xOmicsShiny:一个用于跨组学数据分析和路径映射的R Shiny应用程序。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2025-05-24 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf097
Benbo Gao, Yu H Sun, Xinmin Zhang, Tinchi Lin, Wei Li, Romi Admanit, Baohong Zhang
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引用次数: 0

摘要

总结:我们开发了xOmicsShiny,这是一个功能丰富的R shiny应用程序,使生物学家能够在实验和数据类型中充分探索组学数据集,重点是在通路水平上发现生物学见解。数据合并功能确保了跨组学数据的灵活探索,如转录组学,蛋白质组学,代谢组学和脂质组学。路径映射功能涵盖了广泛的数据库,包括WikiPathways, Reactome和KEGG路径。此外,xOmicsShiny为日常组学数据分析提供了多个可视化选项和分析任务,即PCA,火山图,维恩图,热图,WGCNA和高级聚类分析。该应用程序采用可定制的模块来执行各种任务,生成交互式图表和可供发布的图表。这种动态的模块化设计克服了R Shiny工具加载缓慢的问题,并允许研究和开发人员社区轻松扩展它。可用性和实现:R Shiny应用程序可在:http://xOmicsShiny.bxgenomics.com公开获得。研究人员可以将自己的数据上传到服务器或使用预加载的演示数据集。在MIT许可下的源代码在https://github.com/interactivereport/xOmicsShiny上提供,用于本地安装。该应用程序的完整教程可在https://interactivereport.github.io/xOmicsShiny/tutorial/docs/index.html上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
xOmicsShiny: an R Shiny application for cross-omics data analysis and pathway mapping.

Summary: We developed xOmicsShiny, a feature-rich R Shiny-powered application that enables biologists to fully explore omics datasets across experiments and data types, with an emphasis on uncovering biological insights at the pathway level. The data merging feature ensures flexible exploration of cross-omics data, such as transcriptomics, proteomics, metabolomics, and lipidomics. The pathway mapping function covers a broad range of databases, including WikiPathways, Reactome, and KEGG pathways. In addition, xOmicsShiny offers several visualization options and analytical tasks for everyday omics data analysis, namely, PCA, Volcano plot, Venn Diagram, Heatmap, WGCNA, and advanced clustering analyses. The application employs customizable modules to perform various tasks, generating both interactive plots and publication-ready figures. This dynamic, modular design overcomes the issue of slow loading in R Shiny tools and allows it to be readily expanded by the research and developer community.

Availability and implementation: The R Shiny application is publicly available at: http://xOmicsShiny.bxgenomics.com. Researchers can upload their own data to the server or use the preloaded demo dataset. The source code, under MIT license, is provided at https://github.com/interactivereport/xOmicsShiny for local installation. A full tutorial of the application is available at https://interactivereport.github.io/xOmicsShiny/tutorial/docs/index.html.

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CiteScore
1.60
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