Package: mrbayes 0.5.2.9000

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]

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NEWS

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

Peer review:

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

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

Uses libs:
  • 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:

cpp

5.20 score 4 stars 2 scripts 270 downloads 48 mentions 13 exports 90 dependencies

Last updated 25 days agofrom:99189d64b0. Checks:2 OK, 4 ERROR, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKDec 19 2024
R-4.5-win-x86_64NOTEDec 19 2024
R-4.5-linux-x86_64OKDec 19 2024
R-4.4-win-x86_64NOTEDec 19 2024
R-4.4-mac-x86_64ERRORDec 19 2024
R-4.4-mac-aarch64ERRORDec 19 2024
R-4.3-win-x86_64NOTEDec 19 2024
R-4.3-mac-x86_64ERRORDec 19 2024
R-4.3-mac-aarch64ERRORDec 19 2024

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:abindaskpassbackportsBHbitbit64bootcallrcellrangercheckmateclassclicliprcolorspacecpp11crayoncurldata.tabledescDescToolsdistributionale1071Exactexpmfansifarverforcatsgenericsggplot2gldgluegridExtragtablehavenhmshttrinlineisobandjsonlitelabelinglatticelifecyclelmomloomagrittrMASSMatrixmatrixStatsmgcvmimemunsellmvtnormnlmenumDerivopensslpillarpkgbuildpkgconfigposteriorprettyunitsprocessxprogressproxypsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreadrreadxlrematchrlangrootSolverstanrstantoolsrstudioapiscalesStanHeaderssystensorAtibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

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