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ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion.


ABSTRACT: The field of computational proteomics is approaching the big data age, driven both by a continuous growth in the number of samples analyzed per experiment as well as by the growing amount of data obtained in each analytical run. In order to process these large amounts of data, it is increasingly necessary to use elastic compute resources such as Linux-based cluster environments and cloud infrastructures. Unfortunately, the vast majority of cross-platform proteomics tools are not able to operate directly on the proprietary formats generated by the diverse mass spectrometers. Here, we present ThermoRawFileParser, an open-source, cross-platform tool that converts Thermo RAW files into open file formats such as MGF and the HUPO-PSI standard file format mzML. To ensure the broadest possible availability and to increase integration capabilities with popular workflow systems such as Galaxy or Nextflow, we have also built Conda package and BioContainers container around ThermoRawFileParser. In addition, we implemented a user-friendly interface (ThermoRawFileParserGUI) for those users not familiar with command-line tools. Finally, we performed a benchmark of ThermoRawFileParser and msconvert to verify that the converted mzML files contain reliable quantitative results.

SUBMITTER: Hulstaert N 

PROVIDER: S-EPMC7116465 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion.

Hulstaert Niels N   Shofstahl Jim J   Sachsenberg Timo T   Walzer Mathias M   Barsnes Harald H   Martens Lennart L   Perez-Riverol Yasset Y  

Journal of proteome research 20191206 1


The field of computational proteomics is approaching the big data age, driven both by a continuous growth in the number of samples analyzed per experiment as well as by the growing amount of data obtained in each analytical run. In order to process these large amounts of data, it is increasingly necessary to use elastic compute resources such as Linux-based cluster environments and cloud infrastructures. Unfortunately, the vast majority of cross-platform proteomics tools are not able to operate  ...[more]

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