CausalR

DOI: 10.18129/B9.bioc.CausalR    

Causal network analysis methods

Bioconductor version: Release (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>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/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	1.10.0
In Bioconductor since	BioC 3.2 (R-3.2) (2.5 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.

Source Package	CausalR_1.10.0.tar.gz
Windows Binary	CausalR_1.10.0.zip
Mac OS X 10.11 (El Capitan)	CausalR_1.10.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/CausalR
Package Short Url	http://bioconductor.org/packages/CausalR/
Package Downloads Report	Download Stats