PATH: An interactive web platform for analysis of time-course high-dimensional genomic data.
PATH: An interactive web platform for analysis of time-course high-dimensional genomic data.
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DOI：
10.1504/ijcbdd.2020.10036399
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发表时间：
2020
影响因子：
--
通讯作者：
Ouyang Z
中科院分区：
文献类型：
--
作者：
Zhang Y;Chen Y;Ouyang Z
发现时程基因组数据中的模式可以提供关于健康和疾病中生物系统动态的见解。在这里，我们提出了一个时间过程的高维数据分析平台（PATH）与基因组学研究中的应用。该Web应用程序提供了一个用户友好的界面，具有交互式数据可视化，降维，模式发现和基于主趋势分析（PTA）的特征选择。此外，Web应用程序可以基于联合PTA对时间过程高维数据进行交互式和综合分析。通过仿真和真实的算例，以及与经典的时程数据分析方法如函数主成分分析的比较，说明了PATH的实用性。PATH可在https://ouyanglab.shinyapps.io/PATH/上免费访问。
Discovering patterns in time-course genomic data can provide insights on the dynamics of biological systems in health and disease. Here, we present a Platform for Analysis of Time-course High-dimensional data (PATH) with applications in genomics research. This web application provides a user-friendly interface with interactive data visualisation, dimension reduction, pattern discovery, and feature selection based on the principal trend analysis (PTA). Furthermore, the web application enables interactive and integrative analysis of time-course high-dimensional data based on the Joint PTA. The utilities of PATH are demonstrated through simulated and real examples, and the comparison with classical time-course data analysis methods such as the functional principal component analysis. PATH is freely accessible at https://ouyanglab.shinyapps.io/PATH/.