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Peer-reviewedCC BYNature Communications

MuSpAn: a toolbox for multiscale spatial analysis

  • Joshua A. Bull1,2
  • Joshua W. Moore3,2
  • Shania M. Corry4,2
  • Muyang Lin4,2
  • Hayley L. Belnoue-Davis4,2
  • Eoghan J. Mulholland-Illingworth4
  • Simon J. Leedham4
  • Helen Mary Byrne4,5,6
6 affiliations
  1. 1Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK. [email protected]
  2. 2University of Oxford
  3. 3Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK. [email protected]
  4. 4Centre for Human Genetics, University of Oxford, Oxford, UK
  5. 5Ludwig Institute for Cancer Research, University of Oxford, Oxford, UK
  6. 6Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK
Open at sourceDOICite

Abstract

Advances in multiplex imaging and spatial omics have revolutionised spatial data generation in biology, revealing complex tissue organisation across multiple scales. However, methods for analysing these data have lagged behind, with fragmented, study-specific pipelines and limited guidance for tool selection. To address this, we introduce MuSpAn, a Multiscale Spatial Analysis package offering intuitive, flexible access to a wide range of mathematical tools - including spatial statistics, topological data analysis, geometry, and networks - within a unified framework. MuSpAn supports efficient data querying, is agnostic to imaging modality, and provides extensive documentation and community support. It enables users to create custom pipelines or conduct unbiased exploratory analyses. We demonstrate MuSpAn's capacity to interrogate cross-compartmental cell interactions at multiple length scales in both normal and neoplastic tissue using mouse intestinal spatial transcriptomic datasets. Applied to a CMS4-like murine intestinal cancer model, MuSpAn identifies a continuum of fibroblastic functional phenotypes associated with discrete and coordinated fibroblast-immune interactions, highlighting its utility as a discovery tool across diverse biological contexts.

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Cite

BibTeXRIS
BibTeX
@article{bull2026muspan,
  title = {{MuSpAn: a toolbox for multiscale spatial analysis}},
  author = {Joshua A. Bull and Joshua W. Moore and Shania M. Corry and Muyang Lin and Hayley L. Belnoue-Davis and Eoghan J. Mulholland-Illingworth and Simon J. Leedham and Helen Mary Byrne},
  journal = {Nature Communications},
  year = {2026},
  month = aug,
  doi = {10.1038/s41467-026-75649-7},
  url = {https://doi.org/10.1038/s41467-026-75649-7},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - MuSpAn: a toolbox for multiscale spatial analysis
AU  - Joshua A. Bull
AU  - Joshua W. Moore
AU  - Shania M. Corry
AU  - Muyang Lin
AU  - Hayley L. Belnoue-Davis
AU  - Eoghan J. Mulholland-Illingworth
AU  - Simon J. Leedham
AU  - Helen Mary Byrne
PY  - 2026
DA  - 2026/08/13
JO  - Nature Communications
DO  - 10.1038/s41467-026-75649-7
UR  - https://doi.org/10.1038/s41467-026-75649-7
AB  - Advances in multiplex imaging and spatial omics have revolutionised spatial data generation in biology, revealing complex tissue organisation across multiple scales. However, methods for analysing these data have lagged behind, with fragmented, study-specific pipelines and limited guidance for tool selection. To address this, we introduce MuSpAn, a Multiscale Spatial Analysis package offering intuitive, flexible access to a wide range of mathematical tools - including spatial statistics, topological data analysis, geometry, and networks - within a unified framework. MuSpAn supports efficient data querying, is agnostic to imaging modality, and provides extensive documentation and community support. It enables users to create custom pipelines or conduct unbiased exploratory analyses. We demonstrate MuSpAn's capacity to interrogate cross-compartmental cell interactions at multiple length scales in both normal and neoplastic tissue using mouse intestinal spatial transcriptomic datasets. Applied to a CMS4-like murine intestinal cancer model, MuSpAn identifies a continuum of fibroblastic functional phenotypes associated with discrete and coordinated fibroblast-immune interactions, highlighting its utility as a discovery tool across diverse biological contexts.
SN  - 2041-1723
ER  -