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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
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Technical Note: mzML and imzML Libraries for Processing Mass Spectrometry Data with the High-Performance Programming

Ignacio Rosas-Román1, Héctor Guillén-Alonso2,3, Abigail Moreno-Pedraza4,5

  • 1Universidad de Guanajuato, División de Ciencias e Ingenierías, Loma del Bosque 103, Lomas del Campestre, 37150 León, Guanajuato, Mexico.

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This summary is machine-generated.

A new Julia library enables reading mass spectrometry (MS) data in mzML and imzML formats. This significantly speeds up data processing for large-scale MS-Omics and MS imaging, overcoming previous limitations.

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Area of Science:

  • Computational Biology
  • Data Science
  • Analytical Chemistry

Background:

  • Julia programming language offers high-level readability and low-level performance.
  • Existing Julia libraries lacked support for importing mass spectrometry (MS) data.
  • This created a bottleneck for computationally intensive MS data analysis.

Purpose of the Study:

  • To develop a Julia library for importing mass spectrometry data in HUPO standard mzML and imzML formats.
  • To demonstrate the library's functionality across various MS techniques and platforms.
  • To improve the efficiency of large-scale MS data processing workflows.

Main Methods:

  • Developed a Julia library for parsing mzML and imzML file formats.
  • Tested the library with direct/ambient ionization MS, liquid chromatography-MS, and MS imaging data.
  • Compared processing speed against R for imzML MS imaging files.

Main Results:

  • The Julia library successfully imports MS data in mzML and imzML formats.
  • Processing speed for imzML MS imaging files in Julia was up to 214 times faster than R.
  • The library functions across Windows, Linux, and Mac OS.

Conclusions:

  • Julia can now efficiently process large-scale mass spectrometry data, including MS-Omics and MS imaging.
  • This library removes computational bottlenecks, enabling real-time monitoring and complex pattern recognition.
  • The developed libraries and code are available under the MIT license for broader adoption.