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
DEGs with uninsteresed sample files
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.
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If the D samples don't have batch issues, and a PCA shows that they aren't way different from other others, or have way higher variability than the others, you should leave them in.
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