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

项目摘要：NHGRI基因组数据科学分析，可视化和信息学实验室空间 （AnVIL）将为下一代计算基因组研究提供动力。我们将开发AnVIL 环境使用领先的国家级网络基础设施作为基础， NHGRI研究人员审查的广泛使用的分析环境和框架。我们以用户为中心的解决方案 数据访问、分析和可视化将使各级专业知识的调查人员能够充分利用 基因组数据集使用他们已经熟悉的环境，利用精心设计和 优化的科学计算基础设施，以提高效率和降低成本。 目标1：设计AnVIL数据和计算平台。我们将利用TACC科学云和 龙舌兰科学即服务平台，用于部署支持数据存储的云环境， 访问和计算NHGRI研究社区的需求。 目标二。为数据和计算访问开发API。为了最大限度地提高AnVIL的全域影响力，我们将 利用社区的努力和我们自己的集体经验，支持不同的基因组分析， 访问标准，并设计和实现AnVIL API。 目标3。构建一个AnVIL metaportal集成广泛使用的分析平台。我们将创建一个单一的 Metaportal位于TACC的科学云内，提供用户数据和活动的统一视图， 来源和计费，以及访问几个最广泛使用的工作台进行基因组研究。 这些工作台包括Bioconductor、Galaxy、基因组建模系统、Juypter和RStudio。的 metaportal还将提供最流行的基因组可视化工具。 目标4。开发新的数据聚合、索引和查询方案，以提高分析效率， 降低成本。我们将建立方法，包括关键统计数据的索引和预先计算， 更好地利用现有的（例如，TCGA、GTEx）和未来的大型数据集，目标是提高数据效用， 降低了对大规模数据集提出科学查询的成本。 目标5：发展培训和外联基础设施和材料。我们将为培训提供支持 直接在AnVIL平台，包括紧密耦合到MOOC风格的课程，自我导向的培训 材料和支持材料进行在线和面对面的培训研讨会。 目标6：参与有效的项目治理和评估。我们将建立一个领导层， 涉及NHGRI关键利益相关者的管理结构，包括项目工作人员和NHGRI 任命数据指导委员会和外部咨询委员会。 这项工作的关键创新是我们利用现有的硬件、软件和人力资源， 为建设AnVIL的挑战创造一个切实可行的解决方案。

Project Summary: The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab‐space (AnVIL) will power the next generation of computational genomic research. We will develop the AnVIL environment using the leading national‐scale cyberinfrastructure as the foundation supporting the most widely‐used analysis environments and frameworks vetted by NHGRI researchers. Our user‐centered solution for data access, analysis, and visualization will enable investigators across all levels of expertise to fully utilize genomic datasets using environments they are already familiar with, leveraging well‐engineered and optimized scientific computing infrastructure for greater efficiency and lower costs. Aim 1: Engineer the AnVIL Data and Compute Platform. We will leverage the TACC Science Cloud and the Agave Science‐As‐A‐Service platform to deploy a cloud‐based environment supporting the data storage, access, and compute needs of the NHGRI research community. Aim 2. Develop APIs for Data and Compute Access. To maximize the domain‐wide impact of AnVIL, we will draw on community efforts and our own collective experience supporting diverse genomic analyses to define access standards and to design and implement AnVIL APIs. Aim 3. Build an AnVIL metaportal integrating widely used analysis platforms. We will create a single metaportal residing within TACC's Science Cloud providing a unified view of users' data and activities, provenance and billing, and access to several of the most widely used workbenches for genomic research. These workbenches include Bioconductor, Galaxy, the Genome Modeling System, Juypter, and RStudio. The metaportal will also provide access to the most popular genomic visualization tools. Aim 4. Develop novel data aggregation, indexing and query schemes to increase analysis efficiency and reduce cost. We will build approaches, including indexing and pre‐computation of key statistics, to make better use of existing (e.g., TCGA, GTEx) and future large datasets with the goal of increasing data utility and decreasing the cost of posing scientific queries against massive datasets. Aim 5: Develop training and outreach infrastructure and materials. We will build support for training directly in the AnVIL platform, including tight coupling to MOOC style courses, self‐directed training materials, and support materials for conducting online and in‐person training workshops. Aim 6: Engage in effective project governance and assessment. We will establish a leadership and management structure involving key stakeholders from NHGRI, including program staff and the NHGRI appointed Data Steering Committee and External Advisory Committee. The key innovation of this work is our leveraging of existing hardware, software, and human resources to create a practical and pragmatic solution to the challenge of building the AnVIL.