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bio-single-cell-cell-communication

Infer cell-cell communication networks from scRNA-seq data via ligand-receptor interactions.

Updated Mar 30, 2026
Search Tags:#visualization#ligand-receptor#scrna-seq#cellchat#liana#cell-cell-communication#nichenetr
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-single-cell-cell-communication
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bio-single-cell-cell-communication
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/bio-single-cell-cell-communication
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill bio-single-cell-cell-communication

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when inferring ligand-receptor interactions between cell types.

Core Features & Use Cases

  • Integrates CellChat, NicheNet, and LIANA to identify ligand-receptor interactions and visualize intercellular signaling.
  • Supports cross-method comparisons across conditions or cell types, with pathway-level aggregation and visualization.
  • Example: compare signaling between macrophages and T cells across control vs treated samples.

Quick Start

Run an analysis to identify and visualize intercellular communications among defined cell types using the three tools.

Frequently Asked Questions about bio-single-cell-cell-communication

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I infer cell-cell communication networks from scRNA-seq data?▼

To infer cell-cell communication networks from scRNA-seq data, this Skill identifies ligand-receptor interactions between cell types using CellChat, NicheNet, and LIANA for robust integration and visualization of intercellular signaling results.

Can I compare ligand-receptor interactions between control and treated samples?▼

Yes, you can compare ligand-receptor interactions between control and treated samples, as the Skill supports cross-method comparisons across conditions or cell types with pathway-level aggregation and visualization of the intercellular signaling.

Do I need annotated single-cell data to analyze intercellular signaling?▼

Yes, annotated single-cell data is required to analyze intercellular signaling, and you must also have access to CellChat and NicheNet in R, plus LIANA in Python, to execute the ligand-receptor interaction analysis.

What is the best way to visualize intercellular signaling between macrophages and T cells?▼

The best way to visualize intercellular signaling between macrophages and T cells is using this Skill to integrate CellChat, NicheNet, and LIANA, which identifies ligand-receptor interactions and generates visualizations of intercellular signaling networks.

Does this Skill support pathway-level aggregation for cell-cell communication analysis?▼

Yes, the Skill supports pathway-level aggregation for cell-cell communication analysis, allowing you to compare signaling between cell types and conditions while integrating results from CellChat, NicheNet, and LIANA.

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