PhosNetVis: a web-based tool for kinase enrichment analysis and interactive 2D/3D network visualizations of phosphoproteomics data

Osho Rawal, Berk Turhan, Irene Font Peradejordi, Shreya Chandrasekar, Selim Kalayci, Jeffrey Johnson, Mehdi Bouhaddou, Zeynep H. Gumus
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Abstract

Protein phosphorylation is a vital process in cellular signaling that involves the reversible modification of a protein (substrate) residue by another protein (kinase). Advances in liquid chromatography-mass spectrometry have enabled the rapid generation of massive protein phosphorylation datasets across multiple conditions by many research groups. Researchers are then tasked with inferring kinases responsible for changes in phosphorylation sites of each substrate. Despite the recent explosion of tools to infer kinase-substrate interactions (KSIs) from such datasets, these are not optimized for the interactive exploration of the resulting large and complex KSI networks together with significant phosphorylation sites and states. There are also no dedicated tools that streamline kinase inferences together with interactive visualizations of the resulting networks. There is thus an unmet need for a tool that facilitates uster-intuitive analysis, interactive exploration, visualization, and communication of datasets from phosphoproteomics experiments. Here, we present PhosNetVis, a freely available web-based tool for researchers of all computational skill levels to easily infer, generate and interactively explore KSI networks in 2D or 3D by streamlining multiple phosphoproteomics data analysis steps within one single tool. PhostNetVis significantly lowers the barriers for researchers in rapidly generating high-quality visualizations to translate their rich phosphoproteomics datasets into biological and clinical insights.
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PhosNetVis:一种基于网络的激酶富集分析和磷酸化蛋白质组学数据交互式二维/三维网络可视化工具
蛋白质磷酸化是细胞信号传导的一个重要过程,它涉及另一种蛋白质(激酶)对蛋白质(底物)残基的可逆修饰。液相色谱-质谱联用技术的进步使许多研究小组能够在多种条件下快速生成大量蛋白质磷酸化数据集。随后,研究人员的任务就是推断负责每个底物磷酸化位点变化的激酶。尽管最近从此类数据集中推断激酶-底物相互作用(KSI)的工具层出不穷,但这些工具并没有针对由此产生的庞大而复杂的 KSI 网络以及重要的磷酸化位点和状态进行交互式探索进行优化。此外,还有一些专用工具可以简化激酶推断,并对由此产生的网络进行交互式可视化。因此,我们需要一种工具来促进直观分析、交互式探索、可视化以及磷酸化蛋白质组实验数据集的交流。在这里,我们介绍了 PhosNetVis,这是一种免费提供的基于网络的工具,通过在一个工具中简化多个磷蛋白组学数据分析步骤,让各种计算技能水平的研究人员都能轻松地推断、生成和交互式地探索二维或三维的 KSI 网络。PhostNetViss 大大降低了研究人员快速生成高质量可视化数据的门槛,从而将丰富的磷蛋白组学数据集转化为生物学和临床见解。
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