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Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks
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Didelot, Xavier, Fraser, Christophe, Gardy, Jennifer and Colijn, Caroline (2017) Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks. Molecular Biology and Evolution, 34 (4). pp. 997-1007. doi:10.1093/molbev/msw275 ISSN 0737-4038.
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Official URL: http://dx.doi.org/10.1093/molbev/msw275
Abstract
Genomic data are increasingly being used to understand infectious disease epidemiology. Isolates from a given outbreak are sequenced, and the patterns of shared variation are used to infer which isolates within the outbreak are most closely related to each other. Unfortunately, the phylogenetic trees typically used to represent this variation are not directly informative about who infected whom—a phylogenetic tree is not a transmission tree. However, a transmission tree can be inferred from a phylogeny while accounting for within-host genetic diversity by coloring the branches of a phylogeny according to which host those branches were in. Here we extend this approach and show that it can be applied to partially sampled and ongoing outbreaks. This requires computing the correct probability of an observed transmission tree and we herein demonstrate how to do this for a large class of epidemiological models. We also demonstrate how the branch coloring approach can incorporate a variable number of unique colors to represent unsampled intermediates in transmission chains. The resulting algorithm is a reversible jump Monte–Carlo Markov Chain, which we apply to both simulated data and real data from an outbreak of tuberculosis. By accounting for unsampled cases and an outbreak which may not have reached its end, our method is uniquely suited to use in a public health environment during real-time outbreak investigations. We implemented this transmission tree inference methodology in an R package called TransPhylo, which is freely available from https://github.com/xavierdidelot/TransPhylo.
Item Type: | Journal Article | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | ||||||
Journal or Publication Title: | Molecular Biology and Evolution | ||||||
Publisher: | Oxford University Press | ||||||
ISSN: | 0737-4038 | ||||||
Official Date: | 1 April 2017 | ||||||
Dates: |
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Volume: | 34 | ||||||
Number: | 4 | ||||||
Page Range: | pp. 997-1007 | ||||||
DOI: | 10.1093/molbev/msw275 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
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