This is the R code used in the paper "Mediation Effect Selection in High-Dimensional and Compositional Microbiome Data".
Motivation: The microbiome plays an important role in human health by mediating the path from environmental exposure to health outcome. The relative abundances of the high-dimensional operational taxonomic units (OTUs) in the microbiome have an unit-sum restriction, making standard statistical methods in the Euclidean space inappropriate. To address this problem, we use the isometric logratio (ilr ) transformations of the relative abundances as the mediator variables.
Results: For the goal of selecting significant mediators, we propose a novel closed testing-based selection procedure with desirable confidence. Simulations are provided to verify the effectiveness of our method. As an illustrative example, we apply the proposed method to study the mediation effects of human gut microbiome between dietary fiber intake and body mass index.