In Journal of proteome research
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 m-za), the mass-to-charge (m/z) 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.
Bilbao Aivett, Ross Dylan H, Lee Joon-Yong, Donor Micah T, Williams Sarah M, Zhu Ying, Ibrahim Yehia M, Smith Richard D, Zheng Xueyun
2022-Nov-22
data conversion, data-independent acquisition, ion mobility spectrometry, mass spectrometry, open data format
