MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Journal: Journal of proteome research
Published Date: Nov 22, 2022

Abstract

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich spectra challenges existing data storage and access technologies, therefore precluding informatics advancements. We present MZA (pronounced ), the mass-to-charge (/) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed of a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and cross-programming language access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable, example MS-data and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

Authors

  • Aivett Bilbao
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Dylan H Ross
    Department of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States.
  • Joon-Yong Lee
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Micah T Donor
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Sarah M Williams
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Ying Zhu
    China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
  • Yehia M Ibrahim
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Richard D Smith
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.
  • Xueyun Zheng
    Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Keywords

External Resources

Popular Topics
Recent Journals