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single-cell-cellphonedb-communication-mapping

Quantify ligand–receptor communication between annotated single-cell populations using CellPhoneDB v5.

32|5|Updated Mar 12, 2026
Search Tags:#ligand-receptor#single-cell#omicverse#anndata#cellphonedb#cellchat#cell-cell-communication
One-click install
npx skills add https://github.com/omicverse/omicclaw --skill single-cell-cellphonedb-communication-mapping-omicverse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: single-cell-cellphonedb-communication-mapping
Source: https://github.com/omicverse/omicclaw/tree/main/src/omicverse_skills/skills/single-cellphone-db
Command: npx skills add https://github.com/omicverse/omicclaw --skill single-cell-cellphonedb-communication-mapping-omicverse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quantify and visualize ligand–receptor communication between annotated single-cell populations to reveal cell-cell signalling programs and pathway-level interactions without manual permutation management.

Core Features & Use Cases

  • Run CellPhoneDB v5 analysis on a curated AnnData object to compute ligand-receptor interaction permutations and statistical significance.
  • Aggregate and summarise networks into count and weight matrices for system-level comparison and per-celltype sender/receiver analyses.
  • CellChat-style visualisations including circle plots, chord diagrams, heatmaps, bubble plots, gene-level chords, and centrality/signaling-role analyses for published-like figures.
  • Use Case: Reproduce the trophoblast communication workflow from the OmicVerse tutorial to identify signalling pathways such as FGF or interleukin signaling between EVT and dNK populations.

Quick Start

Run CellPhoneDB v5 on an annotated AnnData file using omicverse, save the cpdb results and processed AnnData, then open CellChat-style visualisations to inspect significant pathways.

Frequently Asked Questions about single-cell-cellphonedb-communication-mapping

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

FAQPage Schema
How do I map ligand-receptor cell-cell communication from scRNA-seq data?▼

To map ligand-receptor communication, you can run CellPhoneDB v5 on a preprocessed AnnData object with curated cell type annotations. The analysis performs statistical permutation testing to identify significant cell-cell signaling interactions between single-cell populations.

Do I need a specific database to run CellPhoneDB v5 on my AnnData object?▼

Yes, running CellPhoneDB v5 requires a CellPhoneDB v5 SQLite bundle to provide the ligand-receptor interaction database. You also need sufficient iterations and threads configured to perform the statistical permutations accurately.

What's the best way to visualize cell-cell communication networks from single-cell data?▼

The best way to visualize cell-cell communication networks is using CellChat-style visualizations provided by omicverse plotting tools. You can generate circle plots, chord diagrams, heatmaps, and bubble plots to inspect significant ligand-receptor pathways and signaling roles.

Can I summarize ligand-receptor interactions into system-level networks for my scRNA-seq dataset?▼

Yes, you can aggregate and summarize ligand-receptor interactions into count and weight matrices. This allows for system-level comparison and per-celltype sender/receiver analyses to understand global cell-cell signaling programs within your single-cell dataset.

How do I identify specific signaling pathways like FGF or interleukin between cell populations?▼

You can identify specific signaling pathways by running CellPhoneDB v5 and performing pathway-level interrogation on the results. This workflow reveals pathway-specific interactions, such as FGF or interleukin signaling between EVT and dNK populations, using omicverse visualization.

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