A robust benchmark for detection of germline large deletions and insertions.

TitleA robust benchmark for detection of germline large deletions and insertions.
Publication TypeJournal Article
Year of Publication2020
AuthorsZook, JM, Hansen, NF, Olson, ND, Chapman, L, Mullikin, JC, Xiao, C, Sherry, S, Koren, S, Phillippy, AM, Boutros, PC, Sahraeian, SMohammad E, Huang, V, Rouette, A, Alexander, N, Mason, CE, Hajirasouliha, I, Ricketts, C, Lee, J, Tearle, R, Fiddes, IT, Barrio, AMartinez, Wala, J, Carroll, A, Ghaffari, N, Rodriguez, OL, Bashir, A, Jackman, S, Farrell, JJ, Wenger, AM, Alkan, C, Soylev, A, Schatz, MC, Garg, S, Church, G, Marschall, T, Chen, K, Fan, X, English, AC, Rosenfeld, JA, Zhou, W, Mills, RE, Sage, JM, Davis, JR, Kaiser, MD, Oliver, JS, Catalano, AP, Chaisson, MJP, Spies, N, Sedlazeck, FJ, Salit, M
JournalNat Biotechnol
Volume38
Issue11
Pagination1347-1355
Date Published2020 Nov
ISSN1546-1696
KeywordsDiploidy, Genomic Structural Variation, Germ-Line Mutation, Humans, INDEL Mutation, Molecular Sequence Annotation, Sequence Analysis, DNA
Abstract

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.

DOI10.1038/s41587-020-0538-8
Alternate JournalNat Biotechnol
PubMed ID32541955
PubMed Central IDPMC8454654
Grant List9999-NIST / ImNIST / Intramural NIST DOC / United States
R01 AI151059 / AI / NIAID NIH HHS / United States

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