أعرض في EDS

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

التفاصيل البيبلوغرافية
العنوان: ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion
المؤلفون: Lennart Martens, Yasset Perez-Riverol, Harald Barsnes, Timo Sachsenberg, Niels Hulstaert, Mathias Walzer, Jim Shofstahl
المصدر: J Proteome Res
Journal of Proteome Research
537–542
بيانات النشر: American Chemical Society (ACS), 2019.
سنة النشر: 2019
مصطلحات موضوعية: Proteomics, 0301 basic medicine, Saccharomyces cerevisiae Proteins, Computer science, Interface (Java), Big data, Cloud computing, computer.software_genre, Biochemistry, Article, Workflow, 03 medical and health sciences, Cross-platform, Databases, Protein, 030102 biochemistry & molecular biology, business.industry, Computational Biology, General Chemistry, Modular design, File format, 030104 developmental biology, Scalability, Operating system, business, computer, Software
الوصف: 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. acceptedVersion
وصف الملف: application/pdf
تدمد: 1535-3907
1535-3893
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9180999ee90467b92541938fb720f01
https://doi.org/10.1021/acs.jproteome.9b00328
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....a9180999ee90467b92541938fb720f01
قاعدة البيانات: OpenAIRE
الوصف
تدمد:15353907
15353893