ArticleNature communications2025
Thor: a platform for cell-level investigation of spatial transcriptomics and histology.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Review
- ConMIL: interactive and contrastive text-guided multiple instance learning for whole slide image classification.Bioinformatics (Oxford, England) · 2026Article
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Histopathology-centered computational evolution of spatial omics: integration, mapping, and foundation models.Briefings in bioinformatics · 2026Review
- Subcellular mRNA localization patterns across tissues resolved with spatial transcriptomics.Nature communications · 2026Article
- SpatialDG: a novel spatial domain identification method for spatially resolved transcriptomics data based on dual-graph neural network.Briefings in bioinformatics · 2026Article
- Spotting a unicorn: spatial transcriptome analysis of the eyelid reveals gene regulatory networks enriched in Moll glands.Briefings in bioinformatics · 2026Article
- Decoding cardiac homeostasis and injury: the evolving landscape of spatial transcriptomics.Frontiers in cell and developmental biology · 2026Review
- Advances in single-cell transcriptomic sequencing in hepatic echinococcosis.Frontiers in immunology · 2026Review
- Perspective on the integration of radiomics and spatial omics in the analysis of the tumor microenvironment of bladder cancer and prospects for precision diagnosis and treatment.Frontiers in immunology · 2026Review
- Biomaterials targeting senescent cells for bone regeneration: State-of-the-art and future perspectives.Bioactive materials · 2025Review
- Immune snapshots along the inflammation-to-cancer road in bladder urothelium.Frontiers in immunology · 2025Review
- Integrating spatial omics with routine haematoxylin and eosin in formalin-fixed paraffin-embedded: a step-by-step clinical workflow.F1000Research · 2025Review
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18 authors.
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Abstract
Spatial transcriptomics links gene expression with tissue morphology, however, current tools often prioritize genomic analysis, lacking integrated image interpretation. To address this, we present Thor, a comprehensive platform for cell-level analysis of spatial transcriptomics and histological images. Thor employs an anti-shrinking Markov diffusion method to infer single-cell spatial transcriptome from spot-level data, effectively combining gene expression and cell morphology. The platform includes 10 modular tools for genomic and image-based analysis, and is paired with Mjolnir, a web-based interface for interactive exploration of gigapixel images. Thor is validated on simulated data and multiple spatial platforms (ISH, MERFISH, Xenium, Stereo-seq). Thor characterizes regenerative signatures in heart failure, screens breast cancer hallmarks, resolves fine layers in mouse olfactory bulb, and annotates fibrotic heart tissue. In high-resolution Visium HD data, it enhances spatial gene patterns aligned with histology. By bridging transcriptomic and histological analysis, Thor enables holistic tissue interpretation in spatial biology.
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