GRIDGEN (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:
GRIDGEN 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 GRIDGEN Documentation.
If you find this repository useful in your research or for educational purposes please refer to:
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).