NICHES

NICHES embeds ligand-receptor signal proxies into single-cell and spatial transcriptomic datasets to quantify and visualize heterogeneous extracellular cell-cell signaling at single-cell resolution.

Key Features:

• Single-Cell Resolution: Preserves individual-cell data to enable analysis of extracellular signaling mechanisms at single-cell resolution.
• Ligand-Receptor Signal Proxies: Embeds ligand-receptor signal proxies to visualize heterogeneous signaling archetypes within and between cell clusters and across experimental conditions.
• Spatial Transcriptomics Compatibility: Applies to spatial transcriptomic data to reflect spatial context of cell-cell interactions and analyze local cellular microenvironments.
• Flexibility with Ligand-Receptor Mechanisms: Operates with any list of ligand-receptor signaling mechanisms to accommodate different signaling definitions.
• Integration with Existing Tools: Compatible with single-cell analysis packages and pseudotime techniques for integration into existing analysis workflows.

Scientific Applications:

• Developmental Biology: Enables analysis of cell-cell signaling dynamics during development.
• Immunology: Supports analysis of intercellular immune signaling.
• Oncology: Supports studies in oncology that require analysis of cell-cell interactions.
• Tissue-Specific Studies and Disease Modeling: Analyzes spatial transcriptomic data to study tissue-specific cell-cell interactions and disease models.

Methodology:

Embeds ligand-receptor signal proxies into single-cell datasets to visualize signaling heterogeneity and preserves individual cell data integrity while enhancing interpretability of interaction networks.