ShinyCore:一个R/Shiny程序,用于建立基于单核酸多态数据的核心收集
Steven Kim1, Dong Sub Kim2, Hana Moyle1,3
1Department of Mathematics and Statistics, California State University, Monterey Bay, Seaside, USA.
Plant methods
|October 11, 2023
概括
ShinyCore是一种选择核心收藏的新方法,增强遗传多样性并改进数据管理. 与现有的算法相比,这种用户友好的工具为大型数据集提供了更快的处理速度.
科学领域:
- 植物育种 植物育种
- 遗传学 遗传学 是一个
- 生物信息学是一种生物信息学.
背景情况:
- 管理大量的遗传资源是复杂的.
- 核心收藏提供了一个代表性的研究和育种子集.
- 有效的核心收藏需要高的遗传多样性和最小的冗余.
研究的目的:
- 介绍ShinyCore,这是一种用于核心集合选择的新双相方法.
- 改进现有的核心集合管理算法.
- 提高遗传多样性和数据处理效率.
主要方法:
- ShinyCore采用了两阶段的方法:覆盖标准,然后是稀有性得分.
- 覆盖标准很快就建立了一个定义的遗传代表水平.
- 稀有度得分优先考虑独特的等位基因以最大限度地提高多样性.
主要成果:
- ShinyCore比GenoCore更快地实现了用户定义的覆盖范围,特别是对于大型数据集.
- 稀有性得分有效地提高了遗传多样性和距离指标.
- ShinyCore展示了卓越的速度和多样性增强能力.
结论:
- ShinyCore为核心收集选择提供了一个可访问和高效的替代方案.
- 该方法很容易通过RStudio实现,并提供交互式Web应用程序.
- ShinyCore有利于研究人员和育种人员,特别是那些与大型遗传数据集工作的人.
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