Data Coordination and Analysis Center

数据协调与分析中心

• 批准号: 9116968
• 负责人: Marcelo Fernandez-Vina
• 金额: $ 39.2万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9116968
• 关键词: Address; Adopted; Alleles; Bioinformatics; Clinical; Collection; Communication; Communities; Complex; Computer software; Consumption; Data; Data Analyses; Data Set; Databases; Development; Disease; Elements; Environment; Europe; Frequencies; Gene Frequency; Generations; Goals; Grant; Haplotypes; Immunogenetics; Informatics; Information Dissemination; International; Internet; Japan; Knowledge; Laboratories; Lead; Leadership; Link; Meta-Analysis; Modeling; Monitor; National Institute of Allergy and Infectious Disease; Online Systems; Research Design; Research Infrastructure; Research Personnel; Resources; Retrieval; Secure; Statistical Data Interpretation; Statistical Models; Supervision; Support Groups; System; United States; Update; base; biobank; cloud based; data access; data integrity; data management; data sharing; data visualization; disorder risk; endophenotype; experience; genome-wide; improved; interoperability; multidisciplinary; nervous system disorder; open source; programs; repository; scale up; statistics; success; tool; trait; whole genome; working group

The Data Coordination and Analysis Center (DCC) will collate, QC, and format for analysis the immunogenetic results generated by Projects 1 and 2 and the clinical/demographic information provided by the Disease Groups. A highly effective centralized data coordination effort in an advanced and secure environment is crucial to the success of a study of this scale, including diligent internal and external communications and multi-channel dissemination the data. The DCC will be located at UCSF and, under the supervision of Dr. Gourraud, will serve as the repository of the Project phenotypic and laboratory informatics systems. The DCC will be electronically linked to the Project BioRepository and centralize communications with BISC. The vast amount of experimental data to be collected requires the development of a reliable informatics platform and a systematic approach for the establishment of data integrity, completeness, and accessibility. We will use a combination of relational and object-oriented databases with file servers, building on the previous experience of the leadership group with multi-dimensional, metacentric, and high data-consumption projects. This cloud-based data and knowledge infrastructure is accessed by an API serving as a data and computation gateway, which centralizes data import and export, transmits computation requests, and monitors data usage while controlling user-defined level credentials. In addition, the DCC team will lead the analysis for 3 types of specific HLA and KIR studies: disease association, disease endophenotype association, and across-disease / across-ancestry analyses. This multi-dimensional strategy will allow the generation of HLA and KIR specific and reproducible analytical variables and the application of consistent statistical models for all INDIGO datasets. Data access via the API will make possible the automated integration of INDIGO data resources with existing Immunogenetic data-sharing initiatives. Using the community-based IDAWG model for promoting data standards, the DCC will contribute to address the emerging challenges posed by HLA/KIR NGS. Finally, the DCC will make available tools for generating aggregated statistics using web-tools connected to the open end of the INDIGO API, and, when possible, enabling computation with third-party datasets using open source software and scripts produced by the program co-investigators.

数据协调和分析中心（DCC）将汇总，QC和格式进行分析 项目1和2产生的结果以及该疾病提供的临床/人口统计信息 组。在高级且安全的环境中，高效的集中数据协调工作是 对于这项研究的成功至关重要，包括勤奋的内部和外部通信以及 多通道传播数据。 DCC将位于UCSF，并在Dr. Gourraud将作为项目表型和实验室信息学系统的存储库。 DCC 将通过电子方式与该项目生物座位联系，并集中与BISC的通信。 要收集的大量实验数据需要开发可靠的信息学 平台和系统的方法，用于建立数据完整性，完整性和可访问性。 我们将使用与文件服务器一起使用关系服务器的关系和面向对象的数据库的组合，以前 领导力小组具有多维，元中心和高数据消费项目的经验。 这种基于云的数据和知识基础架构可通过用作数据和计算的API访问 网关集中数据导入和导出，传输计算请求并监视数据使用情况 同时控制用户定义的级别凭据。此外，DCC团队将领导三种类型的分析 特定的HLA和KIR研究：疾病协会，疾病内表型关联以及跨疾病 / 跨学业分析。这种多维策略将允许HLA和KIR特定的生成 以及可再现的分析变量以及所有靛蓝的一致统计模型的应用 数据集。 通过API访问数据将使靛蓝数据资源与现有的自动集成 免疫遗传数据共享计划。使用基于社区的IDAWG模型来促进数据 标准，DCC将有助于解决HLA/KIR NGS提出的新兴挑战。最后， DCC将提供使用连接到开放端的网络工具生成汇总统计信息的工具 Indigo API的of，并在可能的情况下使用开放源代码使用第三方数据集启用计算 程序共同评估器生成的软件和脚本。