I have performed differential expression (DE) on microRNA-seq data. Unlike RNA-seq data, this is quite small; I only have 1978 genes across X samples. I believe this is why I am running into issues when interpreting the DE results.
The standard for RNA-seq analysis is to use adjusted P values which have been corrected based on the number of genes found. Usually from an RNA-seq analysis we would expect between 20-40,000 genes. Adjusted P values are valuable here and are now seen as a mandatory check used when discussing results.
Meanwhile in the world on microRNAs, we must do with usually < 2,000 genes. Here are my lowest 3 adjusted P.values from contrasting 30 disease samples / 16 non-disease samples -- so plenty of replicates.
lof2fc P value adjusted P value mmu-miR-375-3p 3.589905e-01 6.472503e-06 0.007805839 mmu-miR-200b-3p -7.077764e-03 9.997980e-04 0.602878205 mmu-miR-429-3p 4.179860e+02 1.513482e-03 0.608419692
As such my question is, for miRNA-seq analysis are adjusted P values unnecessary because we lack the number of genes to perform multiple correction testing adequately?
Appreciate any insight.