Hello
I performed several differential gene expression analyses with edgeR (QLF) in which 2 groups were compared to each other. In some comparisons, I noticed something I couldn't explain about the (adjusted) p-values. I am curious to know if this is normal and why this is happening. I noticed two things and will describe them below.
Image for the first observation:
The left panel shows a histogram of raw p-values as obtained by edgeR and the right panel shows a volcanoplot with the FDR (as outputted by edgeR) on the y-axis. I am wondering why many FDR values are numerically the same (on the right side of the volcano plot you see that many FDR values near the top are at the same horizontal position).
I think this is becaues the FDR value is calculated with p.adjust(, method = "BH")
and that uses the cumulative minimum, but I am not sure.
Image for the second observation: These are the same types of graphs as in the first observation. Based on the histogram of p-values, I would expect at least some differentially expressed genes as low p-values seem to be enriched. Howerver, the is no gene with an FDR lower than 0.05. Based on the histogram, I didn't expect this and I have no idea why this is the case.
Thanks in advance.
Thank you very much for the information and advice.
Hello, thank you for this discussion, but I am puzzled : the mapping of the p-value can come with steps, but is that wrong ? I mean, you propose not to draw volcano plot with FDR in y axis, is that because in that case volcano plots are somewhat wrong, when they show dots aligned in steps ?
Best