OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps
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AbstractWe present a new method, OMSV, for accurately and comprehensively identifying structural variations (SVs) from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with or without creating or destroying restriction sites. We show that OMSV has high sensitivity and specificity, with clear performance gains over the latest method. Applying OMSV to a human cell line, we identified hundreds of SVs >2 kbp, with 68 % of them missed by sequencing-based callers. Independent experimental validation confirmed the high accuracy of these SVs. The OMSV software is available at .
All Author(s) ListLe Li, Alden King-Yung Leung, Tsz-Piu Kwok, Yvonne Y. Y. Lai, Iris K. Pang, Grace Tin-Yun Chung, Angel C. Y. Mak, Annie Poon, Catherine Chu, Menglu Li, Jacob J. K. Wu, Ernest T. Lam, Han Cao, Chin Lin, Justin Sibert, Siu-Ming Yiu, Ming Xiao, Kwok-Wai Lo, Pui-Yan Kwok, Ting-Fung Chan, Kevin Y. Yip
Journal nameGenome Biology
Volume Number18
LanguagesEnglish-United Kingdom
KeywordsOptical mapping, Nanochannel, Single-molecule analysis, Structural variation

Last updated on 2020-06-07 at 00:14