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Single-cell, Spatial & Cytometry · Cell-Cell Communication

CellChat

By University of California, Irvine (Nie Lab) →

Inference and analysis of cell-cell communication networks from single-cell data

CellChat quantitatively infers and visualizes intercellular signaling networks from single-cell and spatial transcriptomics data, incorporating curated ligand-receptor-cofactor complexes.

Comprehensive database of signaling interactions accounting for multi-subunit complexesQuantification of incoming and outgoing signaling communication probability per cell typePattern recognition uncovering major signaling coordination pathwaysSupport for spatial transcriptomics to restrict communication by physical distance
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Overview

CellChat quantitatively infers and visualizes intercellular signaling networks from single-cell and spatial transcriptomics data, incorporating curated ligand-receptor-cofactor complexes.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:09:40

Key Features

  • Comprehensive database of signaling interactions accounting for multi-subunit complexes
  • Quantification of incoming and outgoing signaling communication probability per cell type
  • Pattern recognition uncovering major signaling coordination pathways
  • Support for spatial transcriptomics to restrict communication by physical distance

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
Tumor microenvironment analysis, immune cell crosstalk, and developmental biology
Research Workflow
Single-cell expression matrix -> signaling pathway probabilities and network graphs
Compute & Hardware
Standard workstation CPU (R package)
Licensing & Academic Use
GPL-3.0
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing CellChat in scientific publications and benchmark papers.

@software{cellchat_2026,
  title = {{CellChat}},
  author = {{University of California, Irvine (Nie Lab)}},
  year = {2026},
  url = {https://github.com/jinworks/CellChat},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for CellChat.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeR Software Package
Access modeOpen Source
AI roleNetwork Inference & Pattern Recognition
Input dataNot recorded
Output dataNot recorded
Licence conditionsGPL-3.0
Commercial eligibilityOpen source release
Compute requirementsStandard workstation CPU (R package)
ValidationNot recorded
TypeIntercellular signaling inference tool
Intended useNot recorded
CompatibilityNot recorded
ManufacturerUC Irvine
Biological applicationTumor microenvironment analysis, immune cell crosstalk, and developmental biology
Research workflowSingle-cell expression matrix -> signaling pathway probabilities and network graphs
Evidence levelPeer-reviewed research (Nature Communications 2021)
Integration evidencehttps://github.com/jinworks/CellChat
Laboratory handoffValidates predicted ligand-receptor pairs via antibody blockade or co-culture assays
AvailabilityAvailable on GitHub and CRAN
Price / accessFree Open Source

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for CellChat yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

Available on GitHub and CRAN

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating CellChat.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5