Comparison of variant callers using 60 532 multi-ancestry whole genome sequences
Whole genome sequencing (WGS) studies play a pivotal role in studying the genetic underpinnings of human diseases and traits. High quality and reproducible variant calling is the cornerstone for the success of downstream analyses, including WGS association studies and polygenic risk prediction. This paper compares the data quality, performance, and concordance of two widely used WGS variant callers, the Genome Analysis Toolkit (GATK) and Variant Tool set that discovers short variants (VT), using 60 532 multi-ancestry whole genomes sequenced by the Centers for Common Disease Genomics (CCDGs) of the NHGRI Genome Sequencing Program. Our findings show that both QCed GATK and VT pipelines yield highly consistent and reliable called Single Nucleotide Variants (SNVs) in large-scale WGS studies, supporting their agreements in joint variants calling. However, the two pipelines exhibit greater discrepancies in calling insertions and deletions (INDELs).
Authors
- Adam L. Felsenfeld
- Heidi J. Sofia (ORCID: https://orcid.org/0000-0002-4990-5877)
- Ira M. Hall (ORCID: https://orcid.org/0000-0003-4442-6655)
- Robert Maier (ORCID: https://orcid.org/0000-0002-3044-090X)
- Michael C. Zody (ORCID: https://orcid.org/0000-0001-6594-7199)
- T. Matise
- Derek Shyr (ORCID: https://orcid.org/0000-0002-2345-3390)
- Rounak Dey (ORCID: https://orcid.org/0000-0002-6540-8280)
- Nathan O. Stitziel (ORCID: https://orcid.org/0000-0002-4963-8211)
- Neha Gupta (ORCID: https://orcid.org/0000-0001-5135-8916)
- Zilin Li (ORCID: https://orcid.org/0000-0003-1521-8945)
- MJ Daly
- Xihong Lin
- Yushi Tang
- Albert Smith
- Ginger A Metcalf
- Haoyu Yang
- Benjamin Neale (ORCID: https://orcid.org/0000-0003-1513-6077)
- Steve Buyske
- Hufeng Zhou
- Eric Boerwinkle
- Catherine Reeves
- Xihao Li
- Richard A Gibbs
Institutions
- Rutgers, The State University of New Jersey (US)
- Broad Institute (US)
- University of North Carolina at Chapel Hill (US)
- Baylor College of Medicine (US)
- Princeton University (US)
- Washington University in St. Louis (US)
- University of Michigan (US)
- Harvard University Press (US)
- Massachusetts General Hospital (US)
- National Human Genome Research Institute (US)
- Cancer Research And Biostatistics (US)
- Environmental and Occupational Health Sciences Institute (US)
- Center for Genomic Science (IT)
- New York Genome Center (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Briefings in Bioinformatics
- Published
- 2026-03-01
- DOI
- https://doi.org/10.1093/bib/bbag130
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00