How to do pathway analysis after scanpy for single cell data after DE analysis?

The original question was GSEApy vs KEGG. The response below is GSEApy. The question has been edited and is now a different question concerning options within GSEApy.


Response to original question

If GSEApy as described in the publication provides the output you require – that is much, much simpler. KEGG will be complex and you’d need its ids.

However, surely GSEA will require to perform the full calculation of fold-change from scratch rather than be fed the output of scanpy? KEGG will require the output of scanpy. GSEApy primary function is fold-change rather identifying the precisely which pathways are regulating the phenotype under analysis.

KEGG will provide a more accurate answer – in my humble opinion. GSEApy is a lot easier because it very much an “all-in-one” solution. If the answer isn’t satisfactory you can always switch.


Just to note the GSEApy version I’m referring to is the latest publication.

NOTE There was a deleted post from the OP about an option within GSEA. This is a separate question in the SE format of questions and answers. Thats the way the site works.

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