Query Allele Frequency

Filter variants by population allele frequency using gnomAD data, the largest database of human genetic variation. Identify rare, common, or population-specific variants for your research.

About gnomAD

The Genome Aggregation Database (gnomAD) is the largest collection of human genetic variation data, containing allele frequencies from diverse global populations.

Learn more about gnomAD in their official overview.

Quick Filtering with MAF

The simplest way to filter by rarity is using minor allele frequency (MAF). This searches across both gnomAD genomes and exomes datasets simultaneously for comprehensive population frequency filtering.

Common MAF Thresholds

Ultra-rare

maf < 0.001

< 0.1% frequency

Rare

maf < 0.01

< 1% frequency

Low frequency

maf < 0.05

< 5% frequency

Example: Finding Rare Variants

Let's find rare variants (frequency < 1%) usingmaf < 0.01:

Image showing how to search by minor allele frequency with maf < 0.01

Using MAF to quickly identify rare variants across all gnomAD populations

MAF Search Benefits

Using maf as a query automatically searches both gnomAD genomes and gnomAD exomes datasets, providing comprehensive frequency filtering without needing to specify individual datasets.

Population-Specific Searches

For more precise population genetics analysis, query specific gnomAD population datasets using exact field names. This allows you to identify variants that are rare in one population but common in another.

Example: Non-Finnish European Population

Search for variants rare in the Non-Finnish European population usinggnomAD.genomes.af_nfe < 0.01:

Image showing how to search gnomAD by specific population with gnomAD.genomes.af_nfe < 0.01

Filtering for variants rare in the Non-Finnish European population using specific gnomAD field names

Available gnomAD Populations

gnomAD Genomes Populations

  • gnomAD.genomes.af - All populations
  • gnomAD.genomes.af_afr - African/African American
  • gnomAD.genomes.af_amr - Latino/Admixed American
  • gnomAD.genomes.af_asj - Ashkenazi Jewish
  • gnomAD.genomes.af_eas - East Asian
  • gnomAD.genomes.af_fin - Finnish
  • gnomAD.genomes.af_nfe - Non-Finnish European
  • gnomAD.genomes.af_oth - Other

gnomAD Exomes Populations

  • gnomAD.exomes.af - All populations
  • gnomAD.exomes.af_afr - African/African American
  • gnomAD.exomes.af_amr - Latino/Admixed American
  • gnomAD.exomes.af_asj - Ashkenazi Jewish
  • gnomAD.exomes.af_eas - East Asian
  • gnomAD.exomes.af_fin - Finnish
  • gnomAD.exomes.af_nfe - Non-Finnish European
  • gnomAD.exomes.af_sas - South Asian

Complete Field Reference

Bystro reports many gnomAD fields including all population-specific frequencies. See our complete field descriptions for detailed information about all available annotation fields.

Important Considerations

Allele Frequency Reporting

Bystro reports allele frequencies relative to the specific variant allele in your dataset, not all previously observed variants at that position (which is how dbSNP reports frequencies).

gnomAD IDs

gnomAD ID shows only one rs-number per variant. Learn how this can be used to create Set IDs for SKAT analysis in our FAQ section.

Practical Applications

Rare Disease Research

Combine ultra-rare frequency filtering with high CADD scores to identify potentially pathogenic variants:

maf < 0.001 AND cadd > 20

Population Genetics

Compare allele frequencies between populations to identify population-specific variants:

gnomAD.genomes.af_eas > 0.05 AND gnomAD.genomes.af_nfe < 0.01

Clinical Variant Filtering

Focus on clinically relevant rare variants in coding regions:

maf < 0.01 AND refSeq.exonicAlleleFunction:nonSynonymous

Allele Frequency Best Practices

Consider your study population: Use population-specific frequencies when studying specific ethnic groups

Account for sample size: Check allele count (AC) and allele number (AN) fields for reliability

Combine datasets: Use both exomes and genomes data for comprehensive frequency assessment

Validate rare variants: Always validate ultra-rare variants with additional evidence

Performance Note

Dataset used in examples: 1000 Genomes Project (73,452,337 variants in 27,192 genes, queries typically complete in ~0.5 seconds)