Integrative processing of untargeted metabolomic and lipidomic data using MultiABLER

Area of Science:

• Biomedical Research
• Bioinformatics
• Analytical Chemistry

Background:

• Untargeted metabolomic and lipidomic approaches are vital in biomedical research.
• Integrating multi-omic data, including proteomics, metabolomics, and lipidomics, is crucial.
• Existing software lacks a unified pipeline for processing concurrently generated metabolomic and lipidomic data.

Purpose of the Study:

• To present MultiABLER, a unified R pipeline for upstream processing and analysis of metabolomics and lipidomics data.
• To facilitate joint downstream analyses of multi-omic datasets.
• To provide a ready-to-use bioinformatics solution for researchers.

Main Methods:

• Development of an R pipeline named MultiABLER.
• Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) for data acquisition.
• Processing untargeted metabolomic and lipidomic datasets.

Main Results:

• MultiABLER offers a unified and simple upstream processing and analysis pipeline.
• The pipeline is designed for metabolomics and lipidomics datasets.
• The R code is available under an open-source license.

Conclusions:

• MultiABLER addresses the need for a unified bioinformatics pipeline for metabolomics and lipidomics.
• The pipeline supports the integration of metabolomic and lipidomic data for multi-omic studies.
• This tool enhances the utility of mass spectrometry-based approaches in biomedical research.