skelesim: an extensible, general framework for population genetic simulation in R.

Area of Science:

• Molecular Ecology
• Computational Biology
• Population Genetics

Background:

• Simulations are crucial for molecular ecology but are hindered by complex software, bioinformatics barriers, and steep learning curves.
• Growing computational power increases simulation utility but exacerbates accessibility issues for researchers.

Purpose of the Study:

• To introduce skelesim, an R package designed to simplify the use of simulation software in molecular ecology.
• To provide a reproducible pipeline for choosing simulations, setting parameters, and analyzing genetic data.
• To serve as an educational tool for teaching simulation concepts and R programming.

Main Methods:

• skelesim acts as an extensible framework, wrapping around existing simulation engines (fastsimcoal2, rmetasim) within the R environment.
• It guides users through simulation setup, parameterization, and the calculation of genetic summary statistics.
• The package supports coalescent and forward-time models for various demographic scenarios and marker types.

Main Results:

• skelesim facilitates the generation of null distributions for population genetic statistics.
• It enhances reproducibility by organizing data output within a structured R pipeline.
• The package includes a graphical user interface (using shiny) for user-friendly operation.

Conclusions:

• skelesim lowers the barrier to entry for complex population genetic simulations, enabling wider application in molecular ecology.
• The package promotes reproducible research and can be used as an effective teaching tool for simulation methods and R.
• By integrating various simulation engines, skelesim offers a flexible and powerful platform for ecological and genetic research.