Lee Hanbin, Lee Moo Hyuk, Hou Kangcheng, Pasaniuc Bogdan, Han Buhm
Department of Statistics, University of Michigan, Ann Arbor, MI, USA.
Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
Genome Biol. 2025 Jul 11;26(1):201. doi: 10.1186/s13059-025-03672-w.
Admixed populations offer valuable insight into the genetic architecture of complex traits. Many studies have proposed methods for genome-wide association study (GWAS) in admixed populations and various simulation studies have evaluated their performances. In this work, we propose another direction of comparison of recently proposed methods for admixed GWAS from a population genetic viewpoint.
Our theoretical approach mathematically and directly compares the power of methods given that the causal variant is tested. This is done by deriving the variance formula of the methods from the population genetic admixture model. Our results analytically confirm previous observation that the standard GWAS test is more powerful than alternative tests due to leveraging allele frequency heterogeneity in which alternatives do not. As a by-product, we obtain a simple method to improve the power of multi-degrees-of-freedom tests only using summary statistics. We further investigate the problem when the causal variant is not directly known but is detected by tagging variants in linkage disequilibrium (LD). The analysis shows that a genetic segment from admixed genomes may exhibit distinct LD patterns from the single-continental counterpart of the same ancestry.
While the classic admixture model is successful in predicting GWAS power, its popular extension in the literature falls short in explaining the LD patterns found in simulations and real data, warranting an improved model for LD in admixed genomes.
混合群体为复杂性状的遗传结构提供了有价值的见解。许多研究提出了混合群体中全基因组关联研究（GWAS）的方法，各种模拟研究评估了它们的性能。在这项工作中，我们从群体遗传学的角度提出了另一个比较最近提出的混合GWAS方法的方向。
我们的理论方法在假设对因果变异进行检验的情况下，对方法的效能进行数学上的直接比较。这是通过从群体遗传混合模型推导方法的方差公式来完成的。我们的结果通过分析证实了先前的观察结果，即标准GWAS检验比其他检验更有效，因为它利用了等位基因频率的异质性，而其他检验则没有。作为一个副产品，我们获得了一种仅使用汇总统计量来提高多自由度检验效能的简单方法。我们进一步研究了因果变异不直接已知但通过连锁不平衡（LD）中的标记变异检测到的问题。分析表明，混合基因组中的一个遗传片段可能表现出与相同祖先的单大陆对应片段不同的LD模式。
虽然经典混合模型在预测GWAS效能方面很成功，但其在文献中流行的扩展在解释模拟和实际数据中发现的LD模式方面存在不足，这需要一个改进的混合基因组LD模型。
