title: Searching for virus phylotypes.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
  
  
  BACKGROUND
  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.
authors: Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr
authors: François
authors: F
authors: Chevenet
authors: Matthieu
authors: M
authors: Jung
authors: Martine
authors: M
authors: Peeters
authors: Tulio
authors: T
authors: de Oliveira
authors: Olivier
authors: O
authors: Gascuel
mesh_terms: D000465:Algorithms; D015658:HIV Infections / Q000453:epidemiology / Q000821:virology; D015497:HIV-1 / Q000145:classification / Q000302:isolation & purification; D006801:Humans; D020407:Internet; D010802:Phylogeny; D012984:Software; D014780:Viruses / Q000145:classification* / Q000235:genetics