I use the `DEP`

package for label-free proteomics analysis. Differential expression (`test_diff`

) results provide p-values (`p.val`

) and FDR values (`p.adj`

), the latter are calculated by `fdrtool`

using moderated t-statistics of empirical Bayes (`eBayes`

function in `limma`

) as input. What is a reason to use the moderated t-statistic, not p-value, to compute FDRs?
The relations between the t-statistic-derived FDRs and the FDRs calculated by adjusting the p-values using the BH method (with `p.adjust(method = "BH")`

or with `fdrtool::fdrtool(statistic = "pvalue")`

) seem to depend on a contrast of interest, for some comparisons the t-statistic FDR delivers more differentially expressed proteins, whereas for others the p-value-based FDR provides a lower cut-off (see the figure for 4 different contrasts). I would highly appreciate some feedback regarding those differences. Are both procedures correct to apply for FDR calculations?

Very good question that you have asked. I stumbled upon your post when I was searching for the exact information that you have described. I would appreciate if someone can shed a light here.

Same here. I also have no idea why

`fdrtool`

is being applied in the t-statistic.