Spatial Dependence and Heterogeneity in Molecular Imaging: Moran Quadrant Maps Enable Advanced Spatial-Statistical Analysis.

ABSTRACT: Multiplexed molecular imaging, such as imaging mass spectrometry, provides spatially-contextualized insights that are transforming biomedical research by advancing our understanding of tissue organization and disease mechanisms. However, the spatial-statistical properties of molecular imaging data are often underutilized, and scalable computational tools to analyze them are lacking. Here, we demonstrate how local and global spatial autocorrelation (SAC) metrics can be used to quantify spatial dependence and spatial heterogeneity, properties that violate the common assumption of independent and identically distributed measurements. We develop mathematically rigorous methods for SAC-based exploratory analysis. Furthermore, we introduce a novel spatial feature extractor, the Moran quadrant ma

SUBMITTER: Tideman LEM 

PROVIDER: S-EPMC12636587 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature