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A Practical Guide to Phylogenetics for Nonexperts
12:00

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Published on: February 5, 2014

Statistical hypothesis testing in intraspecific phylogeography: nested clade phylogeographical analysis vs.

Alan R Templeton1

  • 1Department of Biology, Washington University, St. Louis, MO 63130-4899, USA. temple_a@wustl.edu

Molecular Ecology
|February 5, 2009
PubMed
Summary

Nested clade phylogeographical analysis (NCPA) offers explicit criteria for testing evolutionary hypotheses, unlike approximate Bayesian computation (ABC). NCPA accounts for sampling error and allows complex models, making it superior for phylogeographical hypothesis testing.

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Area of Science:

  • Evolutionary Biology
  • Population Genetics
  • Phylogeography

Background:

  • Nested clade phylogeographical analysis (NCPA) and approximate Bayesian computation (ABC) are statistical methods used for inferring population genetic structure and evolutionary history.
  • Both methods aim to test phylogeographical hypotheses but differ significantly in their approach and interpretability.

Purpose of the Study:

  • To critically compare the methodologies, assumptions, and statistical rigor of NCPA and ABC for phylogeographical hypothesis testing.
  • To identify the limitations of ABC, particularly concerning model specification, parameter estimation, and statistical interpretation.

Main Methods:

  • The study contrasts NCPA's explicit, component-based model building with ABC's reliance on a priori complete model specification.
  • It highlights NCPA's explicit handling of sampling error and well-defined approximation convergence versus ABC's potential for pseudo-statistical power and undefined convergence.

Main Results:

  • NCPA provides explicit interpretive criteria and accounts for sampling error, enabling complex model construction and analysis of numerous locations.
  • ABC's ad hoc criteria, reliance on highly parameterized models, and failure to account for sampling error lead to statistically non-interpretable probabilities and difficulties in model selection.

Conclusions:

  • NCPA is a more statistically robust and interpretable method for phylogeographical hypothesis testing due to its explicit criteria and accurate error handling.
  • ABC is not recommended for hypothesis testing due to its inherent statistical limitations; however, simulation approaches can be valuable when integrated with methods like NCPA.