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MoBPS - Modular Breeding Program Simulator

The R-package MoBPS provides a computationally efficient and flexible framework to simulate complex breeding programs and compare their economic and genetic impact. Simulations are performed on the base of individuals. MoBPS utilizes a highly efficient implementation with bit-wise data storage and m...

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Detalles Bibliográficos
Autores principales: Pook, Torsten, Schlather, Martin, Simianer, Henner
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263682/
https://www.ncbi.nlm.nih.gov/pubmed/32229505
http://dx.doi.org/10.1534/g3.120.401193
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author Pook, Torsten
Schlather, Martin
Simianer, Henner
author_facet Pook, Torsten
Schlather, Martin
Simianer, Henner
author_sort Pook, Torsten
collection PubMed
description The R-package MoBPS provides a computationally efficient and flexible framework to simulate complex breeding programs and compare their economic and genetic impact. Simulations are performed on the base of individuals. MoBPS utilizes a highly efficient implementation with bit-wise data storage and matrix multiplications from the associated R-package miraculix allowing to handle large scale populations. Individual haplotypes are not stored but instead automatically derived based on points of recombination and mutations. The modular structure of MoBPS allows to combine rather coarse simulations, as needed to generate founder populations, with a very detailed modeling of todays’ complex breeding programs, making use of all available biotechnologies. MoBPS provides pre-implemented functions for common breeding practices such as optimum genetic contributions and single-step GBLUP but also allows the user to replace certain steps with personalized and/or self-written solutions.
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spelling pubmed-72636822020-06-08 MoBPS - Modular Breeding Program Simulator Pook, Torsten Schlather, Martin Simianer, Henner G3 (Bethesda) Software and Data Resources The R-package MoBPS provides a computationally efficient and flexible framework to simulate complex breeding programs and compare their economic and genetic impact. Simulations are performed on the base of individuals. MoBPS utilizes a highly efficient implementation with bit-wise data storage and matrix multiplications from the associated R-package miraculix allowing to handle large scale populations. Individual haplotypes are not stored but instead automatically derived based on points of recombination and mutations. The modular structure of MoBPS allows to combine rather coarse simulations, as needed to generate founder populations, with a very detailed modeling of todays’ complex breeding programs, making use of all available biotechnologies. MoBPS provides pre-implemented functions for common breeding practices such as optimum genetic contributions and single-step GBLUP but also allows the user to replace certain steps with personalized and/or self-written solutions. Genetics Society of America 2020-03-30 /pmc/articles/PMC7263682/ /pubmed/32229505 http://dx.doi.org/10.1534/g3.120.401193 Text en Copyright © 2020 Pook et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software and Data Resources
Pook, Torsten
Schlather, Martin
Simianer, Henner
MoBPS - Modular Breeding Program Simulator
title MoBPS - Modular Breeding Program Simulator
title_full MoBPS - Modular Breeding Program Simulator
title_fullStr MoBPS - Modular Breeding Program Simulator
title_full_unstemmed MoBPS - Modular Breeding Program Simulator
title_short MoBPS - Modular Breeding Program Simulator
title_sort mobps - modular breeding program simulator
topic Software and Data Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263682/
https://www.ncbi.nlm.nih.gov/pubmed/32229505
http://dx.doi.org/10.1534/g3.120.401193
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