High Purity Differential Expression of Genes across Spatial Domains

Spatial transcriptomics maps gene expression within tissue architecture, offering deep insights into cellular function. A key yet overlooked phenomenon is the systematic imbalance in gene regulation within spatial domains, contrasting with traditional analyses. We define and validate this as a prevalent hallmark—High-Purity Differential Expression (HiP-DEP)—where genes in a domain shift predominantly in one direction (i.e., predominantly up- or downregulated). We introduce a Spatial Purity index to quantify it. Analysis of 190 diverse datasets across diverse tissues, diseases, and technologies revealed that spatial domains possess significantly higher purity than conventional bulk ( p = 5.4 × 10 ^{− 11} ) or single-cell data ( p = 6.9 × 10 ^{− 14} ), establishing HiP- DEP as a core hallmark of spatial biology. Using our HiP-DEP framework, we show its utility in: decoding core oncogenic regulation and its spatial gradient in breast cancer; uncovering hidden phenotypic divergence between morphologically similar Alzheimer’s plaques; and identifying active cellular communication niches in normal brain tissue. By shifting focus from individual genes to coordinated transcriptional programs, HiP-DEP provides a new paradigm for precision spatial omics analysis.