| Literature DB >> 25637556 |
Daniel Mapleson1, Nizar Drou1, David Swarbreck1.
Abstract
MOTIVATION: 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.Entities:
Mesh:
Year: 2015 PMID: 25637556 PMCID: PMC4443680 DOI: 10.1093/bioinformatics/btv056
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937
Fig. 1.A simplified representation of RAMPART’s architecture. Although user’s workflow must conform to the linear structure depicted here, each stage is optional and highly configurable. Most stages allow the user to select which third-party tool(s) and parameters are used, although primary input and output parameters to all tools are managed automatically. The most important pipeline stage, MASS, allows the user to execute multiple assemblers, with varying parameters. In the subsequent step, the resultant assemblies are analyzed before a single assembly is selected for use in the second half of the pipeline. Input to the MASS and AMP stages can be selected from any raw input library or from any modified libraries generated during the MECQ stage