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Kart: a divide-and-conquer algorithm for NGS read alignment.
Lin, Hsin-Nan; Hsu, Wen-Lian.
Afiliación
  • Lin HN; Institute of Information Science, Academia Sinica, Taipei, Taiwan.
  • Hsu WL; Institute of Information Science, Academia Sinica, Taipei, Taiwan.
Bioinformatics ; 33(15): 2281-2287, 2017 Aug 01.
Article en En | MEDLINE | ID: mdl-28379292
ABSTRACT
MOTIVATION Next-generation sequencing (NGS) provides a great opportunity to investigate genome-wide variation at nucleotide resolution. Due to the huge amount of data, NGS applications require very fast and accurate alignment algorithms. Most existing algorithms for read mapping basically adopt seed-and-extend strategy, which is sequential in nature and takes much longer time on longer reads.

RESULTS:

We develop a divide-and-conquer algorithm, called Kart, which can process long reads as fast as short reads by dividing a read into small fragments that can be aligned independently. Our experiment result indicates that the average size of fragments requiring the more time-consuming gapped alignment is around 20 bp regardless of the original read length. Furthermore, it can tolerate much higher error rates. The experiments show that Kart spends much less time on longer reads than other aligners and still produce reliable alignments even when the error rate is as high as 15%. AVAILABILITY AND IMPLEMENTATION Kart is available at https//github.com/hsinnan75/Kart/ . CONTACT hsu@iis.sinica.edu.tw. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Alineación de Secuencia / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Alineación de Secuencia / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Taiwán