ArticleNature methods2019
Cell composition analysis of bulk genomics using single-cell data.
Article in Nature methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
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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.
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Who cites it
71 citing papers in PubMed.
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- HistoMap: Reconstructing Spatially Resolved Single-Cell Profiles from Bulk RNA-Seq to Decipher the Immune-Excluded Microenvironment in Colon Cancer.International journal of molecular sciences · 2026Article
- TENT5C extends Odf1 poly(A) tail to sustain sperm morphogenesis and fertility.Nature communications · 2026Article
- Evaluating reference-mixture matching in cell-type deconvolution with single-cell RNA-seq references.Briefings in bioinformatics · 2026Article
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- omnideconv: a unifying framework for using and benchmarking single-cell-informed deconvolution of bulk RNA-seq data.Genome biology · 2026Article
- Multi-Scale Transcriptomics Redefining the Tumor Immune Microenvironment.Biotech (Basel (Switzerland)) · 2026Review
- Non-negative matrix factorization and deconvolution as a dual simplex problem.Genome biology · 2026Article
- Assessing differential cell composition in single-cell studies using voomCLR.Bioinformatics (Oxford, England) · 2026Article
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Article
- Leveraging Multi-omics to Disentangle the Complexity of Ovarian Cancer.Molecular diagnosis & therapy · 2025Review
- BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk.PLoS computational biology · 2025Article
- Deep learning based deconvolution methods: A systematic review.Computational and structural biotechnology journal · 2025Review
- Considerations for building and using integrated single-cell atlases.Nature methods · 2025Review
- Alleviating batch effects in cell type deconvolution with SCCAF-D.Nature communications · 2024Article
- Virtual tissue expression analysis.Bioinformatics (Oxford, England) · 2024Article
- Cell-type deconvolution for bulk RNA-seq data using single-cell reference: a comparative analysis and recommendation guideline.Briefings in bioinformatics · 2024Article
- Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data.Cell reports methods · 2024Article
- Age, sex, and cell type-resolved hypothalamic gene expression across the pubertal transition in mice.Biology of sex differences · 2024Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) is a rich resource of cellular heterogeneity, opening new avenues in the study of complex tissues. We introduce Cell Population Mapping (CPM), a deconvolution algorithm in which reference scRNA-seq profiles are leveraged to infer the composition of cell types and states from bulk transcriptome data ('scBio' CRAN R-package). Analysis of individual variations in lungs of influenza-virus-infected mice reveals that the relationship between cell abundance and clinical symptoms is a cell-state-specific property that varies gradually along the continuum of cell-activation states. The gradual change is confirmed in subsequent experiments and is further explained by a mathematical model in which clinical outcomes relate to cell-state dynamics along the activation process. Our results demonstrate the power of CPM in reconstructing the continuous spectrum of cell states within heterogeneous tissues.
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Registered trials
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.