SpaceXpipeline The SpaceX (spatially dependent gene co-expression network) is a Bayesian methodology to identify both shared and cluster-specific co-expression network across genes. These clusters can be cell type specific or based on spatial regions. SpaceX uses an over-dispersed spatial Poisson model coupled with a high-dimensional factor model which is based on a dimension reduction technique for computational efficiency.

The Figure above shows the overall conceptual flow of our pipeline. Panel A is an image of a tissue section from the region of interest. Panel B shows spatial gene expression and biomarkers which are recorded from that tissue section with the help of sequencing techniques. Panel C is the resulting data matrix of gene expression along with spatial locations and cluster annotations on the tissue. All these serve as input for the SpaceX model to obtain the shared (Panel D) and cluster-specific co-expression networks (Panel E). Finally, we use these networks for downstream analysis to detect gene modules and hub genes across spatial regions (Panel F & Panel G respectively) for biological interpretation.

Citation

Satwik Acharyya, Xiang Zhou and Veerabhadran Baladandayuthapani (2022). SpaceX: Gene Co-expression Network Estimation for Spatial Transcriptomics. Bioinformatics, 38(22): 5033–5041.