Hello,

I hope someone can help me understand this better. I am running the emptyDrops method from DropletUtils library which distinguishes empty from non-empty cells. The function accepts lower parameter which specify the lower bound on the total UMI count, at or below which all barcodes are assumed to correspond to empty droplets. Link to manual.

Based on this, I thought that if I specified small number for lower, it will detect more non-empty cells and if used bigger number for lower, it will detect less non-empty cells. However, it didn't. In fact it is consistently detect more non-empty cells when lower is set to larger number. Am I missing something? Here is the code to reproduce the results.

library(DropletsUtils)
library(BiocFileCache)
bfc <- BiocFileCache("raw_data", ask = FALSE)
raw.path <- bfcrpath(bfc, file.path("http://cf.10xgenomics.com/samples",
 "cell-exp/2.1.0/pbmc4k/pbmc4k_raw_gene_bc_matrices.tar.gz"))
untar(raw.path, exdir=file.path(tempdir(), "pbmc4k"))
library(DropletUtils)
fname <- file.path(tempdir(), "pbmc4k/raw_gene_bc_matrices/GRCh38")
sce <- read10xCounts(fname, col.names=TRUE)

set.seed(100)
e.out <- emptyDrops(counts(sce),lower=100)
sum(e.out$FDR <= 0.001, na.rm=TRUE)
[1] 4237

set.seed(100)
e.out.200 <- emptyDrops(counts(sce),lower=200)
sum(e.out.200$FDR <= 0.001, na.rm=TRUE)
[1] 4346

set.seed(100)
e.out.1000 <- emptyDrops(counts(sce),lower=1000)
sum(e.out.1000$FDR <= 0.001, na.rm=TRUE)
[1] 4326

set.seed(123)
e.out.test <- emptyDrops(counts(sce),lower=100)
sum(e.out.test$FDR <= 0.001, na.rm=TRUE)
[1] 4223

set.seed(123)
e.out.test <- emptyDrops(counts(sce),lower=200)
sum(e.out.test$FDR <= 0.001, na.rm=TRUE)
[1] 4316

set.seed(123)
e.out.test <- emptyDrops(counts(sce),lower=1000)
sum(e.out.test$FDR <= 0.001, na.rm=TRUE)
[1] 4324

lower is used to estimate the "expression" profile of the ambient pool; changing lower just means that you're using more-or-less low-count libraries to do this estimation. Provided all of the low count libraries are empty droplets, the ambient proportion estimates should not change much from using more libraries. The fact that the number of detected cells is stable is actually encouraging as it means that the analysis is robust to the choice of lower, i.e., exactly how empty droplets are defined doesn't matter much.

A secondary effect is that libraries with counts below lower are not tested by default, as we're already assuming that they're empty droplets (so why bother testing them?). This means that there is a small reduction in the multiple testing burden as you increase lower. One would expect this to result in a slight increase in the number of detected cells, though this really depends on whether you start throwing away more cells with total counts below lower, and in this case, it all comes out in the wash.

P.S. I'll give you the benefit of the doubt and assume you're not the same person who posted this, but if you are, it is usually good etiquette to wait a reasonable timeframe before reposting.