Spatially Resolved Gene Expression is Not Necessary for Identifying Spatial Domains

Abstract

The development of Spatially Resolved Transcriptomics (SRT) technologies has revolutionized the study of tissue organization. We introduce a graph convolutional network with an attention and positive emphasis mechanism, named "BINARY," relying exclusively on binarized SRT data to delineate spatial domains. BINARY outperforms existing methods across various SRT data types while using significantly less input information. Our study suggests that precise gene expression quantification may not always be essential, inspiring further exploration of the broader applications of spatially resolved binarized gene expression data.