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Majority-rule reduced consensus trees and their use in bootstrapping

M Wilkinson1

  • 1School of Biological Sciences, University of Bristol, England. Mark.Wilkinson@bris.ac.uk

Molecular Biology and Evolution
|March 1, 1996
PubMed
Summary
This summary is machine-generated.

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New majority-rule reduced consensus methods offer more informative summaries for bootstrap analyses in phylogenetics. These methods improve the assessment of complex phylogenetic hypotheses by highlighting supported relationships across multiple trees.

Area of Science:

  • Phylogenetics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Traditional bootstrap analyses often use majority-rule consensus trees, which can miss agreement on phylogenetic relationships.
  • Component consensus methods are insensitive to various forms of agreement between trees.

Purpose of the Study:

  • To introduce and describe novel majority-rule reduced consensus methods for phylogenetic analyses.
  • To enhance the summarization of bootstrap analyses and improve the assessment of phylogenetic hypotheses.

Main Methods:

  • Development of strict and majority-rule reduced consensus methods requiring agreement across all compared trees.
  • Illustration of methods using hypothetical and real phylogenetic data examples.
  • Description of techniques to reduce consensus profile size and a posteriori selection of trees.

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Main Results:

  • The new methods summarize bootstrap proportions for all n-taxon statements, identifying relationships with high support.
  • Facilitation of the identification of supported hypotheses even without support for specific components or clades.
  • Introduction of surrogates using partition tables and tree pruning options in phylogenetic software.

Conclusions:

  • Majority-rule reduced consensus methods provide more informative summaries of bootstrap analyses.
  • These methods foster a more informed assessment of the strengths and weaknesses of complex phylogenetic hypotheses.
  • The techniques aid in a comprehensive evaluation of phylogenetic inference results.