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Harmonization of study and reference data by PhaseLift: Saving time when imputing study data.
Genet. Epidemiol. 38, 381-388 (2014)
Genome-wide association studies are usually accompanied by imputation techniques to complement genome-wide SNP chip genotypes. Current imputation approaches separate the phasing of study data from imputing, which makes the phasing independent from the reference data. The two-step approach allows for updating the imputation for a new reference panel without repeating the tedious phasing step. This advantage, however, does no longer hold, when the build of the study data differs from the build of the reference data. In this case, the current approach is to harmonize the study data annotation with the reference data (prephasing lift-over), requiring rephasing and re-imputing. As a novel approach, we propose to harmonize study haplotypes with reference haplotypes (postphasing lift-over). This allows for updating imputed study data for new reference panels without requiring rephasing. With continuously updated reference panels, our approach can save considerable computing time of up to 1 month per re-imputation. We evaluated the rephasing and postphasing lift-over approaches by using data from 1,644 unrelated individuals imputed by both approaches and comparing it with directly typed genotypes. On average, both approaches perform equally well with mean concordances of 93% between imputed and typed genotypes for both approaches. Also, imputation qualities are similar (mean difference in RSQ < 0.1%). We demonstrate that our novel postphasing lift-over approach is a practical and time-saving alternative to the prephasing lift-over. This might encourage study partners to accommodate updated reference builds and ultimately improve the information content of study data. Our novel approach is implemented in the software PhaseLift.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
1000 Genomes ; Hapmap ; Genome-wide Association Studies ; Genotype Imputation ; Imputation Quality ; Meta-analysis; Genome-wide Association; Genotype Imputation; Macular Degeneration; Genetic-variation; Disease
ISSN (print) / ISBN
0741-0395
e-ISSN
1098-2272
Journal
Genetic Epidemiology
Quellenangaben
Volume: 38,
Issue: 5,
Pages: 381-388
Publisher
Wiley
Publishing Place
Hoboken
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Genetic Epidemiology (IGE)
CCG Nutrigenomics and Type 2 Diabetes (KKG-KDN)
Institute of Epidemiology II (EPI2)
CCG Nutrigenomics and Type 2 Diabetes (KKG-KDN)
Institute of Epidemiology II (EPI2)