bio-clinical-databases-myvariant-queries

## Version Compatibility Reference examples tested with: SnpEff 5.2+, pandas 2.2+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # MyVariant.info Queries **"Annotate my variants from multiple databases at once"** → Query the myvariant.info aggregation API to retrieve ClinVar, gnomAD, dbSNP, COSMIC, and other annotations in a single request per variant. - Python: `myvariant.MyVariantInfo().getvariants(ids, fields='clinvar,gnomad,dbnsfp')` ## Required Imports ```python import myvariant ``` ## Initialize Client ```python mv = myvariant.MyVariantInfo() ``` ## Query Single Variant **Goal:** Retrieve aggregated annotations for a single variant from multiple databases in one request. **Approach:** Query myvariant.info by HGVS notation or rsID, which returns ClinVar, gnomAD, dbSNP, COSMIC, and CADD data. ```python # 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 **Goal:** Batch-query up to 1000 variants in a single API call with field selection for efficiency. **Approach:** Pass a list of variant identifiers to `getvariants()` with specific field filters to minimize response size. ```python 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 **Goal:** Search for variants by gene, clinical significance, or genomic region using query syntax. **Approach:** Use Lucene-style query strings with `mv.query()` to filter by gene symbol, ClinVar fields, or coordinate ranges. ```python # 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: | Field | Description | |-------|-------------| | `clinvar` | ClinVar annotations | | `gnomad_exome` | gnomAD exome frequencies | | `gnomad_genome` | gnomAD genome frequencies | | `dbsnp` | dbSNP annotations | | `cosmic` | COSMIC cancer mutations | | `cadd` | CADD deleteriousness scores | | `dbnsfp` | dbNSFP functional predictions | | `snpeff` | SnpEff annotations | ## Extract Specific Annotations **Goal:** Extract ClinVar classification, gnomAD frequency, and CADD score from a variant result. **Approach:** Navigate the nested JSON response using dictionary access to reach specific annotation fields. ```python 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 **Goal:** Convert batch variant query results into a structured pandas DataFrame for downstream analysis. **Approach:** Query multiple rsIDs with selected fields, extract key annotations per variant, and assemble into a DataFrame. ```python 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 **Goal:** Handle large variant sets exceeding the 1000-variant-per-request API limit. **Approach:** Split variants into chunks and query sequentially, relying on myvariant's built-in rate limiting. ```python # 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