All functions

add_metadata()

Add meta data to extracted data

add_rsq()

Estimate r-square of each association

allele_frequency()

Estimate allele frequency from SNP

available_outcomes()

Get list of studies with available GWAS summary statistics through API

clump_data()

Perform LD clumping on SNP data

combine_all_mrresults()

Combine all mr results

combine_data()

Combine data

contingency()

Obtain 2x2 contingency table from marginal parameters and odds ratio

convert_outcome_to_exposure()

Convert outcome data to exposure data

dat_to_MRInput()

Convert TwoSampleMR format to MendelianRandomization format

dat_to_RadialMR()

Convert dat to RadialMR format

default_parameters()

List of parameters for use with MR functions

directionality_test()

Perform MR Steiger test of directionality

effective_n()

Estimate the effective sample size in a case control study

enrichment()

Perform enrichment analysis

enrichment_method_list()

Get list of available p-value enrichment methods

estimate_trait_sd()

Estimate trait SD by obtaining beta estimates from z-scores and finding the ratio with original beta values

extract_instruments()

Find instruments for use in MR from the MR Base database

extract_outcome_data()

Supply the output from read_exposure_data and all the SNPs therein will be queried against the requested outcomes in remote database using API.

fishers_combined_test()

Fisher's combined test

forest_plot()

Forest plot for multiple exposures and multiple outcomes

forest_plot_1_to_many()

1-to-many forest plot

forest_plot_basic2()

A basic forest plot

format_1_to_many()

Format MR results for a 1-to-many forest plot

format_aries_mqtl()

Get data from methylation QTL results

format_data()

Read exposure or outcome data

format_gtex_eqtl()

Get data from eQTL catalog into correct format

format_gwas_catalog()

Get data selected from GWAS catalog into correct format

format_metab_qtls()

Get data from metabolomic QTL results

format_mr_results()

Format MR results for forest plot

format_proteomic_qtls()

Get data from proteomic QTL results

generate_odds_ratios()

Generate odds ratios

get_population_allele_frequency()

Estimate the allele frequency in population from case/control summary data

get_p_from_r2n()

Calculate p-value from rsq and sample size

get_r_from_bsen()

Estimate Rsq from beta, standard error and sample size

get_r_from_lor()

Estimate proportion of variance of liability explained by SNP in general population

get_r_from_pn()

Calculate variance explained from p vals and sample size

get_se()

Get SE from effect size and pval

harmonise_data()

Harmonise the alleles and effects between the exposure and outcome

harmonise_ld_dat()

Harmonise LD matrix against summary data

Isq()

I-square calculation

ldsc_h2()

Univariate LDSC

ldsc_rg()

Bivariate LDSC

ld_matrix()

Get LD matrix for list of SNPs

make_dat()

Convenient function to create a harmonised dataset

mr()

Perform all Mendelian randomization tests

mr_density_plot()

Density plot

mr_egger_regression()

Egger's regression for Mendelian randomization

mr_egger_regression_bootstrap()

Run bootstrap to generate standard errors for MR

mr_forest_plot()

Forest plot

mr_funnel_plot()

Funnel plot

mr_heterogeneity()

Get heterogeneity statistics

mr_ivw()

Inverse variance weighted regression

mr_ivw_fe()

Inverse variance weighted regression (fixed effects)

mr_ivw_mre()

Inverse variance weighted regression (multiplicative random effects model)

mr_ivw_radial()

Radial IVW analysis

mr_leaveoneout()

Leave one out sensitivity analysis

mr_leaveoneout_plot()

Plot results from leaveoneout analysis

mr_median()

MR median estimators

mr_meta_fixed()

Perform 2 sample IV using fixed effects meta analysis and delta method for standard errors

mr_meta_fixed_simple()

Perform 2 sample IV using simple standard error

mr_meta_random()

Perform 2 sample IV using random effects meta analysis and delta method for standard errors

mr_method_list()

Get list of available MR methods

mr_mode()

MR mode estimators

mr_moe()

Mixture of experts

mr_penalised_weighted_median()

Penalised weighted median MR

mr_pleiotropy_test()

Test for horizontal pleiotropy in MR analysis

mr_raps()

Robust adjusted profile score

mr_report()

Generate MR report

mr_rucker()

MR Rucker framework

mr_rucker_bootstrap()

Run rucker with bootstrap estimates

mr_rucker_cooksdistance()

MR Rucker with outliers automatically detected and removed

mr_rucker_jackknife()

Run rucker with jackknife estimates

mr_scatter_plot()

Create scatter plot with lines showing the causal estimate for different MR tests

mr_sign()

MR sign test

mr_simple_median()

Simple median method

mr_simple_mode()

MR simple mode estimator

mr_simple_mode_nome()

MR simple mode estimator (NOME)

mr_singlesnp()

Perform 2 sample MR on each SNP individually

mr_steiger()

MR Steiger test of directionality

mr_steiger2()

MR Steiger test of directionality

mr_two_sample_ml()

Maximum likelihood MR method

mr_uwr()

Unweighted regression

mr_wald_ratio()

Perform 2 sample IV using Wald ratio.

mr_weighted_median()

Weighted median method

mr_weighted_mode()

MR weighted mode estimator

mr_weighted_mode_nome()

MR weighted mode estimator (NOME)

mr_wrapper()

Perform full set of MR analyses

mv_basic()

Perform basic multivariable MR

mv_extract_exposures()

Extract exposure variables for multivariable MR

mv_extract_exposures_local()

Attempt to perform MVMR using local data

mv_harmonise_data()

Harmonise exposure and outcome for multivariable MR

mv_ivw()

Perform IVW multivariable MR

mv_lasso_feature_selection()

Apply LASSO feature selection to mvdat object

mv_multiple()

Perform IVW multivariable MR

mv_residual()

Perform basic multivariable MR

mv_subset()

Perform multivariable MR on subset of features

power_prune()

Power prune

read_exposure_data()

Read exposure data

read_outcome_data()

Read outcome data

run_mrmix()

Perform MRMix analysis on harmonised dat object

run_mr_presso()

Wrapper for MR-PRESSO

size.prune()

Size prune

sort_1_to_many()

Sort results for 1-to-many forest plot

split_exposure()

Split exposure column

split_outcome()

Split outcome column

standardise_units()

Try to standardise continuous traits to be in standard deviation units

steiger_filtering()

Steiger filtering function

steiger_sensitivity()

Evaluate the Steiger test's sensitivity to measurement error

subset_on_method()

Subset MR-results on method

trim()

Trim function to remove leading and trailing blank spaces

TwoSampleMR-package

TwoSampleMR: Two Sample MR functions and interface to MR Base database

weighted_median()

Weighted median method

weighted_median_bootstrap()

Calculate standard errors for weighted median method using bootstrap