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DISTREE: a tool for estimating genetic distances between aligned DNA sequences

J Schäfer1, M Schöniger

  • 1Technical University Munich, Garching, Germany. schaefer@theochem.tu-muenchen.de

Computer Applications in the Biosciences : CABIOS
|August 1, 1997
PubMed
Summary

This study introduces a program for estimating DNA substitution rates using various Markov models. It aids in selecting the best evolutionary model and reconstructing phylogenetic trees for accurate sequence relationship analysis.

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Area of Science:

  • Molecular Evolution
  • Bioinformatics
  • Computational Biology

Background:

  • Genetic distances derived from DNA substitution rates are crucial for understanding phylogenetic relationships.
  • Accurate phylogenetic inference necessitates assuming an appropriate Markov model of nucleotide substitution.

Purpose of the Study:

  • To present a computational tool for estimating DNA substitution rates and their standard errors.
  • To facilitate the selection of the most suitable Markov model for analyzing evolutionary data.
  • To enable the reconstruction of phylogenetic trees based on estimated genetic distances.

Main Methods:

  • Implementation of a variety of Markov models for nucleotide substitution, including rate homogeneity and Gamma-distributed rates.
  • Numerical calculation of distances and standard deviations for the Hasegawa et al. (1985) model.

Related Experiment Videos

  • Estimation of heterogeneous substitution rates using the Tamura and Nei (1993) method.
  • Automated parameter estimation directly from sequence data.
  • Model fit analysis to guide model selection.
  • Neighbor-joining algorithm for phylogenetic tree reconstruction.

    • Main Results:

    • A versatile program is available for estimating substitution rates and standard errors across multiple Markov models.
    • The program supports both homogeneous and heterogeneous (Gamma-distributed) substitution rates.
    • It provides tools for model selection and phylogenetic tree construction, simplifying evolutionary analysis.

    Conclusions:

    • The developed program offers a comprehensive solution for estimating evolutionary parameters and inferring phylogenetic relationships.
    • It empowers researchers to select appropriate models and visualize evolutionary history with greater accuracy.
    • The software streamlines the process of phylogenetic analysis by automating parameter estimation and model selection.