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Reference: Lareau, C., Duarte, F., Chew, J., Kartha, V., Burkett, Z., Kohlway, A., Pokholok, D., Aryee, M., Steemers, F., Lebofsky, R., Buenrostro, J. (2019). Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility Nature Biotechnology 518(1), 1 15. https://dx.doi.org/10.1038/s41587-019-0147-6
Downloaded GSE123576_mousebrain_countsData_revision.csv.gz from the Gene Expression Omnibus (GEO) website, accession GSE123576. RCC directory: /project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/
library(Matrix)
library(readr)out <- read_delim("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/raw_data/GSE123576_mousebrain_countsData_revision.csv.gz",delim = " ")
class(out) <- "data.frame"
# binarize counts
out$binarized_count <- as.integer(out$count > 0)samples <- read.table("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/raw_data/GSE123576_mousebrain_cellData_revision.tsv.gz", header = TRUE, stringsAsFactors = FALSE, sep = "\t")
dim(samples)[1] 46653 3cat(sprintf("Number of samples: %d\n",nrow(samples)))Number of samples: 46653print(samples[1:3,]) DropBarcode FRIP clusters
1 N701_Exp119_sample1_S1_BC0003_N01 0.505 9
2 N701_Exp119_sample1_S1_BC0004_N01 0.477 13
3 N701_Exp119_sample1_S1_BC0005_N01 0.496 13peaks <- read.table("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/raw_data/GSE123576_mousebrain_peaks_revision.bed.gz", header = FALSE, stringsAsFactors = FALSE, sep = "\t")
colnames(peaks) <- c("chr", "start", "end")
peaks$name <- paste0(peaks$chr, ":", peaks$start, "-", peaks$end)
cat(sprintf("Number of peaks: %d\n",nrow(peaks)))Number of peaks: 454047print(peaks[1:3,]) chr start end name
1 chr1 3042897 3043397 chr1:3042897-3043397
2 chr1 3094911 3095411 chr1:3094911-3095411
3 chr1 3113443 3113943 chr1:3113443-3113943counts <- sparseMatrix(i = out$cell_idx, j = out$peak_idx, x = out$binarized_count,
dims = c(max(out$cell_idx), max(out$peak_idx)),
dimnames = list(sample = samples$DropBarcode,
peak = peaks$name))j <- which(colSums(counts > 0) >= 1)
peaks <- peaks[j,]
counts <- counts[,j]data.dir <- "/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/processed_data/"
dir.create(data.dir, showWarnings = FALSE, recursive = TRUE)
saveRDS(counts, file.path(data.dir, "counts_Lareau_2019_mousebrain.rds"))
save(list = c("samples", "peaks", "counts"), file = file.path(data.dir, "Lareau_2019_mousebrain.RData"))data.dir <- "/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/mouse_brain/processed_data/"
load(file.path(data.dir, "Lareau_2019_mousebrain.RData"))
cat(sprintf("Loaded %d x %d counts matrix.\n",nrow(counts),ncol(counts)))Loaded 46653 x 451300 counts matrix.cat(sprintf("Number of samples (cells): %d\n",nrow(counts)))Number of samples (cells): 46653cat(sprintf("Number of peaks: %d\n",ncol(counts)))Number of peaks: 451300cat(sprintf("Proportion of counts that are non-zero: %0.1f%%.\n",
100*mean(counts > 0)))Proportion of counts that are non-zero: 2.1%.Downloaded GSE123580_bonemarrow_countsData.csv.gz from the Gene Expression Omnibus (GEO) website, accession GSE123580. RCC directory: /project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/
library(Matrix)
library(readr)
out <- read_delim("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/raw_data/GSE123580_bonemarrow_countsData.csv.gz",delim = " ")
class(out) <- "data.frame"
# binarize counts
out$binarized_count <- as.integer(out$count > 0)samples <- read.table("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/raw_data/GSE123580_bonemarrow_cellData.tsv.gz", header = TRUE, stringsAsFactors = FALSE, sep = "\t")
dim(samples)[1] 136463 4cat(sprintf("Number of samples: %d\n",nrow(samples)))Number of samples: 136463print(samples[1:3,]) DropBarcode FRIP Cluster Condition
1 Exp100-Sample9.all_Tn5-AAAGAA_BC00404_N03 0.755 HSPC Resting
2 Exp100-Sample9.all_Tn5-AAAGAA_BC00461_N02 0.773 HSPC Resting
3 Exp100-Sample9.all_Tn5-AAAGAA_BC00600_N02 0.763 HSPC Restingpeaks <- read.table("/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/raw_data/GSE123580_bonemarrow_peaks.bed.gz", header = FALSE, stringsAsFactors = FALSE, sep = "\t")
colnames(peaks) <- c("chr", "start", "end")
peaks$name <- paste0(peaks$chr, ":", peaks$start, "-", peaks$end)
cat(sprintf("Number of peaks: %d\n",nrow(peaks)))Number of peaks: 156311print(peaks[1:3,]) chr start end name
1 chr1 9942 10442 chr1:9942-10442
2 chr1 11036 11536 chr1:11036-11536
3 chr1 12478 12978 chr1:12478-12978counts <- sparseMatrix(i = out$cell_idx, j = out$peak_idx, x = out$binarized_count,
dims = c(max(out$cell_idx), max(out$peak_idx)),
dimnames = list(sample = samples$DropBarcode,
peak = peaks$name))j <- which(colSums(counts > 0) >= 1)
peaks <- peaks[j,]
counts <- counts[,j]data.dir <- "/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/processed_data/"
dir.create(data.dir, showWarnings = FALSE, recursive = TRUE)
saveRDS(counts, file.path(data.dir, "counts_Lareau_2019_bonemarrow.rds"))
save(list = c("samples", "peaks", "counts"), file = file.path(data.dir, "Lareau_2019_bonemarrow.RData"))data.dir <- "/project2/mstephens/kevinluo/scATACseq-topics/data/Lareau_2019/bone_marrow/processed_data/"
load(file.path(data.dir, "Lareau_2019_bonemarrow.RData"))
cat(sprintf("Loaded %d x %d counts matrix.\n",nrow(counts),ncol(counts)))Loaded 136463 x 146860 counts matrix.cat(sprintf("Number of samples (cells): %d\n",nrow(counts)))Number of samples (cells): 136463cat(sprintf("Number of peaks: %d\n",ncol(counts)))Number of peaks: 146860cat(sprintf("Proportion of counts that are non-zero: %0.1f%%.\n",
100*mean(counts > 0)))Proportion of counts that are non-zero: 0.7%.
sessionInfo()R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 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] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readr_1.3.1 Matrix_1.2-15 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.4.6 knitr_1.28 whisker_0.4 magrittr_1.5
[5] hms_0.4.2 lattice_0.20-38 R6_2.4.1 rlang_0.4.6
[9] stringr_1.4.0 tools_3.5.1 grid_3.5.1 xfun_0.14
[13] git2r_0.27.1 ellipsis_0.3.1 htmltools_0.4.0 yaml_2.2.0
[17] digest_0.6.25 rprojroot_1.3-2 lifecycle_0.2.0 tibble_3.0.1
[21] crayon_1.3.4 later_1.0.0 vctrs_0.3.0 promises_1.1.0
[25] fs_1.3.1 glue_1.4.1 evaluate_0.14 rmarkdown_2.1
[29] stringi_1.4.6 pillar_1.4.4 compiler_3.5.1 backports_1.1.7
[33] httpuv_1.5.3.1 pkgconfig_2.0.3