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We present DEIMoS: Data Extraction for Integrated MultidimensionalSpectrometry, a Python application programming interface (API) and command-linetool for high-dimensional mass spectrometry data analysis workflows that offersease of development and access to efficient algorithmic implementations.Functionality includes feature detection, feature alignment, collision crosssection (CCS) calibration, isotope detection, and MS/MS spectral deconvolution,with the output comprising detected features aligned across study samples andcharacterized by mass, CCS, tandem mass spectra, and isotopic signature.Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisitioninstrumentation; algorithm implementations simultaneously utilize alldimensions to (i) offer greater separation between features, thus improvingdetection sensitivity, (ii) increase alignment/feature matching confidenceamong datasets, and (iii) mitigate convolution artifacts in tandem massspectra. We demonstrate DEIMoS with LC-IMS-MS/MS data to illustrate theadvantages of a multidimensional approach in each data processing step.

DEIMoS: an open-source tool for processing high-dimensional mass spectrometry data