To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("gage")
In most cases, you don't need to download the package archive at all.
gage
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Generally Applicable Gene-set Enrichment for Pathway Analysis
Bioconductor version: Release (3.5)
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>
Citation (from within R,
enter citation("gage")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("gage")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("gage")
| R Script | Gene set and data preparation | |
| R Script | Generally Applicable Gene-set/Pathway Analysis | |
| R Script | RNA-Seq Data Pathway and Gene-set Analysis Workflows | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GO, GeneExpression, GeneSetEnrichment, Genetics, Microarray, MultipleComparison, OneChannel, Pathways, RNASeq, Sequencing, Software, SystemsBiology, TwoChannel |
| Version | 2.26.3 |
| In Bioconductor since | BioC 2.7 (R-2.12) (7 years) |
| License | GPL (>=2.0) |
| Depends | R (>= 2.10) |
| Imports | graph, KEGGREST, AnnotationDbi |
| LinkingTo | |
| Suggests | pathview, gageData, GO.db, org.Hs.eg.db, hgu133a.db, GSEABase, Rsamtools, GenomicAlignments, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq, DESeq2, edgeR, limma |
| SystemRequirements | |
| Enhances | |
| URL | http://www.biomedcentral.com/1471-2105/10/161 |
| Depends On Me | EGSEA |
| Imports Me | anamiR |
| Suggests Me | FGNet, gageData, pathview |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | gage_2.26.3.tar.gz |
| Windows Binary | gage_2.26.3.zip |
| Mac OS X 10.11 (El Capitan) | gage_2.26.3.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/gage |
| Package Short Url | http://bioconductor.org/packages/gage/ |
| Package Downloads Report | Download Stats |
Documentation »
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