Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Cancer Bioinformatics, Peking University Cancer Hospital and Institute, Beijing 100142, China.
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing 100142, China.
Nucleic Acids Res. 2020 Jul 2;48(W1):W463-W471. doi: 10.1093/nar/gkaa423.
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/.
最近的大规模多组学研究导致了癌症相关数据的快速积累，这为研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具有很高的价值和广泛的用途，但针对这些数据在队列水平上的再研究的分析和可视化功能并没有得到充分解决。在这里，我们提出了 CVCDAP，这是一个基于网络的平台，提供了一个现成的交互式和可定制的工具箱，用于分析 TCGA 和 CPTAC 公共数据集以及用户上传的数据集的队列水平。CVCDAP 允许在多个研究中灵活选择具有共同分子和/或临床特征的患者作为虚拟队列，并提供数十个内置的可定制工具，用于对单个虚拟队列进行无缝的基因组、转录组、蛋白质组和临床分析，以及对两个相关的虚拟队列进行比较。CVCDAP 的灵活性和分析能力使实验和临床研究人员能够通过构建和分析他们感兴趣的主题的虚拟队列，来识别新的分子机制并开发潜在的治疗方法。我们通过两个应用程序证明了 CVCDAP 可以方便地重现已发表的研究结果并揭示新的见解。CVCDAP 网络服务器可在 https://omics.bjcancer.org/cvcdap/ 免费获得。
