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ThermoRawFileParser : modular, scalable and cross-platform RAW file conversion

(2020) JOURNAL OF PROTEOME RESEARCH. 19(1). p.537-542
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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.
Keywords
Biochemistry, General Chemistry, MASS-SPECTROMETRY DATA, PROTEOMICS, IDENTIFICATION, DATABASES, bioinformatics, file formats, open source, cloud, mass spectrometry, software, big data, workflows, mzML, metadata

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MLA
Hulstaert, Niels, et al. “ThermoRawFileParser : Modular, Scalable and Cross-Platform RAW File Conversion.” JOURNAL OF PROTEOME RESEARCH, vol. 19, no. 1, 2020, pp. 537–42, doi:10.1021/acs.jproteome.9b00328.
APA
Hulstaert, N., Shofstahl, J., Sachsenberg, T., Walzer, M., Barsnes, H., Martens, L., & Perez-Riverol, Y. (2020). ThermoRawFileParser : modular, scalable and cross-platform RAW file conversion. JOURNAL OF PROTEOME RESEARCH, 19(1), 537–542. https://doi.org/10.1021/acs.jproteome.9b00328
Chicago author-date
Hulstaert, Niels, Jim Shofstahl, Timo Sachsenberg, Mathias Walzer, Harald Barsnes, Lennart Martens, and Yasset Perez-Riverol. 2020. “ThermoRawFileParser : Modular, Scalable and Cross-Platform RAW File Conversion.” JOURNAL OF PROTEOME RESEARCH 19 (1): 537–42. https://doi.org/10.1021/acs.jproteome.9b00328.
Chicago author-date (all authors)
Hulstaert, Niels, Jim Shofstahl, Timo Sachsenberg, Mathias Walzer, Harald Barsnes, Lennart Martens, and Yasset Perez-Riverol. 2020. “ThermoRawFileParser : Modular, Scalable and Cross-Platform RAW File Conversion.” JOURNAL OF PROTEOME RESEARCH 19 (1): 537–542. doi:10.1021/acs.jproteome.9b00328.
Vancouver
1.
Hulstaert N, Shofstahl J, Sachsenberg T, Walzer M, Barsnes H, Martens L, et al. ThermoRawFileParser : modular, scalable and cross-platform RAW file conversion. JOURNAL OF PROTEOME RESEARCH. 2020;19(1):537–42.
IEEE
[1]
N. Hulstaert et al., “ThermoRawFileParser : modular, scalable and cross-platform RAW file conversion,” JOURNAL OF PROTEOME RESEARCH, vol. 19, no. 1, pp. 537–542, 2020.
@article{8637406,
  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.},
  author       = {Hulstaert, Niels and Shofstahl, Jim and Sachsenberg, Timo and Walzer, Mathias and Barsnes, Harald and Martens, Lennart and Perez-Riverol, Yasset},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keywords     = {Biochemistry,General Chemistry,MASS-SPECTROMETRY DATA,PROTEOMICS,IDENTIFICATION,DATABASES,bioinformatics,file formats,open source,cloud,mass spectrometry,software,big data,workflows,mzML,metadata},
  language     = {eng},
  number       = {1},
  pages        = {537--542},
  title        = {ThermoRawFileParser : modular, scalable and cross-platform RAW file conversion},
  url          = {http://dx.doi.org/10.1021/acs.jproteome.9b00328},
  volume       = {19},
  year         = {2020},
}

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