Metrics and methods for cross-population fine mapping

描述（由申请人提供）：全基因组关联研究在识别与复杂疾病和表型相关的数百种变异方面非常成功。相比之下，由于在任何给定位点的高水平的连锁不平衡，到目前为止，只有少数的因果变异被确定。为了弥补这一差距，目前正在对欧洲人、亚洲人、非洲裔美国人或拉丁美洲人等多个人群进行一些涉及密集基因分型或测序的精细测绘研究。多种群精细图谱研究可以利用不同种群间的遗传变异，提高多种群联合分析中定位因果变异的准确性

DESCRIPTION (provided by applicant): Genome-wide association studies have been very successful in identifying hundreds of variants associated to complex diseases and phenotypes. In contrast, due to high levels of linkage disequilibrium at any given locus, only a handful of causal variants have been identified so far. In an attempt to bridge this gap, several fine- mapping studies involving dense genotyping or sequencing are currently being performed in multiple populations such as Europeans, Asians, African Americans or Latinos. Fine mapping studies over multiple populations can leverage different genetic variation across populations to increase the accuracy for localizing the causal variant in a joint analysis of multiple populations as compared to studies in which only one population is analyzed at a time. Surprisingly, despite the large potential of multi ethnic fine mapping studies, current multi population fine mapping studies employ standard statistical techniques within locus specific ad- hoc frameworks. In this application we will introduce novel metrics and automated frameworks for quantifying the performance of fine mapping methods as well as novel statistical methods that leverage multi ethnic genetic variation to increase the localization accuracy for fine mapping.