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Eur J Hum Genet. 2014 Nov;22(11):1321-6. doi: 10.1038/ejhg.2014.19. Epub 2014 Jun 4.

Improved imputation quality of low-frequency and rare variants in European samples using the 'Genome of The Netherlands'.

Author information

1
1] University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands [2] University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, The Netherlands.
2
Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands.
3
Department of Epidemiology, Genetic Epidemiology Unit, Erasmus Medical Center, Rotterdam, The Netherlands.
4
1] Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands [2] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [3] Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Rotterdam, The Netherlands.
5
Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.
6
1] Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands [2] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [3] Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA [4] Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
7
1] Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands [2] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [3] COPSAC; Copenhagen Prospective Studies on Asthma in Childhood; Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
8
University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands.
9
1] University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, The Netherlands [2] NBIC BioAssist, Netherlands Bioinformatics Center, Nijmegen, The Netherlands.
10
Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
11
1] Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands [2] Department of Epidemiology, University Medical Center Utrecht, Utrecht, The Netherlands [3] Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA [4] Broad Institute of Harvard and MIT, Cambridge, MA, USA.

Abstract

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with 'true' genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05-0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r(2), increased from 0.61 to 0.71. We also saw improved imputation accuracy for other European populations (in the British samples, r(2) improved from 0.58 to 0.65, and in the Italians from 0.43 to 0.47). A combined reference set comprising 1000G and GoNL improved the imputation of rare variants even further. The Italian samples benefitted the most from this combined reference (the mean r(2) increased from 0.47 to 0.50). We conclude that the creation of a large population-specific reference is advantageous for imputing rare variants and that a combined reference panel across multiple populations yields the best imputation results.

PMID:
24896149
PMCID:
PMC4200431
DOI:
10.1038/ejhg.2014.19
[Indexed for MEDLINE]
Free PMC Article

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