ArticleNature communications2022
Context-aware deconvolution of cell-cell communication with Tensor-cell2cell.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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Who cites it
77 citing papers in PubMed.
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- Decoding cell-cell communication in spatial transcriptomics: mechanistic insights, modeling constraints, and analytical caveats.Briefings in bioinformatics · 2026Review
- Distinct postnatal trajectories of mouse dendritic epidermal T cells and Langerhans cells independent of microbiota.Science advances · 2026Article
- Myasthenia thymus reprograms class-switched B cells into BAFF-dependent survivors.Science advances · 2026Article
- Single-Cell RNA-Sequencing Reveals Tumor Microenvironment Composition and Prior Therapy Modulate Response to Axl Inhibition.Cellular and molecular bioengineering · 2026Article
- A single-cell atlas of porcine hematopoietic development.Nature communications · 2026Article
- Identifying condition-related cell-cell communication events using supervised tensor analysis.American journal of human genetics · 2026Article
- Unraveling the spatial landscape of dystrophinopathies: a transcriptomic approach to Becker and Duchenne muscular dystrophies.The Journal of pathology · 2026Article
- Cave adaptation drives coordinated transcriptional remodeling across diverse cell types in the brain of a teleost fish.bioRxiv : the preprint server for biology · 2026Article
- Type I Interferon-Driven Monocyte Dysregulation and MAS-associated CD8bioRxiv : the preprint server for biology · 2026Article
- Transcriptional analyses identify pericyte-centered signaling programs altered by sex and brain region in Alzheimer's Disease.Communications biology · 2026Article
- Decoding Multicellular Communication Motifs from Spatial Transcriptomics with ALARMIST.bioRxiv : the preprint server for biology · 2026Article
- Single-nucleus profiling reveals age-associated remodeling opposed by parity in the postmenopausal human ovary.bioRxiv : the preprint server for biology · 2026Article
- Tracing cell communication programs across conditions at single cell resolution with CCC-RISE.bioRxiv : the preprint server for biology · 2026Article
- Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell-cell communication.Bioinformatics (Oxford, England) · 2026Article
- Bridging cancer cell-intrinsic driver genes and -extrinsic cell-cell communication with Driver2Comm.PLoS computational biology · 2026Article
- The Role of Exosomes in Pulmonary Hypertension: Mechanisms and Therapeutic Potential.International journal of nanomedicine · 2026Review
- Inferring spatial single-cell-level interactions through interpreting cell state and niche correlations learned by self-supervised graph transformer.Nature machine intelligence · 2026Article
17 more citing papers are in PubMed but not listed here.
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7 authors.
Funding
Abstract
Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which deciphers context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand-receptor pairs) linked to severities of Coronavirus Disease 2019 and to Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.
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