Abstract
Lipidomic analyses address 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. 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 researchers without a specific technical expertise in mass spectrometry the possibility of broadening the exploration of lipidomic datasets, we have developed liputils, a Python module that specializes in the extraction of fatty acid moieties from individual molecular lipids. There is no prerequisite data format, as liputils extracts residues from RefMet-compliant textual identifiers and from annotations of other commercially available services. We provide three examples of real-world data processing with liputils, as well as a detailed protocol on how to readily process an existing dataset that can be followed with basic informatics skills.
Highlights
It is possible to neatly reprocess lipidomic data to extract from the analyte annotation the information about the fatty residues contained in each sample, or further adapt the module to individual needs
Lipidomic analyses address 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
Lipidomics is the analysis of the large-scale identification and quantification of individual lipid species, which relies—at its finest—on the analytical technology of chromatographic separation coupled to mass spectrometry (MS) and dedicated software[1,2]
Summary
It is possible to neatly reprocess lipidomic data to extract from the analyte annotation the information about the fatty residues contained in each sample, or further adapt the module to individual needs. The following protocol illustrates how to create an environment to use liputils, as well as the required steps to process published data. The data table to be processed has one sample per column, and one lipid analyte per row (Supplementary Fig. S1A).
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