Statistical population genetics and genetic epidemiology

本研究的目的是研究人类性状变异作图领域的统计遗传学问题。我们研究了单位点和多位点作图技术的多重检测性能，例如单倍型与疾病易感性和药物不良反应的关联分析。一个常见的数据挖掘技术（递归分区）的统计特性进行了研究。我们研究了发现真正的协会的机会，采用统计分布的排名真正的协会。我们考虑了大规模作图实验中的多重性问题，如全基因组关联扫描。由于连锁不平衡和单倍型块，我们的设计纳入了在不同遗传位置评估的检验统计量之间的依赖关系。

The purpose of this research is to study statistical genetics problems in the area of mapping human trait variation. We have examined the multiple testing performance of single-locus and multi-locus mapping techniques such as the analysis of association of haplotypes with disease susceptibility and adverse reactions to drugs. Statistical properties of a common data mining technique (recursive partitioning) have been investigated. We studied chances of discovering genuine associations by employing statistical distributions of ranks of true associations. We considered multiplicity issues in the context of large scale mapping experiments, such as whole genome association scans. Our design incorporated dependencies between test statistics evaluated at different genetic locations due to linkage disequilibrium and haplotype blocks.