| Autor: |
Bilbao A; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Ross DH; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Lee JY; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Donor MT; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Williams SM; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Zhu Y; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Ibrahim YM; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Smith RD; Pacific Northwest National Laboratory, Richland, Washington 99352, United States., Zheng X; Pacific Northwest National Laboratory, Richland, Washington 99352, United States. |
| Abstrakt: |
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. |
