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A High-resolution Haplotype-resolved Reference Panel Constructed from the China Kadoorie Biobank Study

Authors :
Canqing Yu
Xianmei Lan
Ye Tao
Yu Guo
Dianjianyi Sun
Puyi Qian
Yuwen Zhou
Robin Walters
Linxuan Li
Iona Millwood
Jingyu Zeng
Pei Pei
Ruidong Guo
Huaidong Du
Tao Yang
Ling Yang
Fan Yang
Yiping Chen
Fengzhen Chen
Xiaosen Jiang
Zhiqiang Ye
Fangyi Ren
Lanlan Dai
Xiaofeng Wei
Xun Xu
Huanming Yang
Jian Wang
Zhengming Chen
Huanhuan Zhu
Jun Lv
Xin Jin
Liming Li
Publication Year :
2022
Publisher :
Cold Spring Harbor Laboratory, 2022.

Abstract

Precision medicine relies on high-accuracy individual-level genotype data. However, the whole-genome sequencing (WGS) is currently not suitable for studies with very large sample sizes due to budget constraints. It is particularly important to construct highly accurate haplotype reference panel for genotype imputation. In this study, we selected 9,950 individuals from the China Kadoorie Biobank (CKB) cohort and 50 Chinese samples from the 1000 Genome Project (1KGP) for medium-depth WGS to construct a CKB reference panel. The results of imputing microarray datasets showed that the CKB panel outperformed the extended high coverage 1KGP, TOPMed, ChinaMAP, and NuyWa panels in terms of both the number of well-imputed variants and imputation accuracy. In addition, we have completed the imputation of over 100,000 CKB microarray data with the CKB panel, and the after-imputed genotype data is the hitherto largest whole genome data of the Chinese population. Finally, we developed an online server for offering free genotype imputation service based on the CKB reference panel (https://db.cngb.org/imputation/). We believe that the constructed CKB reference panel is of great value for imputing microarray or low-depth genotype data of Chinese population. The imputation-completed 100,000 microarray data are fundamental resources of population genetic studies for complex traits and diseases in the Chinese population.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........20fed1e82150f7fd113a9d244aec61c3
Full Text :
https://doi.org/10.1101/2022.12.14.22283491