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Causal network analysis methods

Bioconductor version: Release (3.18)

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")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


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

CausalR.pdf PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, Network Inference, Proteomics, RNASeq, Software, SystemsBiology, Transcriptomics
Version 1.34.0
In Bioconductor since BioC 3.2 (R-3.2) (8.5 years)
License GPL (>= 2)
Depends R (>= 3.2.0)
Imports igraph
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Suggests knitr, RUnit, BiocGenerics
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Follow Installation instructions to use this package in your R session.

Source Package CausalR_1.34.0.tar.gz
Windows Binary CausalR_1.34.0.zip
macOS Binary (x86_64) CausalR_1.34.0.tgz
macOS Binary (arm64) CausalR_1.34.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CausalR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CausalR
Bioc Package Browser https://code.bioconductor.org/browse/CausalR/
Package Short Url https://bioconductor.org/packages/CausalR/
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