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SOAPdenovo-Trans: de novo transcriptome assembly with short RNA-Seq reads.
Xie, Yinlong; Wu, Gengxiong; Tang, Jingbo; Luo, Ruibang; Patterson, Jordan; Liu, Shanlin; Huang, Weihua; He, Guangzhu; Gu, Shengchang; Li, Shengkang; Zhou, Xin; Lam, Tak-Wah; Li, Yingrui; Xu, Xun; Wong, Gane Ka-Shu; Wang, Jun.
Afiliação
  • Xie Y; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Wu G; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Tang J; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Luo R; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Patterson J; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Liu S; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Huang W; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • He G; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Gu S; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Li S; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Zhou X; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Lam TW; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Li Y; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Xu X; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Wong GK; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
  • Wang J; School of Bioscience and Bioengineering, South China University of Technology 510006, Guangzhou, China, BGI-Shenzhen, Shenzhen 518083, China, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory and Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong, In
Bioinformatics ; 30(12): 1660-6, 2014 Jun 15.
Article em En | MEDLINE | ID: mdl-24532719
ABSTRACT
MOTIVATION Transcriptome sequencing has long been the favored method for quickly and inexpensively obtaining a large number of gene sequences from an organism with no reference genome. Owing to the rapid increase in throughputs and decrease in costs of next- generation sequencing, RNA-Seq in particular has become the method of choice. However, the very short reads (e.g. 2 × 90 bp paired ends) from next generation sequencing makes de novo assembly to recover complete or full-length transcript sequences an algorithmic challenge.

RESULTS:

Here, we present SOAPdenovo-Trans, a de novo transcriptome assembler designed specifically for RNA-Seq. We evaluated its performance on transcriptome datasets from rice and mouse. Using as our benchmarks the known transcripts from these well-annotated genomes (sequenced a decade ago), we assessed how SOAPdenovo-Trans and two other popular transcriptome assemblers handled such practical issues as alternative splicing and variable expression levels. Our conclusion is that SOAPdenovo-Trans provides higher contiguity, lower redundancy and faster execution. AVAILABILITY AND IMPLEMENTATION Source code and user manual are available at http//sourceforge.net/projects/soapdenovotrans/.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Sequência de RNA / Perfilação da Expressão Gênica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Guideline Limite: Animals Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Índia
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Análise de Sequência de RNA / Perfilação da Expressão Gênica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Guideline Limite: Animals Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Índia