Super-resolved spatial transcriptomics by deep data fusion

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone. ispartof: NATURE BIOTECHNOLOGY vol:40 issue:4 pages:476-+ ispartof: location:United States status: published