SVision: a deep learning approach to resolve complex structural variants.

Lin, Jiadong; Wang, Songbo; Audano, Peter A; Meng, Deyu; Flores, Jacob I; Kosters, Walter; Yang, Xiaofei; Jia, Peng; Marschall, Tobias; Beck, Christine R; Ye, Kai

Lin, Jiadong; Wang, Songbo; Audano, Peter A; Meng, Deyu; Flores, Jacob I; Kosters, Walter; Yang, Xiaofei; Jia, Peng; Marschall, Tobias; Beck, Christine R; Ye, Kai.

Afiliação

Lin J; MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
Wang S; School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
Audano PA; Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Meng D; Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, the Netherlands.
Flores JI; MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
Kosters W; School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
Yang X; Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jia P; The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Marschall T; MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.
Beck CR; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China.
Ye K; Macau Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau.

Nat Methods ; 19(10): 1230-1233, 2022 10.

Article em En | MEDLINE | ID: mdl-36109679

ABSTRACT

ABSTRACT

Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequencing data. SVision outperforms current callers at identifying the internal structure of complex events and has revealed 80 high-quality CSVs with 25 distinct structures from an individual genome. SVision directly detects CSVs without matching known structures, allowing sensitive detection of both common and previously uncharacterized complex rearrangements.

Assuntos

Aprendizado Profundo; Genoma; Sequenciamento de Nucleotídeos em Larga Escala; Análise de Sequência de DNA

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Idioma: En Revista: Nat Methods Ano de publicação: 2022 Tipo de documento: Article

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