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EGSEA

This is the development version of EGSEA; for the stable release version, see EGSEA.

Ensemble of Gene Set Enrichment Analyses


Bioconductor version: Development (3.19)

This package implements the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. EGSEA algorithm utilizes the analysis results of twelve prominent GSE algorithms in the literature to calculate collective significance scores for each gene set.

Author: Monther Alhamdoosh [aut, cre], Luyi Tian [aut], Milica Ng [aut], Matthew Ritchie [ctb]

Maintainer: Monther Alhamdoosh <m.hamdoosh at gmail.com>

Citation (from within R, enter citation("EGSEA")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("EGSEA")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Classification, DifferentialExpression, GO, GeneExpression, GeneSetEnrichment, GeneSignaling, GeneTarget, Genetics, GraphAndNetwork, ImmunoOncology, KEGG, Metabolomics, Microarray, MultipleComparison, Network, NetworkEnrichment, OneChannel, Pathways, Proteomics, RNASeq, Sequencing, Software, SystemsBiology, TwoChannel
Version 1.31.3
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License GPL-3
Depends R (>= 4.3.0), Biobase, gage(>= 2.14.4), AnnotationDbi, topGO(>= 2.16.0), pathview(>= 1.4.2)
Imports PADOG(>= 1.6.0), GSVA(>= 1.12.0), globaltest(>= 5.18.0), limma(>= 3.20.9), edgeR(>= 3.6.8), HTMLUtils (>= 0.1.5), hwriter (>= 1.2.2), gplots (>= 2.14.2), ggplot2 (>= 1.0.0), safe(>= 3.4.0), stringi (>= 0.5.0), parallel, stats, metap, grDevices, graphics, utils, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, RColorBrewer, methods, EGSEAdata(>= 1.3.1), htmlwidgets, plotly, DT
System Requirements
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Suggests BiocStyle, knitr, testthat
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Depends On Me EGSEA123
Imports Me
Suggests Me EGSEAdata, tidybulk
Links To Me
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Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/EGSEA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/EGSEA
Package Short Url https://bioconductor.org/packages/EGSEA/
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