networkBMA

DOI: 10.18129/B9.bioc.networkBMA    

Regression-based network inference using Bayesian Model Averaging

Bioconductor version: Release (3.13)

An extension of Bayesian Model Averaging (BMA) for network construction using time series gene expression data. Includes assessment functions and sample test data.

Author: Chris Fraley, Wm. Chad Young, Ling-Hong Hung, Kaiyuan Shi, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo)

Maintainer: Ka Yee Yeung <kayee at u.washington.edu>

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

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("networkBMA")

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("networkBMA")

 

PDF R Script networkBMA
PDF   Reference Manual
Text   NEWS

Details

biocViews Bayesian, GeneExpression, GeneTarget, GraphsAndNetwork, Network, NetworkInference, Software
Version 2.32.0
In Bioconductor since BioC 2.11 (R-2.15) (9 years)
License GPL (>= 2)
Depends R (>= 2.15.0), stats, utils, BMA, Rcpp (>= 0.10.3), RcppArmadillo (>= 0.3.810.2), RcppEigen (>= 0.3.1.2.1), leaps
Imports
LinkingTo Rcpp, RcppArmadillo, RcppEigen, BH
Suggests
SystemRequirements liblapack-dev
Enhances
URL
Depends On Me
Imports Me
Suggests Me DREAM4
Links To Me
Build Report  

Package Archives

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

Source Package networkBMA_2.32.0.tar.gz
Windows Binary networkBMA_2.32.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra) networkBMA_2.32.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/networkBMA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/networkBMA
Package Short Url https://bioconductor.org/packages/networkBMA/
Package Downloads Report Download Stats

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