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gage

Generally Applicable Gene-set Enrichment for Pathway Analysis

Bioconductor version: 3.23 · Package version: 2.62.0

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.

Installation

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

BiocManager::install("gage")

Details

MaintainerWeijun Luo <luo_weijun@yahoo.com>
AuthorWeijun Luo
LicenseGPL (>=2.0)
URLhttps://github.com/datapplab/gage, http://www.biomedcentral.com/1471-2105/10/161
Downloads rank1238
Source branchRELEASE_3_23
biocViewsDifferentialExpression, GO, GeneExpression, GeneSetEnrichment, Genetics, Microarray, MultipleComparison, OneChannel, Pathways, RNASeq, Sequencing, Software, SystemsBiology, TwoChannel

Documentation

Download

Dependencies

Depends: R (>= 3.5.0)

Imports: graph, KEGGREST, AnnotationDbi, GO.db

Suggests: pathview, gageData, org.Hs.eg.db, hgu133a.db, GSEABase, Rsamtools, GenomicAlignments, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq2, edgeR, limma

Reverse dependencies

Depends On Me (1): EGSEA

Imports Me (1): postNet

Suggests Me (4): FGNet, gageData, pathview, SBGNview