Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Phylogenetic tree shapes resolve disease transmission patterns

Caroline Colijn, Jennifer Gardy
doi: https://doi.org/10.1101/003194
Caroline Colijn
1Department of Mathematics, Imperial College London, 180 Queen’s Gate London SW7 2AZ ; +44 207 594 2647
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: c.colijn@imperial.ac.uk
Jennifer Gardy
2Communicable Disease Prevention and Control Services, British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver, BC, Canada, V5Z 4R4
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: Jennifer.Gardy@bccdc.ca
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Whole genome sequencing is becoming popular as a tool for understanding outbreaks of communicable diseases, with phylogenetic trees being used to identify individual transmission events or to characterize outbreak-level overall transmission dynamics. Existing methods to infer transmission dynamics from sequence data rely on well-characterised infectious periods, epidemiological and clinical meta-data which may not always be available, and typically require computationally intensive analysis focussing on the branch lengths in phylogenetic trees. We sought to determine whether the topological structures of phylogenetic trees contain signatures of the overall transmission patterns underyling an outbreak. Here we use simulated outbreaks to train and then test computational classifiers. We test the method on data from two real-world outbreaks. We find that different transmission patterns result in quantitatively different phylogenetic tree shapes. We describe five topological features that summarize a phylogeny’s structure and find that computational classifiers based on these are capable of predicting an outbreak’s transmission dynamics. The method is robust to variations in the transmission parameters and network types, and recapitulates known epidemiology of previously characterized real-world outbreaks. We conclude that there are simple structural properties of phylogenetic trees which, when combined, can distinguish communicable disease outbreaks with a super-spreader, homogeneous transmission, and chains of transmission. This is possible using genome data alone, and can be done during an outbreak. We discuss the implications for management of outbreaks.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted March 05, 2014.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Phylogenetic tree shapes resolve disease transmission patterns
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Phylogenetic tree shapes resolve disease transmission patterns
Caroline Colijn, Jennifer Gardy
bioRxiv 003194; doi: https://doi.org/10.1101/003194
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Phylogenetic tree shapes resolve disease transmission patterns
Caroline Colijn, Jennifer Gardy
bioRxiv 003194; doi: https://doi.org/10.1101/003194

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4384)
  • Biochemistry (9609)
  • Bioengineering (7103)
  • Bioinformatics (24896)
  • Biophysics (12632)
  • Cancer Biology (9974)
  • Cell Biology (14372)
  • Clinical Trials (138)
  • Developmental Biology (7966)
  • Ecology (12124)
  • Epidemiology (2067)
  • Evolutionary Biology (16002)
  • Genetics (10936)
  • Genomics (14755)
  • Immunology (9880)
  • Microbiology (23697)
  • Molecular Biology (9490)
  • Neuroscience (50924)
  • Paleontology (370)
  • Pathology (1541)
  • Pharmacology and Toxicology (2686)
  • Physiology (4023)
  • Plant Biology (8674)
  • Scientific Communication and Education (1511)
  • Synthetic Biology (2402)
  • Systems Biology (6444)
  • Zoology (1346)