ArticleScientific reports2024
Dissecting glial scar formation by spatial point pattern and topological data analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Spatial statistics and point pattern analysis reveal lifespan trajectories of microglial density and clustering in the primate hippocampus.Scientific reports · 2026Article
- Screening Biomarkers for Nerve Injury Using Weighted Gene Co-Expression Network Analysis and Machine Learning.Brain and behavior · 2026Article
- Topological data analysis of pattern formation of human induced pluripotent stem cell colonies.Scientific reports · 2025Article
- Unbiased quantification of the spatial distribution of murine cells using point pattern analysis.STAR protocols · 2024Article
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Authors and funding
3 authors.
Funding
Abstract
Glial scar formation represents a fundamental response to central nervous system (CNS) injuries. It is mainly characterized by a well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial scar formation have been extensively studied, yet quantitative descriptors of the spatial arrangement of reactive glial cells remain limited. Here, we present a novel approach using point pattern analysis (PPA) and topological data analysis (TDA) to quantify spatial patterns of reactive glial cells after experimental ischemic stroke in mice. We provide open and reproducible tools using R and Julia to quantify spatial intensity, cell covariance and conditional distribution, cell-to-cell interactions, and short/long-scale arrangement, which collectively disentangle the arrangement patterns of the glial scar. This approach unravels a substantial divergence in the distribution of GFAP
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