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

Schurz, Haiko and Müller, Stephanie J. and van Helden, Paul David and Tromp, Gerard and Hoal, Eileen G. and Kinnear, Craig J. and Möller, Marlo (2019) Evaluating the Accuracy of Imputation Methods in a Five-Way Admixed Population. Frontiers in Genetics, 10. ISSN 1664-8021

[thumbnail of pubmed-zip/versions/1/package-entries/fgene-10-00034/fgene-10-00034.pdf] Text
pubmed-zip/versions/1/package-entries/fgene-10-00034/fgene-10-00034.pdf - Published Version

Download (2MB)

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.

Item Type: Article
Subjects: Librbary Digital > Medical Science
Depositing User: Unnamed user with email support@librbarydigit.com
Date Deposited: 17 Feb 2023 11:47
Last Modified: 17 Jul 2024 10:21
URI: http://info.openarchivelibrary.com/id/eprint/218

Actions (login required)

View Item
View Item