Data & ReproStatistics & Data AnalysisFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction

bio-clinical-databases-polygenic-risk

Maintainer FreedomIntelligence · Last updated April 1, 2026

Calculate polygenic risk scores using PRSice-2, LDpred2, or PRS-CS from GWAS summary statistics. Use when predicting disease risk from genome-wide genetic variants.

OpenClawNanoClawAnalysisReproductionbio-clinical-databases-polygenic-risk🧬 bioinformatics (gptomics bio-* suite)bioinformatics — clinical databases & variant analysiscalculate

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-clinical-databases-polygenic-risk

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

CLI: PRSice_linux --base gwas.txt --target genotypes --out prs_results.
R: bigsnpr::snp_ldpred2_auto() for LDpred2 Bayesian PRS.
Calculate polygenic risk scores for my cohort" → Compute genome-wide risk scores from GWAS summary statistics and individual genotypes to predict disease susceptibility. CLI: PRSice_linux --base gwas.txt --target genotypes --out prs_results R: bigsnpr::snp_ldpred2_auto() for LDpred2 Bayesian PRS.
PRSice_linux \ --base gwas_summary.txt \ --target genotypes \ --snp SNP \ --chr CHR \ --bp BP \ --A1 A1 \ --A2 A2 \ --pvalue P \ --beta BETA \ --clump-kb 250 \ --clump-r2 0.1 \ --bar-levels 5e-8,1e-5,1e-3,0.01,0.05,0.1,0.5,1 \ --fastscore \ --all-score \ --out prs_results.

Source Doc

Excerpt From SKILL.md

PRSice-2 Workflow

Goal: Calculate polygenic risk scores from GWAS summary statistics using clumping and thresholding.

Approach: Run PRSice-2 with GWAS summary stats and target genotypes, applying LD clumping and multiple p-value thresholds.

LDpred2 (R)

Goal: Compute Bayesian polygenic risk scores with automatic hyperparameter tuning via LDpred2-auto.

Approach: Load genotypes with bigsnpr, match GWAS variants, compute LD matrix, estimate heritability with LD score regression, then run LDpred2-auto.