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An algorithm for Morphological Phylogenetic Analysis with Inapplicable Data.

Martin D Brazeau1,2, Thomas Guillerme1,3, Martin R Smith4,5

  • 1Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK.

Systematic Biology
|December 12, 2018
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Summary
This summary is machine-generated.

This study introduces a new algorithm for phylogenetic analysis using morphological data. It addresses issues with inapplicable characters in reductive coding, improving ancestral state reconstruction and evolutionary history inference.

Keywords:
Character independencecharacter optimizationcladistic analysisinapplicable dataphylogenetic tree search

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Area of Science:

  • Evolutionary biology
  • Systematics
  • Computational biology

Background:

  • Morphological data are crucial for understanding evolutionary relationships and the fossil record.
  • Hierarchical interdependence of characters and inapplicable states complicate phylogenetic analyses.
  • Reductive coding, treating inapplicable characters as missing, can lead to inaccurate tree length estimates and phylogenetic results.

Purpose of the Study:

  • To present a novel single-character algorithm for reconstructing ancestral states in reductively coded morphological datasets.
  • To address the limitations of traditional methods in handling inapplicable characters.
  • To improve the accuracy of phylogenetic inference and evolutionary history reconstruction.

Main Methods:

  • Developed a single-character algorithm for ancestral state reconstruction.
  • Employed local optimization for efficiency, enabling application to single characters.
  • Utilized up to four tree traversals for scoring and resolving states, with explicit criteria for ambiguity resolution.
  • Focused on minimizing homoplasy across all characters.

Main Results:

  • The algorithm provides a fast, approximate inference of ancestral states and tree scores.
  • Application to published datasets identified different optimal trees compared to traditional methods.
  • The method effectively handles inapplicable data, potentially altering tree search outcomes.

Conclusions:

  • The proposed algorithm offers a practical solution for handling inapplicable data in phylogenetic analyses.
  • This approach can significantly impact inferred evolutionary relationships and the placement of taxa.
  • It leads to potentially major differences in reconstructions of evolutionary history.