Journal
NATURE BIOTECHNOLOGY
Volume 38, Issue 11, Pages 1347-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41587-020-0538-8
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Funding
- Intramural Research Program of the National Library of Medicine, National Institutes of Health
- Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health
- National Institute of Standards and Technology
- Food and Drug Administration
- STARR [I13-0052]
- NIH [R01AI151059]
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [ZIAHG200398] Funding Source: NIH RePORTER
- NATIONAL LIBRARY OF MEDICINE [ZIHLM200888] Funding Source: NIH RePORTER
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Detection of structural variants in the human genome is facilitated by a benchmark set of large deletions and insertions. New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls >= 50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by >= 1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.
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