I am trying to perform a gene set enrichment analysis in r using the gene sets available from msigdb and a list of gene names from my own data set.
I am able to to use the msigdbr library to import the gene collections from msigdb into r, but I am unsure of how to specifically use a function to compute the overlaps between the genes in my gene set and the gene sets in msigdb and obtain the FDR p-values. Are there any tutorials online for this method or example codes?
Thank you
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wilsonav •
You can try the fgsea package, which is probably most similar to the original GSEA. It can be run in a single command:
fgseaRes <- fgsea(pathways = examplePathways, stats = exampleRanks)
Check the vignette for more details: https://www.bioconductor.org/packages/devel/bioc/vignettes/fgsea/inst/doc/fgsea-tutorial.html
There is also an example in the msigdbr vignette: https://cran.r-project.org/web/packages/msigdbr/vignettes/msigdbr-intro.html
It's worth noting that fgsea is similar to GSEA-Preranked rather than to the original GSEA method published in the GSEA articles that used sample permutation.
OK. It's an important issue because GSEA-preranked doesn't give proper FDR control (and hasn't been claimed to do so by the GSEA developers as far as I know).
i tried msigdbr package and did work find for me. it provides you with msigdb that compatible with fgsea and clusterProfiler. For example, I use it to do the fgea with human hallmark gene sets
library(msigdbr)
library(fgsea)
#Retrieve human H (hallmark) gene set
msigdbr_df <- msigdbr(species = "human", category = "H")
head(msigdbr_df)
# A tibble: 6 x 15
gs_cat gs_subcat gs_name gene_symbol entrez_gene ensembl_gene human_gene_symb…
<chr> <chr> <chr> <chr> <int> <chr> <chr>
1 H "" HALLMA… ABCA1 19 ENSG0000016… ABCA1
2 H "" HALLMA… ABCB8 11194 ENSG0000019… ABCB8
3 H "" HALLMA… ACAA2 10449 ENSG0000016… ACAA2
4 H "" HALLMA… ACADL 33 ENSG0000011… ACADL
5 H "" HALLMA… ACADM 34 ENSG0000011… ACADM
6 H "" HALLMA… ACADS 35 ENSG0000012… ACADS
# fixing format to work with fgsea
pathwaysH = split(x = msigdbr_df$entrez_gene, f = msigdbr_df$gs_name)
# run fgsea enrichment
fgseaRes <- fgsea(pathways=pathwaysH, ranks, ..)
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