gage (original) (raw)

This is the released version of gage; for the devel version, seegage.

Generally Applicable Gene-set Enrichment for Pathway Analysis

Bioconductor version: Release (3.20)

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 (version "4.4") 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")

Details

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