Im currently re performing some analyses of RNA-seq data via DESeq2, however since the first analysis (about a year ago) Ive got some very strange genes turning up as significantly expressed. These genes have exceedingly high p-values and fold changes (>2^15 !!) while also being lowly expressed ( Basemean of <100) and often driven by a single sample.
the experiment is as follows: an RNA seq analysis (Unstranded ) of Cytokine expressing cells from 3 separate patients, comparing 2 cell types (CD4/CD8) expressing 1 of 2 cytokines (pop1/pop2).
any advice would be appreciated. This is the code Ive been using (Cant give the data sets for reproduction due to confidentiality)
dds <- DESeqDataSetFromMatrix(countData = SFpops.454[,3:11], colData = samples.454, design = ~ EXPERIMENT.ID + CELL.CYTOKINE)
vsd <- vst(dds, blind=FALSE)
rld <- rlogTransformation(dds)
res <- results(dds2, contrast = (c("CELL.CYTOKINE", "CD8-pop1", "CD8-pop2")))
and a selection of output results below
Is there something altered in the package which makes these really lowly abundant genes now below the critical threshold?