genomicSimulation: fast R functions for stochastic simulation of breeding programs

Abstract

Simulation tools are key to designing and optimising breeding programs that are multi-year, high-effort endeavours. Tools that operate on real genotypes and integrate easily with other analysis software are needed to guide users to crossing decisions that best balance genetic gains and diversity to maintain gains in the future. This paper presents genomicSimulation, a fast and flexible tool for the stochastic simulation of crossing and selection on real genotypes. It is fully written in C for high execution speeds, has minimal dependencies, and is available as an R package for integration with Rs broad range of analysis and visualisation tools. Comparisons of a simulated recreation of a breeding program to the real data shows that the tools simulated offspring correctly show key population features, such as linkage disequilibrium patterns and genomic relationships. Both versions of genomicSimulation are freely available on GitHub: The R package version at https://github.com/vllrs/genomicSimulation/ and the C library version at https://github.com/vllrs/genomicSimulationC/