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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Published on: August 14, 2018

Is multiple-sequence alignment required for accurate inference of phylogeny?

Michael Höhl1, Mark A Ragan

  • 1Australian Research Council Centre in Bioinformatics, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.

Systematic Biology
|April 25, 2007
PubMed
Summary

This study compares alignment-free phylogenetic tree inference methods. Pattern-based approaches generally perform best, though maximum-likelihood methods with multiple sequence alignment remain superior for accuracy.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Phylogenetics

Background:

  • Phylogenetic tree inference typically relies on multiple sequence alignment.
  • Alignment-free methods offer an alternative but their accuracy is less understood.
  • Assessing the performance of various alignment-free phylogenetic inference techniques is crucial.

Purpose of the Study:

  • To conduct a large-scale comparison of ten alignment-free phylogenetic inference methods.
  • To evaluate the accuracy of these methods under varying biological conditions.
  • To identify superior alignment-free approaches and understand their limitations.

Main Methods:

  • Compared ten alignment-free methods, including a new pattern-based variant and a Bayesian k-mer approach.
  • Evaluated methods based on phylogenetic reconstruction accuracy across different datasets and parameters.
  • Analyzed the impact of among-site rate variation and alphabet choice on accuracy.

Main Results:

  • Pattern-based alignment-free methods demonstrated superior reconstruction accuracy compared to other alignment-free techniques.
  • A new pattern-based variant offered significant speed improvements with a minor loss in accuracy.
  • No alignment-free method outperformed maximum-likelihood distance estimates from multiply aligned sequences.

Conclusions:

  • Pattern-based approaches are the most accurate alignment-free methods for phylogenetic inference, despite higher resource demands.
  • Alignment-free methods show potential, but currently do not match the accuracy of alignment-based maximum-likelihood methods.
  • Understanding parameter influences, like word length and alphabet choice, is key for optimizing alignment-free methods.