(Warning: work in progress! do not use for production purposes)
ultragsea is an ultrafast method to compute gene set enrichment on a preranked list of genes not unlike fGSEA. ultragsea van be used as replacement of fGSEA. Although ultragsea uses a different statistical test (namely z-test or correlation), its scores are highly correlated and its p-values are closely similar to those from GSEA's weighted Kolmogorov-Smirnov test. ultragsea computes its scores using fast sparse computation and parametric p-values and typically is 10-100x faster than fGSEA.
You can install ultragsea from from GitHub:
remotes::install_github("bigomics/ultragsea")For detailed usage examples and tutorials, please see our vignettes:
ultragsea is the main gene set scoring algorithm in OmicsPlayground, our Bioinformatics platform at BigOmics Analytics. In OmicsPlayground, you can perform ultragsea without coding needs.
library(ultragsea)
gs <- msigdbr::msigdbr(collection = "H")
gmt <- tapply(gs$gene_symbol,gs$gs_name,list)
G <- gmt2mat(gmt)
fc <- rnorm(nrow(G))
names(fc) <- rownames(G)
res <- ultragsea(fc, G, format='as.gsea', method='ztest')
head(res)
For more technical details please refer to our papers. Please cite us when you use ultragsea as part of your research.
- ultragsea: Ultrafast preranked gene set enrichment scoring.
- Akhmedov M., et al., Omics Playground: a comprehensive self-service platform for visualization, analytics and exploration of Big Omics Data, NAR Genomics and Bioinformatics, 2020, lqz019.
For support feel free to reach our Bioinformatics Data Science Team at BigOmics Analytics: help@bigomics.ch
If you like ultragsea, please recommend us to your friends, buy us coffee and brag about ultragsea on your social media.