Mol Cell Proteomics; co-auth.: I.Xenarios

Mol Cell Proteomics. 2014 Jun 30. pii: mcp.O113.036681. [Epub ahead of print]

The mzTab Data Exchange Format: communicating MS-based proteomics and metabolomics experimental results to a wider audience.


The HUPO Proteomics Standards Initiative (PSI) has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS) based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools like Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplementary material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. This ranges from a simple summary of the final results up to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found at

Copyright © 2014, The American Society for Biochemistry and Molecular Biology.


Bioinformatics software; Computational Biology; Data standards; Mass Spectrometry; Metabolomics