SPRI: Spatial Pattern Recognition using Information based method for spatial gene expression data

The rapid development of spatially resolved transcriptomics has made it possible to analyze spatial gene expression patterns in complex biological tissues. To identify such genes, we propose a novel and robust nonparametric information-based approach, SPRI, to recognize their spatial patterns. SPRI directly models spatial transcriptome raw count data without model assumptions, which transforms the problem of spatial expression pattern recognition into the detection of dependencies between spatial coordinate pairs with gene read count as the observed frequencies. SPRI was used to analyze four recent published spatially resolved transcriptome data, and all results showed that SPRI outperforms prior methods, by robustly detecting more genes with significant spatial expression patterns, and revealing biological insights that cannot be identified by other methods.