Cloud-Based Analysis of TCR Repertoire Sequencing Data

基于云的 TCR 谱库测序数据分析

• 批准号: 8394673
• 负责人: David Scott Johnson
• 金额: $ 15.65万
• 依托单位: GIGAGEN, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-08 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8394673
• 关键词: Adoption; Algorithms; Applications Grants; Area; Autoimmune Diseases; Bioinformatics; Capital; Clinical; Code; Communities; Complex; DNA Sequence; Data; Data Analyses; Data Quality; Data Set; Databases; Diagnostic; Disease; Disease Progression; Doctor of Philosophy; Foundations; Generic Drugs; Genes; Government; Grant; Human; Imagery; Immune; Immune response; Immune system; Immunology; Immunotherapy; Institution; Internet; Licensing; Marketing; Methods; Monitor; Online Systems; Output; Patients; Phase; Process; Provider; Publications; Research; Research Infrastructure; Research Personnel; Resources; Running; Sampling; Scientist; Security; Sequoia; Services; Small Business Innovation Research Grant; Specialist; Specific qualifier value; T-Cell Receptor; T-Lymphocyte; Technology; Testing; Time; United States National Institutes of Health; Work; Writing; base; cancer immunotherapy; commercialization; computerized data processing; next generation; novel; operation; product development; repository; response; tool; vaccine development; web site

DESCRIPTION (provided by applicant): We propose to build a cloud-based platform and website for the processing, storage, analysis, comparison, and visualization of data generated by deep sequencing of the T cell receptor (TCR) repertoire. Profiling the abundance and expansion of clonally T cell subpopulations (as determined by TCR sequence) fills an unmet diagnostic need for monitoring the immune system during disease progression or in response to immunotherapy. Although several groups have used next-generation sequencing (NGS) to profile the TCR repertoire, widespread adoption of this and other NGS methods is hampered by a lack of bioinformatics tools and resources (Kahn, 2011; Pollack, 2011). Analysis tools do exist for generic NGS applications, but a technology gap remains for specialized applications such as TCR repertoire sequencing. GigaGen performs TCR repertoire sequencing as a service, and offering analysis tools would give us a competitive advantage over other providers while broadening the market for immune signature profiling methods in general. We have already developed a computational pipeline to process raw sequencer output, but we see a clear customer need for tools to interpret and analyze TCR repertoire data. In this Phase I grant, we will: (1) expand our existing pipeline to fully automate NGS data processing and transfer; (2) build a website for users to access and manage their data; and (3) develop algorithms, tools, and workflows that allow users to analyze complex data using cloud computing. The test of feasibility will be for immunology researchers with little computational expertise or resources to perform the following operations on their data through a standard web browser: (1) track abundance and expansion of user-specified TCR sequences across multiple data sets; (2) compare TCR repertoire data sets using resampling-based statistical tests that run in the cloud; and (3) create and configure informative, publication-quality data visualizations. The infrastructure we develop in Phase I will enable broad commercialization of TCR repertoire sequencing in Phase II. We also plan to use the infrastructure we develop as the basis for building a public website and repository for immune sequencing data, to be co-hosted with an educational institution or government entity. PUBLIC HEALTH RELEVANCE: New DNA sequencing methods have the potential to revolutionize how we monitor a patient's immune system during disease progression and treatment. We are building web-based data processing and analysis tools that allow clinicians and researchers to use DNA sequencing data to better understand the immune system.

描述（由申请人提供）：我们建议建立一个基于云的平台和网站，以处理T细胞受体（TCR）曲目的深入测序生成的数据的处理，存储，分析，比较和可视化。分析克隆T细胞亚群的丰度和扩展（由TCR序列确定）填补了未满足的诊断需求，以监测疾病进展过程中的免疫系统或对免疫疗法的反应。尽管几个小组已经使用了下一代测序（NGS）来介绍TCR曲目，但由于缺乏生物信息学工具和资源而阻碍了这种和其他NGS方法的广泛采用（Kahn，2011; Pollack，2011）。确实存在用于通用NGS应用程序的分析工具，但是对于TCR曲目测序等专门应用程序的技术差距仍然存在。 Gigagen执行TCR曲目测序作为一项服务，提供分析工具将使我们比其他提供商具有竞争优势，同时拓宽一般的免疫签名分析方法的市场。我们已经开发了一条计算管道来处理RAW Sequencer输出，但是我们看到客户清楚地需要解释和分析TCR曲目数据。在此阶段I授予中，我们将：（1）将现有管道扩展到完全自动化NGS数据处理和传输； （2）构建一个网站供用户访问和管理其数据； （3）开发算法，工具和工作流程，使用户可以使用云计算分析复杂数据。可行性的测试将用于具有很少的计算专业知识或资源的免疫学研究人员，可以通过标准的Web浏览器对其数据进行以下操作：（1）跟踪丰度和在多个数据集中用户指定的TCR序列的扩展； （2）使用在云中运行的基于重采样的统计测试比较TCR曲目数据集； （3）创建和配置信息丰富的出版物质量数据可视化。我们在第一阶段开发的基础架构将使TCR曲目测序在II阶段进行广泛的商业化。我们还计划使用开发的基础设施作为建立公共网站和存储库以进行免疫测序数据的基础，并与教育机构或政府实体共同托管。 公共卫生相关性：新的DNA测序方法有可能彻底改变我们在疾病进展和治疗过程中如何监测患者的免疫系统。我们正在构建基于Web的数据处理和分析工具，允许临床医生和研究人员使用DNA测序数据来更好地了解免疫系统。