Last updated: 2019-08-17

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Knit directory: scFLASH/

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droplet <- readRDS("./data/droplet.rds")
source("./code/utils.R")

The droplet-based 3’ scRNA-seq dataset analyzed in Montoro et al. (2018) can be obtained here. It includes counts for 18,388 genes and 7,193 cells. Only 9.3% of all counts are nonzero. The data takes up 143 MB when loaded into memory as a sparse Matrix object.

The original analysis assigns each cell to one of seven cell types. The cells are also labelled according to the mice they come from.

cell.type <- as.factor(sapply(strsplit(colnames(droplet), "_"), `[`, 3))
plot.category(cell.type, title = "Number of Cells per Cell Type")

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12
mouse <- as.factor(sapply(strsplit(colnames(droplet), "_"), `[`, 1))
plot.category(mouse, title = "Number of Cells per Mouse")

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12

Library size is distributed as follows.

plot.libsize(droplet)

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12

Note the presence of extreme outliers. There are two of them, and both turn out to be goblet cells. I think that they should be removed from the dataset before analysis.

table(cell.type[which(colSums(droplet) > 30000)])
#> 
#>          Basal       Ciliated           Club         Goblet       Ionocyte 
#>              0              0              0              2              0 
#> Neuroendocrine           Tuft 
#>              0              0

Mean expression is distributed as follows.

plot.meanexp(droplet)

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12

There are two genes that are on average much more highly expressed than any other gene: Bpifa1 and Scgb1a1. Both have bimodal distributions.

high.exp <- names(which(rowMeans(droplet) > 200))
for (gene in high.exp) {
  plot(plot.gene(droplet, gene))
}

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12

Version Author Date
4e8e813 Jason Willwerscheid 2019-08-12


sessionInfo()
#> R version 3.5.3 (2019-03-11)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS Mojave 10.14.6
#> 
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
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