Hello all,
So I've done DGE analysis using DESeq2 and I have a question regarding log2 fold change. Although my DEGs are statistically significant, the vast majority of these genes have a log2 fold change smaller than +/- 0.5. I understand the nature of the data impacts this - such as outliers (I have no sample outliers but I do have gene count outliers for genes here and there that come from different samples each time), but I'm unsure of my next move when thinking about the biological importance of these DEGs. Is there some complimentary analyses I can do help me choose DEGs for validation more confidently? And if I were to either pick the DEGs with the greatest log fold change or ones of interest for validation, will such a small log fold change also be found after running qPCRs? I work with postmortem brain tissue.
Thanks!
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did you apply lfc shrinkage? https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#alternative-shrinkage-estimators
Apologies - I should have stated that I'm not looking at shrunken values and I didn't perform LFC shrinkage (my understanding is that DESeq2 does not report shrunken values by default). I'm looking at the log2FoldChange column you get when you generate results.