I've done about a dozen RNA-seq datasets and the results i get as "differential' are either a few seqs uniquely expressed in only one of the treatments or an empty set. I get hundreds of transcripts expressed at varying levels between the two treatments but these are never called as being significant by Galaxy.
Philosophically, I don't see how this could be. I'm interested in more than on/off changes. What is the point in doing time course experiments if you can't statistically watch differential expression rise and fall.
So, what do i need to change in my analysis in Galaxy to see significant (+/-) 2-fold differences? Is Galaxy designed to only recognize specificities?
Can someone send me a link to a history that has statistically significant, 2-fold (or greater) non-unique differences or, explain how this is done with Galaxy?