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TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution.

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TraitTrainR is a new R package for large-scale simulations of continuous trait evolution. It aids in understanding evolutionary models and estimating them with real trait data, improving comparative biology research.

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Area of Science:

  • Evolutionary biology
  • Phylogenetics
  • Computational biology

Background:

  • Comparative trait data is rapidly expanding, challenging current evolutionary modeling and simulation capabilities.
  • Efficient tools are needed to handle large datasets and complex evolutionary models.
  • Understanding the impact of measurement error on evolutionary inference is crucial.

Purpose of the Study:

  • Introduce TraitTrainR, an R package for efficient, large-scale simulations of continuous trait evolution.
  • Provide a flexible tool for defining parameter spaces, model stacking, and accommodating multi-trait evolution.
  • Facilitate the investigation of measurement error impacts on evolutionary inference.

Main Methods:

  • TraitTrainR is an R package utilizing R 4.4.0.
  • The package supports multiple output formats and popular trait data transformations.
  • It allows for flexible input parameter space definition and model stacking, including measurement error.

Main Results:

  • TraitTrainR enables efficient, large-scale simulations under complex models of continuous trait evolution.
  • The package demonstrates utility in exploring evolutionary model selection through phylogenetic case studies.
  • Applications include experimental design and statistical power analysis in comparative biology.

Conclusions:

  • TraitTrainR offers a powerful and flexible solution for large-scale evolutionary simulations.
  • Its capabilities enhance the ability to confidently estimate evolutionary models with real trait data.
  • The package is freely available with comprehensive documentation and tutorials.