CellGPS reveals multiscale tissue architecture through radius-free distance hierarchies in spatial omics
Abstract
CellGPS is a standalone Windows application for revealing multiscale tissue architecture from spatial omics data through radius-free distance hierarchies. It represents each spatial population by directed nearest-neighbour distance profiles, applies hierarchical clustering to these profiles, and derives dendrogram-based summaries including StructureMap visualizations and the Spatial Separation Score (SSS). The workflow supports both cell-type and single-transcript analyses without requiring a user-defined spatial radius or neighbourhood cutoff. Transcript-level analysis can be performed without cell segmentation. The graphical interface provides a no-code workflow for loading spatial omics data, running the analysis, and exporting interpretable figures and tables. This Zenodo record contains the CellGPS Windows executable and its build-and-run guide. The associated manuscript is "CellGPS reveals multiscale tissue architecture through radius-free distance hierarchies in spatial omics." Authors: Mengping Long; Taobo Hu; Alexandros Sountoulidis; Christos Samakovlis; Mats Nilsson. Correspondence: Mengping Long, mengping.long@scilifelab.se; Taobo Hu, taobo.hu@scilifelab.se; Mats Nilsson, mats.nilsson@scilifelab.se. Mengping Long and Taobo Hu contributed equally to this work. Source code and documentation: https://github.com/hutaobo/Cell-GPS For research use. Please cite this Zenodo record and the associated manuscript when using the software.
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 April 2026