celaref

celaref suggests labels and cell types for clusters from single-cell RNA sequencing experiments by calculating similarity to a reference dataset.

Key Features:

• Cluster Labeling by Reference Comparison: Assigns cell type labels to clusters based on similarity to a reference dataset with known cell types.
• Read Count Input: Requires a table of read counts per cell per gene as input data.
• Cluster Membership Input: Requires a list of cells belonging to each cluster for both test and reference datasets.

Scientific Applications:

• Single-cell RNA-seq Cluster Annotation: Provides cell type suggestions for clusters following the clustering step of single-cell RNA sequencing experiments.
• Cross-dataset Cell Type Identification: Enables identification of cell types by comparison to annotated reference datasets.

Methodology:

The method calculates similarity between test clusters and reference clusters to suggest labels and cell types.