ArticleNature communications2025
SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis.
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 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Melanoma evolution in the lymph node shapes systemic outcomes.bioRxiv : the preprint server for biology · 2026Article
- Iterative multiplex imaging cytometry for cross-species analyses of in situ tissue leukocytes.Journal of immunological methods · 2026Article
- Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data.Nature methods · 2026Article
- Spatial transcriptomics identifies immune-stromal niches associated with cancer in adult dermatomyositis.Nature communications · 2026Article
- Longitudinal spatial neutrophil profiling during ACT in murine melanoma reveals distinct lymph node infiltration patterns.NPJ systems biology and applications · 2026Article
- Review
- Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistance.bioRxiv : the preprint server for biology · 2026Article
- Lymphatic egress recycles tumor-experienced effector CD8 T cells to sustain immune surveillance.bioRxiv : the preprint server for biology · 2026Article
- Integration of spatial single-cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma.bioRxiv : the preprint server for biology · 2026Article
- Foundation cell segmentation models performance on live microscopy and spatial-omics data.bioRxiv : the preprint server for biology · 2026Article
- Lymph node colonization induces tissue remodeling via immunosuppressive fibroblast-myeloid cell niches supporting metastatic tolerance.Cancer cell · 2026Article
- Spatial immune hubs defined by conserved activated dendritic cells are remodeled by immunotherapy.bioRxiv : the preprint server for biology · 2026Article
- GLP-1 Targeting Agents Impair Chemoimmunotherapy Effectiveness in Triple-Negative Breast Cancer.Research square · 2026Article
- Graphical and interactive spatial proteomics image analysis workflow.GigaByte (Hong Kong, China) · 2026Article
- Digital immune twins and ai-integrated multi-omic biomarkers: Redefining personalized immunotherapy in non-small cell lung cancer.Iranian journal of basic medical sciences · 2026Review
- PatternExtract: A Facile, Scalable Pipeline for Point Pattern Generation from Spatial Imaging Data.Computational and structural biotechnology journal · 2026Article
- Single-cell and spatial transcriptomic profiling reveals distinct tumor microenvironment dynamics in cervical adenocarcinoma and squamous cell carcinoma.Communications biology · 2025Article
- Resolving phenotyping discordance with SPACEMAP, an integrated machine learning framework.bioRxiv : the preprint server for biology · 2025Article
- Proximity and metabolic activity proxies in the tumor microenvironment as predictors of survival in high grade serous ovarian cancer.iScience · 2025Article
- Fluid-Squid: DIY Multiplexed Imaging of Cells and Tissues.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Multiplexed imaging has transformed our ability to study tissue organization by capturing thousands of cells and molecules in their native context. However, these datasets are enormous, often comprising tens of gigabytes per image, and require complex workflows that limit their broader use. Current tools are often fragmented, inefficient, and difficult to adopt across disciplines. Here we show that SPACEc, a scalable Python platform, streamlines spatial imaging analysis from start to finish. The platform integrates image processing, cell segmentation, and data preprocessing into a single workflow, while improving computational performance through parallelization and GPU acceleration. We introduce innovative methods, including patch proximity analysis, to more accurately map local cellular neighborhoods and interactions. SPACEc also simplifies advanced approaches such as deep-learning annotation, making them accessible through an intuitive interface. By combining efficiency, accuracy, and usability, this platform enables researchers from diverse backgrounds to gain deeper insights into tissue architecture and cellular microenvironments.
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What Socratic holds
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 Socratic graph.