Package: GraphMRcML 0.1.0

Zhaotong Lin

GraphMRcML: Causal Network Inference via Mendelian Randomization with cML and Network Deconvolution

Combines Mendelian randomization (constrained maximum likelihood, cML) and network deconvolution for inference of causal networks from GWAS summary data, as described in Lin, Xue, and Pan (2023) <doi:10.1371/journal.pgen.1010762>.

Authors:Zhaotong Lin [aut, cre], Haoran Xue [aut], Wei Pan [aut]

GraphMRcML_0.1.0.tar.gz
GraphMRcML_0.1.0.zip(r-4.7)GraphMRcML_0.1.0.zip(r-4.6)GraphMRcML_0.1.0.zip(r-4.5)
GraphMRcML_0.1.0.tgz(r-4.6-any)GraphMRcML_0.1.0.tgz(r-4.5-any)
GraphMRcML_0.1.0.tar.gz(r-4.7-any)GraphMRcML_0.1.0.tar.gz(r-4.6-any)
GraphMRcML_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
GraphMRcML/json (API)

# Install 'GraphMRcML' in R:
install.packages('GraphMRcML', repos = c('https://mrcieu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zhaotongl/graphmrcml/issues

On CRAN:

Conda:

2.43 score 9 stars 12 exports 21 dependencies

Last updated from:a094208265 (on refs/pull/2/head). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK113
source / vignettesOK140
linux-release-x86_64OK107
macos-release-arm64OK64
macos-oldrel-arm64OK99
windows-develOK72
windows-releaseOK58
windows-oldrelOK59
wasm-releaseOK106

Exports:cML_estimate_OcML_estimate_random_OcML_SdTheta_OGenerate_PerturbGraph_EstimateGraph_PerturbGraph_Screenloglikmr_cML_DP_Omr_cML_Oplot_graphsubset_Graph_d1

Dependencies:clicpp11dplyrgenericsglueigraphlatticelifecyclemagrittrMASSMatrixpbmcapplypillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr