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Assembly of long error-prone reads using de Bruijn graphs.
Lin, Yu; Yuan, Jeffrey; Kolmogorov, Mikhail; Shen, Max W; Chaisson, Mark; Pevzner, Pavel A.
Afiliação
  • Lin Y; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92092.
  • Yuan J; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92092.
  • Kolmogorov M; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92092.
  • Shen MW; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92092.
  • Chaisson M; Department of Genome Sciences, University of Washington, Seattle, WA 98105.
  • Pevzner PA; Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92092; ppevzner@ucsd.edu.
Proc Natl Acad Sci U S A ; 113(52): E8396-E8405, 2016 12 27.
Article em En | MEDLINE | ID: mdl-27956617
ABSTRACT
The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2016 Tipo de documento: Article