MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes.

ABSTRACT: Increasing evidence has elucidated that the microbiome plays a critical role in many human diseases. Apart from continuous and binary traits that measure the extent or presence of a disease, multi-categorical outcomes including variations/subtypes of a disease or ordinal levels of disease severity are commonly seen in clinical studies. On top of that, studies with clustered design (i.e., family-based and longitudinal studies) are popular alternatives to population-based ones as they are able to identify characteristics on both individual and population levels and to investigate the trajectory of traits of interest over time. However, existing methods for microbiome association analysis are inadequate to handle multi-categorical outcomes, neither independent nor clustered data. We propose a

SUBMITTER: Jiang Z 

PROVIDER: S-EPMC9010828 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature