stEDGE 1.1.2

Edge-guided multiscale reconstruction of hierarchical spatial domains and transition interfaces in spatial transcriptomics

stEDGE

stEDGE is an edge-guided and interpretable framework for reconstructing multiscale tissue architecture from spatial transcriptomics data.

stEDGE models local boundary probability and domain transition intensity to identify stable compartments, transition-rich interfaces, and hierarchical spatial states.

Installation

Install stEDGE from PyPI:

pip install stEDGE

Documentation

Online documentation and tutorials are available at:

https://stedge-tutorials.readthedocs.io/en/latest/

The source code is available at:

https://github.com/yihe-csu/stEDGE

The tutorial source repository is available at:

https://github.com/yihe-csu/stEDGE_Tutorials

Main features

• Edge-guided reconstruction of fine-grained spatial domains
• Boundary probability and transition interface analysis
• Multiscale hierarchy construction across fine, domain, and coarse levels
• Tree-guided spatial gene program interpretation
• Applications to Visium, Slide-seqV2, Xenium, and other spatial transcriptomics data

Citation

If you use stEDGE in your work, please cite:

He, Y. stEDGE enables edge-guided multiscale reconstruction of hierarchical spatial domains and transition interfaces in spatial transcriptomics. 2026.

Citation information will be updated upon publication.