ADMIXTURE MAPPING AND POPULATION STRUCTURE FOR LOCALIZING DISEASE GENES

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 混合作图，或混合连锁不平衡作图，是近年来获得相当普及的疾病作图策略。它利用了遗传上不同的祖先群体之间的混合所产生的长距离连锁不平衡。与病例对照关联设计相比，混合作图需要较少的标记，并且对等位基因异质性更稳健。与此同时，混合定位可以更强大，可以实现更高的定位分辨率比传统的连锁研究，提供的基础性状变异发生在祖先群体中的足够不同的频率。我们回顾了最近的方法和软件开发和成功的应用。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Admixture mapping, or mapping by admixture linkage disequilibrium, is a disease mapping strategy that has gained considerable popularity in recent years. It exploits the long-range linkage disequilibrium generated by admixture between genetically distinct ancestral populations. Compared to case-control association designs, admixture mapping requires fewer markers, and is more robust to allelic heterogeneity. At the same time, admixture mapping can be more powerful, and can achieve higher mapping resolution than traditional linkage studies, provided that the underlying trait variants occur at sufficiently different frequencies in the ancestral populations. We have reviewed the recent methodology and software development and successful applications.