ArticleNature methods2024
FICTURE: scalable segmentation-free analysis of submicron-resolution spatial transcriptomics.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed.
- SpatialZoomer: multi-scale feature analysis of spatial transcriptomics.Nature biomedical engineering · 2026Article
- Resolving cell-cell interaction networks and their molecular logic in complex tissues.Nature methods · 2026Article
- Kintsugi decides, gene by gene, where spatial transcriptomics borrows information.bioRxiv : the preprint server for biology · 2026Article
- Standardized metrics for assessment and reproducibility of imaging-based spatial transcriptomics datasets.Nature biotechnology · 2026Article
- Imaging-Based Spatial Transcriptomics: Data Interpretation Methods and Biomedical Applications.Biology · 2026Review
- Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders.bioRxiv : the preprint server for biology · 2026Article
- Accurate, scalable and cross-platform cell identification for high-resolution spatial transcriptomics.Nature genetics · 2026Article
- A transcriptomic-driven segmentation and cell simulation framework for high-resolution spatial transcriptomics and cell-cell communication.bioRxiv : the preprint server for biology · 2026Article
- RESCUE: recovery of unattributed expression patterns in spatial transcriptomics.Nature communications · 2026Article
- SM3DD with segmented PCA: a comprehensive method for interpreting 3D spatial transcriptomics.NAR genomics and bioinformatics · 2026Article
- An integrative spatial multi-omic workflow for unified analysis of tumor tissue.Cell reports methods · 2026Article
- Seq-Scope-eXpanded: spatial omics beyond optical resolution.Nature communications · 2026Article
- Expansion omics: from expansion microscopy to spatial omics.Molecular systems biology · 2026Review
- Spatial architecture of development and disease.Nature reviews. Genetics · 2026Review
- Advances in Spatial Transcriptomics in Bone.Current osteoporosis reports · 2026Review
- SpatialRNA: a Python package for easy application of Graph Neural Network models on single-molecule spatial transcriptomics dataset.Bioinformatics (Oxford, England) · 2026Article
- GRIDGENE: Guided Region Identification based on Density of GENEs-a transcript density-based approach to characterize tissues by spatial transcriptomics.Bioinformatics advances · 2026Article
- Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- A complete spatial map of mouse retinal ganglion cells reveals density and gene expression specializations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- MisTIC: Missegmented Transcript Inference Correction for Improved Spatial Transcriptomics Analysis.bioRxiv : the preprint server for biology · 2025Article
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Abstract
Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. However, analysis of high-resolution ST is often challenged by complex tissue structure, where existing cell segmentation methods struggle due to the irregular cell sizes and shapes, and by the absence of segmentation-free methods scalable to whole-transcriptome analysis. Here we present FICTURE (Factor Inference of Cartographic Transcriptome at Ultra-high REsolution), a segmentation-free spatial factorization method that can handle transcriptome-wide data labeled with billions of submicron-resolution spatial coordinates and is compatible with both sequencing-based and imaging-based ST data. FICTURE uses the multilayered Dirichlet model for stochastic variational inference of pixel-level spatial factors, and is orders of magnitude more efficient than existing methods. FICTURE reveals the microscopic ST architecture for challenging tissues, such as vascular, fibrotic, muscular and lipid-laden areas in real data where previous methods failed. FICTURE's cross-platform generality, scalability and precision make it a powerful tool for exploring high-resolution ST.
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