Support for the use and evaluation of large cloud-based genomic datasets.

项目摘要/摘要 该项目的目标是开发以云为重点的培训和使用云的基准 由选定的NIH资助的大数据财团提供的资源。需要通过以下方式进行培训 互动嘉宾利用现有软件通过云进行大规模数据分析。我们会 还可以通过将NIH Anvil服务作为平台与 用于开发和比较管道的原生Google云平台，交互分析，如 设置和使用Jupyter笔记本电脑，并通过自动排行榜运行基准测试。这些 排行榜将与Synapse提供的替代方案进行比较。我们有经验 设计、实施和主办培训学员和工作人员教育的大型活动或研讨会 研究人员了解可用于利用大量基于云的数据并将其集成在一起的工具和方法 将数据输入计算分析管道。云正在成为计算能力的关键组件 生物学家和更大的生物医学研究界在探索人类基因组方面，其 调节，与疾病的联系，以及结构。然而，由于使用云的复杂性- 基于资源这并没有渗透到没有高级计算技能的学生和资源中。 在我们10年在云上实施和管理分析管道的经验中，我们拥有 显示了使用基于云的大规模分析的优越优势。这个项目的目标是 提供关于使用基于云的分析软件、易于使用的数据共享的互动培训，以及 评估两个平台协助创建有效工具的能力。我们有横切和 在数据管理、基因组学、信息学、网络分析和 隐私保护应用程序以及我们领导大型数据协调中心、管理、 以及协调数据和元数据，以及创建黄金标准知识库。

Project Summary/Abstract The goal of this project is to develop cloud-focused training and benchmarks for the use of cloud resources provided from selected NIH funded large data consortium. There is a need for training via interactive jamborees in the use of existing software for large-scale data analysis via the cloud. We will also evaluate the usefulness of the cloud by comparing the NIH AnVIL service as a platform versus the native Google Cloud Platform for developing and comparing pipelines, interactive analyses such as setup and use of Jupyter notebooks, and for running benchmarks via automated leaderboards. These leaderboards will be compared with what is provided by Synapse as an alternative. We have experience in designing, implementing, and hosting jamborees or workshops for the education of trainees and staff researchers in the tools and methods available to utilize large cloud-based data, and to integrate these data into computational analysis pipelines. The cloud is becoming a critical component for computational biologists and the greater biomedical research community in exploring the human genome, its regulation, association with disease, and structure. However, because of the complexity of using cloud- based resource this has not trickled down to students and resources without advanced computing skills. In our 10 years of experience implementing and managing analysis pipelines on the cloud we have shown the superior advantage for use of cloud-based large-scale analyses. The goal of this project is to provide interactive training for the use of cloud-based analysis software, easy to use data sharing, and evaluate two platforms in their ability to assist in creating effective tools. We have cross-cutting and unparalleled technical expertise in data management, genomics, informatics, network analysis, and privacy-preserving applications as well as our roles leading large data coordination centers, managing, and coordinating data and metadata, as well as creating gold standard knowledgebases.