SingleCellSignalR Version 2

Overview

SingleCellSignalR infer ligand-receptor (L-R) interactions from single cells experiments.

Version 2 of the library introduces an important change: we have integrated SignleCellSignalR with its sister Bioconductor library BulkSignalR. This has required several changes starting with a design based on S4 object, but also and very importantly generic mechanisms to update and download reference databases, and to deal with non Homo sapiens species. Previously, only Mus musculus was available and the reference databases were distributed alongside the library.

Moreover, integration with BulkSignalR was also the opportunity to propose a new L-R interaction scoring including target genes in pathways downstream the receptor. This new scoring is based on the BullkSignalR statistical model used in differential analysis mode. It provides a complementary perspective to SingleCellSignalR original scoring named LR-score. The latter was limited to the ligand and the receptor expression, while the differential score from BulkSignalR rather reflects an increase of activity. If many related cell populations are considered, for instance immune cells, then the differential score might miss recurrent though important L-R interactions. The LR-score would not suffer from recurrence. Conversely, to consider target genes below the receptor and to focus on contrasts between cell populations is also highly relevant in many contexts. Hence the interest of the scoring inherited from BulkSignalR. Lastly, we show in the application examples that flexibility of the new S4 design even enables users to implement an expression score based on the LR-score that includes target gene expression on top of the ligand and the receptor expressions.

That is, SingleCellSignalR Version 2 offers a lot of flexibility to adapt to the specifics of the data at hand. Moreover, this new version gives access to the many graphical functions provided with BulkSignalR.

Technically, SingleCellSignalR Version 2 can be regarded as a wrapper to BulkSignalR differential analysis classes. BulkSignalR contains most of the code complexity and serves as a basic layer to develop specific applications such as single-cell analyses.

 

Installation

# Installation can go via GitHub:
# install.packages("devtools")
devtools::install_github("jcolinge/BulkSignalR",build_vignettes = TRUE)
devtools::install_github("jcolinge/SingleCellSignalR",build_vignettes = TRUE)

# or directly from Bioconductor
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("SingleCellSignalR")

# To read the vignette
# browseVignettes("SingleCellSignalR")

 

Notes

For a version history/change logs, see the NEWS file.

Version 1 of SingleCellSignalR (original version as published in NAR in 2020), is still available from a branch of this repository names version_1.

SingleCellSignalR has been successfully installed on Mac OS X, Linux, and Windows using R version 4.5.

The code in this repository is published with the CeCILL License.