Dear list,
Is there any interest in adding a log.p= option to p.adjust() so that it
can accept log-transformed p-values and return log-transformed adjusted
p-values?
I have some functions that, on occasion, return very low p-values. To
avoid underflow in such cases, I allow my users to set log.p=TRUE, which
is passed onto pt(), pchisq(), etc. to return log-transformed p-values.
However, currently, these log-p-values need to be run through exp()
before being used in p.adjust(). This re-introduces the possibility of
underflow errors, sometimes leading to adjusted p-values of zero.
The proposed log.p= mode for p.adjust() would perform all operations in
the log-scale to avoid this - see
https://github.com/MarioniLab/scran/blob/f9ace20d74c7fdbde613aaf91311cdfc6dbe0feb/R/utils_markers.R#L184-L190
for an example with the BH correction. If it were available, we could
conveniently pass along the log.p=TRUE option to p.adjust() as we do for
pt() and friends, and everything would "just work".
If this sounds sensible, I would be happy to put a patch together; the
modifications involved seem simple enough.
Best,
Aaron
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