ArticleNature communications2022
De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution.
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 48 papers.
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Who cites it
48 citing papers in PubMed.
- Biologically-informed integration of drug representations for breast cancer treatment using deep learning.Nature communications · 2025Trial
- Toward simultaneous pseudo-space reconstruction and cell-type deconvolution of single-cell spatial transcriptome using SpaDicer.Cell reports methods · 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
- Integrating single-cell and single-nucleus datasets improves bulk RNA-seq deconvolution.Cell reports methods · 2026Article
- ZBED6-IGF2-PIK3C3 autophagy axis drives ccRCC progression: A multi-omics integration study.iScience · 2026Article
- Unravelling the progression of the zebrafish primary body axis with reconstructed spatiotemporal transcriptomics.Genome biology · 2026Article
- A diagnostic signature derived from NK cell related genes in prostate cancer: insights from integrated scRNA-seq and bulk RNA-seq analyses with functional validation of KIT.Frontiers in immunology · 2026Article
- Single-cell sequencing and organoids: applications in organ development and disease.Molecular biomedicine · 2025Review
- Cell-type deconvolution methods for spatial transcriptomics.Nature reviews. Genetics · 2025Review
- Insulin use promotes pro-inflammatory changes in the transcriptome of atherosclerotic plaques in patients with diabetes mellitus.Journal of molecular and cellular cardiology plus · 2025Article
- Inference of cell-type composition and single-cell spatial maps from spatial transcriptomics data with SWOT.Communications biology · 2025Article
- Comprehensive analysis of single-cell and bulk RNA sequencing uncover tumor microenvironment diversity in invasive Retinoblastoma.Scientific reports · 2025Article
- Unveiling tissue heterogeneity through genomic interaction-encoded image representation of RNA-sequencing data.American journal of human genetics · 2025Article
- A bottom-up septal inhibitory circuit mediates anticipatory control of drinking.Nature neuroscience · 2025Article
- Progress and applications of single-cell RNA sequencing and spatial transcriptome technology in acute kidney injury research.Molecular therapy. Nucleic acids · 2025Review
- Integrating bulk and single-cell RNA sequencing reveals intratumor heterogeneity phenotypes and immune infiltration in pancreatic cancer.Discover oncology · 2025Article
- Application of single-cell and spatial omics in deciphering cellular hallmarks of cancer drug response and resistance.Journal of hematology & oncology · 2025Review
- HDAC9-mediated deacetylation of CALML6 promotes excessive proliferation of glomerular mesangial cells in IgA nephropathy.Clinical and experimental nephrology · 2025Article
- Panoramic spatial enhanced resolution proteomics (PSERP) reveals tumor architecture and heterogeneity in gliomas.Journal of hematology & oncology · 2025Article
- Mature tertiary lymphoid structures evoke intra-tumoral T and B cell responses via progenitor exhausted CD4Nature communications · 2025Article
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Uncovering the tissue molecular architecture at single-cell resolution could help better understand organisms' biological and pathological processes. However, bulk RNA-seq can only measure gene expression in cell mixtures, without revealing the transcriptional heterogeneity and spatial patterns of single cells. Herein, we introduce Bulk2Space ( https://github.com/ZJUFanLab/bulk2space ), a deep learning framework-based spatial deconvolution algorithm that can simultaneously disclose the spatial and cellular heterogeneity of bulk RNA-seq data using existing single-cell and spatial transcriptomics references. The use of bulk transcriptomics to validate Bulk2Space unveils, in particular, the spatial variance of immune cells in different tumor regions, the molecular and spatial heterogeneity of tissues during inflammation-induced tumorigenesis, and spatial patterns of novel genes in different cell types. Moreover, Bulk2Space is utilized to perform spatial deconvolution analysis on bulk transcriptome data from two different mouse brain regions derived from our in-house developed sequencing approach termed Spatial-seq. We have not only reconstructed the hierarchical structure of the mouse isocortex but also further annotated cell types that were not identified by original methods in the mouse hypothalamus.
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