Query gnomAD for population allele frequencies to assess variant rarity. Use when filtering variants by population frequency for rare disease analysis or determining if a variant is common in the general population.
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.
gnomAD Frequency Queries
gnomAD REST API
Goal: Retrieve exome and genome allele frequencies from gnomAD for individual variants.
Approach: Send a GraphQL query to the gnomAD API with variant ID and dataset version, then parse exome/genome frequency fields.
"Check how common this variant is in the population" → Query gnomAD for allele frequency, allele count, and homozygote count.
Goal: Retrieve ancestry-specific allele frequencies to assess variant rarity within relevant populations.
Approach: Query the gnomAD population-stratified AF fields (AFR, AMR, ASJ, EAS, FIN, NFE, SAS) via myvariant.info.
def get_population_frequencies(variant_hgvs):
'''Get gnomAD frequencies by ancestry population'''
mv = myvariant.MyVariantInfo()
result = mv.getvariant(variant_hgvs, fields=['gnomad_exome.af'])
af_data = result.get('gnomad_exome', {}).get('af', {})
populations = {
'af': af_data.get('af'), # Global
'af_afr': af_data.get('af_afr'), # African
'af_amr': af_data.get('af_amr'), # Admixed American
'af_asj': af_data.get('af_asj'), # Ashkenazi Jewish
'af_eas': af_data.get('af_eas'), # East Asian
'af_fin': af_data.get('af_fin'), # Finnish
'af_nfe': af_data.get('af_nfe'), # Non-Finnish European
'af_sas': af_data.get('af_sas'), # South Asian
}
return populations
Filtering Thresholds
Common frequency cutoffs for variant filtering:
Threshold
Use Case
< 0.01 (1%)
Rare disease, ACMG PM2
< 0.001 (0.1%)
Stringent rare disease
< 0.0001 (0.01%)
Ultra-rare
Absent
Novel variant
Filter Variants by Frequency
Goal: Apply population frequency thresholds to retain only rare variants for downstream analysis.
Approach: Compare the maximum allele frequency across exome and genome datasets against a configurable threshold (default 1% per ACMG PM2).
def is_rare(gnomad_af, threshold=0.01):
'''Check if variant is rare based on gnomAD AF
threshold: Default 0.01 (1%) per ACMG PM2 supporting criterion
Use 0.001 for more stringent filtering
'''
if gnomad_af is None:
return True # Absent from gnomAD = rare
return gnomad_af < threshold
def filter_rare_variants(variants, threshold=0.01):
'''Filter list of variants to keep only rare ones'''
rare = []
for v in variants:
exome_af = v.get('gnomad_exome_af')
genome_af = v.get('gnomad_genome_af')
max_af = max(filter(None, [exome_af, genome_af]), default=None)
if is_rare(max_af, threshold):
rare.append(v)
return rare
Batch Query with Local gnomAD
Goal: Perform large-scale frequency lookups using a local gnomAD Hail Table for high throughput.
Approach: Load the gnomAD sites Hail Table from Google Cloud Storage and filter by allele frequency threshold.
For large-scale analysis, use local gnomAD VCF/Hail Table:
# Using Hail for gnomAD v4
import hail as hl
ht = hl.read_table('gs://gcp-public-data--gnomad/release/4.0/ht/exomes/gnomad.exomes.v4.0.sites.ht')
# Filter to rare variants
rare_ht = ht.filter(ht.freq[0].AF < 0.01)
Related Skills
myvariant-queries - Aggregated queries including gnomAD
variant-prioritization - Filter by frequency thresholds
population-genetics/population-structure - Population stratification analysis
