The continuous developments of single-cell RNA-Seq (scRNA-Seq) have sparked an immense interest in understanding intercellular crosstalk. Multiple tools and resources that aid the investigation of cell-cell communication (CCC) were published recently. However, these methods and resources are usually in a fixed combination of a tool and its corresponding resource, but in principle any resource could be combined with any method.

LIANA Framework

To this end, we built a framework to decouple the methods from their corresponding resources.

LIANA also goes a step further as it provides:

  • A robust and extendable architecture that aims to accelerate method development and benchmarks

  • A rank aggregate from the results of different methods

  • A customizable plethora of resources



The tools implemented in this repository are:

*The scoring systems from these methods were re-implemented in LIANA in order to account for multimeric complexes, to simplify the calls to the individual pipelines, or reduce any possible inconsistencies and redundancies in their downstream integration. If you wish to run LIANA with the original tools please see LIANA++.


Cell-cell Communication resources

The following CCC resources are accessible via this pipeline:

  • CellChatDB
  • CellPhoneDB
  • Ramilowski2015
  • Baccin2019
  • LRdb
  • Kiroauc2010
  • iTALK
  • HPMR
  • Guide2Pharma
  • connectomeDB2020
  • talklr
  • CellTalkDB
  • OmniPath


All the resources above are retrieved from OmniPath, and more specifically OmnipathR. However, individual resources retrieved from the OmniPath web service are not to be affected by this, as each resource expected to be identical to its original form, apart from minor processing imperfections.

OmniPath itself serves as a composite CCC resource combining all the ones listed above + more. OmniPath also collects further information about the roles and localisation of proteins in intercellular communication. We made use of this information regarding the and by default the OmniPathCCC resource in LIANA is filtered according to the consensus localisation and curation of ligand-receptor interactions. To obtain more information how we filtered the default CCC OmniPath, as well as to explore custom filter options see customizing OmniPath resources.

Install LIANA

if (!requireNamespace("BiocManager", quietly = TRUE))

If you wish to make use of the CellChat algorithm:


If you also wish to run the CellPhoneDB re-implementation from Squidpy, please set up a conda environment by running the following lines in the terminal:

conda create -n liana_env
conda activate liana_env
conda install -c anaconda python=3.8.5
pip install squidpy


See a tutorial how to use LIANA to run all methods and resource from above! The tutorial with the test data takes minutes to complete!


If you are interested in making use of the LIANA architecture for your own method, this vignette provides instructions how to obtain a comprehensive table of LR statistics, which can then be used by custom scoring functions. In the same vignette are also instructions how to install and run the original methods via a convenient R wrapper, e.g. for their unbiased benchmark.


We appreciate any feedback, so please do not hesitate to open an issue on the liana github page!

Citing LIANA:

Dimitrov, D., Türei, D., Boys, C., Nagai, J.S., Flores, R.O.R., Kim, H., Szalai, B., Costa, I.G., Dugourd, A., Valdeolivas, A. and Saez-Rodriguez, J., 2021. Comparison of Resources and Methods to infer Cell-Cell Communication from Single-cell RNA Data. bioRxiv. 10.1101/2021.05.21.445160v1

Also, if you use the OmniPath CCC Resource for your analysis, please cite:

Türei, D., Valdeolivas, A., Gul, L., Palacio‐Escat, N., Klein, M., Ivanova, O., Ölbei, M., Gábor, A., Theis, F., Módos, D. and Korcsmáros, T., 2021. Integrated intra‐and intercellular signaling knowledge for multicellular omics analysis. Molecular systems biology, 17(3), p.e9923.

Similarly, please consider appropritaly citing any of the methods and/or resources implemented in liana, that were particularly relevant for your research!