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April 7th, 2025
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School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, P.R. China
genomics
biorxiv

Imputation Disparities Driven by Recent Selectionand Their Impact on Disease Risk Estimation in East and Southeast Asian Populations

Li, D.Open in Google Scholar•Tangtanatakul, P.Open in Google Scholar•Lei, Y.Open in Google Scholar•Liu, X.Open in Google Scholar•Huang, H.-Y.Open in Google Scholar•Lin, Y.-C.-D.Open in Google Scholar•Li, C.Open in Google Scholar•Chen, Y.Open in Google Scholar•Cai, L.Open in Google Scholar•Zhao, J.Open in Google Scholaret al.

Using genotype data consisting of 8,316 individuals, we systematically evaluated imputation performance across six state-of-the-art reference panels for Chinese and Thai populations. A substantial proportion of variants identified through whole-genome sequencing, especially low-frequency variants, remained undetected by existing reference panels. In the Chinese population, the TOPMed panel required an R2 threshold of 0.60-0.70 to achieve comparable imputation accuracy of the ChinaMAP panel without R2 filtering, challenging the standard practice of applying a fixed R2 threshold for downstream analyses. Regional analysis highlighted the role of recent selection in imputation discrepancies and revealed an enrichment of immune-related genes in poorly imputed regions. In addition, we showed that the selection of reference panels and R2 thresholds could significantly influence estimation of polygenic risk score for disease prediction. These findings underscore the importance of developing ancestrally diverse reference panels and provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations.

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