Computational Tools for LC-IMS-MS Data Processing in Metabolomics

This chapter provides resources and step-by-step processing guidelines for analyzing liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data in metabolomics. The methods described here are based on open-source software and freely available executables developed at Pacific Northwest National Laboratory (PNNL), including PNNL-PreProcessor, MZA, mzapy, LipidOz, PeakQC, and IonToolPack. Importantly, the same software ecosystem is broadly applicable to IMS-MS workflows both with and without LC and includes algorithms that support other modalities such as proteomics, making it suitable for a wide range of experimental designs. The chapter is written for scientists seeking to establish reproducible workflows to analyze multidimensional metabolomics data, regardless of prior experience with IMS. Demonstrations for both Python-based programmatic data processing and graphical user interface (GUI) workflows are provided to facilitate implementation by users with different levels of computational expertise. Following these procedures, researchers can successfully process, visualize, and interpret LC-IMS-MS data using freely available software and data resources.