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A Practical Guide to Phylogenetics for Nonexperts
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Distance metrics for ranked evolutionary trees.

Jaehee Kim1, Noah A Rosenberg1, Julia A Palacios2,3

  • 1Department of Biology, Stanford University, Stanford, CA 94305.

Proceedings of the National Academy of Sciences of the United States of America
|November 3, 2020
PubMed
Summary
This summary is machine-generated.

We developed new metrics for analyzing evolutionary relationships using ranked genealogies. These metrics enable statistical comparisons of evolutionary trees from different species and time points, aiding in understanding evolutionary processes.

Keywords:
coalescentdistance metricphylogeneticsranked genealogyranked tree shape

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Phylogenetics

Background:

  • Genealogical tree modeling is crucial for estimating evolutionary parameters.
  • Recent advances in ranked genealogies offer new analytical possibilities.
  • Comparing ranked genealogies aids in studying evolutionary processes across diverse organisms and time scales.

Purpose of the Study:

  • To propose novel metrics for analyzing ranked tree shapes and ranked genealogies.
  • To enable statistical comparisons of evolutionary trees from isochronous and heterochronous samples.
  • To facilitate the assessment of differences in tree distributions and quantify estimation uncertainty.

Main Methods:

  • Development of new metrics for ranked tree shapes.
  • Development of new metrics for ranked genealogies (isochronous and heterochronous sampling).
  • Statistical analysis of tree distributions using proposed metrics.

Main Results:

  • The proposed tree metrics allow for statistical analyses of ranked tree shapes and timed ranked tree shapes.
  • These metrics enable quantification of estimation uncertainty and summarization of tree distributions.
  • The utility of the metrics was demonstrated through simulations and an application in infectious diseases.

Conclusions:

  • The developed metrics provide a robust framework for statistical analysis of evolutionary trees.
  • These metrics enhance the study of evolutionary processes by enabling detailed comparisons of ranked genealogies.
  • The approach is valuable for understanding evolutionary dynamics, particularly in fields like infectious disease epidemiology.