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.

The goal of this grant is to provide training in gene mapping. This course will advance the training of researchers and students in the area of statistical genetics to allow them to perform gene mapping of complex traits, which in turn will lead to an improvement in the analysis of genetic data thus increasing knowledge of the genetics of complex disease etiology.