Harmonization of Study and Reference Data by PhaseLift: Saving Time When Imputing Study Data
ABSTRACT 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 a...
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Published in | Genetic epidemiology Vol. 38; no. 5; pp. 381 - 388 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.07.2014
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | ABSTRACT
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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Bibliography: | German Research Foundation - No. WE1259/18-1; No. WE1259/19-1 istex:DE34C7E55AD861E76BD4471F97018CA4A46C2DD8 ark:/67375/WNG-PSWL6KQ4-L Alcon Research Institute (to BHFW) Federal Ministry of Research and Education - No. BMBF 01ER1206 ArticleID:GEPI21812 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 |
ISSN: | 0741-0395 1098-2272 |
DOI: | 10.1002/gepi.21812 |