{"paper_id":"29eeedad-693a-49df-9013-6e21709480e3","body_text":"Abstract\nSpatial transcriptomics measures gene expression together with transcript coordinates in tissues. To date, comparing spatial gene expression patterns within and across samples remains challenging. We present here minkiPy, a geometric framework that computes, for each gene, a compact profile of morphological and topological descriptors based on Minkowski functionals and tensors. These profiles are defined in a shared feature space, enabling direct comparison of spatial organisation across genes, samples, and conditions, and the ranking of genes by the magnitude of their spatial reorganisation. We applied minkiPy to a MERFISH dataset of control and facioscapulohumeral muscular dystrophy myoblast cultures and to a Visium HD dataset of colorectal cancer and normal adjacent tissues, illustrating its utility across tissue types and spatial transcriptomics platforms. minkiPy is an open-source Python library available at https://github.com/BAUDOTlab/minkiPy.\nCompeting Interest Statement\nThe authors have declared no competing interest.","source_license":"CC-BY-4.0","license_restricted":false}