University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Microbiology & Immunology
  • Microbiology & Immunology - Research Publications
  • View Item
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Microbiology & Immunology
  • Microbiology & Immunology - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Differences in Performance among Test Statistics for Assessing Phylogenomic Model Adequacy

    Thumbnail
    Download
    Published version (1.016Mb)

    Citations
    Scopus
    Web of Science
    Altmetric
    2
    3
    Author
    Duchene, DA; Duchene, S; Ho, SYW
    Date
    2018-06-01
    Source Title
    Genome Biology and Evolution
    Publisher
    OXFORD UNIV PRESS
    University of Melbourne Author/s
    Duchene Garzon, Sebastian
    Affiliation
    Microbiology and Immunology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Duchene, D. A., Duchene, S. & Ho, S. Y. W. (2018). Differences in Performance among Test Statistics for Assessing Phylogenomic Model Adequacy. GENOME BIOLOGY AND EVOLUTION, 10 (6), pp.1375-1388. https://doi.org/10.1093/gbe/evy094.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/255143
    DOI
    10.1093/gbe/evy094
    Abstract
    Statistical phylogenetic analyses of genomic data depend on models of nucleotide or amino acid substitution. The adequacy of these substitution models can be assessed using a number of test statistics, allowing the model to be rejected when it is found to provide a poor description of the evolutionary process. A potentially valuable use of model-adequacy test statistics is to identify when data sets are likely to produce unreliable phylogenetic estimates, but their differences in performance are rarely explored. We performed a comprehensive simulation study to identify test statistics that are sensitive to some of the most commonly cited sources of phylogenetic estimation error. Our results show that, for many test statistics, traditional thresholds for assessing model adequacy can fail to reject the model when the phylogenetic inferences are inaccurate and imprecise. This is particularly problematic when analysing loci that have few informative sites. We propose new thresholds for assessing substitution model adequacy and demonstrate their effectiveness in analyses of three phylogenomic data sets. These thresholds lead to frequent rejection of the model for loci that yield topological inferences that are imprecise and are likely to be inaccurate. We also propose the use of a summary statistic that provides a practical assessment of overall model adequacy. Our approach offers a promising means of enhancing model choice in genome-scale data sets, potentially leading to improvements in the reliability of phylogenomic inference.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [45689]
    • Microbiology & Immunology - Research Publications [1555]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors