Mitt, MarioKals, MartPärn, KalleGabriel, Stacey BLander, EricPalotie, AarnoRipatti, SamuliMorris, Andrew PMetspalu, AndresEsko, TõnuMägi, ReedikPalta, Priit2017-11-212017Mitt, M., M. Kals, K. Pärn, S. B. Gabriel, E. S. Lander, A. Palotie, S. Ripatti, et al. 2017. “Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel.” European Journal of Human Genetics 25 (7): 869-876. doi:10.1038/ejhg.2017.51. http://dx.doi.org/10.1038/ejhg.2017.51.http://nrs.harvard.edu/urn-3:HUL.InstRepos:34375059Genetic 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.en-USJournal Article2017-11-2110.1038/ejhg.2017.51