Package: fgsea 1.39.2

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]

fgsea_1.39.2.tar.gz
fgsea_1.39.2.zip(r-4.7)fgsea_1.39.2.zip(r-4.6)fgsea_1.39.2.zip(r-4.5)
fgsea_1.39.2.tgz(r-4.6-x86_64)fgsea_1.39.2.tgz(r-4.6-arm64)fgsea_1.39.2.tgz(r-4.5-x86_64)fgsea_1.39.2.tgz(r-4.5-arm64)
fgsea_1.39.2.tar.gz(r-4.7-arm64)fgsea_1.39.2.tar.gz(r-4.7-x86_64)fgsea_1.39.2.tar.gz(r-4.6-arm64)fgsea_1.39.2.tar.gz(r-4.6-x86_64)
fgsea_1.39.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
fgsea/json (API)

# 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:

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

geneexpressiondifferentialexpressiongenesetenrichmentpathwayscpp

14.60 score 448 stars 54 packages 6.6k scripts 150 mentions 24 exports 31 dependencies

Last updated from:c70539cd6e. Checks:1 ERROR, 11 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR297
linux-devel-arm64WARNING515
linux-devel-x86_64WARNING492
source / vignettesOK934
linux-release-arm64WARNING536
linux-release-x86_64WARNING459
macos-release-arm64WARNING257
macos-release-x86_64WARNING610
macos-oldrel-arm64WARNING282
macos-oldrel-x86_64WARNING782
windows-develWARNING698
windows-releaseWARNING662
windows-oldrelWARNING580
wasm-releaseOK284

Exports:calcGseaStatcalcGseaStatCumulativecollapsePathwayscollapsePathwaysORAfgseafgseaLabelfgseaMultilevelfgseaSimpleforagesecagesecaSimplegmtPathwaysmapIdsListmultilevelErrorplotCoregulationProfileplotCoregulationProfileImageplotCoregulationProfileReductionplotCoregulationProfileSpatialplotEnrichmentplotEnrichmentDataplotGesecaTableplotGseaTablereactomePathwayswriteGmtPathways

Dependencies:BHBiocParallelclicodetoolscowplotcpp11data.tablefarverfastmatchformatRfutile.loggerfutile.optionsggplot2gluegtableisobandlabelinglambda.rlatticelifecycleMatrixR6RColorBrewerRcpprlangS7scalessnowvctrsviridisLitewithr

Gene set co-regulation analysis tutorial
Overiew of GESECA method | Analysis of time course data | Analysis of single-cell RNA-seq | Analysis of spatial transcriptomic data | Analysis of 10X visium spatial data | Analysis of 10X xenium spatial transcriptomics data | Session info

Last update: 2026-06-26
Started: 2025-11-04

Using fgsea package
Loading necessary libraries | Quick run | Performance considerations | Using Reactome pathways | Starting from files | Over-representation test | Session info

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

Readme and manuals

Help Manual

Help pageTopics
Calculates GSEA statistics for a given query gene setcalcGseaStat
Calculates GSEA statistic valus for all gene sets in `selectedStats` list.calcGseaStatBatchCpp
Calculates GSEA statistic values for all the prefixes of a gene setcalcGseaStatCumulative
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 testfora
Runs multilevel Monte-Carlo variant for performing gene sets co-regulation analysisgeseca
Runs simple variant for performing gene sets co-regulation analysisgesecaSimple
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 setplotCoregulationProfile
Spatial visualization of GESECA scores for individual cellsplotCoregulationProfileImage
Plot a spatial expression profile of a gene setplotCoregulationProfileReduction
Plot a spatial expression profile of a gene setplotCoregulationProfileSpatial
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 IDsreactomePathways
Write collection of pathways (list of vectors) to a gmt filewriteGmtPathways