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Comprehensive variation discovery in single human genomes.

Authors :
Weisenfeld, Neil I
Yin, Shuangye
Sharpe, Ted
Lau, Bayo
Hegarty, Ryan
Holmes, Laurie
Sogoloff, Brian
Tabbaa, Diana
Williams, Louise
Russ, Carsten
Nusbaum, Chad
Lander, Eric S
MacCallum, Iain
Jaffe, David B
Source :
Nature Genetics; Dec2014, Vol. 46 Issue 12, p1350-1355, 6p, 3 Charts
Publication Year :
2014

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10614036
Volume :
46
Issue :
12
Database :
Complementary Index
Journal :
Nature Genetics
Publication Type :
Academic Journal
Accession number :
99595735
Full Text :
https://doi.org/10.1038/ng.3121