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Nevin Manimala Statistics

Functional Lipid Analysis via Index-Based Lipidomics Profile: A New Computational Module in LipidOne

Bioinformatics. 2026 Mar 1:btag090. doi: 10.1093/bioinformatics/btag090. Online ahead of print.

ABSTRACT

MOTIVATION: Understanding the functional roles of lipids is essential for interpreting metabolic phenotypes in health, disease, and dietary interventions. However, lipidomic analyses typically focus on individual lipid species, making it difficult to extract mechanistic and systems-level insights. We therefore asked how quantitative lipidomic data can be translated into biologically structured and function-oriented interpretations.

RESULTS: Here, we present a major update to LipidOne (lipidone.eu), introducing the novel analytical module: Functional Lipid Analysis (FLA). FLA computes 42 indices describing lipid functions related to membrane structure, energy storage, and signaling. Indices are derived from lipid classes and fatty acyl-, alkyl-, and alkenyl-chain composition, statistically compared across experimental groups, and explored using multivariate and visualization tools. Each index is semantically annotated and linked to predicted protein mediators, enabling pathway- and network-based interpretation. Application to published datasets confirmed previous conclusions while uncovering additional biologically coherent functional insights.

AVAILABILITY AND IMPLEMENTATION: New FLA module is freely available through LipidOne.eu web platform. The LipidOne FLA core R script (v1.0.0) is archived on Zenodo (DOI: 10.5281/zenodo.18468230). The LipidOne web platform is available at https://lipidone.eu.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:41764409 | DOI:10.1093/bioinformatics/btag090

By Nevin Manimala

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