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DIM SUM: demography and individual migration simulated using a Markov chain.

Jeremy M Brown1, Kevin Savidge, Emily Jane B McTavish

  • 1Section of Integrative Biology and Center for Computational Biology and Bioinformatics, University of Texas-Austin, 1 University Station, Austin, TX 78712, USA. jeremymbrown@gmail.com

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Summary

This study introduces DIM SUM, a Java program simulating population demography and individual migration without coalescent assumptions. It aids in testing phylogeographic and landscape-genetic methods, especially when assumptions are violated.

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Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Computational Biology

Background:

  • Inferring demographic history and genetic relationships is crucial in evolutionary studies.
  • Existing analytical methods often rely on assumptions that may be violated in real-world scenarios.
  • There is a need for robust simulation tools to assess the power and limitations of these methods.

Purpose of the Study:

  • To introduce DIM SUM, a flexible Java program for simulating population demography and individual migration.
  • To provide a tool for testing phylogeographic and landscape-genetic methods under various demographic scenarios.
  • To facilitate the exploration of biological invasion dynamics and serve as a pedagogical resource.

Main Methods:

  • DIM SUM simulates demographic history and individual migration using a Markov chain approach.
  • The program does not assume coalescent processes or discrete population boundaries.
  • Users can customize spatial variables, border effects, carrying capacities, dispersal, reproduction, and sampling strategies.

Main Results:

  • DIM SUM offers high flexibility in specifying demographic and spatial parameters, including time-varying spatial data.
  • The simulation environment records ancestor-descendant relationships.
  • The software is designed for integration with genetic marker simulation tools.

Conclusions:

  • DIM SUM is a valuable tool for evaluating the robustness of phylogeographic and landscape-genetic methods, particularly when coalescent assumptions are violated.
  • It can be used to explore complex demographic scenarios, such as biological invasions.
  • The program serves as an educational tool for understanding population dynamics and genetic inference.