Faculty, Staff and Student Publications

Authors

    Language

    English

    Publication Date

    6-1-2026

    Journal

    Nature Genetics

    DOI

    10.1038/s41588-026-02624-9

    PMID

    42271087

    PMCID

    PMC13263138

    PubMedCentral® Posted Date

    6-10-2026

    PubMedCentral® Full Text Version

    Post-print

    Abstract

    Cells communicate through ligand-receptor (LR) signaling interactions, but identifying when and where these interactions are active remains challenging. We developed CytoSignal to infer the locations and dynamics of cell-cell communication at cellular resolution from spatial transcriptomic data. Here we show that our cellular resolution, spatially resolved signaling scores enable several important analyses-identifying spatial gradients in signaling strength, quantifying the locations of contact-dependent and diffusible interactions, detecting signaling-associated genes and identifying differential signaling across multisample data. Additionally, we can predict the temporal dynamics of a signaling interaction at each spatial location. We experimentally validate our results in situ by proximity ligation assay, confirming that CytoSignal predicts the locations of LR interactions more accurately than previous approaches. This study addresses the field's current need for a robust and scalable tool to detect cell-cell signaling interactions and their dynamics at cellular resolution from spatial transcriptomic data.

    Keywords

    Animals, Humans, Cell Communication, Ligands, Signal Transduction, Spatial Transcriptomics, Transcriptome, Computational biology and bioinformatics, Organogenesis

    Published Open-Access

    yes

    Included in

    Dentistry Commons

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