Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/137227
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Type: Journal article
Title: Pharokka: a fast scalable bacteriophage annotation tool
Author: Bouras, G.
Nepal, R.
Houtak, G.
Psaltis, A.J.
Wormald, P.-J.
Vreugde, S.
Citation: Bioinformatics, 2023; 39(1):1-4
Publisher: Oxford University Press (OUP)
Issue Date: 2023
ISSN: 1367-4803
1367-4811
Editor: Marschall, T.
Statement of
Responsibility: 
George Bouras, Roshan Nepal, Ghais Houtak, Alkis James Psaltis, Peter-John Wormald, and Sarah Vreugde
Abstract: Summary: In recent years, there has been an increasing interest in bacteriophages, which has led to growing numbers of bacteriophage genomic sequences becoming available. Consequently, there is a need for a rapid and consistent genomic annotation tool dedicated for bacteriophages. Existing tools either are not designed specifically for bacteriophages or are web- and email-based and require significant manual curation, which makes their integration into bioinformatic pipelines challenging. Pharokka was created to provide a tool that annotates bacteriophage genomes easily, rapidly and consistently with standards compliant outputs. Moreover, Pharokka requires only two lines of code to install and use and takes under 5 min to run for an average 50-kb bacteriophage genome. Availability and implementation: Pharokka is implemented in Python and is available as a bioconda package using ‘conda install -c bioconda pharokka’. The source code is available on GitHub (https://github.com/gbouras13/phar okka). Pharokka has been tested on Linux-64 and MacOSX machines and on Windows using a Linux Virtual Machine.
Keywords: Bacteriophages
Computational Biology
Genomics
Genome
Software
Rights: © The Author(s) 2022. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1093/bioinformatics/btac776
Grant ID: http://purl.org/au-research/grants/nhmrc/1196832
Published version: http://dx.doi.org/10.1093/bioinformatics/btac776
Appears in Collections:Medicine publications

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