Package: MrDAG 0.1.1

Leonardo Bottolo

MrDAG: MrDAG: Bayesian causal graphical model for joint Mendelian randomization analysis of multiple exposures and outcomes

This package performs Mendelian randomization for multiple exposures and outcomes with Bayesian structure learning and causal effects estimation. The directionality of the causal effects between the exposures and the outcomes is assumed known, i.e., the exposures can only be potential causes of the outcomes and no reverse causation is allowed.

Authors:Leonardo Bottolo [aut, cre], Verena Zuber [aut, ctb]

MrDAG_0.1.1.tar.gz
MrDAG_0.1.1.zip(r-4.7-any)MrDAG_0.1.1.zip(r-4.6-any)MrDAG_0.1.1.zip(r-4.5-any)
MrDAG_0.1.1.tgz(r-4.6-any)MrDAG_0.1.1.tgz(r-4.5-any)
MrDAG_0.1.1.tar.gz(r-4.7-any)MrDAG_0.1.1.tar.gz(r-4.6-any)
MrDAG_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MrDAG/json (API)

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

Bug tracker:https://github.com/lb664/mrdag/issues

Datasets:
  • LBT2MD_data - MrDAG data set: Lifestyle and behavioural exposures that might impact mental health phenotypes
  • MD2LBT_data - MrDAG data set: Mental health phenotypes that might impact lifestyle and behavioural traits

On CRAN:

Conda:

2.74 score 11 stars 4 exports 18 dependencies

Last updated from:9b37d111ac. Checks:7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develNOTE219
source / vignettesOK176
linux-releaseNOTE231
macos-releaseNOTE146
macos-oldrelNOTE148
windows-develNOTE174
windows-releaseNOTE189
windows-oldrelNOTE149
wasm-releaseOK123

Exports:get_causaleffectget_causaleffectsget_edgeprobMrDAG

Dependencies:clicpp11gluegRbaseigraphlatticelifecyclemagrittrMatrixmvtnormpkgconfigrbibutilsRcppRcppArmadilloRcppEigenRdpackrlangvctrs