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gage (version 2.22.0)

Generally Applicable Gene-set Enrichment for Pathway Analysis

Description

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.

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Version

Version

2.22.0

License

GPL (>=2.0)

Maintainer

Last Published

February 15th, 2017

Functions in gage (2.22.0)

egSymb

Mapping between Entrez Gene IDs and official symbols
go.gsets

Generate up-to-date GO (Gene Ontology) gene sets
geneData

View the expression data for selected genes
gageComp

Compare multiple GAGE analyses results
kegg.gs

Common gene set data collections
gse16873

GSE16873: a breast cancer microarray dataset
esset.grp

The non-redundant signcant gene set list
gage-internal

Internal functions
essGene

Essential member genes in a gene set
sigGeneSet

Significant gene set from GAGE analysis
readList

Read in gene set data as a named list
heter.gage

GAGE analysis for heterogeneous data
kegg.gsets

Generate up-to-date KEGG pathway gene sets
gage

GAGE (Generally Applicable Gene-set Enrichment) analysis
gs.tTest

Gene set differential expression test
gagePipe

GAGE analysis pipeline
eg2sym

Conversion between Entrez Gene IDs and official gene symbols for human genes.
readExpData

Read in expression data