Lipidomic Data Analysis Pipeline

Data alignment and peak detection were performed in Progenesis QI (Nonlinear Dynamics; Waters Corp.) with normalization to all compounds. Retention time calibration and lipid identification were calculated with the Python package LiPydomics (66 (link)). Multivariate statistics were created through LiPydomics and ClustVis (66 (link), 67 (link)). MS/MS analysis and identification of the most abundant FAs were performed in Skyline utilizing a targeted lipid library generated with LipidCreator (68 (link), 69 (link)).

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Pruitt E.L., Zhang R., Ross D.H., Ashford N.K., Chen X., Alonzo F I.I.I., Bush M.F., Werth B.J, & Xu L. (2023). Elucidating the impact of bacterial lipases, human serum albumin, and FASII inhibition on the utilization of exogenous fatty acids by Staphylococcus aureus. mSphere, 8(6), e00368-23.

Publication 2023

Progenesis QI

Corresponding Organization :

Other organizations : University of Washington, Loyola University Chicago

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Variable analysis

independent variables

Data alignment and peak detection were performed in Progenesis QI (Nonlinear Dynamics; Waters Corp.)
Retention time calibration and lipid identification were calculated with the Python package LiPydomics
Multivariate statistics were created through LiPydomics and ClustVis
MS/MS analysis and identification of the most abundant FAs were performed in Skyline utilizing a targeted lipid library generated with LipidCreator

dependent variables

Normalized lipid profiles

control variables

Normalization to all compounds

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