Effortless extraction of individual lipid moieties from lipidomics datasets: Liputils, a Python module

Background and Aims: Lipidomic analyses tackle the problem of characterizing the lipid components of given cells, tissues and organisms by means of chromatographic separations coupled to high-resolution, tandem mass spectrometry analyses. Like otheromic techniques, lipidomic analyses have rapidly transitioned from a niche commodity to a widespread tool. A number of software tools have been developed to help in the daunting task of mass spectrometry signal processing and cleaning, peak analysis and compound identification, and a typical finished lipidomic dataset contains hundreds to thousands of individual molecular lipid species. To provide all researchers - including those without specific technical expertise in mass spectrometry and bioinformatics skills - the possibility of broadening the exploration of their lipidomic datasets, squeezing out additional information that would otherwise be discarded, we have developed liputils. Methods: It’s a Python module that specializes in the extraction of fatty acid moieties from all individual molecular lipids of a lipidomic dataset. Results: There is no prerequisite data format, as liputils extracts lipid residues from RefMet-compliant textual identifiers, as well as from annotations of other commercially available services. Plus, with its new graphical user interface (GUI), the processing of even the most complex datasets is performed with a couple of clicks. Conclusions: We herein provide hands-on examples of real-world data processing with liputils.