gwas-database

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• SKILL.md
• api_reference.md · references/
• query.cpython-313.pyc · scripts/__pycache__/
• query.py · scripts/

SKILL.md (first lines)

# GWAS Catalog Database

## Overview

The GWAS Catalog is a comprehensive repository of published genome-wide association studies maintained by the National Human Genome Research Institute (NHGRI) and the European Bioinformatics Institute (EBI). The catalog contains curated SNP-trait associations from thousands of GWAS publications, including genetic variants, associated traits and diseases, p-values, effect sizes, and full summary statistics for many studies.

## When to Use This Skill

This skill should be used when queries involve:

- **Genetic variant associations**: Finding SNPs associated with diseases or traits
- **SNP lookups**: Retrieving information about specific genetic variants (rs IDs)
- **Trait/disease searches**: Discovering genetic associations for phenotypes
- **Gene associations**: Finding variants in or near specific genes
- **GWAS summary statistics**: Accessing complete genome-wide association data
- **Study metadata**: Retrieving publication and cohort information
- **Population genetics**: Exploring ancestry-specific associations
- **Polygenic risk scores**: Identifying variants for risk prediction models
- **Functional genomics**: Understanding variant effects and genomic context
- **Systematic reviews**: Comprehensive literature synthesis of genetic associations

## Core Capabilities

### 1. Understanding GWAS Catalog Data Structure

The GWAS Catalog is organized around four core entities:

- **Studies**: GWAS publications with metadata (PMID, author, cohort details)
- **Associations**: SNP-trait associations with statistical evidence (p ≤ 5×10⁻⁸)
- **Variants**: Genetic markers (SNPs) with genomic coordinates and alleles
- **Traits**: Phenotypes and diseases (mapped to EFO ontology terms)

**Key Identifiers:**
- Study accessions: `GCST` IDs (e.g., GCST001234)
- Variant IDs: `rs` numbers (e.g., rs7903146) or `variant_id` format
- Trait IDs: EFO terms (e.g., EFO_0001360 for type 2 diabetes)
- Gene symbols: HGNC approved names (e.g., TCF7L2)

### 2. Web Interface Searches

The web interface at https://www.ebi.ac.uk/gwas/ supports multiple search modes:

**By Variant (rs ID):**
```
rs7903146
```
Returns all trait associations for this SNP.

**By Disease/Trait:**
```
type 2 diabetes
Parkinson disease
body mass index
```
Returns all associated genetic variants.

**By Gene:**
```
APOE
TCF7L2
```
Returns variants in or near the gene region.

**By Chromosomal Region:**
```
10:114000000-115000000
```
Returns variants in the specified genomic interval.

**By Publication:**
```
PMID:20581827
Author: McCarthy MI
GCST001234
```
Returns study details and all reported associations.

### 3. REST API Access

The GWAS Catalog provides two REST APIs for programmatic access:

**Base URLs:**
- GWAS Catalog API: `https://www.ebi.ac.uk/gwas/rest/api`
- Summary Statistics API: `https://www.ebi.ac.uk/gwas/summary-statistics/api`

**API Documentation:**
- Main API docs: https://www.ebi.ac.uk/gwas/rest/docs/api
- Summary stats docs: https://www.ebi.ac.uk/gwas/summary-statistics/docs/

**Core Endpoints:**

1. **Studies endpoint** - `/studies/{accessionID}`
   ```python
   import requests

   # Get a specific study
   url = "https://www.ebi.ac.uk/gwas/rest/api/studies/GCST001795"
   response = requests.get(url, headers={"Content-Type": "application/json"})
   study = response.json()
   ```

2. **Associations endpoint** - `/associations`
   ```python
   # Find associations for a variant
   variant = "rs7903146"
   url = f"https://www.ebi.ac.uk/gwas/rest/api/singleNucleotidePolymorphisms/{variant}/associations"
   params = {"projection": "associationBySnp"}
   response = requests.get(url, params=params, headers={"Content-Type": "application/json"})
   associations = response.json()
   ```

3. **Variants endpoint** - `/singleNucleotidePolymorphisms/{rsID}`
   ```python
   # Get variant details
   url = "https://www.ebi.ac.uk/gwas/rest/api/singleNucleotidePolymorphisms/rs7903146"
   response = requests.get(url, headers={"Content-Type": "application/json"})
   variant_info = response.json()
   ```

From lamm-mit/scienceclaw, Apache-2.0.

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