A novel methodology for large-scale phylogeny partition

  • Mcf Prosperi
  • , M Ciccozzi
  • , Iuri Fanti
  • , F Saladini
  • , Mauro Pecorari
  • , Vando Borghi
  • , Simona Di Giambenedetto
  • , B Bruzzone
  • , A Capetti
  • , A Vivarelli
  • , S Rusconi
  • , Mc Re
  • , Gismondo
  • , L Sighinolfi
  • , Rr Gray
  • , M Salemi
  • , M Zazzi
  • , Andrea De Luca

Risultato della ricerca: Contributo in rivistaArticolo

Abstract

Understanding the determinants of virus transmission is a fundamental step for effective design of screening and intervention strategies to control viral epidemics. Phylogenetic analysis can be a valid approach for the identification of transmission chains, and very-large data sets can be analysed through parallel computation. Here we propose and validate a new methodology for the partition of large-scale phylogenies and the inference of transmission clusters. This approach, on the basis of a depth-first search algorithm, conjugates the evaluation of node reliability, tree topology and patristic distance analysis. The method has been applied to identify transmission clusters of a phylogeny of 11,541 human immunodeficiency virus-1 subtype B pol gene sequences from a large Italian cohort. Molecular transmission chains were characterized by means of different clinical/demographic factors, such as the interaction between male homosexuals and male heterosexuals. Our method takes an advantage of a flexible notion of transmission cluster and can become a general framework to analyse other epidemics.
Lingua originaleInglese
pagine (da-a)321-321
Numero di pagine1
RivistaNature Communications
Volume2
DOI
Stato di pubblicazionePubblicato - 2011

OSS delle Nazioni Unite

Questo processo contribuisce al raggiungimento dei seguenti obiettivi di sviluppo sostenibile

  1. SDG 3 - Salute e benessere
    SDG 3 Salute e benessere

Keywords

  • Algorithms
  • Classification
  • Female
  • Gene Products, pol
  • HIV Infections
  • HIV-1
  • Humans
  • Male
  • Phylogeny

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