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

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

doi:10.64898/2026.09.01.748618

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bioRxiv · 10.64898/2026.09.01.748618

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

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

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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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Buker, I. E., Ni, Y., Hicks, S. C., Kang, J., Acharyya, S.. 2026-09-05. SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks. https://doi.org/10.64898/2026.09.01.748618

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