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AlphaSimR: An R-package for Breeding Program Simulations

R. Chris Gaynor, View ORCID ProfileGregor Gorjanc, John M. Hickey
doi: https://doi.org/10.1101/2020.08.10.245167
R. Chris Gaynor
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian EH25 9RG, UK
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  • For correspondence: chris.gaynor@roslin.ed.ac.uk
Gregor Gorjanc
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian EH25 9RG, UK
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John M. Hickey
The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Research Centre, Midlothian EH25 9RG, UK
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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.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted August 11, 2020.
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AlphaSimR: An R-package for Breeding Program Simulations
R. Chris Gaynor, Gregor Gorjanc, John M. Hickey
bioRxiv 2020.08.10.245167; doi: https://doi.org/10.1101/2020.08.10.245167
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AlphaSimR: An R-package for Breeding Program Simulations
R. Chris Gaynor, Gregor Gorjanc, John M. Hickey
bioRxiv 2020.08.10.245167; doi: https://doi.org/10.1101/2020.08.10.245167

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