MWASTools: an R/bioconductor package for metabolome-wide association studies

Area of Science:

• Metabolomics
• Epidemiology
• Bioinformatics

Background:

• Large-scale epidemiological studies generate complex metabonomic data.
• Analyzing this data requires specialized bioinformatics tools for robust insights.
• Existing tools may lack integrated pipelines for comprehensive analysis.

Purpose of the Study:

• To introduce MWASTools, an R package for integrated metabonomic data analysis.
• To provide a comprehensive pipeline for large-scale epidemiological studies.
• To facilitate quality control, association analysis, and biological interpretation.

Main Methods:

• The MWASTools R package offers quality control analysis.
• It performs metabolome-wide association analysis using partial correlations and generalized linear models.
• Includes visualization tools and metabolite assignment via statistical total correlation spectroscopy (STOCSY).

Main Results:

• MWASTools provides an integrated pipeline for metabonomic data analysis.
• Enables robust metabolome-wide association studies (MWAS).
• Facilitates biological interpretation of complex datasets.

Conclusions:

• MWASTools is a valuable R package for researchers in metabonomics and epidemiology.
• It streamlines the analysis of large-scale metabonomic data.
• Supports comprehensive MWAS from quality control to biological interpretation.