Hello guys! I would really appreciate if someone could help me with DE analysis. This is my challenge:

I have four conditions and I have five biological replicates for each condition. Performing a PCA (DESeq2) we can observe that most of the replicates don't cluster together. My first question is, can I simply analyze them using DESeq2 or edgeR or this would be wrong because of this replicate scenario? Second, are there any ways to filter out the genes in which the replicates are not good and keep only the ones that are consistent among the replicates of the same condition to run the DE analysis?

Thank for the help!

Since when is a paired t-test best practice for RNASeq?

You can do a paired t-test on Voom-limma transformed data. For edgeR and DEseq2 you will need to put the sample pairing in the linear model as covariate.

You "can", but is it best practice? "5 biological replicates" shouldn't mean "5 different cell lines". It should mean "5 samples that are the same except for incidental variance". You can't do a paired t-test on that.

That's why I started my sentence with "if". Voom-limma is well accepted and shown to be as good as deseq2 or edger, there are numerous papers about that. Regarding the cell lines, I clearly wrote e.g. (=for example). Swbarnes2, if you know a better method, please suggest it.