Introducing dominoSignal: Improved Inference of Cell Signaling from Single Cell RNA Sequencing Data

dominoSignal is an updated version of the original Domino R package published in Nature Biomedical Engineering in Computational reconstruction of the signaling networks surrounding implanted biomaterials from single-cell transcriptomics. domino2 is a tool for analysis of intra- and intercellular signaling in single cell RNA sequencing data based on transcription factor activation and receptor and ligand linkages.

Installation

dominoSignal is undergoing active development to improve analysis capabilities and interpretability, so the codebase is subject to change as new features and fixes are implemented.

The current stable version is currently hosted on the FertigLab dominoSignal repository It was forked from this repository ($\textcolor{orange}{\textsf{which is no longer being maintained!}}$) and can be installed using the remotes package.

if(!require(remotes)){
    install.packages('remotes')
}
remotes::install_github('FertigLab/domino2')

Usage Overview

Here is an overview of how dominoSignal might be used in analysis of a single cell RNA sequencing data set:

1. Transcription factor activation scores are calculated (we recommend using pySCENIC, but other methods can be used as well)
2. A ligand-receptor database is used to map linkages between ligands and receptors (we recommend using CellphoneDB, but other methods can be used as well).
3. A domino object is created using counts, z-scored counts, clustering information, and the data from steps 1 and 2.
4. Parameters such as the maximum number of transcription factors and receptors or the minimum correlation threshold (among others) are used to make a cell communication network
5. Communication networks can be extracted from within the domino object or visualized using a variety of plotting functions

Please see our website for an example analysis that includes all of these steps in detail, from downloading and running pySCENIC to building and visualizing domino results. Other articles include further details on plotting functions and the structure of the domino object.

Improvements

dominoSignal includes updates to domino object construction:

• Uniform formats for inputs of receptor-ligand interaction databases, transcription factor activity features, and regulon gene lists for operability with alternative databases and transcription factor activity inference methods
• Helper functions for reformatting pySCENIC outputs and CellPhoneDB database files to domino-readable uniform formats
• Assessment of transcription factor linkage with receptors that function as a heteromeric complex based on correlation between transcription factor activity and all receptor component genes
• Assessment of complex ligand expression as the mean of component gene expression for plotting functions
• Minimum threshold for the percentage of cells in a cluster expressing a receptor gene for the receptor to be called active within the cluster
• Additional linkage slots for active receptors in each cluster, transcription factor-receptor linkages for each cluster, and incoming ligands to each cluster, while transcription factor-target linkages are now properly stored so that receptors in a transcription factor's regulon are excluded from linkage

Additionally, changes have been made to improve plotting functionality:

• Chord plot of ligand expression targeting a specified receptor where chord widths correspond to the quantity of ligand expression by each cell cluster
• Signaling networks showing only outgoing signaling from specified cell clusters
• Gene networks between two cell clusters
• Ligand nodes sizes in gene networks correspond to quantity of ligand expression

Some new features have been introduced:

• Addition of new class to summarize linkages in objects
• Addition of helper functions to count linkages and compare between objects
• Plotting function for differential linkages

Lastly, the package is being updated to ensure it conforms to BioConductor standards.

Accessing the Original Domino Package

Code used in the version of Domino published in 2021 has been uploaded to Zenodo and is also released here as domino v1.0.0. Again, $\textcolor{orange}{\textsf{please note that this repository is no longer being actively maintained.}}$ To ask questions, report issues, and access new features, please view the dominoSignal repository.

Citation

If you use our package in your analysis, please cite us:

Cherry C, Maestas DR, Han J, Andorko JI, Cahan P, Fertig EJ, Garmire LX, Elisseeff JH. Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics. Nat Biomed Eng. 2021 Oct;5(10):1228-1238. doi: 10.1038/s41551-021-00770-5. Epub 2021 Aug 2. PMID: 34341534; PMCID: PMC9894531.

Cherry C, Mitchell J, Nagaraj S, Krishnan K, Fertig E, Elisseeff J (2024). dominoSignal: Cell Communication Analysis for Single Cell RNA Sequencing. R package version 0.99.0.

Contact Us

If you find any bugs, have questions, or want to contribute, please let us know here.