I was using edgeR to do differential expression on a RNA-seq dataset, but when I check the p.value distribution of the output, I found ~700 genes got a p value larger than 1... Just wondering if anyone else got this problem before? And why I got such a weird a result. Here's my codes,
d <- DGEList(counts=countsTable, group=conds, lib.size = lib.sizes) #I used the raw read counts as instructed
d <- calcNormFactors(d, method="TMM")
d <- estimateCommonDisp(d)
et.commonDis <- exactTest(d)
hist(et.commonDis$table$p.value, breaks=100, col="skyblue", border="slateblue", main="pval distribution_edgeR")
I got a picture as attached...
May I have your ideas? Thanks.
d <- DGEList(counts=countsTable, group=conds, lib.size = lib.sizes) #I used the raw read counts as instructed
d <- calcNormFactors(d, method="TMM")
d <- estimateCommonDisp(d)
et.commonDis <- exactTest(d)
hist(et.commonDis$table$p.value, breaks=100, col="skyblue", border="slateblue", main="pval distribution_edgeR")
I got a picture as attached...
May I have your ideas? Thanks.
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