Nishida Kozo, Maruyama Junichi, Kaizu Kazunari, Takahashi Koichi, Yugi Katsuyuki
Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
Department of Biotechnology and Life Science, Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei-shi, Tokyo, 184-8588, Japan.
NPJ Syst Biol Appl. 2024 Feb 19;10(1):16. doi: 10.1038/s41540-024-00342-8.
Biochemical network visualization is one of the essential technologies for mechanistic interpretation of omics data. In particular, recent advances in multi-omics measurement and analysis require the development of visualization methods that encompass multiple omics data. Visualization in 2.5 dimension (2.5D visualization), which is an isometric view of stacked X-Y planes, is a convenient way to interpret multi-omics/trans-omics data in the context of the conventional layouts of biochemical networks drawn on each of the stacked omics layers. However, 2.5D visualization of trans-omics networks is a state-of-the-art method that primarily relies on time-consuming human efforts involving manual drawing. Here, we present an R Bioconductor package 'transomics2cytoscape' for automated visualization of 2.5D trans-omics networks. We confirmed that transomics2cytoscape could be used for rapid visualization of trans-omics networks presented in published papers within a few minutes. Transomics2cytoscape allows for frequent update/redrawing of trans-omics networks in line with the progress in multi-omics/trans-omics data analysis, thereby enabling network-based interpretation of multi-omics data at each research step. The transomics2cytoscape source code is available at https://github.com/ecell/transomics2cytoscape .
生化网络可视化是对组学数据进行机制解释的关键技术之一。特别是,多组学测量和分析的最新进展要求开发能够涵盖多种组学数据的可视化方法。二维半可视化(2.5D可视化),即堆叠X-Y平面的等距视图,是在每个堆叠组学层上绘制的生化网络的传统布局背景下解释多组学/跨组学数据的便捷方式。然而,跨组学网络的2.5D可视化是一种主要依赖耗时的人工绘制的前沿方法。在这里,我们展示了一个R语言的生物导体包“transomics2cytoscape”,用于二维半跨组学网络的自动可视化。我们证实,transomics2cytoscape可用于在几分钟内快速可视化已发表论文中呈现的跨组学网络。Transomics2cytoscape允许根据多组学/跨组学数据分析的进展频繁更新/重新绘制跨组学网络,从而在每个研究步骤实现基于网络的多组学数据解释。transomics2cytoscape的源代码可在https://github.com/ecell/transomics2cytoscape获取。