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Related Experiment Videos

Very fast algorithms for evaluating the stability of ML and Bayesian phylogenetic trees from sequence data.

Peter J Waddell1, Hirohisa Kishino, Rissa Ota

  • 1Department of Statistics and Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA. waddell@stat.sc.edu

Genome Informatics. International Conference on Genome Informatics
|October 23, 2003
PubMed
Summary

The RELL method offers a fast and accurate approximation for assessing evolutionary tree uncertainty, outperforming some bootstrap methods. This approach improves Bayesian posterior probability estimates, especially when models break down, making tree inference more reliable.

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Area of Science:

  • Phylogenetics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Evolutionary trees are crucial for sequence analysis, homology searches, and structural modeling.
  • Assessing stochastic error in tree estimation is vital, but computationally intensive methods like bootstrapping are often prohibitive.
  • Existing methods struggle with accuracy and speed for large datasets or complex evolutionary models.

Purpose of the Study:

  • To evaluate the performance of the resampling of estimated log likelihoods (RELL) method for evolutionary tree uncertainty assessment.
  • To improve the accuracy of Bayesian posterior probability (BPP) estimates by refining the BIC approximation.
  • To investigate the impact of model breakdown on tree inference and propose solutions using resampling techniques.

Main Methods:

Related Experiment Videos

  • Comparison of the RELL method against bootstrap (BP) methods for tree proportion approximation.
  • Enhancement of the Bayesian Information Criterion (BIC) approximation for BPP using information matrix determinants.
  • Analysis of mammalian mitochondrial amino acid sequences to assess model breakdown effects.
  • Exploration of incorporating bootstrap and other resampling methods with Markov Chain Monte Carlo (MCMC) procedures.

Main Results:

  • RELL approximates bootstrap proportions effectively and is computationally faster than traditional bootstrapping.
  • The refined BIC approximation yields BPP estimates closely matching MCMC results.
  • Model breakdown in deep evolutionary time leads to overly peaked BPP values, necessitating alternative approaches.
  • BP and BPP estimates can remain reliable indicators of the species tree even with site-specific evolutionary processes.

Conclusions:

  • The RELL method provides a computationally efficient and accurate alternative for assessing evolutionary tree uncertainty.
  • Improved BPP estimation methods enhance the reliability of phylogenetic inference, particularly under model misspecification.
  • Integrating resampling techniques with MCMC offers robust solutions for phylogenetic analysis in the face of evolutionary complexities.