Hi all,
I am working on some bulkRNAseq data from GEO and my sample description looks like this. I am interested in A vs B, A vs C and B vs C but I am not interested in sample D.
My question is whether I should include sample D for edgeR or DESeq2 to help them estimate some parameters such as commona variance or something. I have learnt about linear regression so I think I should include sample D(that's what the class taught me - reducing SE) but I am not 100% sure that it applies to DEGs.
Thank you for your suggestion. Yes, looking at a PCA plot will help for sure. Do you mind me asking a question? I would like to know what your reasoning about leaving them in is
Same as yours. See also: http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#if-i-have-multiple-groups-should-i-run-all-together-or-split-into-pairs-of-groups