bio-clinical-databases-polygenic-risk

Version Compatibility

Reference examples tested with: LDpred2 1.14+, PRSice-2 2.3+, numpy 1.26+, scipy 1.12+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters
• CLI: <tool> --version then <tool> --help to confirm flags

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

Polygenic Risk Scores

"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-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.

Basic PRS Calculation

# PRSice-2 with clumping and thresholding
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

PRSice-2 with Covariates

PRSice_linux \
    --base gwas_summary.txt \
    --target genotypes \
    --pheno phenotype.txt \
    --cov covariates.txt \
    --cov-col @PC[1-10],Age,Sex \
    --binary-target T \
    --clump-kb 250 \
    --clump-r2 0.1 \
    --out prs_with_cov

GWAS Summary Statistics Format

SNP          CHR  BP        A1  A2  BETA    SE      P
rs12345      1    10000     A   G   0.05    0.01    1e-8
rs67890      1    20000     T   C   -0.03   0.02    0.001