A New Comprehensive Platform for Profile-Mode-Based Untargeted Metabolomics for Efficient Data Mining to Improve Compound Extraction and Identification

The profile mode of ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) is commonly utilized in metabolomics for its ability to comprehensively retain compound information in mass spectra. However, current data-analysis methods have not been optimized for the entire profile-mode-based untargeted metabolomics. To address this issue, we developed a set of novel algorithms, including centroiding transformation, extracted ion chromatogram construction, and feature extraction. We integrated them into a new automatic data analysis platform, AntDAS-Profiler. The performance of these newly developed algorithms was demonstrated by distinguishing chrysanthemums from various production origins. Additionally, AntDAS-Profiler was comprehensively compared with several state-of-the-art tools such as MS-DIAL, XCMS, and MZmine. Results suggested that AntDAS-Profiler can provide researchers with a comprehensive solution for UHPLC-HRMS profile-mode-based metabolomics. AntDAS-Profiler can be accessed at http://www.pmdb.org.cn/antdasprofiler.