IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0287350.html
   My bibliography  Save this article

Geodesics to characterize the phylogenetic landscape

Author

Listed:
  • Marzieh Khodaei
  • Megan Owen
  • Peter Beerli

Abstract

Phylogenetic trees are fundamental for understanding evolutionary history. However, finding maximum likelihood trees is challenging due to the complexity of the likelihood landscape and the size of tree space. Based on the Billera-Holmes-Vogtmann (BHV) distance between trees, we describe a method to generate intermediate trees on the shortest path between two trees, called pathtrees. These pathtrees give a structured way to generate and visualize part of treespace. They allow investigating intermediate regions between trees of interest, exploring locally optimal trees in topological clusters of treespace, and potentially finding trees of high likelihood unexplored by tree search algorithms. We compared our approach against other tree search tools (Paup*, RAxML, and RevBayes) using the highest likelihood trees and number of new topologies found, and validated the accuracy of the generated treespace. We assess our method using two datasets. The first consists of 23 primate species (CytB, 1141 bp), leading to well-resolved relationships. The second is a dataset of 182 milksnakes (CytB, 1117 bp), containing many similar sequences and complex relationships among individuals. Our method visualizes the treespace using log likelihood as a fitness function. It finds similarly optimal trees as heuristic methods and presents the likelihood landscape at different scales. It found relevant trees that were not found with MCMC methods. The validation measures indicated that our method performed well mapping treespace into lower dimensions. Our method complements heuristic search analyses, and the visualization allows the inspection of likelihood terraces and exploration of treespace areas not visited by heuristic searches.

Suggested Citation

  • Marzieh Khodaei & Megan Owen & Peter Beerli, 2023. "Geodesics to characterize the phylogenetic landscape," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-19, June.
    • Handle: RePEc:plo:pone00:0287350
    DOI: 10.1371/journal.pone.0287350
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287350
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0287350&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0287350?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Roger Shepard, 1962. "The analysis of proximities: Multidimensional scaling with an unknown distance function. II," Psychometrika, Springer;The Psychometric Society, vol. 27(3), pages 219-246, September.
    2. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    3. Roger Shepard, 1962. "The analysis of proximities: Multidimensional scaling with an unknown distance function. I," Psychometrika, Springer;The Psychometric Society, vol. 27(2), pages 125-140, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roger Shepard, 1974. "Representation of structure in similarity data: Problems and prospects," Psychometrika, Springer;The Psychometric Society, vol. 39(4), pages 373-421, December.
    2. Venera Tomaselli, 1996. "Multivariate statistical techniques and sociological research," Quality & Quantity: International Journal of Methodology, Springer, vol. 30(3), pages 253-276, August.
    3. Bijmolt, T.H.A. & Wedel, M., 1996. "A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods," Other publications TiSEM f72cc9d8-f370-43aa-a224-4, Tilburg University, School of Economics and Management.
    4. Phipps Arabie & J. Carroll, 1980. "Mapclus: A mathematical programming approach to fitting the adclus model," Psychometrika, Springer;The Psychometric Society, vol. 45(2), pages 211-235, June.
    5. Dionisios Koutsantonis & Konstantinos Koutsantonis & Nikolaos P. Bakas & Vagelis Plevris & Andreas Langousis & Savvas A. Chatzichristofis, 2022. "Bibliometric Literature Review of Adaptive Learning Systems," Sustainability, MDPI, vol. 14(19), pages 1-18, October.
    6. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    7. Morales José F. & Song Tingting & Auerbach Arleen D. & Wittkowski Knut M., 2008. "Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-20, June.
    8. J. Kruskal, 1964. "Nonmetric multidimensional scaling: A numerical method," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 115-129, June.
    9. Roger Girard & Norman Cliff, 1976. "A monte carlo evaluation of interactive multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 41(1), pages 43-64, March.
    10. repec:plo:pone00:0089091 is not listed on IDEAS
    11. J. Ramsay, 1969. "Some statistical considerations in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 34(2), pages 167-182, June.
    12. Massimiliano Agovino & Maria Ferrara & Antonio Garofalo, 2017. "The driving factors of separate waste collection in Italy: a multidimensional analysis at provincial level," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(6), pages 2297-2316, December.
    13. Jerzy Grobelny & Rafal Michalski & Gerhard-Wilhelm Weber, 2021. "Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic," WORking papers in Management Science (WORMS) WORMS/21/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    14. Bijmolt, T.H.A. & Wedel, M., 1996. "A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods," Research Memorandum 725, Tilburg University, School of Economics and Management.
    15. Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 323-340, December.
    16. Raffaella Piccarreta, 2012. "Graphical and Smoothing Techniques for Sequence Analysis," Sociological Methods & Research, , vol. 41(2), pages 362-380, May.
    17. Xiaomeng Cao & Yuan Gao & Jingwei Cui & Shuangbiao Han & Lei Kang & Sha Song & Chengshan Wang, 2020. "Pore Characteristics of Lacustrine Shale Oil Reservoir in the Cretaceous Qingshankou Formation of the Songliao Basin, NE China," Energies, MDPI, vol. 13(8), pages 1-25, April.
    18. Pepermans, Roland & Verleye, Gino, 1998. "A unified Europe? How euro-attitudes relate to psychological differences between countries," Journal of Economic Psychology, Elsevier, vol. 19(6), pages 681-699, December.
    19. Hossein Safizadeh, M. & McKenna, David R., 1996. "Application of multidimensional scaling techniques to facilities layout," European Journal of Operational Research, Elsevier, vol. 92(1), pages 54-62, July.
    20. He, Jiayi & Shang, Pengjian & Xiong, Hui, 2018. "Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 210-221.
    21. Phipps Arabie, 1991. "Was euclid an unnecessarily sophisticated psychologist?," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 567-587, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0287350. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.