Comprehensive variation discovery in single human genomes.
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Abstract | Complete knowledge of the genetic variation in individual human genomes is a crucial foundation for understanding the etiology of disease. Genetic variation is typically characterized by sequencing individual genomes and comparing reads to a reference. Existing methods do an excellent job of detecting variants in approximately 90% of the human genome; however, calling variants in the remaining 10% of the genome (largely low-complexity sequence and segmental duplications) is challenging. To improve variant calling, we developed a new algorithm, DISCOVAR, and examined its performance on improved, low-cost sequence data. Using a newly created reference set of variants from the finished sequence of 103 randomly chosen fosmids, we find that some standard variant call sets miss up to 25% of variants. We show that the combination of new methods and improved data increases sensitivity by several fold, with the greatest impact in challenging regions of the human genome. |
Year of Publication | 2014
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Journal | Nat Genet
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Volume | 46
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Issue | 12
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Pages | 1350-5
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Date Published | 2014 Dec
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ISSN | 1546-1718
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URL | |
DOI | 10.1038/ng.3121
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PubMed ID | 25326702
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PubMed Central ID | PMC4244235
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Grant list | HHSN272200900018C / AI / NIAID NIH HHS / United States
U54 HG003067 / HG / NHGRI NIH HHS / United States
R01 HG003474 / HG / NHGRI NIH HHS / United States
U54HG003067 / HG / NHGRI NIH HHS / United States
HHSN272200900018C / PHS HHS / United States
R01HG003474 / HG / NHGRI NIH HHS / United States
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