log_alpha[:,np.cumsum(lengths)-1], axis=0)), log_alpha + + +def viterbi_nb_bb_sitewise(X, lengths, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus, log_startprob, log_transmat, log_sitewise_transmat): + ''' + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + exposures: size of n_observations * n_spots. + base_prob: size of n_observations. The expression probability derived from normal spots. + log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. + alpha: size of n_states. Dispersioon parameter of each HMM state. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + Output +# log_prob: a scalar. + labels: size of n_observations. + Intermediate + log_emission: n_states * n_observations * n_spots. Log probability. + log_v: n_states * n_observations per chromosome. Log of viterbi DP table. v[i,t] = max_{q_1, ..., q_{t-1}} P(o_1, q_1, ..., o_{t-1}, q_{t-1}, o_t, q_t=i | lambda). + ''' + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = log_transmat.shape[0] + log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) + log_emission_rdr, log_emission_baf = hmm_sitewise.compute_emission_probability_nb_betabinom(X, base_nb_mean, log_mu, alphas, total_bb_RD, p_binom, taus) + log_emission = log_emission_rdr + log_emission_baf + # initialize viterbi DP table and backtracking table + labels = np.array([]) + merged_labels = np.array([]) + cumlen = 0 + for le in lengths: + log_v = np.zeros((2*n_states, le)) + bt = np.zeros((2*n_states, le)) + for t in np.arange(le): + if cumlen == 0 and t == 0: + log_v[:, 0] = np.mean(log_emission[:,0,:], axis=1) + np.append(log_startprob,log_startprob) + np.log(0.5) + continue + for i in np.arange(2*n_states): + if t > 0: + tmp = log_v[:, (t-1)] + np.append(log_transmat[:,i - n_states * int(i/n_states)], log_transmat[:,i - n_states * int(i/n_states)]) + np.sum(log_emission[i, (cumlen+t), :]) + else: + tmp = np.append(log_startprob[i - n_states * int(i/n_states)], log_startprob[i - n_states * int(i/n_states)]) + np.sum(log_emission[i, (cumlen+t), :]) + bt[i, t] = np.argmax(tmp) + log_v[i, t] = np.max(tmp) + # backtracking to get the sequence + chr_labels = [ np.argmax(log_v[:,-1]) ] + + if cumlen == 0: + for t2 in np.arange(le-1, 0, -1): + chr_labels.append( int(bt[chr_labels[-1],t2])) + else: + for t2 in np.arange(le-2, -1, -1): + chr_labels.append( int(bt[chr_labels[-1],t2])) + + chr_labels = np.array(chr_labels[::-1]).astype(int) + # merge two phases + chr_merged_labels = copy.copy(chr_labels) + chr_merged_labels[chr_merged_labels >= n_states] = chr_merged_labels[chr_merged_labels >= n_states] - n_states + + if cumlen == 0: + labels = chr_labels + merged_labels = chr_merged_labels + else: + labels = np.append(labels, chr_labels) + merged_labels = np.append(merged_labels, chr_merged_labels) + + cumlen += le + return labels, merged_labels + + +def pipeline_baum_welch(output_prefix, X, lengths, n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat, tumor_prop=None, \ + hmmclass=hmm_sitewise, params="smp", t=1-1e-6, random_state=0, \ + in_log_space=True, only_minor=False, fix_NB_dispersion=False, shared_NB_dispersion=True, fix_BB_dispersion=False, shared_BB_dispersion=True, \ + init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, is_diag=True, max_iter=100, tol=1e-4, **kwargs): + """ + tumor_prop : array, (n_obs, n_spots) + Probability of sequencing a tumor read. (tumor cell proportion weighted by ploidy) + + """ + # initialization + n_spots = X.shape[2] + if ((init_log_mu is None) and ("m" in params)) or ((init_p_binom is None) and ("p" in params)): + tmp_log_mu, tmp_p_binom = initialization_by_gmm(n_states, X, base_nb_mean, total_bb_RD, params, random_state=random_state, in_log_space=in_log_space, only_minor=only_minor) + if (init_log_mu is None) and ("m" in params): + init_log_mu = tmp_log_mu + if (init_p_binom is None) and ("p" in params): + init_p_binom = tmp_p_binom + print(f"init_log_mu = {init_log_mu}") + print(f"init_p_binom = {init_p_binom}") + + # fit HMM-NB-BetaBinom + # new_log_mu, new_alphas, new_p_binom, new_taus, new_log_startprob, new_log_transmat = hmmmodel.run_baum_welch_nb_bb(X, lengths, \ + # n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat, tumor_prop, \ + # fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, \ + # fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + # is_diag=is_diag, init_log_mu=init_log_mu, init_p_binom=init_p_binom, init_alphas=init_alphas, init_taus=init_taus, \ + # max_iter=max_iter, tol=tol) + hmmmodel = hmmclass(params=params, t=t) + remain_kwargs = {k:v for k,v in kwargs.items() if k in ["lambd", "sample_length", "log_gamma"]} + new_log_mu, new_alphas, new_p_binom, new_taus, new_log_startprob, new_log_transmat, log_gamma = hmmmodel.run_baum_welch_nb_bb(X, lengths, \ + n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat, tumor_prop, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + is_diag=is_diag, init_log_mu=init_log_mu, init_p_binom=init_p_binom, init_alphas=init_alphas, init_taus=init_taus, \ + max_iter=max_iter, tol=tol, **remain_kwargs) + + # likelihood + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom(X, base_nb_mean, new_log_mu, new_alphas, total_bb_RD, new_p_binom, new_taus) + log_emission = log_emission_rdr + log_emission_baf + else: + if ("m" in params) and ("sample_length" in kwargs): + logmu_shift = [] + for c in range(len(kwargs["sample_length"])): + this_pred_cnv = np.argmax(log_gamma[:,np.sum(kwargs["sample_length"][:c]):np.sum(kwargs["sample_length"][:(c+1)])], axis=0)%n_states + logmu_shift.append( scipy.special.logsumexp(new_log_mu[this_pred_cnv,:] + np.log(kwargs["lambd"]).reshape(-1,1), axis=0) ) + logmu_shift = np.vstack(logmu_shift) + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, new_log_mu, new_alphas, total_bb_RD, new_p_binom, new_taus, tumor_prop, logmu_shift=logmu_shift, sample_length=kwargs["sample_length"]) + else: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, new_log_mu, new_alphas, total_bb_RD, new_p_binom, new_taus, tumor_prop) + # log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(X, base_nb_mean, new_log_mu, new_alphas, total_bb_RD, new_p_binom, new_taus, tumor_prop) + log_emission = log_emission_rdr + log_emission_baf + log_alpha = hmmclass.forward_lattice(lengths, new_log_transmat, new_log_startprob, log_emission, log_sitewise_transmat) + llf = np.sum(scipy.special.logsumexp(log_alpha[:,np.cumsum(lengths)-1], axis=0)) + + log_beta = hmmclass.backward_lattice(lengths, new_log_transmat, new_log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + pred = np.argmax(log_gamma, axis=0) + pred_cnv = pred % n_states + + # save results + if not output_prefix is None: + tmp = np.log10(1 - t) + np.savez(f"{output_prefix}_nstates{n_states}_{params}_{tmp:.0f}_seed{random_state}.npz", \ + new_log_mu=new_log_mu, new_alphas=new_alphas, new_p_binom=new_p_binom, new_taus=new_taus, \ + new_log_startprob=new_log_startprob, new_log_transmat=new_log_transmat, log_gamma=log_gamma, pred_cnv=pred_cnv, llf=llf) + else: + res = {"new_log_mu":new_log_mu, "new_alphas":new_alphas, "new_p_binom":new_p_binom, "new_taus":new_taus, \ + "new_log_startprob":new_log_startprob, "new_log_transmat":new_log_transmat, "log_gamma":log_gamma, "pred_cnv":pred_cnv, "llf":llf} + return res + + +def eval_neymanpearson_bafonly(log_emission_baf_c1, pred_c1, log_emission_baf_c2, pred_c2, bidx, n_states, res, p): + assert log_emission_baf_c1.shape[0] == n_states or log_emission_baf_c1.shape[0] == 2 * n_states + # likelihood under the corresponding state + llf_original = np.append(log_emission_baf_c1[pred_c1[bidx], bidx], log_emission_baf_c2[pred_c2[bidx], bidx]).reshape(-1,1) + # likelihood under the switched state + if log_emission_baf_c1.shape[0] == 2 * n_states: + if (res["new_p_binom"][p[0],0] > 0.5) == (res["new_p_binom"][p[1],0] > 0.5): + switch_pred_c1 = n_states * (pred_c1 >= n_states) + (pred_c2 % n_states) + switch_pred_c2 = n_states * (pred_c2 >= n_states) + (pred_c1 % n_states) + else: + switch_pred_c1 = n_states * (pred_c1 < n_states) + (pred_c2 % n_states) + switch_pred_c2 = n_states * (pred_c2 < n_states) + (pred_c1 % n_states) + else: + switch_pred_c1 = pred_c2 + switch_pred_c2 = pred_c1 + llf_switch = np.append(log_emission_baf_c1[switch_pred_c1[bidx], bidx], log_emission_baf_c2[switch_pred_c2[bidx], bidx]).reshape(-1,1) + # log likelihood difference + return np.mean(llf_original) - np.mean(llf_switch) + + +def eval_neymanpearson_rdrbaf(log_emission_rdr_c1, log_emission_baf_c1, pred_c1, log_emission_rdr_c2, log_emission_baf_c2, pred_c2, bidx, n_states, res, p): + assert log_emission_baf_c1.shape[0] == n_states or log_emission_baf_c1.shape[0] == 2 * n_states + # likelihood under the corresponding state + llf_original = np.append(log_emission_rdr_c1[pred_c1[bidx], bidx] + log_emission_baf_c1[pred_c1[bidx], bidx], \ + log_emission_rdr_c2[pred_c2[bidx], bidx] + log_emission_baf_c2[pred_c2[bidx], bidx]).reshape(-1,1) + # likelihood under the switched state + if log_emission_baf_c1.shape[0] == 2 * n_states: + if (res["new_p_binom"][p[0],0] > 0.5) == (res["new_p_binom"][p[1],0] > 0.5): + switch_pred_c1 = n_states * (pred_c1 >= n_states) + (pred_c2 % n_states) + switch_pred_c2 = n_states * (pred_c2 >= n_states) + (pred_c1 % n_states) + else: + switch_pred_c1 = n_states * (pred_c1 < n_states) + (pred_c2 % n_states) + switch_pred_c2 = n_states * (pred_c2 < n_states) + (pred_c1 % n_states) + else: + switch_pred_c1 = pred_c2 + switch_pred_c2 = pred_c1 + llf_switch = np.append(log_emission_rdr_c1[switch_pred_c1[bidx], bidx] + log_emission_baf_c1[switch_pred_c1[bidx], bidx], \ + log_emission_rdr_c2[switch_pred_c2[bidx], bidx] + log_emission_baf_c2[switch_pred_c2[bidx], bidx]).reshape(-1,1) + # log likelihood difference + return np.mean(llf_original) - np.mean(llf_switch) + + +def compute_neymanpearson_stats(X, base_nb_mean, total_bb_RD, res, params, tumor_prop, hmmclass): + n_obs = X.shape[0] + n_states = res["new_p_binom"].shape[0] + n_clones = X.shape[2] + lambd = np.sum(base_nb_mean, axis=1) / np.sum(base_nb_mean) + # + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"]) + else: + if "m" in params: + logmu_shift = [] + for c in range(n_clones): + this_pred_cnv = np.argmax(res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0)%n_states + logmu_shift.append( scipy.special.logsumexp(res["new_log_mu"][this_pred_cnv,:] + np.log(lambd).reshape(-1,1), axis=0) ) + logmu_shift = np.vstack(logmu_shift) + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"], tumor_prop, logmu_shift=logmu_shift, sample_length=np.ones(n_clones,dtype=int)*n_obs) + else: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"], tumor_prop) + log_emission_rdr = log_emission_rdr.reshape((log_emission_rdr.shape[0], n_obs, n_clones), order="F") + log_emission_baf = log_emission_baf.reshape((log_emission_baf.shape[0], n_obs, n_clones), order="F") + reshaped_pred = np.argmax(res["log_gamma"], axis=0).reshape((X.shape[2],-1)) + reshaped_pred_cnv = reshaped_pred % n_states + all_test_statistics = {(c1, c2):[] for c1 in range(n_clones) for c2 in range(c1+1, n_clones)} + for c1 in range(n_clones): + for c2 in range(c1+1, n_clones): + # unmergeable_bincount = 0 + unique_pair_states = [x for x in np.unique(reshaped_pred_cnv[np.array([c1,c2]), :], axis=1).T if x[0] != x[1]] + list_t_neymanpearson = [] + for p in unique_pair_states: + bidx = np.where( (reshaped_pred_cnv[c1,:]==p[0]) & (reshaped_pred_cnv[c2,:]==p[1]) )[0] + if "m" in params and "p" in params: + t_neymanpearson = eval_neymanpearson_rdrbaf(log_emission_rdr[:,:,c1], log_emission_baf[:,:,c1], reshaped_pred[c1,:], log_emission_rdr[:,:,c2], log_emission_baf[:,:,c2], reshaped_pred[c2,:], bidx, n_states, res, p) + elif "p" in params: + t_neymanpearson = eval_neymanpearson_bafonly(log_emission_baf[:,:,c1], reshaped_pred[c1,:], log_emission_baf[:,:,c2], reshaped_pred[c2,:], bidx, n_states, res, p) + all_test_statistics[(c1, c2)].append( (p[0], p[1], t_neymanpearson) ) + + return all_test_statistics + + +def similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, threshold=2.0, minlength=10, topk=10, params="smp", tumor_prop=None, hmmclass=hmm_sitewise, **kwargs): + n_obs = X.shape[0] + n_states = res["new_p_binom"].shape[0] + n_clones = X.shape[2] + G = nx.Graph() + G.add_nodes_from( np.arange(n_clones) ) + # + lambd = np.sum(base_nb_mean, axis=1) / np.sum(base_nb_mean) + # + if tumor_prop is None: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"]) + else: + if "m" in params: + logmu_shift = [] + for c in range(n_clones): + this_pred_cnv = np.argmax(res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0)%n_states + logmu_shift.append( scipy.special.logsumexp(res["new_log_mu"][this_pred_cnv,:] + np.log(lambd).reshape(-1,1), axis=0) ) + logmu_shift = np.vstack(logmu_shift) + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"], tumor_prop, logmu_shift=logmu_shift, sample_length=np.ones(n_clones,dtype=int)*n_obs) + else: + log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ + total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"], tumor_prop) + log_emission_rdr = log_emission_rdr.reshape((log_emission_rdr.shape[0], n_obs, n_clones), order="F") + log_emission_baf = log_emission_baf.reshape((log_emission_baf.shape[0], n_obs, n_clones), order="F") + reshaped_pred = np.argmax(res["log_gamma"], axis=0).reshape((X.shape[2],-1)) + reshaped_pred_cnv = reshaped_pred % n_states + all_test_statistics = [] + for c1 in range(n_clones): + for c2 in range(c1+1, n_clones): + # unmergeable_bincount = 0 + unique_pair_states = [x for x in np.unique(reshaped_pred_cnv[np.array([c1,c2]), :], axis=1).T if x[0] != x[1]] + list_t_neymanpearson = [] + for p in unique_pair_states: + bidx = np.where( (reshaped_pred_cnv[c1,:]==p[0]) & (reshaped_pred_cnv[c2,:]==p[1]) )[0] + if "m" in params and "p" in params: + t_neymanpearson = eval_neymanpearson_rdrbaf(log_emission_rdr[:,:,c1], log_emission_baf[:,:,c1], reshaped_pred[c1,:], log_emission_rdr[:,:,c2], log_emission_baf[:,:,c2], reshaped_pred[c2,:], bidx, n_states, res, p) + elif "p" in params: + t_neymanpearson = eval_neymanpearson_bafonly(log_emission_baf[:,:,c1], reshaped_pred[c1,:], log_emission_baf[:,:,c2], reshaped_pred[c2,:], bidx, n_states, res, p) + print(c1, c2, p, len(bidx), t_neymanpearson) + all_test_statistics.append( [c1, c2, p, t_neymanpearson] ) + if len(bidx) >= minlength: + list_t_neymanpearson.append(t_neymanpearson) + if len(list_t_neymanpearson) == 0 or np.max(list_t_neymanpearson) < threshold: + max_v = np.max(list_t_neymanpearson) if len(list_t_neymanpearson) > 0 else 1e-3 + G.add_weighted_edges_from([ (c1, c2, max_v) ]) + # maximal cliques + cliques = [] + for x in nx.find_cliques(G): + this_len = len(x) + this_weights = np.sum([G.get_edge_data(a,b)["weight"] for a in x for b in x if a != b]) / 2 + cliques.append( (x, this_len, this_weights) ) + cliques.sort(key = lambda x:(-x[1],x[2]) ) + covered_nodes = set() + merging_groups = [] + for c in cliques: + if len(set(c[0]) & covered_nodes) == 0: + merging_groups.append( list(c[0]) ) + covered_nodes = covered_nodes | set(c[0]) + for c in range(n_clones): + if not (c in covered_nodes): + merging_groups.append( [c] ) + covered_nodes.add(c) + merging_groups.sort(key = lambda x:np.min(x)) + # clone assignment after merging + map_clone_id = {} + for i,x in enumerate(merging_groups): + for z in x: + map_clone_id[z] = i + new_assignment = np.array([map_clone_id[x] for x in res["new_assignment"]]) + merged_res = copy.copy(res) + merged_res["new_assignment"] = new_assignment + merged_res["total_llf"] = np.NAN + merged_res["pred_cnv"] = np.concatenate([ res["pred_cnv"][(c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) + merged_res["log_gamma"] = np.hstack([ res["log_gamma"][:, (c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) + return merging_groups, merged_res + + +def combine_similar_states_across_clones(X, base_nb_mean, total_bb_RD, res, params="smp", tumor_prop=None, hmmclass=hmm_sitewise, merge_threshold=0.1, **kwargs): + n_clones = X.shape[2] + n_obs = X.shape[0] + n_states = res["new_p_binom"].shape[0] + reshaped_pred = np.argmax(res["log_gamma"], axis=0).reshape((X.shape[2],-1)) + reshaped_pred_cnv = reshaped_pred % n_states + # + all_test_statistics = compute_neymanpearson_stats(X, base_nb_mean, total_bb_RD, res, params, tumor_prop, hmmclass) + # make the pair of states consistent between clone c1 and clone c2 if their t_neymanpearson test statistics is small + for c1 in range(n_clones): + for c2 in range(c1+1, n_clones): + list_t_neymanpearson = all_test_statistics[(c1, c2)] + for p1, p2, t_neymanpearson in list_t_neymanpearson: + if t_neymanpearson < merge_threshold: + c_keep = c1 if np.sum(total_bb_RD[:,c1]) > np.sum(total_bb_RD[:,c2]) else c2 + c_change = c2 if c_keep == c1 else c1 + bidx = np.where( (reshaped_pred_cnv[c1,:]==p1) & (reshaped_pred_cnv[c2,:]==p2) )[0] + res['pred_cnv'][(c_change*n_obs):(c_change*n_obs+n_obs)][bidx] = res['pred_cnv'][(c_keep*n_obs):(c_keep*n_obs+n_obs)][bidx] + print(f"Merging states {[p1,p2]} in clone {c1} and clone {c2}. NP statistics = {t_neymanpearson}") + return res + + + +# def similarity_components_rdrbaf_neymanpearson_posterior(X, base_nb_mean, total_bb_RD, res, threshold=2.0, minlength=10, topk=10, params="smp", tumor_prop=None, hmmclass=hmm_sitewise): +# n_obs = X.shape[0] +# n_states = res["new_p_binom"].shape[0] +# n_clones = X.shape[2] +# G = nx.Graph() +# G.add_nodes_from( np.arange(n_clones) ) +# # +# def eval_neymanpearson_bafonly(log_emission_baf_c1, log_gamma_c1, log_emission_baf_c2, log_gamma_c2, bidx, n_states, res, p): +# assert log_emission_baf_c1.shape[0] == n_states or log_emission_baf_c1.shape[0] == 2 * n_states +# # likelihood under the corresponding state +# llf_original = np.append(scipy.special.logsumexp(log_emission_baf_c1[:, bidx] + log_gamma_c1[:, bidx], axis=0), +# scipy.special.logsumexp(log_emission_baf_c2[:, bidx] + log_gamma_c2[:, bidx], axis=0)) +# # likelihood under the switched state +# if log_emission_baf_c1.shape[0] == 2 * n_states: +# whether_switch = False +# pred_c1 = np.argmax(log_gamma_c1[:,bidx[0]]) +# pred_c2 = np.argmax(log_gamma_c2[:,bidx[0]]) +# if ( ((res["new_p_binom"][p[0],0] > 0.5) == (res["new_p_binom"][p[1],0] > 0.5)) ^ ((pred_c1 < n_states) == (pred_c2 < n_states)) ): +# whether_switch = True +# if not whether_switch: +# switch_log_gamma_c1 = log_gamma_c2 +# switch_log_gamma_c2 = log_gamma_c1 +# else: +# switch_log_gamma_c1 = np.vstack([log_gamma_c2[:n_states,:], log_gamma_c2[n_states:,:]]) +# switch_log_gamma_c2 = np.vstack([log_gamma_c1[:n_states,:], log_gamma_c1[n_states:,:]]) +# else: +# switch_log_gamma_c1 = log_gamma_c2 +# switch_log_gamma_c2 = log_gamma_c1 +# llf_switch = np.append(scipy.special.logsumexp(log_emission_baf_c1[:, bidx] + switch_log_gamma_c1[:, bidx], axis=0), +# scipy.special.logsumexp(log_emission_baf_c2[:, bidx] + switch_log_gamma_c2[:, bidx], axis=0)) +# # log likelihood difference +# return np.mean(llf_original) - np.mean(llf_switch) +# # +# def eval_neymanpearson_rdrbaf(log_emission_rdr_c1, log_emission_baf_c1, log_gamma_c1, log_emission_rdr_c2, log_emission_baf_c2, log_gamma_c2, bidx, n_states, res, p): +# assert log_emission_baf_c1.shape[0] == n_states or log_emission_baf_c1.shape[0] == 2 * n_states +# # likelihood under the corresponding state +# llf_original = 0.5 * np.append(scipy.special.logsumexp((log_emission_rdr_c1+log_emission_baf_c1)[:, bidx] + log_gamma_c1[:, bidx], axis=0), \ +# scipy.special.logsumexp((log_emission_rdr_c2+log_emission_baf_c2)[:, bidx] + log_gamma_c2[:, bidx], axis=0)) +# # likelihood under the switched state +# if log_emission_baf_c1.shape[0] == 2 * n_states: +# whether_switch = False +# pred_c1 = np.argmax(log_gamma_c1[:,bidx[0]]) +# pred_c2 = np.argmax(log_gamma_c2[:,bidx[0]]) +# if ( ((res["new_p_binom"][p[0],0] > 0.5) == (res["new_p_binom"][p[1],0] > 0.5)) ^ ((pred_c1 < n_states) == (pred_c2 < n_states)) ): +# whether_switch = True +# if not whether_switch: +# switch_log_gamma_c1 = log_gamma_c2 +# switch_log_gamma_c2 = log_gamma_c1 +# else: +# switch_log_gamma_c1 = np.vstack([log_gamma_c2[:n_states,:], log_gamma_c2[n_states:,:]]) +# switch_log_gamma_c2 = np.vstack([log_gamma_c1[:n_states,:], log_gamma_c1[n_states:,:]]) +# else: +# switch_log_gamma_c1 = log_gamma_c2 +# switch_log_gamma_c2 = log_gamma_c1 +# llf_switch = 0.5 * np.append(scipy.special.logsumexp((log_emission_rdr_c1+log_emission_baf_c1)[:, bidx] + switch_log_gamma_c1[:, bidx], axis=0), \ +# scipy.special.logsumexp((log_emission_rdr_c2+log_emission_baf_c2)[:, bidx] + switch_log_gamma_c2[:, bidx], axis=0)) +# # log likelihood difference +# return np.mean(llf_original) - np.mean(llf_switch) +# # +# if tumor_prop is None: +# log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ +# base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ +# total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"]) +# else: +# log_emission_rdr, log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix(np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ +# base_nb_mean.flatten("F").reshape(-1,1), res["new_log_mu"], res["new_alphas"], \ +# total_bb_RD.flatten("F").reshape(-1,1), res["new_p_binom"], res["new_taus"], tumor_prop) +# log_emission_rdr = log_emission_rdr.reshape((log_emission_rdr.shape[0], n_obs, n_clones), order="F") +# log_emission_baf = log_emission_baf.reshape((log_emission_baf.shape[0], n_obs, n_clones), order="F") +# reshaped_pred = np.argmax(res["log_gamma"], axis=0).reshape((X.shape[2],-1)) +# reshaped_pred_cnv = reshaped_pred % n_states +# reshaped_log_gamma = np.stack([ res["log_gamma"][:,(c*n_obs):(c*n_obs + n_obs)] for c in range(n_clones) ], axis=-1) +# for c1 in range(n_clones): +# for c2 in range(c1+1, n_clones): +# # unmergeable_bincount = 0 +# unique_pair_states = [x for x in np.unique(reshaped_pred_cnv[np.array([c1,c2]), :], axis=1).T if x[0] != x[1]] +# list_t_neymanpearson = [] +# for p in unique_pair_states: +# bidx = np.where( (reshaped_pred_cnv[c1,:]==p[0]) & (reshaped_pred_cnv[c2,:]==p[1]) )[0] +# if "m" in params and "p" in params: +# t_neymanpearson = eval_neymanpearson_rdrbaf(log_emission_rdr[:,:,c1], log_emission_baf[:,:,c1], reshaped_log_gamma[:,:,c1], log_emission_rdr[:,:,c2], log_emission_baf[:,:,c2], reshaped_log_gamma[:,:,c2], bidx, n_states, res, p) +# elif "p" in params: +# t_neymanpearson = eval_neymanpearson_bafonly(log_emission_baf[:,:,c1], reshaped_log_gamma[:,:,c1], log_emission_baf[:,:,c2], reshaped_log_gamma[:,:,c2], bidx, n_states, res, p) +# # if t_neymanpearson > threshold: +# # unmergeable_bincount += len(bidx) +# print(c1, c2, p, len(bidx), t_neymanpearson) +# if len(bidx) >= minlength: +# list_t_neymanpearson.append(t_neymanpearson) +# if len(list_t_neymanpearson) == 0 or np.max(list_t_neymanpearson) < threshold: +# max_v = np.max(list_t_neymanpearson) if len(list_t_neymanpearson) > 0 else 1e-3 +# G.add_weighted_edges_from([ (c1, c2, max_v) ]) +# # if unmergeable_bincount < topk: +# # G.add_edge(c1, c2) +# # maximal cliques +# cliques = [] +# for x in nx.find_cliques(G): +# this_len = len(x) +# this_weights = np.sum([G.get_edge_data(a,b)["weight"] for a in x for b in x if a != b]) / 2 +# cliques.append( (x, this_len, this_weights) ) +# cliques.sort(key = lambda x:(-x[1],x[2]) ) +# covered_nodes = set() +# merging_groups = [] +# for c in cliques: +# if len(set(c[0]) & covered_nodes) == 0: +# merging_groups.append( list(c[0]) ) +# covered_nodes = covered_nodes | set(c[0]) +# for c in range(n_clones): +# if not (c in covered_nodes): +# merging_groups.append( [c] ) +# covered_nodes.add(c) +# merging_groups.sort(key = lambda x:np.min(x)) +# # clone assignment after merging +# map_clone_id = {} +# for i,x in enumerate(merging_groups): +# for z in x: +# map_clone_id[z] = i +# new_assignment = np.array([map_clone_id[x] for x in res["new_assignment"]]) +# merged_res = copy.copy(res) +# merged_res["new_assignment"] = new_assignment +# merged_res["total_llf"] = np.NAN +# merged_res["pred_cnv"] = np.concatenate([ res["pred_cnv"][(c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) +# merged_res["log_gamma"] = np.hstack([ res["log_gamma"][:, (c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) +# return merging_groups, merged_res diff --git a/src/hmm_NB_sharedstates.py b/src/calicost/hmm_NB_sharedstates.py similarity index 78% rename from src/hmm_NB_sharedstates.py rename to src/calicost/hmm_NB_sharedstates.py index 7ad5f6a..a265810 100644 --- a/src/hmm_NB_sharedstates.py +++ b/src/calicost/hmm_NB_sharedstates.py @@ -8,7 +8,7 @@ from scipy.special import logsumexp from sklearn import cluster from sklearn.utils import check_random_state -from hmmlearn.hmm import _BaseHMM as BaseHMM +from hmmlearn.hmm import BaseHMM import statsmodels import statsmodels.api as sm from statsmodels.base.model import GenericLikelihoodModel @@ -78,13 +78,13 @@ class ConstrainedNBHMM(BaseHMM): Examples ---------- - # base_nb_mean = eta.reshape(-1,1) * totalUMI.reshape(1,-1) base_nb_mean = eta.reshape(-1,1) * np.sum(totalUMI) - hmmmodel = ConstrainedNBHMM(base_nb_mean, n_components=3) - hmmmodel.fit( np.sum(count,axis=0).reshape(-1,1) ) - hmmmodel.predict( np.sum(count,axis=0).reshape(-1,1) ) + hmmmodel = ConstrainedNBHMM(n_components=3) + X = np.vstack( [np.sum(count,axis=0), base_nb_mean] ).T + hmmmodel.fit( X ) + hmmmodel.predict( X ) """ - def __init__(self, base_nb_mean, n_components=1, shared_dispersion=False, + def __init__(self, n_components=1, shared_dispersion=False, startprob_prior=1.0, transmat_prior=1.0, algorithm="viterbi", random_state=None, n_iter=10, tol=1e-2, verbose=False, @@ -96,15 +96,12 @@ def __init__(self, base_nb_mean, n_components=1, shared_dispersion=False, random_state=random_state, n_iter=n_iter, tol=tol, params=params, verbose=verbose, init_params=init_params) - self.n_cells = base_nb_mean.shape[1] - self.n_genes = base_nb_mean.shape[0] - self.base_nb_mean = base_nb_mean self.shared_dispersion = shared_dispersion # initialize CNV's effect self.log_mu = np.linspace(-0.1, 0.1, self.n_components) # initialize inverse of dispersion - #self.alphas = np.array([0.01] * self.n_components) - self.alphas = 0.01 * np.ones((self.n_components, self.n_genes)) + self.alphas = np.array([0.01] * self.n_components) + # self.alphas = 0.01 * np.ones(s(self.n_components, self.n_genes)) # initialize start probability and transition probability self.startprob_ = np.ones(self.n_components) / self.n_components t = 0.9 @@ -117,27 +114,28 @@ def _compute_log_likelihood(self, X): Attributes ---------- - X : array_like, shape (n_genes, n_cells) - Observed UMI count matrix + X : array_like, shape (n_genes, 2*n_cells) + First (n_genes, n_cells) is the observed UMI count matrix; second (n_genes, n_cells) is base_nb_mean. Returns ------- lpr : array_like, shape (n_genes, n_components) Array containing the log probabilities of each data point in X. """ - log_prob = np.zeros((self.n_genes, self.n_cells, self.n_components)) + n_genes = X.shape[0] + n_cells = int(X.shape[1] / 2) + base_nb_mean = X[:, n_cells:] + log_prob = np.zeros((n_genes, n_cells, self.n_components)) for i in range(self.n_components): - nb_mean = self.base_nb_mean * np.exp(self.log_mu[i]) - #nb_std = np.sqrt(nb_mean + self.alphas[i] * nb_mean**2) - nb_std = np.sqrt(nb_mean + self.alphas[i,:].reshape(-1,1) * nb_mean**2) + nb_mean = base_nb_mean * np.exp(self.log_mu[i]) + nb_std = np.sqrt(nb_mean + self.alphas[i] * nb_mean**2) + # nb_std = np.sqrt(nb_mean + self.alphas[i,:].reshape(-1,1) * nb_mean**2) n, p = convert_params(nb_mean, nb_std) - log_prob[:,:,i] = scipy.stats.nbinom.logpmf(X, n, p) + log_prob[:,:,i] = scipy.stats.nbinom.logpmf(X[:, :n_cells], n, p) return log_prob.mean(axis=1) # def _initialize_sufficient_statistics(self): stats = super()._initialize_sufficient_statistics() - stats['obs'] = np.zeros((self.n_genes, self.n_cells)) - stats['post'] = np.zeros((self.n_genes, self.n_components)) return stats # def _accumulate_sufficient_statistics(self, stats, X, lattice, posteriors, fwdlattice, bwdlattice): @@ -176,40 +174,43 @@ def _accumulate_sufficient_statistics(self, stats, X, lattice, posteriors, fwdla stats['denoms'] = denoms # def _do_mstep(self, stats): + n_genes = stats['obs'].shape[0] + n_cells = int(stats['obs'].shape[1] / 2) + base_nb_mean = stats['obs'][:, n_cells:] super()._do_mstep(stats) if 'm' in self.params and 'a' in self.params: # NB regression fit dispersion and CNV's effect simultaneously if not self.shared_dispersion: for i in range(self.n_components): - model = Weighted_NegativeBinomial(stats['obs'].flatten(), \ - np.ones(self.n_genes*self.n_cells).reshape(-1,1), \ - weights=np.repeat(stats['post'][:,i], self.n_cells), exposure=self.base_nb_mean.flatten()) + model = Weighted_NegativeBinomial(stats['obs'][:, :n_cells].flatten(), \ + np.ones(n_genes*n_cells).reshape(-1,1), \ + weights=np.repeat(stats['post'][:,i], n_cells), exposure=base_nb_mean.flatten()) res = model.fit(disp=0, maxiter=500) self.log_mu[i] = res.params[0] - #self.alphas[i] = res.params[-1] - self.alphas[i,:] = res.params[-1] + self.alphas[i] = res.params[-1] + # self.alphas[i,:] = res.params[-1] else: - all_states_nb_mean = np.tile(self.base_nb_mean.flatten(), self.n_components) - all_states_y = np.tile(stats['obs'].flatten(), self.n_components) - all_states_weights = np.concatenate([np.repeat(stats['post'][:,i], self.n_cells) for i in range(self.n_components)]) - all_states_features = np.zeros((self.n_components*self.n_genes*self.n_cells, self.n_components)) + all_states_nb_mean = np.tile(base_nb_mean.flatten(), self.n_components) + all_states_y = np.tile(stats['obs'][:, :n_cells].flatten(), self.n_components) + all_states_weights = np.concatenate([np.repeat(stats['post'][:,i], n_cells) for i in range(self.n_components)]) + all_states_features = np.zeros((self.n_components*n_genes*n_cells, self.n_components)) for i in np.arange(self.n_components): - all_states_features[(i*self.n_genes*self.n_cells):((i+1)*self.n_genes*self.n_cells), i] = 1 + all_states_features[(i*n_genes*n_cells):((i+1)*n_genes*n_cells), i] = 1 model = Weighted_NegativeBinomial(all_states_y, all_states_features, weights=all_states_weights, exposure=all_states_nb_mean) res = model.fit(disp=0, maxiter=500) self.log_mu = res.params[:-1] - #self.alphas[:] = res.params[-1] - self.alphas[:,:] = res.params[-1] + self.alphas[:] = res.params[-1] + # self.alphas[:,:] = res.params[-1] # print(res.params) elif 'm' in self.params: # NB regression fit CNV's effect only for i in range(self.n_components): - # model = sm.GLM(stats['obs'].flatten(), np.ones(self.n_genes*self.n_cells).reshape(-1,1), \ - # family=sm.families.NegativeBinomial(alpha=self.alphas[i]), \ - # exposure=self.base_nb_mean.flatten()) model = sm.GLM(stats['obs'].flatten(), np.ones(self.n_genes*self.n_cells).reshape(-1,1), \ - family=sm.families.NegativeBinomial(alpha=np.repeat(self.alphas[i], self.n_cells)), \ - exposure=self.base_nb_mean.flatten(), var_weights=np.repeat(stats['post'][:,i], self.n_cells)) + family=sm.families.NegativeBinomial(alpha=self.alphas[i]), \ + exposure=base_nb_mean.flatten()) + # model = sm.GLM(stats['obs'][:, :n_cells].flatten(), np.ones(n_genes*n_cells).reshape(-1,1), \ + # family=sm.families.NegativeBinomial(alpha=np.repeat(self.alphas[i], n_cells)), \ + # exposure=base_nb_mean.flatten(), var_weights=np.repeat(stats['post'][:,i], n_cells)) res = model.fit(disp=0, maxiter=500) self.log_mu[i] = res.params[0] if 't' in self.params: diff --git a/src/calicost/hmm_gaussian.py b/src/calicost/hmm_gaussian.py new file mode 100644 index 0000000..b053610 --- /dev/null +++ b/src/calicost/hmm_gaussian.py @@ -0,0 +1,807 @@ +import logging +import numpy as np +from numba import njit +from scipy.stats import norm, multivariate_normal, poisson +import scipy.special +from scipy.optimize import minimize +from scipy.optimize import Bounds +from sklearn.mixture import GaussianMixture +from tqdm import trange +import copy + + +############################################################ +# E step related +############################################################ + +@njit +def np_max_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.max(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.max(arr[i, :]) + return result + + +@njit +def np_max_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.max(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.max(arr[i, :]) + return result + + +@njit +def np_sum_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.sum(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.sum(arr[i, :]) + return result + + +@njit +def np_sum_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.sum(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.sum(arr[i, :]) + return result + + +@njit +def np_mean_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.mean(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.mean(arr[i, :]) + return result + +@njit +def np_mean_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.mean(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.mean(arr[i, :]) + return result + + +@njit +def mylogsumexp(a): + # get max + a_max = np.max(a) + if (np.isinf(a_max)): + return a_max + # exponential + tmp = np.exp(a - a_max) + # summation + s = np.sum(tmp) + s = np.log(s) + return s + a_max + + +@njit +def mylogsumexp_ax_keep(a, axis): + # get max + a_max = np_max_ax_keep(a, axis=axis) + # if a_max.ndim > 0: + # a_max[~np.isfinite(a_max)] = 0 + # elif not np.isfinite(a_max): + # a_max = 0 + # exponential + tmp = np.exp(a - a_max) + # summation + s = np_sum_ax_keep(tmp, axis=axis) + s = np.log(s) + return s + a_max + + + +def compute_emission_probability_gaussian(X, rdr_mean, rdr_std, p_mean, p_std): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + + log_mu : array, shape (n_states, n_spots) + Log of read depth change due to CNV. Mean of NB distributions in HMM per state per spot. + + alphas : array, shape (n_states, n_spots) + Over-dispersion of NB distributions in HMM per state per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + + p_mean : array, shape (n_states, n_spots) + BAF due to CNV. Mean of Beta Binomial distribution in HMM per state per spot. + + p_std : array, shape (n_states, n_spots) + Over-dispersion of Beta Binomial distribution in HMM per state per spot. + + Returns + ---------- + log_emission : array, shape (2*n_states, n_obs, n_spots) + Log emission probability for each gene each spot (or sample) under each state. There is a common bag of states across all spots. + """ + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + n_states = rdr_mean.shape[0] + # initialize log_emission + log_emission = np.zeros((2 * n_states, n_obs, n_spots)) + for i in np.arange(n_states): + for s in np.arange(n_spots): + # expression from Gaussian distribution + if np.any(X[:,0,s] > 0): + log_emission[i, :, s] = scipy.stats.norm.logpdf(X[:, 0, s], loc=rdr_mean[i,s], scale=rdr_std[i,s]) + log_emission[i + n_states, :, s] = log_emission[i, :, s] + # BAF from Gaussian distribution + if np.any(X[:,1,s] > 0): + log_emission[i, :, s] += scipy.stats.norm.logpdf(X[:,1,s], loc=p_mean[i, s], scale=p_std[i,s]) + log_emission[i + n_states, :, s] += scipy.stats.norm.logpdf(X[:,1,s], loc=1-p_mean[i, s], scale=p_std[i,s]) + return log_emission + + +@njit +def forward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are 2 * n_states of paired states for (CNV, phasing) pairs. + Input + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: 2*n_states * n_observations * n_spots. Log probability. + log_sitewise_transmat: n_observations, the log transition probability of phase switch. + Output + log_alpha: size 2n_states * n_observations. log alpha[j, t] = log P(o_1, ... o_t, q_t = j | lambda). + ''' + n_obs = log_emission.shape[1] + n_states = int(np.ceil(log_emission.shape[0] / 2)) + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) + # initialize log_alpha + log_alpha = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + combined_log_startprob = np.log(0.5) + np.append(log_startprob,log_startprob) + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_alpha[:, cumlen] = combined_log_startprob + np_sum_ax_squeeze(log_emission[:, cumlen, :], axis=1) + for t in np.arange(1, le): + phases_switch_mat = np.array([[log_sitewise_self_transmat[cumlen + t-1], log_sitewise_transmat[cumlen + t-1]], [log_sitewise_transmat[cumlen + t-1], log_sitewise_self_transmat[cumlen + t-1] ]]) + combined_transmat = np.kron( np.exp(phases_switch_mat), np.exp(log_transmat) ) + combined_transmat = np.log(combined_transmat) + for j in np.arange(log_emission.shape[0]): + for i in np.arange(log_emission.shape[0]): + buf[i] = log_alpha[i, (cumlen + t - 1)] + combined_transmat[i, j] + log_alpha[j, (cumlen + t)] = mylogsumexp(buf) + np.sum(log_emission[j, (cumlen + t), :]) + cumlen += le + return log_alpha + + +@njit +def backward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat): + ''' + Note that n_states is the CNV states, and there are 2 * n_states of paired states for (CNV, phasing) pairs. + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + log_transmat: n_states * n_states. Transition probability after log transformation. + log_startprob: n_states. Start probability after log transformation. + log_emission: 2*n_states * n_observations * n_spots. Log probability. + log_sitewise_transmat: n_observations, the log transition probability of phase switch. + Output + log_beta: size 2*n_states * n_observations. log beta[i, t] = log P(o_{t+1}, ..., o_T | q_t = i, lambda). + ''' + n_obs = log_emission.shape[1] + n_states = int(np.ceil(log_emission.shape[0] / 2)) + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the first dimension of X!" + assert len(log_startprob) == n_states, "Length of startprob_ must be equal to the first dimension of log_transmat!" + log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) + # initialize log_beta + log_beta = np.zeros((log_emission.shape[0], n_obs)) + buf = np.zeros(log_emission.shape[0]) + cumlen = 0 + for le in lengths: + # start prob + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_beta[:, (cumlen + le - 1)] = 0 + for t in np.arange(le-2, -1, -1): + phases_switch_mat = np.array([[log_sitewise_self_transmat[cumlen + t], log_sitewise_transmat[cumlen + t]], [log_sitewise_transmat[cumlen + t], log_sitewise_self_transmat[cumlen + t] ]]) + combined_transmat = np.kron( np.exp(phases_switch_mat), np.exp(log_transmat) ) + combined_transmat = np.log(combined_transmat) + for i in np.arange(log_emission.shape[0]): + for j in np.arange(log_emission.shape[0]): + buf[j] = log_beta[j, (cumlen + t + 1)] + combined_transmat[i, j] + np.sum(log_emission[j, (cumlen + t + 1), :]) + log_beta[i, (cumlen + t)] = mylogsumexp(buf) + cumlen += le + return log_beta + + +def compute_posterior_obs(log_alpha, log_beta): + ''' + Input + log_alpha: output from forward_lattice_gaussian. size n_states * n_observations. alpha[j, t] = P(o_1, ... o_t, q_t = j | lambda). + log_beta: output from backward_lattice_gaussian. size n_states * n_observations. beta[i, t] = P(o_{t+1}, ..., o_T | q_t = i, lambda). + Output: + log_gamma: size n_states * n_observations. gamma[i,t] = P(q_t = i | O, lambda). gamma[i, t] propto alpha[i,t] * beta[i,t] + ''' + n_states = log_alpha.shape[0] + n_obs = log_alpha.shape[1] + # initial log_gamma + log_gamma = np.zeros((n_states, n_obs)) + # compute log_gamma + # for j in np.arange(n_states): + # for t in np.arange(n_obs): + # log_gamma[j, t] = log_alpha[j, t] + log_beta[j, t] + log_gamma = log_alpha + log_beta + if np.any( np.sum(log_gamma, axis=0) == 0 ): + raise Exception("Sum of posterior probability is zero for some observations!") + log_gamma -= scipy.special.logsumexp(log_gamma, axis=0) + return log_gamma + + +@njit +def compute_posterior_transition_sitewise(log_alpha, log_beta, log_transmat, log_emission): + ''' + Input + log_alpha: output from forward_lattice_gaussian. size n_states * n_observations. alpha[j, t] = P(o_1, ... o_t, q_t = j | lambda). + log_beta: output from backward_lattice_gaussian. size n_states * n_observations. beta[i, t] = P(o_{t+1}, ..., o_T | q_t = i, lambda). + log_transmat: n_states * n_states. Transition probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output: + log_xi: size n_states * n_states * (n_observations-1). xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + ''' + n_states = int(log_alpha.shape[0] / 2) + n_obs = log_alpha.shape[1] + # initialize log_xi + log_xi = np.zeros((2*n_states, 2*n_states, n_obs-1)) + # compute log_xi + for i in np.arange(2*n_states): + for j in np.arange(2*n_states): + for t in np.arange(n_obs-1): + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_xi[i, j, t] = log_alpha[i, t] + log_transmat[i - n_states * int(i/n_states), j - n_states * int(j/n_states)] + np.sum(log_emission[j, t+1, :]) + log_beta[j, t+1] + # normalize + for t in np.arange(n_obs-1): + log_xi[:, :, t] -= mylogsumexp(log_xi[:, :, t]) + return log_xi + + +############################################################ +# M step related +############################################################ +@njit +def update_startprob_sitewise(lengths, log_gamma): + ''' + Input + lengths: sum of lengths = n_observations. + log_gamma: size 2 * n_states * n_observations. gamma[i,t] = P(q_t = i | O, lambda). + Output + log_startprob: n_states. Start probability after loog transformation. + ''' + n_states = int(log_gamma.shape[0] / 2) + n_obs = log_gamma.shape[1] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the second dimension of log_gamma!" + # indices of the start of sequences, given that the length of each sequence is in lengths + cumlen = 0 + indices_start = [] + for le in lengths: + indices_start.append(cumlen) + cumlen += le + indices_start = np.array(indices_start) + # initialize log_startprob + log_startprob = np.zeros(n_states) + # compute log_startprob of 2 * n_states + log_startprob = mylogsumexp_ax_keep(log_gamma[:, indices_start], axis=1) + # merge (CNV state, phase A) and (CNV state, phase B) + log_startprob = log_startprob.flatten().reshape(2,-1) + log_startprob = mylogsumexp_ax_keep(log_startprob, axis=0) + # normalize such that startprob sums to 1 + log_startprob -= mylogsumexp(log_startprob) + return log_startprob + + +def update_transition_sitewise(log_xi, is_diag=False): + ''' + Input + log_xi: size (2*n_states) * (2*n_states) * n_observations. xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + Output + log_transmat: n_states * n_states. Transition probability after log transformation. + ''' + n_states = int(log_xi.shape[0] / 2) + n_obs = log_xi.shape[2] + # initialize log_transmat + log_transmat = np.zeros((n_states, n_states)) + for i in np.arange(n_states): + for j in np.arange(n_states): + log_transmat[i, j] = scipy.special.logsumexp( np.concatenate([log_xi[i, j, :], log_xi[i+n_states, j, :], \ + log_xi[i, j+n_states, :], log_xi[i + n_states, j + n_states, :]]) ) + # row normalize log_transmat + if not is_diag: + for i in np.arange(n_states): + rowsum = scipy.special.logsumexp(log_transmat[i, :]) + log_transmat[i, :] -= rowsum + else: + diagsum = scipy.special.logsumexp(np.diag(log_transmat)) + totalsum = scipy.special.logsumexp(log_transmat) + t = diagsum - totalsum + rest = np.log( (1 - np.exp(t)) / (n_states-1) ) + log_transmat = np.ones(log_transmat.shape) * rest + np.fill_diagonal(log_transmat, t) + return log_transmat + + +def weighted_gaussian_fitting(x, weights): + """ + x : 1d array. + weights : 1d array + """ + mu = weights.dot(x) / np.sum(weights) + v = weights.dot( np.square(x - mu) ) / np.sum(weights) + std = np.sqrt(v) + return mu, std + + +def weighted_gaussian_fitting_sharestd(X, Weights): + """ + X : array, (n_obs, n_cluster). + Each cluster has an equal number of observations n_obs. Each cluster has its own mean, but the std is shared across clusters. + Weights : array, (n_obs, n_cluster). + """ + n_clusters = X.shape[1] + mus = np.zeros(n_clusters) + ssr = np.zeros(X.shape) + for i in range(n_clusters): + mus[i] = Weights[:,i].dot(X[:,i]) / np.sum(Weights[:,i]) + ssr[:,i] = np.square(X[:,i] - mus[i]) + v = Weights.flatten().dot(ssr.flatten()) / np.sum(Weights) + stds = np.ones(n_clusters) * np.sqrt(v) + return mus, stds + + +def update_emission_params_rdr_sitewise(X_rdr, log_gamma, rdr_std, \ + start_rdr_mean=None, shared_rdr_std=False): + """ + Attributes + ---------- + X_nb : array, shape (n_observations, n_spots) + Observed expression UMI count UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = X_rdr.shape[1] + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + new_rdr_mean = copy.copy(start_rdr_mean) if not start_rdr_mean is None else np.ones((n_states, n_spots)) + new_rdr_std = copy.copy(rdr_std) + # expression signal by NB distribution + if not shared_rdr_std: + for s in range(n_spots): + for i in range(n_states): + mu, std = weighted_gaussian_fitting( X_rdr[:,s], gamma[i,:]+gamma[i+n_states,:] ) + new_rdr_mean[i, s] = mu + new_rdr_std[i,s] = std + else: + for s in range(n_spots): + mus, stds = weighted_gaussian_fitting_sharestd( np.vstack([ X_rdr[:,s] for i in range(n_states) ]).T, \ + (gamma[:n_states, :] + gamma[n_states:, :]).T ) + new_rdr_mean[:,s] = mus + new_rdr_std[:,s] = stds + return new_rdr_mean, new_rdr_std + + +def update_emission_params_baf_sitewise(X_baf, log_gamma, p_std, \ + start_p_mean=None, shared_p_std=False, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X_baf : array, shape (n_observations, n_spots) + Observed allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = X_baf.shape[1] + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_p_mean = copy.copy(start_p_mean) if not start_p_mean is None else np.ones((n_states, n_spots)) * 0.5 + new_p_std = copy.copy(p_std) + if not shared_p_std: + for s in np.arange(X_baf.shape[1]): + for i in range(n_states): + mu, std = weighted_gaussian_fitting( np.append(X_baf[:,s], 1-X_baf[:,s]), np.append(gamma[i,:], gamma[i+n_states,:]) ) + new_p_mean[i, s] = mu + new_p_std[i, s] = std + else: + for s in np.arange(X_baf.shape[1]): + concat_X_baf = np.append(X_baf[:,s], 1-X_baf[:,s]) + concat_gamma = np.hstack([gamma[:n_states,:], gamma[n_states:, :]]) + mus, stds = weighted_gaussian_fitting_sharestd( np.vstack([ concat_X_baf for i in range(n_states) ]).T, concat_gamma.T) + new_p_mean[:,s] = mus + new_p_std[:,s] = stds + new_p_mean[new_p_mean[:,s] < min_binom_prob, s] = min_binom_prob + new_p_mean[new_p_mean[:,s] > max_binom_prob, s] = max_binom_prob + return new_p_mean, new_p_std + + +############################################################ +# whole inference +############################################################ + +class hmm_gaussian_sitewise(object): + def __init__(self, params="stmp", t=1-1e-4): + """ + Attributes + ---------- + params : str + Codes for parameters that need to be updated. The corresponding parameter can only be updated if it is included in this argument. "s" for start probability; "t" for transition probability; "m" for Negative Binomial RDR signal; "p" for Beta Binomial BAF signal. + + t : float + Determine initial self transition probability to be 1-t. + """ + self.params = params + self.t = t + # + def run_baum_welch_nb_bb_sitewise(self, X, lengths, n_states, log_sitewise_transmat, \ + shared_rdr_std=False, shared_p_std=False, \ + is_diag=False, init_rdr_mean=None, init_p_mean=None, init_rdr_std=None, init_p_std=None, max_iter=100, tol=1e-4): + ''' + Input + X: size n_observations * n_components * n_spots. + lengths: sum of lengths = n_observations. + base_nb_mean: size of n_observations * n_spots. + In NB-BetaBinom model, n_components = 2 + Intermediate + log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. + alpha: size of n_states. Dispersioon parameter of each HMM state. + ''' + n_obs = X.shape[0] + n_comp = X.shape[1] + n_spots = X.shape[2] + assert n_comp == 2 + # initialize NB logmean shift and BetaBinom prob + rdr_mean = np.vstack([np.linspace(0.5, 3, n_states) for r in range(n_spots)]).T if init_rdr_mean is None else init_rdr_mean + p_mean = np.vstack([np.linspace(0.05, 0.45, n_states) for r in range(n_spots)]).T if init_p_mean is None else init_p_mean + # initialize (inverse of) dispersion param in NB and BetaBinom + rdr_std = 0.5 * np.ones((n_states, n_spots)) if init_rdr_std is None else init_rdr_std + p_std = 0.1 * np.ones((n_states, n_spots)) if init_p_std is None else init_p_std + # initialize start probability and emission probability + log_startprob = np.log( np.ones(n_states) / n_states ) + if n_states > 1: + transmat = np.ones((n_states, n_states)) * (1-self.t) / (n_states-1) + np.fill_diagonal(transmat, self.t) + log_transmat = np.log(transmat) + else: + log_transmat = np.zeros((1,1)) + # EM algorithm + for r in trange(max_iter): + # E step + log_emission = compute_emission_probability_gaussian(X, rdr_mean, rdr_std, p_mean, p_std) + log_alpha = forward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_beta = backward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + log_xi = compute_posterior_transition_sitewise(log_alpha, log_beta, log_transmat, log_emission) + # M step + if "s" in self.params: + new_log_startprob = update_startprob_sitewise(lengths, log_gamma) + new_log_startprob = new_log_startprob.flatten() + else: + new_log_startprob = log_startprob + if "t" in self.params: + new_log_transmat = update_transition_sitewise(log_xi, is_diag=is_diag) + else: + new_log_transmat = log_transmat + if "m" in self.params: + new_rdr_mean, new_rdr_std = update_emission_params_rdr_sitewise(X[:,0,:], log_gamma, rdr_std, start_rdr_mean=rdr_mean, shared_rdr_std=shared_rdr_std) + else: + new_rdr_mean = rdr_mean + new_rdr_std = rdr_std + if "p" in self.params: + new_p_mean, new_p_std = update_emission_params_baf_sitewise(X[:,1,:], log_gamma, p_std, start_p_mean=p_mean, \ + shared_p_std=shared_p_std) + else: + new_p_mean = p_mean + new_p_std = p_std + # check convergence + print( np.mean(np.abs( np.exp(new_log_startprob) - np.exp(log_startprob) )), \ + np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )), \ + np.mean(np.abs(new_rdr_mean - rdr_mean)),\ + np.mean(np.abs(new_p_mean - p_mean)) ) + print( np.hstack([new_rdr_mean, new_p_mean]) ) + if np.mean(np.abs( np.exp(new_log_transmat) - np.exp(log_transmat) )) < tol and \ + np.mean(np.abs(new_rdr_mean - rdr_mean)) < tol and np.mean(np.abs(new_p_mean - p_mean)) < tol: + break + log_startprob = new_log_startprob + log_transmat = new_log_transmat + rdr_mean = new_rdr_mean + rdr_std = new_rdr_std + p_mean = new_p_mean + p_std = new_p_std + return new_rdr_mean, new_rdr_std, new_p_mean, new_p_std, new_log_startprob, new_log_transmat + + +# def posterior_nb_bb_sitewise(X, lengths, rdr_mean, rdr_std, p_mean, p_std, log_startprob, log_transmat, log_sitewise_transmat): +# """ +# Attributes +# ---------- +# X : array, shape (n_observations, n_components, n_spots) +# Observed expression UMI count and allele frequency UMI count. + +# lengths : array, shape (n_chromosomes,) +# Number genes (or bins) per chromosome, the sum of this vector should be equal to n_observations. + +# base_nb_mean : array, shape (n_observations, n_spots) +# Mean expression under diploid state. + +# log_mu : array, shape (n_states, n_spots) +# Log read depth shift of each CNV states. + +# alphas : array, shape (n_states, n_spots) +# Inverse of dispersion in NB distribution of each state. + +# total_bb_RD : array, shape (n_observations, n_spots) +# SNP-covering reads for both REF and ALT across genes along genome. + +# p_mean : array, shape (n_states, n_spots) +# MAF of each CNV states. + +# p_std : array, shape (n_states, n_spots) +# Inverse of dispersion of Beta-Binomial distribution of each state. + +# log_startprob : array, shape (n_states,) +# Log of start probability. + +# log_transmat : array, shape (n_states, n_states) +# Log of transition probability across states. + +# log_sitewise_transmat : array, shape (n_observations) +# Log of phase switch probability of each gene (or bin). +# """ +# log_emission = compute_emission_probability_gaussian(X, rdr_mean, rdr_std, p_mean, p_std) +# log_alpha = forward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) +# log_beta = backward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) +# log_gamma = compute_posterior_obs(log_alpha, log_beta) +# return log_gamma + + +# def loglikelihood_nb_bb_sitewise(X, lengths, rdr_mean, rdr_std, p_mean, p_std, log_startprob, log_transmat, log_sitewise_transmat): +# """ +# Attributes +# ---------- +# X : array, shape (n_observations, n_components, n_spots) +# Observed expression UMI count and allele frequency UMI count. + +# lengths : array, shape (n_chromosomes,) +# Number genes (or bins) per chromosome, the sum of this vector should be equal to n_observations. + +# base_nb_mean : array, shape (n_observations, n_spots) +# Mean expression under diploid state. + +# log_mu : array, shape (n_states, n_spots) +# Log read depth shift of each CNV states. + +# alphas : array, shape (n_states, n_spots) +# Inverse of dispersion in NB distribution of each state. + +# total_bb_RD : array, shape (n_observations, n_spots) +# SNP-covering reads for both REF and ALT across genes along genome. + +# p_mean : array, shape (n_states, n_spots) +# MAF of each CNV states. + +# p_std : array, shape (n_states, n_spots) +# Inverse of dispersion of Beta-Binomial distribution of each state. + +# log_startprob : array, shape (n_states,) +# Log of start probability. + +# log_transmat : array, shape (n_states, n_states) +# Log of transition probability across states. + +# log_sitewise_transmat : array, shape (n_observations) +# Log of phase switch probability of each gene (or bin). +# """ +# log_emission = compute_emission_probability_gaussian(X, rdr_mean, rdr_std, p_mean, p_std) +# log_alpha = forward_lattice_sitewise(lengths, log_transmat, log_startprob, log_emission, log_sitewise_transmat) +# return np.sum(scipy.special.logsumexp(log_alpha[:,np.cumsum(lengths)-1], axis=0)), log_alpha + + +# def viterbi_nb_bb_sitewise(X, lengths, base_nb_mean, log_mu, alphas, total_bb_RD, p_mean, p_std, log_startprob, log_transmat, log_sitewise_transmat): +# ''' +# Input +# X: size n_observations * n_components * n_spots. +# lengths: sum of lengths = n_observations. +# exposures: size of n_observations * n_spots. +# base_prob: size of n_observations. The expression probability derived from normal spots. +# log_mu: size of n_states. Log of mean/exposure/base_prob of each HMM state. +# alpha: size of n_states. Dispersioon parameter of each HMM state. +# log_transmat: n_states * n_states. Transition probability after log transformation. +# log_startprob: n_states. Start probability after log transformation. +# Output +# # log_prob: a scalar. +# labels: size of n_observations. +# Intermediate +# log_emission: n_states * n_observations * n_spots. Log probability. +# log_v: n_states * n_observations per chromosome. Log of viterbi DP table. v[i,t] = max_{q_1, ..., q_{t-1}} P(o_1, q_1, ..., o_{t-1}, q_{t-1}, o_t, q_t=i | lambda). +# ''' +# n_obs = X.shape[0] +# n_comp = X.shape[1] +# n_spots = X.shape[2] +# n_states = log_transmat.shape[0] +# log_sitewise_self_transmat = np.log(1 - np.exp(log_sitewise_transmat)) +# log_emission = compute_emission_probability_gaussian(X, rdr_mean, rdr_std, p_mean, p_std) +# # initialize viterbi DP table and backtracking table +# labels = np.array([]) +# merged_labels = np.array([]) +# cumlen = 0 +# for le in lengths: +# log_v = np.zeros((2*n_states, le)) +# bt = np.zeros((2*n_states, le)) +# for t in np.arange(le): +# if cumlen == 0 and t == 0: +# log_v[:, 0] = np.mean(log_emission[:,0,:], axis=1) + np.append(log_startprob,log_startprob) + np.log(0.5) +# continue +# for i in np.arange(2*n_states): +# if t > 0: +# tmp = log_v[:, (t-1)] + np.append(log_transmat[:,i - n_states * int(i/n_states)], log_transmat[:,i - n_states * int(i/n_states)]) + np.sum(log_emission[i, (cumlen+t), :]) +# else: +# tmp = np.append(log_startprob[i - n_states * int(i/n_states)], log_startprob[i - n_states * int(i/n_states)]) + np.sum(log_emission[i, (cumlen+t), :]) +# bt[i, t] = np.argmax(tmp) +# log_v[i, t] = np.max(tmp) +# # backtracking to get the sequence +# chr_labels = [ np.argmax(log_v[:,-1]) ] + +# if cumlen == 0: +# for t2 in np.arange(le-1, 0, -1): +# chr_labels.append( int(bt[chr_labels[-1],t2])) +# else: +# for t2 in np.arange(le-2, -1, -1): +# chr_labels.append( int(bt[chr_labels[-1],t2])) + +# chr_labels = np.array(chr_labels[::-1]).astype(int) +# # merge two phases +# chr_merged_labels = copy.copy(chr_labels) +# chr_merged_labels[chr_merged_labels >= n_states] = chr_merged_labels[chr_merged_labels >= n_states] - n_states + +# if cumlen == 0: +# labels = chr_labels +# merged_labels = chr_merged_labels +# else: +# labels = np.append(labels, chr_labels) +# merged_labels = np.append(merged_labels, chr_merged_labels) + +# cumlen += le +# return labels, merged_labels + + +from sklearn.mixture import GaussianMixture +def initialization_gaussianhmm_by_gmm(n_states, X, params, random_state=None, min_binom_prob=0.1, max_binom_prob=0.9): + # prepare gmm input of RDR and BAF separately + X_gmm_rdr = None + X_gmm_baf = None + if "m" in params: + X_gmm_rdr = np.vstack([ X[:,0,s] for s in range(X.shape[2]) ]).T + if "p" in params: + X_gmm_baf = np.vstack([ X[:,1,s] for s in range(X.shape[2]) ]).T + X_gmm_baf[X_gmm_baf < min_binom_prob] = min_binom_prob + X_gmm_baf[X_gmm_baf > max_binom_prob] = max_binom_prob + + # combine RDR and BAF + if ("m" in params) and ("p" in params): + indexes = np.where(X_gmm_baf[:,0] > 0.5)[0] + X_gmm_baf[indexes,:] = 1 - X_gmm_baf[indexes,:] + X_gmm = np.hstack([X_gmm_rdr, X_gmm_baf]) + elif "m" in params: + X_gmm = X_gmm_rdr + elif "p" in params: + indexes = np.where(X_gmm_baf[:,0] > 0.5)[0] + X_gmm_baf[indexes,:] = 1 - X_gmm_baf[indexes,:] + X_gmm = X_gmm_baf + assert not np.any(np.isnan(X_gmm)) + # run GMM + if random_state is None: + gmm = GaussianMixture(n_components=n_states, max_iter=1).fit(X_gmm) + else: + gmm = GaussianMixture(n_components=n_states, max_iter=1, random_state=random_state).fit(X_gmm) + # turn gmm fitted parameters to HMM rdr_mean and p_mean parameters + if ("m" in params) and ("p" in params): + gmm_rdr_mean = gmm.means_[:,:X.shape[2]] + gmm_p_mean = gmm.means_[:, X.shape[2]:] + elif "m" in params: + gmm_rdr_mean = gmm.means_ + gmm_p_mean = None + elif "p" in params: + gmm_rdr_mean = None + gmm_p_mean = gmm.means_ + return gmm_rdr_mean, gmm_p_mean + + +def pipeline_gaussian_baum_welch(X, lengths, n_states, log_sitewise_transmat, params="smp", t=1-1e-6, random_state=0, \ + shared_rdr_std=True, shared_p_std=True, init_rdr_mean=None, init_p_mean=None, init_rdr_std=None, init_p_std=None, \ + is_diag=True, max_iter=100, tol=1e-4): + # initialization + n_spots = X.shape[2] + if ((init_rdr_mean is None) and ("m" in params)) or ((init_p_mean is None) and ("p" in params)): + tmp_rdr_mean, tmp_p_mean = initialization_gaussianhmm_by_gmm(n_states, X, params, random_state=random_state) + if (init_rdr_mean is None) and ("m" in params): + init_rdr_mean = tmp_rdr_mean + if (init_p_mean is None) and ("p" in params): + init_p_mean = tmp_p_mean + print(f"init_log_mu = {init_rdr_mean}") + print(f"init_p_mean = {init_p_mean}") + + # fit HMM-NB-BetaBinom + hmmmodel = hmm_gaussian_sitewise(params=params, t=t) + new_rdr_mean, new_rdr_std, new_p_mean, new_p_std, new_log_startprob, new_log_transmat = hmmmodel.run_baum_welch_nb_bb_sitewise(X, lengths, \ + n_states, log_sitewise_transmat, shared_rdr_std=shared_rdr_std, shared_p_std=shared_p_std, is_diag=is_diag, \ + init_rdr_mean=init_rdr_mean, init_p_mean=init_p_mean, init_rdr_std=init_rdr_std, init_p_std=init_p_std, max_iter=max_iter, tol=tol) + + # likelihood, posterior and prediction + log_emission = compute_emission_probability_gaussian(X, new_rdr_mean, new_rdr_std, new_p_mean, new_p_std) + log_alpha = forward_lattice_sitewise(lengths, new_log_transmat, new_log_startprob, log_emission, log_sitewise_transmat) + log_beta = backward_lattice_sitewise(lengths, new_log_transmat, new_log_startprob, log_emission, log_sitewise_transmat) + log_gamma = compute_posterior_obs(log_alpha, log_beta) + pred = np.argmax(log_gamma, axis=0) + pred_cnv = pred % n_states + llf = np.sum(scipy.special.logsumexp(log_alpha[:,np.cumsum(lengths)-1], axis=0)) + + # save results + res = {"new_rdr_mean":new_rdr_mean, "new_rdr_std":new_rdr_std, "new_p_mean":new_p_mean, "new_p_std":new_p_std, \ + "new_log_startprob":new_log_startprob, "new_log_transmat":new_log_transmat, "log_gamma":log_gamma, "pred_cnv":pred_cnv, "llf":llf} + return res + diff --git a/src/calicost/hmrf.py b/src/calicost/hmrf.py new file mode 100644 index 0000000..185ca3a --- /dev/null +++ b/src/calicost/hmrf.py @@ -0,0 +1,1101 @@ +import logging +from turtle import reset +import numpy as np +import pandas as pd +from numba import njit +import scipy.special +import scipy.sparse +from sklearn.mixture import GaussianMixture +from sklearn.cluster import KMeans +from sklearn.metrics import adjusted_rand_score, silhouette_score +from sklearn.neighbors import kneighbors_graph +import networkx as nx +from tqdm import trange +import copy +from pathlib import Path +from calicost.hmm_NB_BB_phaseswitch import * +from calicost.utils_distribution_fitting import * +from calicost.utils_IO import * +from calicost.utils_hmrf import * + +import warnings +from statsmodels.tools.sm_exceptions import ValueWarning + + +############################################################ +# Pure clone +############################################################ + +def hmrf_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, res, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = res["new_log_mu"].shape[1] + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + for c in range(n_clones): + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"][:,c:(c+1)], res["new_alphas"][:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"][:,c:(c+1)], res["new_taus"][:,c:(c+1)]) + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,i:(i+1)] > 0) / np.sum(single_base_nb_mean[:,i:(i+1)] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + else: + single_llf[i,c] = np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + if new_assignment[j] >= 0: + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def aggr_hmrf_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, res, pred, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = res["new_log_mu"].shape[1] + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + # idx = np.append(idx, np.array([i])) + for c in range(n_clones): + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"][:,c:(c+1)], res["new_alphas"][:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"][:,c:(c+1)], res["new_taus"][:,c:(c+1)]) + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,idx] > 0) / np.sum(single_base_nb_mean[:,idx] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + else: + single_llf[i,c] = np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + if new_assignment[j] >= 0: + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def hmrf_reassignment_posterior_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, res, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = np.max(prev_assignment) + 1 + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"], res["new_alphas"], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"], res["new_taus"]) + for c in range(n_clones): + if np.sum(single_base_nb_mean[:,i:(i+1)] > 0) > 0 and np.sum(single_total_bb_RD[:,i:(i+1)] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,i:(i+1)] > 0) / np.sum(single_base_nb_mean[:,i:(i+1)] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + else: + single_llf[i,c] = np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def aggr_hmrf_reassignment_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, res, pred, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + """ + HMRF assign spots to tumor clones. + + Attributes + ---------- + single_X : array, shape (n_bins, 2, n_spots) + BAF and RD count matrix for all bins in all spots. + + single_base_nb_mean : array, shape (n_bins, n_spots) + Diploid baseline of gene expression matrix. + + single_total_bb_RD : array, shape (n_obs, n_spots) + Total allele UMI count matrix. + + res : dictionary + Dictionary of estimated HMM parameters. + + pred : array, shape (n_bins * n_clones) + HMM states for all bins and all clones. (Derived from forward-backward algorithm) + + smooth_mat : array, shape (n_spots, n_spots) + Matrix used for feature propagation for computing log likelihood. + + adjacency_mat : array, shape (n_spots, n_spots) + Adjacency matrix used to evaluate label consistency in HMRF. + + prev_assignment : array, shape (n_spots,) + Clone assignment of the previous iteration. + + spatial_weight : float + Scaling factor for HMRF label consistency between adjacent spots. + + Returns + ---------- + new_assignment : array, shape (n_spots,) + Clone assignment of this new iteration. + + single_llf : array, shape (n_spots, n_clones) + Log likelihood of each spot given that its label is each clone. + + total_llf : float + The HMRF objective, which is the sum of log likelihood under the optimal labels plus the sum of edge potentials. + """ + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = int(len(pred) / n_obs) + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + # idx = np.append(idx, np.array([i])) + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"], res["new_alphas"], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"], res["new_taus"]) + for c in range(n_clones): + this_pred = pred[(c*n_obs):(c*n_obs+n_obs)] + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,idx] > 0) / np.sum(single_base_nb_mean[:,idx] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[this_pred, np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[this_pred, np.arange(n_obs), 0]) + else: + single_llf[i,c] = np.sum(tmp_log_emission_rdr[this_pred, np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[this_pred, np.arange(n_obs), 0]) + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + # new_assignment[i] = np.argmax( w_node ) + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def merge_by_minspots(assignment, res, single_total_bb_RD, min_spots_thresholds=50, min_umicount_thresholds=0, single_tumor_prop=None, threshold=0.5): + n_clones = len(np.unique(assignment)) + if n_clones == 1: + merged_groups = [ [assignment[0]] ] + return merged_groups, res + + n_obs = int(len(res["pred_cnv"]) / n_clones) + new_assignment = copy.copy(assignment) + if single_tumor_prop is None: + tmp_single_tumor_prop = np.array([1] * len(assignment)) + else: + tmp_single_tumor_prop = single_tumor_prop + unique_assignment = np.unique(new_assignment) + # find entries in unique_assignment such that either min_spots_thresholds or min_umicount_thresholds is not satisfied + failed_clones = [ c for c in unique_assignment if (np.sum(new_assignment[tmp_single_tumor_prop > threshold] == c) < min_spots_thresholds) or \ + (np.sum(single_total_bb_RD[:, (new_assignment == c)&(tmp_single_tumor_prop > threshold)]) < min_umicount_thresholds) ] + # find the remaining unique_assigment that satisfies both thresholds + successful_clones = [ c for c in unique_assignment if not c in failed_clones ] + # initial merging groups: each successful clone is its own group + merging_groups = [[i] for i in successful_clones] + # for each failed clone, assign them to the closest successful clone + if len(failed_clones) > 0: + for c in failed_clones: + idx_max = np.argmax([np.sum(single_total_bb_RD[:, (new_assignment == c_prime)&(tmp_single_tumor_prop > threshold)]) for c_prime in successful_clones]) + merging_groups[idx_max].append(c) + map_clone_id = {} + for i,x in enumerate(merging_groups): + for z in x: + map_clone_id[z] = i + new_assignment = np.array([map_clone_id[x] for x in new_assignment]) + # while np.min(np.bincount(new_assignment[tmp_single_tumor_prop > threshold])) < min_spots_thresholds or \ + # np.min([ np.sum(single_total_bb_RD[:, (new_assignment == c)&(tmp_single_tumor_prop > threshold)]) for c in unique_assignment ]) < min_umicount_thresholds: + # idx_min = np.argmin(np.bincount(new_assignment[tmp_single_tumor_prop > threshold])) + # idx_max = np.argmax(np.bincount(new_assignment[tmp_single_tumor_prop > threshold])) + # merging_groups = [ [i] for i in range(n_clones) if (i!=idx_min) and (i!=idx_max)] + [[idx_min, idx_max]] + # merging_groups.sort(key = lambda x:np.min(x)) + # # clone assignment after merging + # map_clone_id = {} + # for i,x in enumerate(merging_groups): + # for z in x: + # map_clone_id[z] = i + # new_assignment = np.array([map_clone_id[x] for x in new_assignment]) + # unique_assignment = np.unique(new_assignment) + merged_res = copy.copy(res) + merged_res["new_assignment"] = new_assignment + merged_res["total_llf"] = np.NAN + merged_res["pred_cnv"] = np.concatenate([ res["pred_cnv"][(c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) + merged_res["log_gamma"] = np.hstack([ res["log_gamma"][:, (c[0]*n_obs):(c[0]*n_obs+n_obs)] for c in merging_groups ]) + return merging_groups, merged_res + + +def hmrf_pipeline(outdir, single_X, lengths, single_base_nb_mean, single_total_bb_RD, initial_clone_index, n_states, \ + log_sitewise_transmat, coords=None, smooth_mat=None, adjacency_mat=None, sample_ids=None, max_iter_outer=5, nodepotential="max", \ + hmmclass=hmm_sitewise, params="stmp", t=1-1e-6, random_state=0, init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None,\ + fix_NB_dispersion=False, shared_NB_dispersion=True, fix_BB_dispersion=False, shared_BB_dispersion=True, \ + is_diag=True, max_iter=100, tol=1e-4, unit_xsquared=9, unit_ysquared=3, spatial_weight=1.0): + n_obs, _, n_spots = single_X.shape + n_clones = len(initial_clone_index) + # spot adjacency matric + assert not (coords is None and adjacency_mat is None) + if adjacency_mat is None: + adjacency_mat = compute_adjacency_mat(coords, unit_xsquared, unit_ysquared) + if sample_ids is None: + sample_ids = np.zeros(n_spots, dtype=int) + n_samples = len(np.unique(sample_ids)) + else: + unique_sample_ids = np.unique(sample_ids) + n_samples = len(unique_sample_ids) + tmp_map_index = {unique_sample_ids[i]:i for i in range(len(unique_sample_ids))} + sample_ids = np.array([ tmp_map_index[x] for x in sample_ids]) + log_persample_weights = np.ones((n_clones, n_samples)) * np.log(n_clones) + # pseudobulk + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index) + # initialize HMM parameters by GMM + if (init_log_mu is None) or (init_p_binom is None): + init_log_mu, init_p_binom = initialization_by_gmm(n_states, X, base_nb_mean, total_bb_RD, params, random_state=random_state, in_log_space=False, only_minor=False) + # initialization parameters for HMM + if ("m" in params) and ("p" in params): + last_log_mu = init_log_mu + last_p_binom = init_p_binom + elif "m" in params: + last_log_mu = init_log_mu + last_p_binom = None + elif "p" in params: + last_log_mu = None + last_p_binom = init_p_binom + last_alphas = init_alphas + last_taus = init_taus + last_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + last_assignment[idx] = c + # HMM + for r in range(max_iter_outer): + if not Path(f"{outdir}/round{r}_nstates{n_states}_{params}.npz").exists(): + ##### initialize with the parameters of last iteration ##### + res = pipeline_baum_welch(None, X, lengths, n_states, base_nb_mean, total_bb_RD, log_sitewise_transmat, \ + hmmclass=hmmclass, params=params, t=t, random_state=random_state, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + is_diag=is_diag, init_log_mu=last_log_mu, init_p_binom=last_p_binom, init_alphas=last_alphas, init_taus=last_taus, max_iter=max_iter, tol=tol) + pred = np.argmax(res["log_gamma"], axis=0) + # clone assignmment + if nodepotential == "max": + new_assignment, single_llf, total_llf = aggr_hmrf_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, res, pred, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + elif nodepotential == "weighted_sum": + new_assignment, single_llf, total_llf = hmrf_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, res, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + else: + raise Exception("Unknown mode for nodepotential!") + # handle the case when one clone has zero spots + if len(np.unique(new_assignment)) < X.shape[2]: + res["assignment_before_reindex"] = new_assignment + remaining_clones = np.sort(np.unique(new_assignment)) + re_indexing = {c:i for i,c in enumerate(remaining_clones)} + new_assignment = np.array([re_indexing[x] for x in new_assignment]) + # + res["prev_assignment"] = last_assignment + res["new_assignment"] = new_assignment + res["total_llf"] = total_llf + + # save results + np.savez(f"{outdir}/round{r}_nstates{n_states}_{params}.npz", **res) + + else: + res = np.load(f"{outdir}/round{r}_nstates{n_states}_{params}.npz") + + # regroup to pseudobulk + clone_index = [np.where(res["new_assignment"] == c)[0] for c in np.sort(np.unique(res["new_assignment"]))] + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + + # update last parameter + if "mp" in params: + print("outer iteration {}: total_llf = {}, difference between parameters = {}, {}".format( r, res["total_llf"], np.mean(np.abs(last_log_mu-res["new_log_mu"])), np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + elif "m" in params: + print("outer iteration {}: total_llf = {}, difference between NB parameters = {}".format( r, res["total_llf"], np.mean(np.abs(last_log_mu-res["new_log_mu"])) )) + elif "p" in params: + print("outer iteration {}: total_llf = {}, difference between BetaBinom parameters = {}".format( r, res["total_llf"], np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + print("outer iteration {}: ARI between assignment = {}".format( r, adjusted_rand_score(last_assignment, res["new_assignment"]) )) + if adjusted_rand_score(last_assignment, res["new_assignment"]) > 0.99 or len(np.unique(res["new_assignment"])) == 1: + break + last_log_mu = res["new_log_mu"] + last_p_binom = res["new_p_binom"] + last_alphas = res["new_alphas"] + last_taus = res["new_taus"] + last_assignment = res["new_assignment"] + log_persample_weights = np.ones((X.shape[2], n_samples)) * (-np.log(X.shape[2])) + for sidx in range(n_samples): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res["new_assignment"][index], minlength=X.shape[2]) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + + +def hmrf_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, initial_clone_index, n_states, \ + log_sitewise_transmat, coords=None, smooth_mat=None, adjacency_mat=None, sample_ids=None, max_iter_outer=5, nodepotential="max", hmmclass=hmm_sitewise, \ + params="stmp", t=1-1e-6, random_state=0, init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None,\ + fix_NB_dispersion=False, shared_NB_dispersion=True, fix_BB_dispersion=False, shared_BB_dispersion=True, \ + is_diag=True, max_iter=100, tol=1e-4, unit_xsquared=9, unit_ysquared=3, spatial_weight=1.0): + n_obs, _, n_spots = single_X.shape + n_clones = len(initial_clone_index) + # checking input + assert not (coords is None and adjacency_mat is None) + if adjacency_mat is None: + adjacency_mat = compute_adjacency_mat(coords, unit_xsquared, unit_ysquared) + if sample_ids is None: + sample_ids = np.zeros(n_spots, dtype=int) + n_samples = len(np.unique(sample_ids)) + else: + unique_sample_ids = np.unique(sample_ids) + n_samples = len(unique_sample_ids) + tmp_map_index = {unique_sample_ids[i]:i for i in range(len(unique_sample_ids))} + sample_ids = np.array([ tmp_map_index[x] for x in sample_ids]) + log_persample_weights = np.ones((n_clones, n_samples)) * np.log(n_clones) + # pseudobulk + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index) + # initialize HMM parameters by GMM + if (init_log_mu is None) or (init_p_binom is None): + init_log_mu, init_p_binom = initialization_by_gmm(n_states, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), params, random_state=random_state, in_log_space=False, only_minor=False) + # initialization parameters for HMM + if ("m" in params) and ("p" in params): + last_log_mu = init_log_mu + last_p_binom = init_p_binom + elif "m" in params: + last_log_mu = init_log_mu + last_p_binom = None + elif "p" in params: + last_log_mu = None + last_p_binom = init_p_binom + last_alphas = init_alphas + last_taus = init_taus + last_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + last_assignment[idx] = c + + # HMM + for r in range(max_iter_outer): + # assuming file f"{outdir}/{prefix}_nstates{n_states}_{params}.npz" exists. When r == 0, f"{outdir}/{prefix}_nstates{n_states}_{params}.npz" should contain two keys: "num_iterations" and f"round_-1_assignment" for clone initialization + allres = np.load(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", allow_pickle=True) + allres = dict(allres) + if allres["num_iterations"] > r: + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + else: + res = pipeline_baum_welch(None, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), np.tile(lengths, X.shape[2]), n_states, \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), \ + hmmclass=hmmclass, params=params, t=t, random_state=random_state, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + is_diag=is_diag, init_log_mu=last_log_mu, init_p_binom=last_p_binom, init_alphas=last_alphas, init_taus=last_taus, max_iter=max_iter, tol=tol) + pred = np.argmax(res["log_gamma"], axis=0) + # HMRF clone assignmment + if nodepotential == "max": + new_assignment, single_llf, total_llf = aggr_hmrf_reassignment_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, res, pred, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + elif nodepotential == "weighted_sum": + new_assignment, single_llf, total_llf = hmrf_reassignment_posterior_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, res, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + else: + raise Exception("Unknown mode for nodepotential!") + # handle the case when one clone has zero spots + if len(np.unique(new_assignment)) < X.shape[2]: + res["assignment_before_reindex"] = new_assignment + remaining_clones = np.sort(np.unique(new_assignment)) + re_indexing = {c:i for i,c in enumerate(remaining_clones)} + new_assignment = np.array([re_indexing[x] for x in new_assignment]) + concat_idx = np.concatenate([ np.arange(c*n_obs, c*n_obs+n_obs) for c in remaining_clones ]) + res["log_gamma"] = res["log_gamma"][:,concat_idx] + res["pred_cnv"] = res["pred_cnv"][concat_idx] + # + res["prev_assignment"] = last_assignment + res["new_assignment"] = new_assignment + res["total_llf"] = total_llf + # append to allres + for k,v in res.items(): + if k == "prev_assignment": + allres[f"round{r-1}_assignment"] = v + elif k == "new_assignment": + allres[f"round{r}_assignment"] = v + else: + allres[f"round{r}_{k}"] = v + allres["num_iterations"] = r + 1 + np.savez(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", **allres) + # + # regroup to pseudobulk + clone_index = [np.where(res["new_assignment"] == c)[0] for c in np.sort(np.unique(res["new_assignment"]))] + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + # + if "mp" in params: + print("outer iteration {}: difference between parameters = {}, {}".format( r, np.mean(np.abs(last_log_mu-res["new_log_mu"])), np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + elif "m" in params: + print("outer iteration {}: difference between NB parameters = {}".format( r, np.mean(np.abs(last_log_mu-res["new_log_mu"])) )) + elif "p" in params: + print("outer iteration {}: difference between BetaBinom parameters = {}".format( r, np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + print("outer iteration {}: ARI between assignment = {}".format( r, adjusted_rand_score(last_assignment, res["new_assignment"]) )) + # if np.all( last_assignment == res["new_assignment"] ): + if adjusted_rand_score(last_assignment, res["new_assignment"]) > 0.99 or len(np.unique(res["new_assignment"])) == 1: + break + last_log_mu = res["new_log_mu"] + last_p_binom = res["new_p_binom"] + last_alphas = res["new_alphas"] + last_taus = res["new_taus"] + last_assignment = res["new_assignment"] + log_persample_weights = np.ones((X.shape[2], n_samples)) * (-np.log(X.shape[2])) + for sidx in range(n_samples): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res["new_assignment"][index], minlength=X.shape[2]) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + + + +############################################################ +# Normal-tumor clone mixture +############################################################ + +def aggr_hmrfmix_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, pred, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = res["new_log_mu"].shape[1] + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + lambd = np.sum(single_base_nb_mean, axis=1) / np.sum(single_base_nb_mean) + # + posterior = np.zeros((N, n_clones)) + # + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + idx = idx[~np.isnan(single_tumor_prop[idx])] + for c in range(n_clones): + if np.sum(single_base_nb_mean[:,idx] > 0) > 0: + mu = np.exp(res["new_log_mu"][(pred%n_states),:]) / np.sum(np.exp(res["new_log_mu"][(pred%n_states),:]) * lambd) + weighted_tp = (np.mean(single_tumor_prop[idx]) * mu) / (np.mean(single_tumor_prop[idx]) * mu + 1 - np.mean(single_tumor_prop[idx])) + else: + weighted_tp = np.repeat(np.mean(single_tumor_prop[idx]), single_X.shape[0]) + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"][:,c:(c+1)], res["new_alphas"][:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"][:,c:(c+1)], res["new_taus"][:,c:(c+1)], np.ones((n_obs,1)) * np.mean(single_tumor_prop[idx]), weighted_tp.reshape(-1,1) ) + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,idx] > 0) / np.sum(single_base_nb_mean[:,idx] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + else: + single_llf[i,c] = np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + # + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + if new_assignment[j] >= 0: + # w_edge[new_assignment[j]] += 1 + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + # + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def hmrfmix_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = res["new_log_mu"].shape[1] + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + lambd = np.sum(single_base_nb_mean, axis=1) / np.sum(single_base_nb_mean) + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + idx = idx[~np.isnan(single_tumor_prop[idx])] + for c in range(n_clones): + if np.sum(single_base_nb_mean) > 0: + this_pred_cnv = res["pred_cnv"][:,c] + logmu_shift = np.array( scipy.special.logsumexp(res["new_log_mu"][this_pred_cnv,c] + np.log(lambd), axis=0) ) + kwargs = {"logmu_shift":logmu_shift.reshape(1,1), "sample_length":np.array([n_obs])} + else: + kwargs = {} + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"][:,c:(c+1)], res["new_alphas"][:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"][:,c:(c+1)], res["new_taus"][:,c:(c+1)], np.ones((n_obs,1)) * np.mean(single_tumor_prop[idx]), **kwargs ) + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,i:(i+1)] > 0) / np.sum(single_base_nb_mean[:,i:(i+1)] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + else: + single_llf[i,c] = np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + if new_assignment[j] >= 0: + # w_edge[new_assignment[j]] += 1 + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def hmrfmix_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_index, n_states, log_sitewise_transmat, \ + coords=None, smooth_mat=None, adjacency_mat=None, sample_ids=None, max_iter_outer=5, nodepotential="max", hmmclass=hmm_sitewise, params="stmp", t=1-1e-6, random_state=0, \ + init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None,\ + fix_NB_dispersion=False, shared_NB_dispersion=True, fix_BB_dispersion=False, shared_BB_dispersion=True, \ + is_diag=True, max_iter=100, tol=1e-4, unit_xsquared=9, unit_ysquared=3, spatial_weight=1.0/6, tumorprop_threshold=0.5): + n_obs, _, n_spots = single_X.shape + n_clones = len(initial_clone_index) + # spot adjacency matric + assert not (coords is None and adjacency_mat is None) + if adjacency_mat is None: + adjacency_mat = compute_adjacency_mat(coords, unit_xsquared, unit_ysquared) + if sample_ids is None: + sample_ids = np.zeros(n_spots, dtype=int) + n_samples = len(np.unique(sample_ids)) + else: + unique_sample_ids = np.unique(sample_ids) + n_samples = len(unique_sample_ids) + tmp_map_index = {unique_sample_ids[i]:i for i in range(len(unique_sample_ids))} + sample_ids = np.array([ tmp_map_index[x] for x in sample_ids]) + log_persample_weights = np.ones((n_clones, n_samples)) * np.log(n_clones) + # pseudobulk + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index, single_tumor_prop, threshold=tumorprop_threshold) + # initialize HMM parameters by GMM + if (init_log_mu is None) or (init_p_binom is None): + init_log_mu, init_p_binom = initialization_by_gmm(n_states, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), params, random_state=random_state, in_log_space=False, only_minor=False) + # initialization parameters for HMM + if ("m" in params) and ("p" in params): + last_log_mu = init_log_mu + last_p_binom = init_p_binom + elif "m" in params: + last_log_mu = init_log_mu + last_p_binom = None + elif "p" in params: + last_log_mu = None + last_p_binom = init_p_binom + last_alphas = init_alphas + last_taus = init_taus + last_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + last_assignment[idx] = c + n_clones = len(initial_clone_index) + + # HMM + for r in range(max_iter_outer): + allres = np.load(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", allow_pickle=True) + allres = dict(allres) + if allres["num_iterations"] > r: + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + else: + res = {"new_log_mu":[], "new_alphas":[], "new_p_binom":[], "new_taus":[], "new_log_startprob":[], "new_log_transmat":[], "log_gamma":[], "pred_cnv":[], "llf":[]} + for c in range(n_clones): + tmpres = pipeline_baum_welch(None, X[:,:,c:(c+1)], lengths, n_states, base_nb_mean[:,c:(c+1)], total_bb_RD[:,c:(c+1)], log_sitewise_transmat, np.repeat(tumor_prop[c], X.shape[0]).reshape(-1,1), \ + hmmclass=hmmclass, params=params, t=t, \ + random_state=random_state, fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + is_diag=is_diag, init_log_mu=last_log_mu[:,c:(c+1)], init_p_binom=last_p_binom[:,c:(c+1)], init_alphas=last_alphas[:,c:(c+1)], init_taus=last_taus[:,c:(c+1)], max_iter=max_iter, tol=tol) + pred = np.argmax(tmpres["log_gamma"], axis=0) + for k in res.keys(): + res[k] = [res[k], tmpres[k]] + res["new_log_mu"] = np.hstack(res["new_log_mu"]) + res["new_alphas"] = np.hstack(res["new_alphas"]) + res["new_p_binom"] = np.hstack(res["new_p_binom"]) + res["new_taus"] = np.hstack(res["new_taus"]) + res["new_log_startprob"] = np.hstack(res["new_log_startprob"]) + res["new_log_transmat"] = np.dstack(res["new_log_transmat"]) + res["log_gamma"] = np.hstack(res["log_gamma"]) + res["pred_cnv"] = np.vstack(res["pred_cnv"]).T + + # clone assignmment + if nodepotential == "max": + new_assignment, single_llf, total_llf = aggr_hmrfmix_reassignment(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, pred, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + elif nodepotential == "weighted_sum": + new_assignment, single_llf, total_llf = hmrfmix_reassignment_posterior(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + else: + raise Exception("Unknown mode for nodepotential!") + # handle the case when one clone has zero spots + if len(np.unique(new_assignment)) < X.shape[2]: + res["assignment_before_reindex"] = new_assignment + remaining_clones = np.sort(np.unique(new_assignment)) + re_indexing = {c:i for i,c in enumerate(remaining_clones)} + new_assignment = np.array([re_indexing[x] for x in new_assignment]) + # + res["prev_assignment"] = last_assignment + res["new_assignment"] = new_assignment + res["total_llf"] = total_llf + + # append to allres + for k,v in res.items(): + if k == "prev_assignment": + allres[f"round{r-1}_assignment"] = v + elif k == "new_assignment": + allres[f"round{r}_assignment"] = v + else: + allres[f"round{r}_{k}"] = v + allres["num_iterations"] = r + 1 + np.savez(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", **allres) + + # regroup to pseudobulk + clone_index = [np.where(res["new_assignment"] == c)[0] for c in np.sort(np.unique(res["new_assignment"]))] + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop, threshold=tumorprop_threshold) + + # update last parameter + if "mp" in params: + print("outer iteration {}: total_llf = {}, difference between parameters = {}, {}".format( r, res["total_llf"], np.mean(np.abs(last_log_mu-res["new_log_mu"])), np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + elif "m" in params: + print("outer iteration {}: total_llf = {}, difference between NB parameters = {}".format( r, res["total_llf"], np.mean(np.abs(last_log_mu-res["new_log_mu"])) )) + elif "p" in params: + print("outer iteration {}: total_llf = {}, difference between BetaBinom parameters = {}".format( r, res["total_llf"], np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + print("outer iteration {}: ARI between assignment = {}".format( r, adjusted_rand_score(last_assignment, res["new_assignment"]) )) + # if np.all( last_assignment == res["new_assignment"] ): + if adjusted_rand_score(last_assignment, res["new_assignment"]) > 0.99 or len(np.unique(res["new_assignment"])) == 1: + break + last_log_mu = res["new_log_mu"] + last_p_binom = res["new_p_binom"] + last_alphas = res["new_alphas"] + last_taus = res["new_taus"] + last_assignment = res["new_assignment"] + log_persample_weights = np.ones((X.shape[2], n_samples)) * (-np.log(X.shape[2])) + for sidx in range(n_samples): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res["new_assignment"][index], minlength=X.shape[2]) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + + +def hmrfmix_reassignment_posterior_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = np.max(prev_assignment) + 1 + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + lambd = np.sum(single_base_nb_mean, axis=1) / np.sum(single_base_nb_mean) + if np.sum(single_base_nb_mean) > 0: + logmu_shift = [] + for c in range(n_clones): + this_pred_cnv = np.argmax(res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0)%n_states + logmu_shift.append( scipy.special.logsumexp(res["new_log_mu"][this_pred_cnv,:] + np.log(lambd).reshape(-1,1), axis=0) ) + logmu_shift = np.vstack(logmu_shift) + kwargs = {"logmu_shift":logmu_shift, "sample_length":np.ones(n_clones,dtype=int) * n_obs} + else: + kwargs = {} + # + posterior = np.zeros((N, n_clones)) + + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + idx = idx[~np.isnan(single_tumor_prop[idx])] + for c in range(n_clones): + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"], res["new_alphas"], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"], res["new_taus"], np.ones((n_obs,1)) * np.mean(single_tumor_prop[idx]), **kwargs ) + + if np.sum(single_base_nb_mean[:,i:(i+1)] > 0) > 0 and np.sum(single_total_bb_RD[:,i:(i+1)] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,i:(i+1)] > 0) / np.sum(single_base_nb_mean[:,i:(i+1)] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + else: + single_llf[i,c] = np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + \ + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:, :, 0] + res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)], axis=0) ) + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + # w_edge[new_assignment[j]] += 1 + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def aggr_hmrfmix_reassignment_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, pred, smooth_mat, adjacency_mat, prev_assignment, sample_ids, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise, return_posterior=False): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = int(len(pred) / n_obs) + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + # + lambd = np.sum(single_base_nb_mean, axis=1) / np.sum(single_base_nb_mean) + # + posterior = np.zeros((N, n_clones)) + # + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + idx = idx[~np.isnan(single_tumor_prop[idx])] + for c in range(n_clones): + this_pred = pred[(c*n_obs):(c*n_obs+n_obs)] + if np.sum(single_base_nb_mean[:,idx] > 0) > 0: + mu = np.exp(res["new_log_mu"][(this_pred%n_states),:]) / np.sum(np.exp(res["new_log_mu"][(this_pred%n_states),:]) * lambd) + weighted_tp = (np.mean(single_tumor_prop[idx]) * mu) / (np.mean(single_tumor_prop[idx]) * mu + 1 - np.mean(single_tumor_prop[idx])) + else: + weighted_tp = np.repeat(np.mean(single_tumor_prop[idx]), single_X.shape[0]) + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"], res["new_alphas"], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"], res["new_taus"], np.ones((n_obs,1)) * np.mean(single_tumor_prop[idx]), weighted_tp.reshape(-1,1) ) + + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,idx] > 0) / np.sum(single_base_nb_mean[:,idx] > 0) + # ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[this_pred, np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[this_pred, np.arange(n_obs), 0]) + else: + single_llf[i,c] = np.sum(tmp_log_emission_rdr[this_pred, np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[this_pred, np.arange(n_obs), 0]) + w_node = single_llf[i,:] + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + # w_edge[new_assignment[j]] += 1 + w_edge[new_assignment[j]] += adjacency_mat[i,j] + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + # + posterior[i,:] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + # + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + if return_posterior: + return new_assignment, single_llf, total_llf, posterior + else: + return new_assignment, single_llf, total_llf + + +def hmrfmix_concatenate_pipeline(outdir, prefix, single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_index, n_states, log_sitewise_transmat, \ + coords=None, smooth_mat=None, adjacency_mat=None, sample_ids=None, max_iter_outer=5, nodepotential="max", hmmclass=hmm_sitewise, params="stmp", t=1-1e-6, random_state=0, \ + init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None,\ + fix_NB_dispersion=False, shared_NB_dispersion=True, fix_BB_dispersion=False, shared_BB_dispersion=True, \ + is_diag=True, max_iter=100, tol=1e-4, unit_xsquared=9, unit_ysquared=3, spatial_weight=1.0/6, tumorprop_threshold=0.5): + n_obs, _, n_spots = single_X.shape + n_clones = len(initial_clone_index) + # spot adjacency matric + assert not (coords is None and adjacency_mat is None) + if adjacency_mat is None: + adjacency_mat = compute_adjacency_mat(coords, unit_xsquared, unit_ysquared) + if sample_ids is None: + sample_ids = np.zeros(n_spots, dtype=int) + n_samples = len(np.unique(sample_ids)) + else: + unique_sample_ids = np.unique(sample_ids) + n_samples = len(unique_sample_ids) + tmp_map_index = {unique_sample_ids[i]:i for i in range(len(unique_sample_ids))} + sample_ids = np.array([ tmp_map_index[x] for x in sample_ids]) + log_persample_weights = np.ones((n_clones, n_samples)) * (-np.log(n_clones)) + # pseudobulk + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index, single_tumor_prop, threshold=tumorprop_threshold) + # baseline proportion of UMI counts + lambd = np.sum(single_base_nb_mean, axis=1) / np.sum(single_base_nb_mean) + # initialize HMM parameters by GMM + if (init_log_mu is None) or (init_p_binom is None): + init_log_mu, init_p_binom = initialization_by_gmm(n_states, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), params, random_state=random_state, in_log_space=False, only_minor=False) + # initialization parameters for HMM + if ("m" in params) and ("p" in params): + last_log_mu = init_log_mu + last_p_binom = init_p_binom + elif "m" in params: + last_log_mu = init_log_mu + last_p_binom = None + elif "p" in params: + last_log_mu = None + last_p_binom = init_p_binom + last_alphas = init_alphas + last_taus = init_taus + last_assignment = np.zeros(single_X.shape[2], dtype=int) + for c,idx in enumerate(initial_clone_index): + last_assignment[idx] = c + + # HMM + for r in range(max_iter_outer): + # assuming file f"{outdir}/{prefix}_nstates{n_states}_{params}.npz" exists. When r == 0, f"{outdir}/{prefix}_nstates{n_states}_{params}.npz" should contain two keys: "num_iterations" and f"round_-1_assignment" for clone initialization + allres = np.load(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", allow_pickle=True) + allres = dict(allres) + if allres["num_iterations"] > r: + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + else: + sample_length = np.ones(X.shape[2],dtype=int) * X.shape[0] + remain_kwargs = {"sample_length":sample_length, "lambd":lambd} + if f"round{r-1}_log_gamma" in allres: + remain_kwargs["log_gamma"] = allres[f"round{r-1}_log_gamma"] + res = pipeline_baum_welch(None, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), np.tile(lengths, X.shape[2]), n_states, \ + # base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), tumor_prop, \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), np.repeat(tumor_prop, X.shape[0]).reshape(-1,1), \ + hmmclass=hmmclass, params=params, t=t, random_state=random_state, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, \ + is_diag=is_diag, init_log_mu=last_log_mu, init_p_binom=last_p_binom, init_alphas=last_alphas, init_taus=last_taus, max_iter=max_iter, tol=tol, **remain_kwargs) + pred = np.argmax(res["log_gamma"], axis=0) + # clone assignmment + if nodepotential == "max": + new_assignment, single_llf, total_llf = aggr_hmrfmix_reassignment_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, pred, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + elif nodepotential == "weighted_sum": + new_assignment, single_llf, total_llf = hmrfmix_reassignment_posterior_concatenate(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, res, \ + smooth_mat, adjacency_mat, last_assignment, sample_ids, log_persample_weights, spatial_weight=spatial_weight, hmmclass=hmmclass) + else: + raise Exception("Unknown mode for nodepotential!") + # handle the case when one clone has zero spots + if len(np.unique(new_assignment)) < X.shape[2]: + res["assignment_before_reindex"] = new_assignment + remaining_clones = np.sort(np.unique(new_assignment)) + re_indexing = {c:i for i,c in enumerate(remaining_clones)} + new_assignment = np.array([re_indexing[x] for x in new_assignment]) + concat_idx = np.concatenate([ np.arange(c*n_obs, c*n_obs+n_obs) for c in remaining_clones ]) + res["log_gamma"] = res["log_gamma"][:,concat_idx] + res["pred_cnv"] = res["pred_cnv"][concat_idx] + # add to results + res["prev_assignment"] = last_assignment + res["new_assignment"] = new_assignment + res["total_llf"] = total_llf + # append to allres + for k,v in res.items(): + if k == "prev_assignment": + allres[f"round{r-1}_assignment"] = v + elif k == "new_assignment": + allres[f"round{r}_assignment"] = v + else: + allres[f"round{r}_{k}"] = v + allres["num_iterations"] = r + 1 + np.savez(f"{outdir}/{prefix}_nstates{n_states}_{params}.npz", **allres) + # + # regroup to pseudobulk + clone_index = [np.where(res["new_assignment"] == c)[0] for c in np.sort(np.unique(res["new_assignment"]))] + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop, threshold=tumorprop_threshold) + # + if "mp" in params: + print("outer iteration {}: difference between parameters = {}, {}".format( r, np.mean(np.abs(last_log_mu-res["new_log_mu"])), np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + elif "m" in params: + print("outer iteration {}: difference between NB parameters = {}".format( r, np.mean(np.abs(last_log_mu-res["new_log_mu"])) )) + elif "p" in params: + print("outer iteration {}: difference between BetaBinom parameters = {}".format( r, np.mean(np.abs(last_p_binom-res["new_p_binom"])) )) + print("outer iteration {}: ARI between assignment = {}".format( r, adjusted_rand_score(last_assignment, res["new_assignment"]) )) + # if np.all( last_assignment == res["new_assignment"] ): + if adjusted_rand_score(last_assignment, res["new_assignment"]) > 0.99 or len(np.unique(res["new_assignment"])) == 1: + break + last_log_mu = res["new_log_mu"] + last_p_binom = res["new_p_binom"] + last_alphas = res["new_alphas"] + last_taus = res["new_taus"] + last_assignment = res["new_assignment"] + log_persample_weights = np.ones((X.shape[2], n_samples)) * (-np.log(X.shape[2])) + for sidx in range(n_samples): + index = np.where(sample_ids == sidx)[0] + this_persample_weight = np.bincount(res["new_assignment"][index], minlength=X.shape[2]) / len(index) + log_persample_weights[:, sidx] = np.where(this_persample_weight > 0, np.log(this_persample_weight), -50) + log_persample_weights[:, sidx] = log_persample_weights[:, sidx] - scipy.special.logsumexp(log_persample_weights[:, sidx]) + + +############################################################ +# Final posterior using integer copy numbers +############################################################ +def clonelabel_posterior_withinteger(single_X, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, state_cnv, res, pred, smooth_mat, adjacency_mat, prev_assignment, sample_ids, base_nb_mean, log_persample_weights, spatial_weight, hmmclass=hmm_sitewise): + """ + single_X : array, (n_obs, 2, n_spots) + + single_base_nb_mean : array, (n_obs, n_spots) + + single_total_bb_RD : array, (n_obs, n_spots) + + single_tumor_prop : array, (n_spots,) or None + + state_cnv : DataFrame, (n_clones, n_states) + + adjacency_mat : sparse array, (n_spots, n_spots) + + prev_assignment : array, (n_spot,) + + sample_ids : array, (n_spots,) + + base_nb_mean : array, (n_obs, n_clones) + + log_persample_weights : array, (n_clones, n_samples) + + spatial_weight : float + """ + N = single_X.shape[2] + n_obs = single_X.shape[0] + # clone IDs + tmp_clone_ids = np.array([x[5:].split(" ")[0] for x in state_cnv.columns if x[:5] == "clone"]) + clone_ids = np.array([x for i,x in enumerate(tmp_clone_ids) if i == 0 or x != tmp_clone_ids[i-1]]) + n_clones = len(clone_ids) + n_states = state_cnv.shape[0] + # parameter based on integer copy numbers + lambd = base_nb_mean / np.sum(base_nb_mean, axis=0, keepdims=True) if n_clones == base_nb_mean.shape[1] else base_nb_mean[:,1:] / np.sum(base_nb_mean[:,1:], axis=0, keepdims=True) + log_mu_icn = np.zeros((n_states, n_clones)) + for c,cid in enumerate(clone_ids): + log_mu_icn[:,c] = np.log( (state_cnv[f"clone{cid} A"] + state_cnv[f"clone{cid} B"]) / lambd[:,c].dot( (state_cnv[f"clone{cid} A"] + state_cnv[f"clone{cid} B"])[pred[:,c]] ) ) + p_binom_icn = np.array([ state_cnv[f"clone{cid} A"] / (state_cnv[f"clone{cid} A"] + state_cnv[f"clone{cid} B"]) for cid in clone_ids ]).T + # handle 0 in p_binom_icn + if n_clones == res["new_p_binom"].shape[1]: + p_binom_icn[((p_binom_icn == 0) | (p_binom_icn == 1))] = res["new_p_binom"][((p_binom_icn == 0) | (p_binom_icn == 1))] + elif n_clones + 1 == res["new_p_binom"].shape[1]: + p_binom_icn[((p_binom_icn == 0) | (p_binom_icn == 1))] = res["new_p_binom"][:,1:][((p_binom_icn == 0) | (p_binom_icn == 1))] + # over-dispersion + new_alphas = copy.copy(res["new_alphas"]) if n_clones == res["new_p_binom"].shape[1] else copy.copy(res["new_alphas"][:,1:]) + new_alphas[:,:] = np.max(new_alphas) + new_taus = copy.copy(res["new_taus"]) if n_clones == res["new_p_binom"].shape[1] else copy.copy(res["new_taus"][:,1:]) + new_taus[:,:] = np.min(new_taus) + # result variables + single_llf_rdr = np.zeros((N, n_clones)) + single_llf_baf = np.zeros((N, n_clones)) + single_llf = np.zeros((N, n_clones)) + df_posterior = pd.DataFrame({k:np.zeros(N) for k in [f"post_BAF_clone_{cid}" for cid in clone_ids] + [f"post_RDR_clone_{cid}" for cid in clone_ids] + \ + [f"post_nodellf_clone_{cid}" for cid in clone_ids] + [f"post_combine_clone_{cid}" for cid in clone_ids] }) + # + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] + if not (single_tumor_prop is None): + idx = idx[~np.isnan(single_tumor_prop[idx])] + for c in range(n_clones): + if single_tumor_prop is None: + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), log_mu_icn[:,c:(c+1)], new_alphas[:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), p_binom_icn[:,c:(c+1)], new_taus[:,c:(c+1)] ) + else: + tmp_log_emission_rdr, tmp_log_emission_baf = hmmclass.compute_emission_probability_nb_betabinom_mix( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), log_mu_icn[:,c:(c+1)], new_alphas[:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), p_binom_icn[:,c:(c+1)], new_taus[:,c:(c+1)], np.repeat(np.mean(single_tumor_prop[idx]), single_X.shape[0]).reshape(-1,1) ) + assert not np.any(np.isnan(tmp_log_emission_rdr)) + assert not np.any(np.isnan(tmp_log_emission_baf)) + # !!! tmp_log_emission_baf may be NAN + # Because LoH leads to Beta-binomial p = 0 or 1, but both A and B alleles are observed in the data, which leads to Nan. + # We don't directly model the erroneous measurements associated with LoH. + # + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(single_total_bb_RD[:,idx] > 0) / np.sum(single_base_nb_mean[:,idx] > 0) + single_llf_rdr[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + single_llf_baf[i,c] = np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + single_llf[i,c] = single_llf_rdr[i,c] + single_llf_baf[i,c] + else: + single_llf_rdr[i,c] = np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + single_llf_baf[i,c] = np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + single_llf[i,c] = single_llf_rdr[i,c] + single_llf_baf[i,c] + + w_node = copy.copy(single_llf[i,:]) + w_node += log_persample_weights[:,sample_ids[i]] + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + if n_clones == base_nb_mean.shape[1]: + w_edge[prev_assignment[j]] += adjacency_mat[i,j] + else: + w_edge[prev_assignment[j] - 1] += adjacency_mat[i,j] + # + df_posterior.iloc[i,:n_clones] = np.exp( single_llf_baf[i,:] - scipy.special.logsumexp(single_llf_baf[i,:]) ) + df_posterior.iloc[i,n_clones:(2*n_clones)] = np.exp( single_llf_rdr[i,:] - scipy.special.logsumexp(single_llf_rdr[i,:]) ) + df_posterior.iloc[i,(2*n_clones):(3*n_clones)] = np.exp( single_llf[i,:] - scipy.special.logsumexp(single_llf[i,:]) ) + df_posterior.iloc[i,(3*n_clones):(4*n_clones)] = np.exp( w_node + spatial_weight * w_edge - scipy.special.logsumexp(w_node + spatial_weight * w_edge) ) + + return df_posterior diff --git a/src/calicost/hmrf_normalmixture.py b/src/calicost/hmrf_normalmixture.py new file mode 100644 index 0000000..af68580 --- /dev/null +++ b/src/calicost/hmrf_normalmixture.py @@ -0,0 +1,18 @@ +import numpy as np +from numba import njit +import scipy.special +import scipy.sparse +from sklearn.mixture import GaussianMixture +from sklearn.cluster import KMeans +from sklearn.metrics import adjusted_rand_score +from tqdm import trange +import copy +from pathlib import Path +from hmm_NB_BB_phaseswitch import * +from utils_distribution_fitting import * +from utils_IO import * +from simple_sctransform import * + +import warnings +from statsmodels.tools.sm_exceptions import ValueWarning + diff --git a/src/calicost/joint_allele_generateconfig.py b/src/calicost/joint_allele_generateconfig.py new file mode 100644 index 0000000..7a16294 --- /dev/null +++ b/src/calicost/joint_allele_generateconfig.py @@ -0,0 +1,251 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +import scanpy as sc +import anndata +import logging +import copy +from pathlib import Path +import subprocess +from hmm_NB_BB_phaseswitch import * +from utils_distribution_fitting import * +from hmrf import * +from utils_IO import * + + +def read_joint_configuration_file(filename): + ##### [Default settings] ##### + config = { + "input_filelist" : None, + "snp_dir" : None, + "output_dir" : None, + # supporting files and preprocessing arguments + "hgtable_file" : None, + "normalidx_file" : None, + "tumorprop_file" : None, + "supervision_clone_file" : None, + "alignment_files" : [], + "filtergenelist_file" : None, + "filterregion_file" : None, + "binsize" : 1, + "rdrbinsize" : 1, + # "secondbinning_min_umi" : 500, + "max_nbins" : 1200, + "avg_umi_perbinspot" : 1.5, + "bafonly" : True, + # phase switch probability + "nu" : 1, + "logphase_shift" : 1, + "npart_phasing" : 2, + # HMRF configurations + "n_clones" : None, + "n_clones_rdr" : 2, + "min_spots_per_clone" : 100, + "min_avgumi_per_clone" : 10, + "maxspots_pooling" : 7, + "tumorprop_threshold" : 0.5, + "max_iter_outer" : 20, + "nodepotential" : "max", # max or weighted_sum + "initialization_method" : "rectangle", # rectangle or datadrive + "num_hmrf_initialization_start" : 0, + "num_hmrf_initialization_end" : 10, + "spatial_weight" : 2.0, + "construct_adjacency_method" : "hexagon", + "construct_adjacency_w" : 1.0, + # HMM configurations + "n_states" : None, + "params" : None, + "t" : None, + "t_phaseing" : 1-1e-4, + "fix_NB_dispersion" : False, + "shared_NB_dispersion" : True, + "fix_BB_dispersion" : False, + "shared_BB_dispersion" : True, + "max_iter" : 30, + "tol" : 1e-3, + "gmm_random_state" : 0, + "np_threshold" : 2.0, + "np_eventminlen" : 10 + } + + argument_type = { + "input_filelist" : "str", + "snp_dir" : "str", + "output_dir" : "str", + # supporting files and preprocessing arguments + "hgtable_file" : "str", + "normalidx_file" : "str", + "tumorprop_file" : "str", + "supervision_clone_file" : "str", + "alignment_files" : "list_str", + "filtergenelist_file" : "str", + "filterregion_file" : "str", + "binsize" : "int", + "rdrbinsize" : "int", + # "secondbinning_min_umi" : "int", + "max_nbins" : "int", + "avg_umi_perbinspot" : "float", + "bafonly" : "bool", + # phase switch probability + "nu" : "float", + "logphase_shift" : "float", + "npart_phasing" : "int", + # HMRF configurations + "n_clones" : "int", + "n_clones_rdr" : "int", + "min_spots_per_clone" : "int", + "min_avgumi_per_clone" : "int", + "maxspots_pooling" : "int", + "tumorprop_threshold" : "float", + "max_iter_outer" : "int", + "nodepotential" : "str", + "initialization_method" : "str", + "num_hmrf_initialization_start" : "int", + "num_hmrf_initialization_end" : "int", + "spatial_weight" : "float", + "construct_adjacency_method" : "str", + "construct_adjacency_w" : "float", + # HMM configurations + "n_states" : "int", + "params" : "str", + "t" : "eval", + "t_phaseing" : "eval", + "fix_NB_dispersion" : "bool", + "shared_NB_dispersion" : "bool", + "fix_BB_dispersion" : "bool", + "shared_BB_dispersion" : "bool", + "max_iter" : "int", + "tol" : "float", + "gmm_random_state" : "int", + "np_threshold" : "float", + "np_eventminlen" : "int" + } + + ##### [ read configuration file to update settings ] ##### + with open(filename, 'r') as fp: + for line in fp: + if line.strip() == "" or line[0] == "#": + continue + strs = [x.strip() for x in line.strip().split(":") if x != ""] + assert strs[0] in config.keys(), f"{strs[0]} is not a valid configuration parameter! Configuration parameters are: {list(config.keys())}" + if len(strs) == 1: + config[strs[0]] = [] + elif strs[1].upper() == "NONE": + config[strs[0]] = None + elif argument_type[strs[0]] == "str": + config[strs[0]] = strs[1] + elif argument_type[strs[0]] == "int": + config[strs[0]] = int(strs[1]) + elif argument_type[strs[0]] == "float": + config[strs[0]] = float(strs[1]) + elif argument_type[strs[0]] == "eval": + config[strs[0]] = eval(strs[1]) + elif argument_type[strs[0]] == "bool": + config[strs[0]] = (strs[1].upper() == "TRUE") + elif argument_type[strs[0]] == "list_str": + config[strs[0]] = strs[1].split(" ") + # assertions + assert not config["input_filelist"] is None, "No input file list!" + assert not config["snp_dir"] is None, "No SNP directory!" + assert not config["output_dir"] is None, "No output directory!" + + return config + + + +def write_joint_config_file(outputfilename, config): + list_argument_io = ["input_filelist", + "snp_dir", + "output_dir"] + list_argument_sup = ["hgtable_file", + "normalidx_file", + "tumorprop_file", + "supervision_clone_file", + "alignment_files", + "filtergenelist_file", + "filterregion_file", + "binsize", + "rdrbinsize", + # "secondbinning_min_umi", + "max_nbins", + "avg_umi_perbinspot", + "bafonly"] + list_argument_phase = ["nu", + "logphase_shift", + "npart_phasing"] + list_argument_hmrf = ["n_clones", + "n_clones_rdr", + "min_spots_per_clone", + "min_avgumi_per_clone", + "maxspots_pooling", + "tumorprop_threshold", + "max_iter_outer", + "nodepotential", + "initialization_method", + "num_hmrf_initialization_start", + "num_hmrf_initialization_end", + "spatial_weight", + "construct_adjacency_method", + "construct_adjacency_w"] + list_argument_hmm = ["n_states", + "params", + "t", + "t_phaseing", + "fix_NB_dispersion", + "shared_NB_dispersion", + "fix_BB_dispersion", + "shared_BB_dispersion", + "max_iter", + "tol", + "gmm_random_state", + "np_threshold", + "np_eventminlen"] + with open(outputfilename, 'w') as fp: + # + for k in list_argument_io: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# supporting files and preprocessing arguments\n") + for k in list_argument_sup: + if not isinstance(config[k], list): + fp.write(f"{k} : {config[k]}\n") + else: + fp.write(f"{k} : " + " ".join(config[k]) + "\n") + # + fp.write("\n") + fp.write("# phase switch probability\n") + for k in list_argument_phase: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# HMRF configurations\n") + for k in list_argument_hmrf: + fp.write(f"{k} : {config[k]}\n") + # + fp.write("\n") + fp.write("# HMM configurations\n") + for k in list_argument_hmm: + fp.write(f"{k} : {config[k]}\n") + + +def main(argv): + template_configuration_file = argv[1] + outputdir = argv[2] + hmrf_seed_s = int(argv[3]) + hmrf_seed_t = int(argv[4]) + config = read_joint_configuration_file(template_configuration_file) + for r in range(hmrf_seed_s, hmrf_seed_t): + config["num_hmrf_initialization_start"] = r + config["num_hmrf_initialization_end"] = r+1 + write_joint_config_file(f"{outputdir}/configfile{r}", config) + + +if __name__ == "__main__": + if len(sys.argv) == 1: + print("python joint_allele_generateconfig.py ") + if len(sys.argv) > 1: + main(sys.argv) \ No newline at end of file diff --git a/src/calicost/oldcode.py b/src/calicost/oldcode.py new file mode 100644 index 0000000..217dc49 --- /dev/null +++ b/src/calicost/oldcode.py @@ -0,0 +1,486 @@ +import numpy as np +import scipy.special +from sklearn.mixture import GaussianMixture +from tqdm import trange +import copy +from utils_distribution_fitting import * + + +############################################################ +# M step related +############################################################ + +def update_emission_params_nb_sitewise(X_nb, log_gamma, base_nb_mean, alphas, \ + start_log_mu=None, fix_NB_dispersion=False, shared_NB_dispersion=False, min_log_rdr=-2, max_log_rdr=2): + """ + Attributes + ---------- + X_nb : array, shape (n_observations, n_spots) + Observed expression UMI count UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = X_nb.shape[1] + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # expression signal by NB distribution + if fix_NB_dispersion: + new_log_mu = np.zeros((n_states, n_spots)) + new_alphas = alphas + for s in range(n_spots): + idx_nonzero = np.where(base_nb_mean[:,s] > 0)[0] + for i in range(n_states): + model = sm.GLM(X_nb[idx_nonzero,s], np.ones(len(idx_nonzero)).reshape(-1,1), \ + family=sm.families.NegativeBinomial(alpha=alphas[i,s]), \ + exposure=base_nb_mean[idx_nonzero,s], var_weights=gamma[i,idx_nonzero]+gamma[i+n_states,idx_nonzero]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + # print(s, i, res.params) + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array([start_log_mu[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if -model.loglike(res.params) < -model.loglike(res2.params) else res2.params[0] + else: + new_log_mu = np.zeros((n_states, n_spots)) + new_alphas = np.zeros((n_states, n_spots)) + if not shared_NB_dispersion: + for s in range(n_spots): + idx_nonzero = np.where(base_nb_mean[:,s] > 0)[0] + for i in range(n_states): + model = Weighted_NegativeBinomial(X_nb[idx_nonzero,s], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=gamma[i,idx_nonzero]+gamma[i+n_states,idx_nonzero], exposure=base_nb_mean[idx_nonzero,s]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + new_alphas[i, s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_log_mu[i, s]], [alphas[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_alphas[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + for s in range(n_spots): + idx_nonzero = np.where(base_nb_mean[:,s] > 0)[0] + all_states_nb_mean = np.tile(base_nb_mean[idx_nonzero,s], n_states) + all_states_y = np.tile(X_nb[idx_nonzero,s], n_states) + all_states_weights = np.concatenate([gamma[i,idx_nonzero]+gamma[i+n_states,idx_nonzero] for i in range(n_states)]) + all_states_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + all_states_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + model = Weighted_NegativeBinomial(all_states_y, all_states_features, weights=all_states_weights, exposure=all_states_nb_mean) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[:,s] = res.params[:-1] + new_alphas[:,s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append(start_log_mu[:,s], [alphas[0,s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[:,s] = res.params[:-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[:-1] + new_alphas[:,s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + new_log_mu[new_log_mu > max_log_rdr] = max_log_rdr + new_log_mu[new_log_mu < min_log_rdr] = min_log_rdr + return new_log_mu, new_alphas + + +def update_emission_params_bb_sitewise(X_bb, log_gamma, total_bb_RD, taus, \ + start_p_binom=None, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + percent_threshold=0.99, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X_bb : array, shape (n_observations, n_spots) + Observed allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = X_bb.shape[1] + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_p_binom = np.ones((n_states, n_spots)) * 0.5 + new_taus = copy.copy(taus) + if fix_BB_dispersion: + for s in np.arange(X_bb.shape[1]): + idx_nonzero = np.where(total_bb_RD[:,s] > 0)[0] + for i in range(n_states): + model = Weighted_BetaBinom_fixdispersion(np.append(X_bb[idx_nonzero,s], total_bb_RD[idx_nonzero,s]-X_bb[idx_nonzero,s]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + taus[i,s], \ + weights=np.append(gamma[i,idx_nonzero], gamma[i+n_states,idx_nonzero]), \ + exposure=np.append(total_bb_RD[idx_nonzero,s], total_bb_RD[idx_nonzero,s]) ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array(start_p_binom[i, s]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + else: + if not shared_BB_dispersion: + for s in np.arange(X_bb.shape[1]): + idx_nonzero = np.where(total_bb_RD[:,s] > 0)[0] + for i in range(n_states): + model = Weighted_BetaBinom(np.append(X_bb[idx_nonzero,s], total_bb_RD[idx_nonzero,s]-X_bb[idx_nonzero,s]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + weights=np.append(gamma[i,idx_nonzero], gamma[i+n_states,idx_nonzero]), \ + exposure=np.append(total_bb_RD[idx_nonzero,s], total_bb_RD[idx_nonzero,s]) ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + new_taus[i, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_p_binom[i, s]], [taus[i, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_taus[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + for s in np.arange(X_bb.shape[1]): + idx_nonzero = np.where(total_bb_RD[:,s] > 0)[0] + all_states_exposure = np.tile( np.append(total_bb_RD[idx_nonzero,s], total_bb_RD[idx_nonzero,s]), n_states) + all_states_y = np.tile( np.append(X_bb[idx_nonzero,s], total_bb_RD[idx_nonzero,s]-X_bb[idx_nonzero,s]), n_states) + all_states_weights = np.concatenate([ np.append(gamma[i,idx_nonzero], gamma[i+n_states,idx_nonzero]) for i in range(n_states) ]) + all_states_features = np.zeros((2*n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + all_states_features[(i*2*len(idx_nonzero)):((i+1)*2*len(idx_nonzero)), i] = 1 + model = Weighted_BetaBinom(all_states_y, all_states_features, weights=all_states_weights, exposure=all_states_exposure) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[:,s] = res.params[:-1] + new_p_binom[new_p_binom[:,s] < min_binom_prob, s] = min_binom_prob + new_p_binom[new_p_binom[:,s] > max_binom_prob, s] = max_binom_prob + if res.params[-1] > 0: + new_taus[:, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append(start_p_binom[:,s], [taus[0, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[:,s] = res.params[:-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[:-1] + new_p_binom[new_p_binom[:,s] < min_binom_prob, s] = min_binom_prob + new_p_binom[new_p_binom[:,s] > max_binom_prob, s] = max_binom_prob + if res2.params[-1] > 0: + new_taus[:,s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + return new_p_binom, new_taus + + + +def hmrf_log_likelihood(nodepotential, single_X, single_base_nb_mean, single_total_bb_RD, res, pred, smooth_mat, adjacency_mat, assignment, spatial_weight): + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = res["new_p_binom"].shape[1] + n_states = res["new_p_binom"].shape[0] + single_llf = np.zeros((N, n_clones)) + # + for i in trange(N): + idx = smooth_mat[i,:].nonzero()[1] # smooth_mat can be identity matrix + for c in range(n_clones): + tmp_log_emission_rdr, tmp_log_emission_baf = compute_emission_probability_nb_betabinom_phaseswitch( np.sum(single_X[:,:,idx], axis=2, keepdims=True), \ + np.sum(single_base_nb_mean[:,idx], axis=1, keepdims=True), res["new_log_mu"][:,c:(c+1)], res["new_alphas"][:,c:(c+1)], \ + np.sum(single_total_bb_RD[:,idx], axis=1, keepdims=True), res["new_p_binom"][:,c:(c+1)], res["new_taus"][:,c:(c+1)]) + # + if nodepotential == "weighted_sum": + if np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) > 0 and np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:, 0] + res["log_gamma"][:,:,c], axis=0) ) + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:, 0] + res["log_gamma"][:,:,c], axis=0) ) + else: + single_llf[i,c] = np.sum( scipy.special.logsumexp(tmp_log_emission_rdr[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + np.sum( scipy.special.logsumexp(tmp_log_emission_baf[:,:,0] + res["log_gamma"][:,:,c], axis=0) ) + else: + if np.sum(single_base_nb_mean[:,idx] > 0) > 0 and np.sum(single_total_bb_RD[:,idx] > 0) > 0: + ratio_nonzeros = 1.0 * np.sum(np.sum(single_total_bb_RD[:,idx], axis=1) > 0) / np.sum(np.sum(single_base_nb_mean[:,idx], axis=1) > 0) + single_llf[i,c] = ratio_nonzeros * np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + else: + single_llf[i,c] = np.sum(tmp_log_emission_rdr[pred[:,c], np.arange(n_obs), 0]) + np.sum(tmp_log_emission_baf[pred[:,c], np.arange(n_obs), 0]) + # + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(assignment[adjacency_mat[i,:].nonzero()[1]] == assignment[i]) ) + return total_llf + + +def hmrf_reassignment_compositehmm(single_X, single_base_nb_mean, single_total_bb_RD, res, pred, adjacency_mat, prev_assignment, spatial_weight): + # basic dimension info + N = single_X.shape[2] + n_obs = single_X.shape[0] + n_clones = np.max(prev_assignment) + 1 + n_individual_states = int(len(res["new_p_binom"]) / 2.0) + n_composite_states = int(len(res["state_tuples"]) / 2.0) + + # initialize result vector + single_llf = np.zeros((N, n_clones)) + new_assignment = copy.copy(prev_assignment) + + # re-assign by HMRF + for i in trange(N): + # log emission probability of each composite state, matrix size (2*n_composite_states, n_obs) + tmp_log_emission = compute_emission_probability_nb_betabinom_composite(single_X[:,:,i:(i+1)], res["state_tuples"], \ + single_base_nb_mean[:,i:(i+1)], res["new_log_mu"], res["new_alphas"], single_total_bb_RD[:,i:(i+1)], \ + res["new_p_binom"], res["new_taus"], res["new_scalefactors"]) + for c in range(n_clones): + single_llf[i,c] = np.sum(tmp_log_emission[pred[(c*n_obs):(c*n_obs+n_obs)], np.arange(n_obs)]) + # node potential + w_node = single_llf[i,:] + # edge potential + w_edge = np.zeros(n_clones) + for j in adjacency_mat[i,:].nonzero()[1]: + # w_edge[new_assignment[j]] += 1 + w_edge[new_assignment[j]] += adjacency_mat[i,j] + # combine both potential for the new assignment + new_assignment[i] = np.argmax( w_node + spatial_weight * w_edge ) + + # compute total log likelihood log P(X | Z) + log P(Z) + total_llf = np.sum(single_llf[np.arange(N), new_assignment]) + for i in range(N): + total_llf += np.sum( spatial_weight * np.sum(new_assignment[adjacency_mat[i,:].nonzero()[1]] == new_assignment[i]) ) + return new_assignment, single_llf, total_llf + + + +def allele_starch_combine_clones(): + res_combine = {"new_assignment":np.zeros(single_X.shape[2], dtype=int)} + offset_clone = 0 + for bafc in range(n_baf_clones): + prefix = f"clone{bafc}" + allres = dict( np.load(f"{outdir}/{prefix}_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + r = allres["num_iterations"] - 1 + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + idx_spots = np.where(adata.obs.index.isin( allres["barcodes"] ))[0] + n_obs = single_X.shape[0] + if len(np.unique(res["new_assignment"])) == 1: + n_merged_clones = 1 + c = res["new_assignment"][0] + merged_res = copy.copy(res) + merged_res["new_assignment"] = np.zeros(len(idx_spots), dtype=int) + log_gamma = res["log_gamma"][:, (c*n_obs):(c*n_obs+n_obs)].reshape((2*config["n_states"], n_obs, 1)) + pred_cnv = res["pred_cnv"][ (c*n_obs):(c*n_obs+n_obs) ].reshape((-1,1)) + else: + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in range(n_clones_rdr)]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(res["new_assignment"]==c)[0] for c in range(n_clones_rdr)], single_tumor_prop[idx_spots]) + merging_groups, merged_res = similarity_components_rdrbaf_neymanpearson(X, base_nb_mean, total_bb_RD, res, params="smp", tumor_prop=tumor_prop) + print(f"part {bafc} merging_groups: {merging_groups}") + # + if config["tumorprop_file"] is None: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], res, min_spots_thresholds=50) + else: + merging_groups, merged_res = merge_by_minspots(merged_res["new_assignment"], res, min_spots_thresholds=50, single_tumor_prop=single_tumor_prop[idx_spots]) + # compute posterior using the newly merged pseudobulk + n_merged_clones = len(merging_groups) + tmp = copy.copy(merged_res["new_assignment"]) + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)]) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X[:,:,idx_spots], single_base_nb_mean[:,idx_spots], single_total_bb_RD[:,idx_spots], [np.where(merged_res["new_assignment"]==c)[0] for c in range(n_merged_clones)], single_tumor_prop[idx_spots]) + # + merged_res = pipeline_baum_welch(None, np.vstack([X[:,0,:].flatten("F"), X[:,1,:].flatten("F")]).T.reshape(-1,2,1), np.tile(lengths, X.shape[2]), config["n_states"], \ + base_nb_mean.flatten("F").reshape(-1,1), total_bb_RD.flatten("F").reshape(-1,1), np.tile(log_sitewise_transmat, X.shape[2]), tumor_prop, params="smp", t=config["t"], random_state=config["gmm_random_state"], \ + fix_NB_dispersion=config["fix_NB_dispersion"], shared_NB_dispersion=config["shared_NB_dispersion"], fix_BB_dispersion=config["fix_BB_dispersion"], shared_BB_dispersion=config["shared_BB_dispersion"], \ + is_diag=True, init_log_mu=res["new_log_mu"], init_p_binom=res["new_p_binom"], init_alphas=res["new_alphas"], init_taus=res["new_taus"], max_iter=config["max_iter"], tol=config["tol"]) + merged_res["new_assignment"] = copy.copy(tmp) + log_gamma = np.stack([ merged_res["log_gamma"][:,(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ], axis=-1) + pred_cnv = np.vstack([ merged_res["pred_cnv"][(c*n_obs):(c*n_obs+n_obs)] for c in range(n_merged_clones) ]).T + + # add to res_combine + if len(res_combine) == 1: + res_combine.update({"new_log_mu":np.hstack([ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":log_gamma, "pred_cnv":pred_cnv}) + else: + res_combine.update({"new_log_mu":np.hstack([res_combine["new_log_mu"]] + [ merged_res["new_log_mu"] ] * n_merged_clones), "new_alphas":np.hstack([res_combine["new_alphas"]] + [ merged_res["new_alphas"] ] * n_merged_clones), \ + "new_p_binom":np.hstack([res_combine["new_p_binom"]] + [ merged_res["new_p_binom"] ] * n_merged_clones), "new_taus":np.hstack([res_combine["new_taus"]] + [ merged_res["new_taus"] ] * n_merged_clones), \ + "log_gamma":np.dstack([res_combine["log_gamma"], log_gamma ]), "pred_cnv":np.hstack([res_combine["pred_cnv"], pred_cnv])}) + res_combine["new_assignment"][idx_spots] = merged_res["new_assignment"] + offset_clone + offset_clone += n_merged_clones + # compute HMRF log likelihood + total_llf = hmrf_log_likelihood(config["nodepotential"], single_X, single_base_nb_mean, single_total_bb_RD, res_combine, np.argmax(res_combine["log_gamma"],axis=0), smooth_mat, adjacency_mat, res_combine["new_assignment"], config["spatial_weight"]) + res_combine["total_llf"] = total_llf + # save results + np.savez(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", **res_combine) + + + +def simplify_parameters(res, params="smp", bafthreshold=0.05, rdrthreshold=0.1): + n_states = res["new_p_binom"].shape[0] + G = nx.Graph() + G.add_nodes_from( np.arange(n_states) ) + mAF = np.where(res["new_p_binom"].flatten() < 0.5, res["new_p_binom"].flatten(), 1-res["new_p_binom"].flatten()) + if "m" in params and "p" in params: + tmp_edge_graph = (np.abs( res["new_log_mu"].flatten().reshape(-1,1) - res["new_log_mu"].flatten().reshape(1,-1) ) < rdrthreshold) & (np.abs( mAF.reshape(-1,1) - mAF.reshape(1,-1) ) < bafthreshold) + elif "m" in params: + tmp_edge_graph = (np.abs( res["new_log_mu"].flatten().reshape(-1,1) - res["new_log_mu"].flatten().reshape(1,-1) ) < rdrthreshold) + else: + tmp_edge_graph = (np.abs( mAF.reshape(-1,1) - mAF.reshape(1,-1) ) < bafthreshold) + G.add_edges_from([ (i,j) for i in range(tmp_edge_graph.shape[0]) for j in range(tmp_edge_graph.shape[1]) if tmp_edge_graph[i,j] ]) + # maximal cliques + cliques = [] + for x in nx.find_cliques(G): + this_len = len(x) + cliques.append( (x, this_len) ) + cliques.sort(key = lambda x:(-x[1]) ) + covered_states = set() + merging_state_groups = [] + for c in cliques: + if len(set(c[0]) & covered_states) == 0: + merging_state_groups.append( list(c[0]) ) + covered_states = covered_states | set(c[0]) + for c in range(n_states): + if not (c in covered_states): + merging_state_groups.append( [c] ) + covered_states.add(c) + merging_state_groups.sort(key = lambda x:np.min(x)) + # merged parameters + simplied_res = {"new_log_mu":np.array([ np.mean(res["new_log_mu"].flatten()[idx]) for idx in merging_state_groups]).reshape(-1,1), \ + "new_p_binom":np.array([ np.mean(res["new_p_binom"].flatten()[idx]) for idx in merging_state_groups]).reshape(-1,1), \ + "new_alphas":np.array([ np.mean(res["new_alphas"].flatten()[idx]) for idx in merging_state_groups]).reshape(-1,1), \ + "new_taus":np.array([ np.mean(res["new_taus"].flatten()[idx]) for idx in merging_state_groups]).reshape(-1,1)} + return simplied_res + + +def similarity_components_baf(baf_profiles, res, topk=10, threshold=0.05): + n_clones = baf_profiles.shape[0] + adj_baf_profiles = np.where(baf_profiles > 0.5, 1-baf_profiles, baf_profiles) + G = nx.Graph() + G.add_nodes_from( np.arange(n_clones) ) + for c1 in range(n_clones): + for c2 in range(c1+1, n_clones): + diff = np.sort(np.abs(baf_profiles[c1,:] - baf_profiles[c2,:]))[::-1][topk] + adj_diff = np.sort(np.abs(adj_baf_profiles[c1,:] - adj_baf_profiles[c2,:]))[::-1][topk] + if diff < 2*threshold and adj_diff < threshold: + G.add_edge(c1, c2) + print(c1, c2, diff) + merging_groups = [cc for cc in nx.connected_components(G)] + merging_groups.sort(key = lambda x:np.min(x)) + # clone assignment after merging + map_clone_id = {} + for i,x in enumerate(merging_groups): + for z in x: + map_clone_id[z] = i + new_assignment = np.array([map_clone_id[x] for x in res["new_assignment"]]) + merged_res = copy.copy(res) + merged_res["new_assignment"] = new_assignment + merged_res["total_llf"] = np.NAN + return merging_groups, merged_res + + +def similarity_components_rdrbaf(baf_profiles, rdr_profiles, res, topk=10, bafthreshold=0.05, rdrthreshold=0.1): +# def similarity_components_rdrbaf(baf_profiles, rdr_profiles, res, topk=10, bafthreshold=0.05, rdrthreshold=0.15): + n_clones = baf_profiles.shape[0] + adj_baf_profiles = np.where(baf_profiles > 0.5, 1-baf_profiles, baf_profiles) + G = nx.Graph() + G.add_nodes_from( np.arange(n_clones) ) + for c1 in range(n_clones): + for c2 in range(c1+1, n_clones): + baf_diff = np.sort(np.abs(baf_profiles[c1,:] - baf_profiles[c2,:]))[::-1][topk] + baf_adj_diff = np.sort(np.abs(adj_baf_profiles[c1,:] - adj_baf_profiles[c2,:]))[::-1][topk] + rdr_diff = np.sort(np.abs(rdr_profiles[c1,:] - rdr_profiles[c2,:]))[::-1][topk] + if baf_diff < 2*bafthreshold and baf_adj_diff < bafthreshold and rdr_diff < rdrthreshold: + G.add_edge(c1, c2) + merging_groups = [cc for cc in nx.connected_components(G)] + merging_groups.sort(key = lambda x:np.min(x)) + # clone assignment after merging + map_clone_id = {} + for i,x in enumerate(merging_groups): + for z in x: + map_clone_id[z] = i + new_assignment = np.array([map_clone_id[x] for x in res["new_assignment"]]) + merged_res = copy.copy(res) + merged_res["new_assignment"] = new_assignment + merged_res["total_llf"] = np.NAN + return merging_groups, merged_res + + +def initialization_rdr_bybaf(n_states, X, base_nb_mean, total_bb_RD, params, prior_p_binom, random_state=None, in_log_space=True): + tmp_log_mu, tmp_p_binom = initialization_by_gmm(n_states, X, base_nb_mean, total_bb_RD, params, random_state=random_state, in_log_space=in_log_space, min_binom_prob=0, max_binom_prob=1) + prior_log_mu = np.zeros(prior_p_binom.shape) + for i,x in enumerate(prior_p_binom): + idx_nearest = np.argmin( scipy.spatial.distance.cdist(x.reshape(-1,1), tmp_p_binom) ) + prior_log_mu[i] = tmp_log_mu[idx_nearest] + return prior_log_mu + + + +def output_integer_CN(): + ##### infer integer copy ##### + res_combine = dict(np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True)) + n_final_clone = len(np.unique(res_combine["new_assignment"])) + medfix = ["", "_diploid", "_triploid", "_tetraploid"] + for o,max_medploidy in enumerate([None, 2, 3, 4]): + # A/B copy number per bin + A_copy = np.zeros((n_final_clone, n_obs), dtype=int) + B_copy = np.zeros((n_final_clone, n_obs), dtype=int) + # A/B copy number per state + state_A_copy = np.zeros((n_final_clone, config['n_states']), dtype=int) + state_B_copy = np.zeros((n_final_clone, config['n_states']), dtype=int) + + df_genelevel_cnv = None + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==c)[0] for c in range(n_final_clone)]) + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, [np.where(res_combine["new_assignment"]==c)[0] for c in range(n_final_clone)], single_tumor_prop) + + for s in range(n_final_clone): + # adjust log_mu such that sum_bin lambda * np.exp(log_mu) = 1 + lambd = base_nb_mean[:,s] / np.sum(base_nb_mean[:,s]) + this_pred_cnv = res_combine["pred_cnv"][:,s] + adjusted_log_mu = np.log( np.exp(res_combine["new_log_mu"][:,s]) / np.sum(np.exp(res_combine["new_log_mu"][this_pred_cnv,s]) * lambd) ) + if not max_medploidy is None: + best_integer_copies, _ = hill_climbing_integer_copynumber_oneclone(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv, max_medploidy=max_medploidy) + else: + best_integer_copies, _ = hill_climbing_integer_copynumber_oneclone(adjusted_log_mu, base_nb_mean[:,s], res_combine["new_p_binom"][:,s], this_pred_cnv) + print(f"max med ploidy = {max_medploidy}, clone {s}, integer copy inference loss = {_}") + + A_copy[s,:] = best_integer_copies[res_combine["pred_cnv"][:,s], 0] + B_copy[s,:] = best_integer_copies[res_combine["pred_cnv"][:,s], 1] + state_A_copy[s,:] = best_integer_copies[:,0] + state_B_copy[s,:] = best_integer_copies[:,1] + tmpdf = get_genelevel_cnv_oneclone(best_integer_copies[res_combine["pred_cnv"][:,s], 0], best_integer_copies[res_combine["pred_cnv"][:,s], 1], x_gene_list) + tmpdf.columns = [f"clone{s} A", f"clone{s} B"] + if df_genelevel_cnv is None: + df_genelevel_cnv = copy.copy(tmpdf) + else: + df_genelevel_cnv = df_genelevel_cnv.join(tmpdf) + # output gene-level copy number + df_genelevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_genelevel.tsv", header=True, index=True, sep="\t") + # output segment-level copy number + df_seglevel_cnv = pd.DataFrame({"CHR":[x[0] for x in sorted_chr_pos], "START":[x[1] for x in sorted_chr_pos], \ + "END":[ (sorted_chr_pos[i+1][1] if i+1 < len(sorted_chr_pos) and x[0]==sorted_chr_pos[i+1][0] else -1) for i,x in enumerate(sorted_chr_pos)] }) + for s in range(n_final_clone): + df_seglevel_cnv[f"clone{s} A"] = A_copy[s,:] + df_seglevel_cnv[f"clone{s} B"] = B_copy[s,:] + df_seglevel_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_seglevel.tsv", header=True, index=False, sep="\t") + # output per-state copy number + df_state_cnv = {} + for s in range(n_final_clone): + df_state_cnv[f"clone{s} logmu"] = res_combine["new_log_mu"][:,s] + df_state_cnv[f"clone{s} p"] = res_combine["new_p_binom"][:,s] + df_state_cnv[f"clone{s} A"] = state_A_copy[s,:] + df_state_cnv[f"clone{s} B"] = state_B_copy[s,:] + df_state_cnv = pd.DataFrame.from_dict(df_state_cnv) + df_state_cnv.to_csv(f"{outdir}/cnv{medfix[o]}_perstate.tsv", header=True, index=False, sep="\t") + + ##### output clone label ##### + adata.obs["clone_label"] = res_combine["new_assignment"] + if config["tumorprop_file"] is None: + adata.obs[["clone_label"]].to_csv(f"{outdir}/clone_labels.tsv", header=True, index=True, sep="\t") + else: + adata.obs[["tumor_proportion", "clone_label"]].to_csv(f"{outdir}/clone_labels.tsv", header=True, index=True, sep="\t") + + +def set_bin_exp_to_zero(): + # remove bins for which RDR > MAX_RDR in any smoothed spot + MAX_RDR = 15 + N_STEP = 2 + multi_step_smooth = copy.copy(smooth_mat) + for _ in range(N_STEP): + multi_step_smooth = (multi_step_smooth + multi_step_smooth @ smooth_mat) + multi_step_smooth = (multi_step_smooth > 0).astype(int) + rdr = (copy_single_X_rdr @ multi_step_smooth) / (copy_single_base_nb_mean @ multi_step_smooth) + rdr[np.sum(copy_single_base_nb_mean,axis=1) == 0] = 0 + bidx_inconfident = np.where(~np.all(rdr <= MAX_RDR, axis=1))[0] + rdr_normal[bidx_inconfident] = 0 + rdr_normal = rdr_normal / np.sum(rdr_normal) + copy_single_X_rdr[bidx_inconfident, :] = 0 # avoid ill-defined distributions if normal has 0 count in that bin. + copy_single_base_nb_mean = rdr_normal.reshape(-1,1) @ np.sum(copy_single_X_rdr, axis=0).reshape(1,-1) diff --git a/src/calicost/parse_input.py b/src/calicost/parse_input.py new file mode 100644 index 0000000..9bdd862 --- /dev/null +++ b/src/calicost/parse_input.py @@ -0,0 +1,271 @@ +import sys +import numpy as np +import scipy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +import scanpy as sc +import anndata +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() +import copy +from pathlib import Path +import functools +import subprocess +import argparse +from calicost.utils_IO import * +from calicost.phasing import * +from calicost.arg_parse import * + + +def genesnp_to_bininfo(df_gene_snp): + table_bininfo = df_gene_snp[~df_gene_snp.bin_id.isnull()].groupby('bin_id').agg({"CHR":'first', 'START':'first', 'END':'last', 'gene':set, 'snp_id':set}).reset_index() + table_bininfo['ARM'] = '.' + table_bininfo['INCLUDED_GENES'] = [ " ".join([x for x in y if not x is None]) for y in table_bininfo.gene.values ] + table_bininfo['INCLUDED_SNP_IDS'] = [ " ".join([x for x in y if not x is None]) for y in table_bininfo.snp_id.values ] + table_bininfo['NORMAL_COUNT'] = np.nan + table_bininfo['N_SNPS'] = [ len([x for x in y if not x is None]) for y in table_bininfo.snp_id.values ] + # drop the set columns + table_bininfo.drop(columns=['gene', 'snp_id'], inplace=True) + return table_bininfo + + +def parse_visium(config): + """ + Read multiple 10X Visium SRT samples and SNP data and generate tables with counts and meta info. + + Attributes: + ---------- + config : dictionary + Dictionary containing configuration parameters. Output from read_joint_configuration_file. + + Returns: + ---------- + table_bininfo : DataFrame + DataFrame with columns [chr, arm, start, end, log_phase_transition, included_genes, normal count, n_snps]. + + table_rdrbaf : DataFrame + DataFrame with columns [barcodes, exp_count, tot_count, b_count]. + + meta_info : DataFrame + DataFrame with columns [barcodes, sample, x, y, tumor_proportion] + + expression : sparse matrix, (n_spots, n_genes) + Gene expression UMI count matrix. + + adjacency_mat : array, (n_spots, n_spots) + Adjacency matrix for evaluating label coherence in HMRF. + + smooth_mat : array, (n_spots, n_spots) + KNN smoothing matrix. + """ + if "input_filelist" in config: + adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids, across_slice_adjacency_mat = load_joint_data(config["input_filelist"], config["snp_dir"], config["alignment_files"], config["filtergenelist_file"], config["filterregion_file"], config["normalidx_file"], config['min_snpumi_perspot'], config['min_percent_expressed_spots']) + sample_list = [adata.obs["sample"][0]] + for i in range(1, adata.shape[0]): + if adata.obs["sample"][i] != sample_list[-1]: + sample_list.append( adata.obs["sample"][i] ) + # convert sample name to index + sample_ids = np.zeros(adata.shape[0], dtype=int) + for s,sname in enumerate(sample_list): + index = np.where(adata.obs["sample"] == sname)[0] + sample_ids[index] = s + else: + adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids = load_data(config["spaceranger_dir"], config["snp_dir"], config["filtergenelist_file"], config["filterregion_file"], config["normalidx_file"], config['min_snpumi_perspot'], config['min_percent_expressed_spots']) + adata.obs["sample"] = "unique_sample" + sample_list = [adata.obs["sample"][0]] + sample_ids = np.zeros(adata.shape[0], dtype=int) + across_slice_adjacency_mat = None + + coords = adata.obsm["X_pos"] + + if not config["tumorprop_file"] is None: + df_tumorprop = pd.read_csv(config["tumorprop_file"], sep="\t", header=0, index_col=0) + df_tumorprop = df_tumorprop[["Tumor"]] + df_tumorprop.columns = ["tumor_proportion"] + adata.obs = adata.obs.join(df_tumorprop) + single_tumor_prop = adata.obs["tumor_proportion"] + else: + single_tumor_prop = None + + # read original data + df_gene_snp = combine_gene_snps(unique_snp_ids, config['hgtable_file'], adata) + df_gene_snp = create_haplotype_block_ranges(df_gene_snp, adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids) + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat = summarize_counts_for_blocks(df_gene_snp, \ + adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids, nu=config['nu'], logphase_shift=config['logphase_shift'], geneticmap_file=config['geneticmap_file']) + # infer an initial phase using pseudobulk + if not Path(f"{config['output_dir']}/initial_phase.npz").exists(): + initial_clone_for_phasing = perform_partition(coords, sample_ids, x_part=config["npart_phasing"], y_part=config["npart_phasing"], single_tumor_prop=single_tumor_prop, threshold=config["tumorprop_threshold"]) + phase_indicator, refined_lengths = initial_phase_given_partition(single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_for_phasing, 5, log_sitewise_transmat, \ + "sp", config["t_phaseing"], config["gmm_random_state"], config["fix_NB_dispersion"], config["shared_NB_dispersion"], config["fix_BB_dispersion"], config["shared_BB_dispersion"], 30, 1e-3, threshold=config["tumorprop_threshold"]) + np.savez(f"{config['output_dir']}/initial_phase.npz", phase_indicator=phase_indicator, refined_lengths=refined_lengths) + # map phase indicator to individual snps + df_gene_snp['phase'] = np.where(df_gene_snp.snp_id.isnull(), None, df_gene_snp.block_id.map({i:x for i,x in enumerate(phase_indicator)}) ) + else: + tmp = dict(np.load(f"{config['output_dir']}/initial_phase.npz")) + phase_indicator, refined_lengths = tmp["phase_indicator"], tmp["refined_lengths"] + + # binning + df_gene_snp = create_bin_ranges(df_gene_snp, single_total_bb_RD, refined_lengths, config['secondary_min_umi']) + lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat = summarize_counts_for_bins(df_gene_snp, \ + adata, single_X, single_total_bb_RD, phase_indicator, nu=config['nu'], logphase_shift=config['logphase_shift'], geneticmap_file=config['geneticmap_file']) + # lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, sorted_chr_pos, sorted_chr_pos_last, x_gene_list, n_snps = perform_binning_new(lengths, single_X, \ + # single_base_nb_mean, single_total_bb_RD, sorted_chr_pos, sorted_chr_pos_last, x_gene_list, n_snps, phase_indicator, refined_lengths, config["binsize"], config["rdrbinsize"], config["nu"], config["logphase_shift"], secondary_min_umi=secondary_min_umi) + + # # remove bins where normal spots have imbalanced SNPs + # if not config["tumorprop_file"] is None: + # for prop_threshold in np.arange(0, 0.6, 0.05): + # normal_candidate = (single_tumor_prop <= prop_threshold) + # if np.sum(single_X[:, 0, (normal_candidate==True)]) > single_X.shape[0] * 200: + # break + # index_normal = np.where(normal_candidate)[0] + # lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_gene_snp = bin_selection_basedon_normal(df_gene_snp, \ + # single_X, single_base_nb_mean, single_total_bb_RD, config["nu"], config["logphase_shift"], index_normal, config['geneticmap_file']) + # assert np.sum(lengths) == single_X.shape[0] + # assert single_X.shape[0] == single_total_bb_RD.shape[0] + # assert single_X.shape[0] == len(log_sitewise_transmat) + + # expression count dataframe + exp_counts = pd.DataFrame.sparse.from_spmatrix( scipy.sparse.csc_matrix(adata.layers["count"]), index=adata.obs.index, columns=adata.var.index) + + # smooth and adjacency matrix for each sample + adjacency_mat, smooth_mat = multislice_adjacency(sample_ids, sample_list, coords, single_total_bb_RD, exp_counts, + across_slice_adjacency_mat, construct_adjacency_method=config['construct_adjacency_method'], + maxspots_pooling=config['maxspots_pooling'], construct_adjacency_w=config['construct_adjacency_w']) + n_pooled = np.median(np.sum(smooth_mat > 0, axis=0).A.flatten()) + print(f"Set up number of spots to pool in HMRF: {n_pooled}") + + # If adjacency matrix is only constructed using gene expression similarity (e.g. scRNA-seq data) + # Then, directly replace coords by the umap of gene expression, to avoid potential inconsistency in HMRF initialization + if config["construct_adjacency_method"] == "KNN" and config["construct_adjacency_w"] == 0: + sc.pp.normalize_total(adata, target_sum=np.median(np.sum(exp_counts.values,axis=1)) ) + sc.pp.log1p(adata) + sc.tl.pca(adata) + sc.pp.neighbors(adata) + sc.tl.umap(adata) + coords = adata.obsm["X_umap"] + + # create RDR-BAF table + table_bininfo = genesnp_to_bininfo(df_gene_snp) + table_bininfo['LOG_PHASE_TRANSITION'] = log_sitewise_transmat + + table_rdrbaf = [] + for i in range(single_X.shape[2]): + table_rdrbaf.append( pd.DataFrame({"BARCODES":adata.obs.index[i], "EXP":single_X[:,0,i], "TOT":single_total_bb_RD[:,i], "B":single_X[:,1,i]}) ) + table_rdrbaf = pd.concat(table_rdrbaf, ignore_index=True) + + # create meta info table + # note that table_meta.BARCODES is equal to the unique ones of table_rdrbaf.BARCODES in the original order + table_meta = pd.DataFrame({"BARCODES":adata.obs.index, "SAMPLE":adata.obs["sample"], "X":coords[:,0], "Y":coords[:,1]}) + if not single_tumor_prop is None: + table_meta["TUMOR_PROPORTION"] = single_tumor_prop + + return table_bininfo, table_rdrbaf, table_meta, exp_counts, adjacency_mat, smooth_mat, df_gene_snp + + +def load_tables_to_matrices(config): + """ + Load tables and adjacency from parse_visium_joint or parse_visium_single, and convert to HMM input matrices. + """ + table_bininfo = pd.read_csv(f"{config['output_dir']}/parsed_inputs/table_bininfo.csv.gz", header=0, index_col=None, sep="\t") + table_rdrbaf = pd.read_csv(f"{config['output_dir']}/parsed_inputs/table_rdrbaf.csv.gz", header=0, index_col=None, sep="\t") + table_meta = pd.read_csv(f"{config['output_dir']}/parsed_inputs/table_meta.csv.gz", header=0, index_col=None, sep="\t") + adjacency_mat = scipy.sparse.load_npz( f"{config['output_dir']}/parsed_inputs/adjacency_mat.npz" ) + smooth_mat = scipy.sparse.load_npz( f"{config['output_dir']}/parsed_inputs/smooth_mat.npz" ) + # + df_gene_snp = pd.read_csv(f"{config['output_dir']}/parsed_inputs/gene_snp_info.csv.gz", header=0, index_col=None, sep="\t") + df_gene_snp = df_gene_snp.replace(np.nan, None) + + n_spots = table_meta.shape[0] + n_bins = table_bininfo.shape[0] + + # construct single_X + # single_X = np.zeros((n_bins, 2, n_spots), dtype=int) + single_X = np.zeros((n_bins, 2, n_spots)) + single_X[:, 0, :] = table_rdrbaf["EXP"].values.reshape((n_bins, n_spots), order="F") + single_X[:, 1, :] = table_rdrbaf["B"].values.reshape((n_bins, n_spots), order="F") + + # construct single_base_nb_mean, lengths + single_base_nb_mean = table_bininfo["NORMAL_COUNT"].values.reshape(-1,1) / np.sum(table_bininfo["NORMAL_COUNT"].values) @ np.sum(single_X[:,0,:], axis=0).reshape(1,-1) + + # construct single_total_bb_RD + single_total_bb_RD = table_rdrbaf["TOT"].values.reshape((n_bins, n_spots), order="F") + + # construct log_sitewise_transmat + log_sitewise_transmat = table_bininfo["LOG_PHASE_TRANSITION"].values + + # construct bin info and lengths and x_gene_list + df_bininfo = table_bininfo + lengths = np.array([ np.sum(table_bininfo.CHR == c) for c in df_bininfo.CHR.unique() ]) + + # construct barcodes + barcodes = table_meta["BARCODES"] + + # construct coords + coords = table_meta[["X", "Y"]].values + + # construct single_tumor_prop + single_tumor_prop = table_meta["TUMOR_PROPORTION"].values if "TUMOR_PROPORTION" in table_meta.columns else None + + # construct sample_list and sample_ids + sample_list = [table_meta["SAMPLE"].values[0]] + for i in range(1, table_meta.shape[0]): + if table_meta["SAMPLE"].values[i] != sample_list[-1]: + sample_list.append( table_meta["SAMPLE"].values[i] ) + sample_ids = np.zeros(table_meta.shape[0], dtype=int) + for s,sname in enumerate(sample_list): + index = np.where(table_meta["SAMPLE"].values == sname)[0] + sample_ids[index] = s + + # expression UMI count matrix + exp_counts = pd.read_pickle( f"{config['output_dir']}/parsed_inputs/exp_counts.pkl" ) + + return lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_bininfo, df_gene_snp, \ + barcodes, coords, single_tumor_prop, sample_list, sample_ids, adjacency_mat, smooth_mat, exp_counts + + +def run_parse_n_load(config): + file_exists = np.array([ Path(f"{config['output_dir']}/parsed_inputs/table_bininfo.csv.gz").exists(), \ + Path(f"{config['output_dir']}/parsed_inputs/table_rdrbaf.csv.gz").exists(), \ + Path(f"{config['output_dir']}/parsed_inputs/table_meta.csv.gz").exists(), \ + Path(f"{config['output_dir']}/parsed_inputs/adjacency_mat.npz").exists(), \ + Path(f"{config['output_dir']}/parsed_inputs/smooth_mat.npz").exists(), \ + Path(f"{config['output_dir']}/parsed_inputs/exp_counts.pkl").exists() ]) + if not np.all(file_exists): + # process to tables + table_bininfo, table_rdrbaf, table_meta, exp_counts, adjacency_mat, smooth_mat, df_gene_snp = parse_visium(config) + # table_bininfo, table_rdrbaf, table_meta, exp_counts, adjacency_mat, smooth_mat = parse_hatchetblock(config, cellsnplite_dir, bb_file) + + # save file + p = subprocess.Popen(f"mkdir -p {config['output_dir']}/parsed_inputs", stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) + out,err = p.communicate() + + table_bininfo.to_csv( f"{config['output_dir']}/parsed_inputs/table_bininfo.csv.gz", header=True, index=False, sep="\t" ) + table_rdrbaf.to_csv( f"{config['output_dir']}/parsed_inputs/table_rdrbaf.csv.gz", header=True, index=False, sep="\t" ) + table_meta.to_csv( f"{config['output_dir']}/parsed_inputs/table_meta.csv.gz", header=True, index=False, sep="\t" ) + exp_counts.to_pickle( f"{config['output_dir']}/parsed_inputs/exp_counts.pkl" ) + scipy.sparse.save_npz( f"{config['output_dir']}/parsed_inputs/adjacency_mat.npz", adjacency_mat ) + scipy.sparse.save_npz( f"{config['output_dir']}/parsed_inputs/smooth_mat.npz", smooth_mat ) + # + df_gene_snp.to_csv( f"{config['output_dir']}/parsed_inputs/gene_snp_info.csv.gz", header=True, index=False, sep="\t" ) + + # load and parse data + return load_tables_to_matrices(config) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--configfile", help="configuration file of CalicoST", required=True, type=str) + args = parser.parse_args() + + try: + config = read_configuration_file(args.configfile) + except: + config = read_joint_configuration_file(args.configfile) + + print("Configurations:") + for k in sorted(list(config.keys())): + print(f"\t{k} : {config[k]}") + + _ = run_parse_n_load(config) diff --git a/src/calicost/phasing.py b/src/calicost/phasing.py new file mode 100644 index 0000000..d582ec5 --- /dev/null +++ b/src/calicost/phasing.py @@ -0,0 +1,111 @@ +import logging +from turtle import reset +import numpy as np +from numba import njit +import scipy.special +import scipy.sparse +from sklearn.mixture import GaussianMixture +from sklearn.cluster import KMeans +from sklearn.metrics import adjusted_rand_score, silhouette_score +from sklearn.neighbors import kneighbors_graph +import networkx as nx +from tqdm import trange +import copy +from pathlib import Path +from calicost.hmm_NB_BB_phaseswitch import * +from calicost.utils_distribution_fitting import * +from calicost.utils_hmrf import * +import warnings +from statsmodels.tools.sm_exceptions import ValueWarning + + +def infer_initial_phase(single_X, lengths, single_base_nb_mean, single_total_bb_RD, n_states, log_sitewise_transmat, \ + params, t, random_state, fix_NB_dispersion, shared_NB_dispersion, fix_BB_dispersion, shared_BB_dispersion, max_iter, tol): + # pseudobulk HMM for phase_prob + res = pipeline_baum_welch(None, np.sum(single_X, axis=2, keepdims=True), lengths, n_states, \ + np.sum(single_base_nb_mean, axis=1, keepdims=True), np.sum(single_total_bb_RD, axis=1, keepdims=True), log_sitewise_transmat, \ + hmmclass=hmm_sitewise, params=params, t=t, random_state=random_state, only_minor=True, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, is_diag=True, \ + init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, max_iter=max_iter, tol=tol) + # phase_prob = np.exp(scipy.special.logsumexp(res["log_gamma"][:n_states, :], axis=0)) + # return phase_prob + pred = np.argmax(res["log_gamma"], axis=0) + pred_cnv = pred % n_states + phase_indicator = (pred < n_states) + refined_lengths = [] + cumlen = 0 + for le in lengths: + s = 0 + for i, k in enumerate(pred_cnv[cumlen:(cumlen+le)]): + if i > 0 and pred_cnv[i] != pred_cnv[i-1]: + refined_lengths.append(i - s) + s = i + refined_lengths.append(le - s) + cumlen += le + refined_lengths = np.array(refined_lengths) + return phase_indicator, refined_lengths + + +def initial_phase_given_partition(single_X, lengths, single_base_nb_mean, single_total_bb_RD, single_tumor_prop, initial_clone_index, n_states, log_sitewise_transmat, \ + params, t, random_state, fix_NB_dispersion, shared_NB_dispersion, fix_BB_dispersion, shared_BB_dispersion, max_iter, tol, threshold, min_snpumi=2e3): + EPS_BAF = 0.05 + if single_tumor_prop is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, initial_clone_index, single_tumor_prop, threshold=threshold) + + # pseudobulk HMM for phase_prob + baf_profiles = np.zeros((X.shape[2], X.shape[0])) + pred_cnv = np.zeros((X.shape[2], X.shape[0])) + for i in range(X.shape[2]): + if np.sum(total_bb_RD[:,i]) < min_snpumi: + baf_profiles[i,:] = 0.5 + else: + res = pipeline_baum_welch(None, X[:,:,i:(i+1)], lengths, n_states, base_nb_mean[:,i:(i+1)], total_bb_RD[:,i:(i+1)], log_sitewise_transmat, \ + hmmclass=hmm_sitewise, params=params, t=t, random_state=random_state, only_minor=True, \ + fix_NB_dispersion=fix_NB_dispersion, shared_NB_dispersion=shared_NB_dispersion, \ + fix_BB_dispersion=fix_BB_dispersion, shared_BB_dispersion=shared_BB_dispersion, is_diag=True, \ + init_log_mu=None, init_p_binom=None, init_alphas=None, init_taus=None, max_iter=max_iter, tol=tol) + # + pred = np.argmax(res["log_gamma"], axis=0) + this_baf_profiles = np.where(pred < n_states, res["new_p_binom"][pred%n_states, 0], 1-res["new_p_binom"][pred%n_states, 0]) + this_baf_profiles[np.abs(this_baf_profiles - 0.5) < EPS_BAF] = 0.5 + baf_profiles[i,:] = this_baf_profiles + pred_cnv[i,:] = (pred % n_states) + + if single_tumor_prop is None: + n_total_spots = np.sum([ len(x) for x in initial_clone_index ]) + population_baf = np.array([ 1.0*len(x)/n_total_spots for x in initial_clone_index]) @ baf_profiles + else: + n_total_spots = np.sum([ len(x) * tumor_prop[i] for i,x in enumerate(initial_clone_index) ]) + population_baf = np.array([ 1.0*len(x)*tumor_prop[i]/n_total_spots for i,x in enumerate(initial_clone_index) ]) @ baf_profiles + adj_baf_profiles = np.where(baf_profiles < 0.5, baf_profiles, 1-baf_profiles) + phase_indicator = (population_baf < 0.5) + refined_lengths = [] + cumlen = 0 + for le in lengths: + s = 0 + for i in range(le): + if i > s + 10 and np.any(np.abs(adj_baf_profiles[:,i+cumlen] - adj_baf_profiles[:,i+cumlen-1]) > 0.1): + refined_lengths.append(i - s) + s = i + refined_lengths.append(le - s) + cumlen += le + refined_lengths = np.array(refined_lengths) + return phase_indicator, refined_lengths + + +def perform_partition(coords, sample_ids, x_part, y_part, single_tumor_prop, threshold): + initial_clone_index = [] + for s in range(np.max(sample_ids)+1): + index = np.where(sample_ids == s)[0] + assert len(index) > 0 + if single_tumor_prop is None: + tmp_clone_index = fixed_rectangle_initialization(coords[index,:], x_part, y_part) + else: + tmp_clone_index = fixed_rectangle_initialization_mix(coords[index,:], x_part, y_part, single_tumor_prop[index], threshold=threshold) + for x in tmp_clone_index: + initial_clone_index.append( index[x] ) + return initial_clone_index diff --git a/src/calicost/phylogeny_startle.py b/src/calicost/phylogeny_startle.py new file mode 100644 index 0000000..9265224 --- /dev/null +++ b/src/calicost/phylogeny_startle.py @@ -0,0 +1,234 @@ +import sys +import pandas as pd +import argparse +import itertools +import math +import subprocess +import numpy as np +import seaborn as sns +from matplotlib import pyplot as plt + +import networkx as nx +import itertools +from collections import deque +import argparse + + +def get_LoH_for_phylogeny(df_seglevel_cnv, min_segments): + """ + Treating LoH as irreversible point mutations, output a clone-by-mutation matrix for phylogeny reconstruction. + Mutation states: 0 for no LoH, 1 for lossing A allele, 2 for lossing B allele. + + Attributes + ---------- + df_seglevel_cnv : pd.DataFrame, (n_obs, 3+2*n_clones) + Dataframe from cnv_*seglevel.tsv output. + + Returns + ---------- + df_loh : pd.DataFrame, (n_clones, n_segments) + """ + def get_shared_intervals(acn_profile): + ''' + Takes in allele-specific copy numbers, output a segmentation of genome such that all clones are in the same CN state within each segment. + + anc_profile : array, (n_obs, 2*n_clones) + Allele-specific integer copy numbers for each genomic bin (obs) across all clones. + ''' + intervals = [] + seg_acn = [] + s = 0 + while s < acn_profile.shape[0]: + t = np.where( ~np.all(acn_profile[s:,] == acn_profile[s,:], axis=1) )[0] + if len(t) == 0: + intervals.append( (s, acn_profile.shape[0]) ) + seg_acn.append( acn_profile[s,:] ) + s = acn_profile.shape[0] + else: + t = t[0] + intervals.append( (s,s+t) ) + seg_acn.append( acn_profile[s,:] ) + s = s+t + return intervals, seg_acn + + clone_ids = [x.split(" ")[0] for x in df_seglevel_cnv.columns[ np.arange(3, df_seglevel_cnv.shape[1], 2) ] ] + + acn_profile = df_seglevel_cnv.iloc[:,3:].values + intervals, seg_acn = get_shared_intervals(acn_profile) + df_loh = [] + for i, acn in enumerate(seg_acn): + if np.all(acn != 0): + continue + if intervals[i][1] - intervals[i][0] < min_segments: + continue + idx_zero = np.where(acn == 0)[0] + idx_clones = (idx_zero / 2).astype(int) + is_A = (idx_zero % 2 == 0) + # vector of mutation states + mut = np.zeros( int(len(acn) / 2), dtype=int ) + mut[idx_clones] = np.where(is_A, 1, 2) + df_loh.append( pd.DataFrame(mut.reshape(1, -1), index=[f"bin_{intervals[i][0]}_{intervals[i][1]}"], columns=clone_ids) ) + + df_loh = pd.concat(df_loh).T + return df_loh + + +def get_binary_matrix(df_character_matrix): + + ncells = len(df_character_matrix) + binary_col_dict = {} + for column in df_character_matrix.columns: + state_list = list(df_character_matrix[column].unique()) + for s in state_list: + if s != -1 and s != 0: + state_col = np.zeros((ncells)) + state_col[df_character_matrix[column] == s] = 1 + state_col[df_character_matrix[column] == -1] = -1 + + binary_col_dict[f'{column}_{s}'] = state_col + + df_binary = pd.DataFrame(binary_col_dict, index = df_character_matrix.index, dtype=int) + return df_binary + + +def generate_perfect_phylogeny(df_binary): + + solT_mut = nx.DiGraph() + solT_mut.add_node('root') + + solT_cell = nx.DiGraph() + solT_cell.add_node('root') + + df_binary = df_binary[df_binary.sum().sort_values(ascending=False).index] + + for cell_id, row in df_binary.iterrows(): + if cell_id == 'root': + continue + + curr_node = 'root' + for column in df_binary.columns[row.values == 1]: + if column in solT_mut[curr_node]: + curr_node = column + else: + if column in solT_mut.nodes: + raise NameError(f'{column} is being repeated') + solT_mut.add_edge(curr_node, column) + solT_cell.add_edge(curr_node, column) + curr_node = column + + solT_cell.add_edge(curr_node, cell_id) + + return solT_mut, solT_cell + + +def tree_to_newick(T, root=None): + if root is None: + roots = list(filter(lambda p: p[1] == 0, T.in_degree())) + assert 1 == len(roots) + root = roots[0][0] + subgs = [] + while len(T[root]) == 1: + root = list(T[root])[0] + for child in T[root]: + pathlen = 0 + while len(T[child]) == 1: + child = list(T[child])[0] + pathlen += 1 + if len(T[child]) > 0: + pathlen += 1 + subgs.append(tree_to_newick(T, root=child) + f":{pathlen}") + else: + subgs.append( f"{child}:{pathlen}" ) + return "(" + ','.join(map(str, subgs)) + ")" + + +def output_startle_input_files(calicostdir, outdir, midfix="", startle_bin="startle", min_segments=3): + # get LoH data frame + # rows are clones, columns are bins, entries are 0 (no LoH) or 1 (A allele LoH) of 2 (B allele LoH) + df_seglevel_cnv = pd.read_csv(f"{calicostdir}/cnv{midfix}_seglevel.tsv", header=0, sep="\t") + df_loh = get_LoH_for_phylogeny(df_seglevel_cnv, min_segments) + df_loh.to_csv(f"{outdir}/loh_matrix.tsv", header=True, index=True, sep="\t") + + # binarize + df_binary = get_binary_matrix(df_loh) + + cell_list = list(df_binary.index) + mutation_list = list(df_binary.columns) + mutation_to_index = {x: idx for idx, x in enumerate(mutation_list)} + + # one and missing indices + # one indices + one_cell_mut_list = [] + for cell_idx, cell in enumerate(cell_list): + for mut_idx, mut in enumerate(mutation_list): + if df_binary.loc[cell][mut] == 1: + one_cell_mut_list.append((cell_idx, mut_idx)) + with open(f'{outdir}/loh_one_indices.txt', 'w') as out: + for cell_idx, mut_idx in one_cell_mut_list: + out.write(f'{cell_idx} {mut_idx}\n') + # missimg imdices + character_list = list(set(['_'.join(x.split('_')[:-1]) for x in df_binary.columns])) + missing_cell_character_list = [] + for character_idx, character in enumerate(character_list): + for cell_idx, cell in enumerate(cell_list): + if df_loh.loc[cell][character] == -1: + missing_cell_character_list.append((cell_idx, character_idx)) + with open(f'{outdir}/loh_missing_indices.txt', 'w') as out: + for cell_idx, character_idx in missing_cell_character_list: + out.write(f'{cell_idx} {character_idx}\n') + + # character mutation mapping + with open(f'{outdir}/loh_character_mutation_mapping.txt', 'w') as out: + for _, character in enumerate(character_list): + character_mutation_list = [mutation_to_index[x] for x in mutation_list if x.startswith(f'{character}_')] + out.write(' '.join(map(str, character_mutation_list)) + '\n') + + # count of character states of mutations + max_allowed_homoplasy = {} + for mutation in mutation_list: + max_allowed_homoplasy[mutation] = 2 + with open(f'{outdir}/loh_counts.txt', 'w') as out: + for mutation in mutation_list: + out.write(f'{max_allowed_homoplasy[mutation]}\n') + + # weights + with open(f'{outdir}/loh_weights.txt', 'w') as out: + for mutation in mutation_list: + out.write(f"1\n") + + ##### run startle ##### + m_mutations = df_binary.shape[1] + n_clones = df_binary.shape[0] + command = f"{startle_bin} -m {m_mutations} -n {n_clones} {outdir}/loh_one_indices.txt {outdir}/loh_missing_indices.txt {outdir}/loh_counts.txt {outdir}/loh_character_mutation_mapping.txt {outdir}/loh_weights.txt {outdir}/loh_cpp_output.txt" + print( command ) + p = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) + out,err = p.communicate() + + # parse output + df_cpp_output = pd.read_csv(f'{outdir}/loh_cpp_output.txt', header=None, sep=' ') + df_cpp_output = df_cpp_output.rename(columns={0:'cell_idx', 1:'mut_idx', 2:'state_idx', 3:'entry'}) + df_cpp_output['name'] = df_cpp_output.apply(lambda x: f"{mutation_list[x['mut_idx']]}_{x['state_idx']}", axis =1) + + sol_columns = list(df_cpp_output['name'].unique()) + nsol_columns = len(sol_columns) + sol_entries = np.zeros((n_clones, nsol_columns), dtype=int) + for mut_idx, mut in enumerate(sol_columns): + for cell_idx in df_cpp_output[(df_cpp_output['entry'] == 1) & (df_cpp_output['name'] == mut)]['cell_idx']: + sol_entries[cell_idx][mut_idx] = 1 + df_sol_binary = pd.DataFrame(sol_entries, columns=sol_columns, index=cell_list) + + solT_mut, solT_cell = generate_perfect_phylogeny(df_sol_binary) + with open(f'{outdir}/loh_tree.newick', 'w') as out: + out.write(f"{tree_to_newick(solT_cell)};") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--calicost_dir", help="Directory of a specific random initialization of CalicoST", type=str) + parser.add_argument("-s", "--startle_bin", help="The startle executable path", default="startle", type=str) + parser.add_argument("-p", "--ploidy", help="Ploidy of allele-specific integer copy numbers.", default="", type=str) + parser.add_argument("--min_segments", help="Minimum number of genome segment to keep an LOH event in phylogenetic tree reconstruction.", default=3, type=int) + parser.add_argument("-o", "--outputdir", help="output directory", type=str) + args = parser.parse_args() + + output_startle_input_files(args.calicost_dir, args.outputdir, midfix=args.ploidy, startle_bin=args.startle_bin, min_segments=args.min_segments) \ No newline at end of file diff --git a/src/calicost/phylogeography.py b/src/calicost/phylogeography.py new file mode 100644 index 0000000..e859350 --- /dev/null +++ b/src/calicost/phylogeography.py @@ -0,0 +1,109 @@ +import scanpy as sc +import numpy as np +import pandas as pd +import copy +from matplotlib import pyplot as plt +import seaborn +from ete3 import Tree +import networkx as nx + + +def clone_centers(coords, clone_label, single_tumor_prop=None, sample_list=None, sample_ids=None, tumorprop_threshold=0.6): + df_centers = [] + for l in np.unique(clone_label): + # get spot indices of this clone + index = np.where(clone_label == l)[0] if single_tumor_prop is None else np.where((clone_label == l) & (single_tumor_prop > tumorprop_threshold))[0] + # if the index contains multiple slices, get the most abundance slice + if not sample_ids is None: + most_abundance_slice = pd.Series(sample_ids[index]).mode().values[0] + index = index[ sample_ids[index] == most_abundance_slice ] + # get clone cencer + if single_tumor_prop is None: + center = np.mean(coords[index], axis=0) + else: + center = single_tumor_prop[index].dot(coords[index]) / np.sum(single_tumor_prop[index]) + df_centers.append( pd.DataFrame({'clone':l, 'x':center[0], 'y':center[1]}, index=[0]) ) + df_centers = pd.concat(df_centers, ignore_index=True) + return df_centers + + +def project_phylogeneny_space(newick_file, coords, clone_label, single_tumor_prop=None, sample_list=None, sample_ids=None): + # load tree + with open(newick_file, 'r') as fp: + t = Tree(fp.readline()) + + # get the + list_leaf_nodes = [] + list_internal_nodes = [] + rootnode = np.sort( [leaf.name.replace('clone','') for leaf in t.iter_leaves() ] ) + rootnode = "ancestor" + "_".join( rootnode ) + for node in t.traverse(): + leafnames = np.sort( [leaf.name.replace('clone','') for leaf in node.iter_leaves() ] ) + if node.name == "": + node.name = "ancestor" + "_".join( leafnames ) + + if node.is_leaf(): + list_leaf_nodes.append(node.name) + else: + list_internal_nodes.append(node.name) + + print(f"root node is {rootnode}") + print(f"a list of leaf nodes: {list_leaf_nodes}") + print(f"a list of internal nodes: {list_internal_nodes}") + + # set up multivariate Gaussian distribution to estimate internal node location + N_nodes = len(list_leaf_nodes) + len(list_internal_nodes) + # pairwise distance + G = nx.Graph() + G.add_nodes_from( list_leaf_nodes + list_internal_nodes ) + for nodename in list_leaf_nodes: + node = t&f"{nodename}" + while not node.is_root(): + p = node.up + G.add_edge(node.name, p.name, weight=node.dist) + node = p + + G.edges(data=True) + nx_pdc = dict( nx.all_pairs_dijkstra(G) ) + + # covariance matrix based on pairwise distance + N_nodes = len(list_leaf_nodes) + len(list_internal_nodes) + Sigma_square = np.zeros((N_nodes, N_nodes)) + base_var = max( np.max(np.abs(coords[:,0])), np.max(np.abs(coords[:,1])) ) + + for n1, name1 in enumerate(list_leaf_nodes + list_internal_nodes): + for n2, name2 in enumerate(list_leaf_nodes + list_internal_nodes): + if n1 == n2: + Sigma_square[n1, n2] = base_var + nx_pdc[rootnode][0][name1] + else: + lca_node = t.get_common_ancestor([name1, name2]) + # print( name1, name2, lca_node.name ) + if lca_node.name == rootnode: + Sigma_square[n1, n2] = base_var + else: + Sigma_square[n1, n2] = base_var + nx_pdc[rootnode][0][lca_node.name] + + # mean position + mu_1 = np.zeros(( len(list_leaf_nodes),2 )) + mu_2 = np.zeros(( len(list_internal_nodes),2 )) + + # partition covariance matrix + Sigma_11 = Sigma_square[:len(list_leaf_nodes), :len(list_leaf_nodes)] + Sigma_12 = Sigma_square[:len(list_leaf_nodes), :][:, len(list_leaf_nodes):] + Sigma_22 = Sigma_square[len(list_leaf_nodes):, len(list_leaf_nodes):] + + # get leaf node locations + df_centers = clone_centers(coords, clone_label, single_tumor_prop=single_tumor_prop, + sample_list=sample_list, sample_ids=sample_ids) + obs_1 = df_centers.set_index('clone').loc[list_leaf_nodes].values + + # conditional expectation internal node position | leaf node position = mu_1 + expected_internal = mu_2 + Sigma_12.T @ (np.linalg.inv(Sigma_11) @ (obs_1 - mu_1)) + df_centers = pd.concat([ df_centers, pd.DataFrame({'clone':list_internal_nodes, 'x':expected_internal[:,0], 'y':expected_internal[:,1]}) ]) + + # add to tree features + for node in t.traverse(): + i = np.where(df_centers.clone.values == node.name)[0][0] + node.add_features( x=df_centers.x.values[i], y=df_centers.y.values[i] ) + + return t \ No newline at end of file diff --git a/src/calicost/simple_sctransform.py b/src/calicost/simple_sctransform.py new file mode 100644 index 0000000..1a011b1 --- /dev/null +++ b/src/calicost/simple_sctransform.py @@ -0,0 +1,177 @@ +import numpy as np +import scipy +import statsmodels +import statsmodels.api as sm +from KDEpy import FFTKDE +from scipy.special import psi, polygamma + + +# copied from sctransformPy +def theta_ml(y,mu): + n = y.size + weights = np.ones(n) + limit = 10 + _EPS = np.finfo(float).eps + eps = (_EPS)**0.25 + # inner function + def score(n,th,mu,y,w): + return sum(w*(psi(th + y) - psi(th) + np.log(th) + 1 - np.log(th + mu) - (y + th)/(mu + th))) + # inner function + def info(n,th,mu,y,w): + return sum(w*( - polygamma(1,th + y) + polygamma(1,th) - 1/th + 2/(mu + th) - (y + th)/(mu + th)**2)) + # initialize gradient descent + t0 = n/sum(weights*(y/mu - 1)**2) + it = 0 + de = 1 + # gradient descent + while(it + 1 < limit and abs(de) > eps): + it+=1 + t0 = abs(t0) + i = info(n, t0, mu, y, weights) + de = score(n, t0, mu, y, weights)/i + t0 += de + t0 = max(t0,0) + # note that t0 is the dispersion parameter: var = mu + mu^2 / t0 + return t0 + + +def sample_gene_indices(log_geometric_mean, n_subsample, n_partitions=10): + bounds = np.linspace(np.min(log_geometric_mean), np.max(log_geometric_mean), n_partitions+1) + bounds[-1] += 1e-4 + idx_subsample = [] + for p in range(1, n_partitions): + tmpidx = np.where(np.logical_and(log_geometric_mean >= bounds[p-1], log_geometric_mean < bounds[p]))[0] + np.random.shuffle(tmpidx) + idx_subsample.append(tmpidx[:int(n_subsample/n_partitions)]) + idx_subsample = np.sort(np.concatenate(idx_subsample)) + if len(idx_subsample) < n_subsample: + mask = np.array([True] * len(log_geometric_mean)) + mask[idx_subsample] = False + idx_rest = np.arange(len(log_geometric_mean))[mask] + np.random.shuffle(idx_rest) + n_rest = n_subsample - len(idx_subsample) + idx_subsample = np.sort(np.concatenate([idx_subsample, idx_rest[:n_rest]])) + return idx_subsample + + +def estimate_logmu_dispersion(counts, bw=None): + ''' + counts of size number spots * number genes. + ''' + N = counts.shape[0] + G = counts.shape[1] + eps = 1 + geometric_mean = np.exp(np.log(counts+eps).mean(axis=0).flatten()) - eps + log_geometric_mean = np.log( geometric_mean ) + spot_umi = counts.sum(axis=1) + # fitting logmu and theta (dispersion) + logmu = np.zeros(G) + theta = np.zeros(G) + for i in range(G): + y = counts[:,i] + logmu[i] = np.log( np.sum(y) / np.sum(spot_umi) ) + mu = spot_umi * np.exp(logmu[i]) + theta[i] = theta_ml(y, mu) + # ratio between geometric mean and dispersion parameter theta + log_ratio = np.log(1 + geometric_mean / theta) + # smoothing parameter for kernel ridge regression + if bw is None: + z = FFTKDE(kernel='gaussian', bw='ISJ').fit(log_geometric_mean) + z.evaluate(); + bw_adjust = 3 + bw = z.bw*bw_adjust + # kernel ridge regression for log_ratio (the log ratio between geometric mean expression and dispersion) + kr = statsmodels.nonparametric.kernel_regression.KernelReg(log_ratio, log_geometric_mean[:,None], ['c'], reg_type='ll', bw=[bw]) + pred_log_ratio = kr.fit(data_predict = log_geometric_mean[:,None])[0] + pred_theta = geometric_mean / (np.exp(pred_log_ratio) - 1) + return logmu, pred_theta + + +def pearson_residual(counts, logmu, pred_theta): + ''' + counts of size number spots * number genes. + ''' + N = counts.shape[0] + G = counts.shape[1] + spot_umi = counts.sum(axis=1) + # predicted mean and variance under NB model + mud = np.exp(logmu.reshape(1,-1)) * spot_umi.reshape(-1,1) + vard = mud + mud**2 / pred_theta.reshape(1,-1) + X = (counts * 1.0 - mud) / vard**0.5 + # clipping + clip = np.sqrt(counts.shape[0]/30) + X[X > clip] = clip + X[X < -clip] = -clip + return X + + +def deviance_residual(counts, logmu, pred_theta): + ''' + Equation is taken from Analytic Pearson Residual paper by Lause et al. + counts of size number spots * number genes. + ''' + N = counts.shape[0] + G = counts.shape[1] + spot_umi = counts.sum(axis=1) + # predicted mean + mud = np.exp(logmu.reshape(1,-1)) * spot_umi.reshape(-1,1) + sign = (counts > mud) + part1 = counts * np.log(counts / mud) + part1[counts==0] = 0 + part2 = (counts + pred_theta) * np.log( (counts + pred_theta) / (mud + pred_theta) ) + X = sign * np.sqrt(2 * (part1 - part2)) + return X + + +def estimate_logmu_dispersion2(counts, n_subsample=None, bw=None): + ''' + counts of size number spots * number genes. + ''' + N = counts.shape[0] + G = counts.shape[1] + eps = 1 + geometric_mean = np.exp(np.log(counts+eps).mean(axis=0).flatten()) - eps + log_geometric_mean = np.log( geometric_mean ) + spot_umi = counts.sum(axis=1) + logmu = np.log( np.sum(counts, axis=0) / np.sum(spot_umi) ) + # fitting theta (dispersion) + genes_subsample = np.array([i for i in range(G) if geometric_mean[i] > 0]) + if not (n_subsample is None): + np.random.seed(0) + genes_subsample = sample_gene_indices(log_geometric_mean, n_subsample) + theta = np.zeros(len(genes_subsample)) + for idx,i in enumerate(genes_subsample): + y = counts[:,i] + mu = spot_umi * np.exp(logmu[i]) + theta[idx] = theta_ml(y, mu) + # ratio between geometric mean and dispersion parameter theta + log_ratio = np.log(1 + geometric_mean[genes_subsample] / theta) + # smoothing parameter for kernel ridge regression + if bw is None: + z = FFTKDE(kernel='gaussian', bw='ISJ').fit(log_geometric_mean[genes_subsample]) + z.evaluate(); + bw_adjust = 3 + bw = z.bw*bw_adjust + # kernel ridge regression for log_ratio (the log ratio between geometric mean expression and dispersion) + kr = statsmodels.nonparametric.kernel_regression.KernelReg(log_ratio, log_geometric_mean[genes_subsample][:,None], ['c'], reg_type='ll', bw=[bw]) + pred_log_ratio = kr.fit(data_predict = log_geometric_mean[:,None])[0] + pred_theta = geometric_mean / (np.exp(pred_log_ratio) - 1) + return logmu, pred_theta + + +def pearson_residual2(counts, logmu, pred_theta): + ''' + counts of size number spots * number genes. + ''' + N = counts.shape[0] + G = counts.shape[1] + spot_umi = counts.sum(axis=1) + # predicted mean and variance under NB model + mud = np.exp(logmu.reshape(1,-1)) * spot_umi.reshape(-1,1) + vard = mud + mud**2 / pred_theta.reshape(1,-1) + X = (counts * 1.0 - mud) / vard**0.5 + # clipping + clip = np.sqrt(counts.shape[0]) + X[X > clip] = clip + X[X < -clip] = -clip + return X diff --git a/src/calicost/utils_IO.py b/src/calicost/utils_IO.py new file mode 100644 index 0000000..f248036 --- /dev/null +++ b/src/calicost/utils_IO.py @@ -0,0 +1,1337 @@ +import sys +import numpy as np +import scipy +import copy +import pandas as pd +from pathlib import Path +from sklearn.metrics import adjusted_rand_score +from sklearn.neighbors import LocalOutlierFactor +from sklearn.kernel_ridge import KernelRidge +from sklearn.cluster import KMeans +import scanpy as sc +import anndata +import logging +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s", datefmt="%Y-%m-%d %H:%M:%S") +logger = logging.getLogger() + +from calicost.utils_phase_switch import * +from calicost.utils_distribution_fitting import * +import subprocess + + +def load_data(spaceranger_dir, snp_dir, filtergenelist_file, filterregion_file, normalidx_file, min_snpumis=50, min_percent_expressed_spots=0.005): + ##### read raw UMI count matrix ##### + if Path(f"{spaceranger_dir}/filtered_feature_bc_matrix.h5").exists(): + adata = sc.read_10x_h5(f"{spaceranger_dir}/filtered_feature_bc_matrix.h5") + elif Path(f"{spaceranger_dir}/filtered_feature_bc_matrix.h5ad").exists(): + adata = sc.read_h5ad(f"{spaceranger_dir}/filtered_feature_bc_matrix.h5ad") + else: + logging.error(f"{spaceranger_dir} directory doesn't have a filtered_feature_bc_matrix.h5 or filtered_feature_bc_matrix.h5ad file!") + + adata.layers["count"] = adata.X.A.astype(int) + cell_snp_Aallele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Aallele.npz") + cell_snp_Ballele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Ballele.npz") + unique_snp_ids = np.load(f"{snp_dir}/unique_snp_ids.npy", allow_pickle=True) + snp_barcodes = pd.read_csv(f"{snp_dir}/barcodes.txt", header=None, names=["barcodes"]) + + # add position + if Path(f"{spaceranger_dir}/spatial/tissue_positions.csv").exists(): + df_pos = pd.read_csv(f"{spaceranger_dir}/spatial/tissue_positions.csv", sep=",", header=0, \ + names=["barcode", "in_tissue", "x", "y", "pixel_row", "pixel_col"]) + elif Path(f"{spaceranger_dir}/spatial/tissue_positions_list.csv").exists(): + df_pos = pd.read_csv(f"{spaceranger_dir}/spatial/tissue_positions_list.csv", sep=",", header=None, \ + names=["barcode", "in_tissue", "x", "y", "pixel_row", "pixel_col"]) + else: + raise Exception("No spatial coordinate file!") + df_pos = df_pos[df_pos.in_tissue == True] + # assert set(list(df_pos.barcode)) == set(list(adata.obs.index)) + # only keep shared barcodes + shared_barcodes = set(list(df_pos.barcode)) & set(list(adata.obs.index)) + adata = adata[adata.obs.index.isin(shared_barcodes), :] + df_pos = df_pos[df_pos.barcode.isin(shared_barcodes)] + # sort and match + df_pos.barcode = pd.Categorical(df_pos.barcode, categories=list(adata.obs.index), ordered=True) + df_pos.sort_values(by="barcode", inplace=True) + adata.obsm["X_pos"] = np.vstack([df_pos.x, df_pos.y]).T + + # shared barcodes between adata and SNPs + shared_barcodes = set(list(snp_barcodes.barcodes)) & set(list(adata.obs.index)) + cell_snp_Aallele = cell_snp_Aallele[snp_barcodes.barcodes.isin(shared_barcodes), :] + cell_snp_Ballele = cell_snp_Ballele[snp_barcodes.barcodes.isin(shared_barcodes), :] + snp_barcodes = snp_barcodes[snp_barcodes.barcodes.isin(shared_barcodes)] + adata = adata[adata.obs.index.isin(shared_barcodes), :] + adata = adata[ pd.Categorical(adata.obs.index, categories=list(snp_barcodes.barcodes), ordered=True).argsort(), : ] + + # filter out spots with too small number of UMIs + indicator = (np.sum(adata.layers["count"], axis=1) > min_snpumis) + adata = adata[indicator, :] + cell_snp_Aallele = cell_snp_Aallele[indicator, :] + cell_snp_Ballele = cell_snp_Ballele[indicator, :] + + # filter out spots with too small number of SNP-covering UMIs + indicator = ( np.sum(cell_snp_Aallele, axis=1).A.flatten() + np.sum(cell_snp_Ballele, axis=1).A.flatten() >= min_snpumis ) + adata = adata[indicator, :] + cell_snp_Aallele = cell_snp_Aallele[indicator, :] + cell_snp_Ballele = cell_snp_Ballele[indicator, :] + + # filter out genes that are expressed in <0.5% cells + indicator = (np.sum(adata.X > 0, axis=0) >= min_percent_expressed_spots * adata.shape[0]).A.flatten() + genenames = set(list(adata.var.index[indicator])) + adata = adata[:, indicator] + print(adata) + print("median UMI after filtering out genes < 0.5% of cells = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + # remove genes in filtergenelist_file + # ig_gene_list = pd.read_csv("/n/fs/ragr-data/users/congma/references/cellranger_refdata-gex-GRCh38-2020-A/genes/ig_gene_list.txt", header=None) + if not filtergenelist_file is None: + filter_gene_list = pd.read_csv(filtergenelist_file, header=None) + filter_gene_list = set(list( filter_gene_list.iloc[:,0] )) + indicator_filter = np.array([ (not x in filter_gene_list) for x in adata.var.index ]) + adata = adata[:, indicator_filter] + print("median UMI after filtering out genes in filtergenelist_file = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + if not filterregion_file is None: + regions = pd.read_csv(filterregion_file, header=None, sep="\t", names=["Chrname", "Start", "End"]) + if "chr" in regions.Chrname.iloc[0]: + regions["CHR"] = [int(x[3:]) for x in regions.Chrname.values] + else: + regions.rename(columns={'Chrname':'CHR'}, inplace=True) + regions.sort_values(by=["CHR", "Start"], inplace=True) + indicator_filter = np.array([True] * cell_snp_Aallele.shape[1]) + j = 0 + for i in range(cell_snp_Aallele.shape[1]): + this_chr = int(unique_snp_ids[i].split("_")[0]) + this_pos = int(unique_snp_ids[i].split("_")[1]) + while j < regions.shape[0] and ( (regions.CHR.values[j] < this_chr) or ((regions.CHR.values[j] == this_chr) and (regions.End.values[j] <= this_pos)) ): + j += 1 + if j < regions.shape[0] and (regions.CHR.values[j] == this_chr) and (regions.Start.values[j] <= this_pos) and (regions.End.values[j] > this_pos): + indicator_filter[i] = False + cell_snp_Aallele = cell_snp_Aallele[:, indicator_filter] + cell_snp_Ballele = cell_snp_Ballele[:, indicator_filter] + unique_snp_ids = unique_snp_ids[indicator_filter] + + clf = LocalOutlierFactor(n_neighbors=200) + label = clf.fit_predict( np.sum(adata.layers["count"], axis=0).reshape(-1,1) ) + adata.layers["count"][:, np.where(label==-1)[0]] = 0 + print("filter out {} outlier genes.".format( np.sum(label==-1) )) + + if not normalidx_file is None: + normal_barcodes = pd.read_csv(normalidx_file, header=None).iloc[:,0].values + adata.obs["tumor_annotation"] = "tumor" + adata.obs["tumor_annotation"][adata.obs.index.isin(normal_barcodes)] = "normal" + print( adata.obs["tumor_annotation"].value_counts() ) + + return adata, cell_snp_Aallele.A, cell_snp_Ballele.A, unique_snp_ids + + +def load_joint_data(input_filelist, snp_dir, alignment_files, filtergenelist_file, filterregion_file, normalidx_file, min_snpumis=50, min_percent_expressed_spots=0.005): + ##### read meta sample info ##### + df_meta = pd.read_csv(input_filelist, sep="\t", header=None) + df_meta.rename(columns=dict(zip( df_meta.columns[:3], ["bam", "sample_id", "spaceranger_dir"] )), inplace=True) + logger.info(f"Input spaceranger file list {input_filelist} contains:") + logger.info(df_meta) + df_barcode = pd.read_csv(f"{snp_dir}/barcodes.txt", header=None, names=["combined_barcode"]) + df_barcode["sample_id"] = [x.split("_")[-1] for x in df_barcode.combined_barcode.values] + df_barcode["barcode"] = [x.split("_")[0] for x in df_barcode.combined_barcode.values] + ##### read SNP count ##### + cell_snp_Aallele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Aallele.npz") + cell_snp_Ballele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Ballele.npz") + unique_snp_ids = np.load(f"{snp_dir}/unique_snp_ids.npy", allow_pickle=True) + snp_barcodes = pd.read_csv(f"{snp_dir}/barcodes.txt", header=None, names=["barcodes"]) + + assert (len(alignment_files) == 0) or (len(alignment_files) + 1 == df_meta.shape[0]) + + ##### read anndata and coordinate ##### + # add position + adata = None + for i,sname in enumerate(df_meta.sample_id.values): + # locate the corresponding rows in df_meta + index = np.where(df_barcode["sample_id"] == sname)[0] + df_this_barcode = copy.copy(df_barcode.iloc[index, :]) + df_this_barcode.index = df_this_barcode.barcode + # read adata count info + if Path(f"{df_meta['spaceranger_dir'].iloc[i]}/filtered_feature_bc_matrix.h5").exists(): + adatatmp = sc.read_10x_h5(f"{df_meta['spaceranger_dir'].iloc[i]}/filtered_feature_bc_matrix.h5") + elif Path(f"{df_meta['spaceranger_dir'].iloc[i]}/filtered_feature_bc_matrix.h5ad").exists(): + adatatmp = sc.read_h5ad(f"{df_meta['spaceranger_dir'].iloc[i]}/filtered_feature_bc_matrix.h5ad") + else: + logging.error(f"{df_meta['spaceranger_dir'].iloc[i]} directory doesn't have a filtered_feature_bc_matrix.h5 or filtered_feature_bc_matrix.h5ad file!") + + adatatmp.layers["count"] = adatatmp.X.A + # reorder anndata spots to have the same order as df_this_barcode + idx_argsort = pd.Categorical(adatatmp.obs.index, categories=list(df_this_barcode.barcode), ordered=True).argsort() + adatatmp = adatatmp[idx_argsort, :] + # read position info + if Path(f"{df_meta['spaceranger_dir'].iloc[i]}/spatial/tissue_positions.csv").exists(): + df_this_pos = pd.read_csv(f"{df_meta['spaceranger_dir'].iloc[i]}/spatial/tissue_positions.csv", sep=",", header=0, \ + names=["barcode", "in_tissue", "x", "y", "pixel_row", "pixel_col"]) + elif Path(f"{df_meta['spaceranger_dir'].iloc[i]}/spatial/tissue_positions_list.csv").exists(): + df_this_pos = pd.read_csv(f"{df_meta['spaceranger_dir'].iloc[i]}/spatial/tissue_positions_list.csv", sep=",", header=None, \ + names=["barcode", "in_tissue", "x", "y", "pixel_row", "pixel_col"]) + else: + raise Exception("No spatial coordinate file!") + df_this_pos = df_this_pos[df_this_pos.in_tissue == True] + # only keep shared barcodes + shared_barcodes = set(list(df_this_pos.barcode)) & set(list(adatatmp.obs.index)) + adatatmp = adatatmp[adatatmp.obs.index.isin(shared_barcodes), :] + df_this_pos = df_this_pos[df_this_pos.barcode.isin(shared_barcodes)] + # + # df_this_pos.barcode = pd.Categorical(df_this_pos.barcode, categories=list(df_this_barcode.barcode), ordered=True) + df_this_pos.barcode = pd.Categorical(df_this_pos.barcode, categories=list(adatatmp.obs.index), ordered=True) + df_this_pos.sort_values(by="barcode", inplace=True) + adatatmp.obsm["X_pos"] = np.vstack([df_this_pos.x, df_this_pos.y]).T + adatatmp.obs["sample"] = sname + adatatmp.obs.index = [f"{x}_{sname}" for x in adatatmp.obs.index] + adatatmp.var_names_make_unique() + if adata is None: + adata = adatatmp + else: + adata = anndata.concat([adata, adatatmp], join="outer") + # replace nan with 0 + adata.layers["count"][np.isnan(adata.layers["count"])] = 0 + adata.layers["count"] = adata.layers["count"].astype(int) + + # shared barcodes between adata and SNPs + shared_barcodes = set(list(snp_barcodes.barcodes)) & set(list(adata.obs.index)) + cell_snp_Aallele = cell_snp_Aallele[snp_barcodes.barcodes.isin(shared_barcodes), :] + cell_snp_Ballele = cell_snp_Ballele[snp_barcodes.barcodes.isin(shared_barcodes), :] + snp_barcodes = snp_barcodes[snp_barcodes.barcodes.isin(shared_barcodes)] + adata = adata[adata.obs.index.isin(shared_barcodes), :] + adata = adata[ pd.Categorical(adata.obs.index, categories=list(snp_barcodes.barcodes), ordered=True).argsort(), : ] + + ##### load pairwise alignments ##### + # TBD: directly convert to big "adjacency" matrix + across_slice_adjacency_mat = None + if len(alignment_files) > 0: + EPS = 1e-6 + row_ind = [] + col_ind = [] + dat = [] + offset = 0 + for i,f in enumerate(alignment_files): + pi = np.load(f) + # normalize p such that max( rowsum(pi), colsum(pi) ) = 1, max alignment weight = 1 + pi = pi / np.max( np.append(np.sum(pi,axis=0), np.sum(pi,axis=1)) ) + sname1 = df_meta.sample_id.values[i] + sname2 = df_meta.sample_id.values[i+1] + assert pi.shape[0] == np.sum(df_barcode["sample_id"] == sname1) # double check whether this is correct + assert pi.shape[1] == np.sum(df_barcode["sample_id"] == sname2) # or the dimension should be flipped + # for each spot s in sname1, select {t: spot t in sname2 and pi[s,t] >= np.max(pi[s,:])} as the corresponding spot in the other slice + for row in range(pi.shape[0]): + cutoff = np.max(pi[row,:]) if np.max(pi[row,:]) > EPS else 1+EPS + list_cols = np.where(pi[row, :] >= cutoff - EPS)[0] + row_ind += [offset + row] * len(list_cols) + col_ind += list( offset + pi.shape[0] + list_cols ) + dat += list(pi[row, list_cols]) + offset += pi.shape[0] + across_slice_adjacency_mat = scipy.sparse.csr_matrix((dat, (row_ind, col_ind) ), shape=(adata.shape[0], adata.shape[0])) + across_slice_adjacency_mat += across_slice_adjacency_mat.T + + # filter out spots with too small number of UMIs + indicator = (np.sum(adata.layers["count"], axis=1) >= min_snpumis) + adata = adata[indicator, :] + cell_snp_Aallele = cell_snp_Aallele[indicator, :] + cell_snp_Ballele = cell_snp_Ballele[indicator, :] + if not (across_slice_adjacency_mat is None): + across_slice_adjacency_mat = across_slice_adjacency_mat[indicator,:][:,indicator] + + # filter out spots with too small number of SNP-covering UMIs + indicator = ( np.sum(cell_snp_Aallele, axis=1).A.flatten() + np.sum(cell_snp_Ballele, axis=1).A.flatten() >= min_snpumis ) + adata = adata[indicator, :] + cell_snp_Aallele = cell_snp_Aallele[indicator, :] + cell_snp_Ballele = cell_snp_Ballele[indicator, :] + if not (across_slice_adjacency_mat is None): + across_slice_adjacency_mat = across_slice_adjacency_mat[indicator,:][:,indicator] + + # filter out genes that are expressed in 0, axis=0) >= min_percent_expressed_spots * adata.shape[0]).A.flatten() + genenames = set(list(adata.var.index[indicator])) + adata = adata[:, indicator] + print(adata) + print("median UMI after filtering out genes < 0.5% of cells = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + if not filtergenelist_file is None: + filter_gene_list = pd.read_csv(filtergenelist_file, header=None) + filter_gene_list = set(list( filter_gene_list.iloc[:,0] )) + indicator_filter = np.array([ (not x in filter_gene_list) for x in adata.var.index ]) + adata = adata[:, indicator_filter] + print("median UMI after filtering out genes in filtergenelist_file = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + if not filterregion_file is None: + regions = pd.read_csv(filterregion_file, header=None, sep="\t", names=["Chrname", "Start", "End"]) + if "chr" in regions.Chrname.iloc[0]: + regions["CHR"] = [int(x[3:]) for x in regions.Chrname.values] + else: + regions.rename(columns={'Chrname':'CHR'}, inplace=True) + regions.sort_values(by=["CHR", "Start"], inplace=True) + indicator_filter = np.array([True] * cell_snp_Aallele.shape[1]) + j = 0 + for i in range(cell_snp_Aallele.shape[1]): + this_chr = int(unique_snp_ids[i].split("_")[0]) + this_pos = int(unique_snp_ids[i].split("_")[1]) + while j < regions.shape[0] and ( (regions.CHR.values[j] < this_chr) or ((regions.CHR.values[j] == this_chr) and (regions.End.values[j] <= this_pos)) ): + j += 1 + if j < regions.shape[0] and (regions.CHR.values[j] == this_chr) and (regions.Start.values[j] <= this_pos) and (regions.End.values[j] > this_pos): + indicator_filter[i] = False + cell_snp_Aallele = cell_snp_Aallele[:, indicator_filter] + cell_snp_Ballele = cell_snp_Ballele[:, indicator_filter] + unique_snp_ids = unique_snp_ids[indicator_filter] + + clf = LocalOutlierFactor(n_neighbors=200) + label = clf.fit_predict( np.sum(adata.layers["count"], axis=0).reshape(-1,1) ) + adata.layers["count"][:, np.where(label==-1)[0]] = 0 + print("filter out {} outlier genes.".format( np.sum(label==-1) )) + + if not normalidx_file is None: + normal_barcodes = pd.read_csv(normalidx_file, header=None).iloc[:,0].values + adata.obs["tumor_annotation"] = "tumor" + adata.obs["tumor_annotation"][adata.obs.index.isin(normal_barcodes)] = "normal" + print( adata.obs["tumor_annotation"].value_counts() ) + + return adata, cell_snp_Aallele.A, cell_snp_Ballele.A, unique_snp_ids, across_slice_adjacency_mat + + +def load_slidedna_data(snp_dir, bead_file, filterregion_bedfile): + cell_snp_Aallele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Aallele.npz") + cell_snp_Ballele = scipy.sparse.load_npz(f"{snp_dir}/cell_snp_Ballele.npz") + unique_snp_ids = np.load(f"{snp_dir}/unique_snp_ids.npy", allow_pickle=True) + barcodes = pd.read_csv(f"{snp_dir}/barcodes.txt", header=None, index_col=None) + barcodes = barcodes.iloc[:,0].values + # add spatial position + df_pos = pd.read_csv(bead_file, header=0, sep=",", index_col=None) + coords = np.vstack([df_pos.xcoord, df_pos.ycoord]).T + # remove SNPs within filterregion_bedfile + if not filterregion_bedfile is None: + df_filter = pd.read_csv(filterregion_bedfile, header=None, sep="\t", names=["chrname", "start", "end"]) + df_filter = df_filter[df_filter.chrname.isin( [f"chr{i}" for i in range(1,23)] )] + df_filter["CHR"] = [int(x[3:]) for x in df_filter.chrname] + df_filter.sort_values(by=["CHR", "start"]) + # check whether unique_snp_ids are within the regions in df_filter + snp_chrs = [int(x.split("_")[0]) for x in unique_snp_ids] + snp_pos = [int(x.split("_")[1]) for x in unique_snp_ids] + filter_chrs = df_filter.CHR.values + filter_start = df_filter.start.values + filter_end = df_filter.end.values + is_within_filterregion = [] + j = 0 + for i in range(len(unique_snp_ids)): + while (filter_chrs[j] < snp_chrs[i]) or ((filter_chrs[j] == snp_chrs[i]) and (filter_end[j] < snp_pos[i])): + j += 1 + if filter_chrs[j] == snp_chrs[i] and filter_start[j] <= snp_pos[i] and filter_end[j] >= snp_pos[i]: + is_within_filterregion.append(True) + else: + is_within_filterregion.append(False) + is_within_filterregion = np.array(is_within_filterregion) + # remove SNPs based on is_within_filterregion + cell_snp_Aallele = cell_snp_Aallele[:, ~is_within_filterregion] + cell_snp_Ballele = cell_snp_Ballele[:, ~is_within_filterregion] + unique_snp_ids = unique_snp_ids[~is_within_filterregion] + return coords, cell_snp_Aallele, cell_snp_Ballele, barcodes, unique_snp_ids + + +def taking_shared_barcodes(snp_barcodes, cell_snp_Aallele, cell_snp_Ballele, adata, df_pos): + # shared barcodes between adata and SNPs + shared_barcodes = set(list(snp_barcodes.barcodes)) & set(list(adata.obs.index)) & set(list(df_pos.barcode)) + cell_snp_Aallele = cell_snp_Aallele[snp_barcodes.barcodes.isin(shared_barcodes), :] + cell_snp_Ballele = cell_snp_Ballele[snp_barcodes.barcodes.isin(shared_barcodes), :] + snp_barcodes = snp_barcodes[snp_barcodes.barcodes.isin(shared_barcodes)] + adata = adata[adata.obs.index.isin(shared_barcodes), :] + adata = adata[ pd.Categorical(adata.obs.index, categories=list(snp_barcodes.barcodes), ordered=True).argsort(), : ] + df_pos = df_pos[df_pos.barcode.isin(shared_barcodes)] + df_pos = df_pos.iloc[ pd.Categorical(df_pos.barcode, categories=list(snp_barcodes.barcodes), ordered=True).argsort(), : ] + return snp_barcodes, cell_snp_Aallele, cell_snp_Ballele, adata, df_pos + + +def filter_genes_barcodes_hatchetblock(adata, cell_snp_Aallele, cell_snp_Ballele, snp_barcodes, unique_snp_ids, config, min_umi=100, min_spot_percent=0.005, ordered_chr=[str(c) for c in range(1,23)]): + # filter out spots with too small number of UMIs + indicator = (np.sum(adata.layers["count"], axis=1) > min_umi) + adata = adata[indicator, :] + cell_snp_Aallele = cell_snp_Aallele[indicator, :] + cell_snp_Ballele = cell_snp_Ballele[indicator, :] + + # filter out genes that are expressed in <0.5% cells + indicator = (np.sum(adata.X > 0, axis=0) >= min_spot_percent * adata.shape[0]).A.flatten() + genenames = set(list(adata.var.index[indicator])) + adata = adata[:, indicator] + print(adata) + print("median UMI after filtering out genes < 0.5% of cells = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + if not config["filtergenelist_file"] is None: + filter_gene_list = pd.read_csv(config["filtergenelist_file"], header=None) + filter_gene_list = set(list( filter_gene_list.iloc[:,0] )) + indicator_filter = np.array([ (not x in filter_gene_list) for x in adata.var.index ]) + adata = adata[:, indicator_filter] + print("median UMI after filtering out genes in filtergenelist_file = {}".format( np.median(np.sum(adata.layers["count"], axis=1)) )) + + if not config["filterregion_file"] is None: + regions = pd.read_csv(config["filterregion_file"], header=None, sep="\t", names=["Chrname", "Start", "End"]) + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + # retain only chromosomes in ordered_chr + if ~np.any( regions.Chrname.isin(ordered_chr) ): + regions["Chrname"] = regions.Chrname.map(lambda x: x.replace("chr", "")) + regions = regions[regions.Chrname.isin(ordered_chr)] + regions["int_chrom"] = regions.Chrname.map(ordered_chr_map) + regions.sort_values(by=["int_chrom", "Start"], inplace=True) + indicator_filter = np.array([True] * cell_snp_Aallele.shape[1]) + j = 0 + for i in range(cell_snp_Aallele.shape[1]): + this_chr = int(unique_snp_ids[i].split("_")[0]) + this_pos = int(unique_snp_ids[i].split("_")[1]) + while j < regions.shape[0] and ( (regions.int_chrom.values[j] < this_chr) or ((regions.int_chrom.values[j] == this_chr) and (regions.End.values[j] <= this_pos)) ): + j += 1 + if j < regions.shape[0] and (regions.int_chrom.values[j] == this_chr) and (regions.Start.values[j] <= this_pos) and (regions.End.values[j] > this_pos): + indicator_filter[i] = False + cell_snp_Aallele = cell_snp_Aallele[:, indicator_filter] + cell_snp_Ballele = cell_snp_Ballele[:, indicator_filter] + unique_snp_ids = unique_snp_ids[indicator_filter] + + return adata, cell_snp_Aallele, cell_snp_Ballele, snp_barcodes, unique_snp_ids + + +def read_bias_correction_info(bc_file): + try: + df_info = pd.read_csv(bc_file, header=None, sep="\t") + except: + df_info = pd.read_csv(bc_file, header=0, sep="\t") + return df_info.iloc[:,-1].values + + +def binning_readcount_using_SNP(df_bins, sorted_chr_pos_first): + """ + Returns + ---------- + multiplier : array, (n_bins, n_snp_bins) + Binary matrix to indicate which RDR bins belong to which SNP bins + """ + idx = 0 + multiplier = np.zeros((df_bins.shape[0], len(sorted_chr_pos_first))) + for i in range(df_bins.shape[0]): + this_chr = df_bins.CHR.values[i] + this_s = df_bins.START.values[i] + this_t = df_bins.END.values[i] + mid = (this_s + this_t) / 2 + # move the cursort on sorted_chr_pos_first such that the chr matches that in df_bins + while this_chr != sorted_chr_pos_first[idx][0]: + idx += 1 + while idx + 1 < len(sorted_chr_pos_first) and this_chr == sorted_chr_pos_first[idx+1][0] and mid > sorted_chr_pos_first[idx+1][1]: + idx += 1 + multiplier[i, idx] = 1 + return multiplier + + +def load_slidedna_readcount(countfile, bead_file, binfile, normalfile, bias_correction_filelist, retained_barcodes, retain_chr_list=np.arange(1,23)): + # load counts and the corresponding barcodes per spot in counts + tmpcounts = np.loadtxt(countfile) + counts = scipy.sparse.csr_matrix(( tmpcounts[:,2], (tmpcounts[:,0].astype(int)-1, tmpcounts[:,1].astype(int)-1) )) + tmpdf = pd.read_csv(bead_file, header=0, sep=",", index_col=0) + tmpdf = tmpdf.join( pd.DataFrame(counts.A, index=tmpdf.index)) + # keep only the spots in retained_barcodes + tmpdf = tmpdf[tmpdf.index.isin(retained_barcodes)] + # reorder by retained_barcodes + tmpdf.index = pd.Categorical(tmpdf.index, categories=retained_barcodes, ordered=True) + tmpdf.sort_index(inplace=True) + counts = tmpdf.values[:, 2:] + + # load normal counts + normal_cov = pd.read_csv(normalfile, header=None, sep="\t").values[:,-1].astype(float) + + # load bin info + df_bins = pd.read_csv(binfile, comment="#", header=None, index_col=None, sep="\t") + old_names = df_bins.columns[:3] + df_bins.rename(columns=dict(zip(old_names, ["CHR", "START", "END"])), inplace=True) + + # select bins according to retain_chr_list + retain_chr_list_append = list(retain_chr_list) + [str(x) for x in retain_chr_list] + [f"chr{x}" for x in retain_chr_list] + bidx = np.where(df_bins.CHR.isin(retain_chr_list_append))[0] + df_bins = df_bins.iloc[bidx,:] + counts = counts[:, bidx] + normal_cov = normal_cov[bidx] + + # sort bins + df_bins.CHR = [int(x[3:]) if "chr" in x else int(x) for x in df_bins.CHR] + idx_sort = np.lexsort((df_bins.START, df_bins.CHR)) + df_bins = df_bins.iloc[idx_sort, :] + counts = counts[:, idx_sort] + normal_cov = normal_cov[idx_sort] + + # bias correction + bias_features = [] + for f in bias_correction_filelist: + this_feature = read_bias_correction_info(f) + bias_features.append( this_feature[bidx] ) + bias_features = np.array(bias_features).T + # kernel ridge regression to predict the read count per bin + # the prediction serves as a baseline of the expected read count, and plays a role in base_nb_mean + krr = KernelRidge(alpha=0.2) + krr.fit( bias_features, np.sum(counts, axis=0) / np.sum(counts) ) + pred = krr.predict( bias_features ) + + # single_base_nb_mean from bias correction + expected normal + single_base_nb_mean = (pred * normal_cov).reshape(-1,1) / np.sum(pred * normal_cov) * np.sum(counts, axis=1).reshape(1,-1) + # single_base_nb_mean = pred.reshape(-1,1) / np.sum(pred) * np.sum(counts, axis=1).reshape(1,-1) + + # remove too low baseline + threshold = np.median( np.sum(single_base_nb_mean, axis=1) / df_bins.iloc[:,3].values.astype(float) ) * 0.5 + idx_filter = np.where( np.sum(single_base_nb_mean, axis=1) / df_bins.iloc[:,3].values.astype(float) < threshold )[0] + single_base_nb_mean[idx_filter, :] = 0 + counts[:, idx_filter] = 0 + + return counts, single_base_nb_mean, df_bins, normal_cov + + +def get_slidednaseq_rdr(countfile, bead_file, binfile, normalfile, bias_correction_filelist, retained_barcodes, sorted_chr_pos_first, single_X, single_base_nb_mean, retain_chr_list=np.arange(1,23)): + counts, single_base_nb_mean, df_bins, _ = load_slidedna_readcount(countfile, bead_file, binfile, normalfile, bias_correction_filelist, retained_barcodes) + # remove bins with low-coverage single_base_nb_mean + + multiplier = binning_readcount_using_SNP(df_bins, sorted_chr_pos_first) + single_X[:,0,:] = multiplier.T @ counts.T + single_base_nb_mean = multiplier.T @ single_base_nb_mean + return single_X, single_base_nb_mean + + +def filter_slidedna_spot_by_adjacency(coords, cell_snp_Aallele, cell_snp_Ballele, barcodes): + # distance to center + dist = np.sqrt(np.sum(np.square(coords - np.median(coords, axis=0, keepdims=True)), axis=1)) + idx_keep = np.where(dist < 2500)[0] + # remove spots + coords = coords[idx_keep, :] + cell_snp_Aallele = cell_snp_Aallele[idx_keep, :] + cell_snp_Ballele = cell_snp_Ballele[idx_keep, :] + barcodes = barcodes[idx_keep] + return coords, cell_snp_Aallele, cell_snp_Ballele, barcodes + + +def combine_gene_snps(unique_snp_ids, hgtable_file, adata): + # read gene info and keep only chr1-chr22 and genes appearing in adata + df_hgtable = pd.read_csv(hgtable_file, header=0, index_col=0, sep="\t") + df_hgtable = df_hgtable[df_hgtable.chrom.isin( [f"chr{i}" for i in range(1, 23)] )] + df_hgtable = df_hgtable[df_hgtable.name2.isin(adata.var.index)] + # a data frame including both gene and SNP info: CHR, START, END, snp_id, gene, is_interval + df_gene_snp = pd.DataFrame({"CHR":[int(x[3:]) for x in df_hgtable.chrom.values], "START":df_hgtable.cdsStart.values, "END":df_hgtable.cdsEnd.values, \ + "snp_id":None, "gene":df_hgtable.name2.values, "is_interval":True}) + # add SNP info + snp_chr = np.array([int(x.split("_")[0]) for x in unique_snp_ids]) + snp_pos = np.array([int(x.split("_")[1]) for x in unique_snp_ids]) + df_gene_snp = pd.concat([df_gene_snp, pd.DataFrame({"CHR":snp_chr, "START":snp_pos, "END":snp_pos+1, "snp_id":unique_snp_ids, "gene":None, "is_interval":False}) ], ignore_index=True) + df_gene_snp.sort_values(by=["CHR", "START"], inplace=True) + + # check the what gene each SNP belongs to + # for each SNP (with not null snp_id), find the previous gene (is_interval == True) such that the SNP start position is within the gene start and end interval + vec_is_interval = df_gene_snp.is_interval.values + vec_chr = df_gene_snp.CHR.values + vec_start = df_gene_snp.START.values + vec_end = df_gene_snp.END.values + for i in np.where(df_gene_snp.gene.isnull())[0]: + if i == 0: + continue + this_pos = vec_start[i] + j = i - 1 + while j >= 0 and j >= i-50 and vec_chr[i] == vec_chr[j]: + if vec_is_interval[j] and vec_start[j] <= this_pos and vec_end[j] > this_pos: + df_gene_snp.iloc[i, 4] = df_gene_snp.iloc[j]["gene"] + break + j -= 1 + + # remove SNPs that have no corresponding genes + df_gene_snp = df_gene_snp[~df_gene_snp.gene.isnull()] + return df_gene_snp + + +def create_haplotype_block_ranges(df_gene_snp, adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids, initial_min_umi=15): + """ + Initially block SNPs along genome. + + Returns + ---------- + df_gene_snp : data frame, (CHR, START, END, snp_id, gene, is_interval, block_id) + Gene and SNP info combined into a single data frame sorted by genomic positions. "is_interval" suggest whether the entry is a gene or a SNP. "gene" column either contain gene name if the entry is a gene, or the gene a SNP belongs to if the entry is a SNP. + """ + # first level: partition of genome: by gene regions (if two genes overlap, they are grouped to one region) + tmp_block_genome_intervals = list(zip( df_gene_snp[df_gene_snp.is_interval].CHR.values, df_gene_snp[df_gene_snp.is_interval].START.values, df_gene_snp[df_gene_snp.is_interval].END.values )) + block_genome_intervals = [tmp_block_genome_intervals[0]] + for x in tmp_block_genome_intervals[1:]: + # check whether overlap with previous block + if x[0] == block_genome_intervals[-1][0] and max(x[1], block_genome_intervals[-1][1]) < min(x[2], block_genome_intervals[-1][2]): + block_genome_intervals[-1] = (x[0], min(x[1], block_genome_intervals[-1][1]), max(x[2], block_genome_intervals[-1][2])) + else: + block_genome_intervals.append(x) + # get block_ranges in the index of df_gene_snp + block_ranges = [] + for x in block_genome_intervals: + indexes = np.where((df_gene_snp.CHR.values == x[0]) & \ + (np.maximum(df_gene_snp.START.values, x[1]) < np.minimum(df_gene_snp.END.values, x[2])) )[0] + block_ranges.append( (indexes[0], indexes[-1]+1) ) + assert np.all( np.array(np.array([x[1] for x in block_ranges[:-1]])) == np.array(np.array([x[0] for x in block_ranges[1:]])) ) + # record the initial block id in df_gene_snps + df_gene_snp["initial_block_id"] = 0 + for i,x in enumerate(block_ranges): + df_gene_snp.iloc[x[0]:x[1], -1] = i + + # second level: group the first level blocks into haplotype blocks such that the minimum SNP-covering UMI counts >= initial_min_umi + map_snp_index = {x:i for i,x in enumerate(unique_snp_ids)} + initial_block_chr = df_gene_snp.CHR.values[ np.array([x[0] for x in block_ranges]) ] + block_ranges_new = [] + s = 0 + while s < len(block_ranges): + t = s + while t <= len(block_ranges): + t += 1 + reach_end = (t == len(block_ranges)) + change_chr = (initial_block_chr[s] != initial_block_chr[t-1]) + # count SNP-covering UMI + involved_snps_ids = df_gene_snp[ (df_gene_snp.initial_block_id>=s) & (df_gene_snp.initial_block_id= initial_min_umi: + break + # + if this_snp_umis < initial_min_umi and s > 0 and initial_block_chr[s-1] == initial_block_chr[s]: + indexes = np.where(df_gene_snp.initial_block_id.isin(np.arange(s, t)))[0] + block_ranges_new[-1] = (block_ranges_new[-1][0], indexes[-1]+1) + else: + indexes = np.where(df_gene_snp.initial_block_id.isin(np.arange(s, t)))[0] + block_ranges_new.append( (indexes[0], indexes[-1]+1) ) + s = t + + # record the block id in df_gene_snps + df_gene_snp["block_id"] = 0 + for i,x in enumerate(block_ranges_new): + df_gene_snp.iloc[x[0]:x[1], -1] = i + + df_gene_snp = df_gene_snp.drop(columns=["initial_block_id"]) + return df_gene_snp + + +def summarize_counts_for_blocks(df_gene_snp, adata, cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids, nu, logphase_shift, geneticmap_file): + """ + Attributes: + ---------- + df_gene_snp : pd.DataFrame + Contain "block_id" column to indicate which genes/snps belong to which block. + + Returns + ---------- + lengths : array, (n_chromosomes,) + Number of blocks per chromosome. + + single_X : array, (n_blocks, 2, n_spots) + Transcript counts and B allele count per block per cell. + + single_base_nb_mean : array, (n_blocks, n_spots) + Baseline transcript counts in normal diploid per block per cell. + + single_total_bb_RD : array, (n_blocks, n_spots) + Total allele count per block per cell. + + log_sitewise_transmat : array, (n_blocks,) + Log phase switch probability between each pair of adjacent blocks. + """ + blocks = df_gene_snp.block_id.unique() + single_X = np.zeros((len(blocks), 2, adata.shape[0]), dtype=int) + single_base_nb_mean = np.zeros((len(blocks), adata.shape[0])) + single_total_bb_RD = np.zeros((len(blocks), adata.shape[0]), dtype=int) + # summarize counts of involved genes and SNPs within each block + map_snp_index = {x:i for i,x in enumerate(unique_snp_ids)} + df_block_contents = df_gene_snp.groupby('block_id').agg({"snp_id":list, "gene":list}) + for b in range(df_block_contents.shape[0]): + # BAF (SNPs) + involved_snps_ids = [x for x in df_block_contents.snp_id.values[b] if not x is None] + involved_snp_idx = np.array([map_snp_index[x] for x in involved_snps_ids]) + if len(involved_snp_idx) > 0: + single_X[b, 1, :] = np.sum( cell_snp_Aallele[:, involved_snp_idx], axis=1 ) + single_total_bb_RD[b, :] = np.sum( cell_snp_Aallele[:, involved_snp_idx], axis=1 ) + np.sum( cell_snp_Ballele[:, involved_snp_idx], axis=1 ) + # RDR (genes) + involved_genes = list(set([x for x in df_block_contents.gene.values[b] if not x is None])) + if len(involved_genes) > 0: + single_X[b, 0, :] = np.sum( adata.layers['count'][:, adata.var.index.isin(involved_genes)], axis=1 ) + + # lengths + lengths = np.zeros(len(df_gene_snp.CHR.unique()), dtype=int) + for i,c in enumerate( df_gene_snp.CHR.unique() ): + lengths[i] = len( df_gene_snp[df_gene_snp.CHR == c].block_id.unique() ) + + # phase switch probability from genetic distance + sorted_chr_pos_first = df_gene_snp.groupby('block_id').agg({'CHR': 'first', 'START': 'first'}) + sorted_chr_pos_first = list(zip(sorted_chr_pos_first.CHR.values, sorted_chr_pos_first.START.values)) + sorted_chr_pos_last = df_gene_snp.groupby('block_id').agg({'CHR': 'last', 'END': 'last'}) + sorted_chr_pos_last = list(zip(sorted_chr_pos_last.CHR.values, sorted_chr_pos_last.END.values)) + # + tmp_sorted_chr_pos = [val for pair in zip(sorted_chr_pos_first, sorted_chr_pos_last) for val in pair] + position_cM = get_position_cM_table( tmp_sorted_chr_pos, geneticmap_file ) + phase_switch_prob = compute_phase_switch_probability_position(position_cM, tmp_sorted_chr_pos, nu) + log_sitewise_transmat = np.minimum(np.log(0.5), np.log(phase_switch_prob) - logphase_shift) + # log_sitewise_transmat = log_sitewise_transmat[np.arange(0, len(log_sitewise_transmat), 2)] + log_sitewise_transmat = log_sitewise_transmat[np.arange(1, len(log_sitewise_transmat), 2)] + + return lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat + + +def choose_umithreshold_given_nbins(single_total_bb_RD, refined_lengths, expected_nbins): + def count_num_bins(per_snp_umi, refined_lengths, secondary_min_umi): + cumlen = 0 + s = 0 + bin_counter = 0 + for le in refined_lengths: + while s < cumlen + le: + # initial bin with certain number of SNPs + t = s + 1 + while t < cumlen + le and np.sum(per_snp_umi[s:t]) < secondary_min_umi: + t += 1 + if np.sum(per_snp_umi[s:t]) >= secondary_min_umi: + bin_counter += 1 + s = t + cumlen += le + return bin_counter + per_snp_umi = np.sum(single_total_bb_RD, axis=1) + # candicate range + lo = np.sort(per_snp_umi)[-expected_nbins] + # hi = np.sort(per_snp_umi)[-int(expected_nbins/3)] + hi = int(np.ceil(np.sum(per_snp_umi) / expected_nbins)) + # binary search + while lo < hi: + mid = int((hi + lo) / 2) + bin_counter = count_num_bins(per_snp_umi, refined_lengths, mid) + if bin_counter == expected_nbins: + return mid + elif bin_counter < expected_nbins: + hi = mid - 1 + else: + lo = mid + 1 + return mid + + +def perform_binning_new(lengths, single_X, single_base_nb_mean, single_total_bb_RD, sorted_chr_pos, sorted_chr_pos_last, x_gene_list, n_snps, phase_indicator, refined_lengths, binsize, rdrbinsize, nu, logphase_shift, geneticmap_file, secondary_min_umi=1000, max_binlength=5e6): + per_snp_umi = np.sum(single_total_bb_RD, axis=1) + # secondary_min_umi = np.percentile(per_snp_umi, secondary_percentile) + # bin both RDR and BAF + bin_single_X_rdr = [] + bin_single_X_baf = [] + bin_single_base_nb_mean = [] + bin_single_total_bb_RD = [] + bin_sorted_chr_pos_first = [] + bin_sorted_chr_pos_last = [] + bin_x_gene_list = [] + bin_n_snps = [] + cumlen = 0 + s = 0 + for le in refined_lengths: + while s < cumlen + le: + # initial bin with certain number of SNPs + t = s + 1 + while t < cumlen + le and np.sum(per_snp_umi[s:t]) < secondary_min_umi: + t += 1 + if sorted_chr_pos_last[t-1][1] - sorted_chr_pos[s][1] >= max_binlength: + t = max(t-1, s+1) + break + # expand binsize by minimum number of genes + this_genes = sum([ x_gene_list[i].split(" ") for i in range(s,t) ], []) + this_genes = [z for z in this_genes if z!=""] + idx_A = np.where(phase_indicator[s:t])[0] + idx_B = np.where(~phase_indicator[s:t])[0] + # if np.sum(per_snp_umi[s:t]) >= secondary_min_umi or sorted_chr_pos[s][0] != bin_sorted_chr_pos_last[-1][0]: + # bin_single_X_rdr.append( np.sum(single_X[s:t, 0, :], axis=0) ) + # bin_single_X_baf.append( np.sum(single_X[s:t, 1, :][idx_A,:], axis=0) + np.sum(single_total_bb_RD[s:t, :][idx_B,:] - single_X[s:t, 1, :][idx_B,:], axis=0) ) + # bin_single_base_nb_mean.append( np.sum(single_base_nb_mean[s:t, :], axis=0) ) + # bin_single_total_bb_RD.append( np.sum(single_total_bb_RD[s:t, :], axis=0) ) + # bin_sorted_chr_pos_first.append( sorted_chr_pos[s] ) + # bin_sorted_chr_pos_last.append( sorted_chr_pos_last[t-1] ) + # bin_x_gene_list.append( " ".join(this_genes) ) + # bin_n_snps.append( np.sum(n_snps[s:t]) ) + # else: + # bin_single_X_rdr[-1] += np.sum(single_X[s:t, 0, :], axis=0) + # bin_single_X_baf[-1] += np.sum(single_X[s:t, 1, :][idx_A,:], axis=0) + np.sum(single_total_bb_RD[s:t, :][idx_B,:] - single_X[s:t, 1, :][idx_B,:], axis=0) + # bin_single_base_nb_mean[-1] += np.sum(single_base_nb_mean[s:t, :], axis=0) + # bin_single_total_bb_RD[-1] += np.sum(single_total_bb_RD[s:t, :], axis=0) + # bin_sorted_chr_pos_last[-1] = sorted_chr_pos_last[t-1] + # if len(this_genes) > 0: + # bin_x_gene_list[-1] += " " + " ".join(this_genes) + # bin_n_snps[-1] += np.sum(n_snps[s:t]) + if len(bin_sorted_chr_pos_last) > 0 and sorted_chr_pos[s][0] == bin_sorted_chr_pos_last[-1][0] and \ + np.sum(per_snp_umi[s:t]) < 0.5*secondary_min_umi and sorted_chr_pos_last[t-1][1] - sorted_chr_pos[s][1] < 0.5*max_binlength: + bin_single_X_rdr[-1] += np.sum(single_X[s:t, 0, :], axis=0) + bin_single_X_baf[-1] += np.sum(single_X[s:t, 1, :][idx_A,:], axis=0) + np.sum(single_total_bb_RD[s:t, :][idx_B,:] - single_X[s:t, 1, :][idx_B,:], axis=0) + bin_single_base_nb_mean[-1] += np.sum(single_base_nb_mean[s:t, :], axis=0) + bin_single_total_bb_RD[-1] += np.sum(single_total_bb_RD[s:t, :], axis=0) + bin_sorted_chr_pos_last[-1] = sorted_chr_pos_last[t-1] + if len(this_genes) > 0: + bin_x_gene_list[-1] += " " + " ".join(this_genes) + bin_n_snps[-1] += np.sum(n_snps[s:t]) + else: + bin_single_X_rdr.append( np.sum(single_X[s:t, 0, :], axis=0) ) + bin_single_X_baf.append( np.sum(single_X[s:t, 1, :][idx_A,:], axis=0) + np.sum(single_total_bb_RD[s:t, :][idx_B,:] - single_X[s:t, 1, :][idx_B,:], axis=0) ) + bin_single_base_nb_mean.append( np.sum(single_base_nb_mean[s:t, :], axis=0) ) + bin_single_total_bb_RD.append( np.sum(single_total_bb_RD[s:t, :], axis=0) ) + bin_sorted_chr_pos_first.append( sorted_chr_pos[s] ) + bin_sorted_chr_pos_last.append( sorted_chr_pos_last[t-1] ) + bin_x_gene_list.append( " ".join(this_genes) ) + bin_n_snps.append( np.sum(n_snps[s:t]) ) + s = t + cumlen += le + single_X = np.stack([ np.vstack([bin_single_X_rdr[i], bin_single_X_baf[i]]) for i in range(len(bin_single_X_rdr)) ]) + single_base_nb_mean = np.vstack(bin_single_base_nb_mean) + single_total_bb_RD = np.vstack(bin_single_total_bb_RD) + sorted_chr_pos_first = bin_sorted_chr_pos_first + sorted_chr_pos_last = bin_sorted_chr_pos_last + x_gene_list = bin_x_gene_list + n_snps = bin_n_snps + + # phase switch probability from genetic distance + tmp_sorted_chr_pos = [val for pair in zip(sorted_chr_pos_first, sorted_chr_pos_last) for val in pair] + sorted_chr = np.array([x[0] for x in tmp_sorted_chr_pos]) + position_cM = get_position_cM_table( tmp_sorted_chr_pos, geneticmap_file ) + phase_switch_prob = compute_phase_switch_probability_position(position_cM, tmp_sorted_chr_pos, nu) + log_sitewise_transmat = np.log(phase_switch_prob) - logphase_shift + # log_sitewise_transmat = log_sitewise_transmat[np.arange(0, len(log_sitewise_transmat), 2)] + log_sitewise_transmat = log_sitewise_transmat[np.arange(1, len(log_sitewise_transmat), 2)] + + sorted_chr = np.array([x[0] for x in sorted_chr_pos_first]) + unique_chrs = [sorted_chr[0]] + for x in sorted_chr[1:]: + if x != unique_chrs[-1]: + unique_chrs.append( x ) + lengths = np.array([ np.sum(sorted_chr == chrname) for chrname in unique_chrs ]) + + # bin RDR + s = 0 + while s < single_X.shape[0]: + t = s+1 + this_genes = sum([ x_gene_list[i].split(" ") for i in range(s,t) ], []) + this_genes = [z for z in this_genes if z!=""] + while t < single_X.shape[0] and len(this_genes) < rdrbinsize: + t += 1 + this_genes += x_gene_list[t-1].split(" ") + this_genes = [z for z in this_genes if z!=""] + single_X[s, 0, :] = np.sum(single_X[s:t, 0, :], axis=0) + single_X[(s+1):t, 0, :] = 0 + single_base_nb_mean[s, :] = np.sum(single_base_nb_mean[s:t, :], axis=0) + single_base_nb_mean[(s+1):t, :] = 0 + x_gene_list[s] = " ".join(this_genes) + for k in range(s+1,t): + x_gene_list[k] = "" + s = t + + return lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, sorted_chr_pos_first, sorted_chr_pos_last, x_gene_list, n_snps + + +def create_bin_ranges(df_gene_snp, single_total_bb_RD, refined_lengths, secondary_min_umi, max_binlength=5e6): + """ + Aggregate haplotype blocks to bins + + Attributes + ---------- + df_gene_snp : data frame, (CHR, START, END, snp_id, gene, is_interval, block_id) + Gene and SNP info combined into a single data frame sorted by genomic positions. "is_interval" suggest whether the entry is a gene or a SNP. "gene" column either contain gene name if the entry is a gene, or the gene a SNP belongs to if the entry is a SNP. + + single_total_bb_RD : array, (n_blocks, n_spots) + Total SNP-covering reads per haplotype block per spot. + + refined_lengths : array + Number of haplotype blocks before each phase switch. The numbers should sum up to n_blocks. + + Returns + ------- + df_gene_snp : data frame, (CHR, START, END, snp_id, gene, is_interval, block_id, bin_id) + The newly added bin_id column indicates which bin each gene or SNP belongs to. + """ + def greedy_binning_nobreak(block_lengths, block_umi, secondary_min_umi, max_binlength): + """ + Returns + ------- + bin_ids : array, (n_blocks) + The bin id of the input blocks. Should have the same size with block_lengths and block_umi. + """ + assert len(block_lengths) == len(block_umi) + bin_ranges = [] + s = 0 + while s < len(block_lengths): + t = s + 1 + while t < len(block_lengths) and np.sum(block_umi[s:t]) < secondary_min_umi: + t += 1 + if np.sum(block_lengths[s:t]) >= max_binlength: + t = max(t-1, s+1) + break + # check whether it is a very small bin in the end + if s > 0 and t == len(block_lengths) and np.sum(block_umi[s:t]) < 0.5*secondary_min_umi and np.sum(block_lengths[s:t]) < 0.5*max_binlength: + bin_ranges[-1][1] = t + else: + bin_ranges.append( [s,t] ) + s = t + bin_ids = np.zeros(len(block_lengths), dtype=int) + for i,x in enumerate(bin_ranges): + bin_ids[x[0]:x[1]] = i + return bin_ids + + # block lengths and block umis + sorted_chr_pos_both = df_gene_snp.groupby('block_id').agg({'CHR': 'first', 'START': 'first', 'END': 'last'}) + block_lengths = sorted_chr_pos_both.END.values - sorted_chr_pos_both.START.values + block_umi = np.sum(single_total_bb_RD, axis=1) + n_blocks = len(block_lengths) + + # get a list of breakpoints where bin much break + breakpoints = np.concatenate([ np.cumsum(refined_lengths), np.where(block_lengths > max_binlength)[0], np.where(block_lengths > max_binlength)[0]+1 ]) + breakpoints =np.sort(np.unique(breakpoints)) + # append 0 in the front of breakpoints so that each pair of adjacent breakpoints can be an input to greedy_binning_nobreak + if breakpoints[0] != 0: + breakpoints = np.append( [0], breakpoints ) + assert np.all(breakpoints[:-1] < breakpoints[1:]) + + # loop over breakpoints and bin each block + bin_ids = np.zeros(n_blocks, dtype=int) + offset = 0 + for i in range(len(breakpoints)-1): + b1 = breakpoints[i] + b2 = breakpoints[i+1] + if b2 - b1 == 1: + bin_ids[b1:b2] = offset + offset += 1 + else: + this_bin_ids = greedy_binning_nobreak(block_lengths[b1:b2], block_umi[b1:b2], secondary_min_umi, max_binlength) + bin_ids[b1:b2] = offset + this_bin_ids + offset += np.max(this_bin_ids) + 1 + + # append bin_ids to df_gene_snp + df_gene_snp["bin_id"] = df_gene_snp.block_id.map({i:x for i,x in enumerate(bin_ids)}) + + return df_gene_snp + + +def summarize_counts_for_bins(df_gene_snp, adata, single_X, single_total_bb_RD, phase_indicator, nu, logphase_shift, geneticmap_file): + """ + Attributes: + ---------- + df_gene_snp : pd.DataFrame + Contain "block_id" column to indicate which genes/snps belong to which block. + + Returns + ---------- + lengths : array, (n_chromosomes,) + Number of blocks per chromosome. + + single_X : array, (n_blocks, 2, n_spots) + Transcript counts and B allele count per block per cell. + + single_base_nb_mean : array, (n_blocks, n_spots) + Baseline transcript counts in normal diploid per block per cell. + + single_total_bb_RD : array, (n_blocks, n_spots) + Total allele count per block per cell. + + log_sitewise_transmat : array, (n_blocks,) + Log phase switch probability between each pair of adjacent blocks. + """ + bins = df_gene_snp.bin_id.unique() + bin_single_X = np.zeros((len(bins), 2, adata.shape[0]), dtype=int) + bin_single_base_nb_mean = np.zeros((len(bins), adata.shape[0])) + bin_single_total_bb_RD = np.zeros((len(bins), adata.shape[0]), dtype=int) + # summarize counts of involved genes and SNPs within each block + df_bin_contents = df_gene_snp[~df_gene_snp.bin_id.isnull()].groupby('bin_id').agg({"block_id":set, "gene":set}) + for b in range(df_bin_contents.shape[0]): + # BAF (SNPs) + involved_blocks = [x for x in df_bin_contents.block_id.values[b] if not x is None] + this_phased = np.where(phase_indicator[involved_blocks].reshape(-1,1), single_X[involved_blocks, 1, :], single_total_bb_RD[involved_blocks, :] - single_X[involved_blocks, 1, :]) + bin_single_X[b, 1, :] = np.sum(this_phased, axis=0) + bin_single_total_bb_RD[b, :] = np.sum( single_total_bb_RD[involved_blocks, :], axis=0 ) + # RDR (genes) + involved_genes = [x for x in df_bin_contents.gene.values[b] if not x is None] + bin_single_X[b, 0, :] = np.sum( adata.layers['count'][:, adata.var.index.isin(involved_genes)], axis=1 ) + + # lengths + lengths = np.zeros(len(df_gene_snp.CHR.unique()), dtype=int) + for i,c in enumerate( df_gene_snp.CHR.unique() ): + lengths[i] = len( df_gene_snp[ (df_gene_snp.CHR == c) & (~df_gene_snp.bin_id.isnull()) ].bin_id.unique() ) + + # phase switch probability from genetic distance + sorted_chr_pos_first = df_gene_snp.groupby('bin_id').agg({'CHR': 'first', 'START': 'first'}) + sorted_chr_pos_first = list(zip(sorted_chr_pos_first.CHR.values, sorted_chr_pos_first.START.values)) + sorted_chr_pos_last = df_gene_snp.groupby('bin_id').agg({'CHR': 'last', 'END': 'last'}) + sorted_chr_pos_last = list(zip(sorted_chr_pos_last.CHR.values, sorted_chr_pos_last.END.values)) + # + tmp_sorted_chr_pos = [val for pair in zip(sorted_chr_pos_first, sorted_chr_pos_last) for val in pair] + position_cM = get_position_cM_table( tmp_sorted_chr_pos, geneticmap_file ) + phase_switch_prob = compute_phase_switch_probability_position(position_cM, tmp_sorted_chr_pos, nu) + log_sitewise_transmat = np.minimum(np.log(0.5), np.log(phase_switch_prob) - logphase_shift) + # log_sitewise_transmat = log_sitewise_transmat[np.arange(0, len(log_sitewise_transmat), 2)] + log_sitewise_transmat = log_sitewise_transmat[np.arange(1, len(log_sitewise_transmat), 2)] + + return lengths, bin_single_X, bin_single_base_nb_mean, bin_single_total_bb_RD, log_sitewise_transmat + + +def bin_selection_basedon_normal(df_gene_snp, single_X, single_base_nb_mean, single_total_bb_RD, nu, logphase_shift, index_normal, geneticmap_file, confidence_interval=[0.05, 0.95], min_betabinom_tau=30): + """ + Filter out bins that potential contain somatic mutations based on BAF of normal spots. + """ + # pool B allele counts for each bin across all normal spots + tmpX = np.sum(single_X[:, 1, index_normal], axis=1) + tmptotal_bb_RD = np.sum(single_total_bb_RD[:, index_normal], axis=1) + model = Weighted_BetaBinom(tmpX, np.ones(len(tmpX)), weights=np.ones(len(tmpX)), exposure=tmptotal_bb_RD) + tmpres = model.fit(disp=0) + tmpres.params[0] = 0.5 + tmpres.params[-1] = max(tmpres.params[-1], min_betabinom_tau) + # remove bins if normal B allele frequencies fall out of 5%-95% probability range + removal_indicator1 = (tmpX < scipy.stats.betabinom.ppf(confidence_interval[0], tmptotal_bb_RD, tmpres.params[0] * tmpres.params[1], (1-tmpres.params[0]) * tmpres.params[1])) + removal_indicator2 = (tmpX > scipy.stats.betabinom.ppf(confidence_interval[1], tmptotal_bb_RD, tmpres.params[0] * tmpres.params[1], (1-tmpres.params[0]) * tmpres.params[1])) + print( np.sum(removal_indicator1 | removal_indicator2) ) + index_removal = np.where(removal_indicator1 | removal_indicator2)[0] + index_remaining = np.where(~(removal_indicator1 | removal_indicator2))[0] + # + # change df_gene_snp + col = np.where(df_gene_snp.columns == "bin_id")[0][0] + df_gene_snp.iloc[ np.where(df_gene_snp.bin_id.isin(index_removal))[0], col] = None + # remap bin_id to existing list + df_gene_snp['bin_id'] = df_gene_snp['bin_id'].map({x:i for i,x in enumerate(index_remaining)}) + df_gene_snp.bin_id = df_gene_snp.bin_id.astype('Int64') + + # change the related data matrices + single_X = single_X[index_remaining, :, :] + single_base_nb_mean = single_base_nb_mean[index_remaining, :] + single_total_bb_RD = single_total_bb_RD[index_remaining, :] + + # lengths + lengths = np.zeros(len(df_gene_snp.CHR.unique()), dtype=int) + for i,c in enumerate( df_gene_snp.CHR.unique() ): + lengths[i] = len( df_gene_snp[ (df_gene_snp.CHR == c) & (~df_gene_snp.bin_id.isnull()) ].bin_id.unique() ) + + ## phase switch probability from genetic distance + sorted_chr_pos_first = df_gene_snp.groupby('bin_id').agg({'CHR': 'first', 'START': 'first'}) + sorted_chr_pos_first = list(zip(sorted_chr_pos_first.CHR.values, sorted_chr_pos_first.START.values)) + sorted_chr_pos_last = df_gene_snp.groupby('bin_id').agg({'CHR': 'last', 'END': 'last'}) + sorted_chr_pos_last = list(zip(sorted_chr_pos_last.CHR.values, sorted_chr_pos_last.END.values)) + # + tmp_sorted_chr_pos = [val for pair in zip(sorted_chr_pos_first, sorted_chr_pos_last) for val in pair] + position_cM = get_position_cM_table( tmp_sorted_chr_pos, geneticmap_file ) + phase_switch_prob = compute_phase_switch_probability_position(position_cM, tmp_sorted_chr_pos, nu) + log_sitewise_transmat = np.minimum(np.log(0.5), np.log(phase_switch_prob) - logphase_shift) + # log_sitewise_transmat = log_sitewise_transmat[np.arange(0, len(log_sitewise_transmat), 2)] + log_sitewise_transmat = log_sitewise_transmat[np.arange(1, len(log_sitewise_transmat), 2)] + + return lengths, single_X, single_base_nb_mean, single_total_bb_RD, log_sitewise_transmat, df_gene_snp + + +def filter_de_genes(exp_counts, x_gene_list, normal_candidate, sample_list=None, sample_ids=None, logfcthreshold=4, quantile_threshold=80): + adata = anndata.AnnData(exp_counts) + adata.layers["count"] = exp_counts.values + adata.obs["normal_candidate"] = normal_candidate + # + map_gene_adatavar = {} + map_gene_umi = {} + list_gene_umi = np.sum(adata.layers["count"], axis=0) + for i,x in enumerate(adata.var.index): + map_gene_adatavar[x] = i + map_gene_umi[x] = list_gene_umi[i] + # + if sample_list is None: + sample_list = [None] + # + filtered_out_set = set() + for s,sname in enumerate(sample_list): + if sname is None: + index = np.arange(adata.shape[0]) + else: + index = np.where(sample_ids == s)[0] + tmpadata = adata[index, :].copy() + # + umi_threshold = np.percentile( np.sum(tmpadata.layers["count"], axis=0), quantile_threshold ) + # + sc.pp.filter_cells(tmpadata, min_genes=200) + sc.pp.filter_genes(tmpadata, min_cells=10) + med = np.median( np.sum(tmpadata.layers["count"], axis=1) ) + # sc.pp.normalize_total(tmpadata, target_sum=1e4) + sc.pp.normalize_total(tmpadata, target_sum=med) + sc.pp.log1p(tmpadata) + # new added + sc.pp.pca(tmpadata, n_comps=4) + kmeans = KMeans(n_clusters=2, random_state=0).fit(tmpadata.obsm["X_pca"]) + kmeans_labels = kmeans.predict(tmpadata.obsm["X_pca"]) + idx_kmeans_label = np.argmax(np.bincount( kmeans_labels[tmpadata.obs["normal_candidate"]], minlength=2 )) + clone = np.array(["normal"] * tmpadata.shape[0]) + clone[ (kmeans_labels != idx_kmeans_label) & (~tmpadata.obs["normal_candidate"]) ] = "tumor" + tmpadata.obs["clone"] = clone + # end added + sc.tl.rank_genes_groups(tmpadata, 'clone', groups=["tumor"], reference="normal", method='wilcoxon') + genenames = np.array([ x[0] for x in tmpadata.uns["rank_genes_groups"]["names"] ]) + logfc = np.array([ x[0] for x in tmpadata.uns["rank_genes_groups"]["logfoldchanges"] ]) + geneumis = np.array([ map_gene_umi[x] for x in genenames]) + this_filtered_out_set = set(list(genenames[ (np.abs(logfc) > logfcthreshold) & (geneumis > umi_threshold) ])) + filtered_out_set = filtered_out_set | this_filtered_out_set + print(f"Filter out {len(filtered_out_set)} DE genes") + # + new_single_X_rdr = np.zeros((len(x_gene_list), adata.shape[0])) + for i,x in enumerate(x_gene_list): + g_list = [z for z in x.split() if z != ""] + idx_genes = np.array([ map_gene_adatavar[g] for g in g_list if (not g in filtered_out_set) and (g in map_gene_adatavar)]) + if len(idx_genes) > 0: + new_single_X_rdr[i, :] = np.sum(adata.layers["count"][:, idx_genes], axis=1) + return new_single_X_rdr, filtered_out_set + + +def filter_de_genes_tri(exp_counts, df_bininfo, normal_candidate, sample_list=None, sample_ids=None, logfcthreshold_u=2, logfcthreshold_t=4, quantile_threshold=80): + """ + Attributes + ---------- + df_bininfo : pd.DataFrame + Contains columns ['CHR', 'START', 'END', 'INCLUDED_GENES', 'INCLUDED_SNP_IDS'], 'INCLUDED_GENES' contains space-delimited gene names. + """ + adata = anndata.AnnData(exp_counts) + adata.layers["count"] = exp_counts.values + adata.obs["normal_candidate"] = normal_candidate + # + map_gene_adatavar = {} + map_gene_umi = {} + list_gene_umi = np.sum(adata.layers["count"], axis=0) + for i,x in enumerate(adata.var.index): + map_gene_adatavar[x] = i + map_gene_umi[x] = list_gene_umi[i] + # + if sample_list is None: + sample_list = [None] + # + filtered_out_set = set() + for s,sname in enumerate(sample_list): + if sname is None: + index = np.arange(adata.shape[0]) + else: + index = np.where(sample_ids == s)[0] + tmpadata = adata[index, :].copy() + if np.sum(tmpadata.layers["count"][tmpadata.obs["normal_candidate"], :]) < tmpadata.shape[1] * 10: + continue + # + umi_threshold = np.percentile( np.sum(tmpadata.layers["count"], axis=0), quantile_threshold ) + # + # sc.pp.filter_cells(tmpadata, min_genes=200) + sc.pp.filter_genes(tmpadata, min_cells=10) + med = np.median( np.sum(tmpadata.layers["count"], axis=1) ) + # sc.pp.normalize_total(tmpadata, target_sum=1e4) + sc.pp.normalize_total(tmpadata, target_sum=med) + sc.pp.log1p(tmpadata) + # new added + sc.pp.pca(tmpadata, n_comps=4) + kmeans = KMeans(n_clusters=2, random_state=0).fit(tmpadata.obsm["X_pca"]) + kmeans_labels = kmeans.predict(tmpadata.obsm["X_pca"]) + idx_kmeans_label = np.argmax(np.bincount( kmeans_labels[tmpadata.obs["normal_candidate"]], minlength=2 )) + clone = np.array(["normal"] * tmpadata.shape[0]) + clone[ (kmeans_labels != idx_kmeans_label) & (~tmpadata.obs["normal_candidate"]) ] = "tumor" + ### third part ### + clone[ (kmeans_labels == idx_kmeans_label) & (~tmpadata.obs["normal_candidate"]) ] = "unsure" + tmpadata.obs["clone"] = clone + # end added + # sc.tl.rank_genes_groups(tmpadata, 'clone', groups=["tumor", "unsure"], reference="normal", method='wilcoxon') + # # DE and log fold change comparing tumor and normal + # genenames_t = np.array([ x[0] for x in tmpadata.uns["rank_genes_groups"]["names"] ]) + # logfc_t = np.array([ x[0] for x in tmpadata.uns["rank_genes_groups"]["logfoldchanges"] ]) + # geneumis_t = np.array([ map_gene_umi[x] for x in genenames_t]) + # # DE and log fold change comparing unsure and normal + # genenames_u = np.array([ x[1] for x in tmpadata.uns["rank_genes_groups"]["names"] ]) + # logfc_u = np.array([ x[1] for x in tmpadata.uns["rank_genes_groups"]["logfoldchanges"] ]) + # geneumis_u = np.array([ map_gene_umi[x] for x in genenames_u]) + # this_filtered_out_set = set(list(genenames_t[ (np.abs(logfc_t) > logfcthreshold) & (geneumis_t > umi_threshold) ])) | set(list(genenames_u[ (np.abs(logfc_u) > logfcthreshold) & (geneumis_u > umi_threshold) ])) + # + agg_counts = np.vstack([ np.sum(tmpadata.layers["count"][tmpadata.obs['clone']==c,:], axis=0) for c in ['normal', 'unsure', 'tumor'] ]) + agg_counts = agg_counts / np.sum(agg_counts, axis=1, keepdims=True) * 1e6 + geneumis = np.array([ map_gene_umi[x] for x in tmpadata.var.index]) + logfc_u = np.where( ((agg_counts[1,:]==0) | (agg_counts[0,:]==0)), 10, np.log2(agg_counts[1,:] / agg_counts[0,:]) ) + logfc_t = np.where( ((agg_counts[2,:]==0) | (agg_counts[0,:]==0)), 10, np.log2(agg_counts[2,:] / agg_counts[0,:]) ) + this_filtered_out_set = set(list(tmpadata.var.index[ (np.abs(logfc_u)>logfcthreshold_u) & (geneumis>umi_threshold) ])) | set(list(tmpadata.var.index[ (np.abs(logfc_t)>logfcthreshold_t) & (geneumis>umi_threshold) ])) + filtered_out_set = filtered_out_set | this_filtered_out_set + print(f"Filter out {len(filtered_out_set)} DE genes") + # + # remove genes that are in filtered_out_set + new_single_X_rdr = np.zeros((df_bininfo.shape[0], adata.shape[0])) + for b,genestr in enumerate(df_bininfo.INCLUDED_GENES.values): + # RDR (genes) + involved_genes = set(genestr.split(" ")) - filtered_out_set + new_single_X_rdr[b, :] = np.sum( adata.layers['count'][:, adata.var.index.isin(involved_genes)], axis=1 ) + + return new_single_X_rdr, filtered_out_set + + +def get_lengths_by_arm(sorted_chr_pos, centromere_file): + """ + centromere_file for hg38: /u/congma/ragr-data/datasets/ref-genomes/centromeres/hg38.centromeres.txt + """ + # read and process centromere file + unique_chrs = [f"chr{i}" for i in range(1, 23)] + df = pd.read_csv(centromere_file, sep="\t", header=None, index_col=None, names=["CHRNAME", "START", "END", "LABEL", "SOURCE"]) + df = df[df.CHRNAME.isin(unique_chrs)] + df["CHR"] = [int(x[3:]) for x in df.CHRNAME] + df = df.groupby("CHR").agg({"CHRNAME":"first", "START":"min", "END":"min", "LABEL":"first", "SOURCE":"first"}) + df.sort_index(inplace=True) + # count lengths + mat_chr_pos = np.vstack([ np.array([x[0] for x in sorted_chr_pos]), np.array([x[1] for x in sorted_chr_pos]) ]).T + armlengths = sum([ [np.sum((mat_chr_pos[:,0] == df.index[i]) & (mat_chr_pos[:,1] <= df.END.iloc[i])), \ + np.sum((mat_chr_pos[:,0] == df.index[i]) & (mat_chr_pos[:,1] > df.END.iloc[i]))] for i in range(df.shape[0])], []) + armlengths = np.array(armlengths, dtype=int) + return armlengths + + +# def expand_df_cnv(df_cnv, binsize=1e6): +# df_expand = [] +# for i in range(df_cnv.shape[0]): +# # repeat the row i for int(END - START / binsize) times and save to a new dataframe +# n_bins = max(1, int(1.0*(df_cnv.iloc[i].END - df_cnv.iloc[i].START) / binsize)) +# tmp = pd.DataFrame(np.repeat(df_cnv.iloc[i:(i+1),:].values, n_bins, axis=0), columns=df_cnv.columns) +# for k in range(n_bins): +# tmp.END.iloc[k] = df_cnv.START.iloc[i]+ k*binsize +# tmp.END.iloc[-1] = df_cnv.END.iloc[i] +# df_expand.append(tmp) +# df_expand = pd.concat(df_expand, ignore_index=True) +# return df_expand + + +def expand_df_cnv(df_cnv, binsize=2e5, fillmissing=True): + # get CHR and its END + df_chr_end = df_cnv.groupby("CHR").agg({"END":"max"}).reset_index() + + # initialize df_expand as a dataframe containing CHR, START, END such that END-START = binsize + df_expand = [] + for i,c in enumerate(df_chr_end.CHR.values): + df_expand.append( pd.DataFrame({"CHR":c, "START":np.arange(0, df_chr_end.END.values[i], binsize), "END":binsize + np.arange(0, df_chr_end.END.values[i], binsize)}) ) + df_expand = pd.concat(df_expand, ignore_index=True) + + # find the index in df_cnv such that each entry in df_expand overlaps with the largest length + vec_cnv_chr = df_cnv.CHR.values + vec_cnv_start = df_cnv.START.values + vec_cnv_end = df_cnv.END.values + + seg_index = -1 * np.ones(df_expand.shape[0], dtype=int) + j = 0 + for i, this_chr in enumerate(df_expand.CHR.values): + this_start = df_expand.START.values[i] + this_end = df_expand.END.values[i] + while j < df_cnv.shape[0] and (vec_cnv_chr[j] < this_chr or (vec_cnv_chr[j] == this_chr and vec_cnv_end[j] <= this_start)): + j += 1 + # overlap length of the j-th segment to (j+3)-th segment in df_cnv + overlap_lengths = [] + for k in range(j, min(j+3, df_cnv.shape[0])): + if vec_cnv_chr[k] > this_chr or vec_cnv_start[k] > this_end: + break + overlap_lengths.append( min(vec_cnv_end[k], this_end) - max(vec_cnv_start[k], this_start) ) + if len(overlap_lengths) > 0: + seg_index[i] = j + np.argmax(overlap_lengths) + + for col in df_cnv.columns[df_cnv.columns.str.startswith("clone")]: + df_expand[col] = np.nan + df_expand[col].iloc[seg_index>=0] = df_cnv[col].values[ seg_index[seg_index>=0] ] + df_expand[col] = df_expand[col].astype("Int64") + + if fillmissing: + # for each nan row, fill it with the closest non-nan row + nan_rows = np.where( df_expand.iloc[:,-1].isnull() )[0] + filled_rows = np.where( ~df_expand.iloc[:,-1].isnull() )[0] + for i in nan_rows: + candidates = np.where( (~df_expand.iloc[:,-1].isnull()) & (df_expand.CHR.values == df_expand.CHR.values[i]) )[0] + j = candidates[ np.argmin(np.abs(candidates - i)) ] + df_expand.iloc[i, 3:] = df_expand.iloc[j, 3:].values + + return df_expand + + +def summary_events(cnv_segfile, rescombinefile, minlength=10): + EPS_BAF = 0.07 + # read rescombine file + res_combine = dict(np.load(rescombinefile, allow_pickle=True)) + pred_cnv = res_combine["pred_cnv"] + logrdr_profile = np.vstack([ res_combine["new_log_mu"][pred_cnv[:,c], c] for c in range(pred_cnv.shape[1]) ]) + baf_profile = np.vstack([ res_combine["new_p_binom"][pred_cnv[:,c], c] for c in range(pred_cnv.shape[1]) ]) + + # read CNV file + df_cnv = pd.read_csv(cnv_segfile, header=0, sep='\t') + # get clone names + calico_clones = np.array([ x.split(" ")[0][5:] for x in df_cnv.columns if x.endswith(" A") ]) + # retain only the clones that are not entirely diploid + calico_clones = [c for c in calico_clones if np.sum(np.abs(baf_profile[int(c),:] - 0.5) > EPS_BAF) > minlength ] + # label CNV states per bin per clone into "neu", "del", "amp", "loh" states + for c in calico_clones: + counts = df_cnv.END.values-df_cnv.START.values + counts = np.maximum(1, counts / 1e4).astype(int) + tmp = strict_convert_copy_to_states(df_cnv[f"clone{c} A"].values, df_cnv[f"clone{c} B"].values, counts=counts) + tmp[tmp == "bdel"] = "del" + tmp[tmp == "bamp"] = "amp" + df_cnv[f"srt_cnstate_clone{c}"] = tmp + + # partition the genome into segments such that the allele-specific CN across all clones are the same within each segment + segments, labs = get_intervals_nd(df_cnv[["CHR"] + [ f"clone{x} A" for x in calico_clones ] + [ f"clone{x} B" for x in calico_clones ]].values) + # collect event, that is labs and segments pair such that the cnstate is not normal + events = [] + for i, seg in enumerate(segments): + if seg[1] - seg[0] < minlength: + continue + if np.all(df_cnv[[ f"srt_cnstate_clone{x}" for x in calico_clones ]].iloc[seg[0],:].values == "neu"): + continue + acn_list = [ (df_cnv[f"srt_cnstate_clone{c}"].values[seg[0]], df_cnv[f"clone{c} A"].values[seg[0]], df_cnv[f"clone{c} B"].values[seg[0]]) for c in calico_clones ] + acn_set = set(acn_list) + for e in acn_set: + if e[0] == "neu": + continue + involved_clones = [calico_clones[i] for i in range(len(calico_clones)) if acn_list[i] == e] + events.append( pd.DataFrame({"CHR":df_cnv.CHR.values[seg[0]], "START":df_cnv.START.values[seg[0]], "END":df_cnv.END.values[seg[1]-1], "BinSTART":seg[0], "BinEND":seg[1]-1,\ + "CN":f"{e[1]}|{e[2]}", "Label":e[0], "involved_clones":",".join(involved_clones)}, index=[0]) ) + df_events = pd.concat(events, ignore_index=True) + + # merge adjacent events if they have the same involved_clones and same CN + unique_ic = np.unique(df_events.involved_clones.values) + concise_events = [] + for ic in unique_ic: + tmpdf = df_events[df_events.involved_clones == ic] + # merge adjacent rows in tmpdf if they have the same CN END of the previous row is the same as the START of the next row + concise_events.append( tmpdf.iloc[0:1,:] ) + for i in range(1, tmpdf.shape[0]): + if tmpdf.CN.values[i] == concise_events[-1].CN.values[0] and tmpdf.CHR.values[i] == concise_events[-1].CHR.values[0] and tmpdf.START.values[i] == concise_events[-1].END.values[0]: + concise_events[-1].END.values[0] = tmpdf.END.values[i] + concise_events[-1].BinEND.values[0] = tmpdf.BinEND.values[i] + else: + concise_events.append( tmpdf.iloc[i:(i+1),:] ) + df_concise_events = pd.concat(concise_events, ignore_index=True) + + # add the RDR abd BAF info + rdr = np.nan * np.ones(df_concise_events.shape[0]) + baf = np.nan * np.ones(df_concise_events.shape[0]) + rdr_diff = np.nan * np.ones(df_concise_events.shape[0]) + baf_diff = np.nan * np.ones(df_concise_events.shape[0]) + for i in range(df_concise_events.shape[0]): + involved_clones = np.array([int(c) for c in df_concise_events.involved_clones.values[i].split(",")]) + bs = df_concise_events.BinSTART.values[i] + be = df_concise_events.BinEND.values[i] + # rdr[i] = np.exp(np.mean(res_combine["new_log_mu"][ (pred_cnv[bs:be,:][:,involved_clones].flatten(), np.tile(involved_clones, be-bs)) ])) + # baf[i] = np.mean(res_combine["new_p_binom"][ (pred_cnv[bs:be,:][:,involved_clones].flatten(), np.tile(involved_clones, be-bs)) ]) + rdr[i] = np.exp(np.mean( np.concatenate([logrdr_profile[i, bs:be] for i in involved_clones ]) )) + baf[i] = np.mean( np.concatenate([baf_profile[i, bs:be] for i in involved_clones ]) ) + # get the uninvolved clones + uninvolved_clones = np.array([int(c)for c in calico_clones if int(c) not in involved_clones]) + if len(uninvolved_clones) > 0: + # rdr_diff[i] = np.exp(np.mean(res_combine["new_log_mu"][ (pred_cnv[bs:be,:][:,uninvolved_clones].flatten(), np.tile(uninvolved_clones, be-bs)) ])) - rdr[i] + # baf_diff[i] = np.mean(res_combine["new_p_binom"][ (pred_cnv[bs:be,:][:,uninvolved_clones].flatten(), np.tile(uninvolved_clones, be-bs)) ]) - baf[i] + rdr_diff[i] = rdr[i] - np.exp(np.mean( np.concatenate([logrdr_profile[i, bs:be] for i in uninvolved_clones ]) )) + baf_diff[i] = baf[i] - np.mean( np.concatenate([baf_profile[i, bs:be] for i in uninvolved_clones ]) ) + df_concise_events["RDR"] = rdr + df_concise_events["BAF"] = baf + df_concise_events["RDR_diff"] = rdr_diff + df_concise_events["BAF_diff"] = baf_diff + + return df_concise_events[["CHR", "START", "END", "BinSTART", "BinEND", "RDR", "BAF", "RDR_diff", "BAF_diff", "CN", "Label", "involved_clones"]] + + +def get_best_initialization(output_dir): + """ + find the best HMRF initialization random seed + """ + # get a list */rdrbaf_final_nstates*_smp.npz files within output_dir + rdrbaf_files = [x for x in Path(output_dir).rglob("rdrbaf_final_nstates*_smp.npz")] + df = [] + for file in rdrbaf_files: + outdir = file.parent + res_combine = dict(np.load(str(file)), allow_pickle=True) + df.append( pd.DataFrame({'outdir':str(outdir), "log-likelihood":res_combine["total_llf"]}, index=[0]) ) + df = pd.concat(df, ignore_index=True) + idx = np.argmax(df["log-likelihood"]) + return df["outdir"].iloc[idx] diff --git a/src/calicost/utils_distribution_fitting.py b/src/calicost/utils_distribution_fitting.py new file mode 100644 index 0000000..59b8592 --- /dev/null +++ b/src/calicost/utils_distribution_fitting.py @@ -0,0 +1,272 @@ +import functools +import inspect +import logging + +import numpy as np +import scipy +from scipy import linalg, special +from scipy.special import logsumexp, loggamma +import scipy.integrate +import scipy.stats +from numba import jit, njit +from sklearn import cluster +from sklearn.utils import check_random_state +import statsmodels +import statsmodels.api as sm +from statsmodels.base.model import GenericLikelihoodModel +import os + +os.environ["MKL_NUM_THREADS"] = "1" +os.environ["OPENBLAS_NUM_THREADS"] = "1" +os.environ["OMP_NUM_THREADS"] = "1" + + +def convert_params(mean, alpha): + """ + Convert mean/dispersion parameterization of a negative binomial to the ones scipy supports + + See https://mathworld.wolfram.com/NegativeBinomialDistribution.html + """ + p = 1.0 / (1.0 + mean * alpha) + n = 1.0 / alpha + return n, p + + +class Weighted_NegativeBinomial(GenericLikelihoodModel): + """ + Negative Binomial model endog ~ NB(exposure * exp(exog @ params[:-1]), params[-1]), where exog is the design matrix, and params[-1] is 1 / overdispersion. + This function fits the NB params when samples are weighted by weights: max_{params} \sum_{s} weights_s * log P(endog_s | exog_s; params) + + Attributes + ---------- + endog : array, (n_samples,) + Y values. + + exog : array, (n_samples, n_features) + Design matrix. + + weights : array, (n_samples,) + Sample weights. + + exposure : array, (n_samples,) + Multiplication constant outside the exponential term. In scRNA-seq or SRT data, this term is the total UMI count per cell/spot. + """ + def __init__(self, endog, exog, weights, exposure, seed=0, **kwds): + super(Weighted_NegativeBinomial, self).__init__(endog, exog, **kwds) + self.weights = weights + self.exposure = exposure + self.seed = seed + # + def nloglikeobs(self, params): + nb_mean = np.exp(self.exog @ params[:-1]) * self.exposure + # nb_std = np.sqrt(nb_mean + params[-1] * nb_mean**2) + n, p = convert_params(nb_mean, params[-1]) + llf = scipy.stats.nbinom.logpmf(self.endog, n, p) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + self.exog_names.append('alpha') + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = np.append(0.1 * np.ones(self.nparams), 0.01) + + return super(Weighted_NegativeBinomial, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class Weighted_NegativeBinomial_mix(GenericLikelihoodModel): + def __init__(self, endog, exog, weights, exposure, tumor_prop, seed=0, **kwds): + super(Weighted_NegativeBinomial_mix, self).__init__(endog, exog, **kwds) + self.weights = weights + self.exposure = exposure + self.seed = seed + self.tumor_prop = tumor_prop + # + def nloglikeobs(self, params): + nb_mean = self.exposure * (self.tumor_prop * np.exp(self.exog @ params[:-1]) + 1 - self.tumor_prop) + # nb_std = np.sqrt(nb_mean + params[-1] * nb_mean**2) + n, p = convert_params(nb_mean, params[-1]) + llf = scipy.stats.nbinom.logpmf(self.endog, n, p) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + self.exog_names.append('alpha') + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = np.append(0.1 * np.ones(self.nparams), 0.01) + return super(Weighted_NegativeBinomial_mix, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class Weighted_BetaBinom(GenericLikelihoodModel): + """ + Beta-binomial model endog ~ BetaBin(exposure, tau * p, tau * (1 - p)), where p = exog @ params[:-1] and tau = params[-1]. + This function fits the BetaBin params when samples are weighted by weights: max_{params} \sum_{s} weights_s * log P(endog_s | exog_s; params) + + Attributes + ---------- + endog : array, (n_samples,) + Y values. + + exog : array, (n_samples, n_features) + Design matrix. + + weights : array, (n_samples,) + Sample weights. + + exposure : array, (n_samples,) + Total number of trials. In BAF case, this is the total number of SNP-covering UMIs. + """ + def __init__(self, endog, exog, weights, exposure, **kwds): + super(Weighted_BetaBinom, self).__init__(endog, exog, **kwds) + self.weights = weights + self.exposure = exposure + # + def nloglikeobs(self, params): + a = (self.exog @ params[:-1]) * params[-1] + b = (1 - self.exog @ params[:-1]) * params[-1] + llf = scipy.stats.betabinom.logpmf(self.endog, self.exposure, a, b) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + self.exog_names.append("tau") + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = np.append(0.5 / np.sum(self.exog.shape[1]) * np.ones(self.nparams), 1) + return super(Weighted_BetaBinom, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class Weighted_BetaBinom_mix(GenericLikelihoodModel): + def __init__(self, endog, exog, weights, exposure, tumor_prop, **kwds): + super(Weighted_BetaBinom_mix, self).__init__(endog, exog, **kwds) + self.weights = weights + self.exposure = exposure + self.tumor_prop = tumor_prop + # + def nloglikeobs(self, params): + a = (self.exog @ params[:-1] * self.tumor_prop + 0.5 * (1 - self.tumor_prop)) * params[-1] + b = ((1 - self.exog @ params[:-1]) * self.tumor_prop + 0.5 * (1 - self.tumor_prop)) * params[-1] + llf = scipy.stats.betabinom.logpmf(self.endog, self.exposure, a, b) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + self.exog_names.append("tau") + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = np.append(0.5 / np.sum(self.exog.shape[1]) * np.ones(self.nparams), 1) + return super(Weighted_BetaBinom_mix, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class Weighted_BetaBinom_fixdispersion(GenericLikelihoodModel): + def __init__(self, endog, exog, tau, weights, exposure, **kwds): + super(Weighted_BetaBinom_fixdispersion, self).__init__(endog, exog, **kwds) + self.tau = tau + self.weights = weights + self.exposure = exposure + # + def nloglikeobs(self, params): + a = (self.exog @ params) * self.tau + b = (1 - self.exog @ params) * self.tau + llf = scipy.stats.betabinom.logpmf(self.endog, self.exposure, a, b) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = 0.1 * np.ones(self.nparams) + + return super(Weighted_BetaBinom_fixdispersion, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class Weighted_BetaBinom_fixdispersion_mix(GenericLikelihoodModel): + def __init__(self, endog, exog, tau, weights, exposure, tumor_prop, **kwds): + super(Weighted_BetaBinom_fixdispersion_mix, self).__init__(endog, exog, **kwds) + self.tau = tau + self.weights = weights + self.exposure = exposure + self.tumor_prop = tumor_prop + # + def nloglikeobs(self, params): + a = (self.exog @ params * self.tumor_prop + 0.5 * (1 - self.tumor_prop)) * self.tau + b = ((1 - self.exog @ params) * self.tumor_prop + 0.5 * (1 - self.tumor_prop)) * self.tau + llf = scipy.stats.betabinom.logpmf(self.endog, self.exposure, a, b) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = 0.1 * np.ones(self.nparams) + + return super(Weighted_BetaBinom_fixdispersion_mix, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) + + +class BAF_Binom(GenericLikelihoodModel): + """ + Binomial model endog ~ BetaBin(exposure, tau * p, tau * (1 - p)), where p = exog @ params[:-1] and tau = params[-1]. + This function fits the BetaBin params when samples are weighted by weights: max_{params} \sum_{s} weights_s * log P(endog_s | exog_s; params) + + Attributes + ---------- + endog : array, (n_samples,) + Y values. + + exog : array, (n_samples, n_features) + Design matrix. + + weights : array, (n_samples,) + Sample weights. + + exposure : array, (n_samples,) + Total number of trials. In BAF case, this is the total number of SNP-covering UMIs. + """ + def __init__(self, endog, exog, weights, exposure, offset, scaling, **kwds): + super(BAF_Binom, self).__init__(endog, exog, **kwds) + self.weights = weights + self.exposure = exposure + self.offset = offset + self.scaling = scaling + # + def nloglikeobs(self, params): + linear_term = self.exog @ params + p = self.scaling / (1 + np.exp(-linear_term + self.offset)) + llf = scipy.stats.binom.logpmf(self.endog, self.exposure, p) + neg_sum_llf = -llf.dot(self.weights) + return neg_sum_llf + # + def fit(self, start_params=None, maxiter=10000, maxfun=5000, **kwds): + if start_params is None: + if hasattr(self, 'start_params'): + start_params = self.start_params + else: + start_params = 0.5 / np.sum(self.exog.shape[1]) * np.ones(self.nparams) + return super(BAF_Binom, self).fit(start_params=start_params, + maxiter=maxiter, maxfun=maxfun, + **kwds) \ No newline at end of file diff --git a/src/calicost/utils_hmm.py b/src/calicost/utils_hmm.py new file mode 100644 index 0000000..9c22aaf --- /dev/null +++ b/src/calicost/utils_hmm.py @@ -0,0 +1,1305 @@ +import numpy as np +from numba import njit +import copy +import scipy.special +from tqdm import trange +from sklearn.mixture import GaussianMixture +from calicost.utils_distribution_fitting import * + + +@njit +def np_max_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.max(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.max(arr[i, :]) + return result + + +@njit +def np_max_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.max(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.max(arr[i, :]) + return result + + +@njit +def np_sum_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.sum(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.sum(arr[i, :]) + return result + + +@njit +def np_sum_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.sum(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.sum(arr[i, :]) + return result + + +@njit +def np_mean_ax_squeeze(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros(arr.shape[1]) + for i in range(len(result)): + result[i] = np.mean(arr[:, i]) + else: + result = np.empty(arr.shape[0]) + for i in range(len(result)): + result[i] = np.mean(arr[i, :]) + return result + +@njit +def np_mean_ax_keep(arr, axis=0): + assert arr.ndim == 2 + assert axis in [0, 1] + if axis == 0: + result = np.zeros( (1, arr.shape[1]) ) + for i in range(result.shape[1]): + result[:, i] = np.mean(arr[:, i]) + else: + result = np.zeros( (arr.shape[0], 1) ) + for i in range(result.shape[0]): + result[i, :] = np.mean(arr[i, :]) + return result + + +@njit +def mylogsumexp(a): + # get max + a_max = np.max(a) + if (np.isinf(a_max)): + return a_max + # exponential + tmp = np.exp(a - a_max) + # summation + s = np.sum(tmp) + s = np.log(s) + return s + a_max + + +@njit +def mylogsumexp_ax_keep(a, axis): + # get max + a_max = np_max_ax_keep(a, axis=axis) + # if a_max.ndim > 0: + # a_max[~np.isfinite(a_max)] = 0 + # elif not np.isfinite(a_max): + # a_max = 0 + # exponential + tmp = np.exp(a - a_max) + # summation + s = np_sum_ax_keep(tmp, axis=axis) + s = np.log(s) + return s + a_max + + +def construct_unique_matrix(obs_count, total_count): + """ + Attributes + ---------- + allele_count : array, shape (n_observations, n_spots) + Observed A allele counts per SNP per spot. + + total_bb_RD : array, shape (n_observations, n_spots) + Total SNP-covering reads per SNP per spot. + """ + n_obs = obs_count.shape[0] + n_spots = obs_count.shape[1] + unique_values = [] + mapping_matrices = [] + for s in range(n_spots): + if total_count.dtype == int: + pairs = np.unique( np.vstack([obs_count[:,s], total_count[:,s]]).T, axis=0 ) + else: + pairs = np.unique( np.vstack([obs_count[:,s], total_count[:,s]]).T.round(decimals=4), axis=0 ) + unique_values.append( pairs ) + pair_index = {(pairs[i,0], pairs[i,1]):i for i in range(pairs.shape[0])} + # construct mapping matrix + mat_row = np.arange(n_obs) + mat_col = np.zeros(n_obs, dtype=int) + for i in range(n_obs): + if total_count.dtype == int: + tmpidx = pair_index[(obs_count[i,s], total_count[i,s])] + else: + tmpidx = pair_index[(obs_count[i,s], total_count[i,s].round(decimals=4))] + mat_col[i] = tmpidx + mapping_matrices.append( scipy.sparse.csr_matrix((np.ones(len(mat_row)), (mat_row, mat_col) )) ) + return unique_values, mapping_matrices + + +def initialization_by_gmm(n_states, X, base_nb_mean, total_bb_RD, params, random_state=None, in_log_space=True, only_minor=True, min_binom_prob=0.1, max_binom_prob=0.9): + # prepare gmm input of RDR and BAF separately + X_gmm_rdr = None + X_gmm_baf = None + if "m" in params: + if in_log_space: + X_gmm_rdr = np.vstack([ np.log(X[:,0,s]/base_nb_mean[:,s]) for s in range(X.shape[2]) ]).T + offset = np.mean(X_gmm_rdr[(~np.isnan(X_gmm_rdr)) & (~np.isinf(X_gmm_rdr))]) + normalizetomax1 = np.max(X_gmm_rdr[(~np.isnan(X_gmm_rdr)) & (~np.isinf(X_gmm_rdr))]) - np.min(X_gmm_rdr[(~np.isnan(X_gmm_rdr)) & (~np.isinf(X_gmm_rdr))]) + X_gmm_rdr = (X_gmm_rdr - offset) / normalizetomax1 + else: + X_gmm_rdr = np.vstack([ X[:,0,s]/base_nb_mean[:,s] for s in range(X.shape[2]) ]).T + offset = 0 + normalizetomax1 = np.max(X_gmm_rdr[(~np.isnan(X_gmm_rdr)) & (~np.isinf(X_gmm_rdr))]) + X_gmm_rdr = (X_gmm_rdr - offset) / normalizetomax1 + if "p" in params: + X_gmm_baf = np.vstack([ X[:,1,s] / total_bb_RD[:,s] for s in range(X.shape[2]) ]).T + X_gmm_baf[X_gmm_baf < min_binom_prob] = min_binom_prob + X_gmm_baf[X_gmm_baf > max_binom_prob] = max_binom_prob + # combine RDR and BAF + if ("m" in params) and ("p" in params): + # indexes = np.where(X_gmm_baf[:,0] > 0.5)[0] + # X_gmm_baf[indexes,:] = 1 - X_gmm_baf[indexes,:] + X_gmm = np.hstack([X_gmm_rdr, X_gmm_baf]) + elif "m" in params: + X_gmm = X_gmm_rdr + elif "p" in params: + # indexes = np.where(X_gmm_baf[:,0] > 0.5)[0] + # X_gmm_baf[indexes,:] = 1 - X_gmm_baf[indexes,:] + X_gmm = X_gmm_baf + # deal with NAN + for k in range(X_gmm.shape[1]): + last_idx_notna = -1 + for i in range(X_gmm.shape[0]): + if last_idx_notna >= 0 and np.isnan(X_gmm[i, k]): + X_gmm[i, k] = X_gmm[last_idx_notna, k] + elif not np.isnan(X_gmm[i, k]): + last_idx_notna = i + X_gmm = X_gmm[np.sum(np.isnan(X_gmm), axis=1) == 0, :] + # run GMM + if random_state is None: + gmm = GaussianMixture(n_components=n_states, max_iter=1).fit(X_gmm) + else: + gmm = GaussianMixture(n_components=n_states, max_iter=1, random_state=random_state).fit(X_gmm) + # turn gmm fitted parameters to HMM log_mu and p_binom parameters + if ("m" in params) and ("p" in params): + gmm_log_mu = gmm.means_[:,:X.shape[2]] * normalizetomax1 + offset if in_log_space else np.log(gmm.means_[:,:X.shape[2]] * normalizetomax1 + offset) + gmm_p_binom = gmm.means_[:, X.shape[2]:] + if only_minor: + gmm_p_binom = np.where(gmm_p_binom > 0.5, 1-gmm_p_binom, gmm_p_binom) + elif "m" in params: + gmm_log_mu = gmm.means_ * normalizetomax1 + offset if in_log_space else np.log(gmm.means_[:,:X.shape[2]] * normalizetomax1 + offset) + gmm_p_binom = None + elif "p" in params: + gmm_log_mu = None + gmm_p_binom = gmm.means_ + if only_minor: + gmm_p_binom = np.where(gmm_p_binom > 0.5, 1-gmm_p_binom, gmm_p_binom) + return gmm_log_mu, gmm_p_binom + + +############################################################ +# E step related +############################################################ + +def compute_posterior_obs(log_alpha, log_beta): + ''' + Input + log_alpha: output from forward_lattice_gaussian. size n_states * n_observations. alpha[j, t] = P(o_1, ... o_t, q_t = j | lambda). + log_beta: output from backward_lattice_gaussian. size n_states * n_observations. beta[i, t] = P(o_{t+1}, ..., o_T | q_t = i, lambda). + Output: + log_gamma: size n_states * n_observations. gamma[i,t] = P(q_t = i | O, lambda). gamma[i, t] propto alpha[i,t] * beta[i,t] + ''' + n_states = log_alpha.shape[0] + n_obs = log_alpha.shape[1] + # initial log_gamma + log_gamma = np.zeros((n_states, n_obs)) + # compute log_gamma + # for j in np.arange(n_states): + # for t in np.arange(n_obs): + # log_gamma[j, t] = log_alpha[j, t] + log_beta[j, t] + log_gamma = log_alpha + log_beta + if np.any( np.sum(log_gamma, axis=0) == 0 ): + raise Exception("Sum of posterior probability is zero for some observations!") + log_gamma -= scipy.special.logsumexp(log_gamma, axis=0) + return log_gamma + + +@njit +def compute_posterior_transition_sitewise(log_alpha, log_beta, log_transmat, log_emission): + ''' + Input + log_alpha: output from forward_lattice_gaussian. size n_states * n_observations. alpha[j, t] = P(o_1, ... o_t, q_t = j | lambda). + log_beta: output from backward_lattice_gaussian. size n_states * n_observations. beta[i, t] = P(o_{t+1}, ..., o_T | q_t = i, lambda). + log_transmat: n_states * n_states. Transition probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output: + log_xi: size n_states * n_states * (n_observations-1). xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + ''' + n_states = int(log_alpha.shape[0] / 2) + n_obs = log_alpha.shape[1] + # initialize log_xi + log_xi = np.zeros((2*n_states, 2*n_states, n_obs-1)) + # compute log_xi + for i in np.arange(2*n_states): + for j in np.arange(2*n_states): + for t in np.arange(n_obs-1): + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_xi[i, j, t] = log_alpha[i, t] + log_transmat[i - n_states * int(i/n_states), j - n_states * int(j/n_states)] + np.sum(log_emission[j, t+1, :]) + log_beta[j, t+1] + # normalize + for t in np.arange(n_obs-1): + log_xi[:, :, t] -= mylogsumexp(log_xi[:, :, t]) + return log_xi + + +@njit +def compute_posterior_transition_nophasing(log_alpha, log_beta, log_transmat, log_emission): + ''' + Input + log_alpha: output from forward_lattice_gaussian. size n_states * n_observations. alpha[j, t] = P(o_1, ... o_t, q_t = j | lambda). + log_beta: output from backward_lattice_gaussian. size n_states * n_observations. beta[i, t] = P(o_{t+1}, ..., o_T | q_t = i, lambda). + log_transmat: n_states * n_states. Transition probability after log transformation. + log_emission: n_states * n_observations * n_spots. Log probability. + Output: + log_xi: size n_states * n_states * (n_observations-1). xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + ''' + n_states = int(log_alpha.shape[0] / 2) + n_obs = log_alpha.shape[1] + # initialize log_xi + log_xi = np.zeros((n_states, n_states, n_obs-1)) + # compute log_xi + for i in np.arange(n_states): + for j in np.arange(n_states): + for t in np.arange(n_obs-1): + # ??? Theoretically, joint distribution across spots under iid is the prod (or sum) of individual (log) probabilities. + # But adding too many spots may lead to a higher weight of the emission rather then transition prob. + log_xi[i, j, t] = log_alpha[i, t] + log_transmat[i, j] + np.sum(log_emission[j, t+1, :]) + log_beta[j, t+1] + # normalize + for t in np.arange(n_obs-1): + log_xi[:, :, t] -= mylogsumexp(log_xi[:, :, t]) + return log_xi + + +############################################################ +# M step related (HMM phasing) +############################################################ + +@njit +def update_startprob_sitewise(lengths, log_gamma): + ''' + Input + lengths: sum of lengths = n_observations. + log_gamma: size 2 * n_states * n_observations. gamma[i,t] = P(q_t = i | O, lambda). + Output + log_startprob: n_states. Start probability after loog transformation. + ''' + n_states = int(log_gamma.shape[0] / 2) + n_obs = log_gamma.shape[1] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the second dimension of log_gamma!" + # indices of the start of sequences, given that the length of each sequence is in lengths + cumlen = 0 + indices_start = [] + for le in lengths: + indices_start.append(cumlen) + cumlen += le + indices_start = np.array(indices_start) + # initialize log_startprob + log_startprob = np.zeros(n_states) + # compute log_startprob of 2 * n_states + log_startprob = mylogsumexp_ax_keep(log_gamma[:, indices_start], axis=1) + # merge (CNV state, phase A) and (CNV state, phase B) + log_startprob = log_startprob.flatten().reshape(2,-1) + log_startprob = mylogsumexp_ax_keep(log_startprob, axis=0) + # normalize such that startprob sums to 1 + log_startprob -= mylogsumexp(log_startprob) + return log_startprob + + +def update_transition_sitewise(log_xi, is_diag=False): + ''' + Input + log_xi: size (2*n_states) * (2*n_states) * n_observations. xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + Output + log_transmat: n_states * n_states. Transition probability after log transformation. + ''' + n_states = int(log_xi.shape[0] / 2) + n_obs = log_xi.shape[2] + # initialize log_transmat + log_transmat = np.zeros((n_states, n_states)) + for i in np.arange(n_states): + for j in np.arange(n_states): + log_transmat[i, j] = scipy.special.logsumexp( np.concatenate([log_xi[i, j, :], log_xi[i+n_states, j, :], \ + log_xi[i, j+n_states, :], log_xi[i + n_states, j + n_states, :]]) ) + # row normalize log_transmat + if not is_diag: + for i in np.arange(n_states): + rowsum = scipy.special.logsumexp(log_transmat[i, :]) + log_transmat[i, :] -= rowsum + else: + diagsum = scipy.special.logsumexp(np.diag(log_transmat)) + totalsum = scipy.special.logsumexp(log_transmat) + t = diagsum - totalsum + rest = np.log( (1 - np.exp(t)) / (n_states-1) ) + log_transmat = np.ones(log_transmat.shape) * rest + np.fill_diagonal(log_transmat, t) + return log_transmat + + +def update_emission_params_nb_sitewise_uniqvalues(unique_values, mapping_matrices, log_gamma, base_nb_mean, alphas, \ + start_log_mu=None, fix_NB_dispersion=False, shared_NB_dispersion=False, min_log_rdr=-2, max_log_rdr=2, min_estep_weight=0.1): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = len(unique_values) + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_log_mu = copy.copy(start_log_mu) if not start_log_mu is None else np.zeros((n_states, n_spots)) + new_alphas = copy.copy(alphas) + # expression signal by NB distribution + if fix_NB_dispersion: + new_log_mu = np.zeros((n_states, n_spots)) + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = sm.GLM(unique_values[s][idx_nonzero,0], np.ones(len(idx_nonzero)).reshape(-1,1), \ + family=sm.families.NegativeBinomial(alpha=alphas[i,s]), \ + exposure=unique_values[s][idx_nonzero,1], var_weights=tmp[i,idx_nonzero]+tmp[i+n_states,idx_nonzero]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array([start_log_mu[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if -model.loglike(res.params) < -model.loglike(res2.params) else res2.params[0] + else: + if not shared_NB_dispersion: + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = Weighted_NegativeBinomial(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero]+tmp[i+n_states,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1], \ + penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + new_alphas[i, s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_log_mu[i, s]], [alphas[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_alphas[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + for s in range(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile(unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile(unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_weights = np.concatenate([ tmp[i,idx_nonzero] + tmp[i+n_states,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= min_estep_weight ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + model = Weighted_NegativeBinomial(y, features, weights=weights, exposure=exposure) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_alphas[:,:] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_log_mu[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * alphas[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_alphas[:,:] = res2.params[-1] + new_log_mu[new_log_mu > max_log_rdr] = max_log_rdr + new_log_mu[new_log_mu < min_log_rdr] = min_log_rdr + return new_log_mu, new_alphas + + +def update_emission_params_nb_sitewise_uniqvalues_mix(unique_values, mapping_matrices, log_gamma, base_nb_mean, alphas, tumor_prop, \ + start_log_mu=None, fix_NB_dispersion=False, shared_NB_dispersion=False, min_log_rdr=-2, max_log_rdr=2): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = len(unique_values) + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_log_mu = copy.copy(start_log_mu) if not start_log_mu is None else np.zeros((n_states, n_spots)) + new_alphas = copy.copy(alphas) + # expression signal by NB distribution + if fix_NB_dispersion: + new_log_mu = np.zeros((n_states, n_spots)) + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = sm.GLM(unique_values[s][idx_nonzero,0], np.ones(len(idx_nonzero)).reshape(-1,1), \ + family=sm.families.NegativeBinomial(alpha=alphas[i,s]), \ + exposure=unique_values[s][idx_nonzero,1], var_weights=tmp[i,idx_nonzero]+tmp[i+n_states,idx_nonzero]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array([start_log_mu[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if -model.loglike(res.params) < -model.loglike(res2.params) else res2.params[0] + else: + if not shared_NB_dispersion: + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + model = Weighted_NegativeBinomial_mix(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero]+tmp[i+n_states,idx_nonzero], exposure=unique_values[s][idx_nonzero,1], \ + tumor_prop=this_tp) + # tumor_prop=tumor_prop[s], penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + new_alphas[i, s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_log_mu[i, s]], [alphas[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_alphas[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + tp = [] + for s in range(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile(unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile(unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_tp = np.tile( (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero], n_states) + assert np.all(this_tp < 1+1e-4) + this_weights = np.concatenate([ tmp[i,idx_nonzero] + tmp[i+n_states,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + tp.append( this_tp[idx_row_posweight] ) + # tp.append( tumor_prop[s] * np.ones(len(idx_row_posweight)) ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + tp = np.concatenate(tp) + model = Weighted_NegativeBinomial_mix(y, features, weights=weights, exposure=exposure, tumor_prop=tp, penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_alphas[:,:] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_log_mu[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * alphas[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_alphas[:,:] = res2.params[-1] + new_log_mu[new_log_mu > max_log_rdr] = max_log_rdr + new_log_mu[new_log_mu < min_log_rdr] = min_log_rdr + return new_log_mu, new_alphas + + +def update_emission_params_bb_sitewise_uniqvalues(unique_values, mapping_matrices, log_gamma, total_bb_RD, taus, \ + start_p_binom=None, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + percent_threshold=0.99, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = len(unique_values) + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_p_binom = copy.copy(start_p_binom) if not start_p_binom is None else np.ones((n_states, n_spots)) * 0.5 + new_taus = copy.copy(taus) + if fix_BB_dispersion: + for s in np.arange(len(unique_values)): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) + np.sum(tmp[i+n_states,idx_nonzero]) >= 0.1: + model = Weighted_BetaBinom_fixdispersion(np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + taus[i,s], \ + weights=np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]), \ + exposure=np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]) ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array(start_p_binom[i, s]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + else: + if not shared_BB_dispersion: + for s in np.arange(len(unique_values)): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) + np.sum(tmp[i+n_states,idx_nonzero]) >= 0.1: + model = Weighted_BetaBinom(np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + weights=np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]), \ + exposure=np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]) ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + new_taus[i, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_p_binom[i, s]], [taus[i, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_taus[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + for s in np.arange(len(unique_values)): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile( np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]), n_states) + this_y = np.tile( np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_weights = np.concatenate([ np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]) for i in range(n_states) ]) + this_features = np.zeros((2*n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*2*len(idx_nonzero)):((i+1)*2*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + model = Weighted_BetaBinom(y, features, weights=weights, exposure=exposure) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_taus[:,:] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_p_binom[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * taus[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_taus[:,:] = res2.params[-1] + new_p_binom[new_p_binom < min_binom_prob] = min_binom_prob + new_p_binom[new_p_binom > max_binom_prob] = max_binom_prob + return new_p_binom, new_taus + + +def update_emission_params_bb_sitewise_uniqvalues_mix(unique_values, mapping_matrices, log_gamma, total_bb_RD, taus, tumor_prop, \ + start_p_binom=None, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + percent_threshold=0.99, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (2*n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = len(unique_values) + n_states = int(log_gamma.shape[0] / 2) + gamma = np.exp(log_gamma) + # initialization + new_p_binom = copy.copy(start_p_binom) if not start_p_binom is None else np.ones((n_states, n_spots)) * 0.5 + new_taus = copy.copy(taus) + if fix_BB_dispersion: + for s in np.arange(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) + np.sum(tmp[i+n_states,idx_nonzero]) >= 0.1: + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + assert np.all(this_tp < 1+1e-4) + model = Weighted_BetaBinom_fixdispersion_mix(np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + taus[i,s], \ + weights=np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]), \ + exposure=np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]), \ + tumor_prop=this_tp) + # tumor_prop=tumor_prop[s] ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array(start_p_binom[i, s]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + else: + if not shared_BB_dispersion: + for s in np.arange(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) + np.sum(tmp[i+n_states,idx_nonzero]) >= 0.1: + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + assert np.all(this_tp < 1+1e-4) + model = Weighted_BetaBinom_mix(np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), \ + np.ones(2*len(idx_nonzero)).reshape(-1,1), \ + weights=np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]), \ + exposure=np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]),\ + tumor_prop=this_tp) + # tumor_prop=tumor_prop ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + new_taus[i, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_p_binom[i, s]], [taus[i, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_taus[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + tp = [] + for s in np.arange(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile( np.append(unique_values[s][idx_nonzero,1], unique_values[s][idx_nonzero,1]), n_states) + this_y = np.tile( np.append(unique_values[s][idx_nonzero,0], unique_values[s][idx_nonzero,1]-unique_values[s][idx_nonzero,0]), n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_tp = np.tile( (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero], n_states) + assert np.all(this_tp < 1+1e-4) + this_weights = np.concatenate([ np.append(tmp[i,idx_nonzero], tmp[i+n_states,idx_nonzero]) for i in range(n_states) ]) + this_features = np.zeros((2*n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*2*len(idx_nonzero)):((i+1)*2*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + tp.append( this_tp[idx_row_posweight] ) + # tp.append( tumor_prop[s] * np.ones(len(idx_row_posweight)) ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + tp = np.concatenate(tp) + model = Weighted_BetaBinom_mix(y, features, weights=weights, exposure=exposure, tumor_prop=tp) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_taus[:,:] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_p_binom[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * taus[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_taus[:,:] = res2.params[-1] + new_p_binom[new_p_binom < min_binom_prob] = min_binom_prob + new_p_binom[new_p_binom > max_binom_prob] = max_binom_prob + return new_p_binom, new_taus + + +############################################################ +# M step related (no phasing) +############################################################ +@njit +def update_startprob_nophasing(lengths, log_gamma): + ''' + Input + lengths: sum of lengths = n_observations. + log_gamma: size n_states * n_observations. gamma[i,t] = P(q_t = i | O, lambda). + Output + log_startprob: n_states. Start probability after loog transformation. + ''' + n_states = log_gamma.shape[0] + n_obs = log_gamma.shape[1] + assert np.sum(lengths) == n_obs, "Sum of lengths must be equal to the second dimension of log_gamma!" + # indices of the start of sequences, given that the length of each sequence is in lengths + cumlen = 0 + indices_start = [] + for le in lengths: + indices_start.append(cumlen) + cumlen += le + indices_start = np.array(indices_start) + # initialize log_startprob + log_startprob = np.zeros(n_states) + # compute log_startprob of n_states + log_startprob = mylogsumexp_ax_keep(log_gamma[:, indices_start], axis=1) + # normalize such that startprob sums to 1 + log_startprob -= mylogsumexp(log_startprob) + return log_startprob + + +def update_transition_nophasing(log_xi, is_diag=False): + ''' + Input + log_xi: size (n_states) * (n_states) * n_observations. xi[i,j,t] = P(q_t=i, q_{t+1}=j | O, lambda) + Output + log_transmat: n_states * n_states. Transition probability after log transformation. + ''' + n_states = log_xi.shape[0] + n_obs = log_xi.shape[2] + # initialize log_transmat + log_transmat = np.zeros((n_states, n_states)) + for i in np.arange(n_states): + for j in np.arange(n_states): + log_transmat[i, j] = scipy.special.logsumexp( log_xi[i, j, :] ) + # row normalize log_transmat + if not is_diag: + for i in np.arange(n_states): + rowsum = scipy.special.logsumexp(log_transmat[i, :]) + log_transmat[i, :] -= rowsum + else: + diagsum = scipy.special.logsumexp(np.diag(log_transmat)) + totalsum = scipy.special.logsumexp(log_transmat) + t = diagsum - totalsum + rest = np.log( (1 - np.exp(t)) / (n_states-1) ) + log_transmat = np.ones(log_transmat.shape) * rest + np.fill_diagonal(log_transmat, t) + return log_transmat + + +def update_emission_params_nb_nophasing_uniqvalues(unique_values, mapping_matrices, log_gamma, alphas, \ + start_log_mu=None, fix_NB_dispersion=False, shared_NB_dispersion=False, min_log_rdr=-2, max_log_rdr=2): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = len(unique_values) + n_states = log_gamma.shape[0] + gamma = np.exp(log_gamma) + # initialization + new_log_mu = copy.copy(start_log_mu) if not start_log_mu is None else np.zeros((n_states, n_spots)) + new_alphas = copy.copy(alphas) + # expression signal by NB distribution + if fix_NB_dispersion: + new_log_mu = np.zeros((n_states, n_spots)) + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = sm.GLM(unique_values[s][idx_nonzero,0], np.ones(len(idx_nonzero)).reshape(-1,1), \ + family=sm.families.NegativeBinomial(alpha=alphas[i,s]), \ + exposure=unique_values[s][idx_nonzero,1], var_weights=tmp[i,idx_nonzero]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array([start_log_mu[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if -model.loglike(res.params) < -model.loglike(res2.params) else res2.params[0] + else: + if not shared_NB_dispersion: + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = Weighted_NegativeBinomial(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1], \ + penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + new_alphas[i, s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_log_mu[i, s]], [alphas[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_alphas[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + for s in range(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile(unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile(unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_weights = np.concatenate([ tmp[i,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + model = Weighted_NegativeBinomial(y, features, weights=weights, exposure=exposure) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_alphas[:,:] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_log_mu[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * alphas[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_alphas[:,:] = res2.params[-1] + new_log_mu[new_log_mu > max_log_rdr] = max_log_rdr + new_log_mu[new_log_mu < min_log_rdr] = min_log_rdr + return new_log_mu, new_alphas + + +def update_emission_params_nb_nophasing_uniqvalues_mix(unique_values, mapping_matrices, log_gamma, alphas, tumor_prop, \ + start_log_mu=None, fix_NB_dispersion=False, shared_NB_dispersion=False, min_log_rdr=-2, max_log_rdr=2): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (n_states, n_observations) + Posterior probability of observing each state at each observation time. + + base_nb_mean : array, shape (n_observations, n_spots) + Mean expression under diploid state. + """ + n_spots = len(unique_values) + n_states = log_gamma.shape[0] + gamma = np.exp(log_gamma) + # initialization + new_log_mu = copy.copy(start_log_mu) if not start_log_mu is None else np.zeros((n_states, n_spots)) + new_alphas = copy.copy(alphas) + # expression signal by NB distribution + if fix_NB_dispersion: + new_log_mu = np.zeros((n_states, n_spots)) + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + model = sm.GLM(unique_values[s][idx_nonzero,0], np.ones(len(idx_nonzero)).reshape(-1,1), \ + family=sm.families.NegativeBinomial(alpha=alphas[i,s]), \ + exposure=unique_values[s][idx_nonzero,1], var_weights=tmp[i,idx_nonzero]) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array([start_log_mu[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if -model.loglike(res.params) < -model.loglike(res2.params) else res2.params[0] + else: + if not shared_NB_dispersion: + for s in range(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + model = Weighted_NegativeBinomial_mix(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero], exposure=unique_values[s][idx_nonzero,1], \ + tumor_prop=this_tp) + # tumor_prop=tumor_prop[s], penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] + new_alphas[i, s] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_log_mu[i, s]], [alphas[i, s]]), xtol=1e-4, ftol=1e-4) + new_log_mu[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_alphas[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + tp = [] + for s in range(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile(unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile(unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_tp = np.tile( (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero], n_states) + assert np.all(this_tp < 1 + 1e-4) + this_weights = np.concatenate([ tmp[i,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + tp.append( this_tp[idx_row_posweight] ) + # tp.append( tumor_prop[s] * np.ones(len(idx_row_posweight)) ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + tp = np.concatenate(tp) + model = Weighted_NegativeBinomial_mix(y, features, weights=weights, exposure=exposure, tumor_prop=tp, penalty=0) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_alphas[:,:] = res.params[-1] + if not (start_log_mu is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_log_mu[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * alphas[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_log_mu[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_alphas[:,:] = res2.params[-1] + new_log_mu[new_log_mu > max_log_rdr] = max_log_rdr + new_log_mu[new_log_mu < min_log_rdr] = min_log_rdr + return new_log_mu, new_alphas + + +def update_emission_params_bb_nophasing_uniqvalues(unique_values, mapping_matrices, log_gamma, taus, \ + start_p_binom=None, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + percent_threshold=0.99, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = len(unique_values) + n_states = log_gamma.shape[0] + gamma = np.exp(log_gamma) + # initialization + new_p_binom = copy.copy(start_p_binom) if not start_p_binom is None else np.ones((n_states, n_spots)) * 0.5 + new_taus = copy.copy(taus) + if fix_BB_dispersion: + for s in np.arange(len(unique_values)): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) >= 0.1: + model = Weighted_BetaBinom_fixdispersion(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + taus[i,s], \ + weights=tmp[i,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1] ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array(start_p_binom[i, s]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + else: + if not shared_BB_dispersion: + for s in np.arange(len(unique_values)): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) >= 0.1: + model = Weighted_BetaBinom(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1] ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + new_taus[i, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_p_binom[i, s]], [taus[i, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_taus[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + for s in np.arange(len(unique_values)): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile( unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile( unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_weights = np.concatenate([ tmp[i,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + model = Weighted_BetaBinom(y, features, weights=weights, exposure=exposure) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_taus[:,:] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_p_binom[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * taus[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_taus[:,:] = res2.params[-1] + + new_p_binom[new_p_binom < min_binom_prob] = min_binom_prob + new_p_binom[new_p_binom > max_binom_prob] = max_binom_prob + return new_p_binom, new_taus + + +def update_emission_params_bb_nophasing_uniqvalues_mix(unique_values, mapping_matrices, log_gamma, taus, tumor_prop, \ + start_p_binom=None, fix_BB_dispersion=False, shared_BB_dispersion=False, \ + percent_threshold=0.99, min_binom_prob=0.01, max_binom_prob=0.99): + """ + Attributes + ---------- + X : array, shape (n_observations, n_components, n_spots) + Observed expression UMI count and allele frequency UMI count. + + log_gamma : array, (n_states, n_observations) + Posterior probability of observing each state at each observation time. + + total_bb_RD : array, shape (n_observations, n_spots) + SNP-covering reads for both REF and ALT across genes along genome. + """ + n_spots = len(unique_values) + n_states = log_gamma.shape[0] + gamma = np.exp(log_gamma) + # initialization + new_p_binom = copy.copy(start_p_binom) if not start_p_binom is None else np.ones((n_states, n_spots)) * 0.5 + new_taus = copy.copy(taus) + if fix_BB_dispersion: + for s in np.arange(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) >= 0.1: + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + assert np.all(this_tp < 1 + 1e-4) + model = Weighted_BetaBinom_fixdispersion_mix(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + taus[i,s], \ + weights=tmp[i,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1], \ + tumor_prop=this_tp) + # tumor_prop=tumor_prop[s] ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.array(start_p_binom[i, s]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + else: + if not shared_BB_dispersion: + for s in np.arange(n_spots): + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + for i in range(n_states): + # only optimize for BAF only when the posterior probability >= 0.1 (at least 1 SNP is under this state) + if np.sum(tmp[i,idx_nonzero]) >= 0.1: + this_tp = (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero] + assert np.all(this_tp < 1 + 1e-4) + model = Weighted_BetaBinom_mix(unique_values[s][idx_nonzero,0], \ + np.ones(len(idx_nonzero)).reshape(-1,1), \ + weights=tmp[i,idx_nonzero], \ + exposure=unique_values[s][idx_nonzero,1], \ + tumor_prop=this_tp) + # tumor_prop=tumor_prop[s] ) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] + new_taus[i, s] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.append([start_p_binom[i, s]], [taus[i, s]]), xtol=1e-4, ftol=1e-4) + new_p_binom[i, s] = res.params[0] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[0] + new_taus[i, s] = res.params[-1] if model.nloglikeobs(res.params) < model.nloglikeobs(res2.params) else res2.params[-1] + else: + exposure = [] + y = [] + weights = [] + features = [] + state_posweights = [] + tp = [] + for s in np.arange(n_spots): + idx_nonzero = np.where(unique_values[s][:,1] > 0)[0] + this_exposure = np.tile( unique_values[s][idx_nonzero,1], n_states) + this_y = np.tile( unique_values[s][idx_nonzero,0], n_states) + tmp = (scipy.sparse.csr_matrix(gamma) @ mapping_matrices[s]).A + this_tp = np.tile( (mapping_matrices[s].T @ tumor_prop[:,s])[idx_nonzero] / (mapping_matrices[s].T @ np.ones(tumor_prop.shape[0]))[idx_nonzero], n_states) + assert np.all(this_tp < 1 + 1e-4) + this_weights = np.concatenate([ tmp[i,idx_nonzero] for i in range(n_states) ]) + this_features = np.zeros((n_states*len(idx_nonzero), n_states)) + for i in np.arange(n_states): + this_features[(i*len(idx_nonzero)):((i+1)*len(idx_nonzero)), i] = 1 + # only optimize for states where at least 1 SNP belongs to + idx_state_posweight = np.array([ i for i in range(this_features.shape[1]) if np.sum(this_weights[this_features[:,i]==1]) >= 0.1 ]) + idx_row_posweight = np.concatenate([ np.where(this_features[:,k]==1)[0] for k in idx_state_posweight ]) + y.append( this_y[idx_row_posweight] ) + exposure.append( this_exposure[idx_row_posweight] ) + weights.append( this_weights[idx_row_posweight] ) + features.append( this_features[idx_row_posweight, :][:, idx_state_posweight] ) + state_posweights.append( idx_state_posweight ) + tp.append( this_tp[idx_row_posweight] ) + # tp.append( tumor_prop[s] * np.ones(len(idx_row_posweight)) ) + exposure = np.concatenate(exposure) + y = np.concatenate(y) + weights = np.concatenate(weights) + features = scipy.linalg.block_diag(*features) + tp = np.concatenate(tp) + model = Weighted_BetaBinom_mix(y, features, weights=weights, exposure=exposure, tumor_prop=tp) + res = model.fit(disp=0, maxiter=1500, xtol=1e-4, ftol=1e-4) + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res.params[l1:l2] + if res.params[-1] > 0: + new_taus[:,:] = res.params[-1] + if not (start_p_binom is None): + res2 = model.fit(disp=0, maxiter=1500, start_params=np.concatenate([start_p_binom[idx_state_posweight,s] for s,idx_state_posweight in enumerate(state_posweights)] + [np.ones(1) * taus[0,s]]), xtol=1e-4, ftol=1e-4) + if model.nloglikeobs(res2.params) < model.nloglikeobs(res.params): + for s,idx_state_posweight in enumerate(state_posweights): + l1 = int( np.sum([len(x) for x in state_posweights[:s]]) ) + l2 = int( np.sum([len(x) for x in state_posweights[:(s+1)]]) ) + new_p_binom[idx_state_posweight, s] = res2.params[l1:l2] + if res2.params[-1] > 0: + new_taus[:,:] = res2.params[-1] + new_p_binom[new_p_binom < min_binom_prob] = min_binom_prob + new_p_binom[new_p_binom > max_binom_prob] = max_binom_prob + return new_p_binom, new_taus + diff --git a/src/calicost/utils_hmrf.py b/src/calicost/utils_hmrf.py new file mode 100644 index 0000000..bee9f42 --- /dev/null +++ b/src/calicost/utils_hmrf.py @@ -0,0 +1,704 @@ +import numpy as np +import pandas as pd +import scipy.special +import scipy.sparse +from sklearn.neighbors import kneighbors_graph +from sklearn.neighbors import NearestNeighbors +import copy +import anndata +import scanpy as sc +from statsmodels.tools.sm_exceptions import ValueWarning +from calicost.utils_distribution_fitting import * + + +def compute_adjacency_mat(coords, unit_xsquared=9, unit_ysquared=3): + # pairwise distance + x_dist = coords[:,0][None,:] - coords[:,0][:,None] + y_dist = coords[:,1][None,:] - coords[:,1][:,None] + pairwise_squared_dist = x_dist**2 * unit_xsquared + y_dist**2 * unit_ysquared + # adjacency + A = np.zeros( (coords.shape[0], coords.shape[0]), dtype=np.int8 ) + for i in range(coords.shape[0]): + indexes = np.where(pairwise_squared_dist[i,:] <= unit_xsquared + unit_ysquared)[0] + indexes = np.array([j for j in indexes if j != i]) + if len(indexes) > 0: + A[i, indexes] = 1 + A = scipy.sparse.csr_matrix(A) + return A + + +def compute_adjacency_mat_v2(coords, unit_xsquared=9, unit_ysquared=3, ratio=1): + # pairwise distance + x_dist = coords[:,0][None,:] - coords[:,0][:,None] + y_dist = coords[:,1][None,:] - coords[:,1][:,None] + pairwise_squared_dist = x_dist**2 * unit_xsquared + y_dist**2 * unit_ysquared + # adjacency + A = np.zeros( (coords.shape[0], coords.shape[0]), dtype=np.int8 ) + for i in range(coords.shape[0]): + indexes = np.where(pairwise_squared_dist[i,:] <= ratio * (unit_xsquared + unit_ysquared))[0] + indexes = np.array([j for j in indexes if j != i]) + if len(indexes) > 0: + A[i, indexes] = 1 + A = scipy.sparse.csr_matrix(A) + return A + + +def compute_weighted_adjacency(coords, unit_xsquared=9, unit_ysquared=3, bandwidth=12, decay=5): + # pairwise distance + x_dist = coords[:,0][None,:] - coords[:,0][:,None] + y_dist = coords[:,1][None,:] - coords[:,1][:,None] + pairwise_squared_dist = x_dist**2 * unit_xsquared + y_dist**2 * unit_ysquared + kern = np.exp(-(pairwise_squared_dist / bandwidth)**decay) + # adjacency + A = np.zeros( (coords.shape[0], coords.shape[0]) ) + for i in range(coords.shape[0]): + indexes = np.where(kern[i,:] > 1e-4)[0] + indexes = np.array([j for j in indexes if j != i]) + if len(indexes) > 0: + A[i, indexes] = kern[i,indexes] + A = scipy.sparse.csr_matrix(A) + return A + + +def choose_adjacency_by_readcounts(coords, single_total_bb_RD, maxspots_pooling=7, unit_xsquared=9, unit_ysquared=3): +# def choose_adjacency_by_readcounts(coords, single_total_bb_RD, count_threshold=4000, unit_xsquared=9, unit_ysquared=3): + # XXX: change from count_threshold 500 to 3000 + # pairwise distance + x_dist = coords[:,0][None,:] - coords[:,0][:,None] + y_dist = coords[:,1][None,:] - coords[:,1][:,None] + tmp_pairwise_squared_dist = x_dist**2 * unit_xsquared + y_dist**2 * unit_ysquared + np.fill_diagonal(tmp_pairwise_squared_dist, np.max(tmp_pairwise_squared_dist)) + base_ratio = np.median(np.min(tmp_pairwise_squared_dist, axis=0)) / (unit_xsquared + unit_ysquared) + s_ratio = 0 + for ratio in range(0, 10): + smooth_mat = compute_adjacency_mat_v2(coords, unit_xsquared, unit_ysquared, ratio * base_ratio) + smooth_mat.setdiag(1) + if np.median(np.sum(smooth_mat > 0, axis=0).A.flatten()) > maxspots_pooling: + s_ratio = ratio - 1 + break + s_ratio = ratio + smooth_mat = compute_adjacency_mat_v2(coords, unit_xsquared, unit_ysquared, s_ratio * base_ratio) + smooth_mat.setdiag(1) + for bandwidth in np.arange(unit_xsquared + unit_ysquared, 15*(unit_xsquared + unit_ysquared), unit_xsquared + unit_ysquared): + adjacency_mat = compute_weighted_adjacency(coords, unit_xsquared, unit_ysquared, bandwidth=bandwidth) + adjacency_mat.setdiag(1) + adjacency_mat = adjacency_mat - smooth_mat + adjacency_mat[adjacency_mat < 0] = 0 + if np.median(np.sum(adjacency_mat, axis=0).A.flatten()) >= 6: + print(f"bandwidth: {bandwidth}") + break + return smooth_mat, adjacency_mat + + +def choose_adjacency_by_KNN(coords, exp_counts=None, w=1, maxspots_pooling=7): + """ + Compute adjacency matrix for pooling and for HMRF by KNN of pairwise spatial distance + pairwise expression distance. + + Attributes + ---------- + coords : array, shape (n_spots, 2) + Spatial coordinates of spots. + + exp_counts : None or array, shape (n_spots, n_genes) + Expression counts of spots. + + w : float + Weight of spatial distance in computing adjacency matrix. + + maxspots_pooling : int + Number of spots in the adjacency matrix for pooling. + """ + n_spots = coords.shape[0] + + # pairwise expression distance if exp_counts is not None + pair_exp_dist = scipy.sparse.csr_matrix( np.zeros((n_spots,n_spots)) ) + scaling_factor = 1 + if not exp_counts is None: + adata = anndata.AnnData( pd.DataFrame(exp_counts) ) + sc.pp.normalize_total(adata, target_sum=np.median(np.sum(exp_counts.values,axis=1)) ) + sc.pp.log1p(adata) + sc.tl.pca(adata) + pair_exp_dist = scipy.spatial.distance.squareform(scipy.spatial.distance.pdist(adata.obsm["X_pca"])) + # compute the scaling factor to normalize coords such that it has the same sum of variance as PCA + var_coord = np.sum(np.var(coords, axis=0)) + var_pca = np.sum(np.var(adata.obsm["X_pca"], axis=0)) + EPS = 1e-4 + scaling_factor = np.sqrt(var_coord / var_pca) if var_coord > EPS and var_pca > EPS else 1 + + # pairwise spatial distance + pair_spatial_dist = scipy.spatial.distance.squareform(scipy.spatial.distance.pdist(coords / scaling_factor)) + + # adjacency for pooling + smooth_mat = NearestNeighbors(n_neighbors=maxspots_pooling, metric='precomputed').fit(w * pair_spatial_dist + (1-w) * pair_exp_dist).kneighbors_graph() + smooth_mat.setdiag(1) # include self adjacency + + # adjacency for HMRF + adjacency_mat = NearestNeighbors(n_neighbors=maxspots_pooling + 6, metric='precomputed').fit(w * pair_spatial_dist + (1-w) * pair_exp_dist).kneighbors_graph() + adjacency_mat = adjacency_mat - smooth_mat + adjacency_mat[adjacency_mat < 0] = 0 + adjacency_mat.setdiag(1) # include self adjacency + return smooth_mat, adjacency_mat + + +def choose_adjacency_by_readcounts_slidedna(coords, maxspots_pooling=30): + """ + Merge spots such that 95% quantile of read count per SNP per spot exceed count_threshold. + """ + smooth_mat = kneighbors_graph(coords, n_neighbors=maxspots_pooling) + adjacency_mat = kneighbors_graph(coords, n_neighbors=maxspots_pooling + 6) + adjacency_mat = adjacency_mat - smooth_mat + return smooth_mat, adjacency_mat + + +def multislice_adjacency(sample_ids, sample_list, coords, single_total_bb_RD, exp_counts, across_slice_adjacency_mat, construct_adjacency_method, maxspots_pooling, construct_adjacency_w): + adjacency_mat = [] + smooth_mat = [] + for i,sname in enumerate(sample_list): + index = np.where(sample_ids == i)[0] + this_coords = np.array(coords[index,:]) + if construct_adjacency_method == "hexagon": + tmpsmooth_mat, tmpadjacency_mat = choose_adjacency_by_readcounts(this_coords, single_total_bb_RD[:,index], maxspots_pooling=maxspots_pooling) + elif construct_adjacency_method == "KNN": + tmpsmooth_mat, tmpadjacency_mat = choose_adjacency_by_KNN(this_coords, exp_counts.iloc[index,:], w=construct_adjacency_w, maxspots_pooling=maxspots_pooling) + else: + raise("Unknown adjacency construction method") + # tmpsmooth_mat, tmpadjacency_mat = choose_adjacency_by_readcounts_slidedna(this_coords, maxspots_pooling=config["maxspots_pooling"]) + adjacency_mat.append( tmpadjacency_mat.A ) + smooth_mat.append( tmpsmooth_mat.A ) + adjacency_mat = scipy.linalg.block_diag(*adjacency_mat) + adjacency_mat = scipy.sparse.csr_matrix( adjacency_mat ) + if not across_slice_adjacency_mat is None: + adjacency_mat += across_slice_adjacency_mat + smooth_mat = scipy.linalg.block_diag(*smooth_mat) + smooth_mat = scipy.sparse.csr_matrix( smooth_mat ) + return adjacency_mat, smooth_mat + + +def rectangle_initialize_initial_clone(coords, n_clones, random_state=0): + """ + Initialize clone assignment by partition space into p * p blocks (s.t. p * p >= n_clones), and assign each block a clone id. + + Attributes + ---------- + coords : array, shape (n_spots, 2) + 2D coordinates of spots. + + n_clones : int + Number of clones in initialization. + + Returns + ---------- + initial_clone_index : list + A list of n_clones np arrays, each array is the index of spots that belong to one clone. + """ + np.random.seed(random_state) + p = int(np.ceil(np.sqrt(n_clones))) + # partition the range of x and y axes + px = np.random.dirichlet( np.ones(p) * 10 ) + px[-1] += 1e-4 + xrange = [np.percentile(coords[:,0], 5), np.percentile(coords[:,0], 95)] + xboundary = xrange[0] + (xrange[1] - xrange[0]) * np.cumsum(px) + xboundary[-1] = np.max(coords[:,0]) + 1 + xdigit = np.digitize(coords[:,0], xboundary, right=True) + py = np.random.dirichlet( np.ones(p) * 10 ) + py[-1] += 1e-4 + yrange = [np.percentile(coords[:,1], 5), np.percentile(coords[:,1], 95)] + yboundary = yrange[0] + (yrange[1] - yrange[0]) * np.cumsum(py) + yboundary[-1] = np.max(coords[:,1]) + 1 + ydigit = np.digitize(coords[:,1], yboundary, right=True) + block_id = xdigit * p + ydigit + # assigning blocks to clone (note that if sqrt(n_clone) is not an integer, multiple blocks can be assigneed to one clone) + # block_clone_map = np.random.randint(low=0, high=n_clones, size=p**2) + # while len(np.unique(block_clone_map)) < n_clones: + # bc = np.bincount(block_clone_map, minlength=n_clones) + # assert np.any(bc==0) + # block_clone_map[np.where(block_clone_map==np.argmax(bc))[0][0]] = np.where(bc==0)[0][0] + # block_clone_map = {i:block_clone_map[i] for i in range(len(block_clone_map))} + # clone_id = np.array([block_clone_map[i] for i in block_id]) + # initial_clone_index = [np.where(clone_id == i)[0] for i in range(n_clones)] + while True: + block_clone_map = np.random.randint(low=0, high=n_clones, size=p**2) + while len(np.unique(block_clone_map)) < n_clones: + bc = np.bincount(block_clone_map, minlength=n_clones) + assert np.any(bc==0) + block_clone_map[np.where(block_clone_map==np.argmax(bc))[0][0]] = np.where(bc==0)[0][0] + block_clone_map = {i:block_clone_map[i] for i in range(len(block_clone_map))} + clone_id = np.array([block_clone_map[i] for i in block_id]) + initial_clone_index = [np.where(clone_id == i)[0] for i in range(n_clones)] + if np.min([len(x) for x in initial_clone_index]) > 0.2 * coords.shape[0] / n_clones: + break + return initial_clone_index + + +def fixed_rectangle_initialization(coords, x_part, y_part): + # + px = np.linspace(0, 1, x_part+1) + px[-1] += 0.01 + px = px[1:] + xrange = [np.min(coords[:,0]), np.max(coords[:,0])] + xdigit = np.digitize(coords[:,0], xrange[0] + (xrange[1] - xrange[0]) * px, right=True) + # + py = np.linspace(0, 1, y_part+1) + py[-1] += 0.01 + py = py[1:] + yrange = [np.min(coords[:,1]), np.max(coords[:,1])] + ydigit = np.digitize(coords[:,1], yrange[0] + (yrange[1] - yrange[0]) * py, right=True) + # + initial_clone_index = [] + for xid in range(x_part): + for yid in range(y_part): + initial_clone_index.append( np.where((xdigit == xid) & (ydigit == yid))[0] ) + return initial_clone_index + + +def merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index): + n_obs = single_X.shape[0] + n_spots = len(clone_index) + X = np.zeros((n_obs, 2, n_spots)) + base_nb_mean = np.zeros((n_obs, n_spots)) + total_bb_RD = np.zeros((n_obs, n_spots)) + + for k,idx in enumerate(clone_index): + if len(idx) == 0: + continue + X[:,:, k] = np.sum(single_X[:,:,idx], axis=2) + base_nb_mean[:, k] = np.sum(single_base_nb_mean[:, idx], axis=1) + total_bb_RD[:, k] = np.sum(single_total_bb_RD[:, idx], axis=1) + + return X, base_nb_mean, total_bb_RD + + +def rectangle_initialize_initial_clone_mix(coords, n_clones, single_tumor_prop, threshold=0.5, random_state=0, EPS=1e-8): + np.random.seed(random_state) + p = int(np.ceil(np.sqrt(n_clones))) + # partition the range of x and y axes based on tumor spots coordinates + idx_tumor = np.where(single_tumor_prop > threshold)[0] + px = np.random.dirichlet( np.ones(p) * 10 ) + px[-1] -= EPS + xboundary = np.percentile(coords[idx_tumor, 0], 100*np.cumsum(px)) + xboundary[-1] = np.max(coords[:,0]) + 1 + xdigit = np.digitize(coords[:,0], xboundary, right=True) + ydigit = np.zeros(coords.shape[0], dtype=int) + for x in range(p): + idx_tumor = np.where((single_tumor_prop > threshold) & (xdigit==x))[0] + idx_both = np.where(xdigit == x)[0] + py = np.random.dirichlet( np.ones(p) * 10 ) + py[-1] -= EPS + yboundary = np.percentile(coords[idx_tumor, 1], 100*np.cumsum(py)) + yboundary[-1] = np.max(coords[:,1]) + 1 + ydigit[idx_both] = np.digitize(coords[idx_both,1], yboundary, right=True) + block_id = xdigit * p + ydigit + # assigning blocks to clone (note that if sqrt(n_clone) is not an integer, multiple blocks can be assigneed to one clone) + block_clone_map = np.random.randint(low=0, high=n_clones, size=p**2) + while len(np.unique(block_clone_map)) < n_clones: + bc = np.bincount(block_clone_map, minlength=n_clones) + assert np.any(bc==0) + block_clone_map[np.where(block_clone_map==np.argmax(bc))[0][0]] = np.where(bc==0)[0][0] + block_clone_map = {i:block_clone_map[i] for i in range(len(block_clone_map))} + clone_id = np.array([block_clone_map[i] for i in block_id]) + initial_clone_index = [np.where(clone_id == i)[0] for i in range(n_clones)] + return initial_clone_index + + +def fixed_rectangle_initialization_mix(coords, x_part, y_part, single_tumor_prop, threshold=0.5): + idx_tumor = np.where(single_tumor_prop > threshold)[0] + # + px = np.linspace(0, 1, x_part+1) + px[-1] += 0.01 + px = px[1:] + xrange = [np.min(coords[idx_tumor,0]), np.max(coords[idx_tumor,0])] + xdigit = np.digitize(coords[:,0], xrange[0] + (xrange[1] - xrange[0]) * px, right=True) + # + py = np.linspace(0, 1, y_part+1) + py[-1] += 0.01 + py = py[1:] + yrange = [np.min(coords[idx_tumor,1]), np.max(coords[idx_tumor,1])] + ydigit = np.digitize(coords[:,1], yrange[0] + (yrange[1] - yrange[0]) * py, right=True) + # + initial_clone_index = [] + for xid in range(x_part): + for yid in range(y_part): + initial_clone_index.append( np.where((xdigit == xid) & (ydigit == yid))[0] ) + return initial_clone_index + + +def merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop, threshold=0.5): + n_obs = single_X.shape[0] + n_spots = len(clone_index) + X = np.zeros((n_obs, 2, n_spots)) + base_nb_mean = np.zeros((n_obs, n_spots)) + total_bb_RD = np.zeros((n_obs, n_spots)) + tumor_prop = np.zeros(n_spots) + + for k,idx in enumerate(clone_index): + if len(idx) == 0: + continue + idx = idx[np.where(single_tumor_prop[idx] > threshold)[0]] + X[:,:, k] = np.sum(single_X[:,:,idx], axis=2) + base_nb_mean[:, k] = np.sum(single_base_nb_mean[:, idx], axis=1) + total_bb_RD[:, k] = np.sum(single_total_bb_RD[:, idx], axis=1) + tumor_prop[k] = np.mean(single_tumor_prop[idx]) if len(idx) > 0 else 0 + + return X, base_nb_mean, total_bb_RD, tumor_prop + + +def reorder_results(res_combine, posterior, single_tumor_prop): + EPS_BAF = 0.05 + n_spots = posterior.shape[0] + n_obs = res_combine["pred_cnv"].shape[0] + n_states, n_clones = res_combine["new_p_binom"].shape + new_res_combine = copy.copy(res_combine) + new_posterior = copy.copy(posterior) + if single_tumor_prop is None: + # select near-normal clone and set to clone 0 + pred_cnv = res_combine["pred_cnv"] + baf_profiles = np.array([ res_combine["new_p_binom"][pred_cnv[:,c], c] for c in range(n_clones) ]) + cid_normal = np.argmin(np.sum( np.maximum(np.abs(baf_profiles - 0.5)-EPS_BAF, 0), axis=1)) + cid_rest = np.array([c for c in range(n_clones) if c != cid_normal]).astype(int) + reidx = np.append(cid_normal, cid_rest) + map_reidx = {cid:i for i,cid in enumerate(reidx)} + # re-order entries in res_combine + new_res_combine["new_assignment"] = np.array([ map_reidx[c] for c in res_combine["new_assignment"] ]) + new_res_combine["new_log_mu"] = res_combine["new_log_mu"][:, reidx] + new_res_combine["new_alphas"] = res_combine["new_alphas"][:, reidx] + new_res_combine["new_p_binom"] = res_combine["new_p_binom"][:, reidx] + new_res_combine["new_taus"] = res_combine["new_taus"][:, reidx] + new_res_combine["log_gamma"] = res_combine["log_gamma"][:, :, reidx] + new_res_combine["pred_cnv"] = res_combine["pred_cnv"][:, reidx] + new_posterior = new_posterior[:, reidx] + else: + # add normal clone as clone 0 + new_res_combine["new_assignment"] = new_res_combine["new_assignment"] + 1 + new_res_combine["new_log_mu"] = np.hstack([np.zeros((n_states,1)), res_combine["new_log_mu"]]) + new_res_combine["new_alphas"] = np.hstack([np.zeros((n_states,1)), res_combine["new_alphas"]]) + new_res_combine["new_p_binom"] = np.hstack([0.5 * np.ones((n_states,1)), res_combine["new_p_binom"]]) + new_res_combine["new_taus"] = np.hstack([np.zeros((n_states,1)), res_combine["new_taus"]]) + new_res_combine["log_gamma"] = np.dstack([np.zeros((n_states, n_obs, 1)), res_combine["log_gamma"]]) + new_res_combine["pred_cnv"] = np.hstack([np.zeros((n_obs,1), dtype=int), res_combine["pred_cnv"]]) + new_posterior = np.hstack([np.ones((n_spots,1)) * np.nan, posterior]) + return new_res_combine, new_posterior + + +def reorder_results_merged(res, n_obs): + n_clones = int(len(res["pred_cnv"]) / n_obs) + EPS_BAF = 0.05 + pred_cnv = np.array([ res["pred_cnv"][(c*n_obs):(c*n_obs + n_obs)] for c in range(n_clones) ]).T + baf_profiles = np.array([ res["new_p_binom"][pred_cnv[:,c], 0] for c in range(n_clones) ]) + cid_normal = np.argmin(np.sum( np.maximum(np.abs(baf_profiles - 0.5)-EPS_BAF, 0), axis=1)) + cid_rest = np.array([c for c in range(n_clones) if c != cid_normal]) + reidx = np.append(cid_normal, cid_rest) + map_reidx = {cid:i for i,cid in enumerate(reidx)} + # re-order entries in res + new_res = copy.copy(res) + new_res["new_assignment"] = np.array([ map_reidx[c] for c in res["new_assignment"] ]) + new_res["log_gamma"] = np.hstack([ res["log_gamma"][:, (c*n_obs):(c*n_obs + n_obs)] for c in reidx ]) + new_res["pred_cnv"] = np.concatenate([ res["pred_cnv"][(c*n_obs):(c*n_obs + n_obs)] for c in reidx ]) + return new_res + + +def load_hmrf_last_iteration(filename): + allres = dict( np.load(filename, allow_pickle=True) ) + r = allres["num_iterations"] - 1 + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + if "barcodes" in allres.keys(): + res["barcodes"] = allres["barcodes"] + return res + + +def load_hmrf_given_iteration(filename, r): + allres = dict( np.load(filename, allow_pickle=True) ) + res = {"new_log_mu":allres[f"round{r}_new_log_mu"], "new_alphas":allres[f"round{r}_new_alphas"], \ + "new_p_binom":allres[f"round{r}_new_p_binom"], "new_taus":allres[f"round{r}_new_taus"], \ + "new_log_startprob":allres[f"round{r}_new_log_startprob"], "new_log_transmat":allres[f"round{r}_new_log_transmat"], "log_gamma":allres[f"round{r}_log_gamma"], \ + "pred_cnv":allres[f"round{r}_pred_cnv"], "llf":allres[f"round{r}_llf"], "total_llf":allres[f"round{r}_total_llf"], \ + "prev_assignment":allres[f"round{r-1}_assignment"], "new_assignment":allres[f"round{r}_assignment"]} + if "barcodes" in allres.keys(): + res["barcodes"] = allres["barcodes"] + return res + + +def identify_normal_spots(single_X, single_total_bb_RD, new_assignment, pred_cnv, p_binom, min_count, EPS_BAF=0.05, COUNT_QUANTILE=0.05, MIN_TOTAL=10): + """ + Attributes + ---------- + single_X : array, shape (n_obs, 2, n_spots) + Observed transcript counts and B allele count per bin per spot. + + single_total_bb_RD : array, shape (n_obs, n_spots) + Total allele count per bin per spot. + + new_assignment : array, shape (n_spots,) + Clone assignment for each spot. + + pred_cnv : array, shape (n_obs * n_clones) + Copy number states across bins for each clone. + """ + # aggregate counts for each state, and evaluate the betabinomial likelihood given 0.5 + # spots with the highest likelihood are identified as normal spots + n_obs = single_X.shape[0] + n_spots = single_X.shape[2] + n_clones = int(len(pred_cnv) / n_obs) + n_states = p_binom.shape[0] + reshaped_pred_cnv = pred_cnv.reshape((n_obs, n_clones), order='F') + + baf_profiles = p_binom[reshaped_pred_cnv, 0].T + id_nearnormal_clone = np.argmin(np.sum( np.maximum(np.abs(baf_profiles - 0.5)-EPS_BAF, 0), axis=1)) + umi_quantile = np.quantile(np.sum(single_X[:,0,:], axis=0), COUNT_QUANTILE) + + baf_deviations = np.ones(n_spots) + for i in range(n_spots): + if new_assignment[i] == id_nearnormal_clone and np.sum(single_X[:,0,i]) >= umi_quantile: + # enumerate the partition of all clones to aggregate counts, and list the BAF of each partition + this_bafs = [] + for c in range(n_clones): + agg_b_count = np.array([ np.sum(single_X[reshaped_pred_cnv[:,c]==s, 1, i]) for s in range(n_states) ]) + agg_t_count = np.array([ np.sum(single_total_bb_RD[reshaped_pred_cnv[:,c]==s, i]) for s in range(n_states) ]) + this_bafs.append( agg_b_count[agg_t_count>=MIN_TOTAL] / agg_t_count[agg_t_count>=MIN_TOTAL] ) + this_bafs = np.concatenate(this_bafs) + baf_deviations[i] = np.max(np.abs(this_bafs - 0.5)) + + sorted_idx = np.argsort(baf_deviations) + summed_counts = np.cumsum( np.sum(single_X[:,0,sorted_idx], axis=0) ) + n_normal = np.where(summed_counts >= min_count)[0][0] + + return (baf_deviations <= baf_deviations[sorted_idx[n_normal]]) + + +# def identify_loh_per_clone(single_X, new_assignment, pred_cnv, p_binom, normal_candidate, MIN_BAF_DEVIATION_RANGE=[0.25, 0.12], MIN_BINS_PER_STATE=10, MIN_BINS_ALL=50): +# """ +# Attributes +# ---------- +# single_X : array, shape (n_obs, 2, n_spots) +# Observed transcript counts and B allele count per bin per spot. + +# new_assignment : array, shape (n_spots,) +# Clone assignment for each spot. + +# pred_cnv : array, shape (n_obs * n_clones) +# Copy number states across bins for each clone. + +# p_binom : array, shape (n_states, 1) +# Estimated BAF per copy number state (shared across clones). + +# Returns +# ---------- +# loh_states : array +# An array of copy number states that are identified as LOH. + +# is_B_loss : array +# A boolean array indicating whether B allele is lost (alternative A allele is lost). + +# rdr_values : array +# An array of RDR values corresponding to LOH states. +# """ +# n_obs = single_X.shape[0] +# n_clones = int(len(pred_cnv) / n_obs) +# n_states = p_binom.shape[0] +# reshaped_pred_cnv = pred_cnv.reshape((n_obs, n_clones), order='F') +# # clones that have a decent tumor proportion +# # for each clone, if the clones_hightumor-th BAF deviation is large enough +# k_baf_deviation = np.sort( np.abs(p_binom[reshaped_pred_cnv, 0]-0.5), axis=0)[-MIN_BINS_ALL,:] +# clones_hightumor = np.where(k_baf_deviation >= MIN_BAF_DEVIATION_RANGE[1])[0] +# if len(clones_hightumor) == 0: +# clones_hightumor = np.argsort(k_baf_deviation)[-1:] +# if len(clones_hightumor) == n_clones: +# clones_hightumor = np.argsort(k_baf_deviation)[1:] +# print(f"clones with high tumor proportion: {clones_hightumor}") +# # LOH states +# for threshold in np.arange(MIN_BAF_DEVIATION_RANGE[0], MIN_BAF_DEVIATION_RANGE[1]-0.01, -0.01): +# loh_states = np.where( (np.abs(p_binom[:,0] - 0.5) > threshold) & (np.bincount(pred_cnv, minlength=n_states) >= MIN_BINS_PER_STATE) )[0] +# is_B_lost = (p_binom[loh_states,0] < 0.5) +# if np.all([ np.sum(pd.Series(reshaped_pred_cnv[:,c]).isin(loh_states)) >= MIN_BINS_ALL for c in clones_hightumor ]): +# print(f"BAF deviation threshold = {threshold}, LOH states: {loh_states}") +# break +# # RDR values +# # first get the normal baseline expression per spot per bin +# simple_rdr_normal = np.sum(single_X[:, 0, (normal_candidate==True)], axis=1) +# simple_rdr_normal = simple_rdr_normal / np.sum(simple_rdr_normal) +# simple_single_base_nb_mean = simple_rdr_normal.reshape(-1,1) @ np.sum(single_X[:,0,:], axis=0).reshape(1,-1) +# # then aggregate to clones +# clone_index = [np.where(new_assignment == c)[0] for c in range(n_clones)] +# X, base_nb_mean, _ = merge_pseudobulk_by_index(single_X, simple_single_base_nb_mean, np.zeros(simple_single_base_nb_mean.shape), clone_index) +# rdr_values = [] +# for s in loh_states: +# rdr_values.append( np.sum(X[:,0,:][reshaped_pred_cnv==s]) / np.sum(base_nb_mean[reshaped_pred_cnv==s]) ) +# rdr_values = np.array(rdr_values) + +# """ +# Update ideas: why not finding high purity clone and loh states together by varying BAF deviation threshold? +# Current we first identify high purity clone using BAF deviation threshold = 0.15, then identify loh states. +# But we can vary BAF deviation threshold from the large to small, identify high purity clones and loh states based on the same threshold. +# At very large threshold value, there will be no high purity clone, which is unreasonable. +# While lowering the threshold, purity clone(s) will appear, and we terminate once we are able to find one high purity clone. + +# Another update idea: identification of loh states is unaware of RDR. +# We can first find low-copy-number loh states first by thresholding RDR. If we can't find any, increase RDR threshold. +# """ + +# return loh_states, is_B_lost, rdr_values, clones_hightumor + + +def identify_loh_per_clone(single_X, new_assignment, pred_cnv, p_binom, normal_candidate, single_total_bb_RD, MIN_SNPUMI=10, MAX_RDR=1, MIN_BAF_DEVIATION_RANGE=[0.25, 0.12], MIN_BINS_PER_STATE=10, MIN_BINS_ALL=25): + """ + Attributes + ---------- + single_X : array, shape (n_obs, 2, n_spots) + Observed transcript counts and B allele count per bin per spot. + + new_assignment : array, shape (n_spots,) + Clone assignment for each spot. + + pred_cnv : array, shape (n_obs * n_clones) + Copy number states across bins for each clone. + + p_binom : array, shape (n_states, 1) + Estimated BAF per copy number state (shared across clones). + + Returns + ---------- + loh_states : array + An array of copy number states that are identified as LOH. + + is_B_loss : array + A boolean array indicating whether B allele is lost (alternative A allele is lost). + + rdr_values : array + An array of RDR values corresponding to LOH states. + """ + n_obs = single_X.shape[0] + n_clones = int(len(pred_cnv) / n_obs) + n_states = p_binom.shape[0] + reshaped_pred_cnv = pred_cnv.reshape((n_obs, n_clones), order='F') + + # per-state RDR values + # first get the normal baseline expression per spot per bin + simple_rdr_normal = np.sum(single_X[:, 0, (normal_candidate==True)], axis=1) + simple_rdr_normal = simple_rdr_normal / np.sum(simple_rdr_normal) + simple_single_base_nb_mean = simple_rdr_normal.reshape(-1,1) @ np.sum(single_X[:,0,:], axis=0).reshape(1,-1) + # then aggregate to clones + clone_index = [np.where(new_assignment == c)[0] for c in range(n_clones)] + X, base_nb_mean, _ = merge_pseudobulk_by_index(single_X, simple_single_base_nb_mean, np.zeros(simple_single_base_nb_mean.shape), clone_index) + rdr_values = [] + for s in np.arange(n_states): + rdr_values.append( np.sum(X[:,0,:][reshaped_pred_cnv==s]) / np.sum(base_nb_mean[reshaped_pred_cnv==s]) ) + rdr_values = np.array(rdr_values) + + # SNP-covering UMI per clone + clone_snpumi = np.array([np.sum(single_total_bb_RD[:,new_assignment==c]) for c in range(n_clones)]) + + # clones that have a decent tumor proportion + # for each clone, if the clones_hightumor-th BAF deviation is large enough + k_baf_deviation = np.sort( np.abs(p_binom[reshaped_pred_cnv, 0]-0.5), axis=0)[-MIN_BINS_ALL,:] + # LOH states + for threshold in np.arange(MIN_BAF_DEVIATION_RANGE[0], MIN_BAF_DEVIATION_RANGE[1]-0.01, -0.02): + clones_hightumor = np.where( (k_baf_deviation >= threshold) & (clone_snpumi >= MIN_SNPUMI*n_obs) )[0] + if len(clones_hightumor) == 0: + continue + if len(clones_hightumor) == n_clones: + clones_hightumor = np.argsort(k_baf_deviation)[1:] + # LOH states + loh_states = np.where( (np.abs(p_binom[:,0] - 0.5) > threshold) & (np.bincount(pred_cnv, minlength=n_states) >= MIN_BINS_PER_STATE) & (rdr_values <= MAX_RDR) )[0] + is_B_lost = (p_binom[loh_states,0] < 0.5) + if np.all([ np.sum(pd.Series(reshaped_pred_cnv[:,c]).isin(loh_states)) >= MIN_BINS_ALL for c in clones_hightumor ]): + print(f"threshold = {threshold}") + print(f"clones with high tumor proportion: {clones_hightumor}") + print(f"BAF deviation threshold = {threshold}, LOH states: {loh_states}") + break + + """ + Update ideas: why not finding high purity clone and loh states together by varying BAF deviation threshold? + Current we first identify high purity clone using BAF deviation threshold = 0.15, then identify loh states. + But we can vary BAF deviation threshold from the large to small, identify high purity clones and loh states based on the same threshold. + At very large threshold value, there will be no high purity clone, which is unreasonable. + While lowering the threshold, purity clone(s) will appear, and we terminate once we are able to find one high purity clone. + + Another update idea: identification of loh states is unaware of RDR. + We can first find low-copy-number loh states first by thresholding RDR. If we can't find any, increase RDR threshold. + """ + + return loh_states, is_B_lost, rdr_values[loh_states], clones_hightumor + + +def estimator_tumor_proportion(single_X, single_total_bb_RD, assignments, pred_cnv, loh_states, is_B_lost, rdr_values, clone_to_consider, smooth_mat=None, MIN_TOTAL=10): + """ + Attributes + ---------- + single_X : array, shape (n_obs, 2, n_spots) + Observed transcript counts and B allele count per bin per spot. + + single_total_bb_RD : array, shape (n_obs, n_spots) + Total allele count per bin per spot. + + assignments : pd.DataFrame of size n_spots with columns "coarse", "combined" + Clone assignment for each spot. + + pred_cnv : array, shape (n_obs * n_clones) + Copy number states across bins for each clone. + + loh_states, is_B_lost, rdr_values: array + Copy number states and RDR values corresponding to LOH. + + Formula + ---------- + 0.5 ( 1-theta ) / (theta * RDR + 1 - theta) = B_count / Total_count for each LOH state. + """ + # def estimate_purity(T_loh, B_loh, rdr_values): + # features =(T_loh / 2.0 + rdr_values * B_loh - B_loh)[T_loh>0].reshape(-1,1) + # y = (T_loh / 2.0 - B_loh)[T_loh>0] + # return np.linalg.lstsq(features, y, rcond=None)[0] + def estimate_purity(T_loh, B_loh, rdr_values): + idx = np.where(T_loh > 0)[0] + model = BAF_Binom(endog=B_loh[idx], exog=np.ones((len(idx),1)), weights=np.ones(len(idx)), exposure=T_loh[idx], offset=np.log(rdr_values[idx]), scaling=0.5) + res = model.fit(disp=False) + return 1.0 / (1.0 + np.exp(res.params)) + # + n_obs = single_X.shape[0] + n_spots = single_X.shape[2] + n_clones = int(len(pred_cnv) / n_obs) + reshaped_pred_cnv = pred_cnv.reshape((n_obs, n_clones), order='F') + + clone_mapping = assignments.groupby(['coarse', 'combined']).agg('first').reset_index() + + tumor_proportion = np.zeros(n_spots) + full_tumor_proportion = np.zeros((n_spots, n_clones)) + for i in range(n_spots): + # get adjacent spots for smoothing + if smooth_mat is not None: + idx_adj = smooth_mat[i,:].nonzero()[1] + else: + idx_adj = np.array([i]) + estimation_based_on_clones_single = np.ones(n_clones) * np.nan + estimation_based_on_clones_smoothed = np.ones(n_clones) * np.nan + summed_T_single = np.ones(n_clones) + summed_T_smoothed = np.ones(n_clones) + for c in clone_to_consider: + # single + B_loh = np.array([ np.sum(single_X[:,1,i][reshaped_pred_cnv[:,c]==s]) if is_B_lost[j] else np.sum(single_total_bb_RD[:,i][reshaped_pred_cnv[:,c]==s]) - np.sum(single_X[:,1,i][reshaped_pred_cnv[:,c]==s]) for j,s in enumerate(loh_states)]) + T_loh = np.array([ np.sum(single_total_bb_RD[:,i][reshaped_pred_cnv[:,c]==s]) for s in loh_states]) + if np.all(T_loh == 0): + continue + estimation_based_on_clones_single[c] = estimate_purity(T_loh, B_loh, rdr_values) + summed_T_single[c] = np.sum(T_loh) + # smoothed + B_loh = np.array([ np.sum(single_X[:,1,idx_adj][reshaped_pred_cnv[:,c]==s]) if is_B_lost[j] else np.sum(single_total_bb_RD[:,idx_adj][reshaped_pred_cnv[:,c]==s]) - np.sum(single_X[:,1,idx_adj][reshaped_pred_cnv[:,c]==s]) for j,s in enumerate(loh_states)]) + T_loh = np.array([ np.sum(single_total_bb_RD[:,idx_adj][reshaped_pred_cnv[:,c]==s]) for s in loh_states]) + if np.all(T_loh == 0): + continue + estimation_based_on_clones_smoothed[c] = estimate_purity(T_loh, B_loh, rdr_values) + summed_T_smoothed[c] = np.sum(T_loh) + full_tumor_proportion[i,:] = estimation_based_on_clones_single + if (assignments.combined.values[i] in clone_to_consider) and summed_T_single[assignments.combined.values[i]] >= MIN_TOTAL: + tumor_proportion[i] = estimation_based_on_clones_single[ assignments.combined.values[i] ] + elif (assignments.combined.values[i] in clone_to_consider) and summed_T_smoothed[assignments.combined.values[i]] >= MIN_TOTAL: + tumor_proportion[i] = estimation_based_on_clones_smoothed[ assignments.combined.values[i] ] + elif not assignments.combined.values[i] in clone_to_consider: + tumor_proportion[i] = estimation_based_on_clones_single[np.argmax(summed_T_single)] + else: + tumor_proportion[i] = np.nan + + tumor_proportion = np.where(tumor_proportion < 0, 0, tumor_proportion) + return tumor_proportion, full_tumor_proportion diff --git a/src/calicost/utils_phase_switch.py b/src/calicost/utils_phase_switch.py new file mode 100644 index 0000000..aed6e11 --- /dev/null +++ b/src/calicost/utils_phase_switch.py @@ -0,0 +1,305 @@ +import numpy as np +import pandas as pd +from pathlib import Path +from tqdm import trange +import scipy +import scipy.special + + +def get_position_cM_table(chr_pos_vector, geneticmap_file): + """ + Attributes + ---------- + chr_pos_vector : list of pairs + list of (chr, pos) pairs of SNPs + """ + df = pd.read_csv(geneticmap_file, header=0, sep="\t") + # remove chrX + df = df[df.chrom.isin( [f"chr{i}" for i in range(1,23)] )] + # check the chromosome names + if not ("chr" in str(chr_pos_vector[0][0])): + df["chrom"] = [int(x[3:]) for x in df.chrom] + df = df.sort_values(by=["chrom", "pos"]) + ref_chrom = np.array(df.chrom) + ref_pos = np.array(df.pos) + ref_cm = np.array(df.pos_cm) + # also sort the input argument + chr_pos_vector.sort() + # find the centimorgan values (interpolate between (k-1)-th and k-th rows in centimorgan tables) + position_cM = np.ones(len(chr_pos_vector)) * np.nan + k = 0 + for i,x in enumerate(chr_pos_vector): + chrname = x[0] + pos = x[1] + while k < len(ref_chrom) and (ref_chrom[k] < chrname or (ref_chrom[k] == chrname and ref_pos[k] < pos)): + k += 1 + if k < len(ref_chrom) and ref_chrom[k] == chrname and ref_pos[k] >= pos: + if k > 0 and ref_chrom[k-1] == chrname: + position_cM[i] = ref_cm[k-1] + (pos - ref_pos[k-1]) / (ref_pos[k] - ref_pos[k-1]) * (ref_cm[k] - ref_cm[k-1]) + else: + position_cM[i] = (pos - 0) / (ref_pos[k] - 0) * (ref_cm[k] - 0) + else: + position_cM[i] = ref_cm[k-1] + return position_cM + + +def compute_phase_switch_probability_position(position_cM, chr_pos_vector, nu = 1, min_prob=1e-20): + """ + Attributes + ---------- + position_cM : array, (number SNP positions) + Centimorgans of SNPs located at each entry of position_cM. + + chr_pos_vector : list of pairs + list of (chr, pos) pairs of SNPs. It is used to identify start of a new chr. + """ + phase_switch_prob = np.ones(len(position_cM)) * 1e-20 + for i,cm in enumerate(position_cM[:-1]): + cm_next = position_cM[i+1] + if np.isnan(cm) or np.isnan(cm_next) or chr_pos_vector[i][0] != chr_pos_vector[i+1][0]: + continue + assert cm <= cm_next + d = cm_next - cm + phase_switch_prob[i] = (1 - np.exp(-2 * nu * d)) / 2 + phase_switch_prob[phase_switch_prob < min_prob] = min_prob + return phase_switch_prob + + +def duplicate_RD(chr_baf, pos_baf, chr_rd, start_rd, end_rd, tumor_rd, normal_rd): + tumor_reads = np.ones(len(chr_baf)) * np.nan + normal_reads = np.ones(len(chr_baf)) * np.nan + idx = 0 + for i in range(len(chr_baf)): + while idx < len(chr_rd) and (chr_rd[idx] < chr_baf[i] or (chr_rd[idx] == chr_baf[i] and end_rd[idx] < pos_baf[i])): + idx += 1 + if idx < len(chr_rd) and chr_rd[idx] == chr_baf[i] and end_rd[idx] >= pos_baf[i] and start_rd[idx] <= pos_baf[i]: + tumor_reads[i] = tumor_rd[idx] + normal_reads[i] = normal_rd[idx] + return tumor_reads, normal_reads + + +def generate_input_from_HATCHet(hatchetdir, output_picklefile, rdrfile="abin/bulk.bb", baffile="baf/bulk.1bed", phasefile="phase/phased.vcf.gz", with_chr_prefix=True): + if with_chr_prefix: + unique_chrs = [f"chr{i}" for i in range(1, 23)] + else: + unique_chrs = np.arange(1, 23) + + ### load hatchet outputs ### + if Path(output_picklefile).exists(): + # RDR file + df_all = pd.read_csv(f"{hatchetdir}/{rdrfile}", header=0, sep="\t") + df_all.iloc[:,0] = pd.Categorical(df_all.iloc[:,0], categories=unique_chrs, ordered=True) + df_all.sort_values(by=["#CHR", "START"], inplace=True) + # samples + unique_samples = np.unique(df_all["SAMPLE"]) + # allele counts + df_baf = pd.read_pickle(output_picklefile) + else: + # RDR file + df_all = pd.read_csv(f"{hatchetdir}/{rdrfile}", header=0, sep="\t") + df_all.iloc[:,0] = pd.Categorical(df_all.iloc[:,0], categories=unique_chrs, ordered=True) + df_all.sort_values(by=["#CHR", "START"], inplace=True) + # samples + unique_samples = np.unique(df_all["SAMPLE"]) + # allele counts for individual SNPs + def load_shared_BAF(hatchetdir, baffile, unique_chrs, unique_samples): + tmpdf = pd.read_csv(f"{hatchetdir}/{baffile}", header=None, sep="\t", names=["CHR", "POS", "SAMPLE", "REF", "ALT"]) + df_baf = [] + for chrname in unique_chrs: + tmp = tmpdf[tmpdf.CHR == chrname] + list_pos = [set(list(tmp[tmp["SAMPLE"] == s].POS)) for s in unique_samples] # SNP set of each individual sample + shared_pos = set.intersection(*list_pos) # SNPs that are shared across samples + index = np.array([i for i in range(tmp.shape[0]) if tmp.iloc[i,1] in shared_pos]) + tmp = tmp.iloc[index,:] + tmp.sort_values(by=["POS", "SAMPLE"], inplace=True) + df_baf.append( tmp ) + df_baf = pd.concat(df_baf, ignore_index=True) + return df_baf + df_baf = load_shared_BAF(hatchetdir, baffile, unique_chrs, unique_samples) + # reference-based phasing results + df_phase = pd.read_csv(f"{hatchetdir}/{phasefile}", comment="#", sep="\t", \ + names=["CHR", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO", "FORMAT", "SAMPLENAME"]) + df_phase = df_phase[(df_phase.SAMPLENAME=="0|1") | (df_phase.SAMPLENAME=="1|0")] + print("HATCHet dataframes loaded.") + + ### gather phased BAF info ### + df_combined_baf = [] + for chrname in unique_chrs: + tmpdf_baf = df_baf[df_baf.CHR == chrname] + tmpdf_phase = df_phase[df_phase.CHR == chrname][["POS", "SAMPLENAME"]] + tmpdf_baf = tmpdf_baf.join( tmpdf_phase.set_index("POS"), on="POS") + tmpdf_baf = tmpdf_baf[~tmpdf_baf.SAMPLENAME.isnull()] + tmpdf_baf["B_count"] = np.where(tmpdf_baf.SAMPLENAME=="0|1", tmpdf_baf.REF, tmpdf_baf.ALT) + tmpdf_baf["DP"] = tmpdf_baf.REF + tmpdf_baf.ALT + df_combined_baf.append( tmpdf_baf ) + df_combined_baf = pd.concat(df_combined_baf, ignore_index=True) + df_combined_baf.iloc[:,0] = pd.Categorical(df_combined_baf.CHR, categories=unique_chrs, ordered=True) + df_combined_baf.sort_values(by=["CHR", "POS"], inplace=True) + df_baf = df_combined_baf + + ### duplicate RDR info for each SNP ### + df_baf["TOTAL_READS"] = np.nan + df_baf["NORMAL_READS"] = np.nan + for s in unique_samples: + index = np.where(df_baf["SAMPLE"] == s)[0] + index_rd = np.where(df_all["SAMPLE"] == s)[0] + tumor_reads, normal_reads = duplicate_RD(np.array(df_baf.iloc[index,:].CHR.cat.codes), np.array(df_baf.iloc[index,:].POS), \ + np.array(df_all.iloc[index_rd,0].cat.codes), np.array(df_all.iloc[index_rd,:].START), np.array(df_all.iloc[index_rd,:].END), \ + np.array(df_all.iloc[index_rd,:].TOTAL_READS), np.array(df_all.iloc[index_rd,:].NORMAL_READS)) + df_baf.iloc[index, -2] = tumor_reads + df_baf.iloc[index, -1] = normal_reads + # remove SNP positions with TOTAL_READS=NAN (if NAN occurs in one sample, remove the corresponding SNPs for the other samples too) + def remove_nan_RD(df_baf): + idx_nan = np.where(np.logical_or( df_baf.TOTAL_READS.isnull(), df_baf.NORMAL_READS.isnull() ))[0] + chr = np.array(df_baf.CHR) + pos = np.array(df_baf.POS) + chr_pos = np.array([f"{chr[i]}_{pos[i]}" for i in range(len(chr))]) + nan_chr_pos = set(list(chr_pos[idx_nan])) + idx_remain = np.array([i for i,snpid in enumerate(chr_pos) if not (snpid in nan_chr_pos)]) + df_baf = df_baf.iloc[idx_remain, :] + return df_baf + df_baf = remove_nan_RD(df_baf) + df_baf.to_pickle(output_picklefile) + print("SNP-level BAF and bin-level RDR paired up.") + + ### from BAF, RDR table, generate HMM input ### + lengths = np.array([ np.sum(np.logical_and(df_baf["CHR"]==chrname, df_baf["SAMPLE"]==unique_samples[0])) for chrname in unique_chrs ]) + + X = np.zeros(( np.sum(lengths), 2, len(unique_samples) )) + base_nb_mean = np.zeros((np.sum(lengths), len(unique_samples) )) + total_bb_RD = np.zeros((np.sum(lengths), len(unique_samples) )) + + for k,s in enumerate(unique_samples): + df = df_baf[df_baf["SAMPLE"] == s] + X[:,0,k] = df.TOTAL_READS + X[:,1,k] = df.B_count + + total_bb_RD[:,k] = np.array(df.DP) + df2 = df_all[df_all["SAMPLE"] == s] + base_nb_mean[:,k] = np.array(df.NORMAL_READS / np.sum(df2.NORMAL_READS) * np.sum(df2.TOTAL_READS)) + + # site-wise transition matrix + chr_pos_vector = [(df_baf.CHR.iloc[i], df_baf.POS.iloc[i]) for i in np.where(df_baf["SAMPLE"]==unique_samples[0])[0]] + position_cM = get_position_cM_table(chr_pos_vector) + phase_switch_prob = compute_phase_switch_probability_position(position_cM, chr_pos_vector) + log_sitewise_transmat = np.log(phase_switch_prob) + + return X, lengths, base_nb_mean, total_bb_RD, log_sitewise_transmat + + +def distance_between_p_binom(state_pred1, clone_pred1, p_binom1, state_pred2, clone_pred2, p_binom2): + import networkx as nx + + # matching predicted CNV states + n_states = len(np.unique(state_pred1)) + uniq_pred1 = np.sort(np.unique(state_pred1)) + uniq_pred2 = np.sort(np.unique(state_pred2)) + G = nx.Graph() + G.add_nodes_from([f"A{i}" for i in uniq_pred1], bipartite=0) + G.add_nodes_from([f"B{j}" for j in uniq_pred2], bipartite=1) + # G.add_weighted_edges_from( [(f"A{i}", f"B{j}", np.sum(np.logical_and(state_pred1==uniq_pred1[i], state_pred2==uniq_pred2[j]))) for i in uniq_pred1 for j in uniq_pred2] ) + # tmp = nx.max_weight_matching(G) + # state_matching = {x[0]:x[1] for x in tmp} + # state_matching.update( {x[1]:x[0] for x in tmp} ) + G.add_weighted_edges_from( [(f"A{i}", f"B{j}", len(state_pred1) - np.sum(np.logical_and(state_pred1==uniq_pred1[i], state_pred2==uniq_pred2[j]))) for i in uniq_pred1 for j in uniq_pred2] ) + state_matching = nx.bipartite.minimum_weight_full_matching(G) + + # matching predicted clones + n_clones = len(np.unique(clone_pred1)) + uniq_pred1 = np.sort(np.unique(clone_pred1)) + uniq_pred2 = np.sort(np.unique(clone_pred2)) + G = nx.Graph() + G.add_nodes_from([f"A{i}" for i in uniq_pred1], bipartite=0) + G.add_nodes_from([f"B{j}" for j in uniq_pred2], bipartite=1) + # G.add_weighted_edges_from( [(f"A{i}", f"B{j}", np.sum(np.logical_and(clone_pred1==uniq_pred1[i], clone_pred2==uniq_pred2[j]))) for i in uniq_pred1 for j in uniq_pred2] ) + # tmp = nx.max_weight_matching(G) + # clone_matching = {x[0]:x[1] for x in tmp} + # clone_matching.update( {x[1]:x[0] for x in tmp} ) + G.add_weighted_edges_from( [(f"A{i}", f"B{j}", len(clone_pred1) - np.sum(np.logical_and(clone_pred1==uniq_pred1[i], clone_pred2==uniq_pred2[j]))) for i in uniq_pred1 for j in uniq_pred2] ) + clone_matching = nx.bipartite.minimum_weight_full_matching(G) + + # l2 distance between corresponding CNV at corresponding clone + # reorder p_binom2 based on state_matching and clone_matching + reorder_p_binom2 = p_binom2[:, np.array([ int(clone_matching[f"A{i}"][1:]) for i in range(n_clones)])] + reorder_p_binom2 = reorder_p_binom2[np.array([ int(state_matching[f"A{i}"][1:]) for i in range(n_states) ]), :] + l2 = 0 + for i in range(p_binom1.shape[0]): + l2 += min( np.sum(np.square(p_binom1[i,:] - reorder_p_binom2[i,:])), np.sum(np.square(p_binom1[i,:] - 1 + reorder_p_binom2[i,:])) ) + return l2 + + +def get_intervals(pred_cnv): + intervals = [] + labs = [] + s = 0 + while s < len(pred_cnv): + t = np.where(pred_cnv[s:] != pred_cnv[s])[0] + if len(t) == 0: + intervals.append( (s, len(pred_cnv)) ) + labs.append( pred_cnv[s] ) + s = len(pred_cnv) + else: + t = t[0] + intervals.append( (s,s+t) ) + labs.append( pred_cnv[s] ) + s = s+t + return intervals, labs + + +def get_intervals_nd(pred_cnv): + """ + pred_cnv : np.array of shape (n_bins, n_clones) + """ + intervals = [] + labs = [] + s = 0 + while s < len(pred_cnv): + t = np.where(np.any(pred_cnv[s:] != pred_cnv[s], axis=1))[0] + if len(t) == 0: + intervals.append( (s, len(pred_cnv)) ) + labs.append( pred_cnv[s] ) + s = len(pred_cnv) + else: + t = t[0] + intervals.append( (s,s+t) ) + labs.append( pred_cnv[s] ) + s = s+t + return intervals, labs + + +def postbinning_forvisual(X, base_nb_mean, total_bb_RD, lengths, res, binsize=2): + # a list of intervals used in binning for transforming back to non-binned space + intervals = [] + bin_lengths = [] + # variables for for-loop + chrname = 0 + nextlen = lengths[chrname] + s = 0 + while s < X.shape[0]: + t = min(s+binsize, nextlen) + intervals.append( [s,t] ) + s = t + if s >= nextlen: + if s < X.shape[0]: + chrname += 1 + nextlen += lengths[chrname] + bin_lengths.append( len(intervals) ) + bin_lengths = np.array(bin_lengths) + bin_lengths[1:] = bin_lengths[1:] - bin_lengths[:-1] + + # binning based on previous intervals + n_states = int(res["log_gamma"].shape[0] / 2) + phase_prob = np.exp(scipy.special.logsumexp(res["log_gamma"][:n_states, :], axis=0)) + bin_X = np.zeros((len(intervals), X.shape[1], X.shape[2]), dtype=int) + bin_base_nb_mean = np.zeros((len(intervals), base_nb_mean.shape[1]), dtype=int) + bin_total_bb_RD = np.zeros((len(intervals), total_bb_RD.shape[1]), dtype=int) + bin_pred_cnv = np.zeros(len(intervals), dtype=int) + for i, intvl in enumerate(intervals): + s,t = intvl + bin_X[i,0,:] = np.sum(X[s:t, 0,:], axis=0) + bin_X[i,1,:] = np.sum( phase_prob[s:t].dot(X[s:t, 1,:]) + (1-phase_prob[s:t]).dot(total_bb_RD[s:t,:] - X[s:t,1,:]) ) + bin_base_nb_mean[i,:] = np.sum(base_nb_mean[s:t,:], axis=0) + bin_total_bb_RD[i,:] = np.sum(total_bb_RD[s:t,:], axis=0) + bin_pred_cnv[i] = res["pred_cnv"][s] + + return bin_X, bin_base_nb_mean, bin_total_bb_RD, bin_pred_cnv, bin_lengths, intervals \ No newline at end of file diff --git a/src/calicost/utils_plotting.py b/src/calicost/utils_plotting.py new file mode 100644 index 0000000..079278a --- /dev/null +++ b/src/calicost/utils_plotting.py @@ -0,0 +1,1414 @@ + +import sys +import argparse + +import numpy as np +import scipy +import pandas as pd +from itertools import cycle +import matplotlib +from matplotlib import pyplot as plt +from matplotlib.colors import LinearSegmentedColormap, ListedColormap +from matplotlib.gridspec import GridSpec +import seaborn +from matplotlib.lines import Line2D +import matplotlib.patches as mpatches + +from calicost.utils_IO import * +from calicost.utils_phase_switch import * +from calicost.hmrf import * +from calicost.arg_parse import * + + +def get_full_palette(): + palette = {} + palette.update({(0, 0) : 'darkblue'}) + palette.update({(1, 0) : 'lightblue'}) + palette.update({(1, 1) : 'lightgray', (2, 0) : 'dimgray'}) + palette.update({(2, 1) : 'lightgoldenrodyellow', (3, 0) : 'gold'}) + # palette.update({(2, 1) : 'greenyellow', (3, 0) : 'darkseagreen'}) + palette.update({(2, 2) : 'navajowhite', (3, 1) : 'orange', (4, 0) : 'darkorange'}) + palette.update({(3, 2) : 'salmon', (4, 1) : 'red', (5, 0) : 'darkred'}) + palette.update({(3, 3) : 'plum', (4, 2) : 'orchid', (5, 1) : 'purple', (6, 0) : 'indigo'}) + ordered_acn = [(0, 0), (1, 0), (1, 1), (2, 0), (2, 1), (3, 0), \ + (2, 2), (3, 1), (4, 0), (3, 2), (4, 1), (5, 0), \ + (3, 3), (4, 2), (5, 1), (6, 0)] + return palette, ordered_acn + + +def plot_acn(cn_file, ax_handle, clone_ids=None, clone_names=None, add_chrbar=True, add_arrow=True, chrbar_thickness=0.1, add_legend=True, remove_xticks=True): + # full color palette + palette,_ = get_full_palette() + + # read CN profiles + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + print(final_clone_ids) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + + found = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + found += list(zip(major, minor)) + found = list(set(found)) + found.sort() + + # map CN to single digit number + map_cn = {x:i for i,x in enumerate(found)} + cnv_mapped = [] + ploidy = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + cnv_mapped.append( [map_cn[(major[i], minor[i])] for i in range(len(major))] ) + ploidy.append( np.mean(major + minor) ) + cnv_mapped = pd.DataFrame( np.array(cnv_mapped), index=[f"clone {cid}" for cid in final_clone_ids]) + ploidy = pd.DataFrame(np.around(np.array(ploidy), decimals=2).reshape(-1,1), index=[f"clone {cid}" for cid in final_clone_ids]) + chr_ids = df_cnv.CHR + + colors = [palette[c] for c in found] + if clone_ids is None: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in final_clone_ids] + rename_cnv_mapped = pd.DataFrame(cnv_mapped.values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(final_clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + else: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in clone_ids] + if clone_names is None: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + else: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"{clone_names[c]}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + + # indicate allele switches + if add_arrow: + if clone_ids is None: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(final_clone_ids): + y1 = c + y2 = c+1 + # up-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y2+0.1*y1, dx=0, dy=0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + # down-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y1+0.1*y2, dx=0, dy=-0.7*(y1-y2), head_width=0.3*(sub_int[1]-sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + else: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(clone_ids): + y1 = c + y2 = c+1 + # up-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y2+0.1*y1, dx=0, dy=0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + # down-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y1+0.1*y2, dx=0, dy=-0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + + if add_chrbar: + # add chr color + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + lut = {c:next(chr_palette) for c in np.unique(chr_ids.values)} + col_colors = chr_ids.map(lut) + for i, color in enumerate(col_colors): + ax_handle.add_patch(plt.Rectangle(xy=(i, 1.01), width=1, height=chrbar_thickness, color=color, lw=0, transform=ax_handle.get_xaxis_transform(), clip_on=False, rasterized=True)) + + for c in np.unique(chr_ids.values): + interval = np.where(chr_ids.values == c)[0] + mid = np.percentile(interval, 45) + ax_handle.text(mid-10, 1.04, str(c), transform=ax_handle.get_xaxis_transform()) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + ax_handle.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1)) + return ax_handle + + +def plot_acn_from_df(df_cnv, ax_handle, clone_ids=None, clone_names=None, add_chrbar=True, add_arrow=True, chrbar_thickness=0.1, add_legend=True, remove_xticks=True, rasterized=True): + # full color palette + palette,_ = get_full_palette() + + # read CN profiles + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + print(final_clone_ids) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + + found = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + found += list(zip(major, minor)) + found = list(set(found)) + found.sort() + + # map CN to single digit number + map_cn = {x:i for i,x in enumerate(found)} + cnv_mapped = [] + ploidy = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + cnv_mapped.append( [map_cn[(major[i], minor[i])] for i in range(len(major))] ) + ploidy.append( np.mean(major + minor) ) + cnv_mapped = pd.DataFrame( np.array(cnv_mapped), index=[f"clone {cid}" for cid in final_clone_ids]) + ploidy = pd.DataFrame(np.around(np.array(ploidy), decimals=2).reshape(-1,1), index=[f"clone {cid}" for cid in final_clone_ids]) + chr_ids = df_cnv.CHR + + colors = [palette[c] for c in found] + if clone_ids is None: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in final_clone_ids] + rename_cnv_mapped = pd.DataFrame(cnv_mapped.values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(final_clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=rasterized, ax=ax_handle) + else: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in clone_ids] + if clone_names is None: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + else: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"{clone_names[c]}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=rasterized, ax=ax_handle) + + # indicate allele switches + if add_arrow: + if clone_ids is None: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(final_clone_ids): + y1 = c + y2 = c+1 + # up-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y2+0.1*y1, dx=0, dy=0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + # down-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y1+0.1*y2, dx=0, dy=-0.7*(y1-y2), head_width=0.3*(sub_int[1]-sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + else: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(clone_ids): + y1 = c + y2 = c+1 + # up-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y2+0.1*y1, dx=0, dy=0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + # down-arrow + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black") + ax_handle.arrow(x=intervals[i][0]+np.mean(sub_int), y=0.9*y1+0.1*y2, dx=0, dy=-0.7*(y1-y2), head_width=0.3*(sub_int[1] - sub_int[0]), head_length=0.1*np.abs(y1-y2), fc="black") + + if add_chrbar: + # add chr color + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + lut = {c:next(chr_palette) for c in np.unique(chr_ids.values)} + col_colors = chr_ids.map(lut) + for i, color in enumerate(col_colors): + ax_handle.add_patch(plt.Rectangle(xy=(i, 1 + 0.02*chrbar_thickness), width=1, height=chrbar_thickness, color=color, lw=0, transform=ax_handle.get_xaxis_transform(), clip_on=False, rasterized=rasterized)) + + for c in np.unique(chr_ids.values): + interval = np.where(chr_ids.values == c)[0] + mid = np.percentile(interval, 45) + ax_handle.text(mid-10, 1 + 0.2*chrbar_thickness, str(c), transform=ax_handle.get_xaxis_transform()) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + ax_handle.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1)) + return ax_handle + + +def plot_acn_from_df_anotherscheme(df_cnv, ax_handle, clone_ids=None, clone_names=None, clone_proportions=None, chrbar_pos=None, add_arrow=True, border_linewidth=1, chrbar_thickness=0.1, add_legend=True, remove_xticks=True, rasterized=True): + # full color palette + palette,_ = get_full_palette() + + # read CN profiles + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + print(final_clone_ids) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + + found = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + found += list(zip(major, minor)) + found = list(set(found)) + found.sort() + + # map CN to single digit number + map_cn = {x:i for i,x in enumerate(found)} + cnv_mapped = [] + ploidy = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + cnv_mapped.append( [map_cn[(major[i], minor[i])] for i in range(len(major))] ) + ploidy.append( np.mean(major + minor) ) + cnv_mapped = pd.DataFrame( np.array(cnv_mapped), index=[f"clone {cid}" for cid in final_clone_ids]) + ploidy = pd.DataFrame(np.around(np.array(ploidy), decimals=2).reshape(-1,1), index=[f"clone {cid}" for cid in final_clone_ids]) + chr_ids = df_cnv.CHR + + colors = [palette[c] for c in found] + if clone_ids is None: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in final_clone_ids] + rename_cnv_mapped = pd.DataFrame(cnv_mapped.values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(final_clone_ids)]) + if len(np.unique(rename_cnv_mapped.values)) == 1: + colors = colors + colors + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=rasterized, ax=ax_handle) + else: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in clone_ids] + if clone_names is None: + index_str = [f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)] + else: + index_str = [f"{clone_names[c]}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)] + if not clone_proportions is None: + index_str = [f"{index_str[c]}\nu={clone_proportions[c]:.2f}" for c in range(len(clone_ids))] + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=index_str) + if len(np.unique(rename_cnv_mapped.values)) == 1: + colors = colors + colors + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=rasterized, ax=ax_handle) + + # indicate allele switches + if add_arrow: + if clone_ids is None: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in final_clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(final_clone_ids): + y1 = c + y2 = c+1 + # up-arrow + y_diverge1 = 0.8*y2+0.2*y1 + y_diverge2 = 0.6*y2+0.4*y1 + y_merge = 0.7*y2+0.3*y1 + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + # bounding box + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black", linewidth=border_linewidth) + # arrow + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], [y_diverge1,y_merge], [y_diverge2,y_merge], color="black", edgecolor="black") + # down-arrow + y_diverge1 = 0.2*y2+0.8*y1 + y_diverge2 = 0.4*y2+0.6*y1 + y_merge = 0.3*y2+0.7*y1 + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + # bounding box + ax_handle.fill_between( np.arange(intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]), y1, y2, color="none", edgecolor="black", linewidth=border_linewidth) + # arrow + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], [y_merge,y_diverge1], [y_merge,y_diverge2], color="black", edgecolor="black") + else: + # find regions where there exist both clones with A > B and clones with A < B + has_up = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values > df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + has_down = np.any(np.vstack([ df_cnv[f"clone{cid} A"].values < df_cnv[f"clone{cid} B"].values for cid in clone_ids]), axis=0) + intervals, labs = get_intervals( (has_up & has_down) ) + # for each intervals, find the corresponding clones with A > B to plot up-arrow, and corresponding clones with A < B to plot down-arrow + for i in range(len(intervals)): + if not labs[i]: + continue + for c,cid in enumerate(clone_ids): + y1 = c + y2 = c+1 + # up-arrow + y_diverge1 = 0.8*y2+0.2*y1 + y_diverge2 = 0.6*y2+0.4*y1 + y_merge = 0.7*y2+0.3*y1 + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] > df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + # bounding box + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], y1, y2, color="none", edgecolor="black", linewidth=border_linewidth) + # arrow + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], [y_diverge1,y_merge], [y_diverge2,y_merge], color="black", edgecolor="black") + # down-arrow + y_diverge1 = 0.2*y2+0.8*y1 + y_diverge2 = 0.4*y2+0.6*y1 + y_merge = 0.3*y2+0.7*y1 + sub_intervals, sub_labs = get_intervals( df_cnv[f"clone{cid} A"].values[intervals[i][0]:intervals[i][1]] < df_cnv[f"clone{cid} B"].values[intervals[i][0]:intervals[i][1]] ) + for j, sub_int in enumerate(sub_intervals): + if sub_labs[j]: + # bounding box + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], y1, y2, color="none", edgecolor="black", linewidth=border_linewidth) + # arrow + ax_handle.fill_between( [intervals[i][0]+sub_int[0], intervals[i][0]+sub_int[1]], [y_merge,y_diverge1], [y_merge,y_diverge2], color="black", edgecolor="black") + + # # horizontal separation between clones + # for c,cid in enumerate(clone_ids[:-1]): + # ax_handle.axhline(y=c+1, color="black", lw=0.5) + + if chrbar_pos == "bottom": + chr_ids = df_cnv.CHR + h = len(final_clone_ids) if clone_ids is None else len(clone_ids) + # ax_handle.add_patch(plt.Rectangle(xy=(0, h + chrbar_thickness), width=df_cnv.shape[0], height=chrbar_thickness, color='white', lw=0, transform=ax_handle.transData, clip_on=False, rasterized=rasterized)) + + for i,c in enumerate(np.unique(chr_ids.values)): + interval = np.where(chr_ids.values == c)[0] + # add vertical separation between chromosomes + if not np.max(interval) + 1 >= df_cnv.shape[0]: + ax_handle.axvline(x=np.max(interval), color='black', lw=0.5, ymin=-0.5/(h+1), clip_on = False) + mid = np.percentile(interval, 45) + if i % 2 == 0: + ax_handle.text(mid, h + chrbar_thickness, str(c), ha='center', transform=ax_handle.transData) + else: + ax_handle.text(mid, h + 2*chrbar_thickness, str(c), ha='center', transform=ax_handle.transData) + elif chrbar_pos == "top": + chr_ids = df_cnv.CHR + h = len(final_clone_ids) if clone_ids is None else len(clone_ids) + # ax_handle.add_patch(plt.Rectangle(xy=(0, h + chrbar_thickness), width=df_cnv.shape[0], height=chrbar_thickness, color='white', lw=0, transform=ax_handle.transData, clip_on=False, rasterized=rasterized)) + + for i,c in enumerate(np.unique(chr_ids.values)): + interval = np.where(chr_ids.values == c)[0] + # add vertical separation between chromosomes + if not np.max(interval) + 1 >= df_cnv.shape[0]: + ax_handle.axvline(x=np.max(interval), color='black', lw=0.5, ymax=1+0.5/(h+1), clip_on = False) + mid = np.percentile(interval, 45) + if i % 2 == 0: + ax_handle.text(mid, -0.1*chrbar_thickness, str(c), ha='center', transform=ax_handle.transData) + else: + ax_handle.text(mid, -0.8*chrbar_thickness, str(c), ha='center', transform=ax_handle.transData) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + ax_handle.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1)) + return ax_handle + + + +def plot_acn_legend(fig, shift_y=0.3): + # full palette + palette, ordered_acn = get_full_palette() + + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [palette[c] for c in ordered_acn] + cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)) + + n_total_cn = np.max([x[0]+x[1] for x in ordered_acn]) + 1 + gs = GridSpec(2*n_total_cn-1, 1, figure=fig) + + # total cn = 0 + ax = fig.add_subplot(gs[2*n_total_cn-2, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(0,0)]]).reshape((1,-1)), columns=["{0,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + # total cn = 1 + ax = fig.add_subplot(gs[2*n_total_cn-4, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(1,0)]]).reshape((1,-1)), columns=["{1,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + # total cn = 2 + ax = fig.add_subplot(gs[2*n_total_cn-6, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(1,1)], map_cn[(2,0)]]).reshape((1,-1)), columns=["{1,1}", "{2,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,0.3)) + + # total cn = 3 + ax = fig.add_subplot(gs[2*n_total_cn-8, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(2,1)], map_cn[(3,0)]]).reshape((1,-1)), columns=["{2,1}", "{3,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + # total cn = 4 + ax = fig.add_subplot(gs[2*n_total_cn-10, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(2,2)], map_cn[(3,1)], map_cn[(4,0)]]).reshape((1,-1)), columns=["{2,2}", "{3,1}", "{4,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + # total cn = 5 + ax = fig.add_subplot(gs[2*n_total_cn-12, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(3,2)], map_cn[(4,1)], map_cn[(5,0)]]).reshape((1,-1)), columns=["{3,2}", "{4,1}", "{5,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + # total cn = 6 + ax = fig.add_subplot(gs[2*n_total_cn-14, :]) + seaborn.heatmap( pd.DataFrame(np.array([map_cn[(3,3)], map_cn[(4,2)], map_cn[(5,1)], map_cn[(6,0)]]).reshape((1,-1)), columns=["{3,3}", "{4,2}", "{5,1}", "{6,0}"]), vmin=0, vmax=len(colors), cmap=cmap, cbar=False, linewidths=1, linecolor="black" ) + ax.set_yticks([]) + ax.set_xticklabels(ax.get_xticklabels(), position=(0,shift_y)) + + return fig + + +def plot_acn_withhighlight(cn_file, df_highlight_events, ax_handle, clone_ids=None, clone_names=None, add_chrbar=True, chrbar_thickness=0.1, add_legend=True, remove_xticks=True): + """ + df_highlight_events: dataframe with columns: ["BinSTART", "BinEND", "involved_clones"] + """ + # full color palette + palette,_ = get_full_palette() + + # read CN profiles + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + print(final_clone_ids) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + + found = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + found += list(zip(major, minor)) + found = list(set(found)) + found.sort() + + # map CN to single digit number + map_cn = {x:i for i,x in enumerate(found)} + cnv_mapped = [] + ploidy = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + cnv_mapped.append( [map_cn[(major[i], minor[i])] for i in range(len(major))] ) + ploidy.append( np.mean(major + minor) ) + cnv_mapped = pd.DataFrame( np.array(cnv_mapped), index=[f"clone {cid}" for cid in final_clone_ids]) + ploidy = pd.DataFrame(np.around(np.array(ploidy), decimals=2).reshape(-1,1), index=[f"clone {cid}" for cid in final_clone_ids]) + chr_ids = df_cnv.CHR + + colors = [palette[c] for c in found] + if clone_ids is None: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in final_clone_ids] + rename_cnv_mapped = pd.DataFrame(cnv_mapped.values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(final_clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + else: + tmp_ploidy = [ploidy.loc[f"clone {cid}"].values[0] for cid in clone_ids] + if clone_names is None: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"clone {cid}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + else: + rename_cnv_mapped = pd.DataFrame(cnv_mapped.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"{clone_names[c]}\nploidy {tmp_ploidy[c]}" for c,cid in enumerate(clone_ids)]) + seaborn.heatmap(rename_cnv_mapped, cmap=LinearSegmentedColormap.from_list('multi-level', colors, len(colors)), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + + for i in range(df_highlight_events.shape[0]): + involved_clones = df_highlight_events.involved_clones.values[i] + # interval start and end + interval = [df_highlight_events.BinSTART.values[i], df_highlight_events.BinEND.values[i]] + if clone_ids is None: + for c, cid in enumerate(final_clone_ids): + if not cid in involved_clones: + continue + y1 = c + y2 = c+1 + ax_handle.fill_between( np.arange(interval[0], interval[1]), y1, y2, color="none", edgecolor="black", linewidth=2) + else: + for c, cid in enumerate(clone_ids): + if not cid in involved_clones: + continue + y1 = c + y2 = c+1 + ax_handle.fill_between( np.arange(interval[0], interval[1]), y1, y2, color="none", edgecolor="black", linewidth=2) + + if add_chrbar: + # add chr color + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + lut = {c:next(chr_palette) for c in np.unique(chr_ids.values)} + col_colors = chr_ids.map(lut) + for i, color in enumerate(col_colors): + ax_handle.add_patch(plt.Rectangle(xy=(i, 1.01), width=1, height=chrbar_thickness, color=color, lw=0, transform=ax_handle.get_xaxis_transform(), clip_on=False, rasterized=True)) + + for c in np.unique(chr_ids.values): + interval = np.where(chr_ids.values == c)[0] + mid = np.percentile(interval, 45) + ax_handle.text(mid-10, 1.04, str(c), transform=ax_handle.get_xaxis_transform()) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, + color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + ax_handle.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1 - 0.1 * min(0, rename_cnv_mapped.shape[0]-6))) + return ax_handle + + +def plot_total_cn(df_cnv, ax_handle, df_highlight_events=None, palette_mode=6, clone_ids=None, clone_names=None, add_chrbar=True, chrbar_thickness=0.1, add_legend=True, legend_position="upper left", remove_xticks=True): + """ + df_cnv : pandas.DataFrame + Each row is a genomic bin, containing columns "CHR", "clone {cid}" for each clone id. + palette_mode : int + Either 6 for 6-state palette, or 3 for 3-state palette. + """ + chr_ids = df_cnv.CHR + + # create a cmap that map "amp" to #B44F3D, "bamp" to #E18073, "bdel" to #A0CEEA, "del" to #4F69DF, "loh" to #738B2D + if palette_mode == 6: + full_palette = {"amp":"#B44F3D", "bamp":"#E18073", "bdel":"#A0CEEA", "del":"#4F69DF", "loh":"#738B2D", "neu":"lightgrey"} + else: + full_palette = {"amp":"#B44F3D", "del":"#4F69DF", "neu":"lightgrey"} + + if clone_ids is None: + found = np.unique(df_cnv.iloc[:, df_cnv.columns.str.startswith("clone")].values.flatten()) + lut = {x:i for i,x in enumerate(found)} + palette = matplotlib.colors.ListedColormap([full_palette[x] for x in found]) + df_cnv_mapped = df_cnv.iloc[:, df_cnv.columns.str.startswith("clone")].replace(lut) + df_cnv_mapped = df_cnv_mapped.T + seaborn.heatmap(df_cnv_mapped, cmap=palette, linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + else: + found = np.unique(df_cnv[[f"clone {cid}" for cid in clone_ids]].values.flatten()) + lut = {x:i for i,x in enumerate(found)} + palette = matplotlib.colors.ListedColormap([full_palette[x] for x in found]) + df_cnv_mapped = df_cnv[[f"clone {cid}" for cid in clone_ids]].replace(lut) + df_cnv_mapped = df_cnv_mapped.T + if not clone_names is None: + df_cnv_mapped.rename(index={f"clone {cid}":clone_names[i] for i,cid in enumerate(clone_ids)}, inplace=True) + seaborn.heatmap(df_cnv_mapped, cmap=palette, linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + + if not df_highlight_events is None: + final_clone_ids = [x.split(" ")[1] for x in df_cnv.columns if x.startswith("clone")] + for i in range(df_highlight_events.shape[0]): + involved_clones = df_highlight_events.involved_clones.values[i] + # interval start and end + interval = [df_highlight_events.BinSTART.values[i], df_highlight_events.BinEND.values[i]] + if clone_ids is None: + for c, cid in enumerate(final_clone_ids): + if not cid in involved_clones: + continue + y1 = c + y2 = c+1 + ax_handle.fill_between( np.arange(interval[0], interval[1]), y1, y2, color="none", edgecolor="black", linewidth=2) + else: + for c, cid in enumerate(clone_ids): + if not cid in involved_clones: + continue + y1 = c + y2 = c+1 + ax_handle.fill_between( np.arange(interval[0], interval[1]), y1, y2, color="none", edgecolor="black", linewidth=2) + + if add_chrbar: + # add chr color + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + lut = {c:next(chr_palette) for c in np.unique(chr_ids.values)} + col_colors = chr_ids.map(lut) + for i, color in enumerate(col_colors): + ax_handle.add_patch(plt.Rectangle(xy=(i, 1 + 0.02*chrbar_thickness), width=1, height=chrbar_thickness, color=color, lw=0, transform=ax_handle.get_xaxis_transform(), clip_on=False, rasterized=True)) + + for c in np.unique(chr_ids.values): + interval = np.where(chr_ids.values == c)[0] + mid = np.percentile(interval, 45) + ax_handle.text(mid-10, 1 + 0.2*chrbar_thickness, str(c), transform=ax_handle.get_xaxis_transform()) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + if add_legend: + if palette_mode == 6: + a0 = plt.arrow(0,0, 0,0, color='#B44F3D') + a1 = plt.arrow(0,0, 0,0, color='#E18073') + a2 = plt.arrow(0,0, 0,0, color='lightgrey') + a3 = plt.arrow(0,0, 0,0, color='#A0CEEA') + a4 = plt.arrow(0,0, 0,0, color='#4F69DF') + a5 = plt.arrow(0,0, 0,0, color='#738B2D') + if legend_position == "upper left": + ax_handle.legend([a0, a1, a2, a3, a4, a5], ["amp", "bamp", "neu", "bdel", "del", "loh"], loc='upper left', bbox_to_anchor=(1,1 - 0.1 * min(0, df_cnv_mapped.shape[0]-5))) + else: + ax_handle.legend([a0, a1, a2, a3, a4, a5], ["amp", "bamp", "neu", "bdel", "del", "loh"], loc='lower center', bbox_to_anchor=(0.5, -0.25), ncol=6) + else: + a0 = plt.arrow(0,0, 0,0, color='#B44F3D') + a1 = plt.arrow(0,0, 0,0, color='lightgrey') + a2 = plt.arrow(0,0, 0,0, color='#4F69DF') + if legend_position == "upper left": + ax_handle.legend([a0, a1, a2], ["amp", "neu", "del"], loc='upper left', bbox_to_anchor=(1,1 - 0.1 * min(0, df_cnv_mapped.shape[0]-2))) + else: + ax_handle.legend([a0, a1, a2], ["amp", "neu", "del"], loc='lower center', bbox_to_anchor=(0.5, -0.25), ncol=3) + + return ax_handle + + +def plot_amp_del(cn_file, ax_handle, clone_ids=None, clone_names=None, add_chrbar=True, chrbar_thickness=0.1, add_legend=True, remove_xticks=True): + # define color palette that maps 0 to lightgrey, -2 and -1 to blues with increasing intensity, and 1 and 2 to reds with increasing intensity + palette_map = {-2+i:x for i,x in enumerate(seaborn.color_palette("coolwarm", 5).as_hex())} + + # read CN profiles + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + + # compute the relative copy number with respect to the median copy number per clone + df_cnv_rel = [] + for cid in final_clone_ids: + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + median_copy = np.median(major + minor) + # clamp the relative copy number major + minor - median_copy to [-2,2] + df_cnv_rel.append( np.minimum(2, np.maximum(-2, major + minor - median_copy)) ) + df_cnv_rel = pd.DataFrame( np.array(df_cnv_rel), index=[f"clone {cid}" for cid in final_clone_ids]) + + # plot heatmap + if clone_ids is None: + rename_cnv_mapped = pd.DataFrame(df_cnv_rel.values, index=[f"clone {cid}" for c,cid in enumerate(final_clone_ids)]) + unique_cnv_values = np.unique(rename_cnv_mapped.values) + seaborn.heatmap(rename_cnv_mapped, cmap=ListedColormap([palette_map[x] for x in unique_cnv_values]), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + else: + if clone_names is None: + rename_cnv_mapped = pd.DataFrame(df_cnv_rel.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"clone {cid}" for c,cid in enumerate(clone_ids)]) + else: + rename_cnv_mapped = pd.DataFrame(df_cnv_rel.loc[[f"clone {cid}" for cid in clone_ids]].values, index=[f"{clone_names[c]}" for c,cid in enumerate(clone_ids)]) + unique_cnv_values = np.unique(rename_cnv_mapped.values) + seaborn.heatmap(rename_cnv_mapped, cmap=ListedColormap([palette_map[x] for x in unique_cnv_values]), linewidths=0, cbar=False, rasterized=True, ax=ax_handle) + + if add_chrbar: + chr_ids = df_cnv.CHR + # add chr color + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + lut = {c:next(chr_palette) for c in np.unique(chr_ids.values)} + col_colors = chr_ids.map(lut) + for i, color in enumerate(col_colors): + ax_handle.add_patch(plt.Rectangle(xy=(i, 1.01), width=1, height=chrbar_thickness, color=color, lw=0, transform=ax_handle.get_xaxis_transform(), clip_on=False, rasterized=True)) + + for c in np.unique(chr_ids.values): + interval = np.where(chr_ids.values == c)[0] + mid = np.percentile(interval, 45) + ax_handle.text(mid-10, 1.04, str(c), transform=ax_handle.get_xaxis_transform()) + + ax_handle.set_yticklabels(ax_handle.get_yticklabels(), rotation=0) + if remove_xticks: + ax_handle.set_xticks([]) + + # add legend corresponding to palette + if add_legend: + a0 = plt.arrow(0,0, 0,0, color=palette_map[-2]) + a1 = plt.arrow(0,0, 0,0, color=palette_map[-1]) + a2 = plt.arrow(0,0, 0,0, color=palette_map[0]) + a3 = plt.arrow(0,0, 0,0, color=palette_map[1]) + a4 = plt.arrow(0,0, 0,0, color=palette_map[2]) + ax_handle.legend([a0, a1, a2, a3, a4], ['-2 and below','-1','0','1', '2 and above'], ncol=1, loc='upper left', bbox_to_anchor=(1,1)) + + return ax_handle + + + +def plot_rdr_baf(configuration_file, r_hmrf_initialization, cn_file, clone_ids=None, clone_names=None, remove_xticks=True, rdr_ylim=5, chrtext_shift=-0.3, base_height=3.2, pointsize=15, linewidth=1, palette="chisel"): + # full palette + chisel_palette, ordered_acn = get_full_palette() + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [chisel_palette[c] for c in ordered_acn] + + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # load allele specific integer copy numbers + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + if not '0' in final_clone_ids: + final_clone_ids = np.array(['0'] + list(final_clone_ids)) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + unique_chrs = np.unique(df_cnv.CHR.values) + + # load data + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + dat = np.load(f"{outdir}/binned_data.npz", allow_pickle=True) + lengths = dat["lengths"] + single_X = dat["single_X"] + single_base_nb_mean = dat["single_base_nb_mean"] + single_total_bb_RD = dat["single_total_bb_RD"] + single_tumor_prop = dat["single_tumor_prop"] + res_combine = dict( np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + + n_states = res_combine["new_p_binom"].shape[0] + + assert single_X.shape[0] == df_cnv.shape[0] + + clone_index = [np.where(res_combine["new_assignment"] == c)[0] for c,cid in enumerate(final_clone_ids)] + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop) + n_obs = X.shape[0] + nonempty_clones = np.where(np.sum(total_bb_RD, axis=0) > 0)[0] + + # plotting all clones + if clone_ids is None: + fig, axes = plt.subplots(2*len(nonempty_clones), 1, figsize=(20, base_height*len(nonempty_clones)), dpi=200, facecolor="white") + for s,c in enumerate(nonempty_clones): + cid = final_clone_ids[c] + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + + # plot points + segments, labs = get_intervals(res_combine["pred_cnv"][:,c]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,0,c]/base_nb_mean[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=1, legend=False, ax=axes[2*s]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,0,c]/base_nb_mean[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", linewidth=linewidth, alpha=1, legend=False, ax=axes[2*s]) + axes[2*s].set_ylabel(f"clone {cid}\nRDR") + axes[2*s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[2*s].set_ylim([0,rdr_ylim]) + axes[2*s].set_xlim([0, n_obs]) + if remove_xticks: + axes[2*s].set_xticks([]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s+1]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s+1]) + axes[2*s+1].set_ylabel(f"clone {cid}\nphased AF") + axes[2*s+1].set_ylim([-0.1, 1.1]) + axes[2*s+1].set_yticks([0, 0.5, 1]) + axes[2*s+1].set_xlim([0, n_obs]) + if remove_xticks: + axes[2*s+1].set_xticks([]) + for i, seg in enumerate(segments): + axes[2*s].plot(seg, [np.exp(res_combine["new_log_mu"][labs[i],c]), np.exp(res_combine["new_log_mu"][labs[i],c])], c="black", linewidth=2) + axes[2*s+1].plot(seg, [res_combine["new_p_binom"][labs[i],c], res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + axes[2*s+1].plot(seg, [1-res_combine["new_p_binom"][labs[i],c], 1-res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + + for i in range(len(lengths)): + median_len = np.sum(lengths[:(i)]) * 0.55 + np.sum(lengths[:(i+1)]) * 0.45 + axes[-1].text(median_len-5, chrtext_shift, unique_chrs[i], transform=axes[-1].get_xaxis_transform()) + for k in range(2*len(nonempty_clones)): + axes[k].axvline(x=np.sum(lengths[:(i)]), c="grey", linewidth=1) + fig.tight_layout() + # plot a given clone + else: + fig, axes = plt.subplots(2*len(clone_ids), 1, figsize=(20, base_height*len(clone_ids)), dpi=200, facecolor="white") + for s,cid in enumerate(clone_ids): + c = np.where(final_clone_ids == cid)[0][0] + + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + + # plot points + segments, labs = get_intervals(res_combine["pred_cnv"][:,c]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,0,c]/base_nb_mean[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,0,c]/base_nb_mean[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s]) + axes[2*s].set_ylabel(f"clone {cid}\nRDR" if clone_names is None else f"clone {clone_names[s]}\nRDR") + axes[2*s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[2*s].set_ylim([0,5]) + axes[2*s].set_xlim([0, n_obs]) + if remove_xticks: + axes[2*s].set_xticks([]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s+1]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[2*s+1]) + axes[2*s+1].set_ylabel(f"clone {cid}\nphased AF" if clone_names is None else f"clone {clone_names[s]}\nphased AF") + axes[2*s+1].set_ylim([-0.1, 1.1]) + axes[2*s+1].set_yticks([0, 0.5, 1]) + axes[2*s+1].set_xlim([0, n_obs]) + if remove_xticks: + axes[2*s+1].set_xticks([]) + for i, seg in enumerate(segments): + axes[2*s].plot(seg, [np.exp(res_combine["new_log_mu"][labs[i],c]), np.exp(res_combine["new_log_mu"][labs[i],c])], c="black", linewidth=2) + axes[2*s+1].plot(seg, [res_combine["new_p_binom"][labs[i],c], res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + axes[2*s+1].plot(seg, [1-res_combine["new_p_binom"][labs[i],c], 1-res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + + for i in range(len(lengths)): + median_len = np.sum(lengths[:(i)]) * 0.55 + np.sum(lengths[:(i+1)]) * 0.45 + axes[-1].text(median_len-5, chrtext_shift, unique_chrs[i], transform=axes[-1].get_xaxis_transform()) + for k in range(2*len(clone_ids)): + axes[k].axvline(x=np.sum(lengths[:(i)]), c="grey", linewidth=1) + fig.tight_layout() + + return fig + + + +def plot_baf(configuration_file, r_hmrf_initialization, cn_file, clone_ids=None, clone_names=None, remove_xticks=True, rdr_ylim=5, chrtext_shift=-0.3, base_height=3.2, pointsize=15, linewidth=1, palette="chisel"): + # full palette + chisel_palette, ordered_acn = get_full_palette() + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [chisel_palette[c] for c in ordered_acn] + + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # load allele specific integer copy numbers + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_cnv.columns[3:] ]) + if not '0' in final_clone_ids: + final_clone_ids = np.array(['0'] + list(final_clone_ids)) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + unique_chrs = np.unique(df_cnv.CHR.values) + + # load data + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + dat = np.load(f"{outdir}/binned_data.npz", allow_pickle=True) + lengths = dat["lengths"] + single_X = dat["single_X"] + single_base_nb_mean = dat["single_base_nb_mean"] + single_total_bb_RD = dat["single_total_bb_RD"] + single_tumor_prop = dat["single_tumor_prop"] + res_combine = dict( np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + + n_states = res_combine["new_p_binom"].shape[0] + + assert single_X.shape[0] == df_cnv.shape[0] + + clone_index = [np.where(res_combine["new_assignment"] == c)[0] for c,cid in enumerate(final_clone_ids)] + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop) + n_obs = X.shape[0] + nonempty_clones = np.where(np.sum(total_bb_RD, axis=0) > 0)[0] + + # plotting all clones + if clone_ids is None: + fig, axes = plt.subplots(len(nonempty_clones), 1, figsize=(20, base_height*len(nonempty_clones)), dpi=200, facecolor="white") + for s,c in enumerate(nonempty_clones): + cid = final_clone_ids[c] + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + + # plot points + segments, labs = get_intervals(res_combine["pred_cnv"][:,c]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + axes[s].set_ylabel(f"clone {cid}\nphased AF") + axes[s].set_ylim([-0.1, 1.1]) + axes[s].set_yticks([0, 0.5, 1]) + axes[s].set_xlim([0, n_obs]) + if remove_xticks: + axes[s].set_xticks([]) + for i, seg in enumerate(segments): + axes[s].plot(seg, [res_combine["new_p_binom"][labs[i],c], res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + axes[s].plot(seg, [1-res_combine["new_p_binom"][labs[i],c], 1-res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + + for i in range(len(lengths)): + median_len = np.sum(lengths[:(i)]) * 0.55 + np.sum(lengths[:(i+1)]) * 0.45 + axes[-1].text(median_len-5, chrtext_shift, unique_chrs[i], transform=axes[-1].get_xaxis_transform()) + for k in range(len(nonempty_clones)): + axes[k].axvline(x=np.sum(lengths[:(i)]), c="grey", linewidth=1) + fig.tight_layout() + # plot a given clone + else: + fig, axes = plt.subplots(2*len(clone_ids), 1, figsize=(20, base_height*len(clone_ids)), dpi=200, facecolor="white") + for s,cid in enumerate(clone_ids): + c = np.where(final_clone_ids == cid)[0][0] + + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + + # plot points + segments, labs = get_intervals(res_combine["pred_cnv"][:,c]) + if palette == "chisel": + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + else: + seaborn.scatterplot(x=np.arange(X[:,1,c].shape[0]), y=X[:,1,c]/total_bb_RD[:,c], \ + hue=pd.Categorical(res_combine["pred_cnv"][:,c], categories=np.arange(n_states), ordered=True), \ + palette=palette, s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + axes[s].set_ylabel(f"clone {cid}\nphased AF" if clone_names is None else f"clone {clone_names[s]}\nphased AF") + axes[s].set_ylim([-0.1, 1.1]) + axes[s].set_yticks([0, 0.5, 1]) + axes[s].set_xlim([0, n_obs]) + if remove_xticks: + axes[s].set_xticks([]) + for i, seg in enumerate(segments): + axes[s].plot(seg, [res_combine["new_p_binom"][labs[i],c], res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + axes[s].plot(seg, [1-res_combine["new_p_binom"][labs[i],c], 1-res_combine["new_p_binom"][labs[i],c]], c="black", linewidth=2) + + for i in range(len(lengths)): + median_len = np.sum(lengths[:(i)]) * 0.55 + np.sum(lengths[:(i+1)]) * 0.45 + axes[-1].text(median_len-5, chrtext_shift, unique_chrs[i], transform=axes[-1].get_xaxis_transform()) + for k in range(2*len(clone_ids)): + axes[k].axvline(x=np.sum(lengths[:(i)]), c="grey", linewidth=1) + fig.tight_layout() + + return fig + + +def plot_rdr_baf_from_df(df, clone_ids=None, clone_names=None, base_height=3.2, rdr_ylim=3, baf_ylim=0.5, baf_yticks=None, linewidth=0, pointsize=30, chrtext_shift=-0.3, add_legend=False, remove_xticks=True): + """ + Attributes + ---------- + df : pandas.DataFrame + dataframe with columns: CHR, clone1 RD, clone1 BAF, clone1 A, clone1 B, ... for each clone + """ + # full palette + chisel_palette, ordered_acn = get_full_palette() + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [chisel_palette[c] for c in ordered_acn] + + # load allele specific integer copy numbers + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df.columns if "RD" in x ]) + assert (clone_ids is None) or np.all([ (cid in final_clone_ids) for cid in clone_ids]) + unique_chrs = np.unique(df.CHR.values) + + if clone_ids is None: + fig, axes = plt.subplots(2*len(final_clone_ids), 1, figsize=(20, base_height*len(final_clone_ids)), dpi=200, facecolor="white") + for s,cid in enumerate(final_clone_ids): + # major and minor allele copies give the hue + major = np.maximum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + minor = np.minimum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + + seaborn.scatterplot(x=np.arange(df.shape[0]), y=df[f'clone{cid} RD'].values, \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=0.8, legend=False, ax=axes[2*s]) + axes[2*s].set_ylabel(f"clone {cid}\nRDR") + axes[2*s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[2*s].set_ylim([0,rdr_ylim]) + axes[2*s].set_xlim([0, df.shape[0]]) + if remove_xticks: + axes[2*s].set_xticks([]) + seaborn.scatterplot(x=np.arange(df.shape[0]), y=df[f"clone{cid} BAF"].values, \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=0.8, legend=False, ax=axes[2*s+1]) + axes[2*s+1].set_ylabel(f"clone {cid}\nphased AF") + axes[2*s+1].set_ylim([-0.1, baf_ylim]) + if baf_yticks is None: + axes[2*s+1].set_yticks(np.arange(0, baf_ylim, 0.1)) + else: + axes[2*s+1].set_yticks(baf_yticks) + axes[2*s+1].set_xlim([0, df.shape[0]]) + if remove_xticks: + axes[2*s+1].set_xticks([]) + + for i in unique_chrs: + median_len = np.percentile(np.where(df.CHR.values == i)[0], 45) + max_len = np.max(np.where(df.CHR.values == i)[0]) + axes[-1].text(median_len-5, chrtext_shift, i, transform=axes[-1].get_xaxis_transform()) + if max_len + 1 < df.shape[0]: + for k in range(2*len(final_clone_ids)): + axes[k].axvline(x=max_len, c="grey", linewidth=1) + # plot a given clone + else: + fig, axes = plt.subplots(2*len(clone_ids), 1, figsize=(20, base_height*len(clone_ids)), dpi=200, facecolor="white") + for s,cid in enumerate(clone_ids): + # major and minor allele copies give the hue + major = np.maximum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + minor = np.minimum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + + # plot points + seaborn.scatterplot(x=np.arange(df.shape[0]), y=df[f'clone{cid} RD'].values, \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=0.8, legend=False, ax=axes[2*s]) + axes[2*s].set_ylabel(f"clone {cid}\nRDR" if clone_names is None else f"clone {clone_names[s]}\nRDR") + axes[2*s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[2*s].set_ylim([0,rdr_ylim]) + axes[2*s].set_xlim([0, df.shape[0]]) + if remove_xticks: + axes[2*s].set_xticks([]) + seaborn.scatterplot(x=np.arange(df.shape[0]), y=df[f'clone{cid} BAF'].values, \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=0.8, legend=False, ax=axes[2*s+1]) + axes[2*s+1].set_ylabel(f"clone {cid}\nphased AF" if clone_names is None else f"clone {clone_names[s]}\nphased AF") + axes[2*s+1].set_ylim([-0.1, baf_ylim]) + if baf_yticks is None: + axes[2*s+1].set_yticks(np.arange(0, baf_ylim, 0.1)) + else: + axes[2*s+1].set_yticks(baf_yticks) + axes[2*s+1].set_xlim([0, df.shape[0]]) + if remove_xticks: + axes[2*s+1].set_xticks([]) + + for i in unique_chrs: + median_len = np.percentile(np.where(df.CHR.values == i)[0], 45) + max_len = np.max(np.where(df.CHR.values == i)[0]) + axes[-1].text(median_len-5, chrtext_shift, i, transform=axes[-1].get_xaxis_transform()) + if max_len + 1 < df.shape[0]: + for k in range(2*len(clone_ids)): + axes[k].axvline(x=max_len, c="grey", linewidth=1) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, + color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + axes[0].legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1)) + + fig.tight_layout() + fig.subplots_adjust(hspace=0.1) + return fig, axes + + +def plot_2dscatter_rdrbaf(configuration_file, r_hmrf_initialization, cn_file, clone_ids=None, rdr_ylim=5, base_width=3.2, pointsize=15): + # full palette + palette, ordered_acn = get_full_palette() + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [palette[c] for c in ordered_acn] + + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # load allele specific integer copy numbers + df_cnv = pd.read_csv(cn_file, header=0, sep="\t") + n_final_clones = int(df_cnv.columns[-1].split(" ")[0][5:]) + 1 + assert (clone_ids is None) or np.all([cid <= n_final_clones for cid in clone_ids]) + unique_chrs = np.unique(df_cnv.CHR.values) + + # load data + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + dat = np.load(f"{outdir}/binned_data.npz", allow_pickle=True) + lengths = dat["lengths"] + single_X = dat["single_X"] + single_base_nb_mean = dat["single_base_nb_mean"] + single_total_bb_RD = dat["single_total_bb_RD"] + single_tumor_prop = dat["single_tumor_prop"] + res_combine = dict( np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz", allow_pickle=True) ) + + assert single_X.shape[0] == df_cnv.shape[0] + + clone_index = [np.where(res_combine["new_assignment"] == c)[0] for c in range(len( np.unique(res_combine["new_assignment"]) ))] + if config["tumorprop_file"] is None: + X, base_nb_mean, total_bb_RD = merge_pseudobulk_by_index(single_X, single_base_nb_mean, single_total_bb_RD, clone_index) + tumor_prop = None + else: + X, base_nb_mean, total_bb_RD, tumor_prop = merge_pseudobulk_by_index_mix(single_X, single_base_nb_mean, single_total_bb_RD, clone_index, single_tumor_prop) + n_obs = X.shape[0] + + # plotting all clones + if clone_ids is None: + fig, axes = plt.subplots(1, X.shape[2], figsize=(base_width*X.shape[2], base_width), dpi=200, facecolor="white") + for s in range(X.shape[2]): + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{s} A"].values, df_cnv[f"clone{s} B"].values) + minor = np.minimum(df_cnv[f"clone{s} A"].values, df_cnv[f"clone{s} B"].values) + + # plot points + seaborn.scatterplot(x=X[:,1,s]/total_bb_RD[:,s], y=X[:,0,s]/base_nb_mean[:,s], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + axes[s].set_xlabel(f"clone {s}\nphased AF") + axes[s].set_xlim([-0.1, 1.1]) + axes[s].set_xticks([0, 0.5, 1]) + axes[s].set_ylabel(f"clone {s}\nRDR") + axes[s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[s].set_ylim([0,5]) + fig.tight_layout() + # plot a given clone + else: + fig, axes = plt.subplots(1, len(clone_ids), figsize=(base_width*len(clone_ids), base_width), dpi=200, facecolor="white") + for s,cid in enumerate(clone_ids): + # major and minor allele copies give the hue + major = np.maximum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + minor = np.minimum(df_cnv[f"clone{cid} A"].values, df_cnv[f"clone{cid} B"].values) + + # plot points + seaborn.scatterplot(x=X[:,1,cid]/total_bb_RD[:,cid], y=X[:,0,cid]/base_nb_mean[:,cid], \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", alpha=0.8, legend=False, ax=axes[s]) + axes[s].set_xlabel(f"clone {cid}\nphased AF") + axes[s].set_xlim([-0.1, 1.1]) + axes[s].set_xticks([0, 0.5, 1]) + axes[s].set_ylabel(f"clone {cid}\nRDR") + axes[s].set_yticks(np.arange(1, rdr_ylim, 1)) + axes[s].set_ylim([0,5]) + fig.tight_layout() + + return fig + + +def plot_2dscatter_rdrbaf_from_df(df, axes, cid, cname=None, baf_xlim=0.51, rdr_ylim=3, pointsize=15, linewidth=1, add_legend=False): + """ + Attributes + ---------- + df : pandas.DataFrame + dataframe with columns: clone1 RD, clone1 BAF, clone1 A, clone1 B, ... for each clone + """ + # full palette + palette, ordered_acn = get_full_palette() + map_cn = {x:i for i,x in enumerate(ordered_acn)} + colors = [palette[c] for c in ordered_acn] + + final_clone_ids = np.unique([ x.split(" ")[0][5:] for x in df.columns if "RD" in x ]) + assert cid in final_clone_ids + unique_chrs = np.unique(df.CHR.values) + + # major and minor allele copies give the hue + major = np.maximum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + minor = np.minimum(df[f"clone{cid} A"].values, df[f"clone{cid} B"].values) + + # plot points + seaborn.scatterplot(x=df[f'clone{cid} BAF'].values, y=df[f'clone{cid} RD'].values, \ + hue=pd.Categorical([map_cn[(major[i], minor[i])] for i in range(len(major))], categories=np.arange(len(ordered_acn)), ordered=True), \ + palette=seaborn.color_palette(colors), s=pointsize, edgecolor="black", linewidth=linewidth, alpha=0.8, legend=False, ax=axes) + axes.set_xlabel(f"clone {cid}\nphased AF" if cname is None else f"{cname}\nphased AF") + axes.set_xlim([-0.02, baf_xlim]) + axes.set_xticks(np.arange(0, baf_xlim, 0.1)) + axes.set_ylabel(f"clone {cid}\nRDR" if cname is None else f"{cname}\nRDR") + axes.set_yticks(np.arange(1, rdr_ylim, 1)) + axes.set_ylim([0,rdr_ylim]) + + if add_legend: + a00 = plt.arrow(0,0, 0,0, + color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + axes.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=2, loc='upper left', bbox_to_anchor=(1,1)) + + + +def plot_clones_in_space(coords, assignment, sample_list=None, sample_ids=None, palette="Set2", labels=None, label_coords=None, label_sample_ids=None): + if (sample_list is None) or (len(sample_list) == 1): + fig, axes = plt.subplots(1, 1, figsize=(5.5,4), dpi=200, facecolor="white") + seaborn.scatterplot(x=coords[:,0], y=-coords[:,1], color="lightgrey", alpha=0.5, linewidth=0, s=15, ax=axes) + seaborn.scatterplot(x=coords[~assignment.isnull(),0], y=-coords[~assignment.isnull(),1], \ + hue=assignment[~assignment.isnull()], palette=palette, linewidth=0, s=15, ax=axes) + h,l = axes.get_legend_handles_labels() + axes.legend(h, l, loc="upper left", bbox_to_anchor=(1,1)) + + if not labels is None: + assert len(labels) == len(label_coords) + for i,c in enumerate(labels): + axes.text(label_coords[i][0]-4, -label_coords[i][1], c) + else: + unique_assignments = np.sort(np.unique(assignment[~assignment.isnull()].values)) + fig, axes = plt.subplots(1, len(sample_list), figsize=(5*len(sample_list)+0.5,4), dpi=200, facecolor="white") + for s, sname in enumerate(sample_list): + indexes = np.where(sample_ids == s)[0] + seaborn.scatterplot(x=coords[indexes,0], y=-coords[indexes,1], color="lightgrey", alpha=0.5, linewidth=0, s=15, ax=axes[s]) + if s + 1 != len(sample_list): + seaborn.scatterplot(x=coords[indexes,0][~assignment.iloc[indexes].isnull()], y=-coords[indexes,1][~assignment.iloc[indexes].isnull()], \ + hue=pd.Categorical(assignment.iloc[indexes][~assignment.iloc[indexes].isnull()], categories=unique_assignments, ordered=True), \ + palette=palette, linewidth=0, s=15, legend=False, ax=axes[s]) + else: + seaborn.scatterplot(x=coords[indexes,0][~assignment.iloc[indexes].isnull()], y=-coords[indexes,1][~assignment.iloc[indexes].isnull()], \ + hue=pd.Categorical(assignment.iloc[indexes][~assignment.iloc[indexes].isnull()], categories=unique_assignments, ordered=True), \ + palette=palette, linewidth=0, s=15, ax=axes[s]) + h,l = axes[s].get_legend_handles_labels() + axes[s].legend(h, l, loc="upper left", bbox_to_anchor=(1,1)) + + if not labels is None: + assert len(labels) == len(label_coords) and len(labels) == len(label_sample_ids) + for i,c in enumerate(labels): + s = label_sample_ids[i] + axes[s].text(label_coords[i][0]-4, -label_coords[i][1], c) + + fig.tight_layout() + + return fig + + +def plot_individual_spots_in_space(coords, assignment, single_tumor_prop=None, sample_list=None, sample_ids=None, base_width=4, base_height=3, palette="Set2"): + # combine coordinates across samples + shifted_coords = copy.copy(coords) + if not (sample_ids is None): + x_offset = 0 + for s,sname in enumerate(sample_list): + index = np.where(sample_ids == s)[0] + shifted_coords[index,0] = shifted_coords[index,0] + x_offset + x_offset += np.max(coords[index,0]) + 10 + + # number of clones and samples + final_clone_ids = np.unique(assignment[~assignment.isnull()].values) + n_final_clones = len(final_clone_ids) + n_samples = 1 if sample_list is None else len(sample_list) + + # remove nan of single_tumor_prop + if not single_tumor_prop is None: + copy_single_tumor_prop = copy.copy(single_tumor_prop) + copy_single_tumor_prop[np.isnan(copy_single_tumor_prop)] = 0.5 + + fig, axes = plt.subplots(1, 1, figsize=(base_width*n_samples, base_height), dpi=200, facecolor="white") + if "clone 0" in final_clone_ids: + colorlist = ['lightgrey'] + seaborn.color_palette("Set2", n_final_clones-1).as_hex() + else: + colorlist = seaborn.color_palette("Set2", n_final_clones).as_hex() + + for c,cid in enumerate(final_clone_ids): + idx = np.where( (assignment.values==cid) )[0] + if single_tumor_prop is None: + seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, color=colorlist[c], linewidth=0, legend=None, ax=axes) + else: + # cmap + this_full_cmap = seaborn.color_palette(f"blend:lightgrey,{colorlist[c]}", as_cmap=True) + quantile_colors = this_full_cmap(np.array([0, np.min(copy_single_tumor_prop[idx]), np.max(copy_single_tumor_prop[idx]), 1])) + quantile_colors = [matplotlib.colors.rgb2hex(x) for x in quantile_colors[1:-1]] + this_cmap = seaborn.color_palette(f"blend:{quantile_colors[0]},{quantile_colors[-1]}", as_cmap=True) + seaborn.scatterplot(x=shifted_coords[idx,0], y=-shifted_coords[idx,1], s=10, hue=copy_single_tumor_prop[idx], palette=this_cmap, linewidth=0, legend=None, ax=axes) + + legend_elements = [Line2D([0], [0], marker='o', color="w", markerfacecolor=colorlist[c], label=cid, markersize=10) for c,cid in enumerate(final_clone_ids)] + axes.legend(legend_elements, final_clone_ids, handlelength=0.1, loc="upper left", bbox_to_anchor=(1,1)) + axes.axis("off") + + fig.tight_layout() + return fig diff --git a/utils/filter_snps_forphasing.py b/utils/filter_snps_forphasing.py new file mode 100644 index 0000000..cd45c7c --- /dev/null +++ b/utils/filter_snps_forphasing.py @@ -0,0 +1,54 @@ +#!/bin/python + +import sys +import numpy as np +import pandas as pd +from pathlib import Path +import argparse + + +def main(cellsnplite_result_dir, eagle_out_dir, vaf_threshold=0.1): + cellsnp_base = [str(x) for x in Path(cellsnplite_result_dir).glob("cellSNP.base*")][0] + df_snp = pd.read_csv(cellsnp_base, comment="#", sep="\t", names=["tmpCHR", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO"]) + df_snp["CHROM"] = [f"chr{x}" for x in df_snp.tmpCHR] + df_snp["AD"] = [int(x.split(";")[0].split("=")[-1]) for x in df_snp.INFO] + df_snp["DP"] = [int(x.split(";")[1].split("=")[-1]) for x in df_snp.INFO] + df_snp["OTH"] = [int(x.split(";")[2].split("=")[-1]) for x in df_snp.INFO] + # remove records with DP == 0 + df_snp = df_snp[df_snp.DP > 0] + # keep het SNP (0.1 <= AD/DP <= 0.9) and hom ALT SNP (AD == DP >= 10) + # df_snp = df_snp[((df_snp.AD / df_snp.DP >= 0.1) & (df_snp.AD / df_snp.DP <= 0.9)) | ((df_snp.AD == df_snp.DP) & (df_snp.DP >= 10))] + df_snp = df_snp[((df_snp.AD >= 2) & (df_snp.DP - df_snp.AD >= 2) & (df_snp.AD / df_snp.DP >= vaf_threshold) & (df_snp.AD / df_snp.DP <= 1-vaf_threshold)) | ((df_snp.AD == df_snp.DP) & (df_snp.DP >= 10)) | ((df_snp.AD == 0) & (df_snp.DP >= 10))] + # add addition columns + df_snp["FORMAT"] = "GT" + # df_snp[f"{sample_id}"] = ["0/1" if row.AD < row.DP else "1/1" for i,row in df_snp.iterrows()] + gt_column = np.array(["0/0"] * df_snp.shape[0]) + gt_column[ (df_snp.AD == df_snp.DP) ] = "1/1" + gt_column[ (df_snp.AD > 0) & (df_snp.DP - df_snp.AD > 0) ] = "0/1" + df_snp["SAMPLE_ID"] = gt_column + # output chromosome to folder + for c in range(1, 23): + df = df_snp[ (df_snp.tmpCHR == c) | (df_snp.tmpCHR == str(c)) ] + # remove records that have duplicated snp_id + snp_id = [f"{row.tmpCHR}_{row.POS}_{row.REF}_{row.ALT}" for i,row in df.iterrows()] + df["snp_id"] = snp_id + df = df.groupby("snp_id").agg({"CHROM":"first", "POS":"first", "ID":"first", "REF":"first", "ALT":"first", "QUAL":"first", "FILTER":"first", \ + "INFO":"first", "FORMAT":"first", "SAMPLE_ID":"first", "AD":"sum", "DP":"sum", "OTH":"sum"}) + info = [f"AD={row.AD};DP={row.DP};OTH={row.OTH}" for i,row in df.iterrows()] + df["INFO"] = info + df = df[["CHROM", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO", "FORMAT", "SAMPLE_ID"]] + df.sort_values(by="POS", inplace=True) + fp = open(f"{eagle_out_dir}/chr{c}.vcf", 'w') + fp.write("##fileformat=VCFv4.2\n") + fp.write("##FORMAT=\n") + fp.write("#" + "\t".join(df.columns) + "\n") + df.to_csv(fp, sep="\t", index=False, header=False) + fp.close() + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--cellsnplite_result_dir", help="cellsnplite result directory", type=str) + parser.add_argument("-o", "--eagle_out_dir", help="eagle output directory", type=str) + parser.add_argument("-v", "--vaf_threshold", help="vaf threshold", default=0.1, type=float) + args = parser.parse_args() + main(args.cellsnplite_result_dir, args.eagle_out_dir, args.vaf_threshold) diff --git a/utils/get_snp_matrix.py b/utils/get_snp_matrix.py new file mode 100644 index 0000000..ec9eb09 --- /dev/null +++ b/utils/get_snp_matrix.py @@ -0,0 +1,187 @@ +#!/bin/python + +import sys +import numpy as np +import pandas as pd +from scipy.special import logsumexp +import scipy.io +from pathlib import Path +import json +import gzip +import pickle +from tqdm import trange +import copy +import argparse + + +def process_snp_phasing(cellsnp_folder, eagle_folder, outputfile): + # create a (snp_id, GT) map from eagle2 output + snp_gt_map = {} + for c in range(1, 23): + fname = [str(x) for x in Path(eagle_folder).glob("*chr{}.phased.vcf.gz".format(c))] + assert len(fname) > 0 + fname = fname[0] + tmpdf = pd.read_table(fname, compression = 'gzip', comment = '#', sep="\t", names=["CHR","POS","ID","REF","ALT","QUAL","FILTER","INFO","FORMAT","PHASE"]) + this_snp_ids = [ "{}_{}_{}_{}".format(c, row.POS, row.REF, row.ALT) for i,row in tmpdf.iterrows() ] + this_gt = list(tmpdf.iloc[:,-1]) + assert len(this_snp_ids) == len(this_gt) + snp_gt_map.update( {this_snp_ids[i]:this_gt[i] for i in range(len(this_gt))} ) + # cellsnp DP (read depth) and AD (alternative allele depth) + # first get a list of snp_id and spot barcodes + tmpdf = pd.read_csv(cellsnp_folder + "/cellSNP.base.vcf.gz", header=1, sep="\t") + snp_list = np.array([ "{}_{}_{}_{}".format(row["#CHROM"], row.POS, row.REF, row.ALT) for i,row in tmpdf.iterrows() ]) + tmpdf = pd.read_csv(cellsnp_folder + "/cellSNP.samples.tsv", header=None) + sample_list = np.array(list(tmpdf.iloc[:,0])) + # then get the DP and AD matrix + DP = scipy.io.mmread(cellsnp_folder + "/cellSNP.tag.DP.mtx").tocsr() + AD = scipy.io.mmread(cellsnp_folder + "/cellSNP.tag.AD.mtx").tocsr() + # remove SNPs that are not phased + is_phased = np.array([ (x in snp_gt_map) for x in snp_list ]) + DP = DP[is_phased,:] + AD = AD[is_phased,:] + snp_list = snp_list[is_phased] + # generate a new dataframe with columns (cell, snp_id, DP, AD, CHROM, POS, GT) + rows, cols = DP.nonzero() + cell = sample_list[cols] + snp_id = snp_list[rows] + DP_df = DP[DP.nonzero()].A.flatten() + AD_df = AD[DP.nonzero()].A.flatten() + GT = [snp_gt_map[x] for x in snp_id] + df = pd.DataFrame({"cell":cell, "snp_id":snp_id, "DP":DP_df, "AD":AD_df, \ + "CHROM":[int(x.split("_")[0]) for x in snp_id], "POS":[int(x.split("_")[1]) for x in snp_id], "GT":GT}) + df.to_csv(outputfile, sep="\t", index=False, header=True, compression={'method': 'gzip'}) + return df + + +def read_cell_by_snp(allele_counts_file): + df = pd.read_csv(allele_counts_file, sep="\t", header=0) + index = np.array([i for i,x in enumerate(df.GT) if x=="0|1" or x=="1|0"]) + df = df.iloc[index, :] + df.CHROM = df.CHROM.astype(int) + return df + + +def cell_by_gene_lefthap_counts(cellsnp_folder, eagle_folder, barcode_list): + # create a (snp_id, GT) map from eagle2 output + snp_gt_map = {} + for c in range(1, 23): + fname = [str(x) for x in Path(eagle_folder).glob("*chr{}.phased.vcf.gz".format(c))] + assert len(fname) > 0 + fname = fname[0] + tmpdf = pd.read_table(fname, compression = 'gzip', comment = '#', sep="\t", names=["CHR","POS","ID","REF","ALT","QUAL","FILTER","INFO","FORMAT","PHASE"]) + # only keep heterozygous SNPs + tmpdf = tmpdf[ (tmpdf.PHASE=="0|1") | (tmpdf.PHASE=="1|0") ] + this_snp_ids = (str(c) + "_" + tmpdf.POS.astype(str) +"_"+ tmpdf.REF +"_"+ tmpdf.ALT).values + this_gt = tmpdf.PHASE.values + assert len(this_snp_ids) == len(this_gt) + snp_gt_map.update( {this_snp_ids[i]:this_gt[i] for i in range(len(this_gt))} ) + + # cellsnp-lite output + cellsnp_base = [str(x) for x in Path(cellsnp_folder).glob("cellSNP.base*")][0] + df_snp = pd.read_csv(cellsnp_base, comment="#", sep="\t", names=["tmpCHR", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO"]) + df_snp['snp_id'] = df_snp.tmpCHR.astype(str) + "_" + df_snp.POS.astype(str) + "_" + df_snp.REF + "_" + df_snp.ALT + tmpdf = pd.read_csv(cellsnp_folder + "/cellSNP.samples.tsv", header=None) + sample_list = np.array(list(tmpdf.iloc[:,0])) + barcode_mapper = {x:i for i,x in enumerate(sample_list)} + # DP and AD + DP = scipy.io.mmread(cellsnp_folder + "/cellSNP.tag.DP.mtx").tocsr() + AD = scipy.io.mmread(cellsnp_folder + "/cellSNP.tag.AD.mtx").tocsr() + # retain only SNPs that are phased + is_phased = (df_snp.snp_id.isin(snp_gt_map)).values + df_snp = df_snp[is_phased] + df_snp['GT'] = [snp_gt_map[x] for x in df_snp.snp_id] + DP = DP[is_phased,:] + AD = AD[is_phased,:] + + # phasing + phased_AD = np.where( (df_snp.GT.values == "0|1").reshape(-1,1), AD.A, (DP-AD).A ) + phased_AD = scipy.sparse.csr_matrix(phased_AD) + + # re-order based on barcode_list + index = np.array([barcode_mapper[x] for x in barcode_list if x in barcode_mapper]) + DP = DP[:, index] + phased_AD = phased_AD[:, index] + + # returned matrix has shape (N_cells, N_snps), which is the transpose of the original matrix + return (DP-phased_AD).T, phased_AD.T, df_snp.snp_id.values + + +def cell_by_gene_lefthap_counts_v2(df_cell_snp, hg_table_file, gene_list, barcode_list): + # index of genes and barcodes in the current gene expression matrix + barcode_mapper = {x:i for i,x in enumerate(barcode_list)} + gene_mapper = {x:i for i,x in enumerate(gene_list)} + # make an numpy array for CHROM and POS in df_cell_snp + cell_snp_CHROM = np.array(df_cell_snp.CHROM) + cell_snp_POS = np.array(df_cell_snp.POS) + # read gene ranges in genome + # NOTE THAT THE FOLLOWING CODE REQUIRES hg_table_file IS SORTED BY GENOMIC POSITION! + df_genes = pd.read_csv(hg_table_file, header=0, index_col=0, sep="\t") + index = np.array([ i for i in range(df_genes.shape[0]) if (not "_" in df_genes.chrom.iloc[i]) and \ + (df_genes.chrom.iloc[i] != "chrX") and (df_genes.chrom.iloc[i] != "chrY") and (df_genes.chrom.iloc[i] != "chrM") and \ + (not "GL" in df_genes.chrom.iloc[i]) and (not "KI" in df_genes.chrom.iloc[i]) ]) + df_genes = df_genes.iloc[index, :] + tmp_gene_ranges = {df_genes.name2.iloc[i]:(int(df_genes.chrom.iloc[i][3:]), df_genes.cdsStart.iloc[i], df_genes.cdsEnd.iloc[i]) for i in np.arange(df_genes.shape[0]) } + gene_ranges = [(gname, tmp_gene_ranges[gname]) for gname in gene_list if gname in tmp_gene_ranges] + del tmp_gene_ranges + # aggregate snp counts to genes + N = np.unique(df_cell_snp.cell).shape[0] + G = len(gene_ranges) + i = 0 + j = 0 + cell_gene_snp_counts = [] + snp_ids = np.array(df_cell_snp.snp_id) + unique_snp_ids = df_cell_snp.snp_id.unique() + snp_id_mapper = {unique_snp_ids[i]:i for i in range(len(unique_snp_ids))} + N_snps = len(unique_snp_ids) + cell_snp_Aallele = np.zeros((len(barcode_list), N_snps)) + cell_snp_Ballele = np.zeros((len(barcode_list), N_snps)) + snp_gene_list = [""] * N_snps + for i in trange(df_cell_snp.shape[0]): + if df_cell_snp.GT.iloc[i] == "1|1" or df_cell_snp.GT.iloc[i] == "0|0": + continue + # check cell barcode + if not df_cell_snp.cell.iloc[i] in barcode_mapper: + continue + cell_idx = barcode_mapper[df_cell_snp.cell.iloc[i]] + # if the SNP is not within any genes + if j < len(gene_ranges) and (cell_snp_CHROM[i] < gene_ranges[j][1][0] or \ + (cell_snp_CHROM[i] == gene_ranges[j][1][0] and cell_snp_POS[i] < gene_ranges[j][1][1])): + continue + # if the SNP position passes gene j + while j < len(gene_ranges) and (cell_snp_CHROM[i] > gene_ranges[j][1][0] or \ + (cell_snp_CHROM[i] == gene_ranges[j][1][0] and cell_snp_POS[i] > gene_ranges[j][1][2])): + j += 1 + # if the SNP is within gene j, add the corresponding gene ID + if j < len(gene_ranges) and cell_snp_CHROM[i] == gene_ranges[j][1][0] and \ + cell_snp_POS[i] >= gene_ranges[j][1][1] and cell_snp_POS[i] <= gene_ranges[j][1][2]: + snp_gene_list[ snp_id_mapper[snp_ids[i]] ] = gene_ranges[j][0] + # add the SNP UMI count to the corresponding cell and loci + if df_cell_snp.GT.iloc[i] == "0|1": + cell_snp_Aallele[cell_idx, snp_id_mapper[snp_ids[i]]] = df_cell_snp.DP.iloc[i] - df_cell_snp.AD.iloc[i] + cell_snp_Ballele[cell_idx, snp_id_mapper[snp_ids[i]]] = df_cell_snp.AD.iloc[i] + elif df_cell_snp.GT.iloc[i] == "1|0": + cell_snp_Aallele[cell_idx, snp_id_mapper[snp_ids[i]]] = df_cell_snp.AD.iloc[i] + cell_snp_Ballele[cell_idx, snp_id_mapper[snp_ids[i]]] = df_cell_snp.DP.iloc[i] - df_cell_snp.AD.iloc[i] + + index = np.where(np.logical_and( np.sum(cell_snp_Aallele + cell_snp_Ballele, axis=0) > 0))[0] + cell_snp_Aallele = cell_snp_Aallele[:, index].astype(int) + cell_snp_Ballele = cell_snp_Ballele[:, index].astype(int) + snp_gene_list = np.array(snp_gene_list)[index] + unique_snp_ids = unique_snp_ids[index] + return cell_snp_Aallele, cell_snp_Ballele, snp_gene_list, unique_snp_ids + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-c", "--cellsnplite_result_dir", help="cellsnplite result directory", type=str) + parser.add_argument("-e", "--eagle_out_dir", help="eagle output directory", type=str) + parser.add_argument("-b", "--barcodefile", help="barcode file", type=str) + parser.add_argument("-o", "--outputdir", help="output directory", type=str) + args = parser.parse_args() + + barcode_list = list(pd.read_csv(args.barcodefile, header=None).iloc[:,0]) + cell_snp_Aallele, cell_snp_Ballele, unique_snp_ids = cell_by_gene_lefthap_counts(args.cellsnplite_result_dir, args.eagle_out_dir, barcode_list) + + scipy.sparse.save_npz(f"{args.outputdir}/cell_snp_Aallele.npz", cell_snp_Aallele) + scipy.sparse.save_npz(f"{args.outputdir}/cell_snp_Ballele.npz", cell_snp_Ballele) + np.save(f"{args.outputdir}/unique_snp_ids.npy", unique_snp_ids) diff --git a/utils/maya_plotter.py b/utils/maya_plotter.py new file mode 100644 index 0000000..78bfde5 --- /dev/null +++ b/utils/maya_plotter.py @@ -0,0 +1,619 @@ +#!/usr/bin/env python3.7 + +import sys, os +import argparse +import random +import warnings + +from itertools import cycle +from collections import defaultdict + +import numpy as np +import scipy +import scipy.cluster +import scipy.cluster.hierarchy as hier +import pandas as pd + +import matplotlib as mpl +mpl.use('Agg') +from matplotlib import pyplot as plt +import seaborn as sns + +from Utils import * +from Clusterizer import kclustering + +from matplotlib.colors import LinearSegmentedColormap + +orderchrs = (lambda x : int(''.join([l for l in x if l.isdigit()]))) +order = (lambda b : (orderchrs(b[0]), int(b[1]), int(b[2]))) + + +def parse_args(): + description = "Generate plots for the analysis of estimated RDRs and BAFs, inferred allele- and haplotype-specific copy numbers, and clones." + parser = argparse.ArgumentParser(description=description) + parser.add_argument("INPUT", type=str, help="Input file with combined RDR and BAF per bin and per cell") +# parser.add_argument("-m", "--clonemap", required=True, type=str, default=None, help="Clone map (default: not used, the cells will be clustered for plotting purposes)") + parser.add_argument("-m", "--clonemap", required=False, type=str, default=None, help="Clone map (default: not used, the cells will be clustered for plotting purposes)") + parser.add_argument("-f", "--figformat", required=False, type=str, default='png', help="Format of output figures (default: png, the only other option is pdf)") + parser.add_argument("-s", "--sample", required=False, type=int, default=20, help="Number of cells to sample (default: 20)") + parser.add_argument("--excludenoisy", required=False, default=False, action='store_true', help="Exclude noisy cells from plots (default: False)") + parser.add_argument("--gridsize", required=False, type=str, default='12,6', help="Grid dimenstions specified as comma-separated numbers (default: 12,6)") + parser.add_argument("--plotsize", required=False, type=str, default='5,1.5', help="Plot dimenstions for RDR-BAF plots, specified as comma-separated numbers (default: 5,1.5)") + parser.add_argument("--clussize", required=False, type=str, default='5,3', help="Grid dimenstions for clustered plots, specified as comma-separated numbers (default: 5,3)") + parser.add_argument("--xmax", required=False, type=float, default=None, help="Maximum x-axis value (default: None)") + parser.add_argument("--xmin", required=False, type=float, default=None, help="Minimum x-axis value (default: None)") + parser.add_argument("--ymax", required=False, type=float, default=None, help="Maximum x-axis value (default: None)") + parser.add_argument("--ymin", required=False, type=float, default=None, help="Minimum x-axis value (default: None)") + parser.add_argument("--seed", required=False, type=int, default=None, help="Random seed for replication (default: none)") + args = parser.parse_args() + + if not os.path.isfile(args.INPUT): + raise ValueError('ERROR: input file does not exist!') + if args.clonemap and not os.path.isfile(args.clonemap): + raise ValueError('ERROR: the provided clone map does not exist!') + if args.figformat not in ['pdf', 'png']: + raise ValueError('ERROR: figure format must be either pdf or png!') + if args.sample < 1: + raise ValueError('ERROR: number of sampled cells must be positive!') + if args.seed and args.seed < 0: + raise ValueError("Random seed must be positive or zero!") + else: + np.random.seed(args.seed) + + def get_size(s): + p = s.split(',') + if len(p) != 2: + raise ValueError('ERROR: wrong format for figure sizes!') + return tuple(map(float, p)) + + return { + 'input' : args.INPUT, + 'clonemap' : args.clonemap, + 'format' : args.figformat, + 'sample' : args.sample, + 'nonoisy' : args.excludenoisy, + 'gridsize' : get_size(args.gridsize), + 'plotsize' : get_size(args.plotsize), + 'clussize' : get_size(args.clussize), + 'xmax' : args.xmax, + 'xmin' : args.xmin, + 'ymax' : args.ymax, + 'ymin' : args.ymin + } + + +def main(): + log('Parsing and checking arguments') + args = parse_args() + log('\n'.join(['Arguments:'] + ['\t{} : {}'.format(a, args[a]) for a in args]), level='INFO') + + log('Reading input') + bins, pos, cells, iscorr = read_cells(args['input']) + log('Number of cells: {}'.format(len(cells)), level='INFO') + log('Number of bins: {}'.format(len(pos)), level='INFO') + + log('Setting style') + set_style(args) + + if args['clonemap']: + log('Reading clonemap') + index, clones, selected = clonemap_to_index(args['clonemap'], cells) + if all(selected[e] == 'None' for e in selected): + log('Cell will be re-clustered as no clone has been previously identified', level='WARN') + index, clones = clustering_tot(bins, pos, cells) + selected = dict(clones) + else: + log('Clustering cells') + index, clones = clustering_tot(bins, pos, cells) + selected = dict(clones) + + if args['nonoisy']: + log('Excluding noisy cells') + bins, pos, cells, index, clones, selected = exclude_noisy(bins, pos, cells, index, clones, selected) + log('Number of cells: {}'.format(len(cells)), level='INFO') + log('Number of bins: {}'.format(len(pos)), level='INFO') + + chosen = random.sample(list(enumerate(cells)), args['sample']) + chosen = [p[1] for p in sorted(chosen, key=(lambda x : x[0]))] + + log('Plotting RDR and mirrored BAF plots for {} random cells in rbplot_mirrored.{}'.format(args['sample'], args['format'])) + rbplot_mirrored(bins, chosen, args) + + log('Plotting clustered RDR plots for {} random cells in crdr.{}'.format(args['sample'], args['format'])) + crdr(bins, pos, chosen, args) + + log('Plotting clustered-mirrored BAF plots for {} random cells in cbaf.{}'.format(args['sample'], args['format'])) + cbaf(bins, pos, chosen, args) + + log('Plotting read-depth ratios in {}'.format('rdrs.' + args['format'])) + gridrdrs(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + log('Plotting B-allele frequencies in {}'.format('bafs.' + args['format'])) + gridbafs(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + log('Plotting total copy numbers in {}'.format('totalcn.' + args['format'])) + totalcns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting total copy numbers corrected by clones in {}'.format('totalcn-corrected.' + args['format'])) + totalcns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='totalcn-corrected.', val='CORR-CNS') + + log('Plotting LOH in {}'.format('loh.' + args['format'])) + loh(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting LOH corrected by clones in {}'.format('loh-corrected.' + args['format'])) + loh(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='loh-corrected.', val='CORR-CNS') + + log('Plotting A-specific copy numbers in {}'.format('Aspecificcn.' + args['format'])) + acns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting A-specific copy numbers corrected by clones in {}'.format('Aspecificcn-corrected.' + args['format'])) + acns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='Aspecificcn-corrected.', val='CORR-CNS') + + log('Plotting B-specific copy numbers in {}'.format('Bspecificcn.' + args['format'])) + bcns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting B-specific copy numbers corrected by clones in {}'.format('Bspecificcn-corrected.' + args['format'])) + bcns(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='Bspecificcn-corrected.', val='CORR-CNS') + + log('Plotting allele-specific copy numbers in {}'.format('allelecn.' + args['format'])) + states(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting allele-specific copy numbers corrected by clones in {}'.format('allelecn-corrected.' + args['format'])) + states(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='allelecn-corrected.', val='CORR-CNS') + + log('Plotting haplotype-specific copy numbers in {}'.format('haplotypecn.' + args['format'])) + minor(bins, pos, cells, index=index, clones=clones, selected=selected, args=args) + + if iscorr: + log('Plotting haplotype-specific copy numbers corrected by clones in {}'.format('haplotypecn-corrected.' + args['format'])) + minor(bins, pos, cells, index=index, clones=clones, selected=selected, args=args, out='haplotypecn-corrected.', val='CORR-CNS') + + log('KTHKBYE!') + + +def read_cells(f): + bins = defaultdict(lambda : dict()) + cells = set() + with open(f, 'r') as i: + p = i.readline().strip().split() + if len(p) == 12: + form = (lambda p : ((p[0], int(p[1]), int(p[2])), p[3], float(p[6]), float(p[9]), p[10], tuple(map(int, p[11].split('|'))))) + with open(f, 'r') as i: + for l in i: + if l[0] != '#' and len(l) > 1: + b, e, rdr, baf, c, cns = form(l.strip().split()) + bins[b][e] = {'RDR' : rdr, 'BAF' : baf, 'Cluster' : c, 'CNS' : cns} + cells.add(e) + pos = sorted(bins.keys(), key=order) + for x, b in enumerate(pos): + for e in cells: + bins[b][e]['Genome'] = x + return bins, pos, sorted(cells), False + elif len(p) == 13: + form = (lambda p : ((p[0], int(p[1]), int(p[2])), p[3], float(p[6]), float(p[9]), p[10], tuple(map(int, p[11].split('|'))), tuple(map(int, p[12].split('|'))))) + with open(f, 'r') as i: + for l in i: + if l[0] != '#' and len(l) > 1: + b, e, rdr, baf, c, cns, corr = form(l.strip().split()) + bins[b][e] = {'RDR' : rdr, 'BAF' : baf, 'Cluster' : c, 'CNS' : cns, 'CORR-CNS' : corr} + cells.add(e) + pos = sorted(bins.keys(), key=order) + for x, b in enumerate(pos): + for e in cells: + bins[b][e]['Genome'] = x + return bins, pos, sorted(cells), True + else: + raise ValueError("Input format is wrong: 12 or 13 fields expected but {} were found".format(len(p))) + + +def set_style(args): + plt.style.use('ggplot') + sns.set_style("whitegrid") + #plt.rcParams["font.family"] = "Times New Roman" + plt.rcParams["axes.grid"] = True + plt.rcParams["axes.edgecolor"] = "k" + plt.rcParams["axes.linewidth"] = 1.5 + + +def clonemap_to_index(f, cells): + clonemap = {} + selected = {} + with open(f, 'r') as i: + for l in (g for g in i if g[0] != '#' and len(g) > 1): + p = l.strip().split() + assert p[0] not in clonemap + clonemap[p[0]] = int(p[1]) + selected[p[0]] = p[2] + mapc = [(clonemap[e], e) for e in cells] + return [p[1] for p in sorted(mapc, key=(lambda x : x[0]))], clonemap, selected + + +def clustering_tot(bins, pos, cells): + data = [[bins[b][e]['CNS'][d] for b in pos for d in [0, 1]] for e in cells] + linkage = hier.linkage(data, method='average', metric='hamming', optimal_ordering=True) + clus = hier.fcluster(linkage, t=len(cells), criterion='maxclust') + mapc = [(clus[i], e) for i, e in enumerate(cells)] + return [p[1] for p in sorted(mapc, key=(lambda x : x[0]))], {e : clus[i] for i, e in enumerate(cells)} + + +def exclude_noisy(_bins, _pos, _cells, _index, _clones, _selected): + check = {e : _selected[e] != 'None' for e in _cells} + cells = [e for e in _cells if check[e]] + selected = {e : _selected[e] for e in _selected if check[e]} + clones = {e : _clones[e] for e in _clones if check[e]} + index = [e for e in _index if check[e]] + bins = {b : {e : _bins[b][e] for e in _bins[b] if check[e]} for b in _bins} + pos = sorted(bins.keys(), key=order) + return bins, pos, cells, index, clones, selected + + +def rbplot_unphased(bins, chosen, args): + form = (lambda d, e : {'RDR' : d['RDR'], 'BAF' : d['BAF'], 'Cluster' : d['Cluster'], 'Cell' : e}) + df = [form(bins[b][e], e) for b in bins for e in chosen] + + par= {} + par['data'] = pd.DataFrame(df) + par['x'] = 'RDR' + par['y'] = 'BAF' + par['hue'] = 'Cluster' + par['row'] = 'Cell' + par['fit_reg'] = False + par['legend'] = False + par['palette'] = 'tab20' + par['size'] = args['plotsize'][0] + par['aspect'] = args['plotsize'][1] + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + g = sns.lmplot(**par) + g.despine(top=False, bottom=False, left=False, right=False) + g.set(ylim=(-0.01, 1.01)) + g.set(xlim=(args['xmin'], args['xmax'])) + plt.savefig('rbplot_unphased.{}'.format(args['format']), bbox_inches='tight') + plt.close() + + +def rbplot_mirrored(bins, chosen, args): + form = (lambda d, e : {'RDR' : d['RDR'], '|0.5 - BAF|' : 0.5-min(d['BAF'], 1-d['BAF']), 'Cluster' : d['Cluster'], 'Cell' : e}) + df = [form(bins[b][e], e) for b in bins for e in chosen] + + par= {} + par['data'] = pd.DataFrame(df) + par['x'] = 'RDR' + par['y'] = '|0.5 - BAF|' + par['hue'] = 'Cluster' + par['row'] = 'Cell' + par['fit_reg'] = False + par['legend'] = False + par['palette'] = 'tab20' + par['size'] = args['plotsize'][0] + par['aspect'] = args['plotsize'][1] + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + g = sns.lmplot(**par) + g.despine(top=False, bottom=False, left=False, right=False) + g.set(ylim=(-0.01, 0.51)) + g.set(xlim=(args['xmin'], args['xmax'])) + plt.savefig('rbplot_mirrored.{}'.format(args['format']), bbox_inches='tight') + plt.close() + + +def crdr(bins, pos, chosen, args): + form = (lambda d, e : {'Genome' : d['Genome'], 'RDR' : d['RDR'], 'Cluster' : d['Cluster'], 'Cell' : e}) + df = [form(bins[b][e], e) for b in bins for e in chosen] + + par= {} + par['data'] = pd.DataFrame(df) + par['x'] = 'Genome' + par['y'] = 'RDR' + par['hue'] = 'Cluster' + par['row'] = 'Cell' + par['fit_reg'] = False + par['legend'] = False + par['palette'] = 'tab20' + par['size'] = args['clussize'][0] + par['aspect'] = args['clussize'][1] + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + g = sns.lmplot(**par) + g.despine(top=False, bottom=False, left=False, right=False) + for ax in g.axes: + for x, p in enumerate(pos): + if x > 0 and pos[x-1][0] != pos[x][0]: + ax[0].plot((x, x), (0, 2), '--b', linewidth=1.0) + ax[0].margins(x=0, y=0) + addchrplt(pos) + g.set(xlim=(0, len(pos))) + g.set(xlim=(args['ymin'], args['ymax'])) + plt.savefig('crdr.{}'.format(args['format']), bbox_inches='tight') + plt.close() + + +def cbaf(bins, pos, chosen, args): + form = (lambda d, e : {'Genome' : d['Genome'], '|0.5 - BAF|' : 0.5-min(d['BAF'], 1-d['BAF']), 'Cluster' : d['Cluster'], 'Cell' : e}) + df = [form(bins[b][e], e) for b in bins for e in chosen] + + par= {} + par['data'] = pd.DataFrame(df) + par['x'] = 'Genome' + par['y'] = '|0.5 - BAF|' + par['hue'] = 'Cluster' + par['row'] = 'Cell' + par['fit_reg'] = False + par['legend'] = False + par['palette'] = 'tab20' + par['size'] = args['clussize'][0] + par['aspect'] = args['clussize'][1] + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + g = sns.lmplot(**par) + g.despine(top=False, bottom=False, left=False, right=False) + for ax in g.axes: + for x, p in enumerate(pos): + if x > 0 and pos[x-1][0] != pos[x][0]: + ax[0].plot((x, x), (0, 0.5), '--b', linewidth=1.0) + ax[0].margins(x=0, y=0) + addchrplt(pos) + g.set(xlim=(0, len(pos))) + g.set(xlim=(args['ymin'], args['ymax'])) + plt.savefig('cbaf.'.format(args['format']), bbox_inches='tight') + plt.close() + + +def gridrdrs(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='rdrs.', val='RDR'): + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'RDR' : min(2, bins[b][e][val])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='RDR', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'Read-depth ratios' + draw(table, bins, pos, cells, index, mapc, palette='coolwarm', center=1, method='single', metric='hamming', title=title, out=out, args=args) + + +def gridbafs(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='bafs.', val='BAF'): + df = [] + mapc = {} + mirror = (lambda v : min(v, 1 - v)) + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'Mirrored BAF' : mirror(bins[b][e][val])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='Mirrored BAF', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'Mirrored B-allele frequencies' + draw(table, bins, pos, cells, index, mapc, palette='YlGnBu_r', center=None, method='single', metric='hamming', title=title, out=out, args=args) + + +def totalcns(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='totalcn.', val='CNS'): + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'Total CN' : min(6, sum(bins[b][e][val]))} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='Total CN', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'Total copy numbers' + palette = {} + palette.update({0 : 'darkblue'}) + palette.update({1 : 'lightblue'}) + palette.update({2 : 'lightgray'}) + palette.update({3 : 'lightgoldenrodyellow'}) + palette.update({4 : 'navajowhite'}) + palette.update({5 : 'red'}) + palette.update({6 : 'orchid'}) + colors = [palette[x] for x in range(7) if x in set(df['Total CN'])] + cmap = LinearSegmentedColormap.from_list('multi-level', colors, len(colors)) + draw(table, bins, pos, cells, index, mapc, palette=cmap, center=None, method='single', metric='hamming', title=title, out=out, args=args) + + +def loh(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='loh.', val='CNS'): + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'LOH' : 1 if 0 in bins[b][e][val] else 0} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='LOH', columns=['Genome'], index=['Cell'], aggfunc='first') + myColors = sns.cubehelix_palette(2, start=2, rot=0, dark=0, light=.95) + cmap = LinearSegmentedColormap.from_list('Custom', myColors, len(myColors)) + title = 'Loss of heterozigosity (LOH)' + draw(table, bins, pos, cells, index, mapc, palette=cmap, center=None, method='median', metric='cityblock', title=title, out=out, args=args) + + +def acns(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='Aspecificcn.', val='CNS'): + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'A-specific CN' : min(8, bins[b][e][val][0])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='A-specific CN', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'A-specific copy numbers' + draw(table, bins, pos, cells, index, mapc, palette='coolwarm', center=2, method='single', metric='hamming', title=title, out=out, args=args) + + +def bcns(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='Bspecificcn.', val='CNS'): + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'B-specific CN' : min(8, bins[b][e][val][1])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='B-specific CN', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'B-specific copy numbers' + draw(table, bins, pos, cells, index, mapc, palette='coolwarm', center=2, method='single', metric='hamming', title=title, out=out, args=args) + + +def states(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='allelecn.', val='CNS'): + avail = [(t - i, i) for t in range(7) for i in reversed(range(t+1)) if i <= t - i] + order = (lambda p : (max(p), min(p))) + convert = (lambda p : order(p) if sum(p) <= 6 else min(avail, key=(lambda x : abs(p[0] - x[0]) + abs(p[1] - x[1])))) + df = [] + mapc = {} + found = set() + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'Value' : convert(bins[b][e][val])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + found = [v for v in avail if v in set(df['Value'])] + smap = {v : x for x, v in enumerate(found)} + df['CN states'] = df.apply(lambda r : smap[r['Value']], axis=1) + table = pd.pivot_table(df, values='CN states', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'Copy-number states' + #found = set(df['CN states'] for i, r in df.iterrows()) + palette = {} + palette.update({(0, 0) : 'darkblue'}) + palette.update({(1, 0) : 'lightblue'}) + palette.update({(1, 1) : 'lightgray', (2, 0) : 'dimgray'}) + palette.update({(2, 1) : 'lightgoldenrodyellow', (3, 0) : 'gold'}) + palette.update({(2, 2) : 'navajowhite', (3, 1) : 'orange', (4, 0) : 'darkorange'}) + palette.update({(3, 2) : 'salmon', (4, 1) : 'red', (5, 0) : 'darkred'}) + palette.update({(3, 3) : 'plum', (4, 2) : 'orchid', (5, 1) : 'purple', (6, 0) : 'indigo'}) + colors = [palette[c] for c in found] + cmap = LinearSegmentedColormap.from_list('multi-level', colors, len(colors)) + draw(table, bins, pos, cells, index, mapc, palette=cmap, center=None, method='single', metric='cityblock', title=title, out=out, args=args) + + +def minor(bins, pos, cells, index=None, clones=None, selected=None, args=None, out='haplotypecn.', val='CNS'): + get_minor = (lambda s : (3 - min(2, min(s))) * (0 if s[0] == s[1] else (-1 if s[0] < s[1] else 1))) + df = [] + mapc = {} + for x, e in enumerate(index): + df.extend([{'Cell' : x, 'Genome' : bins[b][e]['Genome'], 'Minor allele' : get_minor(bins[b][e][val])} for b in pos]) + mapc[x] = (clones[e], selected[e]) + df = pd.DataFrame(df) + table = pd.pivot_table(df, values='Minor allele', columns=['Genome'], index=['Cell'], aggfunc='first') + title = 'Minor alleles' + colormap = 'PiYG' + draw(table, bins, pos, cells, index, mapc, palette=colormap, center=0, method='single', metric='hamming', title=title, out=out, args=args) + + +def draw(table, bins, pos, cells, index, clones, palette, center, method, metric, title, out, args): + chr_palette = cycle(['#525252', '#969696', '#cccccc']) + chr_colors = {c : next(chr_palette) for c in sorted(set(b[0] for b in bins), key=orderchrs)} + seen = set() + seen_add = seen.add + ordclones = [clones[x] for x in table.index if not (clones[x][0] in seen or seen_add(clones[x][0]))] + cell_palette = cycle(sns.color_palette("muted", len(set(ordclones)))) + disc_palette = cycle(sns.color_palette("Greys", 8)) + clone_colors = {i[0] : next(cell_palette) if i[1] != 'None' else '#f0f0f0' for i in ordclones} + cell_colors = {x : clone_colors[clones[x][0]] for x in table.index} + + para = {} + para['data'] = table + para['cmap'] = palette + if center: + para['center'] = center + para['yticklabels'] = False + para['row_cluster'] = False + para['xticklabels'] = False + para['col_cluster'] = False + para['figsize'] = args['gridsize'] + para['rasterized'] = True + para['col_colors'] = pd.DataFrame([{'index' : s, 'chromosomes' : chr_colors[pos[x][0]]} for x, s in enumerate(table.columns)]).set_index('index') + para['row_colors'] = pd.DataFrame([{'index' : x, 'Clone' : cell_colors[x]} for x in table.index]).set_index('index') + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + g = sns.clustermap(**para) + addchr(g, pos) + g.fig.suptitle(title) + a00 = plt.arrow(0,0, 0,0, color='darkblue') + a10 = plt.arrow(0,0, 0,0, color='lightblue') + a11 = plt.arrow(0,0, 0,0, color='lightgray') + a20 = plt.arrow(0,0, 0,0, color='dimgray') + a21 = plt.arrow(0,0, 0,0, color='lightgoldenrodyellow') + a30 = plt.arrow(0,0, 0,0, color='gold') + a22 = plt.arrow(0,0, 0,0, color='navajowhite') + a31 = plt.arrow(0,0, 0,0, color='orange') + a40 = plt.arrow(0,0, 0,0, color='darkorange') + a32 = plt.arrow(0,0, 0,0, color='salmon') + a41 = plt.arrow(0,0, 0,0, color='red') + a50 = plt.arrow(0,0, 0,0, color='darkred') + a33 = plt.arrow(0,0, 0,0, color='plum') + a42 = plt.arrow(0,0, 0,0, color='orchid') + a51 = plt.arrow(0,0, 0,0, color='purple') + a60 = plt.arrow(0,0, 0,0, color='indigo') + plt.legend([a00, a10, a11, a20, a21, a30, a22, a31, a40, a32, a41, a50, a33, a42, a51, a60], \ + ['(0, 0)','(1, 0)','(1, 1)','(2, 0)', '(2, 1)','(3, 0)', '(2, 2)','(3, 1)','(4, 0)','(3, 2)', \ + '(4, 1)','(5, 0)', '(3, 3)','(4, 2)','(5, 1)','(6, 0)'], ncol=4, loc='upper left') + plt.savefig(out + args['format'], bbox_inches='tight', dpi=600) + plt.close() + + +def addchr(g, pos, color=None): + corners = [] + prev = 0 + for x, b in enumerate(pos): + if x != 0 and pos[x-1][0] != pos[x][0]: + corners.append((prev, x)) + prev = x + corners.append((prev, x)) + ax = g.ax_heatmap + ticks = [] + for o in corners: + ax.set_xticks(np.append(ax.get_xticks(), int(float(o[1] + o[0] + 1) / 2.0))) + ticks.append(pos[o[0]][0]) + ax.set_xticklabels(ticks, rotation=45, ha='center') + ax.set_yticklabels(ax.get_yticklabels(), rotation=0) + + +def addchrplt(pos): + corners = [] + prev = 0 + val = pos[0][0] + for x, s in enumerate(pos): + if x != 0 and pos[x-1][0] != pos[x][0]: + corners.append((prev, x, val)) + prev = x + val = s[0] + corners.append((prev, x, val)) + ticks = [(int(float(o[1] + o[0] + 1) / 2.0), o[2]) for o in corners] + plt.xticks([x[0] for x in ticks], [x[1] for x in ticks], rotation=45, ha='center') + plt.yticks(rotation=0) + +def generate_discrete_legend(levels, colors=None, ax=None): + """""" + # levels = [(2, 2), (3, 1)], [(2, 1)], [(1, 1), (2, 2)] + # levels = [[(1, 2), (1, 1)], [(0, 2)], [(1, 3), (1, 0)], [(1, 1)]] + if ax is None: + ax = plt.gca() + + if colors is None: + n_colors = len(levels) + cmap = plt.cm.tab20 + colors = [(cmap(idx * 2), cmap(idx * 2 + 1)) for idx in range(n_colors)] + + legend_elements = [] + for level, color in zip(levels, colors): + sub_level = level[0] + sub_label = "{" + str(sub_level[0]) + ", " + str(sub_level[1]) + "}" + if len(level) > 1: + patch_1 = Patch(facecolor=color[1], edgecolor='k', label=sub_label) + sub_level_2 = level[1] + sub_label_2 = "{" + str(sub_level_2[0]) + ", " + str(sub_level_2[1]) + "}" + patch_2 = Patch(facecolor=color[0], edgecolor='k', label=sub_label_2) + else: + # Moves this patch one space over. + patch_1 = Line2D([0], [0], color="w", label="") + patch_2 = Patch(facecolor=color[0], edgecolor='k', label=sub_label) + legend_elements.append([patch_1, patch_2]) + + legend_elements_ordered = [e[0] for e in legend_elements] + [e[1] for e in legend_elements] + # + fig, ax = plt.subplots() + legend = ax.legend(handles=legend_elements_ordered, ncol=2, loc='upper right', frameon=False, + columnspacing=-3.9, labelspacing=1.5, handlelength=3.0, handleheight=1.1, borderpad=0.9, + bbox_to_anchor=(1.13, 1.0)) + for txt in legend.get_texts(): + txt.set_ha("center") + txt.set_x(-52) + txt.set_y(17) + + +if __name__ == '__main__': + main() diff --git a/utils/merge_bamfile.py b/utils/merge_bamfile.py new file mode 100644 index 0000000..df50050 --- /dev/null +++ b/utils/merge_bamfile.py @@ -0,0 +1,58 @@ +#!/bin/python + +import sys +import pysam +import pandas as pd +import subprocess +import argparse + + +def write_merged_bam(input_bamfile_list, suffix_list, output_bam): + fpin = pysam.AlignmentFile(input_bamfile_list[0], "rb") + fpout = pysam.AlignmentFile(output_bam, "wb", template=fpin) + fpin.close() + for i, fname in enumerate(input_bamfile_list): + fpin = pysam.AlignmentFile(fname, "rb") + suffix = suffix_list[i] + for read in fpin: + if read.has_tag("CB"): + b = read.get_tag("CB") + read.set_tag("CB", f"{b}_{suffix}") + fpout.write(read) + fpin.close() + fpout.close() + + +def write_merged_deconvolution(input_deconvfile_list, suffix_list, output_deconv): + df_combined = [] + for i, fname in enumerate(input_deconvfile_list): + suffix = suffix_list[i] + tmpdf = pd.read_csv(fname, header=0, index_col=0, sep="\t") + tmpdf.index = [f"{x}_{suffix}" for x in tmpdf.index] + df_combined.append(tmpdf) + df_combined = pd.concat(df_combined, ignore_index=False) + df_combined.to_csv(output_deconv, header=True, index=True, sep="\t") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("-b", "--bamlistfile", help="cellsnplite result directory", type=str) + parser.add_argument("-o", "--output_dir", help="output directory", type=str) + args = parser.parse_args() + + df = pd.read_csv(args.bamlistfile, sep="\t", header=None, index_col=None) + if df.shape[1] == 3: + df.columns=["bamfilename", "suffix", "cellrangerdir"] + else: + df.columns=["bamfilename", "suffix", "cellrangerdir", "deconv_filename"] + + input_bamfile_list = df.bamfilename.values + suffix_list = df.suffix.values + write_merged_bam(input_bamfile_list, suffix_list, f"{args.output_dir}/unsorted_possorted_genome_bam.bam") + + if df.shape[1] == 4: + # merge deconvolution file + assert "deconv_filename" in df.columns + input_deconvfile_list = df.deconv_filename.values + suffix_list = df.suffix.values + write_merged_deconvolution(input_deconvfile_list, suffix_list, f"{args.output_dir}/merged_deconvolution.tsv") diff --git a/utils/plot_hatchet.py b/utils/plot_hatchet.py new file mode 100644 index 0000000..9e5ccd4 --- /dev/null +++ b/utils/plot_hatchet.py @@ -0,0 +1,838 @@ +import sys +sys.path.append( "/".join(sys.argv[0].split("/")[:-1]) + "/../src/" ) +from calicost.utils_plotting import * +import numpy as np +import pandas as pd +from pathlib import Path + + +def get_best_r_hmrf(configuration_file): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # find the best HMRF initialization random seed + df_3_clone = [] + for random_state in range(10): + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{random_state}_w{config['spatial_weight']:.1f}" + if Path(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz").exists(): + res_combine = dict(np.load(f"{outdir}/rdrbaf_final_nstates{config['n_states']}_smp.npz"), allow_pickle=True) + df_3_clone.append( pd.DataFrame({"random seed":random_state, "log-likelihood":res_combine["total_llf"]}, index=[0]) ) + if len(df_3_clone) > 0: + df_3_clone = pd.concat(df_3_clone, ignore_index=True) + idx = np.argmax(df_3_clone["log-likelihood"]) + r_hmrf_initialization = df_3_clone["random seed"].iloc[idx] + return r_hmrf_initialization + else: + return None + + +def strict_convert_copy_to_states(A_copy, B_copy, counts=None): + if counts is None: + tmp = A_copy + B_copy + tmp = tmp[~np.isnan(tmp)] + else: + tmp = np.concatenate([ np.ones(counts[i]) * (A_copy[i]+B_copy[i]) for i in range(len(counts)) if ~np.isnan(A_copy[i]+B_copy[i]) ]) + base_ploidy = np.median(tmp) + is_homozygous = (A_copy == 0) | (B_copy == 0) + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy != B_copy) ] = "del" + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy == B_copy) ] = "bdel" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy != B_copy) ] = "amp" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy == B_copy) ] = "bamp" + coarse_states[ (A_copy + B_copy == base_ploidy) & (is_homozygous) ] = "loh" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +def convert_copy_to_states(A_copy, B_copy, counts=None): + if counts is None: + tmp = A_copy + B_copy + tmp = tmp[~np.isnan(tmp)] + else: + tmp = np.concatenate([ np.ones(counts[i]) * (A_copy[i]+B_copy[i]) for i in range(len(counts)) if ~np.isnan(A_copy[i]+B_copy[i]) ]) + base_ploidy = np.median(tmp) + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy != B_copy) ] = "del" + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy == B_copy) ] = "bdel" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy != B_copy) ] = "amp" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy == B_copy) ] = "bamp" + coarse_states[ (A_copy + B_copy == base_ploidy) & (A_copy != B_copy) ] = "loh" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +def fixed_convert_copy_to_states(A_copy, B_copy, counts=None): + base_ploidy = 2 + is_homozygous = (A_copy == 0) | (B_copy == 0) + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy != B_copy) ] = "del" + coarse_states[ (A_copy + B_copy < base_ploidy) & (A_copy == B_copy) ] = "bdel" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy != B_copy) ] = "amp" + coarse_states[ (A_copy + B_copy > base_ploidy) & (A_copy == B_copy) ] = "bamp" + coarse_states[ (A_copy + B_copy == base_ploidy) & (is_homozygous) ] = "loh" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +def convert_copy_to_totalcopy_states(A_copy, B_copy, counts=None): + if counts is None: + tmp = A_copy + B_copy + tmp = tmp[~np.isnan(tmp)] + else: + tmp = np.concatenate([ np.ones(counts[i]) * (A_copy[i]+B_copy[i]) for i in range(len(counts)) if ~np.isnan(A_copy[i]+B_copy[i]) ]) + base_ploidy = np.median(tmp) + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) ] = "del" + coarse_states[ (A_copy + B_copy > base_ploidy) ] = "amp" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +def fixed_convert_copy_to_totalcopy_states(A_copy, B_copy, counts=None): + base_ploidy = 2 + coarse_states = np.array(["neutral"] * A_copy.shape[0]) + coarse_states[ (A_copy + B_copy < base_ploidy) ] = "del" + coarse_states[ (A_copy + B_copy > base_ploidy) ] = "amp" + coarse_states[coarse_states == "neutral"] = "neu" + return coarse_states + + +def read_hatchet(hatchet_wes_file, ordered_chr=[str(c) for c in range(1,23)], purity_threshold=0.3): + ##### HATCHet2 WES ##### + df_hatchet = pd.read_csv(hatchet_wes_file, sep='\t', index_col=None, header=0) + # rename the "#CHR" column to "CHR" + df_hatchet = df_hatchet.rename(columns={'#CHR': 'CHR'}) + + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_hatchet.CHR.isin(ordered_chr) ): + df_hatchet["CHR"] = df_hatchet.CHR.map(lambda x: x.replace("chr", "")) + df_hatchet = df_hatchet[df_hatchet.CHR.isin(ordered_chr)] + df_hatchet["int_chrom"] = df_hatchet.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_hatchet = df_hatchet.sort_values(by=["int_chrom", "START"]) + + # find tumor clones that are > purity_threshold in any samples + samples = np.unique(df_hatchet["SAMPLE"].values) + passed_hatchet_clones = [] + for x in df_hatchet.columns: + if not x.startswith("u_clone"): + continue + pu = np.array([ df_hatchet[df_hatchet["SAMPLE"]==s][f"u_clone{x[7:]}"].values[0] for s in samples ]) + if np.max(pu) > purity_threshold: + passed_hatchet_clones.append(x[7:]) + + # get the sample with largest tumor purity + sample_tumor_purity = np.array([1-df_hatchet[df_hatchet["SAMPLE"]==s].u_normal.values[0] for s in samples]) + df_wes = df_hatchet[df_hatchet["SAMPLE"]==samples[np.argmax(sample_tumor_purity)]].copy() + + # drop the clones in df_wes that are not in passed_hatchet_clones + columns_to_drop = [x for x in df_wes.columns if x.startswith("u_clone") and x[7:] not in passed_hatchet_clones] + \ + [x for x in df_wes.columns if x.startswith("cn_clone") and x[8:] not in passed_hatchet_clones] + df_wes = df_wes.drop(columns=columns_to_drop) + hatchet_clones = [x[7:] for x in df_wes.columns if x.startswith("u_clone")] + + # parse A copy and B copy for each clone for each segment + for c in hatchet_clones: + df_wes[f"Acopy_{c}"] = [int(x.split("|")[0]) for x in df_wes[f"cn_clone{c}"].values] + df_wes[f"Bcopy_{c}"] = [int(x.split("|")[1]) for x in df_wes[f"cn_clone{c}"].values] + + if len(passed_hatchet_clones) > 0: + return df_wes + else: + return df_wes.iloc[0:0,:] + + +def map_hatchet_to_bins(df_wes, sorted_chr_pos): + # map HATCHet to allele-specific STARCH bins + snp_seg_index = [] + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while j < df_wes.shape[0] and ( (df_wes.int_chrom.iloc[j] < this_chr) or (df_wes.int_chrom.iloc[j] == this_chr and df_wes.END.iloc[j] < this_pos) ): + j += 1 + if j < df_wes.shape[0] and df_wes.int_chrom.iloc[j] == this_chr and df_wes.START.iloc[j] <= this_pos and df_wes.END.iloc[j] >= this_pos: + snp_seg_index.append(j) + else: + snp_seg_index.append(-1) # maybe the SNP is in centromere, it's not inside any segment + snp_seg_index = np.array(snp_seg_index) + return snp_seg_index + + +def stateaccuracy_allele_starch(configuration_file, r_hmrf_initialization, hatchet_wes_file, midfix="", ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5, purity_threshold=0.3): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # starch results + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + df_starch_cnv = pd.read_csv(f"{outdir}/cnv_{midfix}seglevel.tsv", sep="\t", header=0) + df_starch_cnv.CHR = df_starch_cnv.CHR.astype(str) + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_starch_cnv.CHR.isin(ordered_chr) ): + df_starch_cnv["CHR"] = df_starch_cnv.CHR.map(lambda x: x.replace("chr", "")) + df_starch_cnv = df_starch_cnv[df_starch_cnv.CHR.isin(ordered_chr)] + df_starch_cnv["int_chrom"] = df_starch_cnv.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_starch_cnv = df_starch_cnv.sort_values(by=["int_chrom", "START"]) + sorted_chr_pos = [[df_starch_cnv.int_chrom.iloc[i], df_starch_cnv.START.iloc[i]] for i in range(df_starch_cnv.shape[0])] + df_starch_cnv.drop(columns=["int_chrom"], inplace=True) + clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_starch_cnv.columns[3:] ]) + coarse_states_inferred = np.array([fun_hatchetconvert(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values, counts=((df_starch_cnv.END.values-df_starch_cnv.START.values) / binsize).astype(int)) for cid in clone_ids]) + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file, purity_threshold=purity_threshold) + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + coarse_states_wes = np.array([fun_hatchetconvert(df_wes[f"Acopy_{sid}"].values, df_wes[f"Bcopy_{sid}"].values, counts=((df_wes.END.values-df_wes.START.values) / binsize).astype(int)) for sid in retained_hatchet_clones]) + + percent_category = np.zeros( (len(clone_ids), len(retained_hatchet_clones)) ) + for s,sid in enumerate(retained_hatchet_clones): + # accuracy + for c,cid in enumerate(clone_ids): + # coarse + percent_category[c, s] = 1.0 * np.sum(coarse_states_inferred[c] == coarse_states_wes[s][snp_seg_index]) / len(snp_seg_index) + return percent_category, sorted_chr_pos + + +def stateaccuracy_calicost_fromdf(configuration_file, r_hmrf_initialization, df_compare, midfix="", ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5, purity_threshold=0.3): + """ + df_compare : DataFrame + Contains the following columns: CHR, START, END, Acopy_clone1, Bcopy_clone1, Acopy_clone2, Bcopy_clone2, ... + """ + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # starch results + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + df_starch_cnv = pd.read_csv(f"{outdir}/cnv_{midfix}seglevel.tsv", sep="\t", header=0) + df_starch_cnv.CHR = df_starch_cnv.CHR.astype(str) + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_starch_cnv.CHR.isin(ordered_chr) ): + df_starch_cnv["CHR"] = df_starch_cnv.CHR.map(lambda x: x.replace("chr", "")) + df_starch_cnv = df_starch_cnv[df_starch_cnv.CHR.isin(ordered_chr)] + df_starch_cnv["int_chrom"] = df_starch_cnv.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_starch_cnv = df_starch_cnv.sort_values(by=["int_chrom", "START"]) + sorted_chr_pos = [[df_starch_cnv.int_chrom.iloc[i], df_starch_cnv.START.iloc[i]] for i in range(df_starch_cnv.shape[0])] + df_starch_cnv.drop(columns=["int_chrom"], inplace=True) + clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_starch_cnv.columns[3:] ]) + coarse_states_inferred = np.array([fun_hatchetconvert(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values, counts=((df_starch_cnv.END.values-df_starch_cnv.START.values) / binsize).astype(int)) for cid in clone_ids]) + + # format change on df_compare + df_compare["CHR"] = df_compare["CHR"].astype(str) + if ~np.any( df_compare.CHR.isin(ordered_chr) ): + df_compare["CHR"] = df_compare.CHR.map(lambda x: x.replace("chr", "")) + df_compare = df_compare[df_compare.CHR.isin(ordered_chr)] + df_compare["int_chrom"] = df_compare.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_compare = df_compare.sort_values(by=["int_chrom", "START"]) + + snp_seg_index = map_hatchet_to_bins(df_compare, sorted_chr_pos) + ref_clones = [x[6:] for x in df_compare.columns if x.startswith("Acopy_")] + coarse_states_compare = np.array([fun_hatchetconvert(df_compare[f"Acopy_{sid}"].values, df_compare[f"Bcopy_{sid}"].values, counts=((df_compare.END.values-df_compare.START.values) / binsize).astype(int)) for sid in ref_clones]) + + percent_category = np.zeros( (len(clone_ids), len(ref_clones)) ) + for s,sid in enumerate(ref_clones): + # accuracy + for c,cid in enumerate(clone_ids): + # coarse + percent_category[c, s] = 1.0 * np.sum(coarse_states_inferred[c] == coarse_states_compare[s][snp_seg_index]) / len(snp_seg_index) + return percent_category, sorted_chr_pos + + +def exactaccuracy_allele_starch(configuration_file, r_hmrf_initialization, hatchet_wes_file, midfix="", ordered_chr=[str(c) for c in range(1,23)], purity_threshold=0.3): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # starch results + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + df_starch_cnv = pd.read_csv(f"{outdir}/cnv_{midfix}seglevel.tsv", sep="\t", header=0) + df_starch_cnv.CHR = df_starch_cnv.CHR.astype(str) + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_starch_cnv.CHR.isin(ordered_chr) ): + df_starch_cnv["CHR"] = df_starch_cnv.CHR.map(lambda x: x.replace("chr", "")) + df_starch_cnv = df_starch_cnv[df_starch_cnv.CHR.isin(ordered_chr)] + df_starch_cnv["int_chrom"] = df_starch_cnv.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_starch_cnv = df_starch_cnv.sort_values(by=["int_chrom", "START"]) + sorted_chr_pos = [[df_starch_cnv.int_chrom.iloc[i], df_starch_cnv.START.iloc[i]] for i in range(df_starch_cnv.shape[0])] + df_starch_cnv.drop(columns=["int_chrom"], inplace=True) + clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_starch_cnv.columns[3:] ]) + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file, purity_threshold=purity_threshold) + df_mapped_wes = pd.DataFrame({"CHR":df_starch_cnv.CHR, "START":df_starch_cnv.START, "END":df_starch_cnv.END}) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + percent_exact = np.zeros( (len(clone_ids), len(retained_hatchet_clones)) ) + for s,sid in enumerate(retained_hatchet_clones): + minor_copy_wes = np.minimum(df_wes[f"Acopy_{sid}"].values[snp_seg_index], df_wes[f"Bcopy_{sid}"].values[snp_seg_index]) + major_copy_wes = np.maximum(df_wes[f"Acopy_{sid}"].values[snp_seg_index], df_wes[f"Bcopy_{sid}"].values[snp_seg_index]) + df_mapped_wes[[f'clone{s} A', f'clone{s} B']] = np.vstack([minor_copy_wes, major_copy_wes]).T + for c, cid in enumerate(clone_ids): + # exact + minor_copy_inferred = np.minimum(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values) + major_copy_inferred = np.maximum(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values) + percent_exact[c, s] = 1.0 * np.sum((minor_copy_inferred==minor_copy_wes) & (major_copy_inferred==major_copy_wes)) / len(minor_copy_inferred) + return percent_exact, sorted_chr_pos, df_mapped_wes + + +def stateaccuracy_numbat(numbat_dirs, hatchet_wes_file, sorted_chr_pos, ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5): + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + coarse_states_wes = np.array([fun_hatchetconvert(df_wes[f"Acopy_{sid}"].values, df_wes[f"Bcopy_{sid}"].values, counts=((df_wes.END.values-df_wes.START.values) / binsize).astype(int)) for sid in retained_hatchet_clones]) + + percent_category = [] + states_numbat = [] + for dirname in numbat_dirs: + tmpdf_numbat = pd.read_csv(f"{dirname}/bulk_clones_final.tsv.gz", header=0, sep="\t") + n_numbat_samples = len( np.unique(tmpdf_numbat["sample"]) ) + # check chromosome name + tmpdf_numbat.CHROM = tmpdf_numbat.CHROM.astype(str) + if ~np.any( tmpdf_numbat.CHROM.isin(ordered_chr) ): + tmpdf_numbat["CHROM"] = tmpdf_numbat.CHROM.map(lambda x: x.replace("chr", "")) + tmpdf_numbat = tmpdf_numbat[tmpdf_numbat.CHROM.isin(ordered_chr)] + tmpdf_numbat["int_chrom"] = tmpdf_numbat.CHROM.map(ordered_chr_map) + tmpdf_numbat.sort_values(by=['int_chrom', 'POS'], inplace=True) + + this_percent_category = np.zeros((n_numbat_samples, len(retained_hatchet_clones))) + for sidx,s in enumerate(np.unique(tmpdf_numbat["sample"])): + tmpdf_sample = tmpdf_numbat[tmpdf_numbat["sample"] == s][["int_chrom", "POS", "cnv_state"]] + index = np.ones(len(sorted_chr_pos), dtype=int) * -1 + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while (j < tmpdf_sample.shape[0]) and ((tmpdf_sample.int_chrom.values[j] < this_chr) or (tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.POS.values[j] < this_pos)): + j += 1 + if j < tmpdf_sample.shape[0] and tmpdf_sample.int_chrom.values[j] == this_chr: + index[i] = j + else: + index[i] = j -1 + for c in range(len(retained_hatchet_clones)): + this_percent_category[sidx, c] = 1.0 * np.sum(tmpdf_sample["cnv_state"].values[index] == coarse_states_wes[c][snp_seg_index]) / len(snp_seg_index) + + states_numbat.append( tmpdf_sample["cnv_state"].values[index] ) + percent_category.append(this_percent_category) + + percent_category = np.vstack(percent_category) + states_numbat = np.array(states_numbat) + return percent_category, coarse_states_wes[:,snp_seg_index], states_numbat + + +def stateaccuracy_numbat_fromdf(numbat_dirs, df_compare, sorted_chr_pos, ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5): + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + + # format change on df_compare + df_compare["CHR"] = df_compare["CHR"].astype(str) + if ~np.any( df_compare.CHR.isin(ordered_chr) ): + df_compare["CHR"] = df_compare.CHR.map(lambda x: x.replace("chr", "")) + df_compare = df_compare[df_compare.CHR.isin(ordered_chr)] + df_compare["int_chrom"] = df_compare.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_compare = df_compare.sort_values(by=["int_chrom", "START"]) + + snp_seg_index = map_hatchet_to_bins(df_compare, sorted_chr_pos) + ref_clones = [x[6:] for x in df_compare.columns if x.startswith("Acopy_")] + coarse_states_compare = np.array([fun_hatchetconvert(df_compare[f"Acopy_{sid}"].values, df_compare[f"Bcopy_{sid}"].values, counts=((df_compare.END.values-df_compare.START.values) / binsize).astype(int)) for sid in ref_clones]) + + percent_category = [] + states_numbat = [] + for dirname in numbat_dirs: + tmpdf_numbat = pd.read_csv(f"{dirname}/bulk_clones_final.tsv.gz", header=0, sep="\t") + n_numbat_samples = len( np.unique(tmpdf_numbat["sample"]) ) + # check chromosome name + tmpdf_numbat.CHROM = tmpdf_numbat.CHROM.astype(str) + if ~np.any( tmpdf_numbat.CHROM.isin(ordered_chr) ): + tmpdf_numbat["CHROM"] = tmpdf_numbat.CHROM.map(lambda x: x.replace("chr", "")) + tmpdf_numbat = tmpdf_numbat[tmpdf_numbat.CHROM.isin(ordered_chr)] + tmpdf_numbat["int_chrom"] = tmpdf_numbat.CHROM.map(ordered_chr_map) + tmpdf_numbat.sort_values(by=['int_chrom', 'POS'], inplace=True) + + this_percent_category = np.zeros((n_numbat_samples, len(ref_clones))) + for sidx,s in enumerate(np.unique(tmpdf_numbat["sample"])): + tmpdf_sample = tmpdf_numbat[tmpdf_numbat["sample"] == s][["int_chrom", "POS", "cnv_state"]] + index = np.ones(len(sorted_chr_pos), dtype=int) * -1 + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while (j < tmpdf_sample.shape[0]) and ((tmpdf_sample.int_chrom.values[j] < this_chr) or (tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.POS.values[j] < this_pos)): + j += 1 + if j < tmpdf_sample.shape[0] and tmpdf_sample.int_chrom.values[j] == this_chr: + index[i] = j + else: + index[i] = j -1 + for c in range(len(ref_clones)): + this_percent_category[sidx, c] = 1.0 * np.sum(tmpdf_sample["cnv_state"].values[index] == coarse_states_compare[c][snp_seg_index]) / len(snp_seg_index) + + states_numbat.append( tmpdf_sample["cnv_state"].values[index] ) + percent_category.append(this_percent_category) + + percent_category = np.vstack(percent_category) + states_numbat = np.array(states_numbat) + return percent_category, coarse_states_compare[:,snp_seg_index], states_numbat + + +def cna_precisionrecall_numbat(numbat_dirs, hatchet_wes_file, sorted_chr_pos, ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5): + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + coarse_states_wes = np.array([fun_hatchetconvert(df_wes[f"Acopy_{sid}"].values, df_wes[f"Bcopy_{sid}"].values, counts=((df_wes.END.values-df_wes.START.values) / binsize).astype(int)) for sid in retained_hatchet_clones]) + + precision = [] + recall = [] + states_numbat = [] + for dirname in numbat_dirs: + tmpdf_numbat = pd.read_csv(f"{dirname}/bulk_clones_final.tsv.gz", header=0, sep="\t") + n_numbat_samples = len( np.unique(tmpdf_numbat["sample"]) ) + # check chromosome name + tmpdf_numbat.CHROM = tmpdf_numbat.CHROM.astype(str) + if ~np.any( tmpdf_numbat.CHROM.isin(ordered_chr) ): + tmpdf_numbat["CHROM"] = tmpdf_numbat.CHROM.map(lambda x: x.replace("chr", "")) + tmpdf_numbat = tmpdf_numbat[tmpdf_numbat.CHROM.isin(ordered_chr)] + tmpdf_numbat["int_chrom"] = tmpdf_numbat.CHROM.map(ordered_chr_map) + tmpdf_numbat.sort_values(by=['int_chrom', 'POS'], inplace=True) + + this_precision = np.zeros((n_numbat_samples, len(retained_hatchet_clones))) + this_recall = np.zeros((n_numbat_samples, len(retained_hatchet_clones))) + for sidx,s in enumerate(np.unique(tmpdf_numbat["sample"])): + tmpdf_sample = tmpdf_numbat[tmpdf_numbat["sample"] == s][["int_chrom", "POS", "cnv_state"]] + index = np.ones(len(sorted_chr_pos), dtype=int) * -1 + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while (j < tmpdf_sample.shape[0]) and ((tmpdf_sample.int_chrom.values[j] < this_chr) or (tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.POS.values[j] < this_pos)): + j += 1 + if j < tmpdf_sample.shape[0] and tmpdf_sample.int_chrom.values[j] == this_chr: + index[i] = j + else: + index[i] = j -1 + for c in range(len(retained_hatchet_clones)): + index_truth = set(list( np.where(coarse_states_wes[c][snp_seg_index] != 'neu')[0] )) + index_pred = set(list( np.where(tmpdf_sample["cnv_state"].values[index] != 'neu')[0] )) + this_precision[sidx, c] = 0 if len(index_pred)==0 else len(index_truth & index_pred) / len(index_pred) + this_recall[sidx, c] = 0 if len(index_truth)==0 else len(index_truth & index_pred) / len(index_truth) + + states_numbat.append( tmpdf_sample["cnv_state"].values[index] ) + precision.append(this_precision) + recall.append(this_recall) + + precision = np.vstack(precision) + recall = np.vstack(recall) + f1 = 2 * precision * recall / (precision + recall) + states_numbat = np.array(states_numbat) + return precision, recall, f1, coarse_states_wes[:,snp_seg_index], states_numbat + + +def cna_precisionrecall_calicost(configuration_file, r_hmrf_initialization, hatchet_wes_file, midfix="", ordered_chr=[str(c) for c in range(1,23)], purity_threshold=0.3): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # starch results + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + df_starch_cnv = pd.read_csv(f"{outdir}/cnv_{midfix}seglevel.tsv", sep="\t", header=0) + df_starch_cnv.CHR = df_starch_cnv.CHR.astype(str) + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_starch_cnv.CHR.isin(ordered_chr) ): + df_starch_cnv["CHR"] = df_starch_cnv.CHR.map(lambda x: x.replace("chr", "")) + df_starch_cnv = df_starch_cnv[df_starch_cnv.CHR.isin(ordered_chr)] + df_starch_cnv["int_chrom"] = df_starch_cnv.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_starch_cnv = df_starch_cnv.sort_values(by=["int_chrom", "START"]) + sorted_chr_pos = [[df_starch_cnv.int_chrom.iloc[i], df_starch_cnv.START.iloc[i]] for i in range(df_starch_cnv.shape[0])] + df_starch_cnv.drop(columns=["int_chrom"], inplace=True) + clone_ids = np.unique([ x.split(" ")[0][5:] for x in df_starch_cnv.columns[3:] ]) + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file, purity_threshold=purity_threshold) + df_mapped_wes = pd.DataFrame({"CHR":df_starch_cnv.CHR, "START":df_starch_cnv.START, "END":df_starch_cnv.END}) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + precision = np.zeros( (len(clone_ids), len(retained_hatchet_clones)) ) + recall = np.zeros( (len(clone_ids), len(retained_hatchet_clones)) ) + f1 = np.zeros( (len(clone_ids), len(retained_hatchet_clones)) ) + for s,sid in enumerate(retained_hatchet_clones): + minor_copy_wes = np.minimum(df_wes[f"Acopy_{sid}"].values[snp_seg_index], df_wes[f"Bcopy_{sid}"].values[snp_seg_index]) + major_copy_wes = np.maximum(df_wes[f"Acopy_{sid}"].values[snp_seg_index], df_wes[f"Bcopy_{sid}"].values[snp_seg_index]) + df_mapped_wes[[f'clone{s} A', f'clone{s} B']] = np.vstack([minor_copy_wes, major_copy_wes]).T + for c, cid in enumerate(clone_ids): + # exact + minor_copy_inferred = np.minimum(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values) + major_copy_inferred = np.maximum(df_starch_cnv[f"clone{cid} A"].values, df_starch_cnv[f"clone{cid} B"].values) + index_truth = set(list( np.where( ~((minor_copy_wes==1) & (major_copy_wes==1)) )[0] )) + index_pred = set(list( np.where( ~((minor_copy_inferred==1) & (major_copy_inferred==1)) )[0] )) + + precision[c, s] = 0 if len(index_pred)==0 else len(index_truth & index_pred) / len(index_pred) + recall[c, s] = 0 if len(index_truth)==0 else len(index_truth & index_pred) / len(index_truth) + f1[c,s] = 0 if precision[c, s] + recall[c, s]==0 else 2 * (precision[c, s] * recall[c, s]) / (precision[c, s] + recall[c, s]) + + return precision, recall, f1, sorted_chr_pos, df_mapped_wes + + + +def stateaccuracy_infercnv(infercnv_dirs, hatchet_wes_file, sorted_chr_pos, ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5): + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + coarse_states_wes = np.array([fun_hatchetconvert(df_wes[f"Acopy_{sid}"].values, df_wes[f"Bcopy_{sid}"].values, counts=((df_wes.END.values-df_wes.START.values) / binsize).astype(int)) for sid in retained_hatchet_clones]) + + map_states = {1:"del", 2:"del", 3:"neu", 4:"amp", 5:"amp", 6:"amp"} + percent_category = [] + for dirname in infercnv_dirs: + tmpdf_infercnv = pd.read_csv(f"{dirname}/HMM_CNV_predictions.HMMi6.leiden.hmm_mode-subclusters.Pnorm_0.5.pred_cnv_regions.dat", header=0, index_col=None, sep="\t") + infercnv_samples = np.unique(tmpdf_infercnv["cell_group_name"]) + # check chromosome name + tmpdf_infercnv.chr = tmpdf_infercnv.chr.astype(str) + if ~np.any( tmpdf_infercnv.chr.isin(ordered_chr) ): + tmpdf_infercnv["CHROM"] = tmpdf_infercnv.chr.map(lambda x: x.replace("chr", "")) + tmpdf_infercnv = tmpdf_infercnv[tmpdf_infercnv.chr.isin(ordered_chr)] + tmpdf_infercnv["int_chrom"] = tmpdf_infercnv.chr.map(ordered_chr_map) + + this_percent_category = np.zeros((len(infercnv_samples), len(retained_hatchet_clones))) + for sidx,s in enumerate(infercnv_samples): + tmpdf_sample = tmpdf_infercnv[tmpdf_infercnv["cell_group_name"] == s][["int_chrom", "start", "end", "state"]] + tmpdf_sample = tmpdf_sample.sort_values(by=["int_chrom", "start"]) + # inferCNV states for sorted_chr_pos + cnvstate_sample = 3 * np.ones(len(sorted_chr_pos), dtype=int) + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while (j < tmpdf_sample.shape[0]) and ((tmpdf_sample.int_chrom.values[j] < this_chr) or (tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.end.values[j] < this_pos)): + j += 1 + if j < tmpdf_sample.shape[0] and tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.start.values[j] <= this_pos: + cnvstate_sample[i] = tmpdf_sample.state.values[j] + for c in range(len(retained_hatchet_clones)): + this_percent_category[sidx, c] = 1.0 * np.sum( np.array([map_states[x] for x in cnvstate_sample]) == coarse_states_wes[c][snp_seg_index]) / len(snp_seg_index) + + percent_category.append(this_percent_category) + percent_category = np.vstack(percent_category) + return percent_category + + +def stateaccuracy_oldstarch(oldstarch_dirs, map_hgtable, hatchet_wes_file, sorted_chr_pos, ordered_chr=[str(c) for c in range(1,23)], fun_hatchetconvert=convert_copy_to_states, binsize=1e5): + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + + # hatchet results + df_wes = read_hatchet(hatchet_wes_file) + if df_wes.shape[0] == 0: + return None, None + snp_seg_index = map_hatchet_to_bins(df_wes, sorted_chr_pos) + retained_hatchet_clones = [x[6:] for x in df_wes.columns if x.startswith("Acopy_")] + coarse_states_wes = np.array([fun_hatchetconvert(df_wes[f"Acopy_{sid}"].values, df_wes[f"Bcopy_{sid}"].values, counts=((df_wes.END.values-df_wes.START.values) / binsize).astype(int)) for sid in retained_hatchet_clones]) + + map_states = {0:"del", 1:"neu", 2:"amp"} + percent_category = [] + for dirname in oldstarch_dirs: + tmpdf_oldstarch = pd.read_csv(f"{dirname}/states_STITCH_output.csv", header=0, index_col=0, sep=",") + tmpdf_oldstarch["int_chrom"] = [map_hgtable[x][0] for x in tmpdf_oldstarch.index] + tmpdf_oldstarch["POS"] = [map_hgtable[x][1] for x in tmpdf_oldstarch.index] + + this_percent_category = np.zeros((tmpdf_oldstarch.shape[1]-2, len(retained_hatchet_clones))) + for sidx in range(tmpdf_oldstarch.shape[1]-2): + tmpdf_sample = pd.DataFrame({'int_chrom':tmpdf_oldstarch.int_chrom.values, 'POS':tmpdf_oldstarch.POS.values, 'cnv_state':[map_states[x] for x in tmpdf_oldstarch.iloc[:,sidx]]}) + index = np.ones(len(sorted_chr_pos), dtype=int) * -1 + j = 0 + for i in range(len(sorted_chr_pos)): + this_chr = sorted_chr_pos[i][0] + this_pos = sorted_chr_pos[i][1] + while (j < tmpdf_sample.shape[0]) and ((tmpdf_sample.int_chrom.values[j] < this_chr) or (tmpdf_sample.int_chrom.values[j] == this_chr and tmpdf_sample.POS.values[j] < this_pos)): + j += 1 + if j < tmpdf_sample.shape[0] and tmpdf_sample.int_chrom.values[j] == this_chr: + index[i] = j + else: + index[i] = j -1 + for c in range(len(retained_hatchet_clones)): + this_percent_category[sidx, c] = 1.0 * np.sum(tmpdf_sample["cnv_state"].values[index] == coarse_states_wes[c][snp_seg_index]) / len(snp_seg_index) + + percent_category.append(this_percent_category) + percent_category = np.vstack(percent_category) + return percent_category + + + +def precision_recall_genelevel_allele_starch(configuration_file, r_hmrf_initialization, hatchet_wes_file, midfix="", ordered_chr=[str(c) for c in range(1,23)]): + try: + config = read_configuration_file(configuration_file) + except: + config = read_joint_configuration_file(configuration_file) + + # calicost results + outdir = f"{config['output_dir']}/clone{config['n_clones']}_rectangle{r_hmrf_initialization}_w{config['spatial_weight']:.1f}" + df_calicost = pd.read_csv(f"{outdir}/cnv_{midfix}genelevel.tsv", sep="\t", header=0, index_col=0) + calico_clones = [x.split(" ")[0][5:] for x in df_calicost.columns if x.endswith(" A")] + for c in calico_clones: + tmp = strict_convert_copy_to_states(df_calicost[f"clone{c} A"].values, df_calicost[f"clone{c} B"].values) + tmp[tmp == "bdel"] = "del" + tmp[tmp == "bamp"] = "amp" + df_calicost[f"srt_cnstate_clone{c}"] = tmp + + # read hatchet results and join tables + df_hatchet = pd.read_csv(hatchet_wes_file, header=0, index_col=0, sep="\t") + hatchet_clones = [x[13:] for x in df_hatchet.columns if x.startswith("cnstate_clone")] + df_calicost = df_calicost.join( df_hatchet[[x for x in df_hatchet.columns if "cnstate_clone" in x]], how="inner" ) + + # precision and recall of DEL, AMP, LOH for each pair of clones + df_accuracy = [] + for event in ["del", "amp", "loh"]: + for c in calico_clones: + for s in hatchet_clones: + precision = np.sum( (df_calicost[f"srt_cnstate_clone{c}"].values == event) & (df_calicost[f"cnstate_clone{s}"].values == event) ) / np.sum(df_calicost[f"srt_cnstate_clone{c}"].values == event) + recall = np.sum( (df_calicost[f"srt_cnstate_clone{c}"].values == event) & (df_calicost[f"cnstate_clone{s}"].values == event) ) / np.sum(df_calicost[f"cnstate_clone{s}"].values == event) + df_accuracy.append( pd.DataFrame({"clone_pair":f"{c},{s}", "event":event, "acc":[precision, recall], "acc_name":["precision", "recall"]}) ) + + df_accuracy = pd.concat(df_accuracy, ignore_index=True) + return df_accuracy + + +def plot_hatchet_acn(hatchet_dir, hatchet_cnfile, out_file, binsize=1e6, ordered_chr=[str(c) for c in range(1,23)]): + # read in hatchet integer copy number file + df_hatchet = read_hatchet(f"{hatchet_dir}/results/{hatchet_cnfile}", purity_threshold=0.1) + if df_hatchet.shape[0] == 0: + return + # get CN state from integer copy numbers + df_hatchet = add_cn_state(df_hatchet) + # hatchet clones + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_hatchet.CHR.isin(ordered_chr) ): + df_hatchet["CHR"] = df_hatchet.CHR.map(lambda x: x.replace("chr", "")) + df_hatchet = df_hatchet[df_hatchet.CHR.isin(ordered_chr)] + df_hatchet["int_chrom"] = df_hatchet.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_hatchet = df_hatchet.sort_values(by=["int_chrom", "START"]) + + # expand each row in df_hatchet to multiple rows such that the new row has END - START = binsize + df_expand = [] + for i in range(df_hatchet.shape[0]): + # repeat the row i for int(END - START / binsize) times and save to a new dataframe + n_bins = max(1, int(1.0*(df_hatchet.iloc[i].END - df_hatchet.iloc[i].START) / binsize)) + tmp = pd.DataFrame(np.repeat(df_hatchet.iloc[i:(i+1),:].values, n_bins, axis=0), columns=df_hatchet.columns) + for k in range(n_bins): + tmp.END.iloc[k] = df_hatchet.START.iloc[i]+ k*binsize + tmp.END.iloc[-1] = df_hatchet.END.iloc[i] + df_expand.append(tmp) + df_hatchet = pd.concat(df_expand, ignore_index=True) + + # create another dataframe df_cnv, and apply to plot_acn_from_df function for plotting + df_cnv = df_hatchet[["CHR", "START", "END"]] + # for each clone in df_hatchet, split the A allele copy and B allele copy to separate columns + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + clone_names = [] + for n in hatchet_clones: + A_copy = [int(x.split("|")[0]) for x in df_hatchet[f"cn_clone{n}"]] + B_copy = [int(x.split("|")[1]) for x in df_hatchet[f"cn_clone{n}"]] + df_cnv[f"clone{n} A"] = A_copy + df_cnv[f"clone{n} B"] = B_copy + prop = df_hatchet[f"u_clone{n}"].values[0] + clone_names.append(f"clone{n} ({prop:.2f})") + + # plot + fig, axes = plt.subplots(1, 1, figsize=(20, 0.6*len(hatchet_clones)+0.4), dpi=200, facecolor="white") + plot_acn_from_df(df_cnv, axes, clone_ids=hatchet_clones, clone_names=clone_names, add_chrbar=True, chrbar_thickness=0.4/(0.6*len(hatchet_clones) + 0.4), add_legend=True, remove_xticks=True) + fig.tight_layout() + fig.savefig(out_file, transparent=True, bbox_inches="tight") + + +def plot_hatchet_totalcn(hatchet_dir, hatchet_cnfile, out_file, binsize=1e6, ordered_chr=[str(c) for c in range(1,23)]): + # read in hatchet integer copy number file + df_hatchet = read_hatchet(f"{hatchet_dir}/results/{hatchet_cnfile}", purity_threshold=0.1) + if df_hatchet.shape[0] == 0: + return + # get CN state from integer copy numbers + df_hatchet = add_cn_state(df_hatchet) + # hatchet clones + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + + # check agreement with ordered_chr + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + if ~np.any( df_hatchet.CHR.isin(ordered_chr) ): + df_hatchet["CHR"] = df_hatchet.CHR.map(lambda x: x.replace("chr", "")) + df_hatchet = df_hatchet[df_hatchet.CHR.isin(ordered_chr)] + df_hatchet["int_chrom"] = df_hatchet.CHR.map(ordered_chr_map) + # sort by int_chrom and START + df_hatchet = df_hatchet.sort_values(by=["int_chrom", "START"]) + + # expand each row in df_hatchet to multiple rows such that the new row has END - START = binsize + df_expand = [] + for i in range(df_hatchet.shape[0]): + # repeat the row i for int(END - START / binsize) times and save to a new dataframe + n_bins = max(1, int(1.0*(df_hatchet.iloc[i].END - df_hatchet.iloc[i].START) / binsize)) + tmp = pd.DataFrame(np.repeat(df_hatchet.iloc[i:(i+1),:].values, n_bins, axis=0), columns=df_hatchet.columns) + for k in range(n_bins): + tmp.END.iloc[k] = df_hatchet.START.iloc[i]+ k*binsize + tmp.END.iloc[-1] = df_hatchet.END.iloc[i] + df_expand.append(tmp) + df_hatchet = pd.concat(df_expand, ignore_index=True) + + # create another dataframe df_cnv, and apply to plot_acn_from_df function for plotting + df_cnv = df_hatchet[["CHR", "START", "END"]] + # for each clone in df_hatchet, split the A allele copy and B allele copy to separate columns + clone_names = [] + for n in hatchet_clones: + df_cnv[f"clone {n}"] = df_hatchet[f"cnstate_clone{n}"] + + # plot + fig, axes = plt.subplots(1, 1, figsize=(15,0.9*2+0.6), dpi=200, facecolor="white") + plot_total_cn(df_cnv, axes, palette_mode=6, add_chrbar=True, chrbar_thickness=0.4/(0.6*2 + 0.4), add_legend=True, remove_xticks=True) + fig.tight_layout() + fig.savefig(out_file, transparent=True, bbox_inches="tight") + + +def add_cn_state(df_hatchet): + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + assert ("START" in df_hatchet.columns) and ("END" in df_hatchet.columns) + for n in hatchet_clones: + # compute total copy number per bin + total_cn = np.array([ int(x.split("|")[0]) + int(x.split("|")[1]) for x in df_hatchet[f"cn_clone{n}"] ]) + # check whether each bin is homozygous, i.e., either first cn is 0 or second cn is 0 + is_homozygous = np.array([ (int(x.split("|")[0])==0) or (int(x.split("|")[1])==0) for x in df_hatchet[f"cn_clone{n}"] ]) + # compute median total copy number weighted by END - START + counts = df_hatchet.END.values-df_hatchet.START.values + counts = np.maximum(1, counts / 1e4).astype(int) + tmp = np.concatenate([ np.ones(counts[i]) * (total_cn[i]) for i in range(len(counts)) if ~np.isnan(total_cn[i]) ]) + median_cn = np.median(tmp) + # get cn_state vector such that total_cn > median_cn is "amp", total_cn < median_cn is "del", and total_cn == median_cn is "neu" + cn_state = np.array(["neu"] * len(total_cn)) + cn_state[total_cn > median_cn] = "amp" + cn_state[total_cn < median_cn] = "del" + cn_state[ (total_cn == median_cn) & (is_homozygous) ] = "loh" + # add cn_state to df_hatchet + df_hatchet[f"cnstate_clone{n}"] = cn_state + return df_hatchet + + +def add_log2cnratio(df_hatchet): + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + assert ("START" in df_hatchet.columns) and ("END" in df_hatchet.columns) + for n in hatchet_clones: + # compute total copy number per bin + total_cn = np.array([ int(x.split("|")[0]) + int(x.split("|")[1]) for x in df_hatchet[f"cn_clone{n}"] ]) + # check whether each bin is homozygous, i.e., either first cn is 0 or second cn is 0 + is_homozygous = np.array([ (int(x.split("|")[0])==0) or (int(x.split("|")[1])==0) for x in df_hatchet[f"cn_clone{n}"] ]) + # compute median total copy number weighted by END - START + counts = df_hatchet.END.values-df_hatchet.START.values + counts = np.maximum(1, counts / 1e4).astype(int) + tmp = np.concatenate([ np.ones(counts[i]) * (total_cn[i]) for i in range(len(counts)) if ~np.isnan(total_cn[i]) ]) + median_cn = np.median(tmp) + # compute log2 CNV ratio + df_hatchet[f"log2_cnratio_clone{n}"] = np.log2(total_cn / median_cn) + return df_hatchet + + +def map_hatchet_to_states(hatchet_resultfile, out_file, ordered_chr=[str(c) for c in range(1,23)]): + # read in hatchet integer copy number file + df_hatchet = read_hatchet(hatchet_resultfile, purity_threshold=0.1) + if df_hatchet.shape[0] == 0: + return + # get CN state from integer copy numbers + df_hatchet = add_cn_state(df_hatchet) + # add log2 CNV ratio + df_hatchet = add_log2cnratio(df_hatchet) + # hatchet clones + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + + # re-order df_hatchet_columns + ordered_columns = ["CHR", "START", "END"] + for n in hatchet_clones: + ordered_columns += [f"cn_clone{n}", f"cnstate_clone{n}", f"log2_cnratio_clone{n}"] + + df_hatchet[ordered_columns].to_csv(out_file, sep="\t", header=True, index=False) + + +def map_hatchet_to_genes(hatchet_resultfile, hgtable_file, out_file, ordered_chr=[str(c) for c in range(1,23)]): + # read in hatchet integer copy number file + df_hatchet = read_hatchet(hatchet_resultfile, purity_threshold=0.1) + if df_hatchet.shape[0] == 0: + return + # get CN state from integer copy numbers + df_hatchet = add_cn_state(df_hatchet) + # hatchet clones + hatchet_clones = [x[8:] for x in df_hatchet.columns if x.startswith("cn_clone")] + + # read hgtable file + ordered_chr_map = {ordered_chr[i]:i for i in range(len(ordered_chr))} + df_genes = pd.read_csv(hgtable_file, header=0, index_col=0, sep="\t") + if ~np.any( df_genes["chrom"].map(str).isin(ordered_chr) ): + df_genes["chrom"] = df_genes["chrom"].map(lambda x: x.replace("chr", "")) + df_genes = df_genes[df_genes.chrom.isin(ordered_chr)] + df_genes["int_chrom"] = df_genes.chrom.map(ordered_chr_map) + df_genes.sort_values(by=["int_chrom", "cdsStart"], inplace=True) + + # find the row corresponding to each gene in df_genes + gene_names = [] + gene_cns = [] + gene_states = [] + b = 0 + for g in range(df_genes.shape[0]): + this_chrom = df_genes.int_chrom.values[g] + this_start = df_genes.cdsStart.values[g] + this_end = df_genes.cdsEnd.values[g] + while b < df_hatchet.shape[0] and (df_hatchet.int_chrom.values[b] < this_chrom or (df_hatchet.int_chrom.values[b] == this_chrom and df_hatchet.END.values[b] < this_start)): + b += 1 + if b < df_hatchet.shape[0] and df_hatchet.int_chrom.values[b] == this_chrom and df_hatchet.START.values[b] <= this_start and df_hatchet.END.values[b] >= this_end: + gene_names.append(df_genes.name2.values[g]) + gene_cns.append( np.array([ df_hatchet[f"cn_clone{c}"].values[b] for c in hatchet_clones ]) ) + gene_states.append( np.array([ df_hatchet[f"cnstate_clone{c}"].values[b] for c in hatchet_clones ]) ) + df_hatchet_genes = pd.DataFrame( np.hstack([ np.array(gene_cns), np.array(gene_states) ]), index=gene_names, columns=[f"cn_clone{x}" for x in hatchet_clones] + [f"cnstate_clone{x}" for x in hatchet_clones]) + df_hatchet_genes.to_csv(out_file, sep="\t", header=True, index=True) + + +# if __name__ == "__main__": +# if len(sys.argv) == 1: +# print("python plot_hatchet.py ") +# sys.exit(1) + +# hatchet_dir = sys.argv[1] +# hatchet_cnfile = sys.argv[2] +# out_plot_acn = sys.argv[3] +# out_plot_tcn = sys.argv[4] +# out_file_seg = sys.argv[5] +# out_file_gene = sys.argv[6] +# plot_hatchet_acn(hatchet_dir, hatchet_cnfile, out_plot_acn) +# # plot total copy number +# plot_hatchet_totalcn(hatchet_dir, hatchet_cnfile, out_plot_tcn) +# # output log2 CNV ratio and copy number state of hatchet +# map_hatchet_to_states(f"{hatchet_dir}/results/{hatchet_cnfile}", out_file_seg) +# # output gene-level file +# hgtable_file = "/home/congma/congma/codes/locality-clustering-cnv/data/hgTables_hg38_gencode.txt" +# map_hatchet_to_genes(f"{hatchet_dir}/results/{hatchet_cnfile}", hgtable_file, out_file_gene) \ No newline at end of file diff --git a/utils/process_snps.sh b/utils/process_snps.sh new file mode 100755 index 0000000..bfdef8a --- /dev/null +++ b/utils/process_snps.sh @@ -0,0 +1,59 @@ +#!/bin/bash + +##### input and output data paths ##### +# SAMPLE_ID is used for setting directory/file name +SAMPLE_ID="58408_Primary" +CELLRANGER_OUT="/u/congma/ragr-data/users/congma/Datasets/MM/58408_Primary/cellranger/outs/" +BAMFILE="/u/congma/ragr-data/users/congma/Datasets/MM/58408_Primary/scRNA.unsorted.58408_Primary.bam" +OUTDIR="/u/congma/ragr-data/users/congma/Datasets/MM/58408_Primary/numbatprep/" + +NTHREADS=20 + +##### reference file paths ##### +# PHASING_PANEL is downloaded as instructed in numbat "1000G Reference Panel" and then unzipped. Link to download: wget http://pklab.med.harvard.edu/teng/data/1000G_hg38.zip +PHASING_PANEL="/u/congma/ragr-data/users/congma/references/phasing_ref/1000G_hg38/" +# REGION_VCF serves as the same purpose as "1000G SNP reference file" in numbat, but using a larger SNP set. Link to download: wget https://sourceforge.net/projects/cellsnp/files/SNPlist/genome1K.phase3.SNP_AF5e4.chr1toX.hg38.vcf.gz +REGION_VCF="/u/congma/ragr-data/users/congma/references/snplist/genome1K.phase3.SNP_AF5e4.chr1toX.hg38.vcf.gz" +# HGTABLE_FILE specifies gene positions in the genome, for mapping SNPs to genes. Link to download: https://github.com/raphael-group/STARCH/blob/develop/hgTables_hg38_gencode.txt +HGTABLE_FILE="/u/congma/ragr-data/users/congma/Codes/STARCH_crazydev/hgTables_hg38_gencode.txt" +# there is a reference file in eagle folder +eagledir="/u/congma/ragr-data/users/congma/environments/Eagle_v2.4.1/" + + +##### Following are commands for calling + phasing + processing SNPs ##### +# index bam file +if [[ ! -e ${BAMFILE}.bai ]]; then + samtools index ${BAMFILE} +fi + +# write required barcode list file +mkdir -p ${OUTDIR} +gunzip -c ${CELLRANGER_OUT}/filtered_feature_bc_matrix/barcodes.tsv.gz > ${OUTDIR}/barcodes.txt + +# run cellsnp-lite +mkdir -p ${OUTDIR}/pileup/${SAMPLE_ID} +cellsnp-lite -s ${BAMFILE} \ + -b ${OUTDIR}/barcodes.txt \ + -O ${OUTDIR}/pileup/${SAMPLE_ID} \ + -R ${REGION_VCF} \ + -p ${NTHREADS} \ + --minMAF 0 --minCOUNT 2 --UMItag Auto --cellTAG CB + +# run phasing +mkdir -p ${OUTDIR}/phasing/ +SCRIPTDIR=$(dirname "$0") +python ${SCRIPTDIR}/filter_snps_forphasing.py ${SAMPLE_ID} ${OUTDIR} +for chr in {1..22}; do + bgzip -f ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf + tabix ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf.gz + eagle --numThreads ${NTHREADS} \ + --vcfTarget ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf.gz \ + --vcfRef ${PHASING_PANEL}/chr${chr}.genotypes.bcf \ + --geneticMapFile=${eagledir}/tables/genetic_map_hg38_withX.txt.gz \ + --outPrefix ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.phased +done + + +# run my pythonn to get a cell-by-gene matrix of SNP-covering UMI counts +SCRIPTDIR=$(dirname "$0") +python ${SCRIPTDIR}/get_snp_matrix.py ${OUTDIR} ${SAMPLE_ID} ${HGTABLE_FILE} ${CELLRANGER_OUT}/filtered_feature_bc_matrix/ diff --git a/utils/process_snps_merged.sh b/utils/process_snps_merged.sh new file mode 100755 index 0000000..e1e86c2 --- /dev/null +++ b/utils/process_snps_merged.sh @@ -0,0 +1,65 @@ +#!/bin/bash + +##### input and output data paths ##### +# SAMPLE_ID is used for setting directory/file name +SAMPLE_ID="joint_H1_245_H2_1" +INPUTLIST="/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_snps/joint_H1_245_H2_1/bamfile_list.tsv" +BAMFILE="/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_snps/joint_H1_245_H2_1/possorted_genome_bam.bam" +OUTDIR="/u/congma/ragr-data/datasets/spatial_cna/Lundeberg_organwide/P1_snps/joint_H1_245_H2_1/visium_snpnew" + +NTHREADS=20 + +##### reference file paths ##### +# PHASING_PANEL is downloaded as instructed in numbat "1000G Reference Panel" and then unzipped. Link to download: wget http://pklab.med.harvard.edu/teng/data/1000G_hg38.zip +PHASING_PANEL="/u/congma/ragr-data/users/congma/references/phasing_ref/1000G_hg38/" +# REGION_VCF serves as the same purpose as "1000G SNP reference file" in numbat, but using a larger SNP set. Link to download: wget https://sourceforge.net/projects/cellsnp/files/SNPlist/genome1K.phase3.SNP_AF5e4.chr1toX.hg38.vcf.gz +REGION_VCF="/u/congma/ragr-data/users/congma/references/snplist/nocpg.genome1K.phase3.SNP_AF5e4.chr1toX.hg38.vcf.gz" +# HGTABLE_FILE specifies gene positions in the genome, for mapping SNPs to genes. Link to download: https://github.com/raphael-group/STARCH/blob/develop/hgTables_hg38_gencode.txt +HGTABLE_FILE="/u/congma/ragr-data/users/congma/Codes/STARCH_crazydev/hgTables_hg38_gencode.txt" +# there is a reference file in eagle folder +eagledir="/u/congma/ragr-data/users/congma/environments/Eagle_v2.4.1/" + + +##### Following are commands for calling + phasing + processing SNPs ##### +# index bam file +if [[ ! -e ${BAMFILE}.bai ]]; then + samtools index ${BAMFILE} +fi + +# write required barcode list file +mkdir -p ${OUTDIR} +touch ${OUTDIR}/barcodes.txt +>${OUTDIR}/barcodes.txt +while read -r line; do + CELLRANGER_OUT=$(echo ${line} | awk '{print $3}') + suffix=$(echo ${line} | awk '{print $2}') + gunzip -c ${CELLRANGER_OUT}/filtered_feature_bc_matrix/barcodes.tsv.gz | awk -v var=${suffix} '{print $0"_"var}' >> ${OUTDIR}/barcodes.txt +done < ${INPUTLIST} + +# run cellsnp-lite +mkdir -p ${OUTDIR}/pileup/${SAMPLE_ID} +cellsnp-lite -s ${BAMFILE} \ + -b ${OUTDIR}/barcodes.txt \ + -O ${OUTDIR}/pileup/${SAMPLE_ID} \ + -R ${REGION_VCF} \ + -p ${NTHREADS} \ + --minMAF 0 --minCOUNT 2 --UMItag Auto --cellTAG CB + +# run phasing +mkdir -p ${OUTDIR}/phasing/ +SCRIPTDIR="/u/congma/ragr-data/users/congma/Codes/STARCH_crazydev/scripts" +python ${SCRIPTDIR}/filter_snps_forphasing.py ${SAMPLE_ID} ${OUTDIR} +for chr in {1..22}; do + bgzip -f ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf + tabix ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf.gz + ${eagledir}/eagle --numThreads ${NTHREADS} \ + --vcfTarget ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.vcf.gz \ + --vcfRef ${PHASING_PANEL}/chr${chr}.genotypes.bcf \ + --geneticMapFile=${eagledir}/tables/genetic_map_hg38_withX.txt.gz \ + --outPrefix ${OUTDIR}/phasing/${SAMPLE_ID}_chr${chr}.phased +done + + +# run my pythonn to get a cell-by-gene matrix of SNP-covering UMI counts +#SCRIPTDIR=$(dirname "$0") +python ${SCRIPTDIR}/get_snp_matrix.py ${OUTDIR} ${SAMPLE_ID} ${HGTABLE_FILE} ${OUTDIR}/barcodes.txt ${CELLRANGER_OUT}/filtered_feature_bc_matrix/