CRAmed: a conditional randomization test for high-dimensional mediation analysis in sparse microbiome data.

ABSTRACT:

Motivation

Numerous microbiome studies have revealed significant associations between the microbiome and human health and disease. These findings have motivated researchers to explore the causal role of the microbiome in human complex traits and diseases. However, the complexities of microbiome data pose challenges for statistical analysis and interpretation of causal effects.

Results

We introduced a novel statistical framework, CRAmed, for inferring the mediating role of the microbiome between treatment and outcome. CRAmed improved the interpretability of the mediation analysis by decomposing the natural indirect effect into two parts, corresponding to the presence-absence and abundance of a microbe, respectively. Comprehensive simulations demonstrated the superior performa

SUBMITTER: Liu T 

PROVIDER: S-EPMC11821267 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature