CellMentor

CellMentor implements supervised cell type-aware non-negative matrix factorization (NMF) for dimensional reduction in single-cell RNA sequencing analysis.

Key Features:

• Supervised dimensionality reduction: Incorporates cell type information into the dimensionality reduction process to preserve biological structure.
• Cell type-aware loss function: Simultaneously minimizes variation within known cell populations while maximizing distinctions between different cell types.
• Transfer learning: Enables effective transfer of learned patterns from labeled reference datasets to new unlabeled data.

Scientific Applications:

• Single-cell RNA sequencing analysis: Improves visualization and downstream analysis of single-cell data while preserving biological structure.

Methodology:

Supervised non-negative matrix factorization with a cell type-aware loss function.