Department of Genetics, School of Medicine, Stanford University, Stanford, California 94305, USA.
Genet Epidemiol. 2010 Dec;34(8):783-91. doi: 10.1002/gepi.20520.
Current genome-wide association studies (GWAS) often involve populations that have experienced recent genetic admixture. Genotype data generated from these studies can be used to test for association directly, as in a non-admixed population. As an alternative, these data can be used to infer chromosomal ancestry, and thus allow for admixture mapping. We quantify the contribution of allele-based and ancestry-based association testing under a family-design, and demonstrate that the two tests can provide non-redundant information. We propose a joint testing procedure, which efficiently integrates the two sources information. The efficiencies of the allele, ancestry and combined tests are compared in the context of a GWAS. We discuss the impact of population history and provide guidelines for future design and analysis of GWAS in admixed populations.
目前的全基因组关联研究(GWAS)通常涉及到经历过近期遗传混合的人群。从这些研究中生成的基因型数据可直接用于关联测试,就像在没有混合的人群中一样。作为一种替代方法,这些数据可用于推断染色体祖先,从而允许进行混合映射。我们在家族设计下定量评估基于等位基因和基于祖先的关联测试的贡献,并证明这两种测试可以提供非冗余信息。我们提出了一种联合测试程序,该程序有效地整合了两种信息来源。在 GWAS 的背景下,比较了等位基因、祖先和组合测试的效率。我们讨论了人口历史的影响,并为混合人群中 GWAS 的未来设计和分析提供了指导。