Cloud-Based Bioinformatics for Immune Repertoire Analysis

用于免疫谱分析的基于云的生物信息学

• 批准号: 8642691
• 负责人: David Scott Johnson
• 金额: $ 113.52万
• 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 2016-07-22
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8642691
• 关键词: Acute; Adoption; Applications Grants; Area; Autoimmune Diseases; B cell repertoire; Behavior; Bioinformatics; Capital; Charge; Clinical Research; Complementarity Determining Region III; Complex; Computational algorithm; Computer software; DNA Sequence; Data; Data Analyses; Data Set; Development; Diagnostic; Disease; Disease Progression; Doctor of Philosophy; Ensure; Fees; Foundations; Genes; Housing; Human; Imagery; Immune; Immune response; Immune system; Immunoglobulins; Immunology; Individual; Licensing; Methods; Monitor; Monoclonal Antibodies; Monte Carlo Method; Names; Online Systems; Patients; Phase; Price; Process; Publications; Quality Control; Research; Research Personnel; Resources; Sampling; Scientist; Sequence Analysis; Sequoia; Services; Small Business Innovation Research Grant; Specialist; T-Cell Receptor; T-Lymphocyte; Testing; Time; Translating; United States National Institutes of Health; Work; base; cancer immunotherapy; commercialization; complementarity-determining region 3; computerized data processing; computerized tools; computing resources; deep sequencing; empowered; innovation; meetings; next generation sequencing; product development; public health relevance; quality assurance; tool; usability; web site

PROJECT SUMMARY Project Title: Cloud-Based Bioinformatics for Immune Repertoire Analysis Organization: GigaGen Inc. PI: David S. Johnson, Ph.D. The Specific Aim of this Phase II SBIR grant application is to launch ClonoByte", a website and cloud-based platform for the processing, storage, analysis, comparison, and visualization of immune signature data sets generated by deep sequencing of immune repertoires. There is a rapidly growing demand for T cell receptor (TCR) and immunoglobulin (Ig) repertoire sequencing as a routine clinical and research practice, but the lack of computational resources and tools is blocking widespread adoption. There is thus a strong additional need for resources to translate immune repertoire data generated by NGS into a format useful to immunology researchers and clinicians. The innovation of our product is to enable researchers with little or no bioinformatics expertise or resources to analyze and interpret immune repertoire sequencing data using a cloud-based platform. In Phase I, we first built individual computational algorithms and components for processing, analysis, and visualization of immune repertoire data, particularly (i) primary processing of sequencing data for V/J gene identification and complementarity-determining region 3 (CDR3) extraction, (ii) calculation of sample oligoclonality and sample-sample similarity, (iii) visualization of comparisons of multiple data sets, and (iv) statistical significance testing of findings via a Monte Carlo method. We tested the computational modules with actual immune repertoire data generated in-house for internal research and for external customers. We then integrated several of the key components into the alpha version of ClonoByte". In Phase II, we will take the following steps to launch ClonoByte": (i) integrate remaining standalone computational modules into ClonoByte" for beta release; (ii) perform software quality control (QC) and quality assurance (QA) and front- end usability testing on ClonoByte" beta; and (iii) refine ClonoByte" beta to launch version. We will be successful if the website can achieve the following in the hands of end-users: (i) securely upload raw immune repertoire sequencing FASTQ files for automated primary processing; (ii) track abundance and expansion of clonotype sequences across multiple annotated data sets; and (iii) compare data sets on the basis of whole- repertoire similarity, sample diversity, and behavior of specific clonotypes. After Phase II, the website will be fully available for commercial use by immune repertoire researchers worldwide. GigaGen's pricing plan will be to offer free use of ClonoByte" for the first 10 samples, and then charge a $50/year subscription fee for users that upload more than 10 samples. Though ClonoByte" will enable analysis of immune repertoire sequencing data generated by most amplification kits or third-party services, GigaGen will use ClonoByte"'s best-in-class features and ease of use to promote its own GigaMune(R) lab services and amplification kits for immune repertoire sequencing.

项目摘要 项目名称：基于云的生物信息学用于免疫库分析 Registrant Organization：liu hanlin PI：大卫S.约翰逊博士 第二阶段SBIR拨款申请的具体目标是推出ClonoByte”，一个基于云的网站， 用于处理、存储、分析、比较和可视化免疫特征数据集的平台 通过对免疫系统进行深度测序而产生。 对T细胞受体（TCR）和免疫球蛋白（IG）库测序的需求迅速增长， 常规的临床和研究实践，但缺乏计算资源和工具阻碍了 广泛采用。因此，对翻译免疫库数据的资源存在强烈的额外需求 由NGS生成的格式对免疫学研究人员和临床医生有用。我们的创新 产品是使研究人员很少或根本没有生物信息学专业知识或资源来分析和解释 使用基于云的平台对免疫库测序数据进行分析。 在第一阶段，我们首先构建了用于处理、分析和 免疫库数据的可视化，特别是（i）V/J基因的测序数据的初步处理 鉴定和互补决定区3（CDR 3）提取，（ii）样品计算 寡克隆性和样品-样品相似性，（iii）多个数据集比较的可视化，和（iv） 通过Monte Carlo方法对结果进行统计学显著性检验。我们测试了计算模块， 内部为内部研究和外部客户生成的实际免疫库数据。然后我们 将几个关键组件集成到ClonoByte的alpha版本中”。在第二阶段，我们将采取 （i）将剩余的独立计算模块集成到“ClonoByte”中; ClonoByte”用于beta版本;（ii）执行软件质量控制（QC）和质量保证（QA）以及前端- 结束ClonoByte”测试版的可用性测试;以及（iii）完善ClonoByte”测试版以推出版本。我们将 如果网站在最终用户手中能做到以下几点就成功了：（一）安全地上传原始免疫 用于自动化初级处理的库测序FASTQ文件;（ii）跟踪丰度和扩展 跨多个注释的数据集的克隆型序列;和（iii）基于整个- 库相似性、样品多样性和特定克隆型的行为。 在第二阶段之后，该网站将完全可供免疫库研究人员商业使用 国际吧GigaGen的定价计划将是提供免费使用ClonoByte”的前10个样本，然后 对上传超过10个样本的用户收取50美元/年的订阅费。虽然ClonoByte”将 能够分析由大多数扩增试剂盒或第三方扩增试剂盒生成的免疫谱系测序数据， 服务，GigaGen将使用ClonoByte的一流功能和易用性，以促进自己的 GigaMune（R）实验室服务和扩增试剂盒，用于免疫库测序。