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Sequence length variation, indel costs, and congruence in sensitivity analysis.

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Summary

Congruence measures improve when indels are treated as single events. All measures converge on optimal alignment costs with sufficient data, despite initial disagreements caused by data partition dominance.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Phylogenetics

Background:

  • Sequence alignment is crucial for phylogenetic analysis.
  • Indels (insertions/deletions) present significant challenges in sequence alignment.
  • Evaluating congruence measures helps assess alignment quality.

Purpose of the Study:

  • To investigate the performance of topological and character-based congruence measures.
  • To assess the impact of different indel treatments on congruence.
  • To identify optimal indel cost parameters for sequence alignment.

Main Methods:

  • Analyzed two topological and four character-based congruence measures.
  • Employed direct optimization within a sensitivity analysis framework.
  • Varied indel costs, treating indels as a fifth character state or using linear affine gap costs.

Main Results:

  • Congruence consistently improved when indels were treated as single events.
  • No single congruence measure was consistently superior.
  • All measures converged on the same optimal alignment cost set with sufficient data.
  • Data partition dominance, characterized by length variation, caused initial disagreements.

Conclusions:

  • Treating indels as single events enhances congruence in sequence alignment.
  • Sufficient data integration overcomes disagreements among congruence measures.
  • Data partition dominance can be detected and managed by adjusting indel costs.