SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads.

Yan, Chaokun; He, Junyi; Luo, Junwei; Wang, Jianlin; Zhang, Ge; Luo, Huimin

Yan, Chaokun; He, Junyi; Luo, Junwei; Wang, Jianlin; Zhang, Ge; Luo, Huimin.

Afiliação

Yan C; School of Computer and Information Engineering, Henan University, Kaifeng, China.
He J; School of Computer and Information Engineering, Henan University, Kaifeng, China.
Luo J; College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China.
Wang J; School of Computer and Information Engineering, Henan University, Kaifeng, China.
Zhang G; School of Computer and Information Engineering, Henan University, Kaifeng, China.
Luo H; School of Computer and Information Engineering, Henan University, Kaifeng, China.

Front Genet ; 12: 665812, 2021.

Article em En | MEDLINE | ID: mdl-33995493

Palavras-chave

alignment; short read; soft-clipped read; structural variation; the next generation sequencing technology

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Front Genet Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China País de publicação: Suíça

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