I have treated vs untreated(wt) samples. And I know a subset of genes are very lowly expressed in wt but will be up-regulated in treated samples. When I do the DEseq2 analysis, most of them are at the top if I rank them by adjust p values or by fold change which makes sense. But in this case, it looks like the genes ranking at the top (high pvalue or foldchange) will bias to genes lowly expressed in wt. Their baseMeans are intermediate since they consider all the samples (treated+wt). Thus I think shrinkage method will also not help if it is relative to baseMeans. So I wonder how DESeq2 deals with such bias??
Thank you in advance for your answer.