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  "Title": "Cell-Density Correlated Genes from Spatial Transcriptomics",
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  "Description": "Quantifies the dependence between local cell density and\ngene expression in single-cell resolution spatial\ntranscriptomics data, such as data from the Xenium and MERFISH\nplatforms. Cell locations form a point pattern and gene counts\nare its marks. After aggregation on a regular grid, cell counts\nand summed expression follow Poisson models driven by two\ncoregionalized latent Gaussian fields with Matern covariance,\napproximated by Hilbert space basis functions; the correlation\nbetween the two fields measures the density-expression\ndependence. Models are fitted with 'Stan' through 'cmdstanr'.\nFunctions cover the tissue boundary (an alpha shape of the\ncells), gridding, model fitting, posterior summaries,\nlatent-field decomposition, spatial correlation ranges, and\ngene scans that call density-correlated genes.",
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