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LipidQuant 1.0: automated data processing in lipid class separation–mass spectrometry quantitative workflows

LipidQuant 1.0: automatizované zpracování dat při oddělování lipidových tříd – kvantitativní pracovní postupy hmotnostní spektrometrie
Authors: Denise Wolrab; Eva Cífková; Pavel Cán; Miroslav Lísa; Ondrej Peterka; Michaela Chocholousková; Robert Jirásko; +1 Authors

LipidQuant 1.0: automated data processing in lipid class separation–mass spectrometry quantitative workflows

Abstract

Abstract Summary We present the LipidQuant 1.0 tool for automated data processing workflows in lipidomic quantitation based on lipid class separation coupled with high-resolution mass spectrometry. Lipid class separation workflows, such as hydrophilic interaction liquid chromatography or supercritical fluid chromatography, should be preferred in lipidomic quantitation due to the coionization of lipid class internal standards with analytes from the same class. The individual steps in the LipidQuant workflow are explained, including lipid identification, quantitation, isotopic correction and reporting results. We show the application of LipidQuant data processing to a small cohort of human serum samples. Availability and implementation The LipidQuant 1.0 is freely available at Zenodo https://doi.org/10.5281/zenodo.5151201 and https://holcapek.upce.cz/lipidquant.php. Supplementary information Supplementary data are available at Bioinformatics online.

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Czech Republic
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Keywords

LipidQuant, Mass spectrometry, kvantifikace, lipidy, Lipids, quantification, Mass Spectrometry, Workflow, Quantitation, lipids, Data processing, hmotnostní spektrometrie, lipidomika, Lipidomics, lipidomics, Humans, mass spectrometry, Chromatography, Liquid

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
12
Top 10%
Average
Top 10%
35
86
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gold