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.
A novel methodology for large-scale phylogeny partition / M.C.F. Prosperi, M. Ciccozzi, I. Fanti, F. Saladini, M. Pecorari, V. Borghi, S. Di Giambenedetto, B. Bruzzone, A. Capetti, A. Vivarelli, S. Rusconi, M.C. Re, M.R. Gismondo, L. Sighinolfi, R. R. Gray, M. Salemi, M. Zazzi, A. De Luca on behalf of the ARCA collaborative group. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 2:1(2011 May 24), pp. 321.321.1-321.321.10.
A novel methodology for large-scale phylogeny partition
S. Rusconi;M.R. Gismondo;
2011
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.File | Dimensione | Formato | |
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