Entering edit mode
23 months ago
TM
▴
20
Hi all, I have a naive question regarding the heatmap of the top 50 features for each phenotype in dataset generated by GSEA. I wonder is it also called differentially expressed genes? The heat map showed some genes are clearly up- and down-regulated, however those genes are not differentially expressed when I compared with the DEGs result I got from EdgeR. Noted, I used normalized count value (CPM) from TMM method in edgeR as input for ranked gene list in GSEA. Please help me elaborate, thank you in advance!!!
The heatmaps generated by GSEA are just simply related to the read counts for each specific gene across all your samples, which you provided with the input count matrix.
Thank you for your comment, I am still not clear with these 2 softwares. For example, I found gene X at the 1st top of the heatmap that we can see clearly that its color bar are exactly the same as gene Y at the 2nd top in GSEA, however when I checked the DEGs list generated by EdgeR there is no gene X. Another point for another comparison, in GSEA, we can see clearly different up and down regulated between the 2 phenotype, however in EdgeR, I got only 1 up-regulated DEG between these 2 phenotypes. can you help me explain about this?
Those genes mostly do not come up as DEGs in your analysis because they do not pass the statistical significance threshold (usually adjusted p-value < 0.05). In GSEA, the software by default only assesses the statistical significance of every single pathway (or whatever else, accordingly to the gene set you are using), at FDR < 0.25. If you want to focus on the genes that contribute the most in making a specific pathway up or downregulated in your dataset, then focus on the so-called "leading edge genes".
I got it, thank you so much for your explaination!!