Core E: Data Management and Analysis Core (DMAC)

核心E：数据管理和分析核心（DMAC）

• 批准号: 10559687
• 负责人: SUSAN G. HILSENBECK
• 金额: $ 12.72万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-28 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10559687
• 关键词: Area; Aromatic Polycyclic Hydrocarbons; Big Data; Bioinformatics; Biological; Biometry; Cancer Center; Chemicals; Chronic lung disease; Clinical; Code; Collaborations; Communities; Complex; Consultations; Data; Data Analyses; Data Coordinating Center; Data Engineering; Detection; Education; Educational process of instructing; Educational workshop; Engineering; FAIR principles; Funding; Galaxy; Grant; Individual; Information Management; Infrastructure; Journals; Laboratories; Life Cycle Stages; Malignant Neoplasms; Metadata; Methods; Monitor; Multiomic Data; Neurocognitive Deficit; Outcome; Phenotype; Policies; Postdoctoral Fellow; Premature Birth; Prevention; Process; Program Research Project Grants; Proteomics; Reproducibility; Research; Research Methodology; Research Personnel; Resources; Rice; Role; STEM research; Sampling; Superfund; Technology; Testing; Training and Education; Work; arm; biobank; data centers; data format; data integration; data management; data submission; deep learning; early life exposure; experience; graduate student; informatics shared resource; insight; learning progression; meetings; member; metabolomics; multidisciplinary; multiple omics; novel; programs; quality assurance; remediation; repository; secondary analysis; sharing platform; statistics; success; symposium; tool; user-friendly; web portal

Project Summary Although this is a revised submission of the Baylor-Rice Superfund Research Program (SRP) grant, the Data Management and Analysis Core (DMAC) is a completely new, and indeed, required core. The team represented by this Core is not new to data management or to multi- project programs of research and has a strong track-record of experience and accomplishment. The Data Management and Analysis Core (DMAC) will act as the central hub for the SRP. The DMAC will provide for storage, annotation, and integration of multidisciplinary data generated by the biomedical projects P2, P3, P4 and the engineering projects P1 and P5. The DMAC has the following aims: 1) Implement a robust and comprehensive Data Management Plan; 2) Provide expert analysis in the specialized areas of statistics and bioinformatics for all Projects; 3) Develop new SRP-related data and management and data analysis methods; 4) Provide data management and analysis education and training for the graduate students and postdoctoral trainees connected with Superfund projects. The DMAC will act as the central resource for storage and cross-project access to chemical, physical, biological, and multi-omics data generated by the SRP projects and cores. In collaboration with the SRP investigators, the DMAC will accept a wide variety of data formats, not just ‘big data’, and will systematically incorporate metadata describing samples and laboratory conditions. The DMAC will leverage the extensive experience and infrastructure of the Duncan Cancer Center’s Biostatistics and Informatics Shared Resource, especially for biobanking and sample information management. We will work with the engineering projects to extend this infrastructure to the engineering projects. The DMAC will carry out primary and integrative data analysis for the biomedical projects and engineering projects. The analysis arm of the DMAC will provide advanced integrative methods spanning both omics and engineering data, including omics/phenotypes/chemical data multivariate regression and deep learning. In consultation with the Administrative Core and SRP investigators, the DMAC will enact data governance policies, enabling appropriate role-based access to data, primary and secondary analyses for investigators from the SRP, and from other SRPs nation-wide. The DMAC will submit the data to appropriate national repositories for each data type, and enhance the ability of the scientific community to find and retrieve the data, guided by the FAIR principles.

项目摘要 虽然这是贝勒-赖斯超级基金研究计划(SRP)的修订后的提交 格兰特，数据管理和分析核心(DMAC)是一个全新的，确实， 所需的核心。此核心所代表的团队在数据管理或多业务领域并不陌生 项目研究计划，并有很强的经验和成就记录。 数据管理和分析核心(DMAC)将作为SRP的中心枢纽。这个 DMAC将提供由生成的多学科数据的存储、注释和集成 生物医学项目P2、P3、P4和工程项目P1、P5。DMAC拥有 以下目标：1)实施强大而全面的数据管理计划；2)提供 在统计和生物信息学专门领域为所有项目进行专家分析；3)制定 新的SRP相关数据以及管理和数据分析方法；4)提供数据 对研究生和博士后进行管理分析教育和培训 与超级基金项目相关的实习生。DMAC将作为以下各项的中心资源 存储和跨项目访问化学、物理、生物和多组学数据 由SRP项目和核心生成。在与SRP调查人员的合作下，DMAC 将接受各种各样的数据格式，而不是只接受‘大数据’，并将系统地将 描述样本和实验室条件的元数据。DMAC将利用广泛的 分享邓肯癌症中心生物统计和信息学的经验和基础设施 资源，特别是用于生物库和样本信息管理。我们将与 工程项目将这种基础设施扩展到工程项目。DMAC将携带 对生物医学项目和工程项目进行初步的、综合的数据分析。 DMAC的分析部门将提供跨越这两个组学的先进综合方法 和工程数据，包括组学/表型/化学数据多变量回归和 深度学习。在与行政核心和SRP调查人员协商后，DMAC将 制定数据治理策略，支持基于角色的适当数据访问、主要和 对来自SRP和全国其他SRP的调查人员进行二次分析。DMAC 将每种数据类型的数据提交到适当的国家储存库，并增强能力 在公平原则的指导下，科学界寻找和检索数据。