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CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
Published on: November 10, 2023
Multi-Omics Guided Pathway and Network Analysis of Clinical Metabolomics and Proteomics Data
Christina Schmidt1, Thomas Naake2,3,4,5
1Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany.
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.
