Spatial pattern enhanced cellular and tissue recognition for spatial transcriptomics

Spatially mapping the cellular positions and their microenvironments with spatial transcriptomics (ST) shows great potential to illustrate key factors and mechanisms driving complex tissue organizations. The spatial data requires specialized handling with different statistical and inferential considerations. Here, we develop SPECTRUM (Spatial Pattern Enhanced Cellular and Tissue Recognition Unified Method), which combines inclusive prior known cell-type specific markers and spatial weighting for cell-type identification and spatial community detection. Comprehensive benchmarks demonstrate the superior performance of SPECTRUM. Here we provide source code and simulated datasets used in manuscript "Spatial pattern enhanced cellular and tissue recognition for spatial transcriptomics".