Untargeted Metabolomics Suffers From Incomplete Data Analysis

Introduction: Untargeted metabolomics is a powerful tool for biological discoveries. Significant advances in computational approaches to analyzing the complex raw data have been made, yet it is not clear how exhaustive and reliable are the data analysis results. Objectives: Assessment of the quality of data analysis results in untargeted metabolomics. Methods: Five published untargeted metabolomics studies acquired using instruments from different manufacturers were reanalyzed. Results: Omissions of at least 50 relevant compounds from original results as well as examples of representative mistakes are reported for each study. Conclusion: Incomplete data analysis shows unexplored potential of current and legacy data.