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评估五重混合人群中插补方法的准确性。

Evaluating the Accuracy of Imputation Methods in a Five-Way Admixed Population.

作者信息

Schurz Haiko, Müller Stephanie J, van Helden Paul David, Tromp Gerard, Hoal Eileen G, Kinnear Craig J, Möller Marlo

机构信息

DST-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

South African Tuberculosis Bioinformatics Initiative (SATBBI), Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

出版信息

Front Genet. 2019 Feb 5;10:34. doi: 10.3389/fgene.2019.00034. eCollection 2019.

Abstract

Genotype imputation is a powerful tool for increasing statistical power in an association analysis. Meta-analysis of multiple study datasets also requires a substantial overlap of SNPs for a successful association analysis, which can be achieved by imputation. Quality of imputed datasets is largely dependent on the software used, as well as the reference populations chosen. The accuracy of imputation of available reference populations has not been tested for the five-way admixed South African Colored (SAC) population. In this study, imputation results obtained using three freely-accessible methods were evaluated for accuracy and quality. We show that the African Genome Resource is the best reference panel for imputation of missing genotypes in samples from the SAC population, implemented via the freely accessible Sanger Imputation Server.

摘要

基因型填充是一种在关联分析中增强统计效力的强大工具。对多个研究数据集进行荟萃分析时,为了成功进行关联分析,单核苷酸多态性(SNP)也需要大量重叠,这可以通过填充来实现。填充数据集的质量在很大程度上取决于所使用的软件以及所选的参考群体。对于五向混合的南非有色人种(SAC)群体,尚未测试可用参考群体的填充准确性。在本研究中,评估了使用三种可免费获取的方法获得的填充结果的准确性和质量。我们表明,通过可免费访问的桑格填充服务器实施时,非洲基因组资源是SAC群体样本中缺失基因型填充的最佳参考面板。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c1f/6370942/1c1c1fcf2bc1/fgene-10-00034-g001.jpg

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