I already found out how to select specific comparisons from the object resulting from the DESeq() function
dds <- DESeq(ddsHTSeq)
using the 'contrast' variable in the 'results' function like this:
deseq2.res <- results(dds, contrast=c("condition","treated_A","untreated_A"))
With this 'deseq2.res' object, I can now do my further analyses, also including MA plot, ...
But now, lets say I also want to plot a PCA only for this specific comparison between 'treated_A' and 'untreated_A' using the rld transformed values:
rld <- rlog(dds) plotPCA(rld, intgroup=c("condition", "type"), returnData=TRUE)
Is there a way, to build from the full 'dds' object with all conditions and values a subset only including those for the comparisons 'treated_A' and 'untreated_A'?
It would be nice, to have such an object to continue with downstream analyses like PCA, heatmaps, etc... but still have the normalization and estimations over all samples and conditions from the full 'dds' object.
Is there such a way?