wrap_expression function reverse feature and cell ids from Seurat objects #162
Description
Hi devs!!
I am running into a problem where the feature_ids and cell_ids are reversed from a Seurat object source.
I ran the first lines to prepare the data as explain in the Quick start of dynverse.
SO <- readRDS("my_file.rds")
dataset <- wrap_expression(
counts = SO@assays[["RNA"]]@counts,
expression = SO@assays[["RNA"]]@data
)
guidelines <- guidelines_shiny(dataset)
I tried to use the function provided in the issue dynverse/dynwrap #150 . Unfortunately, the counts and data information are not stored into a matrix, so the transpose function does not work.
> str(SO@assays[["RNA"]]@counts)
Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
..@ i : int [1:113749606] 2 3 4 5 9 13 17 22 24 27 ...
..@ p : int [1:21886] 0 6676 11901 17770 24860 31899 37467 43675 49359 52809 ...
..@ Dim : int [1:2] 23913 21885
..@ Dimnames:List of 2
.. ..$ : chr [1:23913] "Xkr4" "Rp1" "Sox17" "Mrpl15" ...
.. ..$ : chr [1:21885] "GAS_Day4_batch4_AAACCCATCGACTCCT" "GAS_Day4_batch4_AAACGAAGTCATAACC" "GAS_Day4_batch4_AAACGCTCAAGCGAGT" "GAS_Day4_batch4_AAACGCTCACCCTAAA" ...
..@ x : num [1:113749606] 5 9 1 1 2 2 1 2 7 7 ...
..@ factors : list()
In summary, I have in my dataset
- 21885 cells
- 23913 features
For comparison, after wrap_expression() function I run into a dataset with
- 23913 cells (based on cell_ids factor)
- 21885 features (based on features_ids factor)
as shown in the dynguidelines, when I do
> guidelines <- guidelines_shiny(dataset)
> str(dataset)
List of 8
$ id : chr "20211022_112041__data_wrapper__rrmsZuUNII"
$ cell_ids : chr [1:23913] "Xkr4" "Rp1" "Sox17" "Mrpl15" ...
$ cell_info : tbl_df [23,913 × 1] (S3: tbl_df/tbl/data.frame)
..$ cell_id: chr [1:23913] "Xkr4" "Rp1" "Sox17" "Mrpl15" ...
$ feature_ids : chr [1:21885] "GAS_Day4_batch4_AAACCCATCGACTCCT" "GAS_Day4_batch4_AAACGAAGTCATAACC" "GAS_Day4_batch4_AAACGCTCAAGCGAGT" "GAS_Day4_batch4_AAACGCTCACCCTAAA" ...
$ feature_info : tbl_df [21,885 × 1] (S3: tbl_df/tbl/data.frame)
..$ feature_id: chr [1:21885] "GAS_Day4_batch4_AAACCCATCGACTCCT" "GAS_Day4_batch4_AAACGAAGTCATAACC" "GAS_Day4_batch4_AAACGCTCAAGCGAGT" "GAS_Day4_batch4_AAACGCTCACCCTAAA" ...
$ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. ..@ i : int [1:113749606] 2 3 4 5 9 13 17 22 24 27 ...
.. ..@ p : int [1:21886] 0 6676 11901 17770 24860 31899 37467 43675 49359 52809 ...
.. ..@ Dim : int [1:2] 23913 21885
.. ..@ Dimnames:List of 2
.. .. ..$ : chr [1:23913] "Xkr4" "Rp1" "Sox17" "Mrpl15" ...
.. .. ..$ : chr [1:21885] "GAS_Day4_batch4_AAACCCATCGACTCCT" "GAS_Day4_batch4_AAACGAAGTCATAACC" "GAS_Day4_batch4_AAACGCTCAAGCGAGT" "GAS_Day4_batch4_AAACGCTCACCCTAAA" ...
.. ..@ x : num [1:113749606] 5 9 1 1 2 2 1 2 7 7 ...
.. ..@ factors : list()
$ expression :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. ..@ i : int [1:113749606] 2 3 4 5 9 13 17 22 24 27 ...
.. ..@ p : int [1:21886] 0 6676 11901 17770 24860 31899 37467 43675 49359 52809 ...
.. ..@ Dim : int [1:2] 23913 21885
.. ..@ Dimnames:List of 2
.. .. ..$ : chr [1:23913] "Xkr4" "Rp1" "Sox17" "Mrpl15" ...
.. .. ..$ : chr [1:21885] "GAS_Day4_batch4_AAACCCATCGACTCCT" "GAS_Day4_batch4_AAACGAAGTCATAACC" "GAS_Day4_batch4_AAACGCTCAAGCGAGT" "GAS_Day4_batch4_AAACGCTCACCCTAAA" ...
.. ..@ x : num [1:113749606] 0.663 0.99 0.172 0.172 0.319 ...
.. ..@ factors : list()
$ expression_future: NULL
- attr(*, "class")= chr [1:3] "dynwrap::with_expression" "dynwrap::data_wrapper" "list"
I wonder if the trajectory inference methods will well retrieve the information for the step after in infer_trajectory() function.
Does someone know how to get information properly from a Seurat object ?
Thanks,
Céline
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS
Matrix products: default
BLAS: /opt/anaconda3/envs/rossi/lib/libblas.so.3.8.0
LAPACK: /opt/anaconda3/envs/rossi/lib/liblapack.so.3.8.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] shiny_1.6.0 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.3
[6] readr_1.4.0 tidyr_1.1.3 tibble_3.0.3 ggplot2_3.2.1 tidyverse_1.2.1
[11] dyno_0.1.2 dynwrap_1.2.2 dynplot_1.1.0 dynmethods_1.0.5 dynguidelines_1.0.1
[16] dynfeature_1.0.0
loaded via a namespace (and not attached):
[1] readxl_1.3.1 backports_1.2.1 dyndimred_1.0.4 babelwhale_1.0.3 plyr_1.8.6
[6] igraph_1.2.6 lazyeval_0.2.2 sp_1.4-5 proxyC_0.2.1 splines_3.6.1
[11] listenv_0.8.0 digest_0.6.27 foreach_1.5.1 htmltools_0.5.1.1 viridis_0.5.1
[16] fansi_0.4.2 magrittr_2.0.1 carrier_0.1.0 cluster_2.1.0 ROCR_1.0-11
[21] remotes_2.3.0 globals_0.14.0 graphlayouts_0.7.1 modelr_0.1.8 RcppParallel_5.1.4
[26] R.utils_2.10.1 dynutils_1.0.9 colorspace_2.0-2 rvest_1.0.0 ggrepel_0.8.1
[31] rbibutils_2.1.1 haven_2.4.1 crayon_1.4.1 jsonlite_1.7.2 hexbin_1.28.1
[36] zoo_1.8-9 survival_3.2-11 iterators_1.0.13 ape_5.5 glue_1.4.2
[41] polyclip_1.10-0 gtable_0.3.0 leiden_0.3.8 future.apply_1.7.0 dynparam_1.0.2
[46] scales_1.1.1 DBI_1.1.1 Rcpp_1.0.7 metap_1.1 viridisLite_0.3.0
[51] xtable_1.8-4 reticulate_1.20 rsvd_1.0.3 akima_0.6-2.2 SDMTools_1.1-221.2
[56] tsne_0.1-3 htmlwidgets_1.5.3 httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.2
[61] Seurat_3.1.1 ica_1.0-2 pkgconfig_2.0.3 R.methodsS3_1.8.1 farver_2.1.0
[66] sass_0.4.0 uwot_0.1.5 utf8_1.2.1 tidyselect_1.1.1 labeling_0.4.2
[71] rlang_0.4.11 reshape2_1.4.4 later_1.2.0 cachem_1.0.5 munsell_0.5.0
[76] cellranger_1.1.0 tools_3.6.1 cli_2.5.0 generics_0.1.0 ranger_0.13.1
[81] broom_0.7.6 ggridges_0.5.3 fastmap_1.1.0 yaml_2.2.1 processx_3.5.2
[86] fitdistrplus_1.1-3 tidygraph_1.2.0 lmds_0.1.0 RANN_2.6.1 ggraph_2.0.5
[91] pbapply_1.4-3 future_1.21.0 nlme_3.1-150 mime_0.10 GA_3.2.2
[96] R.oo_1.24.0 xml2_1.3.2 compiler_3.6.1 rstudioapi_0.13 plotly_4.9.1
[101] png_0.1-7 testthat_3.0.2 tweenr_1.0.2 bslib_0.2.5.1 stringi_1.4.6
[106] ps_1.6.0 desc_1.3.0 lattice_0.20-44 Matrix_1.2-18 shinyjs_2.0.0
[111] vctrs_0.3.8 pillar_1.6.1 lifecycle_1.0.0 jquerylib_0.1.4 Rdpack_2.1.1
[116] lmtest_0.9-38 RcppAnnoy_0.0.18 data.table_1.14.0 cowplot_1.1.1 irlba_2.3.3
[121] httpuv_1.6.1 patchwork_1.1.1 R6_2.5.0 promises_1.2.0.1 KernSmooth_2.23-18
[126] gridExtra_2.3 vipor_0.4.5 parallelly_1.25.0 codetools_0.2-18 MASS_7.3-54
[131] assertthat_0.2.1 rprojroot_2.0.2 shinyWidgets_0.6.2 withr_2.4.2 sctransform_0.2.0
[136] parallel_3.6.1 hms_1.1.0 grid_3.6.1 waldo_0.2.5 Rtsne_0.15
[141] ggforce_0.3.3 lubridate_1.7.10