Agent skill

plink2-gwas-analysis

GWAS and population genetics tool. Processes PLINK (.bed/.bim/.fam), VCF, and BGEN; runs QC (MAF, HWE, missingness), IBD estimation, PCA, and linear/logistic regression GWAS. Outputs Manhattan-ready summary stats. Use regenie or SAIGE for biobanks (>100k samples) needing mixed models.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill plink2-gwas-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 12 KB
Bundled scripts: none
Path: skills/sciagent/plink2-gwas-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 144
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# PLINK2 — GWAS and Population Genetics ## Overview PLINK2 is the high-performance successor to PLINK 1.9, designed for genome-wide association studies (GWAS) and population genetics analysis on large cohorts. It processes genotype data in PLINK binary format (.bed/.bim/.fam), VCF, and BGEN formats — performing sample and variant quality control (QC), kinship estimation, principal component analysis (PCA), and linear/logistic regression association testing. PLINK2 is 10–100× faster than PLINK 1.9 on most tasks due to multithreading and optimized I/O. Output files are compatible with downstream visualization (Manhattan/QQ plots) and meta-analysis tools. ## When to Use - Running GWAS on a case-control or quantitative trait cohort after genotyping array QC - Performing sample QC: missingness, heterozygosity outliers, sex check, cryptic relatedness - Computing genome-wide LD pruning for PCA or relatedness estimation - Running PCA on genotype data to identify population stratification - Converting between PLINK binary, VCF, and BGEN formats - Filtering variants by MAF, HWE, missingness, or INFO score in VCF/imputed data - Use **regenie** or **SAIGE** instead for biobank-scale GWAS (>100

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. Prerequisites
  4. Quick Start
  5. Workflow
  6. Step 1: Convert VCF/Imputed Data to PLINK Binary Format
  7. Step 2: Sample QC — Missingness and Heterozygosity
  8. Step 3: Variant QC — MAF, HWE, and INFO Score Filtering
  9. Step 4: LD Pruning and PCA for Population Stratification
  10. Step 5: Run GWAS Association Analysis
  11. Step 6: Plot Manhattan and QQ Plots
  12. Key Parameters
  13. Common Recipes
  14. Recipe 1: Relatedness QC and Remove One from Each Related Pair
Commands it runs
Skip install if already present
if command -v plink2 >/dev/null 2>&1; then
echo "plink2 already installed: $(plink2 --version)"
else
wget https://s3.amazonaws.com/plink2-assets/alpha6/plink2_linux_avx2_20241112.zip
unzip plink2_linux_avx2_20241112.zip
chmod +x plink2
export PATH="$PWD:$PATH"
plink2 --version
fi
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About this skill
What does the plink2-gwas-analysis skill do?

GWAS and population genetics tool. Processes PLINK (.bed/.bim/.fam), VCF, and BGEN; runs QC (MAF, HWE, missingness), IBD estimation, PCA, and linear/logistic regression GWAS. Outputs Manhattan-ready summary stats. Use regenie or SAIGE for biobanks (>100k samples) needing mixed models.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill plink2-gwas-analysis --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 144 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.

Keep going