CellAnn

CellAnn annotates cell types in single-cell RNA sequencing (scRNA-seq) clusters by transferring labels from curated reference single-cell datasets to support accurate cluster-level cell-type assignment.

Key Features:

• Extensive reference database: Contains 204 human and 191 mouse single-cell datasets covering 32 organs.
• Cluster-to-cluster alignment method: Implements a cluster-to-cluster alignment approach to transfer cell labels from reference to query clusters with scalability and improved accuracy.
• Reference dataset searching: Supports searching and selecting relevant reference datasets from the curated collection.
• Label transfer: Performs transfer of cell labels from reference datasets to query clusters.
• Visualization: Produces visualizations of annotation results for assessed clusters.
• Harmonization of annotations: Harmonizes cell annotation labels across references and query datasets.

Scientific Applications:

• Cell-type annotation: Assigns cell-type identities to clusters derived from scRNA-seq experiments.
• Cross-reference validation: Enables cross-validation of cluster annotations using multiple published reference datasets.
• Cross-species comparison: Facilitates comparative annotation workflows using both human and mouse references.

Methodology:

Performs reference dataset searching, applies a cluster-to-cluster alignment method to transfer cell labels from reference to query clusters, harmonizes annotation labels, and generates visualization of results.