To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("networkBMA")

In most cases, you don't need to download the package archive at all.

networkBMA

 

   

Regression-based network inference using Bayesian Model Averaging

Bioconductor version: Release (3.4)

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("networkBMA")

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 2.12.0
In Bioconductor since BioC 2.11 (R-2.15) (4 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)
Imports
LinkingTo Rcpp, RcppArmadillo, RcppEigen, BH
Suggests
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me DREAM4
Build Report  

Package Archives

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

Package Source networkBMA_2.12.0.tar.gz
Windows Binary
Mac OS X 10.9 (Mavericks)
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/networkBMA/tree/release-3.4
Package Short Url http://bioconductor.org/packages/networkBMA/
Package Downloads Report Download Stats

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