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outbreaker2 : a modular platform for outbreak reconstruction

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Campbell, Finlay, Didelot, Xavier, Fitzjohn, Rich, Ferguson, Neil, Cori, Anne and Jombart, Thibaut (2018) outbreaker2 : a modular platform for outbreak reconstruction. BMC Bioinformatics, 19 (Supplement 11). 363. doi:10.1186/s12859-018-2330-z

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Official URL: http://dx.doi.org/10.1186/s12859-018-2330-z

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Abstract

Background
Reconstructing individual transmission events in an infectious disease outbreak can provide valuable information and help inform infection control policy. Recent years have seen considerable progress in the development of methodologies for reconstructing transmission chains using both epidemiological and genetic data. However, only a few of these methods have been implemented in software packages, and with little consideration for customisability and interoperability. Users are therefore limited to a small number of alternatives, incompatible tools with fixed functionality, or forced to develop their own algorithms at considerable personal effort.

Results
Here we present outbreaker2, a flexible framework for outbreak reconstruction. This R package re-implements and extends the original model introduced with outbreaker, but most importantly also provides a modular platform allowing users to specify custom models within an optimised inferential framework. As a proof of concept, we implement the within-host evolutionary model introduced with TransPhylo, which is very distinct from the original genetic model in outbreaker, and demonstrate how even complex model results can be successfully included with minimal effort.

Conclusions
outbreaker2 provides a valuable starting point for future outbreak reconstruction tools, and represents a unifying platform that promotes customisability and interoperability. Implemented in the R software, outbreaker2 joins a growing body of tools for outbreak analysis.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH): Epidemics -- Mathematical models, Communicable diseases -- Transmission, Epidemiology -- Data processing, Epidemiology -- Statistical methods
Journal or Publication Title: BMC Bioinformatics
Publisher: BioMed Central Ltd.
ISSN: 1471-2105
Official Date: 22 October 2018
Dates:
DateEvent
22 October 2018Published
1 October 2018Accepted
Volume: 19
Number: Supplement 11
Article Number: 363
DOI: 10.1186/s12859-018-2330-z
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDWellcome Trusthttp://dx.doi.org/10.13039/100010269
UNSPECIFIED[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
UNSPECIFIED[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
UNSPECIFIEDNational Institute of General Medical Scienceshttp://dx.doi.org/10.13039/100000057
UNSPECIFIEDBill and Melinda Gates Foundationhttp://dx.doi.org/10.13039/100000865

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