Skip to contents

LIANA LIANA logo

LIgand-receptor ANalysis frAmework for Single-Cell Transcriptomics

📚 Documentation

Full tutorials with figures and examples: https://zaoqu-liu.github.io/liana/

Quick Start 

library(liana)

# Load your SingleCellExperiment or Seurat object
# sce <- your_single_cell_data

# Run LIANA with multiple methods
liana_res <- liana_wrap(
    sce,
    method = c("natmi", "connectome", "logfc", "sca", "cellphonedb"),
    resource = "Consensus"
)

# Aggregate results across methods
liana_aggr <- liana_aggregate(liana_res)

# Visualize top interactions
liana_dotplot(liana_aggr, ntop = 20)

Installation 

install.packages("liana", repos = "https://zaoqu-liu.r-universe.dev")

From GitHub 

if (!requireNamespace("remotes", quietly = TRUE))
    install.packages("remotes")

remotes::install_github("Zaoqu-Liu/liana")

Overview

LIANA (LIgand-receptor ANalysis frAmework) is a comprehensive framework for inferring cell-cell communication from single-cell RNA sequencing (scRNA-seq) data. This package integrates multiple ligand-receptor inference methods and curated molecular interaction resources, enabling systematic and reproducible intercellular communication analysis.

This repository is a maintained fork of saezlab/liana, incorporating performance optimizations and enhanced compatibility.

Key Features

  • Multi-method Integration: Unified interface for running CellPhoneDB, NATMI, SingleCellSignalR, Connectome, CytoTalk, and logFC-based approaches
  • Consensus Ranking: Robust rank aggregation across multiple methods to identify high-confidence interactions
  • Flexible Resources: Access to 15+ curated ligand-receptor databases via OmniPath
  • Tensor Decomposition: Context-aware analysis across multiple samples/conditions via cell2cell integration
  • Cross-species Support: Built-in ortholog conversion for mouse and other model organisms

Citation

If you use LIANA in your research, please cite the original publication:

Dimitrov D, Türei D, Garrido-Rodriguez M, Buber PL, Raber G, Nagai JS, Boys C, Flores ROR, Kim H, Szalai B, Costa IG, Valdeolivas A, Dugourd A, Saez-Rodriguez J. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nature Communications. 2022;13(1):3224. doi:[10.1038/s41467-022-30755-0](https://doi.org/10.1038/s41467-022-30755-0)

Authors

Original LIANA Development Team
Daniel Dimitrov, Charlotte Boys, Martin Garrido Rodriguez, Denes Turei, James Nagai
Saez-Rodriguez Lab, Heidelberg University

Fork Maintainer
Zaoqu Liu ()
ORCID: 0000-0002-0452-742X

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.