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PHYLOSCANNER: Inferring transmission from within- and petween-host pathogen genetic diversity.

Abstract:
A central feature of pathogen genomics is that different infectious particles (virions, bacterial cells, etc.) within an infected individual may be genetically distinct, with patterns of relatedness amongst 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 harbour 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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/molbev/msx304

Authors

More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; BDI-NDM
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; Human Genetics Wt Centre
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM; NDM Experimental Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Human Genetics Wt Centre
Role:
Author


Publisher:
Oxford University Press
Journal:
Molecular Biology and Evolution More from this journal
Volume:
35
Issue:
3
Pages:
719–733
Publication date:
2017-11-23
Acceptance date:
2017-11-17
DOI:
EISSN:
1537-1719
ISSN:
0737-4038
Pmid:
29186559


Language:
English
Keywords:
Pubs id:
pubs:807449
UUID:
uuid:b7652459-cbc0-4acf-8906-97f69449bca3
Local pid:
pubs:807449
Source identifiers:
807449
Deposit date:
2018-01-24
ARK identifier:

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