LipiDex 2 Integrates MS<sup>n</sup> Tree-Based Fragmentation Methods and Quality Control Modules to Improve Discovery Lipidomics
Benton J. Anderson, Dain R. Brademan, Yuchen He, Katherine A. Overmyer, Joshua J. Coon
Abstract
As lipidomics experiments increase in scale and complexity, data processing tools must support workflows for new liquid chromatography–mass spectrometry (LC-MS) methods while simultaneously supporting quality controls to maximize the confidence in lipid identifications. LipiDex 2 improves lipidomics data processing algorithms from LipiDex 1 and introduces new tools for spectral matching and peak annotation functions, with improvements in speed and user-friendliness. In silico spectral library generation now supports tandem mass spectral (MS n ) tree-based fragmentation methods, and the LipiDex 2 workflow fully integrates the fragmentation logic into the data processing steps to enable lipid identification at the appropriate level of structural resolution. Finally, LipiDex 2 features new modules for automated quality control checks that also allow users to visualize data quality in a data dashboard user interface.