FDR corrections

Dear all!
I have one question about FDR correction (q value).
For example, I have alpha diversity metrics, plotted like this:

I performed MWU test to compare grouped boxes within each time point and obtained p-values. Now I want to apply FDR correction to P values. This correction should be performed for p-values of entire subplot (including all time-points), or only within time-point, inside which p-values were calculated. Right now I did in on entire subplot (three time-points inside subplot together)
Thank you in advance

Hi @timanix,
This is something you’ll find different answers to across the online forums. So take my answer here with a grain of salt, as a non-statistician.
The answer depends on what your question is and how your model is set up. Given that these are time-point data, I assume you were interested in the effect of Groups across time on microbiome alpha diversity measures.
Is your formula set up to detect interactions? i.e. diversity ~ time*groups? If so, what are the significant effects? If you see a significant effect of time*group, I don’t really see a benefit of doing post-hoc tests at each time point. Your answer is very clear, that microbiome changes exist within each group and these changes are different across time. If you see an effect of time but not groups, then again I don’t see a point in your post-hoc test because you determine groups were not different, so you don’t care about the time effect by itself. If you see a sig effect of group but not time, then it might be worth looking at each time-point to see perhaps at what specific time point things were different. In that case you should adjust your p values in your post-hoc tests specific at each time point. At least this is what I do.

If your formula does not have an interaction term, then you should only do a post-hoc test if there was a significant effect of Group. Again your post-hoc test would adjust for p values at each time-point.

Again, reiterating that I am not a statistician, so you’ll want to check this with someone trained as so.

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Hi, @Mehrbod_Estaki!
Thank you for this awesome explanations! Now it is easier for me to digest the outputs

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