SPAmix: a scalable, accurate, and universal analysis framework for large-scale genetic association studies in admixed populations

作者：Yuzhuo Ma, He Xu, Ying Li, Hyesung Kim, Linlin Xu, Miao Lin, Peng Xu, Fengbiao Mao, Shu‐Feng Zhou, Wei Zhou, Seunggeun Lee, Ji‐Feng Zhang, Peipei Zhang, Wenjian Bi · 发表于：Genome biology · 年份：2025 · DOI：10.1186/s13059-025-03827-9 · 被引用次数：2 · 研究领域：Genetic Associations and Epidemiology、Genetic and phenotypic traits in livestock、Genetic Mapping and Diversity in Plants and Animals

Inclusion of individuals with diverse or admixed genetic ancestries is crucial to discover novel findings that may be missed by genomics analyses rooted solely in European population. Here, we present an analysis framework, SPAmix, which is scalable to a large-scale biobank data analysis including hundreds of thousands of admixed individuals and is universally applicable to various types of complex traits including quantitative traits, time-to-event traits, ordinal traits, and longitudinal traits. Since no alternative model is fitted, SPAmix primarily focuses on association p values. For each genetic variant, SPAmix uses genotype data and genetic principal components to estimate individual-specific allele frequency, which is subsequently used to calibrate p values via a retrospective analysis. A hybrid strategy including saddlepoint approximation (SPA) can greatly increase the accuracy to analyze rare genetic variants, especially if the phenotypic distribution is unbalanced or extremely unbalanced. We also propose SPAmix local to incorporate local ancestry to calculate ancestry-specific p values. To maximize the statistical powers, SPAmix CCT is proposed to combine the p values of SPAmix and SPAmix local via Cauchy combination. The SPAmix-based approaches are more accurate than Tractor to address phenotypic variance heterogeneity among ancestries when analyzing quantitative traits and to address an unbalanced case–control ratio when analyzing binary traits. SPAmix CCT is an o...