ArticleNature biotechnology2025
Coordinated, multicellular patterns of transcriptional variation that stratify patient cohorts are revealed by tensor decomposition.
Article in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Article
- Interpretable multi-omics integration across mixed-order tensors with MANTRA.Molecular systems biology · 2026Article
- Assessing tensor decomposition quality of immune profiling data from a dictionary learning perspective.bioRxiv : the preprint server for biology · 2026Article
- Decoding Immune Regulation: From Genetic Variation to Mechanism Through Single-Cell Genomics.Immune network · 2026Review
- Interpretation, extrapolation and perturbation of single cells.Nature reviews. Genetics · 2026Review
- A transcriptional patient map of systemic lupus erythematosus reveals disease-related multicellular immune programs conserved between blood and kidney.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
- Single-nucleus brain transcriptomics reveals microglia dysfunction in multiple system atrophy.Nature communications · 2026Article
- Single-cell and spatial profiling in cancer biology and clinical oncology.Nature cancer · 2026Review
- Dynamic changes of the immune microenvironment in ovarian cancer following neoadjuvant chemotherapy.Cell death discovery · 2026Article
- Single-cell transcriptomics of multi-site cell therapy in osteoarthritis: Tissue-specific treatment correlations.Molecular therapy. Nucleic acids · 2026Article
- Impact and correction of segmentation errors in spatial transcriptomics.Nature genetics · 2026Article
- Impact of disease-associated chromatin accessibility QTLs across immune cell types and contexts.Cell genomics · 2026Article
- PULSAR: a Foundation Model for Multi-scale and Multi-cellular Biology.bioRxiv : the preprint server for biology · 2025Article
- Deep generative modeling of sample-level heterogeneity in single-cell genomics.Nature methods · 2025Article
- LaGrACE: estimating gene program dysregulation with latent regulatory network.Molecular systems biology · 2025Article
- New Insights and Implications of Cell-Cell Interactions in Developmental Biology.International journal of molecular sciences · 2025Review
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- Combining LIANA and Tensor-cell2cell to decipher cell-cell communication across multiple samples.Cell reports methods · 2024Article
- Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease.eLife · 2023Article
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Tissue-level and organism-level biological processes often involve the coordinated action of multiple distinct cell types. The recent application of single-cell assays to many individuals should enable the study of how donor-level variation in one cell type is linked to that in other cell types. Here we introduce a computational approach called single-cell interpretable tensor decomposition (scITD) to identify common axes of interindividual variation by considering joint expression variation across multiple cell types. scITD combines expression matrices from each cell type into a higher-order matrix and factorizes the result using the Tucker tensor decomposition. Applying scITD to single-cell RNA-sequencing data on 115 persons with lupus and 83 persons with coronavirus disease 2019, we identify patterns of coordinated cellular activity linked to disease severity and specific phenotypes, such as lupus nephritis. scITD results also implicate specific signaling pathways likely mediating coordination between cell types. Overall, scITD offers a tool for understanding the covariation of cell states across individuals, which can yield insights into the complex processes that define and stratify disease.
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