mgsa
This package is for version 3.18 of Bioconductor; for the stable, up-to-date release version, see mgsa.
Model-based gene set analysis
Bioconductor version: 3.18
Model-based Gene Set Analysis (MGSA) is a Bayesian modeling approach for gene set enrichment. The package mgsa implements MGSA and tools to use MGSA together with the Gene Ontology.
Author: Sebastian Bauer <mail at sebastianbauer.info>, Julien Gagneur <gagneur at genzentrum.lmu.de>
Maintainer: Sebastian Bauer <mail at sebastianbauer.info>
citation("mgsa")
):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("mgsa")
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("mgsa")
Overview of the mgsa package. | R Script | |
Reference Manual |
Details
biocViews | GO, GeneSetEnrichment, Pathways, Software |
Version | 1.50.0 |
In Bioconductor since | BioC 2.8 (R-2.13) (13 years) |
License | Artistic-2.0 |
Depends | R (>= 2.14.0), methods, gplots |
Imports | graphics, stats, utils |
System Requirements | |
URL | https://github.com/sba1/mgsa-bioc |
See More
Suggests | DBI, RSQLite, GO.db, testthat |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | pareg |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | mgsa_1.50.0.tar.gz |
Windows Binary | mgsa_1.50.0.zip (64-bit only) |
macOS Binary (x86_64) | mgsa_1.50.0.tgz |
macOS Binary (arm64) | mgsa_1.50.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/mgsa |
Source Repository (Developer Access) | git clone [email protected]:packages/mgsa |
Bioc Package Browser | https://code.bioconductor.org/browse/mgsa/ |
Package Short Url | https://bioconductor.org/packages/mgsa/ |
Package Downloads Report | Download Stats |