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MRPC: PC Algorithm with the Principle of Mendelian Randomization

A PC Algorithm with the Principle of Mendelian Randomization. This package implements the MRPC (PC with the principle of Mendelian randomization) algorithm to infer causal graphs. It also contains functions to simulate data under a certain topology, to visualize a graph in different ways, and to compare graphs and quantify the differences. See Badsha and Fu (2019) <doi:10.3389/fgene.2019.00460>,Badsha, Martin and Fu (2021) <doi:10.3389/fgene.2021.651812>.

Version: 3.1.0
Depends: R (≥ 4.0)
Imports: bnlearn, compositions, dynamicTreeCut, GGally, fastcluster, gtools, graph, graphics, Hmisc, methods, mice, network, pcalg, psych, Rgraphviz, stats, sna, utils, WGCNA, plyr
Published: 2022-04-11
Author: Md Bahadur Badsha [aut,cre],Evan A Martin [ctb] and Audrey Qiuyan Fu [aut]
Maintainer: Audrey Fu <audreyqyfu at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
In views: CausalInference
CRAN checks: MRPC results

Documentation:

Reference manual: MRPC.pdf

Downloads:

Package source: MRPC_3.1.0.tar.gz
Windows binaries: r-devel: MRPC_3.1.0.zip, r-release: MRPC_3.1.0.zip, r-oldrel: MRPC_3.1.0.zip
macOS binaries: r-release (arm64): MRPC_3.1.0.tgz, r-oldrel (arm64): MRPC_3.1.0.tgz, r-release (x86_64): MRPC_3.1.0.tgz, r-oldrel (x86_64): MRPC_3.1.0.tgz
Old sources: MRPC archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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