I have a very general question on roughly checking the results of DE tests for RNA-Seq data.
After a proper comparison of a control and treatment group using, say, edgeR, DESeq, etc., we can plot the histogram of raw p-values and see if there is any strange pattern there. I think if there is strong signal in the treatment group, and the test is good, then the DE test raw p-values should have a histogram that looks like this: it is used to illustrate FDR methodology, but I think maybe in general, we should always observe such a p-value histogram. Otherwise, if there are so few or so many very small p-values, then there may be something wrong with the test itself?
Thanks for sharing your thoughts and your experience :0
After a proper comparison of a control and treatment group using, say, edgeR, DESeq, etc., we can plot the histogram of raw p-values and see if there is any strange pattern there. I think if there is strong signal in the treatment group, and the test is good, then the DE test raw p-values should have a histogram that looks like this: it is used to illustrate FDR methodology, but I think maybe in general, we should always observe such a p-value histogram. Otherwise, if there are so few or so many very small p-values, then there may be something wrong with the test itself?
Thanks for sharing your thoughts and your experience :0
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