## Data repository This repository contains data associated with the research article "Dissecting glial scar formation by spatial point pattern and topological data analysis" published in XXXX. This repository was created and organized by Daniel Manrique-Castano ( https://orcid.org/0000-0002-1912-1764), postdoctoral fellow at the Laboratory of Neurovascular Interactions (Director Dr. Ayman ElAli) at Université Laval, Québec Canada. Article preprint: https://doi.org/10.1101/2023.10.04.560910 The user can find the following material: 1. GitHub repository, containing the files associated with the computation of results. This folder maps the linked GitHub account. We recommend the user to check directly the repository. 2. **Article figures:** This folder contains the images prepared for the scientific publication. It contains as well the .svg source file created in Inkscape to design the figure pannels. 2. **Bayesian Models:** The `2022_GlialTopology_Notebook.qmd` file available in the GitHub repository performs the computations of Bayesian statistical models that are saved as .rds objects for further analysis or reuse in other modeling contexts. 3. **Cell Coordinates:** It contains the coordinates extracted from individual cells/objects. These analysis was performed using QuPath (https://qupath.github.io/). Please accces this Zenodo repository (10.5281/zenodo.8399976) to obtain the complete Raw imges and QuPath projects for full reproducibility of this step. 4. **Hyperframes:** This folder comprises the `.rds` hyperframes storing the collection of point patterns used in the current research. This objects can be download and reused for further analysis or education purposes. 5. **Raw Data**: A collection of `.csv` files used to perform the analysis presented in the research article. The `2022_GlialTopology_Notebook.qmd` file depicts the data handling and analysis.