SCITUNA: single-cell data integration tool using network alignment
SCITUNA effectively removes batch effects while retaining the biological signals present in the data. Our extensive experiments reveal that SCITUNA will be a valuable tool for diverse integration tasks.
Authors
- Öznur Taştan (ORCID: https://orcid.org/0000-0001-7058-5372)
- Aissa Houdjedj (ORCID: https://orcid.org/0000-0002-8400-0854)
- Cesim Erten (ORCID: https://orcid.org/0000-0002-8149-7113)
- Şenol Doğan (ORCID: https://orcid.org/0000-0001-7358-4850)
- Hilal Kazan (ORCID: https://orcid.org/0000-0003-2461-4579)
- Yacine Marouf (ORCID: https://orcid.org/0000-0002-4621-1407)
- Mekan Myradov
- Burak Onur Erten
Institutions
- Sabancı Üniversitesi (TR)
- University of Arizona (US)
- Akdeniz University (TR)
- Cornell University (US)
- Antalya Bilim University (TR)
- Weill Cornell Medicine (US)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1186/s12859-025-06087-3
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Türkiye Bilimsel ve Teknolojik Araştırma Kurumu