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MendelianRandomization (version 0.7.0)

Mendelian Randomization Package

Description

Encodes several methods for performing Mendelian randomization analyses with summarized data. Summarized data on genetic associations with the exposure and with the outcome can be obtained from large consortia. These data can be used for obtaining causal estimates using instrumental variable methods.

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Version

Install

install.packages('MendelianRandomization')

Monthly Downloads

4,276

Version

0.7.0

License

GPL-2 | GPL-3

Maintainer

Stephen Burgess

Last Published

January 9th, 2023

Functions in MendelianRandomization (0.7.0)

MVMedian-class

MRMVMedian class
MVEgger-class

MVEgger Class
cML_estimate

Estimate with Regular Likelihood
MRcML-class

MRcML Class
WeightedMedian-class

WeightedMedian Class
cML_SdTheta

Standard Error of Estimated Theta
cML_estimate_random

Estimate with Regular Likelihood Using Multiple Random Start Points
MVIVW-class

MVIVW Class
het.weight

Heterogeneity-penalized weight function
MVLasso-class

MRMVLasso class
MaxLik-class

MaxLik Class
calcium

Data on effect of calcium on fasting glucose (correlated variants)
ci_t

Calculate confidence intervals using the t-distribution
extract.pheno.csv

Extract summarized data from a PhenoScanner .csv file (legacy)
egger.bounds

Calculates confidence intervals for the MR-Egger method
decimals

Produce nicely rounded numbers
ldlc

Data on lipid effects on coronary artery disease (uncorrelated variants)
coursedata

Course data
ci_normal

Calculate confidence intervals using the normal distribution
getter

Applies method $ to different classes
mr_divw

Debiased inverse-variance weighted method
mr_conmix

Contamination mixture method
mbe_est

Mode-based estimate (Hartwig) estimation function
loglikelihood

Calculates log-likelihood with uncorrelated variants in two-sample setting (no correlation from sample overlap)
loglikelihoodcorrel

Calculates log-likelihood with correlated variants in two-sample setting (no correlation from sample overlap)
model.prior

Prior weight function
mr_allmethods

Mendelian randomization estimation using all methods
mr_cML

Constrained maximum likelihood (cML) method
mbe_boot

Mode-based estimate (Hartwig) bootstrap function
loglikelihoodrhocorrel

Calculates log-likelihood with correlation from sample overlap
mr_funnel

Draw a funnel plot of variant-specific estimates
mr_egger

MR-Egger method
mr_maxlik

Maximum-likelihood method
mr_hetpen

Heterogeneity-penalized method
mr_input

Inputting and formatting data for use in causal estimation
mr_ivw

Inverse-variance weighted method
mr_forest

Draw a forest plot of causal estimates
mr_mbe

Mode-based method of Hartwig
mr_lasso

MR-Lasso method
mr_loo

Leave-one-out estimates
mr_mvinput

Inputting and formatting data for use in causal estimation
mr_mvivw

Multivariable inverse-variance weighted method
mr_mvmedian

Multivariable median-based method
mr_mvlasso

Multivariable MR-Lasso method
penalised.weights.delta

Calculates p-values for penalization of weights with second-order weights
pheno_input

Extract summarized data from PhenoScanner
mr_plot

Draw a scatter plot of the genetic associations and/or causal estimates
penalised.weights

Calculates p-values for penalization of weights
weighted.median

Weighted median function
values

Applies method values() to different output classes
mr_mvegger

Multivariable MR-Egger method
mr_median

Median-based method
r.weights.delta

Calculates p-values for penalization of weights with second-order weights
r.weights

Calculates p-values for penalization of weights
phenoscanner

PhenoScanner
simpleCap

Capitalize a word
weighted.median.boot.se

Weighted median standard error function
MRMBE-class

MRMBE Class
MRInput-class

MRInput Class
MRConMix-class

MRConMix Class
IVW-class

IVW Class
MRMVInput-class

MRMVInput Class
MRHetPen-class

MRHetPen Class
MRAll-class

MRAll Class
DIVW-class

DIVW Class
MRLasso-class

MRLasso class
Egger-class

Egger Class