Package: clusterProfiler 4.21.0

Guangchuang Yu

clusterProfiler: A Universal Enrichment Tool for Interpreting Omics Data

A universal tool for interpreting functional characteristics of omics data. It supports Over-Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) for both coding and non-coding genomics data of thousands of species. It provides a unified and tidy interface to access, manipulate, and visualize enrichment results. A key capability is the simultaneous analysis and comparison of datasets from multiple treatments or time points. Furthermore, it integrates Large Language Model (LLM) capabilities to provide automated and insightful interpretation of enrichment results.

Authors:Guangchuang Yu [aut, cre, cph], Li-Gen Wang [ctb], Xiao Luo [ctb], Meijun Chen [ctb], Giovanni Dall'Olio [ctb], Wanqian Wei [ctb], Chun-Hui Gao [ctb]

clusterProfiler_4.21.0.tar.gz
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clusterProfiler_4.21.0.tgz(r-4.6-any)clusterProfiler_4.21.0.tgz(r-4.5-any)
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clusterProfiler_4.21.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
clusterProfiler/json (API)
NEWS

# Install 'clusterProfiler' in R:
install.packages('clusterProfiler', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yulab-smu/clusterprofiler/issues

Datasets:
  • DE_GSE8057 - Datasets gcSample contains a sample of gene clusters.
  • gcSample - Datasets gcSample contains a sample of gene clusters.

On BioConductor:clusterProfiler-4.21.0(bioc 3.24)clusterProfiler-4.20.0(bioc 3.23)

annotationclusteringgenesetenrichmentgokeggmultiplecomparisonpathwaysreactomevisualizationenrichment-analysisgseaquarto

17.35 score 1.2k stars 47 packages 16k scripts 42k downloads 2.2k mentions 73 exports 118 dependencies

Last updated from:400f57a5dc. Checks:1 ERROR, 9 OK. Indexed: yes.

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bioc-checksERROR215
linux-devel-x86_64OK367
source / vignettesOK286
linux-release-x86_64OK325
macos-release-arm64OK263
macos-oldrel-arm64OK278
windows-develOK612
windows-releaseOK307
windows-oldrelOK655
wasm-releaseOK175

Exports:%<>%%>%append_kegg_categoryarrangebitrbitr_keggbrowseKEGGbuildGOmapcnetplotcompareClusterdotplotdownload_KEGGdropGOemapplotenrichDAVIDenricherenrichGOenrichKEGGenrichMKEGGenrichPCenrichWPfiltergeneIDgeneInCategoryget_organismget_wp_organismsgetPPIgetTaxIDgetTaxInfoGff2GeneTablego2ontgo2termgofiltergoplotgroup_bygroupGOGSEAgseaplotgseGOgseKEGGgseMKEGGgsePCgseWPgsfiltergson_GOgson_GO_localgson_KEGGgson_KEGG_mappergson_WPheatplotidTypeinterpretinterpret_agentinterpret_hierarchicalko2namemerge_resultmutatenplotGOgraphread.blast2goread.gafread.gmtread.gmt.pcread.gmt.wprenameridgeplotsearch_kegg_organismselectsetReadablesimplifyslicesummariseuniprot_get

Dependencies:aisdkAnnotationDbiapeaplotaskpassbase64encBiobaseBiocGenericsBiostringsbitbit64blobbslibcachemcallrcliclustercpp11crayoncurlDBIdigestDOSEdplyrenrichitenrichplotevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverfsgdtoolsgenericsggforceggfunggiraphggnewscaleggplot2ggplotifyggrepelggtangleggtreeglueGO.dbGOSemSimgridGraphicsgsongtablehighrhtmltoolshtmlwidgetshttrhttr2igraphIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglatticelazyevallifecyclemagrittrMASSMatrixmemoisemimenlmeopensslpatchworkpillarpkgconfigplyrpngpolyclipprocessxpspurrrqvalueR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownRSQLiteS4VectorsS7sassscalesscatterpieSeqinfostringistringrsyssystemfontstibbletidydrtidyrtidyselecttidytreetinytextreeiotweenrutf8vctrsviridisLitewithrxfunXVectoryamlyulab.utils

Statistical analysis and visualization of functional profiles for genes and gene clusters

Rendered fromclusterProfiler.qmdusingquarto::htmlon May 30 2026.

Last update: 2025-11-20
Started: 2025-11-20

Readme and manuals

Help Manual

Help pageTopics
append_kegg_categoryappend_kegg_category
bitrbitr
bitr_keggbitr_kegg
browseKEGGbrowseKEGG
Compare gene clusters functional profilecompareCluster
Datasets gcSample contains a sample of gene clusters.DataSet DE_GSE8057 gcSample kegg_category kegg_species
download_KEGGdownload_KEGG
dropGOdropGO
enrichDAVIDenrichDAVID
enricherenricher
GO Enrichment Analysis of a gene set. Given a vector of genes, this function will return the enrichment GO categories after FDR control.enrichGO
KEGG Enrichment Analysis of a gene set. Given a vector of genes, this function will return the enrichment KEGG categories with FDR control.enrichKEGG
KEGG Module Enrichment Analysis of a gene set. Given a vector of genes, this function will return the enrichment KEGG Module categories with FDR control.enrichMKEGG
enrichPCenrichPC
enrichWPenrichWP
get_wp_organismget_wp_organisms
getPPIgetPPI
getTaxIDgetTaxID
getTaxInfogetTaxInfo
Gff2GeneTableGff2GeneTable
go2ontgo2ont
go2termgo2term
gofiltergofilter
Functional Profile of a gene set at specific GO level. Given a vector of genes, this function will return the GO profile at a specific level.groupGO
Class "groupGOResult" This class represents the result of functional Profiles of a set of gene at specific GO level.groupGOResult-class show,groupGOResult-method
GSEAGSEA
gseGOgseGO
gseKEGGgseKEGG
gseMKEGGgseMKEGG
gsePCgsePC
gseWPgseWP
gson_KEGGgson_GO
Build a gson object that annotate Gene Ontologygson_GO_local
gson_KEGGgson_KEGG
Build KEGG annotation for novel species using KEGG Mappergson_KEGG_mapper
gson_WPgson_WP
idTypeidType
Interpret Enrichment Results Using LLMsinterpret
Interpret enrichment results using a multi-agent pipeline (Deep Mode)interpret_agent
Interpret enrichment results using a hierarchical strategyinterpret_hierarchical
ko2nameko2name
merge_resultmerge_result
plotplot.interpretation
plotGOgraphplotGOgraph
read.gmt.pcread.gmt.pc
search_kegg_organismsearch_kegg_organism
simplify methodsimplify simplify,compareClusterResult-method simplify,enrichResult-method simplify,gseaResult-method
uniprot_getuniprot_get