Multi-omics guided pathway and network analysis of clinical metabolomics and proteomics data

Abstract

Metabolomics, the study of small molecules in biological systems, is a powerful tool for understanding biochemical pathways, discovering biomarkers, and elucidating disease mechanisms. This chapter provides a guide to performing metabolomics data analysis in R, focusing on enrichment analysis and network-based approaches. It covers essential steps in data processing, quality control (QC), differential expression analysis, integration with proteomics using multi-omics factor analysis (MOFA) and statistical network analysis, as well as enrichment analysis using prior knowledge. The methods outlined provide a framework for biomarker discovery and advancing systems-level understanding of disease processes using metabolomics data in combination with prior knowledge and proteomics data.