Employing phylogenetic tree shape statistics to resolve the underlying host population structure.

Journal: BMC bioinformatics
Published Date: Nov 10, 2021

Abstract

BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a population is structured or not is useful in informing the type of phylogenetic methods to be used in a given study. We employ tree statistics derived from phylogenetic trees and machine learning classification techniques to reveal an underlying population structure.

Authors

  • Hassan W Kayondo
    Institute of Basic Sciences, Technology and Innovation (PAUSTI), Pan African University, Nairobi, Kenya. whkayondo@gmail.com.
  • Alfred Ssekagiri
    Uganda Virus Research Institute (UVRI), Entebbe, Uganda.
  • Grace Nabakooza
    Department of Immunology and Molecular Biology, Makerere University, Kampala, Uganda.
  • Nicholas Bbosa
    Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe, Uganda.
  • Deogratius Ssemwanga
    Uganda Virus Research Institute (UVRI), Entebbe, Uganda.
  • Pontiano Kaleebu
    Uganda Virus Research Institute (UVRI), Entebbe, Uganda.
  • Samuel Mwalili
    Department of Statistics and Actuarial Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.
  • John M Mango
    Department of Mathematics, Makerere University, Kampala, Uganda.
  • Andrew J Leigh Brown
    Institute of Evolutionary Biology, University of Edinburg, Edinburg, UK.
  • Roberto A Saenz
    Facultad de Ciencias, Universidad de Colima, Colima, Mexico.
  • Ronald Galiwango
    Centre for Computational Biology, Uganda Christian University, Mukono, Uganda.
  • John M Kitayimbwa
    Centre for Computational Biology, Uganda Christian University, Mukono, Uganda.

Keywords

External Resources

Popular Topics
Recent Journals