High-dimensional count and compositional data analysis in\\ microbiome studies

The human microbiome plays an important role in human health and disease. The development of high-throughput sequencing technologies makes it possible to quantify all microbes constituting the microbiome. In this paper, we give a review of recent advances in high-dimensional count and compositional data analysis in microbiome studies. It includes the Dirichlet-multinomial model and its extensions, composition estimation from large sparse count matrix, high-dimensional regression with compositional covariates, and statistical inference for log-basis-based compositional data.