title: RAMPART: a workflow management system for de novo genome assembly.
abstract: BACKGROUND
  The de novo assembly of genomes from whole- genome shotgun sequence data is a computationally intensive, multi-stage task and it is not known a priori which methods and parameter settings will produce optimal results. In current de novo assembly projects, a popular strategy involves trying many approaches, using different tools and settings, and then comparing and contrasting the results in order to select a final assembly for publication.
  
  
  RESULTS
  Herein, we present RAMPART, a configurable workflow management system for de novo genome assembly, which helps the user identify combinations of third-party tools and settings that provide good results for their particular genome and sequenced reads. RAMPART is designed to exploit High performance computing environments, such as clusters and shared memory systems, where available.
  
  
  METHODS
  RAMPART is available under the GPLv3 license at: https://github.com/TGAC/RAMPART.
authors: The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.
authors: Daniel
authors: D
authors: Mapleson
authors: The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.
authors: Nizar
authors: N
authors: Drou
authors: The Genome Analysis Centre, Norwich Research Park, Norwich NR4 7UH, UK.
authors: David
authors: D
authors: Swarbreck
mesh_terms: D016678:Genome; D023281:Genomics / Q000379:methods*; D012984:Software; D057188:Workflow
references: Proc Natl Acad Sci U S A. 2011 Jan 25;108(4):1513-8
references: 21187386
references: PLoS One. 2012;7(9):e42304
references: 23028432
references: BMC Genomics. 2014;15 Suppl 9:S10
references: 25521762
references: Bioinformatics. 2014 Jul 15;30(14):2068-9
references: 24642063
references: BMC Bioinformatics. 2014;15:126
references: 24884846