To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("CausalR")

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

CausalR

 

   

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

Causal network analysis methods

Bioconductor version: Development (3.6)

Causal network analysis methods for regulator prediction and network reconstruction from genome scale data.

Author: Glyn Bradley, Steven Barrett, Chirag Mistry, Mark Pipe, David Wille, David Riley, Bhushan Bonde, Peter Woollard

Maintainer: Glyn Bradley <glyn.x.bradley at gsk.com>, Steven Barrett <steven.j.barrett at gsk.com>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("CausalR")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("CausalR")

 

PDF R Script CausalR.pdf
PDF   Reference Manual

Details

biocViews DifferentialExpression, GraphAndNetwork, Microarray, Network, Network Inference, Proteomics, RNASeq, Software, SystemsBiology, Transcriptomics
Version 1.9.0
In Bioconductor since BioC 3.2 (R-3.2) (1.5 years)
License GPL (>= 2)
Depends R (>= 3.2.0)
Imports igraph
LinkingTo
Suggests knitr, RUnit, BiocGenerics
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source CausalR_1.9.0.tar.gz
Windows Binary CausalR_1.9.0.zip
Mac OS X 10.11 (El Capitan) CausalR_1.9.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/CausalR
Package Short Url http://bioconductor.org/packages/CausalR/
Package Downloads Report Download Stats

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