ArticleHeliyon2023
TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 47 citations in OpenAlex.
- Review
- MilliMap: interactive closed-loop analysis for spatial omics.bioRxiv : the preprint server for biology · 2026Article
- Integrating Spatial Proteogenomics in Cancer Research.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- FGFR signaling establishes spatial gradients of secretory cell identities along the airway proximal-distal axis.Nature communications · 2026Article
- Article
- SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis.Nature communications · 2025Article
- Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.Nature communications · 2025Article
- Spatiotemporal gene expression and cellular dynamics of the developing human heart.Nature genetics · 2025Article
- Article
- Surgical and Blood-Based Minimal Residual Disease in Patients with Ovarian Cancer after First-line Therapy: Clinical Outcomes and Translational Opportunities.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- Multi-omic identification of perineurial hyperplasia and lipid-associated nerve macrophages in human polyneuropathies.Nature communications · 2025Article
- Cancer therapy resistance from a spatial-omics perspective.Clinical and translational medicine · 2025Review
- High-resolution spatial transcriptomics and cell lineage analysis reveal spatiotemporal cell fate determination during craniofacial development.Nature communications · 2025Article
- Streamlining Multiplexed Tissue Image Analysis with PIPΣX: An Integrated Automated Pipeline for Image Processing and EXploration for Diverse Tissue Types.bioRxiv : the preprint server for biology · 2025Article
- Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows.Nature methods · 2025Article
- A clinical prostate biopsy dataset with undetected cancer.Scientific data · 2025Article
- ENACT: End-to-End Analysis of Visium High Definition (HD) Data.Bioinformatics (Oxford, England) · 2025Article
- Vitessce: integrative visualization of multimodal and spatially resolved single-cell data.Nature methods · 2025Article
- Advanced single-cell and spatial analysis with high-multiplex characterization of circulating tumor cells and tumor tissue in prostate cancer: Unveiling resistance mechanisms with the CoDuCo in situ assay.Biomarker research · 2024Article
- High-parametric protein maps reveal the spatial organization in early-developing human lung.Nature communications · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objectives: Spatially resolved techniques for exploring the molecular landscape of tissue samples, such as spatial transcriptomics, often result in millions of data points and images too large to view on a regular desktop computer, limiting the possibilities in visual interactive data exploration. TissUUmaps is a free, open-source browser-based tool for GPU-accelerated visualization and interactive exploration of 10 Methods: Herein we describe how TissUUmaps 3 provides instant multiresolution image viewing and can be customized, shared, and also integrated into Jupyter Notebooks. We introduce new modules where users can visualize markers and regions, explore spatial statistics, perform quantitative analyses of tissue morphology, and assess the quality of decoding in situ transcriptomics data. Results: We show that thanks to targeted optimizations the time and cost associated with interactive data exploration were reduced, enabling TissUUmaps 3 to handle the scale of today's spatial transcriptomics methods. Conclusion: TissUUmaps 3 provides significantly improved performance for large multiplex datasets as compared to previous versions. We envision TissUUmaps to contribute to broader dissemination and flexible sharing of largescale spatial omics data.
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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.