Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel

• Main Authors: Mitt, Mario (Author), Kals, Mart (Author), Pärn, Kalle (Author), Ripatti, Samuli (Author), Morris, Andrew P (Author), Metspalu, Andres (Author), Esko, Tõnu (Author), Mägi, Reedik (Author), Palta, Priit (Author), Gabriel, Stacey (Contributor), Lander, Eric Steven (Contributor), Palotie, Aarno (Contributor)
• Other Authors: Broad Institute of MIT and Harvard (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor)
• Format: Article
• Language: English
• Published: Nature Publishing Group, 2018-06-29T16:08:14Z.
• Subjects: Article
• Online Access: Get fulltext

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF<5%) across diverse populations, but the imputation of rare variation (MAF<0.5%) is still rather limited. In the current study, we evaluate imputation accuracy achieved with reference panels from diverse populations with a population-specific high-coverage (30 ×) whole-genome sequencing (WGS) based reference panel, comprising of 2244 Estonian individuals (0.25% of adult Estonians). Although the Estonian-specific panel contains fewer haplotypes and variants, the imputation confidence and accuracy of imputed low-frequency and rare variants was significantly higher. The results indicate the utility of population-specific reference panels for human genetic studies.