Automated Integration and Quality Assessment of Chromatographic Peaks in LC–MS-Based Metabolomics and Lipidomics Using TARDIS

In recent years, liquid chromatography coupled to mass spectrometry (LC–MS) has emerged as the main technology to measure the whole of small molecules (the metabolome) in a diversity of matrices. Within the field of computational metabolomics, significant efforts have been made in the development of tools to (pre)process untargeted LC–MS data. However, tools that circumvent the time-consuming, manual preprocessing of targeted LC–MS data with vendor-specific software remain sparse. We therefore present TARDIS, an open-source R package for the analysis of targeted LC–MS metabolomics and lipidomics data. Both established (area under the curve, maximum intensity and points over the peak) and recently developed (custom signal-to-noise ratio and bell-curve similarity) quality metrics were included to offer increased efficiency of peak quality evaluation. The robustness of TARDIS’ peak integration was demonstrated through a quantitative comparison to state-of-the-art vendor software. To this end, applicability at a large scale (n = 1786) was validated across three distinct biofluids (stool, saliva and urine) and two LC–MS instruments, using data from the FAME, ENVIRONAGE, and FGFP cohort studies. In conclusion, TARDIS offers a robust and scalable open-source solution for the targeted analysis of LC–MS metabolomics and lipidomics data. TARDIS and its source code are freely available at https://github.com/UGent-LIMET/TARDIS.