Entering edit mode
3.8 years ago
Rob
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170
what is the cut-off for saying hat a gene set is positively/negatively represented in GSEA? Based on FDR <0.25 no gene sets are significantly represented in the GSEA output. Why is that? Is FDR<0.25 the correct cut-off for GSEA? I have a large gene data and some of them were significantly differentially expressed. but why my GSEA have weird results?
Which implementation of GSEA are you using (there are many)? - please show code, input, and output, where possible. Your definition of 'weird results' is neither well defined; so, please define it further. I would be skeptical about using 25% FDR.
Hi Kevin Thanks for responding. I dont know excatly what to tell yu. I am using hallmark in GSEA. What do you mean by code? I am running GSEA in server for broad institute. in the output no gene set is significantly regulated based on FDR<0.25 cut off. this cut off is in the guideline of GSEA server.So, what cut-off would you use? What else do you want me to tell about my analysis?
Please use
ADD REPLYto comment. Given you used the tool correctly and there are no significant results then it is what it is. Your data are not generally enriched for the gene sets you tested. Having many DEGs is not any guarantee for a significant GSEA result. GSEA tests if globally your transcriptome in one vs the other condition is enriched for a certain gene set, so if most of these genes tend to have high or low ranks based on your ranking method. You might try other methods such as enrichment profiling of only the significantly upregulated genes with tools such as g:profiler2 using all genes you analyzed as a background.As per ATpoint, this may very well be the genuine result. Ensure that your gene names match those of the pathway / signature against which you are enriching, too (i.e. Ensembl IDs == Ensembl IDs). Other than that, as we cannot really see your screen and walk through this for you (and we neither have the time for that), I can only suggest that you contact Broad Institute if you still feel that there is an issue with their program.
Thanks GSEA only accept alphabetical IDs for genes ( i.e MUC16) and IPA for pathway analysis accept numerical values (i.e.94025 ). Differential gene expression can be done with mixed IDs (i.e. MUC16|94025) I dont think this can be the reason for weird result. what is your idea?
Hey, you still have not specifically defined "weird result" (?). Also, the gene IDs should match exactly.
Note: the numerical IDs are Entrez gene IDs.
Weird result mean no significantly enriched based on FDR <0.25. How should the gene IDs be similar? different programs accept different IDs format.