I'm looking for a tool (better would be a Bioconductor package) able to perform differential expression analysis on a table of RPKMs. I've seen so far only solutions implementing raw read counts, like DEGSeq, edgeR and BaySeq. And yeah, in this particular case I cannot transform RPKMs back to read counts.
Do you have any idea? Furthermore, a great advantage would be the capability of calculating significance of "contrasts of contrasts" analysis, i.e. of tetrafactorial designs.
E.g. having 4 conditions: WT control, WT treated, mutant control, mutant treated.
DE1 = WT treated vs. WT control DE2 = mutant treated vs. mutant control DE1DE2 = (mutant trated vs. mutant control) vs. (WT treated vs. WT control)
Something like the great limma does for microarrays. But on RNASeq RPKMs.
Thanks a lot for any hint! :-)