Removing array-specific batch effects in GWAS mega-analyses by applying a two-step imputation workflow
The study provides a workflow for high-quality imputation results without batch effects, fostering genetic analysis involving multiple genotyping arrays.
Authors
- Henry Völzke (ORCID: https://orcid.org/0000-0001-7003-399X)
- Eva König (ORCID: https://orcid.org/0000-0002-2079-3525)
- Christian Fuchsberger (ORCID: https://orcid.org/0000-0002-5918-8947)
- Hans Jörgen Grabe (ORCID: https://orcid.org/0000-0003-3684-4208)
- M. Kamal Nasr (ORCID: https://orcid.org/0009-0004-2816-7168)
- Sahar Ghasemi (ORCID: https://orcid.org/0000-0002-9565-0289)
- Alexander Teumer (ORCID: https://orcid.org/0000-0002-8309-094X)
- Uwe Völker (ORCID: https://orcid.org/0000-0002-5689-3448)
Institutions
- Eurac Research (IT)
- University of Freiburg (DE)
- Universitätsmedizin Greifswald (DE)
- University Medical Center Freiburg (DE)
- German Center for Neurodegenerative Diseases (DE)
- Universität Greifswald (DE)
- Institute for Biomedicine (IT)
- German Centre for Cardiovascular Research (DE)
Publication Details
- Journal
- Bioinformatics Advances
- Published
- 2025-12-12
- DOI
- https://doi.org/10.1093/bioadv/vbaf317
- Citations
- 1
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.82
Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Siemens Healthineers
- Universität Greifswald