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Solovey, M.* ; Celik, M.A. ; Salcher, F. ; Gülec, C. ; Abdalfattah, M. ; Ali, M.I.H ; Heinig, M. ; Scialdone, A. ; Ziemann, F.* ; Colomé-Tatché, M.

Community: Component based differential cell communication analysis in large multi-sample case-control scRNAseq datasets.

iScience 29:117314 (2026)
Publ. Version/Full Text Research data DOI
Open Access Gold
Creative Commons Lizenzvertrag
Changes in cell-cell communication during disease can result from shifts in tissue composition, variations in the proportion of cells engaged in signaling, and differences in ligand-receptor expression. To address this, we developed community, an R package designed for differential communication analysis in multi-sample case-control scRNAseq datasets. Community reconstructs interactions by evaluating cell type abundance, the active fraction of cells, and their expression levels. This method identifies communication patterns that are upregulated, downregulated, unchanged, or compensated. Applied to ulcerative colitis, melanoma under immune checkpoint inhibitor treatment, and acute myeloid leukemia, community captured disease- and response-associated communication changes, including increased communication in ulcerative colitis, reduced immunosuppressive signaling in melanoma responders, and decreased immune communication in AML. Comparisons with existing tools showed improved robustness to outlier-driven signals and better scalability. These component-level analyses help connect altered communication patterns to biological mechanisms in healthy and disease states.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Component (thermodynamics) ; Sample (material) ; Differential (mechanical Device) ; Computer Science ; Engineering ; Chemistry ; Physics; Death
ISSN (print) / ISBN 2589-0042
e-ISSN 2589-0042
Journal iScience
Quellenangaben Volume: 29, Issue: 9, Pages: , Article Number: 117314 Supplement: ,
Publisher Elsevier
Publishing Place Amsterdam ; Bosten ; London ; New York ; Oxford ; Paris ; Philadelphia ; San Diego ; St. Louis
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Institute of Epigenetics and Stem Cells (IES)
Institiute of Functional Epigenetics (IFE)
Grants Forderprogramm fur Forschung und Lehre (FoFoLe) of LMU Munich
Bavarian Cancer Research Center (BZKF)
German Cancer Consortium (DKTK)
Forderprogramm fur Forschung und Lehre of the LMU University
MICIU/AEI
Impuls-und Vernetzungsfonds of the Helmholtz-Gemeinschaft
Helmholtz Association under the joint research school "HIDSS-006-Munich School for Data Science@- Helmholtz, TUMLMU