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Updated: Oct 26, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
SCG: Identifying spatially co-expressed genes using spatial covariance regression
Abstract:
Spatial transcriptomics has enabled the advancement of gene expression analysis, yet spatial co-expression remains understudied. We introduce spatial covariance regression (SCR), a scalable Bayesian factor-model-based framework for estimation of spatially-resolved gene co-expression networks across tissue domains. These networks provide the spatial map of gene-gene correlations and enable the identification of spatially co-expressed genes (SCGs), which serve as potential prognostic biomarkers and therapeutic targets.
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