scMapNet: Marker-based cell type annotation of scRNA-seq data via vision transfer learning with tabular-to-image transformations
scMapNet shows significant performance in annotation accuracy and batch insensitivity. Besides, this method also has good interpretability and can provide biological insights for researchers.
Authors
- Jianbo Pan (ORCID: https://orcid.org/0000-0001-6014-8160)
- Ying Ye (ORCID: https://orcid.org/0000-0002-6886-8602)
- Zhe Yu (ORCID: https://orcid.org/0009-0007-1508-439X)
Institutions
- Dalian Medical University (CN)
- Second Affiliated Hospital of Chongqing Medical University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Journal of Advanced Research
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1016/j.jare.2025.10.056
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81