Mendelian Randomization in R

关于

This skill equips Claude with specialized knowledge for conducting Mendelian Randomization (MR) studies within the R ecosystem. It provides standardized implementation patterns for instrument selection using GWAS databases, primary MR methods like IVW and MR-Egger, and rigorous sensitivity testing including pleiotropy assessment and MR-PRESSO. Whether performing two-sample MR, multivariable MR, or advanced causal analysis using methods like CAUSE, this skill ensures adherence to best practices and STROBE-MR reporting guidelines for high-quality epidemiological research.

主要功能

• Support for TwoSampleMR and MendelianRandomization package workflows.
• Advanced sensitivity analyses including MR-PRESSO outlier detection and Steiger filtering.
• Complex multivariable and bidirectional MR patterns for investigating interrelated exposures.
• 0 GitHub stars
• Publication-ready visualizations including scatter, forest, funnel, and radial plots.
• Automated instrument selection with LD clumping and F-statistic calculation for instrument strength.

使用场景

• Validating observational epidemiological findings against potential confounding factors using genetic instruments.
• Determining causal relationships between clinical biomarkers and disease outcomes using GWAS summary statistics.
• Identifying pleiotropic effects and influential outliers in genetic data to improve the robustness of causal estimates.