Clinical Biomarkers Laboratory, Department of Medicine, Emory University, Atlanta, GA 30322, USA.
Bioinformatics. 2018 Feb 15;34(4):701-702. doi: 10.1093/bioinformatics/btx656.
Integrative omics is a central component of most systems biology studies. Computational methods are required for extracting meaningful relationships across different omics layers. Various tools have been developed to facilitate integration of paired heterogenous omics data; however most existing tools allow integration of only two omics datasets. Furthermore, existing data integration tools do not incorporate additional steps of identifying sub-networks or communities of highly connected entities and evaluating the topology of the integrative network under different conditions. Here we present xMWAS, a software for data integration, network visualization, clustering, and differential network analysis of data from biochemical and phenotypic assays, and two or more omics platforms.
https://kuppal.shinyapps.io/xmwas (Online) and https://github.com/kuppal2/xMWAS/ (R).
Supplementary data are available at Bioinformatics online.
整合组学是大多数系统生物学研究的核心组成部分。需要计算方法来提取不同组学层面之间有意义的关系。已经开发了各种工具来促进异质组学数据的整合；然而，大多数现有的工具只允许整合两个组学数据集。此外，现有的数据集成工具不包括识别高度连接实体的子网或社区的附加步骤，以及在不同条件下评估集成网络的拓扑结构。在这里，我们提出了 xMWAS，这是一个用于数据集成、网络可视化、聚类和生化及表型测定数据以及两个或更多组学平台的差异网络分析的软件。
https://kuppal.shinyapps.io/xmwas（在线）和 https://github.com/kuppal2/xMWAS/（R）。
补充数据可在生物信息学在线获得。
