Institute of Molecular and Cell Biology, A*STAR, Singapore, Singapore.
Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Bioinformatics. 2019 Jan 15;35(2):346-348. doi: 10.1093/bioinformatics/bty534.
Data visualization is often regarded as a post hoc step for verifying statistically significant results in the analysis of high-throughput datasets. This common practice leaves a large amount of raw data behind, from which more information can be extracted. However, existing solutions do not provide capabilities to explore large-scale raw datasets using biologically sensible queries, nor do they allow user interaction based real-time customization of graphics. To address these drawbacks, we have designed an open-source, web-based tool called Systems-Level Interactive Data Exploration, or SLIDE to visualize large-scale -omics data interactively. SLIDE's interface makes it easier for scientists to explore quantitative expression data in multiple resolutions in a single screen.
SLIDE is publicly available under BSD license both as an online version as well as a stand-alone version at https://github.com/soumitag/SLIDE.
Supplementary data are available at Bioinformatics online.
在分析高通量数据集时,数据可视化通常被视为事后步骤,用于验证具有统计学意义的结果。这种常见的做法会留下大量原始数据,而这些数据可以从中提取更多信息。然而,现有的解决方案无法提供使用合理生物学查询来探索大规模原始数据集的功能,也不允许根据用户交互实时定制图形。为了解决这些缺点,我们设计了一个名为 Systems-Level Interactive Data Exploration(SLIDE)的开源、基于网络的工具,用于交互式可视化大规模组学数据。SLIDE 的界面使科学家可以更轻松地在单个屏幕上以多种分辨率探索定量表达数据。
SLIDE 可根据 BSD 许可证在网上和独立版本(https://github.com/soumitag/SLIDE)上公开使用。
补充数据可在 Bioinformatics 在线获得。