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LipidAnalyst: A Comprehensive Tool for Lipidomic Data Visualization and Analysis

Year: 2026
Type: article
Abstract: Introduction: Proper analysis of lipidomic data requires specialized tools for data processing, normalization, and visualization. Limitations in lipid parsing, data processing and visualization in most commercially available packages generated gaps for optimal analysis of lipidomic data. LipidAnalyst is developed to fill the gaps in current packages, enabling efficient lipid parsing, data processing, visualization, and analysis of lipidomic data. Methods: We used R Shiny platform to develop LipidAnalyst which is hosted on MiServer, at “https://lipidanalyst.miserver.it.umich.edu/lipidanalyst/”. Results: LipidAnalyst capabilities are summarized in three major categories of data processing, visualization, and analysis. Data processing includes quality control filtering, normalization and quantification by internal standards, besides unique features for imputation, lipid parsing, combination, further normalization, transformation, and scaling. Visualization capabilities include demonstration of data distribution by boxplots or violin plots, principal component analysis (PCA) plots, hierarchical clustering heatmaps, differential mean lipid heatmaps, volcano plots, correlation plots, and debiased sparse partial correlation (DSPC) clustering plots. Analysis includes t-test, analysis of variance (ANOVA), DSPC, partial least square-differential analysis (PLS-DA), orthogonal partial least square-differential analysis (OPLS-DA), and Random Forest. Conclusion: LipidAnalyst is a powerful tool for optimal processing, visualization, and analysis of lipidomic data. LipidAnalyst allows comprehensive visualization of lipidomic data, empowering researchers to develop appropriate analytical plans accordingly.
Source: Metabolites
DOI: 10.3390/metabo16080526
Language: English
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W7171364936
FWCI:
Cites: 55
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Related to: 10