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Linus Alawa

Adjusted P-value from DESeq2

Amelia Noah  Follow

If we look at documentation of DESEQ2 and search "adjusted p-value", we find the section "Multiple test correction". In this section they discuss Benjamini-Hochberg ("BH") false discovery rate (FDR) correction procedures:

FDR/Benjamini-Hochberg: Benjamini and Hochberg (1995) defined the concept of FDR and created an algorithm to control the expected FDR below a specified level given a list of independent p-values. An interpretation of the BH method for controlling the FDR is implemented in DESeq2 in which we rank the genes by p-value, then multiply each ranked p-value by m/rank.

Earlier, they write:

m = total number of tests

They further add:

So what does FDR < 0.05 mean? By setting the FDR cutoff to < 0.05, we’re saying that the proportion of false positives we expect amongst our differentially expressed genes is 5%. For example, if you call 500 genes as differentially expressed with an FDR cutoff of 0.05, you expect 25 of them to be false positives.

I would suggest reading Benjamini and Hochberg (1995) to learn more details if desired.

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