A deep learning approach to prediction of blood group antigens from genomic data
High accuracy in a variety of blood groups proves viability of deep learning-based blood type prediction using array chip genotypes, even in blood groups with nontrivial genetic underpinnings. These techniques are suitable for aiding in identifying blood donors with rare blood types by greatly narrowing down the potential pool of candidate donors before clinical grade confirmation.
Authors
- Mie Topholm Bruun (ORCID: https://orcid.org/0000-0002-8819-5388)
- Susanne Gjørup Sækmose (ORCID: https://orcid.org/0000-0002-1346-0052)
- Thorsten Brodersen (ORCID: https://orcid.org/0000-0003-4431-9972)
- Christina Mikkelsen (ORCID: https://orcid.org/0000-0002-2945-6197)
- Camous Moslemi (ORCID: https://orcid.org/0000-0001-7905-9774)
- Henrik Ullum (ORCID: https://orcid.org/0000-0001-7306-9058)
- Jukka Partanen (ORCID: https://orcid.org/0000-0001-6681-4734)
- Maria Didriksen (ORCID: https://orcid.org/0000-0002-4856-496X)
- Kati Hyvärinen (ORCID: https://orcid.org/0000-0003-4605-2837)
- Joseph Dowsett (ORCID: https://orcid.org/0000-0001-5381-2633)
- Jarmo Ritari (ORCID: https://orcid.org/0000-0002-3458-9314)
- Martin L. Olsson (ORCID: https://orcid.org/0000-0003-1647-9610)
- Jakob Thaning Bay (ORCID: https://orcid.org/0000-0003-1159-4003)
- Ole Birger Pedersen (ORCID: https://orcid.org/0000-0003-2312-5976)
- Sisse Rye Ostrowski (ORCID: https://orcid.org/0000-0001-5288-3851)
- Rune Larsen (ORCID: https://orcid.org/0000-0002-7635-8012)
- Khoa Manh Dinh (ORCID: https://orcid.org/0000-0003-1881-5673)
- Kaspar René Nielsen (ORCID: https://orcid.org/0000-0003-4406-9643)
- Christian Erikstrup
Institutions
- Statens Serum Institut (DK)
- Roskilde University (DK)
- University of Copenhagen (DK)
- Lund University (SE)
- Aarhus University (DK)
- Aalborg University Hospital (DK)
- Finnish Red Cross (FI)
- Odense University Hospital (DK)
- Aarhus University Hospital (DK)
- Copenhagen University Hospital (DK)
- Zealand University Hospital Køge (DK)
Publication Details
- Journal
- Transfusion
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1111/trf.18013
- Citations
- 4
- Primary Topic
- Blood groups and transfusion
- Type
- article
- Field-Weighted Citation Impact
- 1.82
Funders
- Novo Nordisk
- Novo Nordisk Fonden