Title
Searching for virus phylotypes.
Abstract
Large phylogenies are being built today to study virus evolution, trace the origin of epidemics, establish the mode of transmission and survey the appearance of drug resistance. However, no tool is available to quickly inspect these phylogenies and combine them with extrinsic traits (e.g. geographic location, risk group, presence of a given resistance mutation), seeking to extract strain groups of specific interest or requiring surveillance.We propose a new method for obtaining such groups, which we call phylotypes, from a phylogeny having taxa (strains) annotated with extrinsic traits. Phylotypes are subsets of taxa with close phylogenetic relationships and common trait values. The method combines ancestral trait reconstruction using parsimony, with combinatorial and numerical criteria measuring tree shape characteristics and the diversity and separation of the potential phylotypes. A shuffling procedure is used to assess the statistical significance of phylotypes. All algorithms have linear time complexity. This results in low computing times, typically a few minutes for the larger data sets with a number of shuffling steps. Two HIV-1 data sets are analyzed, one of which is large, containing >3000 strains of HIV-1 subtype C collected worldwide, where the method shows its ability to recover known clusters and transmission routes, and to detect new ones.This method and companion tools are implemented in an interactive Web interface (www.phylotype.org), which provides a wide choice of graphical views and output formats, and allows for exploratory analyses of large data sets.
Year
DOI
Venue
2013
10.1093/bioinformatics/btt010
Bioinformatics
Keywords
Field
DocType
virus phylotypes,supplementary data,hiv-1 data set,larger data set,large data set,potential phylotypes,ancestral trait reconstruction,large phylogeny,hiv-1 subtype,extrinsic trait,new method,internet,algorithms,phylogeny
Data mining,Data set,Phylogenetic tree,Trait,Computer science,Shuffling,Bioinformatics,Time complexity,Phylogenetics,User interface,Taxon
Journal
Volume
Issue
ISSN
29
5
1367-4811
Citations 
PageRank 
References 
1
0.59
6
Authors
5
Name
Order
Citations
PageRank
François Chevenet11018.66
Matthieu Jung210.59
Martine Peeters371.28
Tulio de Oliveira4497.79
Olivier Gascuel543376.01