Statistical Analysis and Bioinformatics Core

核心C：迈阿密大学（UM）Udall中心的统计分析和生物信息学核心 在过去的12年里，我们在PD基因分析方面的经验。核心的目标是 通过应用强大的下一代序列分析方法来支持项目的需求， 生物信息学技术，并建立统计分析。核心整合了信息学， 生物信息学和统计支持。它利用了胡斯曼大学现有的资源， 人类基因组学研究所（HIHG）和计算科学中心（CCS）。核心由博士领导。 他是HIHG的信息学主任，遗传关联分析专家。他 取代马丁博士作为PI，并一直在我们的Udall中心项目PI自成立以来。她仍然在 作为一个共同调查员的核心。数据管理、计算机、统计和生物信息学成员 HIHG的工作人员将构成统计分析和生物信息学核心的核心， 通过以下具体目标满足项目需求： 提供信息学以支持家族史的数据库管理、存储和快速检索， 项目和临床核心的临床、风险因素、基因型、DNA序列和RNA表达数据。 为下一代测序提供分析支持。我们将为整个 下一代测序数据分析管道;从数据生成到统计分析， 解释。分析包括质量控制、装配、比对、变体调用、功能 注释和表型关联分析。 为所有项目和核心提供额外的统计分析支持。我们将进行各种 分析，包括质量控制，关联分析，参数和非参数连锁，基因-基因 以及基因-环境相互作用、生物途径分析和拷贝数变异检测， 协会

Core C: The Statistical Analysis and Bioinformatics Core of the University of Miami (UM) Udall Center builds on our experience in analysis of genes in PD over the previous twelve years. The goal of the Core is to support the needs of the Projects by applying powerful next-generation sequence analysis approaches, bioinformatics techniques, and established statistical analyses. The Core has integrated informatics, bioinformatics and statistical support. It takes advantage of existing resources within UM in the Hussman Institute for Human Genomics (HIHG) and Center for Computational Science (CCS). The core is lead by Dr. Beecham who is the director of informatics at the HIHG, an expert in genetic association analysis. He replaces Dr. Martin as PI, and has been a Project PI in our Udall Center since its inception. She remains on the core as a co-investigator. Members of the data management, computer, statistical, and bioinformatics staff of the HIHG staff will form the nucleus of the Statistical Analysis and Bioinformatics Core, addressing the projects' needs through the following specific aims: To provide the informatics to support database management, storage, and rapid retrieval of family history, clinical, risk factor, genotypic, DNA sequence and RNA expression data for the projects and clinical core. To provide analytical support for next-generation sequencing. We will provide support for the entire pipeline of next-generation sequencing data analysis; from data generation to statistical analysis and interpretation. The analyses include quality control, assembly, alignment, variant calling, functional annotation, and phenotype association analyses. To provide additional statistical analysis support for all projects and cores. We will conduct various analyses, including quality control, association analysis, parametric and non-parametric linkage, gene-gene and gene-environment interaction, biological pathway analysis, and copy-number variant detection and association.