SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks

Authors

Buker, I. E., Ni, Y., Hicks, S. C., Kang, J., Acharyya, S.

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.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 06 Sep 2026.

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