Comparison of Two Automated Targeted Metabolomics Programs to Manual Profiling by an Experienced Spectroscopist for1 H‐NMR Spectra

Abstract

Automated programs that carry out targeted metabolite identification and quantification using proton nuclear magnetic resonance spectra can overcome time and cost barriers that limit metabolomics use. However, their performance needs to be comparable to that of an experienced spectroscopist. A previously analyzed pediatric sepsis data set of serum samples was used to com-pare results generated by the automated programs rDolphin and BATMAN with the results ob-tained by manual profiling for 58 identified metabolites. Metabolites were selected using Student’s t‐tests and evaluated with several performance metrics. The manual profiling results had the high-est performance metrics values, especially for sensitivity (76.9%), area under the receiver operating characteristic curve (0.90), precision (62.5%), and testing accuracy based on a neural net (88.6%). All three approaches had high specificity values (77.7–86.7%). Manual profiling by an expert spectros-copist outperformed two open‐source automated programs, indicating that further development is needed to achieve acceptable performance levels.