GAGE specifications

Information


Unique identifier OMICS_18498
Name GAGE
Alternative name Generally Applicable Gene-set Enrichment
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data A gene set.
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 2.26.0
Stability Stable
Maintained Yes

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Documentation


Maintainers


  • person_outline Peter Woolf <>
  • person_outline Weijun Luo <>
  • person_outline Michael Friedman <>
  • person_outline Kerby Shedden <>
  • person_outline Kurt Hankenson <>

Additional information


https://github.com/Bioconductor-mirror/gage/tree/release-3.5

GAGE article

GAGE citations

 (2)
2018
PMCID: 5813940

[…] for each module that was significantly associated with at least one diabetes trait, we summarized the module based on its top ten significant gene ontology (go) terms. we also used the r package gage [99] to identify pathways that were perturbed in a single direction or generally dysregulated due to maternal diet, and visualized those pathways using the r package pathview [100]., […]

2017
PMCID: 5435363

[…] the control (see fig 4b & s8 table). degs were then used to obtain enriched biological functions by a parametric gene set enrichment analysis by using package ‘gage’ [62]. the method defined in ‘gage’ enabled to extract gene ontology terms associated with up-regulated degs. finally, a distance matrix was calculated from the expression data for degs based on the correlation distance [63], […]

GAGE institution(s)
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Bioinformatics Shared Resource, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Thermogenesis Corporation, Rancho Cordova, CA, USA; Department of Statistics, University of Michigan, Ann Arbor, MI, USA; Department of Animal Biology, University of Pennsylvania, Philadelphia, PA, USA; Bioinformatics Program, University of Michigan, Ann Arbor, MI, USA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
GAGE funding source(s)
Supported by NIH grant R01 DE017471; by NIH grant U54-DA-021519 and by NIH grants R01 AR054714 and R01 AR049682.

GAGE review

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Dr Nick

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Desktop
A fairly easy algorithm and R package to perform custom gene set enrichment analyses with normalized expression datasets. My only qualm is the lack of information and examples to assist in the guidance of variable universe sizes among different datasets. A Fisher's test is very explicit in the effects of a changing universe size, but have had to empirically test, through numerous iterations, the equivalency of one sets enrichment results to another using the same reference set for comparison. Regardless, the ease of implementation compared with other popular packages, such as GSEA, make it possible to iteratively test such parameter changes in short order.