Hi, When launching the DESeq function, I get results like this:

res<- results(dds, name="genotypeA.treatment2")

summary(res)

out of 20717 with nonzero total read count adjusted p-value < 0.1 LFC > 0 (up) : 154, 0.74% LFC < 0 (down) : 7, 0.034% outliers [1] : 5, 0.024% low counts [2] : 15258, 74% (mean count < 804) [1] see 'cooksCutoff' argument of ?results [2] see 'independentFiltering' argument of ?results

My question is why low counts mean count <804?

That's the independent filtering (see vignette), which here is jumping over many genes with mean counts < 800. I wonder if you are using a current version of DESeq2, because we've tried to mitigate that behavior in recent versions. It can still happen though, it just means that there were few significant genes with counts < 800. I would however prefer to turn off independent filtering in this case (or use IHW, see example in vignette).