Global Infrastructure for Collaborative High-throughput Cancer Genomics Analysis

协作高通量癌症基因组分析的全球基础设施

基本信息

批准号：
9571405
负责人：
GAD A GETZ
金额：
$ 5.08万
依托单位：
BROAD INSTITUTE, INC.
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-20 至 2021-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9571405
关键词：
Address Algorithms Attention Bioinformatics Biological Biomedical Research Cancer Center Cancer Gene Mutation Categories Classification Clinic Clinical Clinical Data Clinical Trials Code Collaborations Communities Complex Consensus Correlative Study Credentialing Custom Data Data Aggregation Data Analyses Data Analytics Data Set Databases Deposition Development Documentation Ensure Evolution Freezing Future General Population Genome Data Analysis Center Genome Data Analysis Network Genomic Data Commons Goals Institutes Knowledge Link Malignant Neoplasms Manuscripts Mission Modeling Molecular Morphologic artifacts National Cancer Institute Paper Pathway Analysis Patient-Focused Outcomes Patients Phase Process Production Publications Publishing Reporting Reproducibility Research Infrastructure Research Personnel Running Sampling Science Scientist Services Structure Suggestion Summary Reports System The Cancer Genome Atlas Time TimeLine Tumor Subtype Update Vertebral column Work Writing base cancer genome cancer genomics clinical diagnostics clinically relevant cost disorder subtype experience experimental study genome analysis high standard improved innovation insight member molecular subtypes operation prevent repository tool treatment response user-friendly whole genome working group

项目摘要

Abstract The Cancer Genome Atlas (TCGA) set the standards for large-scale cancer genome projects worldwide. In the next phase, the National Cancer Institute and its Center for Cancer Genomics are planning large-scale projects closely tied to clinical questions and trials. In order to perform the analysis of these data, the NCI is creating a Genome Data Analysis Network (GDAN) of different types of Genome Data Analysis Centers (GDACs). Central to this Network is a single Processing GDAC, which will take all the harmonized data, as stored in the NCI's Genomics Data Commons, and perform higher level integrated analyses on these data to support both the Analysis Working Groups (AWGs) within the Network (which will be formed for each project to perform special analyses of the data and write manuscripts) as well as the entire biomedical research community. Herein we propose to build the centralized Processing GDAC on top of our FireCloud platform, an infrastructure to run large scale computation on the cloud in a fully rigorous and reproducible fashion. FireCloud development was based on our experience with Firehose, the Broad internal platform on which the standard TCGA data and analyses currently run. We propose to create and operate the GDAN Standard Workflow, incorporating tools actively developed and used within the GDAN and across the entire field, with particular emphasis on clinical tools. This Workflow will serve as the starting point for AWGs and set the highest standards of transparency, reproducibility and rigor for cancer genome analysis. The results of the Standard Workflow will be stored in a public database, and accessible via standard APIs, and used together with a continuously updated database of prior knowledge to create scientific reports that will be made available to the community, in a pre-publication manner. Finally, a major innovation is that AWG members will be able to login into FireCloud and rerun the entire workflow, or parts of it, with their own parameters and subsets of the data – thus making the entire GDAN analysis fully reproducible and scalable. Our goals are therefore: (1) To create a global infrastructure for collaborative extreme- scale cancer analysis; (2) Operate the Standard Workflows at scale; (3) Rapidly and continuously evolve the Standard Workflows; and (4) created improved capabilities for reporting, exploring the results, clinical diagnostics and reproducibility.

抽象的癌症基因组图谱 (TCGA) 为大规模癌症基因组设定了标准在下一阶段，国家癌症研究所及其中心将开展全球项目。癌症基因组学正在规划与临床问题密切相关的大型项目为了对这些数据进行分析，NCI 正在创建基因组数据。不同类型的基因组数据分析中心 (GDAC) 的分析网络 (GDAN)。该网络的核心是单个处理 GDAC，它将处理所有协调一致的数据数据，如存储在 NCI 的基因组数据共享中，并执行更高级别的集成对这些数据进行分析，以支持分析工作组 (AWG) 网络（将为每个项目形成对数据进行专门分析和写手稿）以及整个生物医学研究界。在此，我们建议在 FireCloud 之上构建集中处理 GDAC 平台，一个在云上以完全严格的方式运行大规模计算的基础设施和可复制的时尚 FireCloud 开发是基于我们的经验。 Firehose，标准 TCGA 数据和分析的 Broad 内部平台我们建议创建并运行 GDAN 标准工作流程，整合 GDAN 和整个领域积极开发和使用的工具领域，特别强调临床工具，该工作流程将作为起点。 AWG 的要点，并为透明度、可重复性和严格性设定最高标准标准工作流程的结果将存储在公共场所。数据库，可通过标准 API 访问，并与连续使用更新先验知识数据库以创建可供使用的科学报告最后，一个重大创新是 AWG。成员将能够登录 FireCloud 并重新运行整个工作流程或其中的一部分，具有自己的参数和数据子集 - 从而进行整个 GDAN 分析完全可重复和可扩展。因此，我们的目标是：（1）为协作极端创建全球基础设施大规模癌症分析；(2) 大规模运行标准工作流程；(3) 快速且有效不断发展标准工作流程；(4) 创造改进的能力；报告、探索结果、临床诊断和再现性。