PrimeKG Knowledge Graph Skill

Overview

PrimeKG (Chandak, Huang & Zitnik, Scientific Data 2023; mims-harvard/PrimeKG) is a precision medicine knowledge graph integrating 20 primary resources. It contains 129,375 nodes and 4,050,249 edges across 30 edge types and 10 node types, including drug-target, disease-gene, and disease-phenotype associations.

Key capabilities:

• Search for nodes (genes, proteins, drugs, diseases, phenotypes)
• Retrieve direct neighbors (associated entities and clinical evidence)
• Analyze local disease context (related genes, drugs, phenotypes)
• Identify drug-disease paths (potential repurposing opportunities)

Data access: Programmatic access via scripts/query_primekg.py. Point the loader at the kg.csv released on Harvard Dataverse via the PRIMEKG_DATA_PATH environment variable (it defaults to ../data/kg.csv relative to the script). All functions operate on the x_*/y_*/relation/display_relation columns of kg.csv.

When to Use This Skill

This skill should be used when: