Literature DB >> 32002535

Genotype imputation and reference panel: a systematic evaluation on haplotype size and diversity.

Wei-Yang Bai1,2, Xiao-Wei Zhu1,2, Pei-Kuan Cong1,2, Xue-Jun Zhang3, J Brent Richards4, Hou-Feng Zheng1,2.   

Abstract

Here, 622 imputations were conducted with 394 customized reference panels for Han Chinese and European populations. Besides validating the fact that imputation accuracy could always benefit from the increased panel size when the reference panel was population specific, the results brought two new thoughts. First, when the haplotype size of the reference panel was fixed, the imputation accuracy of common and low-frequency variants (Minor Allele Frequency (MAF) > 0.5%) decreased while the population diversity of the reference panel increased, but for rare variants (MAF < 0.5%), a small fraction of diversity in panel could improve imputation accuracy. Second, when the haplotype size of the reference panel was increased with extra population-diverse samples, the imputation accuracy of common variants (MAF > 5%) for the European population could always benefit from the expanding sample size. However, for the Han Chinese population, the accuracy of all imputed variants reached the highest when reference panel contained a fraction of an extra diverse sample (8-21%). In addition, we evaluated the imputation performances in the existing reference panels, such as the Haplotype Reference Consortium (HRC), 1000 Genomes Project Phase 3 and the China, Oxford and Virginia Commonwealth University Experimental Research on Genetic Epidemiology (CONVERGE). For the European population, the HRC panel showed the best performance in our analysis. For the Han Chinese population, we proposed an optimum imputation reference panel constituent ratio if researchers would like to customize their own sequenced reference panel, but a high-quality and large-scale Chinese reference panel was still needed. Our findings could be generalized to the other populations with conservative genome; a tool was provided to investigate other populations of interest (https://github.com/Abyss-bai/reference-panel-reconstruction).
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  Chinese population; HRC; genotype imputation; reference panel

Year:  2019        PMID: 32002535     DOI: 10.1093/bib/bbz108

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  6 in total

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Journal:  PLoS One       Date:  2022-06-28       Impact factor: 3.752

2.  PredPromoter-MF(2L): A Novel Approach of Promoter Prediction Based on Multi-source Feature Fusion and Deep Forest.

Authors:  Miao Wang; Fuyi Li; Hao Wu; Quanzhong Liu; Shuqin Li
Journal:  Interdiscip Sci       Date:  2022-04-30       Impact factor: 3.492

3.  Genomic analyses of 10,376 individuals in the Westlake BioBank for Chinese (WBBC) pilot project.

Authors:  Pei-Kuan Cong; Wei-Yang Bai; Jin-Chen Li; Meng-Yuan Yang; Saber Khederzadeh; Si-Rui Gai; Nan Li; Yu-Heng Liu; Shi-Hui Yu; Wei-Wei Zhao; Jun-Quan Liu; Yi Sun; Xiao-Wei Zhu; Pian-Pian Zhao; Jiang-Wei Xia; Peng-Lin Guan; Yu Qian; Jian-Guo Tao; Lin Xu; Geng Tian; Ping-Yu Wang; Shu-Yang Xie; Mo-Chang Qiu; Ke-Qi Liu; Bei-Sha Tang; Hou-Feng Zheng
Journal:  Nat Commun       Date:  2022-05-26       Impact factor: 17.694

4.  False positive findings during genome-wide association studies with imputation: influence of allele frequency and imputation accuracy.

Authors:  Zhihui Zhang; Xiangjun Xiao; Wen Zhou; Dakai Zhu; Christopher I Amos
Journal:  Hum Mol Genet       Date:  2021-12-17       Impact factor: 5.121

5.  Investigating the accuracy of imputing autosomal variants in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome.

Authors:  Isis da Costa Hermisdorff; Raphael Bermal Costa; Lucia Galvão de Albuquerque; Hubert Pausch; Naveen Kumar Kadri
Journal:  BMC Genomics       Date:  2020-11-10       Impact factor: 3.969

6.  Best practices for analyzing imputed genotypes from low-pass sequencing in dogs.

Authors:  Reuben M Buckley; Alex C Harris; Guo-Dong Wang; D Thad Whitaker; Ya-Ping Zhang; Elaine A Ostrander
Journal:  Mamm Genome       Date:  2021-09-08       Impact factor: 2.957

  6 in total

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