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Related Experiment Videos

Logarithmic gap costs decrease alignment accuracy.

Reed A Cartwright1

  • 1Department of Genetics, University of Georgia, Athens, GA 30602-7223, USA. racartwr@ncsu.edu

BMC Bioinformatics
|December 7, 2006
PubMed
Summary
This summary is machine-generated.

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Logarithmic gap costs perform poorly in sequence alignment, contrary to expectations. Affine gap costs are biologically relevant and produce accurate alignments, supporting current algorithms.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Indel size distributions follow a power law, suggesting logarithmic gap costs for sequence alignment.
  • Logarithmic gap costs were proposed as more biologically realistic than affine gap costs.
  • Affine gap costs are currently favored for their speed and efficiency in global sequence alignment.

Purpose of the Study:

  • To evaluate if logarithmic gap costs significantly improve sequence alignment accuracy over affine gap costs.
  • To determine the biological realism and practical utility of different gap cost models.

Main Methods:

  • Global sequence alignment of simulated sequence pairs using affine, logarithmic, and log-affine gap costs.
  • Alignment accuracy was assessed by comparing generated alignments to known true alignments.

Related Experiment Videos

  • A model was developed to explain the observed performance differences.

    • Main Results:

    • Log-affine gap costs yielded the highest alignment accuracy.
    • Affine gap costs demonstrated strong accuracy, closely following log-affine costs.
    • Logarithmic gap costs performed poorly in comparison.

    Conclusions:

    • Logarithmic gap costs do not improve alignment accuracy and are not implied by power-law indel distributions.
    • Affine gap costs produce accurate alignments and approximate biologically realistic gap costs.
    • This study reinforces the biological relevance of existing sequence alignment algorithms using affine gap costs.