Hi,
I have a set of genes along with their respective GOs. Anyone can suggest me a tool or package to perform a gene set enrichment analysis (GSEA) on a subset of these genes that are ranked according to their p-values? Please suggest freely available software (not like blast2GO). I know I can do a singular enrichment analysis (SEA) by doing a Fisher exact test in R. I want to include their significance as well.
Thanks!
2 answers
If you have list of genes, try Gene Set Clustering based on Functional annotation (GeneSCF)
I've had good experience with fGSEA through bioconductor (stands for fast GSEA). It's recommended that you use the t-statistic as opposed to the p-value, as this will give you directional information as well (up- vs downregulated genes).
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You can try this one : https://bioconductor.org/packages/release/bioc/vignettes/ReactomePA/inst/doc/ReactomePA.html
Thank you! The organism is not a model organism, and it is not available in any databases that these tools use. The genes are just predicted genes and their names are not available in databases. I just need software that performs the statistical test on my data, suppose I have 5 genes as a population:
gene1 ----> GO1
gene2 ----> GO2
gene3 ----> GO3,GO2
gene4 ----> GO4
gene5 ----> GO5
I have two genes as significant genes with their p-value:
gene2 ----> 0.001
gene3 ----> 0.0001
I just want to find out which GOs are enriched among gene2 and gene3 by GSEA algorithm, I already have my GOs and I do not need to obtain them again.
If you have a
.gmtfile with gene sets or GO terms then you can run fGSEA, you just need to specify the input, it doesn't need to be from MSigDB, you can generate your own and run it. If you don't have a.gmtfile then how are you defining GO terms or gene sets to begin with?