Abstract

We 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 http://yiplab.cse.cuhk.edu.hk/omsv/.

Details

Title
OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps
Author
Li, Le; Alden King-Yung Leung; Kwok, Tsz-Piu; Lai, Yvonne Y Y; Pang, Iris K; Chung, Grace Tin-Yun; Mak, Angel C Y; Poon, Annie; Chu, Catherine; Li, Menglu; Wu, Jacob J K; Lam, Ernest T; Cao, Han; Lin, Chin; Sibert, Justin; Siu-Ming Yiu
Publication year
2017
Publication date
2017
Publisher
BioMed Central
ISSN
14747596
e-ISSN
1474760X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2208009631
Copyright
© 2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.