Cell-level QC with SampleQC - summary
Will Macnair
Institute for Molecular Life Sciences, University of Zurich, SwitzerlandSwiss Institute of Bioinformatics (SIB), University of Zurich, SwitzerlandMarch 10, 2022
Last updated: 2022-03-10
Checks: 4 3
Knit directory: MS_lesions/
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- plot_qc_summary_heatmap_wm
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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/ms03_SampleQC_summary.Rmd) and HTML (public/ms03_SampleQC_summary.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | fcc465f | wmacnair | 2022-02-11 | Tweak QC metric heatmaps |
| html | fcc465f | wmacnair | 2022-02-11 | Tweak QC metric heatmaps |
| Rmd | aedfb86 | wmacnair | 2022-02-09 | Make and add supp figs on QC metric summaries |
| html | aedfb86 | wmacnair | 2022-02-09 | Make and add supp figs on QC metric summaries |
Setup / definitions
Libraries
Helper functions
source('code/ms00_utils.R')
source('code/ms03_SampleQC.R')Inputs
qc_dir = 'output/ms03_SampleQC'
date_tag = '2021-02-10'
qc_f = file.path(qc_dir, 'ms_qc_dt.txt')
outliers_f = sprintf('%s/outliers_dt_%s.txt', qc_dir, date_tag)
meta_f = "data/metadata/metadata_checked_assumptions_2021-10-08.xlsx"Outputs
Load inputs
outliers_dt = fread(outliers_f) %>% .[, .(sample_id, cell_id, outlier)]
qc_dt = get_qc_dt(qc_dir, qc_f)
meta_dt = load_meta_dt_from_xls(meta_f)Processing / calculations
keep_dt = outliers_dt %>%
.[ (outlier == FALSE) & (sample_id %in% meta_dt$sample_id) ] %>%
.[, .(sample_id, cell_id) ]
qc_stats = qc_dt[ cell_id %in% keep_dt$cell_id ] %>%
.[, log10_N := log10(.N), by = sample_id] %>%
melt.data.table( id = c('sample_id', 'cell_id'),
variable.name = 'qc_var', value.name = 'qc_val' ) %>%
.[, .(med_val = median(qc_val)), by = c('sample_id', 'qc_var')]Analysis
How many cells and samples retained?
(plot_totals_split_by_meta(pre_dt = qc_dt, post_dt = keep_dt, meta_dt))
| Version | Author | Date |
|---|---|---|
| aedfb86 | wmacnair | 2022-02-09 |
QC summaries by sample
sel_ms = c("WM", "GM")
for (sel_m in sel_ms) {
cat("### ", sel_m, "\n")
draw(plot_qc_summary_heatmap(qc_stats, meta_dt[ matter == sel_m ]), merge_legend = TRUE)
cat("\n\n")
}
Ctrl vs MS donor-level metadata
to_show = c('diagnosis', 'sex', 'age_at_death', 'pmi_minutes', 'sample_source')
(plot_ctrl_vs_ms_metadata( meta_dt[ sample_id %in% unique(keep_dt$sample_id) ] , to_show ))
| Version | Author | Date |
|---|---|---|
| aedfb86 | wmacnair | 2022-02-09 |
Lesions per donor
(plot_lesions_per_donor(keep_dt, meta_dt,
to_show = c('NAWM', 'AL', 'CAL', 'CIL', 'RL', 'NAGM', 'GML')))
Outputs
devtools::session_info()- Session info ---------------------------------------------------------------
setting value
version R version 4.0.5 (2021-03-31)
os CentOS Linux 7 (Core)
system x86_64, linux-gnu
ui X11
language (EN)
collate en_US.UTF-8
ctype C
tz Europe/Zurich
date 2022-02-09
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[1] /pstore/home/macnairw/lib/conda_r3.12
[2] /pstore/home/macnairw/.conda/envs/r_4.0.3/lib/R/library
sessionInfo()R version 4.0.5 (2021-03-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS/LAPACK: /pstore/home/macnairw/.conda/envs/r_4.0.3/lib/libopenblasp-r0.3.12.so
locale:
[1] LC_CTYPE=C LC_NUMERIC=C
[3] 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
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] SampleQC_0.6.1 SingleCellExperiment_1.12.0
[3] SummarizedExperiment_1.20.0 Biobase_2.50.0
[5] GenomicRanges_1.42.0 GenomeInfoDb_1.26.7
[7] IRanges_2.24.1 S4Vectors_0.28.1
[9] BiocGenerics_0.36.1 MatrixGenerics_1.2.1
[11] matrixStats_0.61.0 Matrix_1.3-4
[13] loomR_0.2.0 itertools_0.1-3
[15] iterators_1.0.13 hdf5r_1.3.3
[17] R6_2.5.1 patchwork_1.1.1
[19] readxl_1.3.1 forcats_0.5.1
[21] ggplot2_3.3.5 scales_1.1.1
[23] viridis_0.6.2 viridisLite_0.4.0
[25] assertthat_0.2.1 stringr_1.4.0
[27] data.table_1.14.2 magrittr_2.0.1
[29] circlize_0.4.13 RColorBrewer_1.1-2
[31] BiocStyle_2.18.1 colorout_1.2-2
[33] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] colorspace_2.0-2 ellipsis_0.3.2 mclust_5.4.7
[4] rprojroot_2.0.2 XVector_0.30.0 GlobalOptions_0.1.2
[7] fs_1.5.0 farver_2.1.0 remotes_2.4.1
[10] bit64_4.0.5 fansi_0.5.0 mvtnorm_1.1-3
[13] codetools_0.2-18 splines_4.0.5 cachem_1.0.6
[16] knitr_1.36 pkgload_1.2.3 jsonlite_1.7.2
[19] kernlab_0.9-29 uwot_0.1.10 BiocManager_1.30.16
[22] compiler_4.0.5 fastmap_1.1.0 cli_3.0.1
[25] later_1.3.0 htmltools_0.5.2 prettyunits_1.1.1
[28] tools_4.0.5 igraph_1.2.7 gtable_0.3.0
[31] glue_1.4.2 GenomeInfoDbData_1.2.4 dplyr_1.0.7
[34] Rcpp_1.0.7 cellranger_1.1.0 jquerylib_0.1.4
[37] vctrs_0.3.8 xfun_0.27 ps_1.6.0
[40] testthat_3.1.0 lifecycle_1.0.1 gtools_3.9.2
[43] devtools_2.4.2 zlibbioc_1.36.0 MASS_7.3-54
[46] promises_1.2.0.1 yaml_2.2.1 mvnfast_0.2.7
[49] memoise_2.0.0 gridExtra_2.3 sass_0.4.0
[52] segmented_1.3-4 stringi_1.7.4 highr_0.9
[55] desc_1.4.0 pkgbuild_1.2.0 BiocParallel_1.24.1
[58] shape_1.4.6 rlang_0.4.12 pkgconfig_2.0.3
[61] bitops_1.0-7 evaluate_0.14 lattice_0.20-45
[64] purrr_0.3.4 bit_4.0.4 tidyselect_1.1.1
[67] processx_3.5.2 generics_0.1.1 DelayedArray_0.16.3
[70] DBI_1.1.1 pillar_1.6.4 withr_2.4.2
[73] mixtools_1.2.0 survival_3.2-13 RCurl_1.98-1.5
[76] tibble_3.1.5 crayon_1.4.1 utf8_1.2.2
[79] rmarkdown_2.11 usethis_2.1.2 grid_4.0.5
[82] callr_3.7.0 git2r_0.28.0 digest_0.6.28
[85] httpuv_1.6.3 munsell_0.5.0 bslib_0.3.1
[88] sessioninfo_1.1.1