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UNINFORMATIVE BOOTSTRAPPING.

James M Carpenter1

  • 1Department of Entomology, American Museum of Natural History, Central Park West at 79th Street, New York, NY 10024, U.S.A.

Cladistics : the International Journal of the Willi Hennig Society
|December 18, 2021
PubMed
Summary
This summary is machine-generated.

Uninformative characters in phylogenetic analysis can reduce statistical significance when bootstrapping. This study found that including autapomorphies often decreases significance, contrary to prior expectations.

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Area of Science:

  • Systematic Botany
  • Computational Biology
  • Phylogenetic Systematics

Background:

  • Bootstrapping is a common method for assessing the statistical significance of clades in phylogenetic analysis.
  • The impact of uninformative characters, such as autapomorphies, on bootstrapping results has been debated.
  • Previous assumptions suggested autapomorphies might not negatively affect significance levels.

Discussion:

  • This empirical investigation analyzed 28 datasets using Random Cladistics and Hennig86 software.
  • Exact calculations and 1000 bootstrap replicates were employed to evaluate significance levels.
  • The study specifically examined the influence of uninformative characters on bootstrapping outcomes.

Key Insights:

  • Contrary to some assurances, the inclusion of autapomorphies in phylogenetic matrices frequently leads to a reduction in statistical significance.
  • Uninformative characters can distort the perceived robustness of clades derived from bootstrapping.
  • The findings challenge the notion that autapomorphies are neutral or beneficial to significance levels.

Outlook:

  • Further research is needed to refine bootstrapping methodologies to account for the effects of uninformative characters.
  • Understanding the impact of data matrix composition is crucial for accurate phylogenetic inference.
  • This study highlights the importance of careful data curation in cladistic analysis.