Pathway enrichment analysis on time-series data by filtering out age comparisons

Question

[fullycratered]

Hello,

I am currently conducting RNA-seq analysis on a time-series dataset (multiple samples over various 3 month periods, specifically). I have just finished with pathway enrichment analysis looking at GO pathways, and I'm curious if there is a way to essentially "filter out" pathways that may be statistically significant in the age comparisons, essentially (hopefully) leaving me with pathways that are altered due to the treatment and not normal aging.

I'm sorry if this question doesn't make sense or if there's something obvious, I am new to all of this and it's been a lot of learn-as-you-go kind of stuff. I can be more specific if needed.

Answer 1

[nux]

I think you can do this prior the enrichment. During the differential expression analysis, just add the age (or what ever quantifiers you have for that) as confounding variable. This will help your DE analysis take into consideration this factor and so do their results. After that you can use the results to perform the ORA or GSEA if you want. If you also want to make sure that age isnt a factor in separating the differences you can try plotting them

[fullycratered]

Ah that makes sense, I hadn't done the DE analysis myself in this case. I will look at doing that, thank you!