clustifyr

clustifyr classifies cells from single-cell RNA sequencing data using external reference data such as bulk RNA-seq, scRNA-seq, microarray expression data, or signature gene lists to assign cell types via correlation-based and gene list enrichment methods.

Key Features:

• Multi-source reference compatibility: Leverages external data types including scRNA-seq, bulk RNA-seq, microarray expression data, and signature gene lists for cell type assignment.
• Correlation-based classification: Implements various correlation-based methods for assigning likely cell types to cell clusters.
• Gene list enrichment methods: Provides gene list enrichment methods to assist cell type assignment.
• Benchmarked parameters: Various parameters of the correlation-based approach are benchmarked for performance optimization.

Scientific Applications:

• Automated scRNA-seq cluster classification: Assigns cell types from single-cell RNA sequencing data in an automated manner to reduce time consumption and error in manual classification.
• Cross-platform cell type assignment: Enables cell type identification using diverse reference data types across different transcriptomic platforms.

Methodology:

clustifyr uses correlation-based approaches and gene list enrichment methods; various parameters of the correlation-based approach are benchmarked.