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.
Applyθ(t)←step·θ(t) + (1−step)·θ(t−1)
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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.