Norm-SVR for the Enhancement of Single-Cell Metabolomic Stability in ToF-SIMS

Purpose : Data stability is a critical factor in ToF-SIMS single-cell analysis. However, various factors, such as sample processing, instrument condition, and data acquisition, can introduce uncertainties into ToF-SIMS data. Correcting this data is vital, yet current methods mainly focus on total ion current normalization or using consistent substrates. No specific correction method exists for ToF-SIMS single-cell metabolomics. Methods: This study utilizes the Norm-SVR, commonly used methods for correcting large-scale metabolomics data, for the correction of ToF-SIMS single-cell metabolomic analysis and assesses its performance in comparison to traditional total ion current normalization. Results and Conclusion: The results suggest that Norm-SVR effectively diminishes batch effects and reduces variability, thereby underscoring the method's efficacy and practicality. This approach is expected to improve data quality assurance in extensive ToF-SIMS analytical datasets.