ArticleNature communications2025
Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors.
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 56 papers.
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Who cites it
56 citing papers in PubMed.
- SpatialZoomer: multi-scale feature analysis of spatial transcriptomics.Nature biomedical engineering · 2026Article
- Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.The Plant cell · 2026Review
- The dual-enhanced graph learning framework DePass allows paired data integration in single-cell and spatial multiomics.Nature cell biology · 2026Article
- Integrated scRNA-Seq and Spatial Transcriptomics Reveal CHPF and GPC1 as Markers of Cancer-Associated Fibroblast-Dominant Domains in Colorectal Cancer.Cancer medicine · 2026Article
- Fishing with two lines: a hybrid approach to spatial transcriptomics discovery.Life science alliance · 2026Article
- STAT3D as a new image-tailored Xenium-based spatial transcriptomics tool for accurately dissecting the tumor microenvironment.Nucleic acids research · 2026Article
- Kintsugi decides, gene by gene, where spatial transcriptomics borrows information.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking copy number alteration inference methods for spatial transcriptomics.Nature communications · 2026Article
- A spatial and temporal transcriptomic atlas of mouse intestinal regeneration in the jejunum.Nature communications · 2026Article
- Ten quick tips for spatial transcriptomics analysis.PLoS computational biology · 2026Review
- Multi-omics characterization of a GPRC5AJournal of translational medicine · 2026Article
- Spatial ecotype in tumor immune exclusion: from spatial architecture to therapeutic strategies.Molecular cancer · 2026Review
- From black-box prediction to transparent insight: the status quo and paradigm shift of explainable artificial intelligence in hepatocellular carcinoma research.Journal of the Egyptian National Cancer Institute · 2026Review
- Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.Nature communications · 2026Article
- Binary-SPA: a reference-free method for cell annotation in high-resolution spatial transcriptomics.Nucleic acids research · 2026Article
- PRISM: Prior-enhanced Inference for Spatial Transcriptomic Cell Type Mapping.Bioinformatics (Oxford, England) · 2026Article
- Single-cell spatial transcriptomics of formalin-fixed, paraffin-embedded biopsies reveals colitis-associated cell networks.The Journal of clinical investigation · 2026Article
- Spatial Transcriptomics for Dissecting Cellular and Molecular Heterogeneity in the Aging and Diseased Brain.International journal of molecular sciences · 2026Review
- PromptSTG: prototype-guided prompting for few-shot spatial transcriptomics annotation.Briefings in bioinformatics · 2026Article
- CD4Science (New York, N.Y.) · 2026Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. Here, we generate serial tissue sections from colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer samples for systematic evaluation. Using these uniformly processed samples, we generate spatial transcriptomics data across four high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profile proteins on tissue sections adjacent to all platforms using CODEX and perform single-cell RNA sequencing on the same samples. Leveraging manual nuclear segmentation and detailed annotations, we systematically assess each platform's performance across capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and concordance with adjacent CODEX. The uniformly generated and processed multi-omics dataset could advance computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download.
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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.