LCMS: An R package for automated semitargeted analysis in lipidomics

While nontargeted analysis aims to profile and report the relative distributions of a wide range of molecules from different lipid classes/subclasses, its major challenge is the annotation and identification of the molecules. Semitargeted analysis circumvents the problem by establishing a (potentially large) list of molecules to be targeted in the samples that are identified before the analysis. This approach is particularly adapted for lipid analysis to help with the automation of lipid annotation and identification. However, the manual extraction of peaks for many molecules and many samples is time consuming. Consequently, an automation of these extractions is deeply required. This paper presents a free R package for the automation of semitargeted analysis for lipid analysis. From raw files collected with LC-MS device and a list of molecules to target (containing their class), it automatically returns Excel files containing the intensities for each targeted molecule and each sample. This package allows a fast computation of the intensities. Furthermore, it guarantees the reproducibility of the results and is freely available and user-friendly.

Practical Applications: With the help of the R package presented in this paper, the use of semitargeted lipidomics as an alternative to untargeted analysis should be investigated by more labs. Work on the comparisons between the approaches could be conducted. While untargeted methods are mostly used, they require long pretreatments and identification of molecules of interest. On the contrary, in semitargeted analysis, once the integration table and retention time are obtained, the results are fast and directly interpretable. An idea for lipidomics would be to use untargeted lipidomics to compute the integration table and retention table, then use semitargeted analysis for a fast computation of well identified molecules.