My pipeline so far is
hisat2->featureCounts->DESeq2. I have generated heatmaps after rlog and log2 transformation of the genes with the most variance, which is somewhat meaningful. What I really want to do is compare everything to the control sample and take the genes with the most log fold change in either direction. I've read through the DESeq2 vignette and haven't found a good example of that. Maybe I do this under the
design parameter when running
DESeqDataSetFromMatrix()? So far I've only set the design parameter to
~condition as I'm a little shaky on how that parameter works.
Maybe this is more of an R problem than a DESeq2 one? Is EdgeR the better tool since it allows you to do some analysis with no biological replicates by setting the dispersion value?