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Annotate Microbial Genome with RASTtk - v1.073


By: chenry, olson


Annotate or re-annotate bacterial or archaeal genome using RASTtk (Rapid Annotations using Subsystems Technology toolkit).

This KBase annotation App (Annotate Microbial Genome) uses components from the RAST (Rapid Annotations using Subsystems Technology) toolkit [1,2,3] to annotate a prokaryotic genome or to update the annotations of a genome.

The release versions of the RASTtk component services used in this app are:

The Annotate Microbial Genome App takes a Genome-typed object as input and allows users to annotate or re-annotate the genome. This will make the annotations consistent with other KBase genomes and prepare the genome for further analysis by other KBase Apps, especially the Metabolic Modeling Apps.

A Genome object can be imported or generated with one of the following annotation Apps or their multi-object versions:

The Default Annotation Pipeline
Clicking "Run" will run the default pipeline. For a typical 2-5 MBp genome, the default annotation pipeline should take about 5 minutes. It is assumed that Genomes already have some annotation. As a result, the default behavior of this App is to use SEED to re-annotate just the protein-encoding genes. The default pipeline for this App consists of the following steps:

Advanced Annotation Options
If you wish to customize the features in your annotation, click the "show advanced options" link. This will display the full set of available annotation options.

The Results

GUI Output
The GUI output currently consists of three tabs. The "Overview" tab provides basic information on the annotation job, the "Browse Features" tab allows the user to scroll through the features that were called, and the "Browse Contigs" tab provides information on the contigs in the genome. Users can sort on the various types of features. Note that some features will overlap (e.g., "prophage" and "CDS").

Additional Information
For more information on the steps of the default RAStk pipeline please refer to our publication on this (publication forthcoming). For more detailed tutorial information and to explore the additional functionality of RASTtk not currently available in the Narrative interface, please refer to

Team members who developed & deployed algorithm in KBase: Thomas Brettin, James Davis, Terry Disz, Robert Edwards, Chris Henry, Gary Olsen, Robert Olson, Ross Overbeek, Bruce Parrello, Gordon Pusch, Roman Sutormin, and Fangfang Xia. For questions, please contact us.

The authors of RAST request that if you use the results of this annotation in your work, please cite the first three listed publications:

Related Publications

App Specification:

Module Commit: 7171090d87fccc8b7ecf1a1d02398995dcc2dd45