SPACEc: a streamlined, interactive Python workflow for multiplexed image processing and analysis
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.
Authors
- Michael Hölzel (ORCID: https://orcid.org/0000-0003-4048-8824)
- Rong Fan (ORCID: https://orcid.org/0000-0001-7805-8059)
- Garry P. Nolan (ORCID: https://orcid.org/0000-0002-8862-9043)
- Yuqi Tan (ORCID: https://orcid.org/0000-0002-7200-3222)
- Andrew J. Rech (ORCID: https://orcid.org/0000-0002-6585-8839)
- John W. Hickey (ORCID: https://orcid.org/0000-0001-9961-7673)
- Martin Becker (ORCID: https://orcid.org/0000-0003-4296-3481)
- Graham Su (ORCID: https://orcid.org/0000-0002-4170-0180)
- Marieta Toma (ORCID: https://orcid.org/0000-0002-4803-3712)
- Jiaqi Liu (ORCID: https://orcid.org/0009-0009-1878-8258)
- Maximilian Haist (ORCID: https://orcid.org/0000-0002-6720-7570)
- Dorien Feyaerts (ORCID: https://orcid.org/0000-0002-0795-6625)
- Yang Xiao (ORCID: https://orcid.org/0000-0001-7878-4923)
- Tim Kempchen (ORCID: https://orcid.org/0009-0007-0173-2026)
Institutions
- University of Bonn (DE)
- Philipps University of Marburg (DE)
- Duke University (US)
- University of Michigan (US)
- University Hospital Bonn (DE)
- Yale Cancer Center (US)
- Yale University (US)
- Stanford Medicine (US)
- University of Rostock (DE)
- Columbia University (US)
- University of Pennsylvania (US)
- Stanford University (US)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1038/s41467-025-65658-3
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- Bill and Melinda Gates Foundation
- Cancer Research Institute
- Celgene
- Kenneth Rainin Foundation
- Parker Institute for Cancer Immunotherapy
- Cancer Research UK
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung
- Deutsche Krebshilfe
- Hamilton Health Sciences Foundation
- National Institutes of Health
- University of Texas MD Anderson Cancer Center
- Defence Science and Technology Laboratory
- Stanford Cancer Institute
- Stanford Maternal and Child Health Research Institute