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Scaling up genome annotation using MAKER and work queue.
Thrasher, Andrew; Musgrave, Zachary; Kachmarck, Brian; Thain, Douglas; Emrich, Scott.
Afiliação
  • Thrasher A; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA.
  • Musgrave Z; Yelp, Inc., San Francisco, CA, USA.
  • Kachmarck B; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA.
  • Thain D; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA.
  • Emrich S; Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA.
Int J Bioinform Res Appl ; 10(4-5): 447-60, 2014.
Article em En | MEDLINE | ID: mdl-24989862
Next generation sequencing technologies have enabled sequencing many genomes. Because of the overall increasing demand and the inherent parallelism available in many required analyses, these bioinformatics applications should ideally run on clusters, clouds and/or grids. We present a modified annotation framework that achieves a speed-up of 45x using 50 workers using a Caenorhabditis japonica test case. We also evaluate these modifications within the Amazon EC2 cloud framework. The underlying genome annotation (MAKER) is parallelised as an MPI application. Our framework enables it to now run without MPI while utilising a wide variety of distributed computing resources. This parallel framework also allows easy explicit data transfer, which helps overcome a major limitation of bioinformatics tools that often rely on shared file systems. Combined, our proposed framework can be used, even during early stages of development, to easily run sequence analysis tools on clusters, grids and clouds.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma / Biologia Computacional / Sequenciamento de Nucleotídeos em Larga Escala Limite: Animals Idioma: En Revista: Int J Bioinform Res Appl Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma / Biologia Computacional / Sequenciamento de Nucleotídeos em Larga Escala Limite: Animals Idioma: En Revista: Int J Bioinform Res Appl Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos