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

Causal network analysis methods

Bioconductor version: Development (3.20)

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>, Steven Barrett <steven.j.barrett at>

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


To install this package, start R (version "4.4") and enter:

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

# The following initializes usage of Bioc devel


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 1.37.0
In Bioconductor since BioC 3.2 (R-3.2) (9 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_1.37.0.tar.gz
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macOS Binary (x86_64) CausalR_1.37.0.tgz
macOS Binary (arm64) CausalR_1.37.0.tgz
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