Implementing the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

实施基因组数据科学分析、可视化和信息学实验室空间 (AnVIL)

• 批准号: 10405959
• 负责人: Jeremy Goecks
• 金额: $ 64.5万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-21 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10405959
• 关键词: Address; Bioconductor; Biomedical Research; Budgets; Cloud Computing; Data; Data Analyses; Data Science; Data Set; Data Storage and Retrieval; Development; Environment; Fast Healthcare Interoperability Resources; Galaxy; Generations; Genome; Genomics; Informatics; Language; Lead; Link; Modeling; Movement; National Human Genome Research Institute; Publishing; Research; Research Personnel; Running; Services; Statistical Data Interpretation; System; Systems Analysis; Technology; United States National Institutes of Health; Visualization; Work; base; cloud based; cloud platform; computing resources; cost; data access; data management; data repository; data resource; genomic data; health data; interoperability; member; next generation; outreach; resource guides; tool; working group

Project Summary NIH-sponsored biomedical research is increasingly moving to cloud-based data storage and analysis systems. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) powers the next generation of computational genomics research across the NHGRI using cloud-scale data and compute resources. The platform provides multiple entry points for data access and analysis, including data search with Gen3, workflows with Terra and Dockstore, notebook environments including Jupyter and RStudio, Bioconductor packages for analysis leveraging AnVIL APIs and services, and Galaxy instances for interactive analysis. By providing a unified environment for data management and compute, AnVIL eliminates the need for data movement, allows for controlled access to sensitive data, and provides elastic computing resources that can be acquired by researchers as needed. The NIH Cloud Platform Interoperability (NCPI) effort aims to address interoperability issues across NIH cloud systems, including AnVIL, by implementing key technologies and standards. We will work with NCPI working groups to define use cases and lead outreach as well as implement several major technologies within the AnVIL. First, we will enhance support for the NIH Researcher Auth Service (RAS) to enable researchers to establish their identity and access data they are authorized to use across Terra and Galaxy. Second, we will enhance support for the Global Alliance for Genomics and Health (GA4GH) Data Repository Service (DRS) so that data consumers can access data objects in a single, standard way. Third, we will enhance support in AnVIL for the Fast Healthcare Interoperability Resources (FHIR) standard. This will facilitate access to eMERGE and related projects by users in AnVIL and other NCPI platforms. Next, we will develop new resources and guides for budgeting for cloud computing. For this, we will identify the most commonly used tools and workflows run within Galaxy, and model the cost of these tools by varying data sets (e.g., sequencing coverage or number of genomes) and computational resources (e.g., number of CPUs, peak RAM). Statistical analysis of results will be published and serve as a tool to decrease cost as a barrier to cloud research and cloud interoperabily. Finally, interoperability of workflow generation is hampered by the fact that not all cloud platforms support the same sets of workflow languages. To address this, we will develop a Kubernetes- based computational engine to link workflows from multiple workflow languages. This work will initially focus on usage of Snakemake workflows, followed by extending development to support the workflow languages WDL, CWL and Galaxy workflows using their respective execution engines. This will simplify the transition from institutional HPC to the cloud and make it possible for researchers to seamlessly execute workflows across NCPI platforms.

项目摘要 NIH赞助的生物医学研究越来越多地转向基于云的数据存储和分析系统。 NHGRI基因组数据科学分析，可视化和信息学实验室空间（Anvil）为 使用云规模数据跨NHGRI的下一代计算基因组学研究并计算 资源。该平台为数据访问和分析提供了多个入口点，包括与数据搜索 Gen3，与Terra和Dockstore的工作流程，笔记本环境，包括Jupyter和Rstudio， 用于分析的生物处理套件利用砧座API和服务，以及银河系实例进行交互式 分析。通过为数据管理和计算提供统一的环境，Anvil消除了需求 对于数据移动，允许对敏感数据的控制访问，并提供弹性计算资源 研究人员可以根据需要获取。 NIH云平台互操作性（NCPI）努力旨在解决NIH的互操作性问题 通过实施关键技术和标准，包括铁砧在内的云系统。我们将与NCPI合作 工作组定义用例和领导外展，并在内部实施多种主要技术 砧。首先，我们将增强对NIH研究人员授课服务（RAS）的支持，以使研究人员能够 建立他们的身份和访问数据，被授权在Terra和Galaxy上使用。第二，我们会的 增强对全球基因组和健康联盟（GA4GH）数据存储库服务（DRS）的支持 数据消费者可以以单一的标准方式访问数据对象。第三，我们将增强支持 快速医疗保健互操作性资源（FHIR）标准的砧。这将有助于进入 用户在Anvil和其他NCPI平台中出现和相关项目。接下来，我们将开发新的 用于云计算预算的资源和指南。为此，我们将确定最常用的 工具和工作流程在银河系内运行，并通过改变数据集（例如， 测序覆盖范围或基因组数量）和计算资源（例如，CPU的数量，峰值RAM）。 结果的统计分析将发布，并作为降低成本作为云研究障碍的工具 和云室内。最后，工作流程的互操作性受到以下事实的阻碍 云平台支持相同的工作流语言集。为了解决这个问题，我们将开发一个Kubernetes- 基于从多种工作流语言链接工作流程的计算引擎。这项工作最初将 专注于使用Snakemake工作流程，然后扩展开发以支持工作流程 语言WDL，CWL和Galaxy Workflows使用各自的执行引擎。这将简化 从机构HPC过渡到云，使研究人员无缝执行 跨NCPI平台的工作流程。