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.

项目描述（申请人提供）：拟建立一个基于云的平台和网站，用于T细胞受体（TCR）库深度测序产生的数据的处理、存储、分析、比较和可视化。分析克隆T细胞亚群的丰度和扩增（由TCR序列决定）填补了在疾病进展或免疫治疗反应期间监测免疫系统的未满足诊断需求。尽管一些研究小组已经使用下一代测序（NGS）来分析TCR库，但由于缺乏生物信息学工具和资源，这种方法和其他NGS方法的广泛采用受到阻碍（Kahn, 2011; Pollack, 2011）。通用NGS应用的分析工具确实存在，但TCR曲目测序等专门应用的技术差距仍然存在。GigaGen提供TCR全库测序服务，提供分析工具将使我们比其他供应商更具竞争优势，同时拓宽了免疫特征分析方法的市场。我们已经开发了一个计算管道来处理原始测序器输出，但我们看到一个明确的客户需要工具来解释和分析TCR曲目数据。在第一阶段的授权中，我们将：(1)扩大我们现有的管道，使NGS数据处理和传输完全自动化；(2)建立一个网站，供用户访问和管理他们的数据；(3)开发允许用户使用云计算分析复杂数据的算法、工具和工作流。对于缺乏计算专业知识或资源的免疫学研究人员来说，可行性的测试将是通过一个标准的网络浏览器对他们的数据进行以下操作：(1)在多个数据集上跟踪用户指定的TCR序列的丰度和扩展；(2)使用在云中运行的基于重采样的统计测试来比较TCR全表数据集；(3)创建和配置信息丰富、具有发布质量的数据可视化。我们在第一阶段开发的基础设施将在第二阶段实现TCR曲目测序的广泛商业化。我们还计划利用我们开发的基础设施作为基础，建立一个公共网站和免疫测序数据存储库，与教育机构或政府实体共同托管。