Scalable and comprehensive mosaic variant calling using DRAGEN
Detecting low variant allele fraction (VAF) mosaic variants without matching controls remains a major challenge in genomics, limited by technical noise, lack of benchmarks, and computational scalability. We present the DRAGEN mosaic caller, a hardware-accelerated approach identifying variants down to ~1-2% VAF with low false-positive rates and hour-scale runtimes for mosaic SNV/indel detection from bulk sequencing. To support evaluation, we introduce a genome-wide low-VAF benchmark for variants between 1-10% VAF. Application to blood, sperm, and brain tissues revealed patterns, including mosaic hotspots and mutational signatures. The first analysis of HG002 blood showed that many "mosaic" variants defined from HG002 cell lines are likely culture-derived and not in vivo mutations. Importantly, DRAGEN also enables personalized assembly pangenome references to improve alignment and mosaic variant detection in complex regions. Together, this development makes routine low-VAF discovery feasible, opening new opportunities to study mosaic mutations in healthy and disease individuals.
Authors
- Ester Kalef-Ezra (ORCID: https://orcid.org/0000-0002-1297-3315)
- Severine Catreux (ORCID: https://orcid.org/0009-0008-1813-1240)
- Kavya Kottapalli (ORCID: https://orcid.org/0000-0003-3872-0196)
- C. Proukakis
- Theodore M. Nelson (ORCID: https://orcid.org/0000-0002-8600-0444)
- Thomas X. Garcia (ORCID: https://orcid.org/0000-0001-7761-2660)
- Duke Tran
- Massimiliano Rossi (ORCID: https://orcid.org/0000-0002-3012-1394)
- Arun Visvanath
- Gavin Parnaby
- Michal Izydorczyk (ORCID: https://orcid.org/0000-0003-3461-1224)
- Oona Shigeno Risse-Adams (ORCID: https://orcid.org/0000-0002-4350-663X)
- Sonja W. Scholz
- Heer Mehta
- Xinchang Zheng
- James Han
- Sairam Behera
- Harsha Doddapaneni
- Helen Shen
- Rami Mehio
- Fritz Sedlazeck
- Christopher E Mason
- Yina Wang
- Clifton L Dalgard
Institutions
- Johns Hopkins University (US)
- Uniformed Services University of the Health Sciences (US)
- Illumina (United States) (US)
- Baylor College of Medicine (US)
- Cornell University (US)
- Kennedy Center (DK)
- Quantitative BioSciences (US)
- National Institute of Neurological Disorders and Stroke (US)
- National Hospital for Neurology and Neurosurgery (GB)
- University College London (GB)
- Rice University (US)
Publication Details
- Journal
- medRxiv
- Published
- 2026-02-04
- DOI
- https://doi.org/10.64898/2026.02.03.26345450
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- Weill Cornell Medical College
- National Institute of General Medical Sciences