Package: mrbayes 0.5.3.9000

Tom Palmer

mrbayes: Bayesian Summary Data Models for Mendelian Randomization Studies

Bayesian estimation of inverse variance weighted (IVW), Burgess et al. (2013) <doi:10.1002/gepi.21758>, and MR-Egger, Bowden et al. (2015) <doi:10.1093/ije/dyv080>, summary data models for Mendelian randomization analyses.

Authors:Okezie Uche-Ikonne [aut], Frank Dondelinger [aut], Tom Palmer [aut, cre]

mrbayes_0.5.3.9000.tar.gz
mrbayes_0.5.3.9000.zip(r-4.7-x86_64)mrbayes_0.5.3.9000.zip(r-4.7-arm64)mrbayes_0.5.3.9000.zip(r-4.6-x86_64)mrbayes_0.5.3.9000.zip(r-4.6-arm64)mrbayes_0.5.3.9000.zip(r-4.5-x86_64)
mrbayes_0.5.3.9000.tgz(r-4.6-x86_64)mrbayes_0.5.3.9000.tgz(r-4.6-arm64)mrbayes_0.5.3.9000.tgz(r-4.5-x86_64)mrbayes_0.5.3.9000.tgz(r-4.5-arm64)
mrbayes_0.5.3.9000.tar.gz(r-4.7-arm64)mrbayes_0.5.3.9000.tar.gz(r-4.7-x86_64)mrbayes_0.5.3.9000.tar.gz(r-4.6-arm64)mrbayes_0.5.3.9000.tar.gz(r-4.6-x86_64)
mrbayes_0.5.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mrbayes/json (API)

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

Bug tracker:https://github.com/okezie94/mrbayes/issues

Pkgdown/docs site:https://okezie94.github.io

Uses libs:
  • onetbb– Parallelism library for C++
  • c++– GNU Standard C++ Library v3
Datasets:
  • bmi_insulin - Dataset from Richmond et al. 2017 investigating the association of BMI on insulin resistance
  • dodata - Dataset from Do et al., Nat Gen, 2013 containing summary level data on associations of genotypes with lipid traits and the risk of coronary heart diseases

On CRAN:

Conda:

onetbbcpp

5.85 score 5 stars 9 scripts 449 downloads 48 mentions 13 exports 88 dependencies

Last updated from:369a5d4599. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK364
linux-devel-x86_64OK397
source / vignettesOK482
linux-release-arm64OK383
linux-release-x86_64OK450
macos-release-arm64OK344
macos-release-x86_64OK645
macos-oldrel-arm64OK439
macos-oldrel-x86_64OK623
windows-devel-arm64OK472
windows-devel-x86_64OK578
windows-release-arm64OK468
windows-release-x86_64OK589
windows-oldrel-x86_64OK625
wasm-releaseOK301

Exports:mr_egger_rjagsmr_egger_stanmr_formatmr_ivw_rjagsmr_ivw_stanmr_radialegger_rjagsmr_radialegger_stanmrinput_mr_formatmvmr_egger_rjagsmvmr_egger_stanmvmr_formatmvmr_ivw_rjagsmvmr_ivw_stan

Dependencies:abindaskpassbackportsBHbitbit64bootcallrcellrangercheckmateclassclicliprcpp11crayoncurldata.tabledescDescToolsdistributionale1071Exactexpmfarverforcatsfsgenericsggplot2gldgluegridExtragtablehavenhmshttrinlineisobandjsonlitelabelinglatticelifecyclelmomloomagrittrMASSMatrixmatrixStatsmimemvtnormnumDerivopensslotelpillarpkgbuildpkgconfigposteriorprettyunitsprocessxprogressproxypsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreadrreadxlrematchrlangrootSolverstanrstantoolsrstudioapiS7scalesStanHeaderssystensorAtibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

Readme and manuals

Help Manual

Help pageTopics
mrbayes: Bayesian implementation of the IVW and MR-Egger models for two-sample Mendelian randomization analysesmrbayes-package mrbayes
Dataset from Richmond et al. 2017 investigating the association of BMI on insulin resistancebmi_insulin
Dataset from Do et al., Nat Gen, 2013 containing summary level data on associations of genotypes with lipid traits and the risk of coronary heart diseasesdodata
Bayesian implementation of the MR-Egger multivariate model with choice of prior distributions fitted using JAGS.mr_egger_rjags
Bayesian inverse variance weighted model with a choice of prior distributions fitted using Stanmr_egger_stan
Organises the summary level data for use in the Bayesian MR functionsmr_format
Bayesian inverse variance weighted model with a choice of prior distributions fitted using JAGS.mr_ivw_rjags
Bayesian inverse variance weighted model with a choice of prior distributions fitted using RStan.mr_ivw_stan
Bayesian radial MR-Egger model with a choice of prior distributions fitted using JAGS.mr_radialegger_rjags
Bayesian inverse variance weighted model with a choice of prior distributions fitted using RStan.mr_radialegger_stan
Convert an object of class MRInput from the MendelianRandomization package to the mrbayes mr_format classmrinput_mr_format
Bayesian implementation of the MVMR-Egger model with choice of prior distributions fitted using JAGS.mvmr_egger_rjags
Bayesian implementation of the MVMR-Egger model with choice of prior distributions fitted using RStan.mvmr_egger_stan
Organises the summary level data for use in the Bayesian MR functionsmvmr_format
Bayesian multivariate inverse variance weighted model with a choice of prior distributions fitted using JAGS.mvmr_ivw_rjags
Bayesian multivariate inverse variance weighted model with a choice of prior distributions fitted using RStan.mvmr_ivw_stan