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

Abstract

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares’ complex capabilities, composing code and input files, a daunting bioinformatics barrier, and a steep conceptual learning curve. skeleSim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics, and organizing data output, in a reproducible pipeline within the R environment. skeleSim is designed to be an extensible framework that can ‘wrap’ around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skeleSim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skeleSim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skeleSim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny).

Efficient ancestry and mutation simulation with msprime 1.0

“…In practice, for any reproducible simulation project, users will write a script to generate the required command lines or input parameter files, invoke the simulation engine, and process the results in some way. This process is cumbersome and labor intensive, and a number of packages have been developed to allow simulations to be run directly in a high-level scripting language ( Staab and Metzler 2016 ; Parobek et al 2017 ; Gladstein et al 2018 ).…”

Efficient ancestry and mutation simulation with msprime 1.0

“…In practice, for any reproducible simulation project users will write a script to generate the required command lines or input parameter files, invoke the simulation engine, and process the results in some way. This process is cumbersome and labour intensive, and a number of packages have been developed to allow simulations to be run directly in a high-level scripting language (Staab and Metzler, 2016; Parobek et al, 2017; Gladstein et al, 2018).…”

Integrating demography and population genetics through landscape genetics

“…Otros programas como Bottlesim simulan cuellos de botella en especies de vida larga y con ciclos de vida complejos para cuantificar sus efectos sobre la diversidad genética, pero teniendo en cuenta también los efectos de los cambios en el paisaje. Si el investigador carece de escenarios iniciales, puede generarlos con la mayoría de los programas mencionados, y el paquete de R skeleSim (Parobek et al 2017) ofrece una opción gráfica muy intuitiva y sencilla que ayuda diseñar los diferentes escenarios demográficos y genéticos que se quieren simular, al igual que PopPlanner (Ewing et al 2015) que facilita la definición de escenarios demográficos complejos simulados mediante algoritmos de coancestría (Ewing y Hermisson 2010).…”