Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal

Date:	February 28, 2026
PMID:	https://pmc.ncbi.nlm.nih.gov/articles/PMC12998610/
Category:	N/A
Authors:	Jacob T Mitchell, Orian Stapleton, Kavita Krishnan, Sushma Nagaraj, Dmitrijs Lvovs, Christopher Cherry, Amanda Poissonnier, Wesley Horton, Andrew Adey, Varun Rao, Amanda Huff, Jacquelyn W Zimmerman, Luciane T Kagohara, Neeha Zaidi, Lisa M Coussens, Elizabeth M Jaffee, Jennifer H Elisseeff , Elana J Fertig
Abstract:

Motivation: Algorithms for ligand-receptor network inference have emerged as commonly used tools to estimate cell-cell communication from reference single-cell data. Many studies employ these algorithms to compare signaling between conditions and lack methods to statistically identify signals that are significantly different. We previously developed the cell communication inference algorithm Domino, which considers ligand and receptor gene expression in association with downstream transcription factor activity scoring. We developed the dominoSignal software to innovate upon Domino and extend its functionality to test statistically differential cellular signaling.

Results: This new functionality includes the compilation of active signals as linkages from multiple subjects in a single-cell data set and testing condition-dependent signaling linkage. The software is applicable for analysis of single-cell data sets with multiple subjects as biological replicates as well as with bootstrapped replicates from data sets with few or pooled subjects. We use simulation studies to benchmark the number of subjects in compared groups and cells within an annotated cell type sufficient to accurately identify differential linkages. We demonstrate the application of the Differential Cell Signaling Test (DCST) in the dominoSignal software to investigate consequences of cancer cell phenotypes and immunotherapy on cell-cell communication in tumor microenvironments. These applications in cancer studies demonstrate the ability of differential cell signaling analysis to infer changes to cell communication networks from therapeutic or experimental perturbations, which is broadly applicable across biological systems.

Availability: dominoSignal is available through Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/dominoSignal.html.

---

Acknowledgements:

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, or the National Institute of Health.

The Translational and Basic Science Research in Early Lesions (TBEL) Research Consortia is supported and funded by grants from the National Cancer Institute and the National Institutes of Health under the following award numbers:

Project Number:	Awardee Organization
U54CA274374	Fred Hutchinson Cancer Center
U54CA274375	Houston Methodist Research Institute
U54CA274370	Johns Hopkins University
U54CA274371	UT MD Anderson Cancer Center
U54CA274367	Vanderbilt University Medical Center