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

ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion
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DOI:
10.1021/acs.jproteome.9b00328
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发表时间:
2020-01-01
影响因子:
4.4
通讯作者:
Perez-Riverol, Yasset
Perez-Riverol, Yasset
中科院分区:
生物学2区
文献类型:
--
作者:
Hulstaert, Niels;Shofstahl, Jim;Perez-Riverol, Yasset

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计算蛋白质组学领域正在接近大数据时代,这是由每次实验分析的样本数量的持续增长以及每次分析运行中获得的数据量的不断增长所驱动的。为了处理这些大量数据,越来越需要使用弹性计算资源,例如基于Linux的集群环境和云基础设施。不幸的是,绝大多数跨平台的蛋白质组学工具不能直接对各种质谱仪生成的专有格式进行操作。在这里,我们介绍了ThermoRawFileParser,这是一个开源的跨平台工具,可以将Thermo RAW文件转换为MGF和HUPO-PSI标准文件格式mzML等开放文件格式。为了确保尽可能广泛的可用性,并提高与Galaxy或Nextflow等流行工作流系统的集成能力,我们还围绕ThermoRawFileParser构建了Conda包和BioContainers容器。此外,我们为那些不熟悉命令行工具的用户实现了一个用户友好的界面(ThermoRawFileParserGUI)。最后,我们执行了ThermoRawFileParser和msconvert的基准测试,以验证转换后的mzML文件包含可靠的定量结果。
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.