What's the DEal? Differential Expression using RSEM
We've been looking for ways to analyze transcriptomes correctly, with sufficient power, not too many type I and II errors, and not much fuss. For those relatively unfamiliar with performing differential expression analyses on RNA-seq data, a great review of the statistical methods employed to analyze these data can be found here . What it all comes down to is the fundamental problem associated with RNA seq experiments -- the absence of a single transcript could be due to down regulation OR, could be due to the up regulation of ANOTHER gene. That's right, what you are measuring are RELATIVE expression levels, and given libraries of the same size, you cannot accurately distinguish the first scenario from the second unless you've spiked the libraries with some standards of known quantity (which, interestingly enough, has been done before with success by Mary Ann Moran's group here ). From Mary Ann Moran's paper on the subject, we have this very nice depiction of ...