Heterogeneity-Aware Gaussian Graphical Models for High- Dimensional Omics: A Narrative Review
In high-dimensional omics data, sparse precision matrices of Gaussian graphical models (GGMs) can be used to encode conditional dependence among molecular features to allow for interpretable network inference. This narrative review integrates some of the heterogeneity-aware extensions of GGMs and categorizes them based...