Package: gage 2.63.0

Weijun Luo

gage: Generally Applicable Gene-set Enrichment for Pathway Analysis

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.

Authors:Weijun Luo

gage_2.63.0.tar.gz
gage_2.63.0.zip(r-4.7)gage_2.63.0.zip(r-4.6)gage_2.63.0.zip(r-4.5)
gage_2.63.0.tgz(r-4.6-any)gage_2.63.0.tgz(r-4.5-any)
gage_2.63.0.tar.gz(r-4.7-any)gage_2.63.0.tar.gz(r-4.6-any)
gage_2.63.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
gage/json (API)

# Install 'gage' in R:
install.packages('gage', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/datapplab/gage/issues

Datasets:
  • bods - Common gene set data collections
  • carta.gs - Common gene set data collections
  • egSymb - Mapping between Entrez Gene IDs and official symbols
  • go.gs - Common gene set data collections
  • gse16873 - GSE16873: a breast cancer microarray dataset
  • kegg.gs - Common gene set data collections
  • kegg.gs.dise - Common gene set data collections
  • khier - Common gene set data collections
  • korg - Common gene set data collections

On BioConductor:gage-2.63.0(bioc 3.24)gage-2.62.0(bioc 3.23)

pathwaysgodifferentialexpressionmicroarrayonechanneltwochannelrnaseqgeneticsmultiplecomparisongenesetenrichmentgeneexpressionsystemsbiologysequencing

9.23 score 6 stars 3 packages 1.1k scripts 45 mentions 20 exports 37 dependencies

Last updated from:8234ca0cd1. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR258
linux-devel-x86_64WARNING333
source / vignettesOK399
linux-release-x86_64WARNING358
macos-release-arm64WARNING151
macos-oldrel-arm64WARNING209
windows-develWARNING323
windows-releaseWARNING351
windows-oldrelWARNING391
wasm-releaseOK243

Exports:eg2symesset.grpessGenegagegageCompgagePipegagePrepgageSumgeneDatago.gsetsgs.KSTestgs.tTestgs.zTestheter.gagekegg.gsetspairDatareadExpDatareadListsigGeneSetsym2eg

Dependencies:AnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64blobcachemclicpp11crayoncurlDBIfastmapgenericsglueGO.dbgraphhttrIRangesjsonliteKEGGRESTlifecyclememoisemimeopensslpkgconfigpngR6rlangRSQLiteS4VectorsSeqinfosysvctrsXVector

Generally Applicable Gene-set/Pathway Analysis
Cite our work | Quick start with demo data | New features | Introduction | Installation | Get Started | Basic Analysis | Result Presentation and Intepretation | Advanced Analysis | Common Errors

Last update: 2021-04-29
Started: 2013-11-01

RNA-Seq Data Pathway and Gene-set Analysis Workflows
Introduction | Cite our work | Quick start: RNA-Seq pathway analysis in about 40 lines | The native workflow | GO analysis and other gene set analyses | Per gene score choices | Joint workflows with common RNA-Seq analysis tools

Last update: 2021-04-29
Started: 2013-11-01

Gene set and data preparation
Introduction | Expression data input | Gene set data input | Probe set ID conversion | gene or transcript ID conversion

Last update: 2017-06-24
Started: 2013-11-01