**7.4k**wrote:

In an ordinary differential expression test, where the null hypothesis is log(FC) = 0, I can expect that in the absence of differential expression, the distribution of p-values from the test will be approximately uniform. However, for threshold tests like `limma::treat`

, `edgeR::glmTreat`

, `DESeq2::results`

with `lfcThreshold != 0`

and/orĀ `altHypothesis != "greaterAbs"`

, or even something as simple as a series of ordinary one-sided t-tests, this is no longer the case, since the null hypothesis is not a lower-dimensional subspace of the full parameter space, and many genes will be contained in the interior of the null hypothesis and have p-values at or near 1. With these kinds of tests, is there any equivalent rule to the "null p-values are uniform" rule described above for tests against an more typical null hypothesis?

**39k**• written 3.8 years ago by Ryan C. Thompson ♦

**7.4k**