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MRZero (version 0.2.0)

Diet Mendelian Randomization

Description

Encodes several methods for performing Mendelian randomization analyses with summarized data. Similar to the 'MendelianRandomization' package, but with fewer bells and whistles, and less frequent updates. As described in Yavorska (2017) and Broadbent (2020) .

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Version

Install

install.packages('MRZero')

Monthly Downloads

197

Version

0.2.0

License

GPL-2 | GPL-3

Maintainer

Stephen Burgess

Last Published

April 14th, 2024

Functions in MRZero (0.2.0)

MVIVWME-class

MVIVWME Class
cML_SdTheta

Standard Error of Estimated Theta
MRMBE-class

MRMBE Class
MRMVInput-class

MRMVInput Class
WeightedMedian-class

WeightedMedian Class
coursedata

Course data
decimals

Produce nicely rounded numbers
calcium

Data on effect of calcium on fasting glucose (correlated variants)
MVLasso-class

MRMVLasso class
ci_normal

Calculate confidence intervals using the normal distribution
ldlc

Data on lipid effects on coronary artery disease (uncorrelated variants)
MRHetPen-class

MRHetPen Class
mr_clr

Conditional likelihood ratio (CLR) method
MVMRcML-class

MVMRcML Class
MVMedian-class

MRMVMedian class
PIVW-class

PIVW Class
mr_funnel

Draw a funnel plot of variant-specific estimates
mr_conmix

Contamination mixture method
PCGMM-class

PCGMM Class
mr_forest

Draw a forest plot of causal estimates
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)
loglikelihoodrhocorrel

Calculates log-likelihood with correlation from sample overlap
MVGMM-class

MVGMM Class
mbe_boot

Mode-based estimate (Hartwig) bootstrap function
mr_maxlik

Maximum-likelihood method
MVIVW-class

MVIVW Class
condFstat

Calculates conditional F-statistic for each risk factor using summarized data
MaxLik-class

MaxLik Class
MVPCGMM-class

MVPCGMM Class
mr_mbe

Mode-based method of Hartwig
mbe_est

Mode-based estimate (Hartwig) estimation function
ci_t

Calculate confidence intervals using the t-distribution
mr_loo

Leave-one-out estimates
mr_mvpcgmm

Multivariable principal components generalized method of moments (PC-GMM) method
mr_lasso

MR-Lasso method
cML_estimate

Estimate with Regular Likelihood
cML_estimate_random

Estimate with Regular Likelihood Using Multiple Random Start Points
getter

Applies method $ to different classes
egger.bounds

Calculates confidence intervals for the MR-Egger method
mr_egger

MR-Egger method
mr_divw

Debiased inverse-variance weighted method
mr_mvlasso

Multivariable MR-Lasso method
mr_mvgmm

Multivariable generalized method of moments (GMM) method
mr_mvmedian

Multivariable median-based method
mr_cML

Constrained maximum likelihood (cML) method
mr_allmethods

Mendelian randomization estimation using all methods
values

Applies method values() to different output classes
mr_ivw

Inverse-variance weighted method
mr_input

Inputting and formatting data for use in causal estimation
mr_mvegger

Multivariable MR-Egger method
weighted.median

Weighted median function
mr_median

Median-based method
mr_pcgmm

Univariable principal components generalized method of moments (PC-GMM) method
mr_mvivw

Multivariable inverse-variance weighted method
r.weights.delta

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

Capitalize a word
mr_mvivwme

Multivariable inverse-variance weighted method with measurement error
penalised.weights.delta

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

Inputting and formatting data for use in causal estimation
mr_plot

Draw a scatter plot of the genetic associations and/or causal estimates
mr_pivw

Penalized inverse-variance weighted method
mv_norm

Sampling from multivariate normal distribution
penalised.weights

Calculates p-values for penalization of weights
r.weights

Calculates p-values for penalization of weights
weighted.median.boot.se

Weighted median standard error function
MRConMix-class

MRConMix Class
BF_dist

Generate bootstrap samples for the bootstrapping Fieller's confidence interval of the penalized inverse-variance weighted (pIVW) method
DIVW-class

DIVW Class
MRInput-class

MRInput Class
MRLasso-class

MRLasso class
IVW-class

IVW Class
CLR-class

CLR Class
MRAll-class

MRAll Class
Egger-class

Egger Class
MRcML-class

MRcML Class
MVEgger-class

MVEgger Class