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CoMuS: simulating coalescent histories and polymorphic data from multiple species.

S Papadantonakis1, P Poirazi2, P Pavlidis3

  • 1Department of Biology, University of Crete, PO Box 2208, 71409, Heraklio, Greece.

Molecular Ecology Resources
|May 31, 2016
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Summary
This summary is machine-generated.

Analyzing intra- and interspecies variation is difficult due to limited data. CoMuS (Coalescent of Multiple Species) software simulates polymorphisms, aiding species delimitation and evolutionary studies.

Keywords:
approximate Bayesian computationcoalescentpopulation geneticssimulationsspeciation

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Area of Science:

  • Evolutionary biology
  • Computational biology
  • Population genetics

Background:

  • Simultaneous analysis of intra- and interspecies variation is challenging due to limited knowledge of polymorphism patterns.
  • Understanding species divergence and demographic histories requires sophisticated simulation tools.

Purpose of the Study:

  • Introduce CoMuS (Coalescent of Multiple Species), a novel software for simulating intra- and interspecies polymorphisms.
  • Provide a versatile tool for studying species evolution, speciation models, and demographic scenarios.

Main Methods:

  • CoMuS simulates polymorphisms using a multispecies coalescent framework.
  • Supports various speciation models (instant/gradual isolation) and sampling strategies (extinct/extant species).
  • Incorporates infinite- and finite-site models with substitution rate heterogeneity and invariable sites.

Main Results:

  • Demonstrates CoMuS applications in species delimitation, software testing, and model selection.
  • Shows utility in parameter inference with ancestral samples and comparing isolation models.
  • Successfully estimates human-chimpanzee speciation time using both intra- and interspecies variation.

Conclusions:

  • CoMuS is a powerful tool for simulating complex evolutionary histories, especially for recently diverged species.
  • Facilitates research on phenomena like incomplete lineage sorting and introgression.
  • Enhances the study of population genetics and evolutionary processes.