Testing microbiome association using integrated quantile regression models.

ABSTRACT:

Motivation

Most existing microbiome association analyses focus on the association between microbiome and conditional mean of health or disease-related outcomes, and within this vein, vast computational tools and methods have been devised for standard binary or continuous outcomes. However, these methods tend to be limited either when the underlying microbiome-outcome association occurs somewhere other than the mean level, or when distribution of the outcome variable is irregular (e.g. zero-inflated or mixtures) such that conditional outcome mean is less meaningful. We address this gap by investigating association analysis between microbiome compositions and conditional outcome quantiles.

Results

We introduce a new association analysis tool named MiRKAT-IQ within the Microbio

SUBMITTER: Wang T 

PROVIDER: S-EPMC10060731 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature