Package: fgsea 1.39.0

Alexey Sergushichev

fgsea: Fast Gene Set Enrichment Analysis

The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.

Authors:Gennady Korotkevich [aut], Vladimir Sukhov [aut], Nikita Golikov [aut], Nikolay Budin [ctb], Nikita Gusak [ctb], Zieman Mark [ctb], Alexey Sergushichev [aut, cre]

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manual.pdf |manual.html✨
card.svg |card.png
fgsea/json (API)
NEWS

# Install 'fgsea' in R:

install.packages('fgsea', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/alserglab/fgsea/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

exampleExpressionMatrix - Example of expression values obtained for GSE14308.
examplePathways - Example list of mouse Reactome pathways.
exampleRanks - Example vector of gene-level statistics obtained for Th1 polarization.

On BioConductor:fgsea-1.39.0(bioc 3.24)fgsea-1.38.0(bioc 3.23)

geneexpression differentialexpression genesetenrichment pathways cpp

16.21 score 444 stars 53 packages 6.3k scripts 52k downloads 150 mentions 23 exports 31 dependencies

Last updated from:814dad48f0. Checks:1 ERROR, 11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	331
linux-devel-arm64	NOTE	547
linux-devel-x86_64	NOTE	493
source / vignettes	OK	998
linux-release-arm64	NOTE	533
linux-release-x86_64	NOTE	565
macos-release-arm64	NOTE	397
macos-release-x86_64	NOTE	507
macos-oldrel-arm64	NOTE	369
macos-oldrel-x86_64	NOTE	647
windows-devel	NOTE	652
windows-release	NOTE	659
windows-oldrel	NOTE	765
wasm-release	OK	254

Exports:calcGseaStat collapsePathways collapsePathwaysORA fgsea fgseaLabel fgseaMultilevel fgseaSimple fora geseca gesecaSimple gmtPathways mapIdsList multilevelError plotCoregulationProfile plotCoregulationProfileImage plotCoregulationProfileReduction plotCoregulationProfileSpatial plotEnrichment plotEnrichmentData plotGesecaTable plotGseaTable reactomePathways writeGmtPathways

Dependencies:BH BiocParallel cli codetools cowplot cpp11 data.table farver fastmatch formatR futile.logger futile.options ggplot2 glue gtable isoband labeling lambda.r lattice lifecycle Matrix R6 RColorBrewer Rcpp rlang S7 scales snow vctrs viridisLite withr

Gene set co-regulation analysis tutorial

Rendered fromgeseca-tutorial.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2025-12-30
Started: 2025-11-04

Using fgsea package

Rendered fromfgsea-tutorial.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2025-11-04
Started: 2016-06-03

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculates GSEA statistics for a given query gene set	calcGseaStat
Calculates GSEA statistic valus for all gene sets in `selectedStats` list.	calcGseaStatBatchCpp
Collapse list of enriched pathways to independent ones.	collapsePathways
Collapse list of enriched pathways to independent ones (GESECA version, highly experimental).	collapsePathwaysGeseca
Collapse list of enriched pathways to independent ones. Version for ORA hypergeometric test.	collapsePathwaysORA
Example of expression values obtained for GSE14308.	exampleExpressionMatrix
Example list of mouse Reactome pathways.	examplePathways
Example vector of gene-level statistics obtained for Th1 polarization.	exampleRanks
Wrapper to run methods for preranked gene set enrichment analysis.	fgsea
Runs label-permuring gene set enrichment analysis.	fgseaLabel
Runs preranked gene set enrichment analysis.	fgseaMultilevel
Runs preranked gene set enrichment analysis.	fgseaSimple
Runs preranked gene set enrichment analysis for preprocessed input data.	fgseaSimpleImpl
Simple overrepresentation analysis based on hypergeometric test	fora
Runs multilevel Monte-Carlo variant for performing gene sets co-regulation analysis	geseca
Runs simple variant for performing gene sets co-regulation analysis	gesecaSimple
Returns a list of pathways from a GMT file.	gmtPathways
Effeciently converts collection of pathways using AnnotationDbi::mapIds function. Parameters are the sames as for mapIds except for keys, which is assumed to be a list of vectors.	mapIdsList
Calculates the expected error for the standard deviation of the P-value logarithm.	multilevelError
Calculates P-values for preprocessed data.	multilevelImpl
Plots expression profile of a gene set	plotCoregulationProfile
Spatial visualization of GESECA scores for individual cells	plotCoregulationProfileImage
Plot a spatial expression profile of a gene set	plotCoregulationProfileReduction
Plot a spatial expression profile of a gene set	plotCoregulationProfileSpatial
Plots GSEA enrichment plot. For more flexibility use `plotEnrichmentData` function.	plotEnrichment
Returns data required for doing an enrichment plot.	plotEnrichmentData
Plots table of gene set profiles.	plotGesecaTable
Plots table of enrichment graphs using ggplot and gridExtra.	plotGseaTable
Returns a list of Reactome pathways for given Entrez gene IDs	reactomePathways
Write collection of pathways (list of vectors) to a gmt file	writeGmtPathways