Cantrell Kalen, Fedarko Marcus W, Rahman Gibraan, McDonald Daniel, Yang Yimeng, Zaw Thant, Gonzalez Antonio, Janssen Stefan, Estaki Mehrbod, Haiminen Niina, Beck Kristen L, Zhu Qiyun, Sayyari Erfan, Morton James T, Armstrong George, Tripathi Anupriya, Gauglitz Julia M, Marotz Clarisse, Matteson Nathaniel L, Martino Cameron, Sanders Jon G, Carrieri Anna Paola, Song Se Jin, Swafford Austin D, Dorrestein Pieter C, Andersen Kristian G, Parida Laxmi, Kim Ho-Cheol, Vázquez-Baeza Yoshiki, Knight Rob
Department of Computer Science, Jacobs School of Engineering, University of California, San Diego, California, USA.
Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA.
mSystems. 2021 Mar 16;6(2):e01216-20. doi: 10.1128/mSystems.01216-20.
Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality-including ordination integration and animations-alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of 'omic data. Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets.
分析微生物群落的标准工作流程通常包括系统发育树的创建和整理。在此,我们展示了EMPress,这是一个交互式网络工具,用于在微生物组、代谢组和其他群落数据的背景下可视化树,可扩展到节点数超过500,000的树。EMPress提供了新颖的功能,包括排序整合和动画,以及许多标准的树可视化功能,从而简化了对多种形式的“组学”数据的探索性分析。系统发育树是分析微生物群落不可或缺的数据结构。最近的研究还表明,从某些代谢组数据集构建的树具有实用性,进一步凸显了它们在微生物组研究中的重要性。现代微生物组调查规模的不断扩大,给这些数据的可视化带来了诸多挑战。在本文中,我们使用了五个不同的数据集来展示EMPress(一种交互式网络可视化工具)的多功能性和可扩展性。EMPress满足了对能够处理大型、复杂多组学数据集的探索性分析工具日益增长的需求。