Hardening Globus Genomics to make large-scale genomics analysis available for everybody

项目摘要 Globus基因组学已经在芝加哥大学计算研究所作为一项先进的 基因组分析平台以软件即服务的形式在亚马逊网络服务上运行，由Globus提供支持 还有银河系。它旨在满足研究人员和核心实验室提供商的需求，他们需要 具有最先进功能的高质量服务，可帮助简化数据移动、简化 基因组分析流水线，自动化这些流水线的执行，并在 弹性计算基础架构。已经开发了三年的Globus基因组学已经被使用 由主要机构的研究人员广泛研究，包括华盛顿大学、芝加哥大学、 华盛顿大学圣路易斯分校、乔治城大学和约翰斯·霍普金斯大学。有很大的潜力和 需要扩大该服务的使用范围，以满足现有的两家公司快速增长的基因组分析需求 用户和大型新用户社区。我们现在提出的工作将扩大 通过提供(1)由数千名用户同时进行数千次分析的可扩展性，(2)支持 提供最先进的高性能工作流程和工具，包括大规模归责分析和共识 呼吁结构变化，(3)自动化成本和性能优化，以大幅削减云计算成本 和周转时间，以及(4)用于大规模分析的端到端和摘要视图的功能强大的仪表板。 这些改进将通过以下关键领域的发展而得以实现：增强和扩展 Globus Genome计算框架，支持高性能可靠执行标准和 针对大数据集和超大型数据集的新型NGS分析工作流；创建和维护最先进的 用于变量调用、全基因组分析、RNAseq和ChipSeq的管道，这涉及到计算 分析最新版本的工具并了解不同的计算模式以实现最佳执行 在Amazon Web服务上；创建分析和优化框架，以实现自动化、成本和/或 在大型云系统上对NGS应用程序和工作流进行时间优化配置；并创建 自动计算配置框架。赠款奖励将使我们能够满足以下关键需求 当前和潜在用户，从而为研究人员提供重要的生物信息学平台 否则，就不能轻松访问这些功能。

Project Summary Globus Genomics has been developed at the Computation Institute, University of Chicago as an advanced genomics analysis platform running as a Software-as-a-Service on Amazon Web Services, powered by Globus and Galaxy. It was developed to meet the needs of both researchers and core lab providers who require a high-quality service with state-of-the-art capabilities to help streamline data movement, simplify the creation of genomics analysis pipelines, automate the execution of those pipelines, and run analysis at very large scale on elastic compute infrastructure. Globus Genomics, under development for three years, has been used extensively by researchers at leading institutions, including University of Washington, University of Chicago, Washington University St. Louis, Georgetown University, and Johns Hopkins. There is significant potential and demand to expand use of the service to meet the rapidly growing genomics analysis needs of both existing users and large communities of new users. We now propose work that will amplify the utility and impact of Globus Genomics by providing (1) scalability to 1000s of simultaneous analyses by 1000s of users, (2) support for state-of-art high performance workflows and tools, including large-scale imputation analysis and consensus calling on structural variants, (3) automated cost and performance optimization to slash cloud computing costs and turnaround times, and (4) powerful dashboards for end-to-end and summary views of large-scale analyses. These enhancements will be enabled by development in the following key areas: enhancing and extending the Globus Genomics computational framework to enable high-performance reliable execution of standard and novel NGS analysis workflows on large and extremely large datasets; creating and maintaining state-of-the-art pipelines for variant calling, whole genome analysis, RNASeq and ChipSeq, which involves computationally profiling the latest versions of tools and understanding different computational modalities for optimal execution on Amazon Web Services; creating a profiling and optimization framework to enable automated, cost- and/or time-optimal configuration of NGS applications and workflows on large cloud systems; and creating an automatic computational provisioning framework. The grant award would allow us to address key needs of current and prospective users and thus to provide an important bioinformatics platform to researchers who otherwise could not easily access such capabilities.