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Related Experiment Videos

Multiple sequence alignment in phylogenetic analysis.

A Phillips1, D Janies, W Wheeler

  • 1Department of Invertebrates, American Museum of Natural History, Central Park West at 79th Street, New York, New York, 10024-5192, USA.

Molecular Phylogenetics and Evolution
|September 19, 2000
PubMed
Summary
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This study emphasizes optimizing multiple sequence alignment for phylogenetic research by minimizing nonhomology. Consistent application of phylogenetic optimality criteria, treating gaps as data, and sensitivity analysis of cost functions are crucial for robust homology assessments.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Multiple sequence alignment (MSA) is fundamental for assessing homology in phylogenetic research.
  • Existing alignment methods range from exact algorithms to heuristic procedures.
  • The primary goal of alignment is to establish the most accurate representation of initial homology.

Purpose of the Study:

  • To review and evaluate pairwise and multiple sequence alignment methods.
  • To advocate for alignment strategies that minimize nonhomology and maximize phylogenetic optimality.
  • To promote consistency in optimality criteria across phylogenetic analyses.

Main Methods:

  • Review of exact and heuristic alignment procedures.
  • Emphasis on treating alignment gaps as informative character data.
Keywords:
Non-programmatic

Related Experiment Videos

  • Application of sensitivity analysis to cost function assumptions (e.g., insertion-deletion, transversions, transitions).

    • Main Results:

    • Alignment methods minimizing nonhomology are favored for accurate homology statements.
    • Phylogenetic optimality criteria should be consistently applied from alignment to phylogeny reconstruction.
    • Sensitivity analysis of cost functions is essential for testing the robustness of alignment and phylogenetic results.

    Conclusions:

    • Consistent homology assessment requires treating gaps as data and using robust cost functions.
    • Parameter variation and sensitivity analysis enhance the reliability of phylogenetic reconstructions.
    • The principle of consistency between assumptions and analysis should extend to methods beyond parsimony, including maximum likelihood.