May 10, 2022
Journal Article

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data


We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface and command-line tool for high-dimensional mass spectrometry data analysis workflows, offering ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation: algorithm implementations utilize all dimensions simultaneously to (i) offer greater separation between features, improving detection sensitivity, (ii) increase alignment/feature matching confidence among datasets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS data, demonstrating the advantages of a multidimensional approach in each data processing step.

Published: May 10, 2022


Colby S.M., C.H. Chang, J.L. Bade, J. Nunez, M.R. Blumer, D.J. Orton, and K.J. Bloodsworth, et al. 2022. DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data. Analytical Chemistry 94, no. 16:6130-6138. PNNL-SA-168444. doi:10.1021/acs.analchem.1c05017