LipidMatch Normalizer (LMN) can be used to perform relative quantification for lipidomics using class specific lipid standards and LC-MS data. The user provides a feature table containing all the annotated lipids and their respective m/z values, retention time, and intensities across samples. The feature table format is flexible, and hence LMN can be integrated with any lipid identification and feature finding software. LMN automatically selects internal standards that represent similar lipid structure to the target lipids and takes into account signal suppression effects in liquid chromatography mass spectrometry, prioritizing a match of lipid class, adduct, and retention time, respectively. If multiple internal standards are provided for a particular lipid class, internal standards with the closest retention time to the target analyte will be chosen.
A step-by-step video tutorial for LipidMatch Normalizer can be found here: https://youtu.be/Br7GW5O4LoI
For software developers and to report bugs the GitHub page for LipidMatch Quant is: https://github.com/GarrettLab-UF/LipidMatch-Normalizer
Jeremy P. Koelmel, Jason A. Cochran, Candice Z. Ulmer, Allison J. Levy, Rainey E. Patterson, Berkley C. Olsen, Richard A. Yost, John A. Bowden, Timothy J. Garrett: Influence of Data-Processing Strategies on Normalized Lipid Levels using an Open-Source LC-HRMS/MS Lipidomics Workflow. Journal of the American Society for Mass Spectrometry. Submitted (2018)
- Download LipidMatch Normalizer Here
- Click the “Source code (zip)” to download the newest version of the code