Search the PGS Catalog for polygenic scores by free text.

Case-insensitive substring match across PGS ID, score name, reported trait, and EFO trait. Optionally filter to a genome build (GRCh37 / GRCh38, harmonized cross-build scores included). Returns up to limit matches with their key metadata.

Get cleaned metadata for a single PGS score by its ID (e.g. 'PGS000001').

Look up the best evaluation performance for a score (largest sample, EUR-preferred).

Returns parsed effect sizes (OR/HR/Beta) and classification metrics (AUROC/C-index) plus pre-formatted display strings.

Search the PGS Catalog REST API for traits by term (e.g. 'type 2 diabetes').

Fetch a trait by EFO ID (e.g. 'EFO_0001645') with its associated PGS IDs.

Normalize a VCF to a quality-filtered genotype Parquet (background task).

Strips the chr prefix, renames id→rsid, computes genotype from GT, applies optional quality filters (FILTER allow-list, min DP, min QUAL), and writes zstd-compressed Parquet. The output is a drop-in genotype source for compute_prs / compute_prs_batch (pass it as genotypes_path), so a VCF is normalized once and reused across many scores.

Runs as a real MCP background task: the client gets a task id immediately and polls for the result. Normalization is the slow step (seconds to minutes depending on VCF size).

Compute a polygenic risk score for one VCF against one PGS score.

Downloads the harmonized scoring file (cached) and scores the genotypes. Pass genotypes_path to reuse a normalized Parquet from normalize_vcf (avoids re-reading the VCF); otherwise the VCF is read directly. Returns the score, match rate, variant counts, trait, and (when data permits) a theoretical percentile.

Estimate the population percentile (0-100) for a computed PRS value.

Uses the 3-tier fallback: precomputed reference-panel distributions (best), then a theoretical distribution, then an AUROC approximation. superpopulation is a 1000G code (AFR/AMR/EAS/EUR/SAS).

Estimate absolute disease risk from a PRS z-score and population prevalence.

Joins the score's trait to prevalence + effect-size data. z_score is the PRS in standard deviations from the population mean. Raises if the required prevalence / effect-size data is unavailable for this score.

Classify and interpret a PRS result's quality (pure logic — no I/O).

match_rate is the fraction of scoring variants matched (0-1). Returns a quality label/color and a human-readable interpretation combining match rate, AUROC, and (optionally) the result percentile.