Xenium is a recently developed high-resolution spatial transcriptomics platform that enables subcellular mapping of RNA molecules across intact tissue sections. This project aims to perform large-scale data analysis of Xenium datasets generated from human and mouse samples to investigate spatial gene expression patterns in disease and development. The analyses will include image-based transcript detection, cell segmentation, gene expression quantification, clustering of cell populations, and integration with single-cell RNA-seq reference atlases. By leveraging national compute resources, we will process multi-terabyte raw datasets into cell-resolved expression matrices and perform computationally intensive downstream analyses such as spatial differential expression, ligand-receptor interaction inference, and multi-modal integration with histopathology images. The expected outcomes are high-resolution maps of cell types and their spatial interactions, providing novel insights into tissue organization and pathology. This project is conducted at Stockholm University and SciLifeLab, and it will directly support collaborative research in molecular medicine, cancer biology, and translational pathology. The analyses require significant compute and storage resources due to the size and complexity of Xenium data, and the results will be disseminated through peer-reviewed publications and open-access data repositories, in line with FAIR data principles.