ArticleBMC bioinformatics2019
Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- Lipidome changes indicate oxidative stress, inflammation, and specific loss of glycerophosphoserine inflammatory protection in patients with lupus.Journal of pharmaceutical and biomedical analysis · 2026Article
- Analytical Approaches to the Rapid Characterisation of Marine Glycolipids in Bioproduct Discovery.Marine drugs · 2025Review
- Advancements in Mass Spectrometry-Based Targeted Metabolomics and Lipidomics: Implications for Clinical Research.Molecules (Basel, Switzerland) · 2024Review
- Angiotensin II Alters Mitochondrial Membrane Potential and Lipid Metabolism in Rat Colonic Epithelial Cells.Biomolecules · 2024Article
- Comparison of Workflows for Milk Lipid Analysis: Phospholipids.Foods (Basel, Switzerland) · 2022Article
- Improving quantitative analysis of spark-induced breakdown spectroscopy: Multivariate calibration of metal particles using machine learning.Journal of aerosol science · 2022Article
- High Throughput Semiquantitative UHPSFC-MS/MS Lipid Profiling and Lipid Class Determination.Journal of chromatographic science · 2021Article
- HIGH RESOLUTION MASS SPECTROMETRY IN LIPIDOMICS.Mass spectrometry reviews · 2021Review
- Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview.Biomolecules · 2021Review
- Review
- Environmental lipidomics: understanding the response of organisms and ecosystems to a changing world.Metabolomics : Official journal of the Metabolomic Society · 2020Review
- Lipidomics from sample preparation to data analysis: a primer.Analytical and bioanalytical chemistry · 2020Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundLipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows.
resultsLMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine.
conclusionsLMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.