Data Science Core (Data Analytics, Biostatistics and Database)

数据科学核心（核心C）项目摘要/摘要 UT肺癌孢子提出的研究包括广泛的活动，包括 在临床注释的患者肿瘤样品、肿瘤细胞系、异种移植物和小鼠模型中的研究，以及 人体临床试验这些研究产生了多种类型的数据，包括临床、组织学、全基因组 分子（突变、表达）、蛋白质组学、生物化学、免疫组织化学、药物和免疫反应 表型、代谢组学和肿瘤环境。数据科学核心提供全面的专业知识 确保研究的统计完整性、数据完整性、数据共享能力和数据分析准确性 由孢子执行。核心在每个机构都有一名主任（Y。Xie，UTSW和J. Wang，MDACC） 以及将人员与现有SPORE项目不断变化的需求相匹配的灵活性， 研究和职业提升计划（DRP，CEP）项目。确保适当考虑到 在整个SPORE工作中，生物统计学和数据管理问题，本核心成员参与 每月一次的所有SPORE项目和核心会议，以及特定的数据科学SPORE视频/WebEx 会议连接研究人员在UTSW和MDACC。数据科学核心将执行以下操作：（a） 开发和维护数据存储、检索、分析和共享系统;（B）为所有 （c）提供分析， UT Lung SPORE以外的研究者可以适当访问SPORE数据集，并且能够轻松地 独立复制和验证生物统计和计算分析。核心服务包括 创新，独特，偶尔定制的方法来解决数据分析和解释 现代数据中心研究实验室的挑战。目标1：提供有效的 SPORE实验室研究、临床试验和转化实验的统计设计。目标2：监督 并进行创新的统计建模，模拟，数据分析和数据集成所需的 项目、DRP和CEP以及病理学核心，以实现其特定目标。目标3：确保所有复杂 分子、生物和临床数据集受到保密保护，并在SPORE之间进行分析和共享 研究者和合作者，并根据需要适当存入可供查阅的数据库， 使用有效和创新的生物信息学方法。目标4：开发和维持一个安全的、可上网查阅的网站 用于SPORE研究数据集成和存储，与广泛的临床和组织存储库相关联， 分子注释的存档患者样品、肿瘤移植物、肿瘤和正常细胞系以及相关小鼠 肺癌模型;我们还将（a）开发和维护来自肺癌文献的集中存款 癌症相关的数据集在一个网站（“肺癌浏览器”），以支持SPORE研究人员和更广泛的 研究界;及（B）提供与数据有关的分析及文件以供出版（例如“Swave”） 允许研究团体独立地复制和验证我们的分析。

Data Sciences Core (Core C) Project Summary/Abstract The research proposed by the UT Lung Cancer SPORE encompasses a broad range of activities, including studies in clinically annotated patient tumor samples, tumor cell lines, xenografts, and mouse models, as well as human clinical trials. These studies generate multiple types of data, including clinical, histologic, genome-wide molecular (mutation, expression), proteomic, biochemical, immunohistochemical, drug and immune response phenotype, metabolomic, and tumor environmental. The Data Sciences Core provides comprehensive expertise to ensure the statistical integrity, data integrity, data sharing capability, and data analysis accuracy of the studies performed by the SPORE. The Core has a Director at each institution (Y. Xie, UTSW, and J. Wang, MDACC) and the flexibility to match personnel to the evolving needs of existing SPORE Projects, and Developmental Research and Career Enhancement Program (DRP, CEP) Projects. To ensure appropriate consideration of biostatistics and data management concerns throughout all SPORE work, members of this Core participate in monthly all-SPORE Project and Core meetings, and in the specific Data Sciences SPORE video/WebEx conferences linking researchers at UTSW and MDACC. The Data Sciences Core will perform the following: (a) develop and maintain systems for data storage, retrieval, analysis, and sharing; (b) provide an interface for all SPORE investigators to exchange data and information easily and freely; (c) provide analyses to allow investigators outside the UT Lung SPORE to have appropriate access to SPORE datasets, and to be able easily to independently reproduce and validate biostatistical and computational analyses. The Core services include innovative, unique, and occasionally customized approaches to solving the data analysis and interpretation challenges of the modern data-centric research laboratory. The Core Specific Aims are: Aim 1: Provide valid statistical designs for SPORE laboratory research, clinical trials and translational experiments. Aim 2: Oversee and conduct innovative statistical modeling, simulations, data analyses and data integration needed by the Projects, DRP and CEP, and Pathology Core to achieve their specific aims. Aim 3: Ensure that all complex molecular, biologic, and clinical datasets are protected for confidentiality, analyzed, shared among SPORE investigators and collaborators, and appropriately deposited into publically accessible databases as required, using valid and innovative bioinformatics methods. Aim 4: Develop and maintain a secure, web-accessible site for SPORE research data integration and storage linked to an extensive tissue repository of clinically and molecularly annotated archived patient samples, tumor grafts, tumor and normal cell lines, and relevant mouse models of lung cancer; we will also (a) develop and maintain centralized deposits from the literature of lung cancer-relevant datasets in a web site (“Lung Cancer Explorer”) to support SPORE investigators and the broader research community; and (b) provide data-related analyses and documents for publication (such as “Sweave”) that allow the research community to independently reproduce and validate our analyses.