I have a relatively large RNAseq data set: 360 Human blood biological replicates, 100bp PE reads with 60M read depth on average, with Poly-A removal.
I'm analyzing these data with DESeq2 following these basic steps:
dds = DESeqDataSetFromMatrix(countData = dat0, colData = colDat, design = ~ Age + Sex + RIN + pH + Treatment)
dds <- estimateSizeFactors(dds)
dds <- estimateDispersions(dds)
dds <- nbinomWaldTest(dds)
ddsRes <- results(dds, pAdjustMethod = "BH")
However, many of the most significant (including the top 6 results) are small ncRNA with relatively low baseMean counts (<10). Below I am attaching a plot of the p-values versus baseMean distribution, does this look abnormal? It certainly looks different than the ones presented in the DESeq2 tutorial found here: https://www.bioconductor.org/help/course-materials/2015/LearnBioconductorFeb2015/B02.1.1_RNASeqLab.html#diagnostic (under the Independent Filtering section).