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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...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
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.
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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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