bio-clinical-databases-myvariant-queries

name: bio-clinical-databases-myvariant-queries description: Query myvariant.info API for aggregated variant annotations from multiple databases (ClinVar, gnomAD, dbSNP, COSMIC, etc.) in a single request. Use when annotating variants with clinical and population data from multiple sources simultaneously. tool_type: python primary_tool: myvariant measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command

MyVariant.info Queries

Required Imports

import myvariant

Initialize Client

mv = myvariant.MyVariantInfo()

Query Single Variant

# Query by HGVS notation (recommended)
result = mv.getvariant('chr7:g.140453136A>T')

# Query by rsID
result = mv.getvariant('rs121913527')

# Query by gene and protein change
result = mv.getvariant('BRAF:p.V600E')

Query Multiple Variants

variants = [
    'chr7:g.140453136A>T',
    'chr17:g.7577120C>T',
    'rs121913527'
]

# Batch query (up to 1000 variants per request)
results = mv.getvariants(variants)

# With specific fields
results = mv.getvariants(
    variants,
    fields=['clinvar', 'gnomad_exome', 'dbsnp']
)

Search Variants

# Search by gene
results = mv.query('clinvar.gene.symbol:BRCA1', size=100)

# Search pathogenic variants in gene
results = mv.query(
    'clinvar.gene.symbol:BRCA1 AND clinvar.clinical_significance:Pathogenic',
    size=100
)

# Search by genomic region
results = mv.query('chr7:140400000-140500000')

Available Fields

Common field paths for annotations:

Extract Specific Annotations

result = mv.getvariant('chr7:g.140453136A>T')

# ClinVar classification
clinvar_sig = result.get('clinvar', {}).get('clinical_significance')

# gnomAD allele frequency
gnomad_af = result.get('gnomad_exome', {}).get('af', {}).get('af')

# CADD score
cadd_phred = result.get('cadd', {}).get('phred')

Batch Processing with DataFrame

import pandas as pd

variants = ['rs121913527', 'rs1800566', 'rs104894155']
results = mv.getvariants(variants, fields=['clinvar', 'gnomad_exome'])

records = []
for r in results:
    records.append({
        'query': r.get('query'),
        'clinvar_sig': r.get('clinvar', {}).get('clinical_significance'),
        'gnomad_af': r.get('gnomad_exome', {}).get('af', {}).get('af')
    })

df = pd.DataFrame(records)

Rate Limiting

# myvariant handles rate limiting automatically
# For large batches, use chunks
def batch_query(variants, chunk_size=1000):
    all_results = []
    for i in range(0, len(variants), chunk_size):
        chunk = variants[i:i + chunk_size]
        results = mv.getvariants(chunk)
        all_results.extend(results)
    return all_results

Related Skills

• clinvar-lookup - Detailed ClinVar queries
• gnomad-frequencies - gnomAD-specific frequency queries
• dbsnp-queries - dbSNP rsID lookups