scExploreR:一个灵活的平台,用于非程序员对多式联网单元数据进行民主化分析
bioRxiv : the preprint server for biology
|June 12, 2025
概括
scExploreR使非程序员能够使用R Shiny应用程序分析单细胞测序数据. 它为出版品质量数据提供了广泛的定制,并处理多模式数据,简化生物医学研究洞察力.
科学领域:
- 生物医学研究的研究.
- 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:
- 单细胞测序揭示了细胞异质性,这对于理解疾病机制和推进个性化医学至关重要.
- 当前的单细胞数据分析工具往往需要编程专业知识,这限制了许多研究人员的可访问性.
- 现有的用于单细胞数据分析的图形用户界面在分析深度和数据格式灵活性方面存在局限性.
研究的目的:
- 开发一个可访问的工具,scExploreR,使非程序员能够进行全面的单细胞数据分析.
- 扩大对没有广泛编程经验的研究人员可用的分析任务范围.
- 为了促进单细胞数据的直接探索和分析,弥合生物学和计算科学家之间的差距.
主要方法:
- 开发了scExploreR作为一个包装的R Shiny应用程序,用于本地或服务器部署.
- 集成的SCUBA包可无处理多式联运单细胞数据.
- 实施了广泛的定制选项,以生成出版物质量的数据.
主要成果:
- scExploreR为单细胞数据分析提供了一个用户友好的界面,减少了对编程技能的需求.
- 该应用程序支持多模式数据分析,在不同的输入格式中具有一致的绘图功能.
- 用户可以在scExploreR环境中直接生成高度定制的,准备发布的数字.
结论:
- scExploreR显著降低了单细胞数据分析的进入障碍,使访问强大的见解变得民主化.
- 该工具通过提供一个共同的,可访问的平台来增强生物学家和计算科学家之间的合作.
- scExploreR简化了从复杂的单细胞数据集生成洞察力,加速生物医学研究和个性化医学.
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