Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, 45220, USA.
LINCS Data Coordination and Integration Center (DCIC), Cincinnati, USA.
Nat Commun. 2022 Aug 9;13(1):4678. doi: 10.1038/s41467-022-32205-3.
There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.
目前仅有少数几个平台能够整合多种组学数据类型、生物信息学工具以及用于集成分析和可视化的接口,而这些平台并不需要编程技能。在这里,我们将介绍 iLINCS(http://ilincs.org),这是一个用于分析组学数据和细胞扰动特征的集成型网络平台。该平台便于挖掘和重新分析大量的组学数据集(>34000 个)、预先计算的特征(>200000 个)及其关联,以及分析用户提交的疾病和细胞扰动的组学特征。iLINCS 分析工作流程将大量的组学数据资源与各种分析和交互式可视化工具集成到一个全面的组学特征分析平台中。iLINCS 用户友好的界面使用户能够执行组学特征的复杂分析、作用机制分析以及基于特征的药物重定位。我们通过三个用例来说明 iLINCS 的实用性,涉及癌症蛋白质基因组学特征、COVID-19 转录组学特征和 mTOR 信号的分析。