an R/Shiny app for interactive analysis and exploration of cell-cell communication based on single-cell transcriptomics data

InterCellar allows researchers to interactively analyze the results of cell-cell communication from scRNA-seq data. Starting from pre-computed ligand-receptor interactions, InterCellar provides filtering options, annotations and multiple visualizations to explore clusters, genes and functions. Moreover, based on functional annotation from Gene Ontology and pathway databases, InterCellar implements data-driven analyses to investigate cell-cell communication in one or multiple conditions.

Every step of the analysis can be performed interactively, thus not requiring any programming skills. Moreover, InterCellar runs on your local machine, avoiding issues related to data privacy.

Branch	R CMD check	Last updated
devel
release

InterCellar is distributed as a Bioconductor package and requires R (version 4.1) and Bioconductor (version 3.14).

To install InterCellar package enter:

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

BiocManager::install("InterCellar")

Alternatively, InterCellar can be installed through Bioconda. We recommend installing InterCellar in a fresh environment, such as:

conda create --name=intercellar_env 
conda activate intercellar_env
conda install bioconductor-intercellar

Once the installation is done, you can start R simply by

R

A third option would be to pull the docker container as indicated here. See bioconductor-intercellar/tags for valid values for <tag>, then run:

docker pull quay.io/biocontainers/bioconductor-intercellar:<tag>

Lastly, you would need to run

docker run -td quay.io/biocontainers/bioconductor-intercellar:<tag>
docker exec -it <container_ID> /bin/bash

R

Once InterCellar is successfully installed, it can be loaded inside R or Rstudio as follow:

library(InterCellar)

In order to start the app, please run the following command:

InterCellar::run_app( reproducible = TRUE )

InterCellar should be opening in a browser. If this does not happen automatically, please open a browser and navigate to the address shown (for example, Listening on http://127.0.0.1:6134). The flag reproducible = TRUE ensures that your results will be reproducible across R sessions.

It might happen that the installation through BiocManager fails due to missing packages, throwing a similar error:

ERROR: dependencies 'golem', 'ComplexHeatmap' are not available for package 'InterCellar' 

One solution would be to install the missing packages independently, such as:

BiocManager::install("ComplexHeatmap")
install.packages("golem")

And afterwards re-install InterCellar:

BiocManager::install("InterCellar")

For users that have installed InterCellar through Bioconda or Docker, running InterCellar::run_app() might fail due to this error:

Error in utils::browseURL(appUrl) : 
  'browser' must be a non-empty character string

Try this solution:

# After starting R
options(browser="firefox")

# and then as usual
InterCellar::run_app( reproducible = TRUE )

First time here? Please have a look at InterCellar user guide here.

Please have a look at InterCellar-reproducibility if you are interested in data and results showed in the manuscript.

If you have any question, problem or suggestion, please feel free to open an issue or contact Marta Interlandi at marta.interlandi@uni-muenster.de

Interlandi, M., Kerl, K. & Dugas, M. InterCellar enables interactive analysis and exploration of cell−cell communication in single-cell transcriptomic data. Commun Biol 5, 21 (2022). [https://doi.org/10.1038/s42003-021-02986-2]

Please note that the InterCellar project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.