escheR:统一的多维可视化使用 Gestalt 原则
Boyi Guo1, Louise A Huuki-Myers2, Melissa Grant-Peters3,4
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, United States.
Bioinformatics advances
|December 18, 2023
概括
这项研究介绍了escheR,一个R包,通过使用Gestalt原则增强2D的多维数据可视化. 它提高了复杂的生物医学数据的解释性,包括空间解析的转录学.
科学领域:
- 生物医学数据可视化可视化
- 计算生物学是一种计算生物学.
- 基因组学就是基因组学.
背景情况:
- 有效的数据可视化对于数据分析至关重要,特别是在生物医学研究中.
- 现有的工具很难在二维空间中可视化复杂的多维数据.
- 在标准的2D图中解释高维数据集存在挑战.
研究的目的:
- 改进2D多维数据可视化的设计和可解释性.
- 为解决复杂的生物医学数据当前数据可视化工具的局限性.
- 为了利用 Gestalt 原则来增强数据表示.
主要方法:
- 利用 Gestalt 原则来层次化审美,用于在 2D 可视化中显示多个变量.
- 开发了一个名为escheR.R的开源R包.
- 在ggplot2可视化框架上构建该包,以实现无集成.
主要成果:
- escheR包为多维数据提供了增强的可视化功能.
- 该方法适用于空间分辨率的转录组学和其他2D嵌入可视化.
- 该包可以集成到现有的基因组学工作流程中.
结论:
- escheR包为2D复杂多维数据的可视化提供了一种新的解决方案.
- 通过Gestalt原则,可以实现生物医学数据可视化的更好解释性.
- escheR的开源性质促进了其在生物医学研究和数据分析工作流程中的采用.
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