ViCTree: an automated framework for taxonomic classification from protein sequences

Modha, S. , Thanki, A., Cotmore, S. F., Davison, A. J. and Hughes, J. (2018) ViCTree: an automated framework for taxonomic classification from protein sequences. Bioinformatics, 34(13), pp. 2195-2200. (doi: 10.1093/bioinformatics/bty099) (PMID:29474519) (PMCID:PMC6022645)

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Motivation: The increasing rate of submission of genetic sequences into public databases is providing a growing resource for classifying the organisms that these sequences represent. To aid viral classification, we have developed ViCTree, which automatically integrates the relevant sets of sequences in NCBI GenBank and transforms them into an interactive maximum likelihood phylogenetic tree that can be updated automatically. ViCTree incorporates ViCTreeView, which is a JavaScript-based visualisation tool that enables the tree to be explored interactively in the context of pairwise distance data. Results: To demonstrate utility, ViCTree was applied to subfamily Densovirinae of family Parvoviridae. This led to the identification of six new species of insect virus. Availability: ViCTree is open-source and can be run on any Linux- or Unix-based computer or cluster. A tutorial, the documentation and the source code are available under a GPL3 license, and can be accessed at

Item Type:Articles
Glasgow Author(s) Enlighten ID:Hughes, Dr Joseph and Davison, Professor Andrew and Modha, Ms Sejal
Authors: Modha, S., Thanki, A., Cotmore, S. F., Davison, A. J., and Hughes, J.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:Bioinformatics
Publisher:Oxford University Press
ISSN (Online):1460-2059
Published Online:20 February 2018
Copyright Holders:Copyright © 2018 The Authors
First Published:First published in Bioinformatics 34(13): 2195-2200
Publisher Policy:Reproduced under a Creative Commons License

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