Generally Applicable Gene-set Enrichment for Pathway Analysis

Bioconductor version: 2.9

GAGE is a published method for gene set or pathway analysis. GAGE is generally applicable independent of microarray data attributes including sample sizes, experimental designs, microarray 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>

To install this package, start R and enter:


To cite this package in a publication, start R and enter:



PDF R Script Generally Applicable Gene-set/Pathway Analysis
PDF   Reference Manual
Text   NEWS


biocViews Pathways, GO, DifferentialExpression, Microarray, OneChannel, TwoChannel, RNAseq, DataRepresentation, Genetics, Bioinformatics, MultipleComparisons
Depends graph, multtest
Suggests gageData, GO.db, GSEABase, KEGG.db,
System Requirements
License GPL (>=2.0)
Depends On Me
Imports Me
Suggests Me gageData
Version 2.4.0
Since Bioconductor 2.7 (R-2.12)

Package Downloads

Package Source gage_2.4.0.tar.gz
Windows Binary (32- & 64-bit)
MacOS 10.5 (Leopard) binary gage_2.4.0.tgz
Package Downloads Report Download Stats

Workflows »

Common Bioconductor workflows include:


Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Fred Hutchinson Cancer Research Center