I am performing a gene set analysis on RNA Seq data, using camera on Reactome database.
camera returns a lot of significant pathways (more than 100) and I suspect that some of them are redundant, like small pathways included into larger ones and other imbrications.
I guess I have several solutions :
- Sending this large lists of pathways to the biologists, which is complicated for them to study
- Keeping the most significant pathways, or pathways with largest absolute FC : is it relevant to do that? Or I will miss interesting small pathways?
- Using a method that removes redundancy among pathways by computing an overlap measure but I did not find any satisfying method for the moment. I know that GAGE package has an esset.grp function that does a similar job but I do not find any equivalent for camera. Maybe I am missing it?
Here is my question(s) : is there a usual solution among the 3 I suggested above? Do you know tools that would remove redundancy into Reactome pathways?
Thank you very much for your help.