CrossTalkeR

CrossTalkeR analyzes ligand-receptor interaction networks from single-cell RNA sequencing (scRNA-seq) data to quantify and visualize changes in cellular crosstalk between biological phenotypes.

Key Features:

• Focused Analysis: Enables interrogation of specific cell types, ligands, or receptors within ligand-receptor (LR) networks derived from scRNA-seq data.
• Phenotype Contrast: Quantifies and analyzes changes in cellular crosstalk between two distinct biological phenotypes, such as disease versus homeostasis.
• Visualization: Provides visualization of LR interaction networks to aid interpretation of contributors to altered cell communication patterns.

Scientific Applications:

• Disease crosstalk characterization: Identifies molecular mechanisms and altered cell-cell communication associated with pathological conditions by contrasting disease and normal states.
• Case study — myeloproliferative neoplasms: Applied to scRNA-seq data from human myeloproliferative neoplasms to elucidate complex LR interactions driving disease-associated crosstalk changes.

Methodology:

Constructs and analyzes ligand-receptor interaction networks from single-cell RNA sequencing (scRNA-seq) data, identifies relevant ligands, receptors, and cell types, and quantifies crosstalk alterations between contrasted phenotypes.