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PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity.
Wymant, Chris; Hall, Matthew; Ratmann, Oliver; Bonsall, David; Golubchik, Tanya; de Cesare, Mariateresa; Gall, Astrid; Cornelissen, Marion; Fraser, Christophe.
Afiliación
  • Wymant C; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
  • Hall M; Department of Infectious Disease Epidemiology, Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.
  • Ratmann O; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
  • Bonsall D; Department of Infectious Disease Epidemiology, Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.
  • Golubchik T; Department of Infectious Disease Epidemiology, Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.
  • de Cesare M; Department of Mathematics, Imperial College London, London, United Kingdom.
  • Gall A; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, United Kingdom.
  • Cornelissen M; Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine and the NIHR Oxford BRC, University of Oxford, United Kingdom.
  • Fraser C; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, United Kingdom.
Mol Biol Evol ; 35(3): 719-733, 2018 Mar 01.
Article en En | MEDLINE | ID: mdl-29186559
ABSTRACT
A central feature of pathogen genomics is that different infectious particles (virions and bacterial cells) within an infected individual may be genetically distinct, with patterns of relatedness among infectious particles being the result of both within-host evolution and transmission from one host to the next. Here, we present a new software tool, phyloscanner, which analyses pathogen diversity from multiple infected hosts. phyloscanner provides unprecedented resolution into the transmission process, allowing inference of the direction of transmission from sequence data alone. Multiply infected individuals are also identified, as they harbor subpopulations of infectious particles that are not connected by within-host evolution, except where recombinant types emerge. Low-level contamination is flagged and removed. We illustrate phyloscanner on both viral and bacterial pathogens, namely HIV-1 sequenced on Illumina and Roche 454 platforms, HCV sequenced with the Oxford Nanopore MinION platform, and Streptococcus pneumoniae with sequences from multiple colonies per individual. phyloscanner is available from https//github.com/BDI-pathogens/phyloscanner.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2018 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Mol Biol Evol Asunto de la revista: BIOLOGIA MOLECULAR Año: 2018 Tipo del documento: Article País de afiliación: Reino Unido