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在R中使用Morphospace构建和可视化形状数据的顺序
Pablo S Milla Carmona1,2, Oscar E R Lehmann3, William J Deakin1
1Bristol Palaeobiology Group, School of Earth Sciences University of Bristol Bristol UK.
Ecology and evolution
|June 20, 2025
概括
通过统一形状排序和可视化方法,R包"morphospace"简化了几何形态测量. 它增强了生物相关性,并有助于探索进化模式.
科学领域:
- 进化生物学 进化生物学
- 形态测量法 形态测量法 形态测量法
- 计算生物学 计算生物学
背景情况:
- 几何形态度简化了高维形状数据进行分析.
- 目前的排序和可视化方法缺乏统一的方法,限制了生物洞察力.
研究的目的:
- 引入"形态空间",一个R包,用于简化形状排序和可视化.
- 通过综合工具增强形态测量分析的生物相关性.
主要方法:
- "形态空间"包提供了一种工作流程,用于过麻烦变化,构建生物相关的排序,并投射各种元素.
- 它将形状数据与非形状信息集成为高级可视化.
- 该套件有助于创建准备发布的数据和启发式探索.
主要成果:
- "形态空间"提供了一种统一的方法,用于在几何形态学中的形状排序和可视化.
- 该包允许过有害变异,并强调不同的生物信号.
- 它允许各种元素 (形状,集群,轴,系谱) 的投影,并集成非形状数据.
结论:
- "morphospace" R 软件包有助于创建几何形态学的准备发布的可视化图像.
- 它增强了对形状变异模式和潜在的进化过程的探索.
- 该工具通过改进数据解释来支持古生物学和进化研究.
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