The Hitchhiker’s Guide to Untargeted Lipidomics Analysis: Practical Guidelines

TLDR

Lipidomics is a rapidly growing omics discipline that identifies and quantifies thousands of lipids, generating large datasets that demand efficient analysis methods. This paper provides practical guidelines for analyzing and interpreting untargeted LC‑MS lipidomics data, outlining a state‑of‑the‑art workflow from study design to lipid feature annotation. The authors present a detailed R notebook based on xcms for untargeted LC‑MS lipidome analysis, offering a practical workflow from data acquisition to annotation.

Abstract

Lipidomics is a newly emerged discipline involving the identification and quantification of thousands of lipids. As a part of the omics field, lipidomics has shown rapid growth both in the number of studies and in the size of lipidome datasets, thus, requiring specific and efficient data analysis approaches. This paper aims to provide guidelines for analyzing and interpreting lipidome data obtained using untargeted methods that rely on liquid chromatography coupled with mass spectrometry (LC-MS) to detect and measure the intensities of lipid compounds. We present a state-of-the-art untargeted LC-MS workflow for lipidomics, from study design to annotation of lipid features, focusing on practical, rather than theoretical, approaches for data analysis, and we outline possible applications of untargeted lipidomics for biological studies. We provide a detailed R notebook designed specifically for untargeted lipidome LC-MS data analysis, which is based on xcms software.