GRIDGENE (Guided Region Identification based on Density of GENEs) is a Python package designed for defining
regions of interest based on transcript density. It enables the identification of biologically relevant tissue compartments, including interfaces between regions
(e.g., cancer vs. stroma), phenotype-enriched areas, and zones defined by specific gene signatures.
- Generate masks and expansions for spatial transcriptomics based on density of genes
- Contour identification
- Tissue mask mapping and expansion
- Mask information retrieval
- Cell segmentation overlay
General view:
GRIDGENE contains the following Case Studies:
- tumor microenvironment analysis
- Definition of population-specific objects in CRC in CosMx (single and multiclass)
- Integration with cell segmentation pipelines
- Alternative masking strategies using KD-Trees and Self-Organizing Maps (SOM)
Documentation is available at GRIDGENE Documentation.
If you find this repository useful in your research or for educational purposes please refer to: Sequeira, A. M., Ijsselsteijn, M., Rocha, M., Roelands, J., & de Miranda, N. F. (2025). GRIDGENE: Guided Region Identification based on Density of GENEs-a transcript density-based approach to characterize tissues by spatial transcriptomics. bioRxiv, 2025-08. https://doi.org/10.1101/2025.08.14.670318
Developed at the Leiden University Medical Centre, The Netherlands and Centre of Biological Engineering, University of Minho, Portugal
Released under the GNU Public License (version 3.0).