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Differences in Performance among Test Statistics for Assessing Phylogenomic Model Adequacy.

David A Duchêne1, Sebastian Duchêne2, Simon Y W Ho1

  • 1School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.

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Statistical phylogenetic models are crucial for genomic analysis. New thresholds for model adequacy testing improve the reliability of phylogenetic estimates, especially for data with few informative sites.

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Area of Science:

  • Genomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Phylogenetic analyses rely on accurate substitution models.
  • Model adequacy testing is vital for reliable evolutionary inference.
  • Current tests may fail to detect poor model fit, impacting phylogenetic accuracy.

Purpose of the Study:

  • To evaluate test statistics for assessing substitution model adequacy in phylogenetics.
  • To identify statistics sensitive to common sources of phylogenetic error.
  • To propose improved methods for model adequacy testing in phylogenomics.

Main Methods:

  • Comprehensive simulation study of various test statistics.
  • Analysis of phylogenetic estimation error sources.
  • Development and application of new model adequacy thresholds.

Main Results:

  • Traditional model adequacy thresholds often fail to reject inadequate models.
  • This failure is pronounced with limited informative sites.
  • Proposed new thresholds effectively reject models associated with imprecise phylogenies.

Conclusions:

  • Enhanced model adequacy testing is crucial for reliable phylogenomic inference.
  • New thresholds improve the identification of problematic substitution models.
  • The proposed approach aids in selecting appropriate models for genome-scale data.