Adaptive and powerful microbiome multivariate association analysis via feature selection.

ABSTRACT: The important role of human microbiome is being increasingly recognized in health and disease conditions. Since microbiome data is typically high dimensional, one popular mode of statistical association analysis for microbiome data is to pool individual microbial features into a group, and then conduct group-based multivariate association analysis. A corresponding challenge within this approach is to achieve adequate power to detect an association signal between a group of microbial features and the outcome of interest across a wide range of scenarios. Recognizing some existing methods' susceptibility to the adverse effects of noise accumulation, we introduce the Adaptive Microbiome Association Test (AMAT), a novel and powerful tool for multivariate microbiome association analysis, which u

SUBMITTER: Banerjee K 

PROVIDER: S-EPMC8759573 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature