Spatial transcriptomics has enabled the study of mRNA distributions within cells, a key aspect of cellular function. However, there is a dearth of tools that can identify and interpret functionally relevant spatial patterns of subcellular transcript distribution. To address this, we present CellSP, a computational framework for identifying, visualizing, and characterizing consistent subcellular spatial patterns of mRNA. CellSP introduces the concept of "gene-cell modules", which are gene sets with non-random subcellular transcript distributions in many cells. It provides intuitive visualizations of the captured patterns and offers functional insights into each discovered module. We demonstrate that CellSP reliably identifies functionally significant modules across diverse tissues and technologies. We use the tool to discover subcellular spatial phenomena related to myelination, axonogenesis and synapse formation in the mouse brain. We find immune response-related modules that change between kidney cancer and healthy samples, and myelination-related modules specific to mouse models of Alzheimer's Disease.