PyBrOpS: a Python package for breeding program simulation and optimization for multi-objective breeding.

IF 2.1 3区生物学 Q3 GENETICS & HEREDITY

G3: Genes|Genomes|Genetics Pub Date : 2024-10-07 DOI:10.1093/g3journal/jkae199

Robert Z Shrote, Addie M Thompson

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引用次数: 0

Abstract

Plant breeding is a complex endeavor that is almost always multi-objective in nature. In recent years, stochastic breeding simulations have been used by breeders to assess the merits of alternative breeding strategies and assist in decision-making. In addition to simulations, visualization of a Pareto frontier for multiple competing breeding objectives can assist breeders in decision-making. This paper introduces Python Breeding Optimizer and Simulator (PyBrOpS), a Python package capable of performing multi-objective optimization of breeding objectives and stochastic simulations of breeding pipelines. PyBrOpS is unique among other simulation platforms in that it can perform multi-objective optimizations and incorporate these results into breeding simulations. PyBrOpS is built to be highly modular and has a script-based philosophy, making it highly extensible and customizable. In this paper, we describe some of the main features of PyBrOpS and demonstrate its ability to map Pareto frontiers for breeding possibilities and perform multi-objective selection in a simulated breeding pipeline.

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PyBrOpS：用于多目标育种程序模拟和优化的 Python 软件包。

植物育种是一项复杂的工作，几乎总是具有多目标性质。近年来，育种人员利用随机育种模拟来评估备选育种策略的优劣，并协助决策制定。除了模拟之外，将多个相互竞争的育种目标的帕累托前沿可视化也有助于育种人员做出决策。本文介绍了 Python 育种优化和模拟器（PyBrOpS），这是一个 Python 软件包，能够对育种目标进行多目标优化，并对育种流水线进行随机模拟。在其他模拟平台中，PyBrOpS 的独特之处在于它可以执行多目标优化，并将这些结果纳入育种模拟。PyBrOpS 采用高度模块化设计，并以脚本为基础，因此具有很强的可扩展性和可定制性。在本文中，我们将介绍 PyBrOpS 的一些主要功能，并演示其绘制育种可能性的帕累托前沿以及在模拟育种流水线中执行多目标选择的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

G3: Genes|Genomes|Genetics GENETICS & HEREDITY-

CiteScore

5.10

自引率

3.80%

发文量

305

审稿时长

3-8 weeks

期刊介绍： G3: Genes, Genomes, Genetics provides a forum for the publication of high‐quality foundational research, particularly research that generates useful genetic and genomic information such as genome maps, single gene studies, genome‐wide association and QTL studies, as well as genome reports, mutant screens, and advances in methods and technology. The Editorial Board of G3 believes that rapid dissemination of these data is the necessary foundation for analysis that leads to mechanistic insights. G3, published by the Genetics Society of America, meets the critical and growing need of the genetics community for rapid review and publication of important results in all areas of genetics. G3 offers the opportunity to publish the puzzling finding or to present unpublished results that may not have been submitted for review and publication due to a perceived lack of a potential high-impact finding. G3 has earned the DOAJ Seal, which is a mark of certification for open access journals, awarded by DOAJ to journals that achieve a high level of openness, adhere to Best Practice and high publishing standards.