Human Microbiome Mixture Analysis Using Weighted Quantile Sum Regression.

ABSTRACT: Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQS_RSRH), a mixture method successfully applied to 'omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQS_RSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculat

SUBMITTER: Eggers S 

PROVIDER: S-EPMC9819204 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature