Statistical population genetics and genetic epidemiology

本研究的目的是研究人类性状变异图谱领域的统计遗传学问题。我们研究了单位点和多位点定位技术的多重检测性能，如单倍型与疾病易感性和药物不良反应的关联分析。研究了一种常用的数据挖掘技术（递归划分）的统计特性。我们通过使用真实关联等级的统计分布来研究发现真实关联的机会。我们考虑了大规模制图实验背景下的多样性问题，如全基因组关联扫描。我们的设计纳入了由于连锁不平衡和单倍型块而在不同遗传位置评估的检验统计量之间的相关性。

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.