AgenticGenomics: pharmacogenomics benchmark dataset for "Trustworthy agentic genomics through versioned skill libraries"

AgenticGenomics benchmark dataset. Controlled three-arm comparison of nine frontier large language models on pharmacogenomic interpretation: Claude Opus 4, Claude Sonnet 4, GPT-5.2, GPT-4.1, o3, o4-mini, Gemini 2.5 Flash, DeepSeek V3 and Mistral Large 2, evaluated on 110 CPIC Level A cases across three population contexts (European, admixed Latin American, East African) under three conditions (free-prompted; retrieval-augmented from the CPIC guideline corpus; constrained by a versioned SKILL.md-format specification executed as a contract), three replicates per cell, 26,730 evaluations. The archive contains raw model responses, baseline and clinical-equivalence rescorer outputs, the locked merged three-arm dataset (26,730 rows), the forward and reverse adversarial scrambled-specification experiments, the (gene, drug)-keyed chunking control, the drug-recommendation regression classification, and figure-input tables. Records are scored on phenotype identification (A1), drug recommendation (A2) and lethal-class safety action (A3). All data derive from public CPIC Level A guidelines and PharmGKB annotations; genotypes are synthetic canonical cases; no patient data and no new sequencing data are included. Analysis code: https://github.com/manuelcorpas/24-AGENTIC-PGX-BENCHMARK (commit dc2c849e). Companion to the Perspective "Agentic Genomics: From Pipeline Automation to Autonomous Validation" (under review at Cell Genomics). Version 1.1.0 adds the three-population real-genome validation arm: agent interpretation of star-allele diplotypes called by a single deterministic caller (PyPGx, GRCh37) from a European family (Corpas family), the Peruvian Genome Project (Latin American) and the Uganda Genome Resource (East African, controlled access; no genotypes redistributed). Adds the aggregate per-population result table, the cross-population figure, and a complete snapshot of the analysis repository at commit a6a8e9d. No individual-level genotypes are included.