Over-representation analysis in addition to GSEA about differentialabundance HOT 2 CLOSED

Sure, I'm a little wary of the Fishers-based methods because of arbitrary thresholding and methodological issues, but they remain popular, so I'd support having one here. You're correct on the covariates of course- I actually really like the limma-hosted methods (romer(), piano() and so on) for that reason (though they're easier to integrate with edgeR than I suspect they would be for DESeq2). I do also have a plan to use the preranked mode for GSEA, which if based on the estimated fold changes from modelling might allow some consideration of covariates.

For consistency with how we're doing things so far in the workflow, we'd need a non-local clusterProfiler module first. If you could look at how the output of the DESeq2 module is structured that will inform on how you might structure the input channel(s).

I'm inclined to keep the GSEA implementation as-is, just because it's well established and recognised.

from differentialabundance.

@WackerO 's work on gprofiler2 addresses the request for over-representation, so closing this for now. PRs implementing other methods welcome.

from differentialabundance.