However, these observations and generalizations are built on an assumption that the study design and data quality assurance are always correctly executed and considered , and the underlying philosophy of chemometrics is efficiently applied throughout the metabolomics study from the start to biological interpretation . To maximize the value of metabolomic data, exploration of different algorithms and methods might be the best trade-off currently. As this study demonstrates, different steps involved in data mining are interdependent (Figure 6), and methods employed in each step would influence the downstream steps. However, although an exploration of different algorithms and methods is encouraged, this should be guided and discerned based on a thorough manual examination of the raw data and a strong analytical and chemometric knowledge.