A Federated Galaxy for user-friendly large-scale cancer genomics research

用于用户友好的大规模癌症基因组学研究的联邦星系

• 批准号: 10245142
• 负责人: Jeremy Goecks
• 金额: $ 76.23万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-11 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10245142
• 关键词: Awareness; Benchmarking; Centers for Disease Control and Prevention (U.S.); Communities; Community Developments; Complement; Data; Data Analyses; Data Analytics; Data Commons; Data Scientist; Data Set; Data Sources; Data Store; Development; Discipline; Disease; Galaxy; Genomic Data Commons; Genomics; Health; Health Sciences; Individual; Informatics; Infrastructure; Internet; Knowledge; Language; Lead; Life; Location; Malignant Neoplasms; Maps; Metadata; Minority; Names; Online Systems; Oregon; Output; Pharmaceutical Preparations; Phenotype; Play; Privatization; Proteomics; Reporting; Research; Research Personnel; Resources; Running; Scientist; Services; Standardization; System; Technology; Time; Universities; Variant; Visualization; Work; analytical method; anticancer research; cancer genomics; cancer health disparity; cloud based; cloud platform; computational platform; computing resources; cost; data exchange; data resource; data standards; design; distributed data; drug response prediction; empowered; flexibility; genomic data; genomics cloud; machine learning algorithm; machine learning method; multiple omics; next generation; phenotypic data; precision oncology; prediction algorithm; response; skills; tool; transcriptome sequencing; tumor; user-friendly; web interface

Project Summary Cancer research is now a data-driven discipline, but only a minority of cancer researchers are data scientists. This severely restricts our ability to effectively study and cure the disease. The far reaching significance of our project is in federating disparate data and computational resources in order to provide a unifying analysis platform for computational cancer research. We will extend the popular scientific workbench Galaxy (https://galaxyproject.org) so that it can integrate with distributed data and compute resources used and needed by cancer researchers, including those resources in the NCI Cancer Research Data Commons (NCR DC). Our Federated Galaxy system will allow users to seamlessly access NCR DC data across multiple resources. It will support multiple analysis scenarios tuned to skills and computational requirements of individual researchers. The aims of this project are: Aim 1. Extend Galaxy for working with distributed cancer genomics and phenotypic data. This will enable Galaxy users to access both public and private cancer data regardless of their actual physical location. Best-practice approaches will be used for accessing restricted datasets. Aim 2. Enhance Galaxy for context-aware, distributed cancer genomics analyses using shared workflow representations. This will enable Galaxy users to run genomics analyses on different clouds, ultimately reducing the time, cost, and data transfer associated with analyses. Aim 3. Apply Federated Galaxy to precision oncology research. Workflows developed in this aim will leverage the technologies in Aims 1 and 2 to benchmark machine learning algorithms for predicting tumor phenotype and drug response. Interactive reports will summarize benchmarking results and utilize ITCR visualizations for deep dives into results. Our system will provide a singular access point to distributed cancer datasets and will enable these data to be analyzed within a single portal in a way that satisfies multiple analysis scenarios and utilizes diverse computational resources. Finally, a cloud-centric Galaxy built for the NCR DC will substantially grow the community of users working with the GDC and the NCR DC. This is because Galaxy brings with itself a vibrant world-wide community of users and developers, which numbers tens of thousands of scientists. These individuals will help to tune the GDC and other resources within the NCR DC to the needs of real-life analysis scenarios and will enrich the set of tools accessible to cancer researchers.

项目摘要 癌症研究现在是一门数据驱动的学科，但是只有少数癌症研究人员是数据科学家。这严重限制了我们有效研究和治愈疾病的能力。我们项目的重要性在于联合不同的数据和计算资源，以便为计算癌症研究提供统一的分析平台。 我们将扩展流行的科学工作台星系（https://galaxyproject.org），以便它可以与癌症研究人员（包括NCI癌症研究数据共享CONSONS（NCR DC）中的这些资源（NCR DC）中的这些资源相结合。我们联合的银河系系统将允许用户无缝地跨多个资源访问NCR DC数据。它将支持多种分析方案，以调整各个研究人员的技能和计算要求。 该项目的目的是： AIM 1。扩展银河系，用于使用分布式癌症基因组学和表型数据。这将使Galaxy用户能够访问公共和私人癌症数据，无论其实际的实际位置如何。最佳实践方法将用于访问限制数据集。 AIM 2。使用共享工作流表示形式来增强情境感知的，分布式癌症基因组学分析。这将使Galaxy用户能够对不同云进行基因组学分析，最终减少与分析相关的时间，成本和数据传输。 目标3。将联邦星系应用于精确的肿瘤学研究。在此目标中开发的工作流将利用目标1和2中的技术来基准机器学习算法来预测肿瘤表型和药物反应。交互式报告将总结基准测试结果，并利用ITCR可视化来深入研究结果。 我们的系统将为分布式癌症数据集提供一个奇异的访问点，并以满足多个分析场景并利用各种计算资源的方式在单个门户网站内进行分析。最后，为NCR DC建造的以云为中心的星系将大大发展与GDC和NCR DC一起工作的用户社区。这是因为Galaxy带来了一个充满活力的全球用户和开发人员社区，这些社区数以万计的科学家。这些人将帮助NCR DC内的GDC和其他资源调整现实生活分析方案的需求，并丰富癌症研究人员可以使用的一组工具。