PT  - JOURNAL ARTICLE
AU  - Gennady Korotkevich
AU  - Vladimir Sukhov
AU  - Nikolay Budin
AU  - Boris Shpak
AU  - Maxim N. Artyomov
AU  - Alexey Sergushichev
TI  - Fast gene set enrichment analysis
AID  - 10.1101/060012
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 060012
4099  - http://biorxiv.org/content/early/2021/02/01/060012.short
4100  - http://biorxiv.org/content/early/2021/02/01/060012.full
AB  - Gene set enrichment analysis (GSEA) is an ubiquitously used tool for evaluating pathway enrichment in transcriptional data. Typical experimental design consists in comparing two conditions with several replicates using a differential gene expression test followed by preranked GSEA performed against a collection of hundreds and thousands of pathways. However, the reference implementation of this method cannot accurately estimate small P-values, which significantly limits its sensitivity due to multiple hypotheses correction procedure.Here we present FGSEA (Fast Gene Set Enrichment Analysis) method that is able to estimate arbitrarily low GSEA P-values with a high accuracy in a matter of minutes or even seconds. To confirm the accuracy of the method, we also developed an exact algorithm for GSEA P-values calculation for integer gene-level statistics. Using the exact algorithm as a reference we show that FGSEA is able to routinely estimate P-values up to 10−100 with a small and predictable estimation error. We systematically evaluate FGSEA on a collection of 605 datasets and show that FGSEA recovers much more statistically significant pathways compared to other implementations.FGSEA is open source and available as an R package in Bioconductor (http://bioconductor.org/packages/fgsea/) and on GitHub (https://github.com/ctlab/fgsea/).Competing Interest StatementThe authors have declared no competing interest.