How does this skill handle horizontal pleiotropy?

It provides built-in workflows for the MR-Egger intercept test, Cochran’s Q heterogeneity test, and MR-PRESSO global tests to detect and correct for pleiotropy.

Is it compatible with the IEU Open GWAS database?

Yes, it includes automated scripts for extracting instruments and outcome data directly from the IEU Open GWAS Project using unique GWAS IDs.

Which R packages does this skill support?

The skill supports leading libraries including TwoSampleMR, MendelianRandomization, MRPRESSO, RadialMR, mr.raps, and CAUSE.

Does it calculate instrument strength?

Yes, the skill includes functions to calculate F-statistics for each instrument to ensure they meet the recommended threshold (F > 10) for robust inference.

Can I perform multivariable Mendelian Randomization?

Yes, it includes specific implementation patterns for Multivariable MR (MVMR) to account for multiple related exposures simultaneously.

Mendelian Randomization in R

Name: Mendelian Randomization in R
Author: choxos

bychoxos

0•

데이터 과학 및 ML

Performs causal inference using genetic variants as instrumental variables through comprehensive R-based Mendelian Randomization workflows.

This skill provides a standardized framework for conducting Mendelian Randomization (MR) analyses within R, enabling researchers to estimate causal effects between exposures and outcomes using summary-level GWAS data. It streamlines the entire pipeline—from instrument selection and harmonization to robust sensitivity analyses like MR-Egger, MR-PRESSO, and multivariable MR. By integrating industry-standard packages like TwoSampleMR and MendelianRandomization, it helps biostatisticians and epidemiologists implement best practices for robust causal inference while identifying potential biases such as horizontal pleiotropy and weak instrument effects.

주요 기능

01Advanced Multivariable MR (MVMR) and MR-PRESSO for outlier detection and correction.

02Robust sensitivity testing including Cochran’s Q, MR-Egger intercept, and Leave-One-Out analysis.

030 GitHub stars

04Automated instrument selection and LD clumping via IEU Open GWAS database integration.

05Comprehensive Two-Sample MR using IVW, MR-Egger, and weighted median methods.

06Publication-ready visualizations including scatter, forest, funnel, and radial MR plots.

사용 사례

01Identifying and correcting for horizontal pleiotropy in genetic epidemiology studies.

02Conducting bidirectional MR to investigate potential reverse causation between phenotypes.

03Estimating the causal effect of clinical biomarkers or risk factors on complex disease outcomes.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add choxos/biostatagent mendelian-randomization

For use in Claude.ai and ChatGPT

주요 기능

01Advanced Multivariable MR (MVMR) and MR-PRESSO for outlier detection and correction.

02Robust sensitivity testing including Cochran’s Q, MR-Egger intercept, and Leave-One-Out analysis.

030 GitHub stars

04Automated instrument selection and LD clumping via IEU Open GWAS database integration.

05Comprehensive Two-Sample MR using IVW, MR-Egger, and weighted median methods.

06Publication-ready visualizations including scatter, forest, funnel, and radial MR plots.

사용 사례

01Identifying and correcting for horizontal pleiotropy in genetic epidemiology studies.

02Conducting bidirectional MR to investigate potential reverse causation between phenotypes.

03Estimating the causal effect of clinical biomarkers or risk factors on complex disease outcomes.