Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)

拟议的基因组数据分析中心B(GDAC B)将与资助的其他GDAC合作 由癌症基因组图谱(TCGA)项目(TCGA)：(I)为以下系统开发一种创新的综合管道- TCGA对多种不同类型人类肿瘤的分子图谱数据的水平分析和(Ii)应用 管道及其组件模块连接到TCGA数据，以解决重要的生物学和临床问题。一个 首要目标是在新肿瘤的基础上对癌症患者的管理进行“个性化” 生物标志物和生物签名。这是第一次，生成数百万个关于肿瘤的数据点比 要分析或解释这些数据，生物信息学的挑战是巨大的。这条管道将是 使用敏捷软件开发范例和语义网查询体系结构构建。会是 基于GDAC参与者开发的新算法和模块。将包括以下模块 数据集成、数据可视化、路径分析和系统生物学解释，所有这些都旨在 便于临床研究人员和临床医生使用。这些模块将与其他模块连接 由其他GDAC开发，所有开发都将遵循TCGA和癌症生物医学的标准 信息网格(CaBIG)，并将提供受控访问，以确保个人身份的机密性 数据。拟议的GDAC团队为该项目带来了生物信息学、生物统计学、软件 工程学、高通量分子图谱技术、面向系统的生物学、生物标记物研究 病理学和临床研究。三个联合绩效指标(用于生物信息学、系统生物学和临床研究) 自TCGA成立以来，每个人都积极参与了TCGA，小组的其他成员也是如此，包括 首席软件工程师。一个主要的优势是德克萨斯大学安德森癌症中心 (MDACC)作为一个机构。MDACC一直是，而且可能将继续是最大的 肿瘤标本用于TCGA。作为该国最重要的癌症中心之一，拥有迄今为止最大的癌症 临床研究计划，MDACC在跟踪重要的医学线索方面拥有无与伦比的专业知识 这是TCGA数据管道开发和应用的结果。

The proposed Genome Data Analysis Center B (GDAC B) will work cooperatively with other GDACs funded by The Cancer Genome Atlas (TCGA) project to (i) develop an innovative, integrative pipeline for systems- level analysis of TCGA's molecular profiling data on many different types of human tumors and (ii) apply that pipeline and its component modules to TCGA data to address important biological and clinical questions. An overarching goal is to 'personalize' the management of patients' cancers on the basis of new tumor biomarkers and biosignatures. For the first time, it is easier to generate millions of data points on tumors than to analyze or interpret those data, hence the bioinformatic challenge is formidable. The pipeline will be constructed using the Agile software development paradigm and semantic web query architecture. It will be based on novel algorithms and modules developed by participants in the GDAC. Included will be modules for data integration, data visualization, pathway analysis, and systems biological interpretation, all designed to be user-friendly for the bench researcher and clinician. Those modules will be interfaced with additional ones developed by other GDACs, All development will adhere to standards of TCGA and the Cancer Biomedical Informatics Grid (caBIG) and will provide controlled access to ensure confidentiality of personally identifiable data. The proposed GDAC team brings to this project expertise in bioinformatics, biostatistics, software engineering, high-throughput molecular profiling technologies, systems-oriented biology, biomarker studies, pathology, and clinical research. The three co-PIs (for bioinformatics, systems biology, and clinical research) have each participated actively in TCGA since its inception, as have other members of the team, including the lead software engineer. A major strength is the University of Texas M. D. Anderson Cancer Center (MDACC) as an institution. MDACC has been, and presumably will continue to be, the largest source of tumor specimens for TCGA. As one of the country's foremost cancer centers, with by far the largest cancer clinical research program, MDACC has unparalleled expertise for follow up on medically important leads that result from the development and application of the pipeline to TCGA data.