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

Dataset ·
DOI:https://doi.org/10.25584/2483273· OSTI ID:2483273

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.

Research Organization:
Pacific Northwest National Laboratory 2
Sponsoring Organization:
DOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
2483273
Country of Publication:
United States
Language:
English

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