LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation

Area of Science:

• Lipidomics
• Mass Spectrometry
• Bioinformatics

Background:

• Data-dependent acquisition (DDA) is the primary mode for untargeted lipidomics, yet initial LipidMS versions focused on data-independent acquisition (DIA).
• A comprehensive workflow for DDA data analysis in lipidomics is needed to leverage its widespread use.

Purpose of the Study:

• To introduce LipidMS 3.0, an R package extending lipidomics analysis capabilities.
• To incorporate DDA support and a full data analysis pipeline, including pre-processing and annotation, into LipidMS.
• To provide a user-friendly web application for broader accessibility.

Main Methods:

• Development of LipidMS 3.0 as an R package.
• Implementation of pre-processing steps: peak-picking, alignment, and grouping.
• Integration of DDA and DIA data acquisition modes for lipid annotation.
• Validation using a human serum pool spiked with lipid standards.

Main Results:

• LipidMS 3.0 demonstrates comparable performance to XCMS in data pre-processing.
• It complements MS-DIAL by providing enhanced structural information and reducing incorrect lipid annotations.
• The package supports a wider range of lipid classes and acquisition modes.

Conclusions:

• LipidMS 3.0 offers a robust and comprehensive solution for untargeted lipidomics.
• The package improves the accuracy and depth of lipid identification from LC-MS/MS data.
• Its availability as an R package and web application promotes wider adoption in lipidomics research.