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Bootstrap confidence levels for phylogenetic trees

B Efron1, E Halloran, S Holmes

  • 1Department of Statistics, Stanford University, Stanford, CA 94305, USA.

Proceedings of the National Academy of Sciences of the United States of America
|July 9, 1996
PubMed
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This study clarifies the bootstrap method for evolutionary tree confidence. While Felsenstein's approach is not biased, a corrected bootstrap method offers better confidence levels for phylogenetic analyses.

Area of Science:

  • Phylogenetics
  • Computational Biology
  • Evolutionary Genetics

Background:

  • Estimating evolutionary trees from DNA/RNA sequences is crucial.
  • Assessing confidence in these phylogenetic trees is a significant challenge.
  • Felsenstein's bootstrap method (1985) is widely used but criticized for bias.

Purpose of the Study:

  • To evaluate the bias of Felsenstein's bootstrap method in phylogenetic tree estimation.
  • To propose corrections to the bootstrap method for improved confidence assessment.
  • To align bootstrap results with standard statistical confidence levels and hypothesis testing.

Main Methods:

  • Analysis of Felsenstein's bootstrap method for phylogenetic inference.
  • Development and application of a corrected bootstrap approach.

Related Experiment Videos

  • Comparison of corrected bootstrap results against established statistical criteria.

    • Main Results:

    • Felsenstein's bootstrap method for tree confidence is not inherently biased.
    • The proposed corrected bootstrap method improves agreement with standard confidence levels.
    • Enhanced accuracy comes with increased computational cost.

    Conclusions:

    • The bootstrap is a valid tool for assessing confidence in evolutionary trees.
    • A refined bootstrap methodology provides more statistically robust confidence estimates.
    • Researchers can achieve better phylogenetic inference with computational trade-offs.