Registration Open for Bioc2024 July 24-26


Generally Applicable Gene-set Enrichment for Pathway Analysis

Bioconductor version: Release (3.19)

GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

Author: Weijun Luo

Maintainer: Weijun Luo <luo_weijun at>

Citation (from within R, enter citation("gage")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Gene set and data preparation PDF R Script
Generally Applicable Gene-set/Pathway Analysis PDF R Script
RNA-Seq Data Pathway and Gene-set Analysis Workflows PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, GO, GeneExpression, GeneSetEnrichment, Genetics, Microarray, MultipleComparison, OneChannel, Pathways, RNASeq, Sequencing, Software, SystemsBiology, TwoChannel
Version 2.54.0
In Bioconductor since BioC 2.7 (R-2.12) (13.5 years)
License GPL (>=2.0)
Depends R (>= 3.5.0)
Imports graph, KEGGREST, AnnotationDbi, GO.db
System Requirements
See More
Suggests pathview, gageData,, hgu133a.db, GSEABase, Rsamtools, GenomicAlignments, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq2, edgeR, limma
Linking To
Depends On Me EGSEA
Imports Me
Suggests Me FGNet, SBGNview, pathview, gageData
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package gage_2.54.0.tar.gz
Windows Binary
macOS Binary (x86_64) gage_2.54.0.tgz
macOS Binary (arm64) gage_2.54.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats