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Phylodynamic Model Adequacy Using Posterior Predictive Simulations

Abstract Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is neces... Full description

Journal Title: Systematic biology 2019, Vol.68 (2), p.358-364
Main Author: Duchene, Sebastian
Other Authors: Bouckaert, Remco , Duchene, David A , Stadler, Tanja , Drummond, Alexei J
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: England: Oxford University Press
ID: ISSN: 1063-5157
Link: https://www.ncbi.nlm.nih.gov/pubmed/29945220
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6368481
title: Phylodynamic Model Adequacy Using Posterior Predictive Simulations
format: Article
creator:
  • Duchene, Sebastian
  • Bouckaert, Remco
  • Duchene, David A
  • Stadler, Tanja
  • Drummond, Alexei J
subjects:
  • Bayesian phylogenetics
  • BEAST2
  • Computer Simulation
  • Ebolavirus - classification
  • Ebolavirus - genetics
  • Evolution
  • Genome, Viral - genetics
  • Hemorrhagic Fever, Ebola - epidemiology
  • Hemorrhagic Fever, Ebola - virology
  • Humans
  • Influenza A Virus, H1N1 Subtype - classification
  • Influenza A Virus, H1N1 Subtype - genetics
  • Influenza, Human - epidemiology
  • Influenza, Human - virology
  • model adequacy
  • phylodynamics
  • Phylogeny
  • posterior predictive simulation
  • Software
  • Software for Systematics
  • Software for Systematics and Evolution
  • viral evolution
  • virus diseases
  • viruses
ispartof: Systematic biology, 2019, Vol.68 (2), p.358-364
description: Abstract Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy, a package for the popular BEAST2 software that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analyzing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data were best described by the birth–death susceptible-infected-recovered model.
language: eng
source:
identifier: ISSN: 1063-5157
fulltext: no_fulltext
issn:
  • 1063-5157
  • 1076-836X
url: Link


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descriptionAbstract Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy, a package for the popular BEAST2 software that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analyzing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data were best described by the birth–death susceptible-infected-recovered model.
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subjectBayesian phylogenetics ; BEAST2 ; Computer Simulation ; Ebolavirus - classification ; Ebolavirus - genetics ; Evolution ; Genome, Viral - genetics ; Hemorrhagic Fever, Ebola - epidemiology ; Hemorrhagic Fever, Ebola - virology ; Humans ; Influenza A Virus, H1N1 Subtype - classification ; Influenza A Virus, H1N1 Subtype - genetics ; Influenza, Human - epidemiology ; Influenza, Human - virology ; model adequacy ; phylodynamics ; Phylogeny ; posterior predictive simulation ; Software ; Software for Systematics ; Software for Systematics and Evolution ; viral evolution ; virus diseases ; viruses
ispartofSystematic biology, 2019, Vol.68 (2), p.358-364
rightsThe Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. 2018
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descriptionAbstract Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy, a package for the popular BEAST2 software that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analyzing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data were best described by the birth–death susceptible-infected-recovered model.
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6Genome, Viral - genetics
7Hemorrhagic Fever, Ebola - epidemiology
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11Influenza A Virus, H1N1 Subtype - genetics
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abstractAbstract Rapidly evolving pathogens, such as viruses and bacteria, accumulate genetic change at a similar timescale over which their epidemiological processes occur, such that, it is possible to make inferences about their infectious spread using phylogenetic time-trees. For this purpose it is necessary to choose a phylodynamic model. However, the resulting inferences are contingent on whether the model adequately describes key features of the data. Model adequacy methods allow formal rejection of a model if it cannot generate the main features of the data. We present TreeModelAdequacy, a package for the popular BEAST2 software that allows assessing the adequacy of phylodynamic models. We illustrate its utility by analyzing phylogenetic trees from two viral outbreaks of Ebola and H1N1 influenza. The main features of the Ebola data were adequately described by the coalescent exponential-growth model, whereas the H1N1 influenza data were best described by the birth–death susceptible-infected-recovered model.
copEngland
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pmid29945220
doi10.1093/sysbio/syy048
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