Advancing reproducibility in multi-omics studies

Combining data across biological layers, including DNA, RNA, proteins, and metabolites, provides a detailed view of human health and disease. However, variation in biology, measurement techniques, and analytical methods makes integrating these multi-omics datasets difficult to reproduce. This thesis develops guidelines and reusable procedures to improve the reliability of multi-omics integration. Applying these strategies to multiple datasets, the research demonstrates how complex biological data can be analyzed more soundly to yield dependable insights.