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mogsa

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

Multiple omics data integrative clustering and gene set analysis


Bioconductor version: Development (3.19)

This package provide a method for doing gene set analysis based on multiple omics data.

Author: Chen Meng

Maintainer: Chen Meng <mengchen18 at gmail.com>

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

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("mogsa")

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("mogsa")
moCluster: Integrative clustering using multiple omics data PDF R Script
mogsa: gene set analysis on multiple omics data PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, GeneExpression, PrincipalComponent, Software, StatisticalMethod
Version 1.37.0
In Bioconductor since BioC 3.1 (R-3.2) (9 years)
License GPL-2
Depends R (>= 3.4.0)
Imports methods, graphite, genefilter, BiocGenerics, gplots, GSEABase, Biobase, parallel, corpcor, svd, cluster, grDevices, graphics, stats, utils
System Requirements
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Suggests BiocStyle, knitr, org.Hs.eg.db
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Build Report Build Report

Package Archives

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

Source Package mogsa_1.37.0.tar.gz
Windows Binary mogsa_1.37.0.zip
macOS Binary (x86_64) mogsa_1.37.0.tgz
macOS Binary (arm64) mogsa_1.37.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/mogsa
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/mogsa
Bioc Package Browser https://code.bioconductor.org/browse/mogsa/
Package Short Url https://bioconductor.org/packages/mogsa/
Package Downloads Report Download Stats