Hi,

I'm analyzing a large number of gene sets in RNAseq data, hoping to find sets that can differentiate between 2 conditions. I'm using fry(), from the limma package.

I understand that there are 3 different hypotheses tested for each gene set (upregulated, downregulated, and the last one to my understanding is that the genes are not equally expressed in the two conditions = there is a mix of genes, which are either up or downregulated). I hope my understanding is correct there.

Out of thousands of genesets, one has an *FDR* of 0.02, for which the *FDR.mixed* is rather high, and the rest are all above 0.25. About 10 has an *FDR.mixed* bellow 0.01, and for some of those, the two sided/normal *FDR* is really high (almost 1).
For visualizing the results, I tried creating heatmaps with the mean pattern expressions of the significant sets, and the separation is not as good as I'd like.

My questions are:

- What is a sensible choice of FDR cutoff? Should I consider both FDR and FDR.Mixed?
- How to interpret the two sided FDR and the mixed FDR? (why is the two sided FDR low, yet the mixed FDR high, and also the other way around)
- Does it make sense to take a closer look at sets with a significant mixed FDR, and split them futher depending on the direction of DE (up, down, not DEd)?

Thank you for your help in advance!

Now asked on BioConductor: https://support.bioconductor.org/p/121592/