Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel
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&l...
| Main Authors: | , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
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Nature Publishing Group
2018
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| Online Access: | http://hdl.handle.net/1721.1/116697 |
| _version_ | 1811085068175671296 |
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| author | Mitt, Mario Kals, Mart Pärn, Kalle Ripatti, Samuli Morris, Andrew P Metspalu, Andres Esko, Tõnu Mägi, Reedik Palta, Priit Gabriel, Stacey Lander, Eric Steven Palotie, Aarno |
| author2 | Broad Institute of MIT and Harvard |
| author_facet | Broad Institute of MIT and Harvard Mitt, Mario Kals, Mart Pärn, Kalle Ripatti, Samuli Morris, Andrew P Metspalu, Andres Esko, Tõnu Mägi, Reedik Palta, Priit Gabriel, Stacey Lander, Eric Steven Palotie, Aarno |
| author_sort | Mitt, Mario |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:02:25Z |
| format | Article |
| id | mit-1721.1/116697 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:02:25Z |
| publishDate | 2018 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1166972022-10-01T12:43:03Z Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel Mitt, Mario Kals, Mart Pärn, Kalle Ripatti, Samuli Morris, Andrew P Metspalu, Andres Esko, Tõnu Mägi, Reedik Palta, Priit Gabriel, Stacey Lander, Eric Steven Palotie, Aarno Broad Institute of MIT and Harvard Massachusetts Institute of Technology. Department of Biology Gabriel, Stacey Lander, Eric Steven Palotie, Aarno 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. 2018-06-29T16:08:14Z 2018-06-29T16:08:14Z 2017-04 2016-12 2018-06-28T13:23:36Z Article http://purl.org/eprint/type/JournalArticle 1018-4813 1476-5438 http://hdl.handle.net/1721.1/116697 Mitt, Mario et al. “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 (April 2017): 869–876 © 2017 The Author(s) http://dx.doi.org/10.1038/EJHG.2017.51 European Journal of Human Genetics Creative Commons Attribution-NonCommercial 4.0 International http://creativecommons.org/licenses/by-nc/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Mitt, Mario Kals, Mart Pärn, Kalle Ripatti, Samuli Morris, Andrew P Metspalu, Andres Esko, Tõnu Mägi, Reedik Palta, Priit Gabriel, Stacey Lander, Eric Steven Palotie, Aarno Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title | Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title_full | Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title_fullStr | Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title_full_unstemmed | Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title_short | Improved imputation accuracy of rare and low-frequency variants using population-specific high-coverage WGS-based imputation reference panel |
| title_sort | improved imputation accuracy of rare and low frequency variants using population specific high coverage wgs based imputation reference panel |
| url | http://hdl.handle.net/1721.1/116697 |
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