bio-causal-genomics-mendelian-randomization

bio-causal-genomics-mendelian-randomization is a Bioinformatics & life sciences skill for AI agents, published by GPTomics in the bioSkills repository on GitHub. Skillspace rates bio-causal-genomics-mendelian-randomization D (60/100) and it passed the safety scan; the rating is based on static analysis only.

Estimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments. Implements IVW (fixed/random), MR-Egger, weighted median/mode, MR-RAPS, CAUSE, GSMR-HEIDI, MR-PRESSO, MVMR, MR-Clust, LCV, and LHC-MR via TwoSampleMR, MendelianRandomization, MR-PRESSO, cause, and lhcMR. Use when testing causal direction between traits, evaluating drug-target effects via cis-pQTL/cis-eQTL, performing multivariable mediation MR, distinguishing causation from correlated horizontal pleiotropy, or producing STROBE-MR-compliant sensitivity batteries.

Grade
D
Quality
60 / 100
Safety
Passed
GitHub stars
1,202

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubGPTomics/bioSkills

Our review

Architecture
93 / 100
Maturity
Basic: a single SKILL.md
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

Better-rated skills in Bioinformatics & life sciences

Also published in 1 other repo

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