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中文摘要
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脑血管畸形协会(BVMC)的遗传和统计分析核心(GSAC)是一个集中的资源,为所有BVMC研究人员提供数据管理、统计分析和遗传学服务。GSAC可供BVMC调查人员使用,用于(a)管理和检查进入数据库资源的信息流;(b)追踪标本;(c)遗传分析;(d)为统计分析提供数据集,并为其分析提供支持。所有项目,包括试点项目和培训项目,都将使用该核心。GSAC有四个具体目标:目标1:在研究设计的统计和遗传方面进行合作;目标2:维持数据管理和样品跟踪系统;目的3:包皮基因分型和遗传分析;目标4:进行数据分析,并为演示文稿和手稿准备提供支持。通过GSAC实现数据管理和基因组服务的集中化,将为整个BVMC提供统一的数据质量控制,并优化BVMC项目之间的沟通和协同作用。GSAC与BVMC行政部门紧密结合,数据管理和遗传学基础设施及协议已在BVMC的第一个资金周期中实施和完善,并已为计划的延续做好准备。将为该方案的所有项目提供一致的高水平遗传和生物统计投入。该核心结构将通过提供单一的集中资源,促进跨项目和BVMC其他组成部分的数据共享和假设生成,从而实现临床和基础科学研究项目组成部分的最佳协调。
英文摘要
The Genetic and Statistical Analysis Core (GSAC) of the Brain Vascular Malformation Consortium (BVMC) is a centralized resource that provides data management statistical analysis and genetics services to all BVMC investigators. The GSAC is available to BVMC investigators for (a) managing and checking the flow of information into the database resources; (b) tracking specimens; (c) genetic analyses; and (d) providing datasets for statistical analysis and support for their analyses. All projects, including pilot projects and trainees, will use this Core. The GSAC has four specific aims: Aim 1: collaborate on statistical and genetic aspects of study design; Aim 2: maintain a data management and sample tracking system; Aim 3: periderm genotyping and genetic analyses; and Aim 4: perform data analysis and provide support for presentation and manuscript preparation. Centralization of data management and genomics services through the GSAC will provide uniform quality control of data across the BVMC and optimize communication and synergy between BVMC Projects. The GSAC is closely integrated with the BVMC Administrative Unit and the data management and gentics infrastructure and protocols have been implemented and refined during the first funding cycle of the BVMC and are in place for the proposed continuation of the program. A consistent high level of genetic and biostatistical input will be attained for all projects in the Program. This core structure will allow for optimal coordination of the clinical and basic science research program components by providing a single centralized resource and facilitating sharing of data and hypothesis generation across the Projects and other components of the BVMC.
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Improving statistical inference when interest focuses on the identification of extreme random effects in clustered data
Improving statistical inference when interest focuses on the identification of extreme random effects in clustered data
Career Enhancement Core
Career Enhancement Core
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