feat: add PrimeKG Precision Medicine Knowledge Graph skill

scientific-skills/primekg/SKILL.md

@@ -0,0 +1,97 @@
+---
+name: primekg
+description: Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological data including genes, drugs, diseases, phenotypes, and more.
+license: Unknown
+metadata:
+    skill-author: K-Dense Inc. (PrimeKG original from Harvard MIMS)
+---
+
+# PrimeKG Knowledge Graph Skill
+
+## Overview
+
+PrimeKG is a precision medicine knowledge graph that integrates over 20 primary databases and high-quality scientific literature into a single resource. It contains over 100,000 nodes and 4 million edges across 29 relationship types, including drug-target, disease-gene, and phenotype-disease 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 `query_primekg.py`. Data is stored at `C:\Users\eamon\Documents\Data\PrimeKG\kg.csv`.
+
+## When to Use This Skill
+
+This skill should be used when:
+
+- **Knowledge-based drug discovery:** Identifying targets and mechanisms for diseases.
+- **Drug repurposing:** Finding existing drugs that might have evidence for new indications.
+- **Phenotype analysis:** Understanding how symptoms/phenotypes relate to diseases and genes.
+- **Multiscale biology:** Bridging the gap between molecular targets (genes) and clinical outcomes (diseases).
+- **Network pharmacology:** Investigating the broader network effects of drug-target interactions.
+
+## Core Workflow
+
+### 1. Search for Entities
+
+Find identifiers for genes, drugs, or diseases.
+
+```python
+from scripts.query_primekg import search_nodes
+
+# Search for Alzheimer's disease nodes
+results = search_nodes("Alzheimer", node_type="disease")
+# Returns: [{"id": "EFO_0000249", "type": "disease", "name": "Alzheimer's disease", ...}]
+```
+
+### 2. Get Neighbors (Direct Associations)
+
+Retrieve all connected nodes and relationship types.
+
+```python
+from scripts.query_primekg import get_neighbors
+
+# Get all neighbors of a specific disease ID
+neighbors = get_neighbors("EFO_0000249")
+# Returns: List of neighbors like {"neighbor_name": "APOE", "relation": "disease_gene", ...}
+```
+
+### 3. Analyze Disease Context
+
+A high-level function to summarize associations for a disease.
+
+```python
+from scripts.query_primekg import get_disease_context
+
+# Comprehensive summary for a disease
+context = get_disease_context("Alzheimer's disease")
+# Access: context['associated_genes'], context['associated_drugs'], context['phenotypes']
+```
+
+## Relationship Types in PrimeKG
+
+The graph contains several key relationship types including:
+- `protein_protein`: Physical PPIs
+- `drug_protein`: Drug target/mechanism associations
+- `disease_gene`: Genetic associations
+- `drug_disease`: Indications and contraindications
+- `disease_phenotype`: Clinical signs and symptoms
+- `gwas`: Genome-wide association studies evidence
+
+## Best Practices
+
+1. **Use specific IDs:** When using `get_neighbors`, ensure you have the correct ID from `search_nodes`.
+2. **Context first:** Use `get_disease_context` for a broad overview before diving into specific genes or drugs.
+3. **Filter relationships:** Use the `relation_type` filter in `get_neighbors` to focus on specific evidence (e.g., only `drug_protein`).
+4. **Multiscale integration:** Combine with `OpenTargets` for deeper genetic evidence or `Semantic Scholar` for the latest literature context.
+
+## Resources
+
+### Scripts
+- `scripts/query_primekg.py`: Core functions for searching and querying the knowledge graph.
+
+### Data Path
+- Data: `/mnt/c/Users/eamon/Documents/Data/PrimeKG/kg.csv`
+- Total nodes: ~129,000
+- Total edges: ~4,000,000
+- Database: CSV-based, optimized for pandas querying.