Performance of Genotype Imputation for Low Frequency and Rare Variants from the 1000 Genomes

Hou-Feng Zheng, Jing-Jing Rong, Ming Liu, Fang Han, Xing-Wei Zhang, J Brent Richards and Li Wang

PLOS ONE, 2015, vol. 10, issue 1, 1-10

Abstract: Genotype imputation is now routinely applied in genome-wide association studies (GWAS) and meta-analyses. However, most of the imputations have been run using HapMap samples as reference, imputation of low frequency and rare variants (minor allele frequency (MAF) 0.4) and higher mean info score in each MAF bin. Similarly, 1M chip array outperformed 610K and 317K. However for very rare variants (MAF≤0.3%), only 0–1% of the variants were well imputed. We conclude that the imputation of low frequency and rare variants improves with larger reference panels and higher density of genome-wide genotyping arrays. Yet, despite a large reference panel size and dense genotyping density, very rare variants remain difficult to impute.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0116487

DOI: 10.1371/journal.pone.0116487

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