Cell Annotation and Matching Methods for Single-Cell Analysis
Date:
Detailed presentation on automated cell type annotation and cell matching algorithms for single-cell transcriptomics. Introduced novel methods for transferring cell type labels across datasets using optimal transport, contrastive learning, and attention mechanisms. Discussed challenges in batch effect correction, rare cell type identification, and handling technical variability across sequencing platforms. Demonstrated the CellScout framework for interactive cell annotation with visual analytics support. Covered applications in atlas-scale cell annotation, cross-species cell mapping, and identifying disease-associated cell states through comparative analysis.