Entering edit mode
2.2 years ago
Akash D
▴
40
When considering Top 'X' enriched pathways of GO results. On what basis is the TOP 'X' say TOP 10/30 taken?
If I have obtained say 50 terms after taking enriched p adj. <0.05, on what basis i select the top 10 from the enriched 50 terms? Can i take 'counts/no of genes' to select top 10?
Are 'normalized enrichment score', 'Rich factor', 'P value' same thing? can you please brief a bit...
I've never heard of rich factor, but no, p-values and normalized enrichment scores are not the same. Your title says GSEA, but your post says GO, so I'm not sure whether you're doing GO term enrichment analyses with a gene list or GSEA from actual differential expression results. There is a good summary of what these values mean in relation to GSEA here.
Can you clarify what you are actually doing and with what tools?
Thank you. I will get back to basics.
I am trying to do GO term enrichment with my data. My data contains rice gene ids (DEGs) and i am using CARMO online tool for the analysis.
Oh, I have not used that tool. Some tools spit out scores based on some combination of p-values, gene set size, and enrichment (like enrichr), and I assume that's what the rich factor is here. I can't find anything about that specific metric in their manual though.
People do rank by p-value (or -log10(p-value)) sometimes, which is rather questionable in terms of what a p-value actually means, but so long as you provide the full results, it's probably okay for trimming the list down to something that's easier to visualize and show.
Thanks al lot for your insights. I am benefitted.
As per my knowledge ''Rich Factor" is nothing but the ratio of 'No. of genes (of any process X) found in your list/ Total no. of genes in that process X'.