# Bio Causal Genomics Mediation Analysis

Decompose genetic effects into direct and indirect paths through mediating variables...

- Repository: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills (3090 stars)
- Category: Testing
- License: see repository
- Last updated: 2026-07-21
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-causal-genomics-mediation-analysis -g -a claude-code -y`
Codex: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-causal-genomics-mediation-analysis -g -a codex -y`
Cursor: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-causal-genomics-mediation-analysis -g -a cursor -y`
Gemini CLI: `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-causal-genomics-mediation-analysis -g -a gemini-cli -y`

## Description

Decompose genetic effects into direct and indirect paths through mediating variables using the mediation R package. Tests whether gene expression, methylation, or other molecular phenotypes mediate the effect of genetic variants on disease. Use when testing whether a molecular phenotype mediates the genotype-to-phenotype relationship.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## Version Compatibility

Reference examples tested with: R stats (base), ggplot2 3.5+

Before using code patterns, verify installed versions match. If versions differ:
- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# Mediation Analysis

**"Test whether gene expression mediates the effect of this variant on disease"** → Decompose the total genetic effect into direct and indirect (mediated) paths through a molecular phenotype, estimating ACME, ADE, and proportion mediated with bootstrap confidence intervals.
- R: `mediation::mediate()` for causal mediation analysis

## Framework

Causal mediation decomposes the total effect of a treatment (genotype) on an outcome
(phenotype) into:

- **ACME** (Average Causal Mediation Effect) - Indirect effect through the mediator
- **ADE** (Average Direct Effect) - Direct effect not through the mediator
- **Total effect** = ACME + ADE
- **Proportion mediated** = ACME / Total effect

Typical genomic applications:
- SNP -> gene expression (mediator) -> disease
- SNP -> DNA methylation (mediator) -> gene expression
- SNP -> protein levels (mediator) -> clinical outcome

## Basic Mediation with the mediation Package

**Goal:** Decompose a genetic effect into direct and indirect (mediated) paths through a molecular phenotype.

**Approach:** Fit separate models for mediator and outcome, then run mediate() with bootstrap to estimate ACME (indirect), ADE (direct), and proportion mediated.

```r
library(mediation)

# --- Step 1: Fit mediator model ---
# How does the treatment (genotype) affect the mediator (expression)?
mediator_model <- lm(expression ~ genotype + age + sex + pc1 + pc2, data = dat)

The rest: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/blob/HEAD/skills/bio-causal-genomics-mediation-analysis/SKILL.md