Journal
ANALYTICAL CHEMISTRY
Volume 89, Issue 11, Pages 6258-6265Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.7b01259
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To date, the main limitations for LC-MS-based untargeted lipidomics reside in the lack of. adequate computational and cheminformatics tools that are able to support the analysis of several thousands of species from biological samples, enabling data mining and automating lipid identification and external prediction processes. To address these issues, we developed Lipostar, novel vendor-neutral high-throughput software that effectively supports both targeted and untargeted LC-MS lipidomics, implementing data acquisition, user-friendly multivariate analysis (to be used for model,generation and new sample predictions), and advanced lipid identification protocols that can work with or without the support of preformed lipid databases. Moreover; Lipostar integrates the lipidomic processes With a full metabolite identification (MetID) procedure, essential in drug safety applications and in translational studies. Case studies demonstrating a. number of Lipostar features are also presented.
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