Are the top 50 features in heat map for each phenotype in dataset generated by GSEA called differentially expressed genes?
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10 weeks 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!!!

GSEA EdgeR Heatmap DEGs • 386 views
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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.

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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?

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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".

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I got it, thank you so much for your explaination!!

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