Recent large-scale multi-omics studies resulted in quick accumulation of an overwhelming amount of cancer-related data, which provides an unprecedented resource to interrogate diverse questions. While certain existing web servers are valuable and widely used, analysis and visualization functions with regard to re-investigation of these data at cohort level are not adequately addressed. Here, we present CVCDAP, a web-based platform to deliver an interactive and customizable toolbox off the shelf for cohort-level analysis of TCGA and CPTAC public datasets, as well as user uploaded datasets. CVCDAP allows flexible selection of patients sharing common molecular and/or clinical characteristics across multiple studies as a virtual cohort, and provides dozens of built-in customizable tools for seamless genomic, transcriptomic, proteomic and clinical analysis of a single virtual cohort, as well as, to compare two virtual cohorts with relevance. The flexibility and analytic competence of CVCDAP empower experimental and clinical researchers to identify new molecular mechanisms and develop potential therapeutic approaches, by building and analyzing virtual cohorts for their subject of interests. We demonstrate that CVCDAP can conveniently reproduce published findings and reveal novel insights by two applications. The CVCDAP web server is freely available at https://omics.bjcancer.org/cvcdap/.

中文翻译：

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CVCDAP：癌症虚拟队列分子和临床分析的综合平台。


最近的大规模多组学研究迅速积累了大量与癌症相关的数据，这为探究各种问题提供了前所未有的资源。虽然某些现有的网络服务器很有价值并且被广泛使用，但在队列级别重新调查这些数据的分析和可视化功能没有得到充分解决。在这里，我们介绍了 CVCDAP，这是一个基于网络的平台，可提供现成的交互式且可定制的工具箱，用于对 TCGA 和 CPTAC 公共数据集以及用户上传的数据集进行队列级别分析。 CVCDAP 允许灵活选择在多项研究中具有共同分子和/或临床特征的患者作为虚拟队列，并提供数十种内置可定制工具，用于单个虚拟队列的无缝基因组、转录组、蛋白质组和临床分析，以及，比较两个虚拟群组的相关性。 CCVCDAP 的灵活性和分析能力使实验和临床研究人员能够通过为其感兴趣的主题构建和分析虚拟队列来识别新的分子机制并开发潜在的治疗方法。我们证明 CVCDAP 可以通过两个应用程序方便地重现已发表的发现并揭示新颖的见解。 CVCDAP Web 服务器可在 https://omics.bjcancer.org/cvcdap/ 上免费获取。