xOmicsShiny:一个R Shiny应用程序,用于交叉omics数据分析和路径映射
Benbo Gao1, Yu H Sun1, Xinmin Zhang2
1Research and Development, Biogen Inc., Cambridge, MA 02142, United States.
Bioinformatics advances
|May 29, 2025
概括
xOmicsShiny是一个新的R Shiny应用程序,用于生物学家探索多omics数据,整合转录组学,蛋白质组学和代谢组学,以获得途径级洞察力. 它提供各种分析和可视化,增强生物发现.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 探索多组数据集 (转录组,蛋白组,代谢组,脂组组) 对于生物发现至关重要.
- 现有的工具往往缺乏全面的整合和途径级分析能力.
- 对复杂的omics数据进行高效的可视化和分析仍然是研究人员面临的挑战.
研究的目的:
- 开发一个R Shiny应用程序xOmicsShiny,用于全面探索多omics数据.
- 通过整合各种omics数据集,在途径层面促进生物洞察的发现.
- 为omics数据提供一个用户友好的平台,提供先进的分析和可视化工具.
主要方法:
- 开发一个功能丰富的R Shiny应用程序,xOmicsShiny.
- 实施数据合并功能,用于跨学科数据集成.
- 集成多个路径数据库 (WikiPathways,Reactome,KEGG) 用于路径映射.
- 包括各种分析模块:PCA,火山图,Venn图,热图,WGCNA和集群.
- 模块化设计以提高性能和可扩展性.
主要成果:
- xOmicsShiny可以灵活地探索集成的奥米克数据 (转录组学,蛋白组学,代谢组学,脂组学).
- 该应用程序在多个数据库中提供了全面的路径映射.
- 它提供了一套标准的omics分析和可视化,包括交互式和准备发布的输出.
- 模块化设计解决了R Shiny工具中常见的缓慢加载问题.
结论:
- xOmicsShiny是一个强大的,多功能工具,用于生物学家探索多omics数据和发现生物见解.
- 它的综合方法和以途径为中心的分析增强了对复杂生物系统的理解.
- 该应用程序的设计促进社区的扩张和未来的发展.
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