| Literature DB >> 31418766 |
Adriano de Bernardi Schneider1, Colby T Ford2, Reilly Hostager1, John Williams2, Michael Cioce2, Ümit V Çatalyürek3, Joel O Wertheim1, Daniel Janies2.
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.Entities:
Mesh:
Year: 2020 PMID: 31418766 PMCID: PMC8215912 DOI: 10.1093/bioinformatics/btz646
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937