StrainHub: a phylogenetic tool to construct pathogen transmission networks

Author:

de Bernardi Schneider Adriano1ORCID,Ford Colby T2,Hostager Reilly1,Williams John2,Cioce Michael2,Çatalyürek Ümit V3,Wertheim Joel O1,Janies Daniel2

Affiliation:

1. Department of Medicine, University of California, San Diego, San Diego, CA 92103, USA

2. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA

3. School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA

Abstract

Abstract Summary In exploring the epidemiology of infectious diseases, networks have been used to reconstruct contacts among individuals and/or populations. Summarizing networks using pathogen metadata (e.g. host species and place of isolation) and a phylogenetic tree is a nascent, alternative approach. In this paper, we introduce a tool for reconstructing transmission networks in arbitrary space from phylogenetic information and metadata. Our goals are to provide a means of deriving new insights and infection control strategies based on the dynamics of the pathogen lineages derived from networks and centrality metrics. We created a web-based application, called StrainHub, in which a user can input a phylogenetic tree based on genetic or other data along with characters derived from metadata using their preferred tree search method. StrainHub generates a transmission network based on character state changes in metadata, such as place or source of isolation, mapped on the phylogenetic tree. The user has the option to calculate centrality metrics on the nodes including betweenness, closeness, degree and a new metric, the source/hub ratio. The outputs include the network with values for metrics on its nodes and the tree with characters reconstructed. All of these results can be exported for further analysis. Availability and implementation strainhub.io and https://github.com/abschneider/StrainHub.

Funder

National Institutes of Health (NIH) National Institute of Allergy and Infectious Diseases

Department of Bioinformatics and Genomics, the College of Computing and Informatics and the Graduate School

University of North Carolina at Charlotte

Defense Threat Reduction Agency

NIH

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference21 articles.

1. outbreaker2: a modular platform for outbreak reconstruction;Campbell;BMC Bioinformatics,2018

2. The igraph software package for complex network research;Csardi;InterJournal Complex Syst,2006

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