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Fast and accurate read alignment for resequencing.
Mu, John C; Jiang, Hui; Kiani, Amirhossein; Mohiyuddin, Marghoob; Bani Asadi, Narges; Wong, Wing H.
Afiliação
  • Mu JC; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
Bioinformatics ; 28(18): 2366-73, 2012 Sep 15.
Article em En | MEDLINE | ID: mdl-22811546
MOTIVATION: Next-generation sequence analysis has become an important task both in laboratory and clinical settings. A key stage in the majority sequence analysis workflows, such as resequencing, is the alignment of genomic reads to a reference genome. The accurate alignment of reads with large indels is a computationally challenging task for researchers. RESULTS: We introduce SeqAlto as a new algorithm for read alignment. For reads longer than or equal to 100 bp, SeqAlto is up to 10 × faster than existing algorithms, while retaining high accuracy and the ability to align reads with large (up to 50 bp) indels. This improvement in efficiency is particularly important in the analysis of future sequencing data where the number of reads approaches many billions. Furthermore, SeqAlto uses less than 8 GB of memory to align against the human genome. SeqAlto is benchmarked against several existing tools with both real and simulated data. AVAILABILITY: Linux and Mac OS X binaries free for academic use are available at http://www.stanford.edu/group/wonglab/seqalto CONTACT: whwong@stanford.edu.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Alinhamento de Sequência / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Alinhamento de Sequência / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido