Nucleic Acids ResearchGenetic & Genomic MedicinePeer-reviewed journal article
A High-resolution Haplotype-resolved Reference Panel Constructed from the China Kadoorie Biobank Study
Canqing YuiD, Xianmei LaniD, Ye TaoiD, Yu GuoiD, Dianjianyi SuniD, Puyi Qian, Yuwen Zhou, Robin G. WaltersiD, Linxuan LiiD, Yunqing ZhuiD, Jingyu ZengiD, Iona Y. MillwoodiD, Ruidong Guo, Pei PeiiD, Tao Yang, Huaidong DuiD, Ling YangiD, Fangyi Ren, Fengzhen CheniD, Xiaosen JiangiD, Zhiqiang Ye, Lanlan Dai, Xiaofeng WeiiD, Xun XuiD, Jian WangiD, , Liming LiiD
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.
- organism: human
- assay: whole-genome sequencing
- research focus: imputation
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- Citations
- 20
- FWCI
- 3.48
- Field percentile
- top 6%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A reference panel of 64,976 haplotypes for genotype imputation
Shane McCarthy, Sayantan Das, … Jonathan Marchini·Nature GeneticsPeer-reviewed·Aug 22, 2016
- Whole-genome reference panel of 1,781 Northeast Asians improves imputation accuracy of rare and low-frequency variants
Seong‐Keun Yoo, Chang-Uk Kim, … Jeong‐Sun Seo·Genome MedicinePeer-reviewed·Oct 22, 2019
- Genotype Imputation and Reference Panel: A Systematic Evaluation
Wei-Yang Bai, Xiao-Wei Zhu, … Hou‐Feng Zheng·bioRxiv·May 19, 2019
- Evaluation of imputation performance of multiple reference panels in a Pakistani population
Jiayi Xu, Dongjing Liu, … Laura M. Huckins·Human Genetics and Genomics AdvancesPeer-reviewed·Dec 18, 2024
- Genotype Imputation Performance of Three Reference Panels Using African Ancestry Individuals
Candelaria Vergara, Margaret M. Parker, … Priya Duggal·Human GeneticsPeer-reviewed·Apr 1, 2018
- The effects of reference panel perturbations on the accuracy of genotype imputation
Jeremiah H. Li, Andy Liu, … Lex Flagel·bioRxiv·Aug 10, 2023