scDiffCom
Differential Analysis of Intercellular Communication from scRNA-Seq Data
Analysis tools to investigate changes in intercellular communication from scRNA-seq data. Using a Seurat object as input, the package infers which cell-cell interactions are present in the dataset and how these interactions change between two conditions of interest (e.g. young vs old). It relies on an internal database of ligand-receptor interactions (available for human, mouse and rat) that have been gathered from several published studies. Detection and differential analyses rely on permutation tests. The package also contains several tools to perform over-representation analysis and visualize the results. See Lagger, C. et al. (2023) <doi:10.1038/s43587-023-00514-x> for a full description of the methodology.
README
<!-- README.md is generated from README.Rmd. Please edit that file -->
# scDiffCom
<!-- badges: start -->
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://CRAN.R-project.org/package=scDiffCom)
[](https://app.codecov.io/gh/CyrilLagger/scDiffCom)
[](https://github.com/CyrilLagger/scDiffCom/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
scDiffCom stands for “single-cell Differential Communication” and infers
changes in intercellular communication between two biological conditions
from scRNA-seq data (as [Seurat](https://satijalab.org/seurat/)
objects). The package relies on an internal collection of
ligand-receptor interactions (available for human, mouse and rat)
retrieved from seven curated databases.
<details>
<summary>
Display LRI databases
</summary>
- [CellChat](https://github.com/jinworks/CellChat)
- [CellPhoneDB](https://www.cellphonedb.org/)
- [CellTalkDB](https://github.com/ZJUFanLab/CellTalkDB)
- [connectomeDB2020](https://github.com/forrest-lab/NATMI)
- [ICELLNET](https://github.com/soumelis-lab/ICELLNET)
- [NicheNet](https://github.com/saeyslab/nichenetr)
- [SingleCellSignalR](https://www.bioconductor.org/packages/release/bioc/html/SingleCellSignalR.html)
</details>
## Installation
``` r
# Install the development version from GitHub
devtools::install_github("CyrilLagger/scDiffCom")
# Install release version from CRAN
install.packages("scDiffCom")
```
## Usage
As an introduction, please look at the
[documentation](https://cyrillagger.github.io/scDiffCom/) and this
[vignette](https://cyrillagger.github.io/scDiffCom/articles/scDiffCom-vignette.html).
For a concrete and large-scale project that used scDiffCom, please look
at [scagecom.org](https://scagecom.org/), our murine atlas of
age-related changes in intercellular communication.
## Citation
Please consider reading and citing our Nature Aging paper:
[here](https://www.nature.com/articles/s43587-023-00514-x).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2.0 |
rolling linux/jammy R-4.5 | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
rolling linux/noble R-4.5 | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
rolling source/ R- | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
latest linux/jammy R-4.5 | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
latest linux/noble R-4.5 | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
latest source/ R- | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
2026-04-26 source/ R- | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.2.0 |
2026-04-23 source/ R- | scDiffCom_1.2.0.tar.gz |
2.1 MiB |
1.0.0 |
2025-04-20 source/ R- | scDiffCom_1.0.0.tar.gz |
2.1 MiB |