The Cancer Genome Atlas Data Analysis Center

描述（由申请人提供）：TCGA的总体目标是通过癌症基因组学改变癌症医学的实践并提高患者的生存率。一个关键的交付成果是能够访问和使用复杂的多维基因组数据进行下游研究。我们建议运营一个GDAC-A中心，该中心具有开发分析管道所需的领导力、专业知识和基础设施，该分析管道将生成预定义的综合分析和解释，这些分析和解释是为基础、转化和临床研究者的假设检验而量身定制的。我们的团队由癌症生物学、基因组学和生物信息学方面的专家组成，他们在TCGA领域具有领导地位。分析工具和管道结构基于我们丰富的TCGA经验，旨在最佳地实现其目标。该管道将使用GenePattern生物信息学工作流环境构建-这是一种灵活的模块化架构，符合caBIG和caGRID标准，在Broad Institute完善，强大和安全的IT基础设施中维护，并可以作为生产管道24/7运行。 我们会善用这方面的资源，达致以下的具体目标。 目标1。我们将为所有输入和输出文件定义符合caBIG的数据格式。为了进一步加强标准化，我们建议对试点项目（1 - 4级）中定义的标准数据结构增加两项内容。0级将定义分析中使用的所有参考数据库的特定版本，5级将捕获包含先验知识的疾病级结果。 目标2.我们将设计分析模块来整合TCGA所有组件的数据并进行综合分析。结果将以符合caBIG标准的输出文件提交给DCC，并附有人类可读的报告，其中包含文本摘要、表格和图表，格式为不同学科的科学家可以理解，类似于出版物的结果部分。此外，我们还致力于对产品线进行持续的技术和分析改进，特别是在支持向下一代测序平台过渡方面。 目标3.我们将在严格的质量控制下以工业级生产模式实施这一高通量分析管道，利用远大的基础设施支持以及在运行和维护高通量计算管道方面的丰富经验。

DESCRIPTION (provided by applicant): The overarching goal of TCGA is to change the practice of cancer medicine and improve patient survival through cancer genomics. A key deliverable is to enable access and use of complex multi-dimensional genomic data for downstream studies. We propose to operate a GDAC-A center with the leadership, expertise and infrastructure required to develop an analysis pipeline that will generate pre-defined integrative analyses and interpretations that are tailor-designed for hypothesis-testing by basic, translational and clinical investigators. Our team consists of experts in cancer biology, genomics and bioinformatics with a track record of leadership in TCGA. The analytical tools and pipeline structure are based on our extensive TCGA experiences and designed to optimally achieve its goals. This pipeline will be built using the GenePattern bioinformatic workflow environment - a flexible and modular architecture that is caBIG and caGRID compliant, maintained in the well-established, robust and secure IT infrastructure at the Broad Institute and can be operated 24/7 as a Production Pipeline. Leveraging this well-established resource, we will pursue the following specific aims. Aim 1. We will define caBIG compliant data format for all input and output files. To further enhance standardization, we propose two additions to the standard data structure defined in the Pilot Project (Levels 1-4). Level 0 will define specific versions of all reference databases used in the analyses and Level 5 will capture disease-level findings that incorporate prior knowledge. Aim 2. We will design analysis modules to consolidate data from all components of TCGA and to perform integrative analyses. Results will be submitted to DCC in caBIG compliant output files accompanied by human-readable reports containing text summaries, tables and figures in a format understandable to scientists of diverse disciplines, similar to the Results Section of a publication. In addition, we are committed to continuous technical and analytical improvement of the pipeline, particularly in supporting the transition to next-generation sequencing platforms. Aim 3. We will implement this high-throughput analysis pipeline in an industrial-level production mode with rigorous quality control, leveraging the Broad's infrastructural support and extensive experiences in running and maintaining high-throughput computational pipelines.