scatterbar:一个R包,用于在空间解析的坐标中可视化比例数据
Dee Velazquez1,2, Jean Fan1,2
1Center for Computational Biology, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21211, United States.
Bioinformatics (Oxford, England)
|January 31, 2025
概括
新的 R 包 Scatterbar 改进了空间转录学中的比例数据的可视化. 它使用散点堆叠的条形图表来增强与传统散点饼图表相比的解释.
科学领域:
- 生物信息学是一种生物信息学.
- 数据可视化 数据可视化
- 计算生物学 计算生物学
背景情况:
- 在空间坐标上可视化比例数据对于空间转录学等领域至关重要.
- 现有的方法,如散布饼图,呈现的感知挑战,妨碍准确的解释.
- 需要增强视觉突出性,以更好地识别比例趋势和差异.
研究的目的:
- 介绍一个R包,用于在空间分辨的环境中可视化比例数据.
- 提供一种替代散落饼情节的替代方案,解决他们的感知局限性.
- 提高复杂数据集中比例分布的区分能力.
主要方法:
- 开发Scatterbar,这是一个开源的R包,扩展了ggplot2.
- 实现分散堆叠的条形图,用于比例数据可视化.
- 从小鼠大脑空间转录组学数据中,将散射条应用于解卷细胞类型的比例.
主要成果:
- Scatterbar有效地可视化了跨多个空间分辨率坐标的比例数据.
- 由散射棒生成的散射堆叠条图增强了比例分布的区分能力.
- 与传统的散布饼图相比,该包显示了空间转录学数据的提高清晰度.
结论:
- Scatterbar为研究人员提供了一个有价值的工具,用于处理空间解析的比例数据.
- 分散堆叠条形图的方法为复杂的生物数据集提供了卓越的感知清晰度.
- 这种可视化方法有助于更准确地解释空间转录学中的细胞类型分布.
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