A two-stage microbial association mapping framework with advanced FDR control.

ABSTRACT:

Background

In microbiome studies, it is important to detect taxa which are associated with pathological outcomes at the lowest definable taxonomic rank, such as genus or species. Traditionally, taxa at the target rank are tested for individual association, followed by the Benjamini-Hochberg (BH) procedure to control for false discovery rate (FDR). However, this approach neglects the dependence structure among taxa and may lead to conservative results. The taxonomic tree of microbiome data represents alignment from phylum to species rank and characterizes evolutionary relationships across microbial taxa. Taxa that are closer on the tree usually have similar responses to the exposure (environment). The statistical power in microbial association tests can be enhanced by efficiently em

SUBMITTER: Hu J 

PROVIDER: S-EPMC6060480 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature