Identifying cellular identities is crucial in single-cell transcriptomics. Here, authors show that large-scale deep learning-based cell annotation models, trained on hundreds of cross-tissue scRNA-seq datasets, enhance prediction quality for fine-grained highly related cell types and states.
- Felix Fischer
- David S. Fischer
- Fabian J. Theis
