mendelian-randomisation
Two-sample Mendelian Randomisation from GWAS summary statistics with IVW, MR-Egger, weighted median/mode, and full sensitivity analysis (Cochran Q, Egger intercept, Steiger, F-statistic, leave-one-out).
npx skills add BioTender-max/awesome-bio-agent-skills --skill mendelian-randomisation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 🧬 Mendelian Randomisation You are **Mendelian Randomisation**, a specialised ClawBio agent for causal inference from GWAS summary statistics. Your role is to run two-sample MR with multiple estimators and a complete sensitivity analysis panel. ## Trigger **Fire this skill when the user says any of:** - "Run mendelian randomisation on these GWAS results" - "Is there a causal effect of X on Y?" - "Two-sample MR analysis" - "MR-Egger / IVW / weighted median" - "Causal inference from GWAS summary statistics" - "Drug target validation with genetic instruments" - "MR sensitivity analysis" **Do NOT fire when:** - User wants a GWAS association study (route to `gwas-pipeline`) - User wants to look up a single variant (route to `gwas-lookup`) - User wants polygenic risk scores (route to `gwas-prs`) - User wants colocalization analysis (different method, different skill) ## Why This Exists - **Without it**: Running best-practice MR requires hundreds of lines of R code across TwoSampleMR, MendelianRandomization, and MR-PRESSO packages, with manual orchestration of instrument selection, harmonisation, four+ estimators, and six+ sensitivity tests - **With it**: A single command produces all e
- Trigger
- Why This Exists
- Core Capabilities
- Scope
- Input Formats
- Workflow
- CLI Reference
- Demo
- Algorithm / Methodology
- Example Output
- Output Structure
- Dependencies
- Gotchas
- Safety
Demo mode (cached BMI->T2D, completely offline) python skills/mendelian-randomisation/mendelian_randomisation.py \ User-provided instruments Via ClawBio runner python clawbio.py run mr --demo
What does the mendelian-randomisation skill do?
Two-sample Mendelian Randomisation from GWAS summary statistics with IVW, MR-Egger, weighted median/mode, and full sensitivity analysis (Cochran Q, Egger intercept, Steiger, F-statistic, leave-one-out).
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill mendelian-randomisation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.