Yitao Yang

Dec 19, 2023 | biorxiv.org | Yitao Yang |Yang Cui |Xin Zeng |Yubo Zhang

AbstractSpatial transcriptomics is an essential application for investigating cellular structures and interactions, requiring multi-modal information to precisely study the spatial domains. Here, we propose STAIG, a novel deep-leaning model that integrates gene expression, spatial coordinates, and histological images using graph contrastive learning coupled with a high-performance feature extraction. STAIG can integrate tissue slices without pre-alignment along with removing batch effects.