PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
Gorski, M.* ; Winkler, T.W.* ; Stark, K.* ; Müller-Nurasyid, M. ; Ried, J.S. ; Grallert, H. ; Weber, B.H.F.* ; Heid, I.M.

Harmonization of study and reference data by PhaseLift: Saving time when imputing study data.

Genet. Epidemiol. 38, 381-388 (2014)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
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.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Altmetric
2.951
1.154
1
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 1000 Genomes ; Hapmap ; Genome-wide Association Studies ; Genotype Imputation ; Imputation Quality ; Meta-analysis; Genome-wide Association; Genotype Imputation; Macular Degeneration; Genetic-variation; Disease
Sprache englisch
Veröffentlichungsjahr 2014
HGF-Berichtsjahr 2014
ISSN (print) / ISBN 0741-0395
e-ISSN 1098-2272
Zeitschrift Genetic Epidemiology
Quellenangaben Band: 38, Heft: 5, Seiten: 381-388 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort Hoboken
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Genetic Epidemiology (IGE)
CCG Nutrigenomics and Type 2 Diabetes (KKG-KDN)
Institute of Epidemiology (EPI)
POF Topic(s) 30501 - Systemic Analysis of Genetic and Environmental Factors that Impact Health
30502 - Diabetes: Pathophysiology, Prevention and Therapy
30202 - Environmental Health
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-504100-001
G-521600-002
G-504091-002
PubMed ID 24962562
DOI 10.1002/gepi.21812
WOS ID WOS:000340556700003
Scopus ID 84902961915
Erfassungsdatum 2014-07-09
[➜Korrektur melden]