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OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709945/ https://www.ncbi.nlm.nih.gov/pubmed/29195502 http://dx.doi.org/10.1186/s13059-017-1356-2 |
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author | Li, Le Leung, Alden King-Yung 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 Yiu, Siu-Ming Xiao, Ming Lo, Kwok-Wai Kwok, Pui-Yan Chan, Ting-Fung Yip, Kevin Y. |
author_facet | Li, Le Leung, Alden King-Yung 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 Yiu, Siu-Ming Xiao, Ming Lo, Kwok-Wai Kwok, Pui-Yan Chan, Ting-Fung Yip, Kevin Y. |
author_sort | Li, Le |
collection | PubMed |
description | 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/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1356-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5709945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57099452017-12-06 OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps Li, Le Leung, Alden King-Yung 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 Yiu, Siu-Ming Xiao, Ming Lo, Kwok-Wai Kwok, Pui-Yan Chan, Ting-Fung Yip, Kevin Y. Genome Biol Method 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/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1356-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-01 /pmc/articles/PMC5709945/ /pubmed/29195502 http://dx.doi.org/10.1186/s13059-017-1356-2 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Li, Le Leung, Alden King-Yung 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 Yiu, Siu-Ming Xiao, Ming Lo, Kwok-Wai Kwok, Pui-Yan Chan, Ting-Fung Yip, Kevin Y. OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title | OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title_full | OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title_fullStr | OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title_full_unstemmed | OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title_short | OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
title_sort | omsv enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709945/ https://www.ncbi.nlm.nih.gov/pubmed/29195502 http://dx.doi.org/10.1186/s13059-017-1356-2 |
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