Statistical data analysis software tools | Mass spectrometry-based untargeted lipidomics
Statistical data analysis: As for other omics data, high dimensionality of typical lipidomics datasets demands careful statistical analysis. The methods applied are closely related to those used in metabolomics applications.
Assists users in identifying and quantifying small molecules by mass spectral deconvolution. MS-DIAL is able to deal with data independent acquisition tandem mass spectrometry (MS/MS) thanks by two step algorithms for spectral deconvolution. Moreover, it supports compound identification, peak alignment, and principal component analysis on the graphical user interface.
An approach for the quantitation of lipids in LC-MS data. The algorithm obtains its analytical power by two major innovations: (i) a 3D algorithm that confines the peak borders in m/z and time direction and (ii) the use of the theoretical isotopic distribution of an analyte as selection/exclusion criterion. The algorithm is integrated in the Lipid Data Analyzer (LDA) application which additionally provides standardization, a statistics module for results analysis, a batch mode for unattended analysis of several runs and a 3D viewer for the manual verification.