ArticleNature biotechnology2022
Robust decomposition of cell type mixtures in spatial transcriptomics.
Article in Nature biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06625203 (Multi Omics and Spatial Atlas In Cancer), which is not on this map. Cited by 949 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Multi Omics and Spatial Atlas In Cancer
Who cites it
949 citing papers in PubMed, 1,307 citations in OpenAlex.
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- Cell plasticity in cancer and therapy resistance.Experimental & molecular medicine · 2026Review
- Spatial transcriptomics reveals microenvironmental heterogeneity in osteoarthritic subchondral bone.Nature communications · 2026Article
- Hox/Meis-dependent gene-regulatory transition underlies cardiopharyngeal neural crest diversification.The EMBO journal · 2026Article
- Spatial and Single-Cell Multi-Omics Analyses of T-Cell Subsets and Interactions in Melanoma Lymph Node Metastasis.Experimental dermatology · 2026Review
- Integrated Immunological Analysis of Interactions Between CXCL13+ T Cells and LAMP3+ DC in the Immunotherapy Response of Bladder Cancer.Molecular carcinogenesis · 2026Article
- A Spatial Atlas of Muscle-Invasive Bladder Cancer Reveals Lineage-Specific Vulnerabilities and Immune Architecture.Cancer discovery · 2026Article
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- Asynchronous Evolution of Epithelium and Stroma Differentiates Precursor Lesions from Pancreatic Cancer.Cancer discovery · 2026Article
- Integrated Multi-Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Three dimensional reconstruction of the human nucleus accumbens reveals topographic organization and molecular heterogeneity of D1-islands across the anterior posterior axis.bioRxiv : the preprint server for biology · 2026Article
- Multiplatform single-cell and spatial transcriptomics reveal sex-specific malignant states and architecture in male breast cancer.Science advances · 2026Article
- Multi-omic analysis of jaw-bone periosteum identifies the role of macrophage-derived SPP1 in CtskBone research · 2026Article
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- CoexpressDeconvolve enables reference-free single-cell-resolution deconvolution from spot-based spatial transcriptomics.iScience · 2026Article
889 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
A limitation of spatial transcriptomics technologies is that individual measurements may contain contributions from multiple cells, hindering the discovery of cell-type-specific spatial patterns of localization and expression. Here, we develop robust cell type decomposition (RCTD), a computational method that leverages cell type profiles learned from single-cell RNA-seq to decompose cell type mixtures while correcting for differences across sequencing technologies. We demonstrate the ability of RCTD to detect mixtures and identify cell types on simulated datasets. Furthermore, RCTD accurately reproduces known cell type and subtype localization patterns in Slide-seq and Visium datasets of the mouse brain. Finally, we show how RCTD's recovery of cell type localization enables the discovery of genes within a cell type whose expression depends on spatial environment. Spatial mapping of cell types with RCTD enables the spatial components of cellular identity to be defined, uncovering new principles of cellular organization in biological tissue. RCTD is publicly available as an open-source R package at https://github.com/dmcable/RCTD .
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.