ViCTree: an automated framework for taxonomic classification from protein sequences

• Published in: Bioinformatics Vol. 34; no. 13; pp. 2195 - 2200
• Main Authors: Modha, Sejal, Thanki, Anil S, Cotmore, Susan F, Davison, Andrew J, Hughes, Joseph
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.07.2018
• Subjects: Amino Acid Sequence; Databases, Factual; Original Papers; Phylogeny; Sequence Analysis, Protein - methods; Software; Viral Proteins - chemistry; Viral Proteins - genetics; Viral Proteins - metabolism; Viruses - genetics; Viruses - metabolism
• DOI: 10.1093/bioinformatics/bty099
• ISSN: 1367-4803; 1367-4811

Abstract 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 visualization 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 and implementation 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 http://bioinformatics.cvr.ac.uk/victree_web/. Supplementary information Supplementary data are available at Bioinformatics online.