Iterative GVCF Genotyper
Informatics Products

DRAGEN Iterative gVCF Genotyper

High-performance analysis for population-scale variant aggregation

Rapid genotyping at scale

The DRAGEN Iterative gVCF Genotyper (IGG) offers a breakthrough solution for population-scale variant analysis, enabling efficient aggregation and genotyping of small germline variants across large cohorts.

Built for speed, accuracy, and scalability, DRAGEN IGG supports incremental analysis, allowing new sample batches to be added without reprocessing the entire data set. Whether you're powering national biobanks, rare disease studies or PopGen studies, DRAGEN IGG delivers the performance and precision needed to study modern population genomics.

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Key features

Iterative workflow

Add new samples to existing cohorts without reprocessing the entire cohort—ideal for large studies.

Compact multisample output

Generate compact, normalized msVCFs, and PLINK formats with per-variant metrics, including allele frequencies and genotype statistics, and per-sample metrics as provided in the input gVCFs.

Accurate results

Achieve variant calling accuracy with ML-based cohort-level variant filtering, high genotyping rate, and genotype consistency.

Scalable architecture

Scale efficiently across distributed nodes without adding CPU or memory pressure to any single node.

Seamless integration

Integrate easily with tools such as Hail, PLINK, and BCFtools for association studies, cohort exploration, and phasing/imputation analyses.

Flexible deployment

Deploy on Illumina Connected Analytics (ICA), DRAGEN servers, or high-performance computing (HPC) clusters for cloud or high-performance computing.

Used by the world's largest PopGen programs

Solving the variant aggregation bottleneck to unlock genomic discovery from cohorts

This on-demand webinar showcases Illumina DRAGEN Iterative gVCF Genotyper, designed to overcome legacy tool limitations with iterative analysis and batchwise processing without full cohort regenotyping.

Nature: Whole-genome sequencing of 490,640 UK Biobank participants

This landmark Nature study demonstrates how DRAGEN IGG powered the joint analysis of 490,640 whole genomes for the UK Biobank, enabling the discovery of 1.5 billion variants across ancestries, with precision and speed.

Alliance for Genomic Discovery completes 250,000 whole genomes to accelerate drug discovery

The Alliance for Genomic Discovery (AGD) leveraged DRAGEN IGG to aggregate 250,000 whole genomes, enhancing variant calling accuracy and enabling deeper insights into rare and complex traits across ancestrally diverse population.

Technical specifications

Input format Whole-genome gVCFs generated with DRAGEN (single or multisample)
Output format Multisample VCF with cohort-wide metrics
Variant types Single nucleotide variants (SNVs), insertions and deletions (indels), and PLINK format outputs
Reference support Genome Reference Consortium human build 38 (GRCh38) and telomere-to-telomere CHM13 (T2T-CHM13) assemblies
Deployment options Illumina Connected Analytics, DRAGEN server, on-premises high-performance compute infrastructure (early access)
Performance Up to 384 unique dual (UD) combinations and 96 combinatorial dual (CD) combinations

FAQ

The DRAGEN Iterative gVCF Genotyper is a tool developed by Illumina as part of the DRAGEN secondary analysis software toolkit, designed to perform genotyping and aggregation of multiple genomic germline samples that have been preprocessed into gVCF (Genomic VCF) format using the DRAGEN variant caller (VC). 

Sample genotyping and aggregation are critical steps in large-scale variant calling pipelines, such as those used for population studies, GWAS or PheWAS analyses, genomic research projects, and clinical research. 

Researchers working with large cohorts of whole-genome samples will benefit significantly from DRAGEN IGG. 

Current users include organizations such as Genomics England, UK Biobank, and the Alliance for Genomic Discovery (AGD). 

DRAGEN IGG is available on the DRAGEN server, HPC software nodes, and Illumina Connected Analytics. 

DRAGEN Server: IGG on the DRAGEN server is recommended for small cohorts, typically consisting of a few hundred samples. 

HPC: DRAGEN IGG on HPC is recommended for large, population-level cohorts, typically several thousand samples or more, depending on compute capacity. Software for both the DRAGEN server and HPC is available for download on the DRAGEN support page. 

ICA: DRAGEN IGG on ICA is recommended for large-scale population genomics programs, providing a fully managed workflow with click-button experience. IGG on ICA is available through the ICA entitled bundle in each ICA region. 

The DRAGEN Integrated Genotyping (IGG) workflow differs from traditional GATK joint genotyping in several ways:

  • Higher accuracy: DRAGEN IGG delivers superior sample-level variant accuracy compared to GATK and other variant callers
  • Independent sample calls: During aggregation, DRAGEN IGG maintains each sample’s genotype rather than refining it based on other samples
  • Cohort-level ranking: A machine learning model ranks and filters variant quality at the cohort level
  • Enhanced performance: This approach enhances variant and genotype accuracy and improves computational efficiency relative to GATK joint genotyping
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Product resources

DRAGEN gVCF Genotyper product guide

This guide offers a detailed walkthrough of DRAGEN gVCF Genotyper, along with comprehensive insights, configuration tips, and best practices to help you maximize performance and accuracy in cohort-based genotyping.

Related products

DRAGEN secondary analysis

Maximize genomic insights with Illumina DRAGEN secondary analysis. Learn about the latest updates, read FAQs, and find product support.

Illumina Connected Analytics

Operationalize bioinformatics workflows with sequencing system integration, automatic analysis of customizable workflows, or out-of-the-box DRAGEN pipelines.

DRAGEN server

The DRAGEN server provides an on-premises solution for highly accurate and comprehensive secondary analysis in a fraction of the time compared with a traditional CPU-based system.

Request a demo

Reach out to explore how DRAGEN IGG can accelerate your variant analysis and scale with your research.