Visualization hub for genomics data exploration and translational discovery

用于基因组学数据探索和转化发现的可视化中心

• 批准号: 9756153
• 负责人: Eric Collisson
• 金额: $ 72.38万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-13 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9756153
• 关键词: Automobile Driving; Big Data; Bioinformatics; Biological; Cancer Patient; Cause of Death; Clinical; Clinical Research; Clinical Treatment; Clinical Trials; Communities; Computers; DNA Sequence; DNA copy number; Data; Data Set; Development; Disease; Disease Progression; Ensure; Environment; Evolution; Future; Genome Data Analysis Network; Genomic medicine; Genomics; Goals; Imagery; Immune response; Immunologics; Immunotherapy; Individual; Institution; International; Investigation; Knowledge; Libraries; Malignant Neoplasms; Malignant neoplasm of pancreas; Measures; Medicine; Metastatic Melanoma; Molecular; Oncoproteins; Online Systems; Patient-Focused Outcomes; Patients; Performance; Play; Principal Investigator; Process; Proteins; RNA; Receptor Cell; Receptors, Antigen, B-Cell; Research; Research Personnel; Research Project Grants; Resistance; Role; Scientist; Secure; Structure; System; T-Cell Receptor; Testing; Therapeutic; Time; Visual; Visualization software; Work; anticancer research; base; cancer care; cancer genome; cancer genomics; cancer initiation; cancer therapy; cloud platform; data access; data hub; data resource; data visualization; design; effective therapy; experience; experimental study; genome-wide; genomic data; immunogenic; improved; interoperability; knowledge translation; meetings; neglect; neoantigens; next generation; novel; novel therapeutics; open source; personalized medicine; petabyte; portability; precision medicine; programs; repository; response; small molecule; software repository; success; symposium; therapy resistant; tool; transcriptome; treatment response; tumor; usability; user-friendly; web interface; working group

Project Summary/Abstract Large NCI clinical trials and research projects have been generating data on cancer genomes at an unprecedented rate, elucidating the mechanisms of cancer initiation and evolution, as well as resistance to therapy. To fully utilize this comprehensive data resource, which has exceeded a petabyte (1015 bytes) of data, the scientific community needs deep, user-friendly interactive computer visualizations of the data. These will empower investigators to discover the molecular processes driving each patient's cancer, and to identify potential translations of this knowledge into new therapies, ultimately advancing both our knowledge of cancer mechanisms and patient outcomes. We propose to develop a web-based Data Hub and Viz Hub platform to allow researchers to visualize the richness of the NCI's cancer genomics data from a single web interface. Visualizations will be composed of a set of “bio-centric” views developed by the bioinformatics community and made available in BioJS, an open- source repository of tools to represent biological data. This will establish a new paradigm of web-based biological data visualization development by way of sharable and reusable modular open source components. To initiate the Viz Hub platform, we will integrate seven popular 3rd-party bioinformatics visualizations into the existing UCSC Xena Browser utilizing a plug-and-play framework. We will then work closely with several clinical labs to develop two new translational visualizations for the next generation of genomic medicine. One will be a Longitudinal Omics Integrator, giving researchers a highlighted overview of a patient while drilling down into genomic and functional data collected throughout treatment. Another will help researchers investigate responses to various new types of immunotherapy, which promise to revolutionize cancer treatment. This Immuno-Tracker and Immunoediting Viewer will show how immunogenic neoantigens, T-cell receptors, and B-cell receptors change over disease progression and in response to treatment. The visualization needs of the scientific community, NCI's Genomic Data Analysis Network, and Disease Working groups will be fully supported through our system of public and restricted Data Hubs. Our high- performance Data Hubs will be easy to install on a diverse range of computing environments. Users will be able to integrate public and restricted data, from large consortia and individual researchers (including their own labs), seamlessly on our web-based Viz Hub. Our commitment to bioinformatics community standards, such as GA4GH and BioJS, ensures that our contributions will be interoperable. Our designs will be vetted by users through testing in tumor boards and at designated booths at international cancer meetings. This will ensure that our platform will effectively serve researchers, biologists and clinicians now and into the future of precision medicine.

项目总结/摘要 NCI的大型临床试验和研究项目一直在以最快的速度生成癌症基因组数据。 前所未有的速度，阐明了癌症发生和演变的机制，以及对 疗法为了充分利用这一超过千万亿字节（1015字节）的综合数据资源， 科学界需要对数据进行深入的、用户友好的交互式计算机可视化。这些将 使研究人员能够发现驱动每个患者癌症的分子过程， 将这些知识转化为新的疗法，最终提高我们对癌症的认识， 机制和患者结局。 我们建议开发一个基于Web的数据中心和Viz Hub平台，让研究人员可以可视化 NCI的癌症基因组学数据的丰富性。可视化将由一个 一套“以生物为中心”的观点，由生物信息学社区开发，并在BioJS中提供，一个开放的， 表示生物数据的工具的源存储库。这将建立一个基于网络的新范式， 通过可共享和可重用的模块化开源组件进行生物数据可视化开发。 为了启动Viz Hub平台，我们将把七个流行的第三方生物信息学可视化整合到 现有的UCSC Xena浏览器使用即插即用框架。我们将与几个国家密切合作， 临床实验室为下一代基因组医学开发两种新的翻译可视化。一 将是一个纵向组学集成器，在钻孔时为研究人员提供患者的突出概述 在整个治疗过程中收集的基因组和功能数据。另一个将帮助研究人员 研究对各种新型免疫疗法的反应，这些疗法有望彻底改变癌症 治疗这个免疫追踪器和免疫编辑查看器将显示免疫原性新抗原，T细胞 受体和B细胞受体随疾病进展和对治疗的反应而变化。 科学界的可视化需求，NCI的基因组数据分析网络和疾病 工作组将通过我们的公共和限制数据中心系统得到充分支持。我们的高- 性能数据中心将易于安装在各种计算环境中。用户将 能够整合来自大型财团和个人研究人员（包括他们自己的）的公共和受限数据 实验室），在我们基于Web的Viz Hub上无缝连接。我们对生物信息学社区标准的承诺，例如 GA 4GH和BioJS，确保我们的贡献将是可互操作的。我们的设计将由用户审查 通过在肿瘤委员会和国际癌症会议的指定展位进行测试。这将确保 我们的平台将有效地为研究人员、生物学家和临床医生提供服务， 药