Advanced Gene Mapping Course

描述（由申请人提供）：本提案的具体目标是在纽约洛克菲勒大学开展为期一周的高级基因图谱课程。该课程是针对高级研究人员谁熟悉统计遗传学的基本方面，但谁需要变得更加精通复杂性状的分析。该课程将在韦斯大厅举行，该大厅配备了34台运行Linux和Windows的笔记本电脑。 将向其中7名博士前学生或博士后研究员提供旅费津贴，以支付机票、旅馆和膳食费用。 本课程由两部分组成：关于基因图谱中重要的当前主题的讲座，以及使用最新软件程序进行的实践练习。本课程目前的重点是从下一代序列数据中获得的罕见变异的关联分析。在2013年1月28日2月1日高级基因图谱课程的主题将包括：全基因组关联分析的数量和质量性状（基于人口和家庭的数据）;（由基因分型阵列产生）和罕见的（从下一代序列数据获得）变体;序列和基因型数据的数据质量控制;变异位点的功能预测，从序列数据中识别变异，控制群体亚结构\混合;数据质量控制（基因型和序列数据）;基因型数据的插补（例如HapMap）和全基因组序列数据（例如1000个基因组）; Meta分析;基因x基因相互作用;样本量估计和评估功效（对于罕见和常见变异）。课程参与者将教授和使用的程序包括：Armitage Power Tool，Eigenstrat，GenABEL，METAL，MINIMAC，Mutation Taster，PLINK，Polyphen 2，PSEQ，QDT，Quanto，R，RarePower，SIFT，SimRare UnMAKE和变体关联工具（VAT）。由于基因图谱是一个快速变化的领域，主题和分析程序将每年更新和改变，以反映统计遗传学领域的最新发展。鉴于生成的遗传数据量大幅增加，特别是序列数据，培训研究人员并为他们提供必要的信息和工具来分析这些数据以更好地理解复杂性状的病因学是非常重要的。

DESCRIPTION (provided by applicant): The specific aim of this proposal is to carry out an annual, full week course in advanced gene mapping at The Rockefeller University in New York. The course is directed towards advanced researchers who are familiar with the basic aspects of statistical genetics but who need to become more proficient in the analysis of complex traits. The course will be held in Weiss Hall which is equipped with 34 laptops running Linux and windows. Travel stipends will be provided to seven of the participants who are either predoctoral students or postdoctoral fellows to cover the cost of airfare, hotel and board. The course consists of two components: lectures on important, current topics in gene mapping, as well as hands on exercises to be carried out with the latest software programs. The current emphasis of the course is association analysis of rare variants obtained from next generation sequence data. In the January 28February 1, 2013 Advanced Gene Mapping course topics will include: whole genome association analysis of quantitative and qualitative traits (population and family based data); association analysis of common (generated from genotyping arrays) and of rare (obtained from next generation sequence data) variants; data quality control for sequence and genotype data; functional prediction of variant sites, calling variants from sequence data, controlling for population substructure\admixture; data quality control (genotype and sequence data); imputation of data from genotypes (e.g. HapMap) and whole genome sequence data (e.g. 1000genomes); meta analysis; gene x gene interaction; sample size estimation and evaluating power (for rare and common variants). Programs that will be taught and utilized by course participants include: Armitage Power Tool, Eigenstrat, GenABEL, METAL, MINIMAC, Mutation Taster, PLINK, Polyphen2, PSEQ, QTDT, Quanto, R, RarePower, SIFT, SimRare UnMAKE, and variant association tool (VAT). Since gene mapping is a quickly changing field the topics and analytic programs will be updated and changed annually to reflect the latest developments in the field of statistical genetics. Given the large increases in the amount of genetic data being generated, and in particular sequence data, it is extremely important to train researchers and give them the necessary information and tools to analyze this data to bring about a better understanding of the etiology of complex traits.