Package 'MR.CUE'

Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology

Description

Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology.

Details

The DESCRIPTION file:

Type:	Package
Package:	MR.CUE
Title:	Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology
Version:	1.0
Authors@R:	person("Qing", "Cheng", , "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5144-4515"))
Description:	Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology.
License:	GPL (>= 3)
Imports:	Rcpp (>= 1.0.8.3), ggplot2, mvtnorm, stats, utils
LinkingTo:	BH, Rcpp, RcppArmadillo, RcppDist
Encoding:	UTF-8
Repository:	https://mrcieu.r-universe.dev
Date/Publication:	2026-03-16 06:57:33 UTC
RemoteUrl:	https://github.com/remlapmot/MR.CUE
RemoteRef:	suggestions
RemoteSha:	eafb841d9ab1437237cbe1ac20519a661a545171
Author:	Qing Cheng [aut, cre] (ORCID: <https://orcid.org/0000-0001-5144-4515>)
Maintainer:	Qing Cheng <[email protected]>

Index of help topics:

EstRho                  Estimate the Correlation Parameter Rho
EstRhofun               Estimate Rho from Summary Statistic Files
genRawGeno              Generate Raw Genotype Data
genSumStat              Generate Summary Statistics for Simulation
MR.CUE-package          Mendelian randomization accounting for complex
                        correlated horizontal pleiotropy while
                        elucidating shared genetic etiology
MRCUE                   Mendelian Randomization with Correlated
                        pleiotropy Using Empirical priors
MRCUEIndep              MR-CUE for Independent Instruments
MRCUESim                MR-CUE with Simple LD Block Structure
ReadSummaryStat         Read and Match Summary Statistics
RemoveMHCCfun           Remove MHC Region SNPs and Apply QC Filters
summaryQC               Quality Control for Summary Statistics
traceplot               Trace Plot of MCMC Samples

The main user-facing functions are MRCUE, MRCUEIndep, and MRCUESim for Mendelian randomization analysis, and ReadSummaryStat and EstRho for data preparation.

Author(s)

Qing Cheng [aut, cre] (ORCID: <https://orcid.org/0000-0001-5144-4515>)

Maintainer: Qing Cheng <[email protected]>

References

Cheng, Q. et al. (2022) Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology. Nature Communications 13, 6490.

---

Estimate the Correlation Parameter Rho

Description

Estimates the correlation parameter rho between exposure and outcome using matched summary statistics and LD clumping.

Usage

EstRho(fileexp, fileout, filepan, snpinfo, ld_r2_thresh, lambad, pth)

Arguments

fileexp	Path to exposure summary statistics file.
fileout	Path to outcome summary statistics file.
filepan	Path to reference panel file.
snpinfo	Path to SNP info file.
ld_r2_thresh	LD r-squared threshold for clumping.
lambad	Regularisation parameter for LD matrix estimation.
pth	P-value threshold for instrument selection.

Value

Estimated rho value.

---

Estimate Rho from Summary Statistic Files

Description

Estimates the correlation parameter rho between exposure and outcome from summary statistic files with LD clumping.

Usage

EstRhofun(fileexposure, fileoutcome, stringname3, ld_r2_thresh, lam, pth,
          block_file)

Arguments

fileexposure	Path to exposure summary statistics file.
fileoutcome	Path to outcome summary statistics file.
stringname3	Path to reference panel file prefix.
ld_r2_thresh	LD r-squared threshold for clumping.
lam	Regularisation parameter for LD matrix estimation.
pth	P-value threshold for instrument selection.
block_file	Path to the LD block definition file.

Value

Estimated rho value.

---

Generate Raw Genotype Data

Description

Simulates raw genotype data with a specified LD structure for use in simulation studies.

Usage

genRawGeno(maf, L, M, rho, n)

Arguments

maf	Numeric vector of minor allele frequencies.
L	Number of LD blocks.
M	Number of SNPs per block.
rho	Correlation parameter controlling LD decay within blocks.
n	Sample size.

Value

A matrix of simulated genotypes (n rows, L*M columns).

---

Generate Summary Statistics for Simulation

Description

Simulates GWAS summary statistics with pleiotropy and genetic effects for use in simulation studies.

Usage

genSumStat(x12, n1, n2, M, L, b1, rho_ag, Alrate, h2a, h2t, h2g)

Arguments

x12	Simulated genotype matrix from genRawGeno.
n1	Sample size for exposure.
n2	Sample size for outcome.
M	Number of SNPs per block.
L	Number of LD blocks.
b1	True causal effect.
rho_ag	Correlation between pleiotropic effects.
Alrate	Proportion of pleiotropic SNPs.
h2a	Heritability of pleiotropic effects.
h2t	Heritability of total effects.
h2g	Heritability explained by genetic instruments.

Value

A list of simulated summary statistics.

---

Mendelian Randomization with Correlated pleiotropy Using Empirical priors

Description

Performs MR-CUE analysis using LD block structure for correlated horizontal pleiotropy modelling.

Usage

MRCUE(F4gammah, F4Gammah, F4se1, F4se2, F4Rblock, rho, coreNum, opts = NULL)

Arguments

F4gammah	Numeric vector of SNP effects on exposure.
F4Gammah	Numeric vector of SNP effects on outcome.
F4se1	Numeric vector of standard errors for exposure effects.
F4se2	Numeric vector of standard errors for outcome effects.
F4Rblock	List of LD correlation matrices by block.
rho	Estimated correlation parameter.
coreNum	Number of CPU cores to use.
opts	Optional list of algorithm parameters.

Value

A list of posterior samples and summary statistics.

References

Cheng, Q. et al. (2022) Nature Communications 13, 6490.

---

MR-CUE for Independent Instruments

Description

Performs MR-CUE analysis assuming independent instruments (no LD).

Usage

MRCUEIndep(gammah, Gammah, se1, se2, rho, opts = NULL)

Arguments

gammah	Numeric vector of SNP effects on exposure.
Gammah	Numeric vector of SNP effects on outcome.
se1	Numeric vector of standard errors for exposure effects.
se2	Numeric vector of standard errors for outcome effects.
rho	Estimated correlation parameter.
opts	Optional list of algorithm parameters.

Value

A list of posterior samples and summary statistics.

References

Cheng, Q. et al. (2022) Nature Communications 13, 6490.

---

MR-CUE with Simple LD Block Structure

Description

Performs MR-CUE analysis with a simplified LD block representation.

Usage

MRCUESim(gammah, Gammah, se1, se2, rho, R, block_inf, coreNum, opts = NULL)

Arguments

gammah	Numeric vector of SNP effects on exposure.
Gammah	Numeric vector of SNP effects on outcome.
se1	Numeric vector of standard errors for exposure effects.
se2	Numeric vector of standard errors for outcome effects.
rho	Estimated correlation parameter.
R	LD correlation matrix.
block_inf	Block information matrix.
coreNum	Number of CPU cores to use.
opts	Optional list of algorithm parameters.

Value

A list of posterior samples and summary statistics.

References

Cheng, Q. et al. (2022) Nature Communications 13, 6490.

---

Read and Match Summary Statistics

Description

Reads exposure and outcome GWAS summary statistics, matches SNPs, and integrates a reference panel for LD calculation.

Usage

ReadSummaryStat(fileexp, fileout, filepan, snpinfo, pva_cutoff, lambad)

Arguments

fileexp	Path to exposure summary statistics file.
fileout	Path to outcome summary statistics file.
filepan	Path to reference panel file (plink binary format).
snpinfo	Path to SNP info file.
pva_cutoff	P-value cutoff for instrument selection.
lambad	Regularisation parameter for LD matrix estimation.

Value

A list of matched summary statistics and LD block information.

---

Remove MHC Region SNPs and Apply QC Filters

Description

Removes SNPs in the MHC region (chromosome 6) and applies chi-squared bounds for quality control.

Usage

RemoveMHCCfun(mhcstart, mhcend, bh1, bh2, s12, s22, bp, chr, rsname,
              xbound, ybound)

Arguments

mhcstart	Start position of MHC region (bp).
mhcend	End position of MHC region (bp).
bh1	Numeric vector of exposure effect estimates.
bh2	Numeric vector of outcome effect estimates.
s12	Numeric vector of exposure standard errors squared.
s22	Numeric vector of outcome standard errors squared.
bp	Numeric vector of SNP base pair positions.
chr	Numeric vector of chromosome numbers.
rsname	Character vector of SNP identifiers.
xbound	Chi-squared upper bound for exposure QC.
ybound	Chi-squared upper bound for outcome QC.

Value

A list of filtered summary statistics.

---

Quality Control for Summary Statistics

Description

Filters SNPs in the MHC region and applies chi-squared bounds for quality control of GWAS summary statistics.

Usage

summaryQC(mhcstart, mhcend, bh1, bh2, s12, s22, bp, chr, rsname, avbIndex,
          idx4panel, xbound, ybound)

Arguments

mhcstart	Start position of MHC region (bp).
mhcend	End position of MHC region (bp).
bh1	Numeric vector of exposure effect estimates.
bh2	Numeric vector of outcome effect estimates.
s12	Numeric vector of exposure standard errors squared.
s22	Numeric vector of outcome standard errors squared.
bp	Numeric vector of SNP base pair positions.
chr	Numeric vector of chromosome numbers.
rsname	Character vector of SNP identifiers.
avbIndex	Index of available SNPs.
idx4panel	Index of SNPs in the reference panel.
xbound	Chi-squared upper bound for exposure QC.
ybound	Chi-squared upper bound for outcome QC.

Value

A list of QC-filtered summary statistics.

---

Trace Plot of MCMC Samples

Description

Creates a trace plot of the posterior samples for the causal effect estimate from an MR-CUE analysis.

Usage

traceplot(bhatpoint)

Arguments

bhatpoint

Numeric vector of posterior samples for the causal effect.

Value

A ggplot2 object.

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