MIMYR: Generative modeling of missing tissue in spatial transcriptomics.

ABSTRACT: Spatial transcriptomics enables the study of how gene expression is organized across tissues, revealing how cells interact within their native microenvironments in health and disease. However, tissue damage during sectioning and the allocation of intermediate slices to other assays often result in regions or entire planes missing from the data, limiting downstream analysis. Here, we introduce MIMYR, a generative framework for reconstructing realistic spatial transcriptomics data in unmeasured tissue regions. MIMYR addresses this challenge through three coupled components: predicting cell locations via guided diffusion, assigning cell types through supervised classification, and generating gene expression profiles with a transformer conditioned on spatial and cellular context. MIMYR accurat

SUBMITTER: Deshpande A 

PROVIDER: S-EPMC12697367 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature