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RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

Scientific Reports · 2015 · Vol. 5(1) · pp. 8365–8365
Thomas BrettinJames J. DavisTerry DiszRobert A. EdwardsSvetlana GerdesGary J. OlsenRobert OlsonRoss OverbeekBruce ParrelloGordon D. PuschMaulik ShuklaJames ThomasonRick StevensVeronika VonsteinAlice R. WattamFangfang Xia

Abstract

The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

Genomics and Phylogenetic StudiesRNA and protein synthesis mechanismsMachine Learning in BioinformaticsAnnotationComputer scienceSoftwarePipeline (software)Modular designGenome projectGene AnnotationGenomeExtensibilityPipeline transport

MeSH terms

SoftwareMolecular Sequence Annotation

Funding

  • National Science Foundation
  • U.S. Department of Energy
  • National Aeronautics and Space Administration
  • NASA Astrobiology Institute
  • National Institutes of Health
  • Science Mission Directorate
  • National Institute of Allergy and Infectious Diseases
Citations
2,826
FWCI
45.19
field-weighted impact
References
39
Percentile
100%
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Citations per year
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