Motivation: Isotopic labeling is an essential relative quantification strategy in mass spectrometry-based metabolomics, ideal for studying large cohorts by minimizing common sources of variations in quantitation. MS-DIAL is a free and popular general metabolomics platform that has isotopic labeling data processing capabilities but lacks features provided by other software specialized for isotopic labeling data analysis, such as isotopic pair validation and tabular light-to-heavy peak ratio reporting.
Results: We developed Peak Pair Pruner (PPP), a standalone Python program for post-processing of MS-DIAL alignment matrixes. PPP provides these missing features and innovation including isotopic overlap subtraction based on a light-tagged pool sample as quality control. The MS-DIAL+PPP workflow for isotopic labeling-based metabolomics data processing was validated using light and heavy dansylated amino acid standard mixture and metabolite extract from human plasma.
Availability and implementation: Peak Pair Pruner is freely available on Github: https://github.com/QibinZhangLab/Peak_Pair_Pruner. Raw MS data and .ibf files analyzed are on Metabolomics Workbench with Study ID ST002427.
Contact: q_zhang2@uncg.edu.
Supplementary information: Supplementary data are available at Bioinformatics Advances online.
© The Author(s) 2023. Published by Oxford University Press.