Last updated: 2022-03-02
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Knit directory: BAUH_2020_MND-single-cell/analysis/
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Unstaged changes:
Modified: analysis/2022-01-07_pilot3_Cell-Calling-Comparison.Rmd
Modified: analysis/2022-03-01_pilot3_cellbender.Rmd
Modified: analysis/2022-03-01_pilot3_dropkick.Rmd
Modified: config/config_pilot3.0_MN.yml
Modified: config/config_pilot3.0_iPSC.yml
Modified: workflow/Snakefile
Modified: workflow/rules_cellcalling.smk
Modified: workflow/rules_demultiplexing.smk
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 9eb9fcc | cazodi | 2022-03-01 | add rmd for dropkick and dropletqc |
| html | 9eb9fcc | cazodi | 2022-03-01 | add rmd for dropkick and dropletqc |
cellbender is a deep generative model for inferring empty and cell-containing droplets, learning the background RNA profile, and retrieving uncontaminated counts from the non-empty droplets ( preprint). Like with nearest-neighbor pooling of similar observations, cellbender learns the distribution of gene expression across all droplets using a neural network. The learned distribution acts as a prior over background-corrected gene expression that combines information from similar cells, allowing for significantly improved estimation of background contamination. Learning the prior distribution of biological counts and estimating the background contamination of individual droplets is performed simultaneously and self-consistently within an amortized (incremental) variational inference framework.
These numbers are pulled out of the log files.
c1 <- scan(paste0(mn_dir, "Capture1-GEX/matrix_cell_barcodes.csv"),
what="character")
c2 <- scan(paste0(mn_dir, "Capture2-GEX/matrix_cell_barcodes.csv"),
what="character")
c3 <- scan(paste0(mn_dir, "Capture3-GEX/matrix_cell_barcodes.csv"),
what="character")
c4 <- scan(paste0(mn_dir, "Capture4-GEX/matrix_cell_barcodes.csv"),
what="character")
c5 <- scan(paste0(ipsc_dir, "Capture5-GEX/matrix_cell_barcodes.csv"),
what="character")
run_stats <- as.data.frame(list(non_zero_genes=c(28209, 28463, 28514, 28143, 26815),
prior_count_empty=c(491, 600, 600, 329, 65),
prior_count_cell=c(995, 1199, 1064, 1148, 8739),
excluding_counts_below=c(245, 300, 300, 164, 32),
largest_empty_barcode=c(579, 683, 646, 711, 5283),
optimal_regularization=c(0.70, 0.77, 0.66, 0.94, 1.97),
nCells=c(length(c1), length(c2), length(c3),
length(c4), length(c5))))
rownames(run_stats) <- c("Capture1", "Capture2", "Capture3", "Capture4", "Capture5")
round(t(run_stats),0) Capture1 Capture2 Capture3 Capture4 Capture5
non_zero_genes 28209 28463 28514 28143 26815
prior_count_empty 491 600 600 329 65
prior_count_cell 995 1199 1064 1148 8739
excluding_counts_below 245 300 300 164 32
largest_empty_barcode 579 683 646 711 5283
optimal_regularization 1 1 1 1 2
nCells 8582 8827 8113 19979 20000Summary figures from cellbender
sessionInfo()R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux 8.5 (Ootpa)
Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.12.so
locale:
[1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
[5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
[7] LC_PAPER=en_AU.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] data.table_1.14.2 tidyr_1.1.4 dplyr_1.0.7
loaded via a namespace (and not attached):
[1] Rcpp_1.0.7 pillar_1.6.4 compiler_4.1.1 bslib_0.3.1
[5] later_1.3.0 jquerylib_0.1.4 git2r_0.29.0 highr_0.9
[9] workflowr_1.6.2 tools_4.1.1 digest_0.6.29 jsonlite_1.7.2
[13] evaluate_0.14 lifecycle_1.0.1 tibble_3.1.6 pkgconfig_2.0.3
[17] rlang_0.4.12 DBI_1.1.1 yaml_2.2.1 xfun_0.28
[21] fastmap_1.1.0 stringr_1.4.0 knitr_1.36 generics_0.1.1
[25] fs_1.5.2 vctrs_0.3.8 sass_0.4.0 tidyselect_1.1.1
[29] rprojroot_2.0.2 glue_1.6.0 R6_2.5.1 fansi_1.0.0
[33] rmarkdown_2.11 purrr_0.3.4 magrittr_2.0.1 whisker_0.4
[37] promises_1.2.0.1 ellipsis_0.3.2 htmltools_0.5.2 assertthat_0.2.1
[41] httpuv_1.6.5 utf8_1.2.2 stringi_1.7.6 crayon_1.4.2