Dear all,

I run DESeq2_1.18.1 with default options and obtained odd results. The significant transcripts (FDR<5%) are due to one or two outlier samples.

I checked the expression values and all samples except the outliers have 0 counts,

How can I deal with this situation? Which parameters should I modify? changing Cook's distance? disable independent filtering?

Thanks,

It could be you have too few samples for the outlier detection to kick in, or the counts are not high enough to count as outliers. Either way, you can perform more aggressive filtering to remove genes with a count in only one or two samples:

dds <- estimateSizeFactors(dds)
keep <- rowSums(counts(dds,normalized=TRUE) >= 10) >= 3
dds <- dds[keep,]