A self-training interpretable cell type annotation framework using specific marker gene
The source code of sICTA is available in public at https://github.com/nbnbhwyy/sICTA. The processed datasets can be found at https://drive.google.com/drive/folders/1jbqSxacL_IDIZ4uPjq220C9Kv024m9eL. The final version of the model will be permanently available at https://doi.org/10.5281/zenodo.13474010.
Authors
- Hegang Chen (ORCID: https://orcid.org/0000-0001-8338-3884)
- Yuyin Lu
- Yanghui Rao (ORCID: https://orcid.org/0000-0003-1610-9599)
Institutions
- Sun Yat-sen University (CN)
Publication Details
- Journal
- Bioinformatics
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1093/bioinformatics/btae569
- Citations
- 1
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- National Natural Science Foundation of China