Network inference from abundance data using a latent mixture on spanning tree structures.
Networks are tools used to represent species relationships in microbiology and ecology. Gaussian Graphical Models provide with a mathematical framework for the inference of networks representing conditional dependence relationships, allowing for a clear separation of direct and indirect effects. However observed data are often discrete counts and the inference cannot be directly performed within this framework.