2.8 years ago by
I would like to highlight that GSEA is not a tool for differential expression analysis. You can check what is written in the website
In particular: Prior to conducting gene set enrichment analysis,
conduct your differential expression analysis using any of the tools
developed by the bioinformatics community (e.g., cuffdiff, edgeR,
DESeq, etc). Based on your differential expression analysis, rank your
features and capture your ranking in an RNK-formatted file. The
ranking metric can be whatever measure of differential expression you
choose from the output of your selected DE tool. For example, cuffdiff
provides the (base 2) log of the fold change. Run GSEAPreranked, but
make sure to select "classic" for your enrichment score (thus, not
weighting each gene's contribution to the enrichment score by the
value of its ranking metric).
It is reccomended to use the different DEG tools to find out the genes that are differentially expressed and then use the GSEAPreRanked. I believe you should try count based tools like DESeq2 , edgeR with the same normalization method and try to find the overlap of them and then perform your downstream or rather use any of them to go ahead with GSEA.
Please take a look at this link section
Can I use GSEA to analyze SNP, SAGE, ChIP-Seq or RNA-Seq data?
I believe this will be able to make it more clear for you.