Cellinker

Cellinker catalogs literature-supported ligand-receptor (L-R) interactions to enable analysis of intercellular communication, cell adhesion, recognition, and ligand-receptor-mediated signaling in single-cell RNA-sequencing (scRNA-seq) studies.

Key Features:

• Curated L-R interaction database: Provides a curated collection of high-confidence, literature-supported ligand-receptor (L-R) interactions.
• Coverage of protein-protein interactions (PPIs): Documents over 3,700 human and 3,200 mouse L-R protein-protein interactions (PPIs).
• Endogenous small molecule (sMOL) interactions: Includes information on over 400 endogenous small molecule related L-R interactions.
• scRNA-seq integration: Supports decoding intercellular communications using single-cell RNA-sequencing (scRNA-seq) data.
• Coronavirus-related L-Rs: Contains 16 CoV-human L-R PPIs with detailed information for 12 L-R PPIs related to SARS-CoV-2 infection.

Scientific Applications:

• Intercellular communication analysis: Inference and interpretation of cell-cell communication networks from scRNA-seq data.
• Signaling pathway investigation: Study of cell adhesion, recognition, and ligand-receptor-mediated signaling in physiological and pathological contexts.
• Host-virus interaction research: Analysis of CoV and SARS-CoV-2 L-R PPIs to investigate virus–host interactions.
• Algorithm development and benchmarking: Use as a reference resource for development and benchmarking of scRNA-seq-based interaction inference algorithms.

Methodology:

Decoding intercellular communications from single-cell RNA-sequencing (scRNA-seq) data by mapping expression data to the curated, literature-supported L-R interaction database.