multimedia: Multimodal Mediation Analysis of Microbiome Data

Area of Science:

• Microbiome research
• Statistical modeling
• Causal inference

Background:

• Mediation analysis is crucial for understanding causal pathways in microbiome research.
• Existing software often has rigid assumptions, limiting interpretability.
• There is a need for accessible and adaptable mediation analysis tools.

Purpose of the Study:

• To develop an R package (multimedia) for advanced, interpretable mediation analysis in microbiome studies.
• To provide a user-friendly interface for various statistical modeling techniques.
• To facilitate the exploration of mechanistic questions in biological data.

Main Methods:

• The multimedia R package offers a uniform interface for effect estimation, hypothesis testing, and sensitivity analysis.
• It supports diverse modeling approaches including regularized linear, compositional, random forest, hierarchical, and hurdle models.
• The package was illustrated using two case studies involving Inflammatory Bowel Disease and mindfulness practice.

Main Results:

• The package uncovered potential mechanistic interactions between the microbiome and metabolites in Inflammatory Bowel Disease patients.
• Mediation analysis revealed that mindfulness practice influences microbial taxa associated with depression, independent of diet or sleep.
• The multimedia package demonstrated flexibility and utility across different microbiome-related research questions.

Conclusions:

• The multimedia R package democratizes advanced mediation analysis for microbiome research.
• It enables deeper mechanistic insights into host-microbe interactions and the impact of interventions.
• The tool supports adaptable modeling strategies suitable for complex biological datasets.