This is a test version of Biostars. For the public version, visit https://www.biostars.org.
Statistically Comparing Two DiffEx Gene Sets To Discern Treatment Effect

I'm trying to compare the treatment effect on differentially expressed genes between control and diseased RNA-seq data. This question is based off another post I made where unfortunately the treatment was confounded with the batches.

It was suggested I used duplicateCorrelation() from the limma package to calculate the differentially expressed genes. More specifically, because the treatment was confounded with batches, I would have to do something like this to see what the treatment did:

(Treated Disease v. Untreated Disease) v. (Treated Control v. Untreated Control)

Again, the details of why I have to do this are in my last post

My question is really just about the specifics on how I would go about making this comparison and what the results mean. A commenter on the previous post states I'll be able to make inferences on how the treatment affects differentially expressed genes, but I'm having trouble working this out intuitively. If I separately did DEX analysis on: (TD v. UnTD) and then (TC v. UnTC), how would I compare the differentially expressed genes statistically. Any help would be great. Also if you have any thoughts about this whole thing in general, those would be appreciated!

statistics expression design rnaseq ngs

0 answers

No answers yet.

Log in to answer this question.