Untargeted metabolomics suffers from incomplete raw data processing

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