Package: autoMR 1.1.2
autoMR: Automated Mendelian Randomization Workflows and Visualizations
Provides tools to summarize, analyze, and visualize results from Mendelian randomization studies using summarized genetic association data. The package includes functions for generating forest plots and scatter plots at the single-nucleotide polymorphism and Mendelian randomization method levels, and for fitting multiple estimators in a unified workflow, including inverse-variance weighted estimation, Mendelian randomization Egger regression, the weighted median estimator, the robust adjusted profile score, Mendelian randomization pleiotropy residual sum and outlier, Mendelian randomization with the genotype recoding invariance property, and a Bayesian horseshoe method. Related methods are described by Burgess (2013) <doi:10.1002/gepi.21758>, Bowden (2015) <doi:10.1093/ije/dyv080>, Bowden (2016) <doi:10.1002/gepi.21965>, Zhao (2020) <doi:10.1214/19-AOS1866>, Verbanck (2018) <doi:10.1038/s41588-018-0099-7>, Dudbridge (2025) <doi:10.1371/journal.pgen.1011967>, and Grant and Burgess (2024) <doi:10.1016/j.ajhg.2023.12.002>. Related open-source software includes 'TwoSampleMR' <https://github.com/MRCIEU/TwoSampleMR>, 'mr.raps' <https://github.com/qingyuanzhao/mr.raps>, 'MR-PRESSO' <https://github.com/rondolab/MR-PRESSO>, and 'MR-Horse' <https://github.com/aj-grant/mrhorse>.
Authors:
autoMR_1.1.2.tar.gz
autoMR_1.1.2.zip(r-4.7)autoMR_1.1.2.zip(r-4.6)autoMR_1.1.2.zip(r-4.5)
autoMR_1.1.2.tgz(r-4.6-any)autoMR_1.1.2.tgz(r-4.5-any)
autoMR_1.1.2.tar.gz(r-4.7-any)autoMR_1.1.2.tar.gz(r-4.6-any)
autoMR_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
autoMR/json (API)
| # Install 'autoMR' in R: |
| install.packages('autoMR', repos = c('https://kelinzhong.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kelinzhong/automr/issues
- jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
- c++– GNU Standard C++ Library v3
- fi_49item - Frailty Index Dataset
- fried_frailty - Fried Frailty Phenotype Dataset
- merged_data - Merged Frailty Index Dataset
Last updated from:87844dd8e7. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 187 | ||
| source / vignettes | OK | 206 | ||
| linux-release-x86_64 | OK | 181 | ||
| macos-release-arm64 | OK | 175 | ||
| macos-oldrel-arm64 | OK | 193 | ||
| windows-devel | OK | 144 | ||
| windows-release | OK | 126 | ||
| windows-oldrel | OK | 120 | ||
| wasm-release | OK | 126 |
Exports:export_forest_plotsexport_scatter_plotsformat_mr_inputGWAS_forestharmonize_mr_dataMR_forestplot_mr_scatterrun_mr_analysisshowplot
Dependencies:abindarrangementsaskpassbase64encbootbslibcachemclicodacodetoolscpp11crosstalkcurldata.tableDEoptimRdigestdplyrevaluatefarverfastmapfontawesomeforeachfsgenericsggplot2glmnetgluegmpgtablehighrhtmltoolshtmlwidgetshttrisobanditeratorsiterpcjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixMatrixModelsmemoiseMendelianRandomizationmimenortestnumDerivopensslotelpillarpkgconfigplotlypromisespurrrquantregR2jagsR2WinBUGSR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenrjagsrjsonrlangrmarkdownrobustbaseS7sassscalesshapeSparseMstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Export MR Forest Plots to Disk | export_forest_plots |
| Export MR Scatter Plots to Disk | export_scatter_plots |
| Frailty Index Dataset (49-items) | fi_49item |
| Format vectors into a Mendelian Randomization input data frame | format_mr_input |
| Fried Frailty Phenotype Dataset | fried_frailty |
| Generate Instrument-level Forest Plots for Mendelian Randomization | GWAS_forest |
| Harmonize exposure and outcome SNP data | harmonize_mr_data |
| Merged Frailty Index Dataset (49-items and fried frailty) | merged_data |
| Generate Forest Plots across Multiple MR Methods | MR_forest |
| Plot MR Scatter Plots for Multiple Outcomes and Exposures | plot_mr_scatter |
| Run MR Analysis for Multiple Outcomes | run_mr_analysis |
| Display MR Plots on Screen | showplot |
