Mapping cellular interactions from spatially resolved transcriptomics data
- PMID: 39227721
- DOI: 10.1038/s41592-024-02408-1
Mapping cellular interactions from spatially resolved transcriptomics data
Abstract
Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently through the introduction of spatially resolved transcriptomics (SRT) technologies, especially those that achieve single-cell resolution. Nevertheless, substantial challenges remain to analyze such highly complex data properly. Here, we introduce a multiple-instance learning framework, Spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight Spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates and, most importantly, the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of Spacia for three commercialized single-cell resolution SRT technologies: MERSCOPE/Vizgen, CosMx/NanoString and Xenium/10x. Overall, Spacia represents a notable step in advancing quantitative theories of cellular communications.
© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.
Update of
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Mapping Cellular Interactions from Spatially Resolved Transcriptomics Data.bioRxiv [Preprint]. 2024 Jan 25:2023.09.18.558298. doi: 10.1101/2023.09.18.558298. bioRxiv. 2024. Update in: Nat Methods. 2024 Oct;21(10):1830-1842. doi: 10.1038/s41592-024-02408-1. PMID: 37781617 Free PMC article. Updated. Preprint.
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- RC2DK129994/U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01CA258584/U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- RP230363/Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas)
- RR220024/Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas)
- R01DK135535/U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01 AI190103/AI/NIAID NIH HHS/United States
- RP190208/Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas)
- RR170061/Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas)
- R01CA255064/U.S. Department of Health & Human Services | National Institutes of Health (NIH)
- R01 CA258584/CA/NCI NIH HHS/United States
- P50 CA070907/CA/NCI NIH HHS/United States
- R01DK115477/U.S. Department of Health & Human Services | National Institutes of Health (NIH)
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