ShinyGS-一个图形工具包,包含一系列基因和机器学习模型用于基因组选择:应用,比较和建议
Le Yu1,2, Yifei Dai3, Mingjia Zhu4
1Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, China.
Frontiers in plant science
|January 8, 2025
概括
通过为16个预测模型提供用户友好的界面,ShinyGS简化了育种者的基因组选择. 这种R Shiny应用程序减少了技术障碍,使得在动物和作物计划中更容易获得遗传收益和更快的繁殖周期.
科学领域:
- 遗传学 遗传学 是一个
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 基因组预测加速了遗传收益,缩短了农业中的繁殖周期.
- 目前的基因组选择模型需要先进的R编程和命令行专业知识,这限制了育种者的可访问性.
研究的目的:
- 开发ShinyGS,一个用户友好的R Shiny应用程序用于基因组选择.
- 为育种者提供一种可访问的工具,可以在没有高级编程技能的情况下实施各种基因组预测模型.
主要方法:
- 开发了ShinyGS,这是一个独立的R Shiny应用程序,具有图形用户界面.
- 集成了16种基因组预测方法,包括线性模型 (BA,BB,BC,BL,BRR) 和机器学习算法.
- 包括数据可视化功能和跨不同人群和特征的基准模型性能.
主要成果:
- ShinyGS提供了一个点击界面,用于执行基因组选择.
- 该应用程序包含16种不同的预测模型的综合套件.
- 基准测试提供了基于育种应用的具体情况的模型选择建议.
结论:
- 通过消除育种者的技术障碍,ShinyGS使基因组选择民主化.
- 该软件是独立于平台的,可以通过Docker轻松安装,并且免费使用.
- 促进在动物和作物科学中改善遗传收益和育种效率.
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