LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data

Compared to single nucleotide variants and short indels, structural variants (SVs) are often more challenging to detect using high-throughput sequencing based methods. Here, the authors develop LinkedSV, a computational tool for SV detection using linked-read exome and genome sequencing data.

Bibliographic Details
Main Authors: Li Fang, Charlly Kao, Michael V. Gonzalez, Fernanda A. Mafra, Renata Pellegrino da Silva, Mingyao Li, Sören-Sebastian Wenzel, Katharina Wimmer, Hakon Hakonarson, Kai Wang
Format: Article
Language:English
Published: Nature Portfolio 2019-12-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-13397-7
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author Li Fang
Charlly Kao
Michael V. Gonzalez
Fernanda A. Mafra
Renata Pellegrino da Silva
Mingyao Li
Sören-Sebastian Wenzel
Katharina Wimmer
Hakon Hakonarson
Kai Wang
author_facet Li Fang
Charlly Kao
Michael V. Gonzalez
Fernanda A. Mafra
Renata Pellegrino da Silva
Mingyao Li
Sören-Sebastian Wenzel
Katharina Wimmer
Hakon Hakonarson
Kai Wang
author_sort Li Fang
collection DOAJ
description Compared to single nucleotide variants and short indels, structural variants (SVs) are often more challenging to detect using high-throughput sequencing based methods. Here, the authors develop LinkedSV, a computational tool for SV detection using linked-read exome and genome sequencing data.
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spelling doaj.art-76f9da9e0bae457b92757a7d2b1f0be42022-12-21T20:29:32ZengNature PortfolioNature Communications2041-17232019-12-0110111510.1038/s41467-019-13397-7LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing dataLi Fang0Charlly Kao1Michael V. Gonzalez2Fernanda A. Mafra3Renata Pellegrino da Silva4Mingyao Li5Sören-Sebastian Wenzel6Katharina Wimmer7Hakon Hakonarson8Kai Wang9Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of PhiladelphiaCenter for Applied Genomics, Children’s Hospital of PhiladelphiaCenter for Applied Genomics, Children’s Hospital of PhiladelphiaCenter for Applied Genomics, Children’s Hospital of PhiladelphiaCenter for Applied Genomics, Children’s Hospital of PhiladelphiaDepartment of Biostatistics, Epidemiology and Informatics, University of PennsylvaniaInstitute of Human Genetics, Department for Genetics and Pharmacology, Medical University of InnsbruckInstitute of Human Genetics, Department for Genetics and Pharmacology, Medical University of InnsbruckDepartment of Pediatrics, University of PennsylvaniaRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of PhiladelphiaCompared to single nucleotide variants and short indels, structural variants (SVs) are often more challenging to detect using high-throughput sequencing based methods. Here, the authors develop LinkedSV, a computational tool for SV detection using linked-read exome and genome sequencing data.https://doi.org/10.1038/s41467-019-13397-7
spellingShingle Li Fang
Charlly Kao
Michael V. Gonzalez
Fernanda A. Mafra
Renata Pellegrino da Silva
Mingyao Li
Sören-Sebastian Wenzel
Katharina Wimmer
Hakon Hakonarson
Kai Wang
LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
Nature Communications
title LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
title_full LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
title_fullStr LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
title_full_unstemmed LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
title_short LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data
title_sort linkedsv for detection of mosaic structural variants from linked read exome and genome sequencing data
url https://doi.org/10.1038/s41467-019-13397-7
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