The Hitchhiker's Guide to Untargeted Lipidomics Analysis: Practical Guidelines.
Dmitrii SmirnovPavel V MazinMaria OsetrovaElena StekolshchikovaEkaterina KhrameevaPublished in: Metabolites (2021)
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.
Keyphrases
- data analysis
- mass spectrometry
- liquid chromatography
- high resolution mass spectrometry
- tandem mass spectrometry
- gas chromatography
- high performance liquid chromatography
- capillary electrophoresis
- gas chromatography mass spectrometry
- simultaneous determination
- fatty acid
- solid phase extraction
- high resolution
- clinical practice
- electronic health record
- case control
- machine learning
- deep learning
- ms ms