-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathmethylomes.html
317 lines (296 loc) · 23.2 KB
/
methylomes.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
<meta name="author" content="">
<link rel="icon" href="images/rnb_favicon.ico">
<title>RnBeads</title>
<!-- Bootstrap Core CSS -->
<link href="css/bootstrap.min.css" rel="stylesheet">
<!-- Custom CSS -->
<link href="css/small-business.css" rel="stylesheet">
</head>
<body>
<!-- Navigation -->
<nav class="navbar navbar-default navbar-fixed-top" role="navigation">
<div class="container">
<!-- Brand and toggle get grouped for better mobile display -->
<div class="navbar-header">
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
<span class="sr-only">Toggle navigation</span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="navbar-brand" href="index.html">
<img src="images/rnb_logo_145x50.png" alt="">
</a>
</div>
<!-- Collect the nav links, forms, and other content for toggling -->
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav">
<li>
<a href="index.html">About</a>
</li>
<li>
<a href="installation.html">Installation</a>
</li>
<li>
<a href="tutorial.html">Tutorials</a>
</li>
<li>
<a href="examples.html">Examples</a>
</li>
<li class="dropdown active">
<a class="dropdown-toggle" data-toggle="dropdown" href="#">Resources
<span class="caret"></span></a>
<ul class="dropdown-menu">
<li class="active"><a href="methylomes.html">Methylome Resource</a></li>
<li><a href="regions.html">Region Sets</a></li>
<li><a href="ageprediction.html">Age Prediction</a></li>
</ul>
</li>
<li>
<a href="references.html">References</a>
</li>
<li>
<a href="faq.html">FAQ</a>
</li>
<!-- <li>
<a href="webservice.html">Webservice</a>
</li> -->
<li>
<a href="contact.html">Contact</a>
</li>
</ul>
</div>
<!-- /.navbar-collapse -->
</div>
<!-- /.container -->
</nav>
<!-- Page Content -->
<div class="container">
<!-- Page Heading/Breadcrumbs -->
<h1 class="mt-4 mb-3">Methylome Resource <!-- <small>Comprehensive RnBeads analyses of large-scale reference epigenome datasets</small> --></h1>
<!--
<ol class="breadcrumb">
<li class="breadcrumb-item">
<a href="index.html">Home</a>
</li>
<li class="breadcrumb-item active">Contact</li>
</ol>
-->
<div class="row">
<div class="col-md-12">
<p>The Methylome Resource was established by applying <a href="index.html">RnBeads</a> to some of the largest public reference datasets that are currently available for whole genome bisulfite sequencing (WGBS), for reduced representation bisulfite sequencing (RRBS) and for the Illumina Infinium HumanMethylation450 assay. This resource provides a reference for large-scale DNA methylation analyses that can be used in complementary ways:
<ul>
<li>Researchers can browse the reports online, explore biological hypotheses and load relevant data points for visual inspection or custom data analysis into R or into other software tools. For instance, using the links from the "Tracks and Tables" reports, the tracks can be visualized in various Genome Browsers.<br />
<i>↳ To explore the Methylome Resource, please click any of the "View analysis report" links below.</i>
</li>
<li>Researchers can download the data and configuration files, add their own DNA methylation data and then run RnBeads in order to analyze their data in the context of methylome datasets that span a broad set of tissue types.<br />
<i>↳ To rerun the Methylome Resource analyses, please download the data and configuration files from the table below. Each dataset can either run in full or using a representative subset of samples to reduce runtime. A more detailed explanation on how to run these analyses is available on the <a href="faq.html">FAQ</a> page.</i>
</li>
</ul>
</p>
<table class="table table-hover">
<thead>
<tr>
<th>Resource</th>
<th>Data Source</th>
<th>Data Archive</th>
<th>Sample Annotation Files</th>
<th>RnBeads Configuration</th>
</tr>
</thead>
<tbody>
<tr>
<td rowspan="2">Genome-scale RRBS data for<br />216 tissues and cell lines</td>
<td rowspan="2"><a href="https://www.encodeproject.org/">Encode Project Website</a></td>
<td rowspan="2"><a href="./materials/resource/encode/data.zip"><code>data.zip</code></a> (3 GB)</td>
<td><a href="./materials/resource/encode/samples.csv"><code>samples.csv</code></a> (all samples)</td>
<td rowspan="2"><a href="./materials/resource/encode/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr class="section">
<td><a href="./materials/resource/encode/17/samples.csv"><code>samples.csv</code></a> (17 untreated samples)</td>
</tr>
<tr>
<td rowspan="2">Genome-wide WGBS data for<br />41 tissues and cell lines</td>
<td rowspan="2"><a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46644">Gene Expression Omnibus</a></td>
<td rowspan="2"><a href="./materials/resource/ziller2013/data.zip"><code>data.zip</code></a> (10 GB)</td>
<td><a href="./materials/resource/ziller2013/samples.csv"><code>samples.csv</code></a> (all 41 samples)</td>
<td rowspan="2"><a href="./materials/resource/ziller2013/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr class="section">
<td><a href="./materials/resource/ziller2013/samples.csv"><code>samples.csv</code></a> (10 adult primary tissues)</td>
</tr>
<tr>
<td rowspan="2">Infinium 450k data for<br />4034 cancer and normal samples</td>
<td rowspan="2"><a href="https://portal.gdc.cancer.gov/">TCGA data portal</a></td>
<td rowspan="2"><a href="./materials/resource/tcga/data.zip"><code>data.zip</code></a> (34 GB)</td>
<td><a href="./materials/resource/tcga/samples.csv"><code>samples.csv</code></a> (all samples)</td>
<td rowspan="2"><a href="./materials/resource/tcga/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr class="section">
<td><a href="./materials/resource/tcga/40/samples.csv"><code>samples.csv</code></a> (40 samples from 10 primary tumors)</td>
</tr>
<tr>
<td>WGBS data for BLUEPRINT<br />methylomes (2015 release)</td>
<td><a href="http://dcc.blueprint-epigenome.eu/">BLUEPRINT data portal</a></td>
<td><a href="./materials/resource/blueprint/data.zip"><code>data.zip</code></a> (18 GB)</td>
<td><a href="./materials/resource/blueprint/samples.tsv"><code>samples.tsv</code></a> (81 samples)</td>
<td><a href="./materials/resource/blueprint/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr>
<td>WGBS and NOMe-seq data for<br />T cell memory formation</td>
<td><a href="http://deep.dkfz.de">DEEP data portal</a></td>
<td><a href="./materials/resource/deepTcells/import_RnBSet.zip"><code>import_RnBSet.zip</code></a><br />(2 GB; <code>RnBSet</code> object)</td>
<td><a href="./materials/resource/deepTcells/samples.tsv"><code>samples.tsv</code></a> (13 samples)</td>
<td><a href="./materials/resource/deepTcells/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr>
<td>[Use case 1] Infinium 450k data for whole blood and sorted blood cells</td>
<td><a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE87571">GEO</a><br /><a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35069">GEO</a></td>
<td><a href="./materials/resource/450k_blood_JR/data.zip"><code>data.zip</code></a> (6.3 GB)</td>
<td><a href="./materials/resource/450k_blood_JR/samples.csv"><code>samples.csv</code></a> (792 samples)</td>
<td><a href="./materials/resource/450k_blood_JR/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr>
<td>[Use case 2] WGBS data for BLUEPRINT<br />methylomes (2016 release)</td>
<td><a href="http://dcc.blueprint-epigenome.eu/">BLUEPRINT data portal</a></td>
<td><a href="./materials/resource/blueprint2016/data.zip"><code>data.zip</code></a> (45 GB)</td>
<td><a href="./materials/resource/blueprint2016/samples.tsv"><code>samples.tsv</code></a> (195 samples)</td>
<td><a href="./materials/resource/blueprint2016/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
<tr>
<td>[Use case 3] RRBS data for Ewing Sarcoma (188 samples)</td>
<td><a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE88826">Gene Expression Omnibus</a></td>
<td><a href="./materials/resource/ewing/data.zip"><code>data.zip</code></a> (5.7 GB)</td>
<td><a href="./materials/resource/ewing/samples.csv"><code>samples.csv</code></a> (188 samples)</td>
<td><a href="./materials/resource/ewing/analysis.xml"><code>analysis.xml</code></a><br /><a href="./materials/resource/ewing/preanalysis.R"><code>preanalysis.R</code></a></td>
</tr>
<tr>
<td>[Use case 4] Cross-platform data set (450k, EPIC, WGBS) from an EPIC evaluation study</td>
<td><a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86831">GEO</a></td>
<td><a href="./materials/resource/pidsley2016_crossplatform/dataset-all.zip"><code>combined RnBSet</code></a><br />(136 MB)</td>
<td></td>
<td><a href="./materials/resource/pidsley2016_crossplatform/analysis.xml"><code>analysis.xml</code></a></td>
</tr>
</tbody>
</table>
</div>
</div>
<!-- /.row -->
<div class="row">
<div class="col-md-6">
<h3>Resource 1: Genome-scale RRBS data for 216 tissues and cell lines</h3>
<p>
In the context of the <a href="https://www.genome.gov/Funded-Programs-Projects/ENCODE-Project-ENCyclopedia-Of-DNA-Elements">ENCODE</a> project, <a href="http://genome.cshlp.org/content/23/3/555">Varley et al.</a> established genome-scale DNA methylation maps for various tissue samples and cell lines using reduced representation bisulfite sequencing (RRBS). This <b>RnBeads</b> analysis of 216 samples shows that cells from different germ layers are clearly distinguished by their DNA methylation profiles, and it identifies characteristic loci that can be used for classifying samples according to their tissue type. Including parts or all of this dataset in custom RnBeads analyses provides a useful reference for quality control, analysis and interpretation of user-generated DNA methylation datasets.
</p>
<img class="img-responsive img-rounded" src="images/encode_pca_scatter.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_ENCODE/index.html">View analysis reports</a>
</div>
<div class="col-md-6">
<h3>Resource 2: Genome-wide WGBS data for 41 tissues and cell lines</h3>
<p>
<a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12433.html">Ziller et al.</a> compiled whole genome bisulfite sequencing (WGBS) data for 41 tissues and cell lines comprising data from the Roadmap Epigenomics Project and other sources. The <b>RnBeads</b> analysis identified clear grouping of samples according to tissue types. Furthermore, sample type is strongly correlated with the laboratory performing the experiment. Outliers in terms of experimental quality as well as long term cell culturing are identified. This analysis illustrates how this methylome resource can be used for identifying both technical and biological outliers in large-scale DNA methylation datasets.
</p>
<img class="img-responsive img-rounded" src="images/ziller_wgbs_cluster_heatmap.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_Ziller2013_WGBS/index.html">View analysis reports</a>
</div>
</div>
<!-- /.row -->
<div class="row">
<div class="col-md-6">
<h3>Resource 3: Infinium 450k data for 4034 cancer samples</h3>
<p>
In the context of <a href="https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga">The Cancer Genome Atlas (TCGA)</a> researchers have generated a large collection of cancer methylomes using the Infinium 450k assay. While an integrative analysis of the full dataset has not been published yet, <a href="https://www.jci.org/articles/view/69740">Weisenberger</a> recently summarized and reviewed the activities that led to creating this dataset. This <b>RnBeads</b> analysis of 4034 blood, breast, intestinal and brain cancer samples provides an extensive and interactively browsable analysis of this dataset, which can be used as a starting point for more targeted investigation and hypothesis testing, but also as a reference for interpreting DNA methylation aberrations observed in other cancer cohorts.
</p>
<img class="img-responsive img-rounded" src="images/tcga_scatter_mds_study_cgis.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_TCGA/index.html">View analysis reports</a>
</div>
<div class="col-md-6">
<h3>Resource 4: Analysis of BLUEPRINT methylomes (WGBS, 2015 release)</h3>
<p>
In the context of the BLUEPRINT project, whole genome bisulfite sequencing data have been generated for 81 blood related samples. Among others primary monocyte and neutrophil cell samples from healthy donors were profiled. The <b>RnBeads</b> analysis shows similar methylomes between these two closely related cell types, but also significant DNA methylation differences enriched for important biological processes of the immune system.
</p>
<img class="img-responsive img-rounded" src="images/blueprint_differential_scatter.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_bp_wgbs_v201508excl/index.html">View analysis reports</a>
</div>
</div>
<!-- /.row -->
<div class="row">
<div class="col-md-6">
<h3>Resource 5: DNA methylation reprogramming in memory formation of human T cells (WGBS, NOMe-seq)</h3>
<p>
In the context of the DEEP project, whole genome bisulfite sequencing and NOMe-seq data have been generated for multiple stages during the process of memory formation in human CD4+ T cells <a href="https://doi.org/10.1016/j.immuni.2016.10.022">(Durek et al., 2016)</a>. The data was anlyzed in <b>RnBeads</b>. The results show a progressive loss of DNA methylation during memory formation, particularly in putative regulatory regions of the genome. Two technologies (WGBS and NOMe-seq) were employed to assess CpG methylation levels. Overall, the agreement between both methods is high.
</p>
<img class="img-responsive img-rounded" src="images/deep_tmem_heatmap.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_deep_tmem/index.html">View analysis reports</a>
</div>
<div class="col-md-6">
<h3>Resource 6 [use case 1]: Infinium 450k data for 792 whole blood and sorted blood cells</h3>
<p>
Combined cohort of two studies: (1) 732 whole blood samples from an age study by <a href="https://www.ncbi.nlm.nih.gov/pubmed/23826282">Johansson <i>et al</i>.</a>, and (2) 60 samples from isolated cell types, peripheral blood and whole blood from cell type composition study by <a href="https://www.ncbi.nlm.nih.gov/pubmed/22848472">Reinius <i>et al</i>.</a> The IDAT files and sample annotations are obtained from the Gene Expression Omnibus, data series <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE87571">GSE87571</a> and <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35069">GSE35069</a>.
</p>
<img class="img-responsive img-rounded" src="images/johansson_ageprediction.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/450k_blood_JR/index.html">View analysis reports</a>
</div>
</div>
<div class="row">
<div class="col-md-6">
<h3>Resource 7 [use case 2]: Analysis of BLUEPRINT methylomes (WGBS, 2016 release)</h3>
<p>
The final release of the BLUEPRINT project contained whole genome bisulfite sequencing profiles for healthy and malignant blood cell types. The <b>RnBeads</b> analysis of 195 samples identified cell-type-specific variability in methylation patterns and indicated epigenetic similarity between cell types that share a common differentiation history.
</p>
<img class="img-responsive img-rounded" src="images/blueprint2016_dimred.png" alt="">
<br clear="all" />
<!-- <a class="btn btn-primary" href="./materials/reports/bpRel201609_rnb_v02/index.html">View analysis reports</a> -->
<a class="btn btn-primary" href="./materials/reports/bpRel201609_rnb_v04/index.html">View analysis reports</a>
</div>
<div class="col-md-6">
<h3>Resource 8 [use case 3]: DNA methylation variability associated with Ewing Sarcoma (RRBS, 188 samples)</h3>
<p>
This analysis focuses on DNA methylation associated with Ewing Sarcoma, a bone cancer primarily affecting children and young adults. In addition to Ewing tissue samples, healthy Mesenchymal Stem Cells (MSCs), MSCs affected with Ewing sarcoma and Ewing Cell Lines are part of the data set <a href="https://www.nature.com/articles/nm.4273">(Sheffield et al., 2017)</a>. Using <b>RnBeads'</b> differential methylation module, only few differences between the groups could be detected. However, higher methylation variability was detected in normal MSCs vs. MSCs affected with Ewing Sarcoma, contradicting the assumption that Ewing Sarcoma increases heterogeneity among individual samples.
</p>
<img class="img-responsive img-rounded" src="images/ewing_rrbs_0218.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/reports_Ewing/index.html">View analysis reports</a>
</div>
</div>
<!-- /.row -->
<div class="row">
<div class="col-md-6">
<h3>Resource 9 [use case 4]: Analysis of a cross-platform data set (450k, EPIC, WGBS) from an EPIC evaluation study</h3>
<p>
<a href="https://www.ncbi.nlm.nih.gov/pubmed/27717381">Pidsley <i>et al.</i></a> performed a critical evaluation of the EPIC array using a selection of of prostate cancer samples, healthy control tissues and prostate cell lines (<a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86831">GEO: GSE86831</a>). They compared the results of profiling with EPIC array to the predecessor array version, Infinium 450k, as well as whole-genome methylomes of similar samples. Using the recently extended RnBSet merging functionality we processed all these data jointly in one RnBeads analysis. The results showed that, although there are clear technical differences between the methylation values obtained with the three platforms, biological variability could still break through the platform-specific biases. Combined differential methylation analysis in mixed groups of samples measured with different platforms often lead to meaningful functional annotation enrichments.
</p>
<img class="img-responsive img-rounded" src="images/crossplatform_pca.png" alt="">
<br clear="all" />
<a class="btn btn-primary" href="./materials/reports/report_prostate_crossplatform/index.html">View analysis reports</a>
</div>
</div>
<!-- /.row -->
</div>
<!-- /.container -->
<!-- Footer -->
<hr>
<footer class="py-5 bg-inverse">
<div class="container">
<p class="m-0 text-center text-white">Copyright © <a href="mailto:[email protected]">RnBeads Development Team</a> 2024 | <a href="https://cemm.at/contact/disclaimer/">Disclaimer / Impressum / Data protection</a></p>
</div>
</footer>
<!-- jQuery -->
<script src="js/jquery.js"></script>
<!-- Bootstrap Core JavaScript -->
<script src="js/bootstrap.min.js"></script>
</body>
</html>