Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology.

ABSTRACT: Spatial transcriptomics (ST) has demonstrated enormous potential for generating intricate molecular maps of cells within tissues. Here we present iStar, a method based on hierarchical image feature extraction that integrates ST data and high-resolution histology images to predict spatial gene expression with super-resolution. Our method enhances gene expression resolution to near-single-cell levels in ST and enables gene expression prediction in tissue sections where only histology images are available.

SUBMITTER: Zhang D 

PROVIDER: S-EPMC11260191 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature