mSGR is a Bayesian framework that infers spatially varying gene regulatory networks from multi-resolution hierarchical spatial transcriptomics data using Gaussian process priors and variational Bayes inference.
Numerical note:WhenE[λ k ij] is positively or negatively large (e.g.,|E[λk ij]|>10), we have Φ(E[λk ij])→1 or 0, and hence logit(Φ(E[λk ij])) is not well-defined numerically
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Multi-resolution Spatial Graphical Regression Models for Hierarchical Spatial Transcriptomics Data
mSGR is a Bayesian framework that infers spatially varying gene regulatory networks from multi-resolution hierarchical spatial transcriptomics data using Gaussian process priors and variational Bayes inference.