SpatialTRACE extends sparse annotations into tissue-wide anatomical axis and region maps and predicts the same coordinates from DAPI images alone
The authors developed SpatialTRACE, comprising graph- and image-based models: SpatialTRACE-Graph combines gene-expression profiles with spatial neighborhoods to predict crypt-villus and epithelial-distance axis coordinates and to identify Peyer's patches in mouse small-intestine sections using as few as 10 annotated training villi, while SpatialTRACE-Image, a multiscale vision transformer that learns from the coordinate and region predictions generated by SpatialTRACE-Graph, predicts the same anatomical axis coordinates and regions across entire tissue images from DAPI alone and was applied to immunofluorescence images to map antigen-specific P14 CD8 T cells responding to acute systemic LCMV Armstrong infection in the small intestine, showing that a retinoic acid receptor inhibitor-treated