gage

DOI: 10.18129/B9.bioc.gage  

Generally Applicable Gene-set Enrichment for Pathway Analysis

Bioconductor version: Release (3.16)

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 yahoo.com>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("gage")

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

Documentation

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

browseVignettes("gage")

 

PDF	R Script	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		Reference Manual
Text		NEWS

Details

biocViews	DifferentialExpression, GO, GeneExpression, GeneSetEnrichment, Genetics, Microarray, MultipleComparison, OneChannel, Pathways, RNASeq, Sequencing, Software, SystemsBiology, TwoChannel
Version	2.48.0
In Bioconductor since	BioC 2.7 (R-2.12) (12.5 years)
License	GPL (>=2.0)
Depends	R (>= 3.5.0)
Imports	graph, KEGGREST, AnnotationDbi, GO.db
LinkingTo
Suggests	pathview, gageData, org.Hs.eg.db, hgu133a.db, GSEABase, Rsamtools, GenomicAlignments, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq2, edgeR, limma
SystemRequirements
Enhances
URL	https://github.com/datapplab/gage http://www.biomedcentral.com/1471-2105/10/161
Depends On Me	EGSEA
Imports Me
Suggests Me	FGNet, gageData, pathview, SBGNview
Links To Me
Build Report

Package Archives

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

Source Package	gage_2.48.0.tar.gz
Windows Binary	gage_2.48.0.zip (64-bit only)
macOS Binary (x86_64)	gage_2.48.0.tgz
macOS Binary (arm64)	gage_2.48.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/gage
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/gage
Bioc Package Browser	https://code.bioconductor.org/browse/gage/
Package Short Url	https://bioconductor.org/packages/gage/
Package Downloads Report	Download Stats