Dennis Trent, Lee Donghyung
Department of Statistics, Miami University, Oxford, OH 45056, United States.
Winton Hill Business Center, P&G, Cincinnati, OH 45232, United States.
Bioinform Adv. 2024 Aug 29;4(1):vbae128. doi: 10.1093/bioadv/vbae128. eCollection 2024.
With larger and more diverse studies becoming the standard in genome-wide association studies (GWAS), accurate estimation of ancestral proportions is increasingly important for summary-statistics-based methods such as those for imputing association summary statistics, adjusting allele frequencies (AFs) for ancestry, and prioritizing disease candidate variants or genes. Existing methods for estimating ancestral proportions in GWAS rely on the availability of study reference AFs, which are often inaccessible in current GWAS due to privacy concerns.
In this study, we propose ZMIX (Z-score-based estimation of ethnic MIXing proportions), a novel method for estimating ethnic mixing proportions in GWAS using only association Z-scores, and we compare its performance to existing reference AF-based methods in both real-world and simulated GWAS settings. We found that ZMIX offered comparable results to the reference AF-based methods in simulation and real-world studies. When applied to summary-statistics imputation, all three methods produced high-quality imputations with almost identical results.
随着规模更大、更多样化的研究成为全基因组关联研究（GWAS）的标准，对于基于汇总统计的方法（如用于推算关联汇总统计、针对祖先调整等位基因频率（AF）以及对疾病候选变异或基因进行优先级排序的方法）而言，准确估计祖先比例变得愈发重要。GWAS中现有的估计祖先比例的方法依赖于研究参考AF的可用性，由于隐私问题，当前GWAS中这些参考AF往往难以获取。
在本研究中，我们提出了ZMIX（基于Z分数的种族混合比例估计法），这是一种仅使用关联Z分数来估计GWAS中种族混合比例的新方法，并且在实际和模拟的GWAS设置中，我们将其性能与现有的基于参考AF的方法进行了比较。我们发现，在模拟和实际研究中，ZMIX与基于参考AF的方法得出的结果相当。当应用于汇总统计推算时，所有三种方法都产生了高质量的推算结果，且结果几乎相同。
