NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing

The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we...

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Main Authors:	Tham, Cheng Yong, Tirado-Magallanes, Roberto, Goh, Yufen, Fullwood, Melissa Jane, Koh, Bryan T. H., Wang, Wilson, Ng, Chin Hin, Chng, Wee Joo, Thiery, Alexandre, Tenen, Daniel G., Benoukraf, Touati
Other Authors:	School of Biological Sciences
Format:	Article
Language:	English
Published:	2021
Subjects:	Science::Medicine Structural Variants SV Characterization
Online Access:	https://hdl.handle.net/10356/147971
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1479712023-02-28T17:09:07Z NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing Tham, Cheng Yong Tirado-Magallanes, Roberto Goh, Yufen Fullwood, Melissa Jane Koh, Bryan T. H. Wang, Wilson Ng, Chin Hin Chng, Wee Joo Thiery, Alexandre Tenen, Daniel G. Benoukraf, Touati School of Biological Sciences Science::Medicine Structural Variants SV Characterization The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we present NanoVar, an optimized structural variant caller utilizing low-depth (8X) whole-genome sequencing data generated by Oxford Nanopore Technologies. NanoVar exhibits higher structural variant calling accuracy when benchmarked against current tools using low-depth simulated datasets. In patient samples, we successfully validate structural variants characterized by NanoVar and uncover normal alternative sequences or alleles which are present in healthy individuals. Ministry of Education (MOE) National Research Foundation (NRF) Published version Work in the T.B. laboratory is supported by the National Research Foundation, the Singapore Ministry of Education under its Centres of Excellence initiative and the RNA Biology Center at the Cancer Science Institute of Singapore, NUS, as part of funding under the Singapore Ministry of Education’s AcRF Tier 3 grants [MOE2014-T3-1-006]. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. C.Y.T. and R.T.M. are supported by a Doctoral Scholarship from the Cancer Science Institute of Singapore. 2021-04-30T08:02:24Z 2021-04-30T08:02:24Z 2020 Journal Article Tham, C. Y., Tirado-Magallanes, R., Goh, Y., Fullwood, M. J., Koh, B. T. H., Wang, W., Ng, C. H., Chng, W. J., Thiery, A., Tenen, D. G. & Benoukraf, T. (2020). NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing. Genome Biology, 21(1). https://dx.doi.org/10.1186/s13059-020-01968-7 1474-760X 0000-0002-4789-8028 https://hdl.handle.net/10356/147971 10.1186/s13059-020-01968-7 32127024 2-s2.0-85081042927 1 21 en MOE2014-T3-1-006 Genome Biology © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License,which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/.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 in a credit line to the data. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Science::Medicine Structural Variants SV Characterization
spellingShingle	Science::Medicine Structural Variants SV Characterization Tham, Cheng Yong Tirado-Magallanes, Roberto Goh, Yufen Fullwood, Melissa Jane Koh, Bryan T. H. Wang, Wilson Ng, Chin Hin Chng, Wee Joo Thiery, Alexandre Tenen, Daniel G. Benoukraf, Touati NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
description	The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we present NanoVar, an optimized structural variant caller utilizing low-depth (8X) whole-genome sequencing data generated by Oxford Nanopore Technologies. NanoVar exhibits higher structural variant calling accuracy when benchmarked against current tools using low-depth simulated datasets. In patient samples, we successfully validate structural variants characterized by NanoVar and uncover normal alternative sequences or alleles which are present in healthy individuals.
author2	School of Biological Sciences
author_facet	School of Biological Sciences Tham, Cheng Yong Tirado-Magallanes, Roberto Goh, Yufen Fullwood, Melissa Jane Koh, Bryan T. H. Wang, Wilson Ng, Chin Hin Chng, Wee Joo Thiery, Alexandre Tenen, Daniel G. Benoukraf, Touati
format	Article
author	Tham, Cheng Yong Tirado-Magallanes, Roberto Goh, Yufen Fullwood, Melissa Jane Koh, Bryan T. H. Wang, Wilson Ng, Chin Hin Chng, Wee Joo Thiery, Alexandre Tenen, Daniel G. Benoukraf, Touati
author_sort	Tham, Cheng Yong
title	NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
title_short	NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
title_full	NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
title_fullStr	NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
title_full_unstemmed	NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
title_sort	nanovar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
publishDate	2021
url	https://hdl.handle.net/10356/147971
_version_	1759855905787084800

NanoVar : accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing

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