ArticleNature methods2025
Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Mesolens imaging in microbiology.Essays in biochemistry · 2026Review
- Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.The journal of pathology. Clinical research · 2026Article
- HisToSpatialCNV: an interpretable deep learning method predicting spatial copy number variations from histopathology images.Nature biomedical engineering · 2026Article
- Disruption of hippocampal upstream regulators of mTOR and insulin pathways in Down syndrome with Alzheimer's disease neuropathology: Preliminary observations.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Decoding Cardiac Development and Maturation at Single-Cell and Spatial Transcriptomic Resolution.Circulation research · 2026Review
- Histopathology-centered computational evolution of spatial omics: integration, mapping, and foundation models.Briefings in bioinformatics · 2026Review
- Cross-Modality Alignment of Spatial Transcriptomics, Multiplexed Imaging, and Histology with PHARAOH.Research square · 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
- Generalist biological artificial intelligence in modeling the language of life.Nature biotechnology · 2026Review
- Pixel2Gene enables histology-guided reconstruction and prediction of spatial gene expression.bioRxiv : the preprint server for biology · 2026Article
- Reconstructing multi-scale tissue spatial architecture from single-cell RNA-seq with REMAP.bioRxiv : the preprint server for biology · 2026Article
- HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics.bioRxiv : the preprint server for biology · 2026Article
- Dual-mode microfluidic immunostaining device for diagnostic biomarkers detection and tumor microenvironment evaluation.Science advances · 2026Article
- Multimodal AI in precision medicine: linking omics, imaging and clinical decisions.American journal of clinical and experimental immunology · 2026Article
- Spatial Treg niches and the therapeutic reprogramming of tumour tolerance in cancer.Frontiers in cell and developmental biology · 2026Review
- Smart spatial omics (S2-omics) optimizes region of interest selection to capture molecular heterogeneity in diverse tissues.Nature cell biology · 2025Article
- Bridging histology and spatial gene expression across scales.Nature methods · 2025Article
- Multi-modal brain data exploration software for imaging transcriptomics: A comparative evaluation and future directions.Imaging neuroscience (Cambridge, Mass.)Article
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Abstract
Recent advances in spatial transcriptomics (ST) technologies have transformed our ability to profile gene expression while preserving crucial spatial context within tissues. However, existing ST platforms are constrained by high costs, long turnaround times, low resolution, limited gene coverage and inherently small tissue capture areas, which hinder their broad applications. Here we present iSCALE, a method that reconstructs large-scale, super-resolution gene expression landscapes and automatically annotates cellular-level tissue architecture in samples exceeding capture areas of current ST platforms. The performance of iSCALE was assessed by comprehensive evaluations involving benchmarking experiments, immunohistochemistry staining and manual annotations by pathologists. When applied to multiple sclerosis human brain samples, iSCALE uncovered lesion-associated cellular characteristics undetectable by conventional ST experiments. Our results demonstrate the utility of iSCALE in analyzing large tissues by enabling unbiased annotation, resolving cell type composition, mapping cellular microenvironments and revealing spatial features beyond the reach of standard ST analysis or routine histopathological assessment.
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