mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements

Bhamber, Ranjeet S, Jankevics, Andris, Deutsch, Eric W, Jones, Andrew R ORCID: 0000-0001-6118-9327 and Dowsey, Andrew W (2021) mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements. JOURNAL OF PROTEOME RESEARCH, 20 (1). pp. 172-183.

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Official URL: http://dx.doi.org/10.1021/acs.jproteome.0c00192

Abstract

With ever-increasing amounts of data produced by mass spectrometry (MS) proteomics and metabolomics, and the sheer volume of samples now analyzed, the need for a common open format possessing both file size efficiency and faster read/write speeds has become paramount to drive the next generation of data analysis pipelines. The Proteomics Standards Initiative (PSI) has established a clear and precise extensible markup language (XML) representation for data interchange, mzML, receiving substantial uptake; nevertheless, storage and file access efficiency has not been the main focus. We propose an HDF5 file format "mzMLb" that is optimized for both read/write speed and storage of the raw mass spectrometry data. We provide an extensive validation of the write speed, random read speed, and storage size, demonstrating a flexible format that with or without compression is faster than all existing approaches in virtually all cases, while with compression is comparable in size to proprietary vendor file formats. Since our approach uniquely preserves the XML encoding of the metadata, the format implicitly supports future versions of mzML and is straightforward to implement: mzMLb's design adheres to both HDF5 and NetCDF4 standard implementations, which allows it to be easily utilized by third parties due to their widespread programming language support. A reference implementation within the established ProteoWizard toolkit is provided.

Item Type:	Article
Uncontrolled Keywords:	Proteomics Standards Initiative, mzML, mass spectrometry, proteomics, metabolomics, data compression, HDF5
Depositing User:	Symplectic Admin
Date Deposited:	18 Feb 2021 16:11
Last Modified:	18 Jan 2023 22:59
DOI:	10.1021/acs.jproteome.0c00192
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3115828