AlphaSimR: an R package for breeding program simulations.

R Chris Gaynor,John M Hickey,Gregor Gorjanc,D-J De Koning

doi:10.1093/g3journal/jkaa017

R Chris Gaynor, John M Hickey + Show 2 more

Open Access

https://doi.org/10.1093/g3journal/jkaa017

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Abstract

This paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs. AlphaSimR is a highly flexible software package able to simulate a wide range of plant and animal breeding programs for diploid and autopolyploid species. AlphaSimR is ideal for testing the overall strategy and detailed design of breeding programs. AlphaSimR utilizes a scripting approach to building simulations that is particularly well suited for modeling highly complex breeding programs, such as commercial breeding programs. The primary benefit of this scripting approach is that it frees users from preset breeding program designs and allows them to model nearly any breeding program design. This paper lists the main features of AlphaSimR and provides a brief example simulation to show how to use the software.

Highlights

This paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs
This section will demonstrate AlphaSimR using a simulation of a single breeding cycle for a generic wheat breeding program
The doubled haploid (DH) lines are visually evaluated in a head row (HDRW) nursery

Summary

Introduction

This paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs. Stochastic simulations of whole breeding programs have rarely, if ever, been used to improve long-term performance of breeding programs for many agriculturally important species. This is likely due to the difficultly in setting up and running these simulations. This difficulty is in no small part due to the need for a person with thorough knowledge of breeding programs and computer programming. The amount of programming skills this person needs to possess is considerable when there are no existing software programs for modeling the specific breeding program of interest To address this issue, new software is needed that can lower the programming burden and thereby increase the ease of running simulations

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