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.
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/dominoSignal')
Here is an overview of how dominoSignal might be used in analysis of a single cell RNA sequencing data set:
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.
dominoSignal includes updates to domino object construction:
Additionally, changes have been made to improve plotting functionality:
Some new features have been introduced:
Lastly, the package is being updated to ensure it conforms to BioConductor standards.
Domino
PackageCode 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.
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, Lvovs D, Fertig E, Elisseeff J (2024). dominoSignal: Cell Communication Analysis for Single Cell RNA Sequencing. R package version 0.99.2.
If you find any bugs, have questions, or want to contribute, please let us know here.