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A Practical Guide to Phylogenetics for Nonexperts
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Published on: February 5, 2014

A hierarchical model for incomplete alignments in phylogenetic inference.

Fuxia Cheng1, Stefanie Hartmann, Mayetri Gupta

  • 1Department of Mathematics, Illinois State University, Normal, IL, USA.

Bioinformatics (Oxford, England)
|January 17, 2009
PubMed
Summary

This study introduces a Bayesian statistical method to accurately infer phylogenetic trees from incomplete multiple sequence alignments (MSAs) derived from expressed sequence tags (ESTs). The new approach improves the accuracy of evolutionary relationship estimations despite missing data challenges.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Multiple sequence alignments (MSAs) are crucial for inferring evolutionary relationships.
  • Expressed sequence tags (ESTs) are common but introduce significant missing data into MSAs.
  • Missing data in EST-derived MSAs compromises the accuracy of phylogenetic tree inference.

Purpose of the Study:

  • To develop a statistical method for accurate phylogenetic tree inference from incomplete MSAs, particularly those derived from ESTs.
  • To address the challenge of missing data in sequence alignments for evolutionary analyses.

Main Methods:

  • A Bayesian statistical framework utilizing hierarchical models to estimate pairwise distances between sequences.
  • Development of a fully Bayesian approach for parameter estimation in phylogenetic modeling.
  • Application of neighbor-joining or other algorithms to construct phylogenetic trees from the estimated distance matrix.

Main Results:

  • The proposed Bayesian method effectively infers phylogenetic trees from incomplete, EST-based MSA data.
  • Maximizing marginal likelihood in the Bayesian approach provides results comparable to profile likelihood estimation.
  • The method's performance was validated using simulated protein families with known phylogenies and one real protein family.

Conclusions:

  • The developed Bayesian method offers a robust solution for phylogenetic inference with incomplete sequence data.
  • This approach enhances the reliability of evolutionary relationship estimations when using ESTs.
  • The R code for fitting these models is publicly available for broader application.