A novel methodology for large-scale phylogeny partition

Mattia C.F. Prosperi (), Massimo Ciccozzi, Iuri Fanti, Francesco Saladini, Monica Pecorari, Vanni Borghi, Simona Di Giambenedetto, Bianca Bruzzone, Amedeo Capetti, Angela Vivarelli, Stefano Rusconi, Maria Carla Re, Maria Rita Gismondo, Laura Sighinolfi, Rebecca R. Gray, Marco Salemi, Maurizio Zazzi and Andrea De Luca
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Mattia C.F. Prosperi: Clinic of Infectious Diseases, Catholic University of the Sacred Heart
Massimo Ciccozzi: Istituto Superiore di Sanità
Iuri Fanti: Clinic of Infectious Diseases, Catholic University of the Sacred Heart
Francesco Saladini: Section of Microbiology, University of Siena
Monica Pecorari: Modena Hospital
Vanni Borghi: Infectious Diseases Clinic, Modena Hospital
Simona Di Giambenedetto: Clinic of Infectious Diseases, Catholic University of the Sacred Heart
Bianca Bruzzone: Hygiene Unit, S. Martino Hospital
Amedeo Capetti: L. Sacco Hospital, University of Milan
Angela Vivarelli: Infectious Diseases Clinic, Pistoia Hospital
Stefano Rusconi: Section of Infectious Diseases and Immunopathology, L. Sacco Hospital, University of Milan
Maria Carla Re: Section of Microbiology, University of Bologna
Maria Rita Gismondo: Microbiology Laboratory, L. Sacco Hospital, University of Milan
Laura Sighinolfi: S. Anna Hospital
Rebecca R. Gray: Immunology and Laboratory Medicine, College of Medicine, Emerging pathogens Institute, University of Florida, PO BOX 103633, Gainesville, Florida, USA.
Marco Salemi: Immunology and Laboratory Medicine, College of Medicine, Emerging pathogens Institute, University of Florida, PO BOX 103633, Gainesville, Florida, USA.
Maurizio Zazzi: Section of Microbiology, University of Siena
Andrea De Luca: Clinic of Infectious Diseases, Catholic University of the Sacred Heart

Nature Communications, 2011, vol. 2, issue 1, 1-10

Abstract: Phylogenetic analysis is used to identify transmission chains, but no software is available for the automated partition of large phylogenies. Prosperiet al. apply a new search algorithm to identify transmission clusters within the phylogeny of HIV-1gene sequences linking molecular and epidemiological data.

Date: 2011
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DOI: 10.1038/ncomms1325

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