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dc.contributor.authorHulstaert, Niels
dc.contributor.authorShofstahl, Jim
dc.contributor.authorSachsenberg, Timo
dc.contributor.authorWalzer, Mathias
dc.contributor.authorBarsnes, Harald
dc.contributor.authorMartens, Lennart
dc.contributor.authorPerez-Riverol, Yasset
dc.date.accessioned2021-05-18T11:11:55Z
dc.date.available2021-05-18T11:11:55Z
dc.date.created2020-02-26T12:25:32Z
dc.date.issued2020
dc.identifier.issn1535-3893
dc.identifier.urihttps://hdl.handle.net/11250/2755440
dc.description.abstractThe 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.en_US
dc.language.isoengen_US
dc.publisherACSen_US
dc.titleThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversionen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright 2019 American Chemical Societyen_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.doi10.1021/acs.jproteome.9b00328
dc.identifier.cristin1797768
dc.source.journalJournal of Proteome Researchen_US
dc.source.pagenumber537–542en_US
dc.relation.projectBergens forskningsstiftelse: BFS2016REK02en_US
dc.relation.projectNorges forskningsråd: 251235en_US
dc.identifier.citationJournal of Proteome Research. 2020, 19(1), 537–542en_US
dc.source.volume19en_US
dc.source.issue1en_US


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