LipidMatch Quant (LMQ) 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 LMQ can be integrated with any lipid identification and feature finding software. LMQ 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.
For software developers and to report bugs the GitHub page for LipidMatch Quant is: https://github.com/GarrettLab-UF/LipidMatch-Quant
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: Annotation and quantification of lipids using an open source LC-HRMS/MS workflow and LipidMatch Quant. Journal of the American Society for Mass Spectrometry. Submitted (2017)
- Download LipidMatch Quant Here
- Click the “Source code (zip)” to download the newest version of the code