Bioinformatics Core Unit, Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff Institute, Ludwigstr. 43, Bad Nauheim, Germany.
Bioinformatics Core Unit, Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff Institute, Ludwigstr. 43, Bad Nauheim, Germany; The German Center for Cardiovascular Research (DZHK), Partner Site Rhine-Main.
Mol Cell Proteomics. 2019 Aug;18(8):1700-1702. doi: 10.1074/mcp.TIR119.001505. Epub 2019 May 16.
In the context of publishing data sets acquired by mass spectrometry or works based on such molecular screens, metadata documenting the instrument settings are of central importance to the evaluation and reproduction of results. A single experiment may be linked to hundreds of data acquisitions, which are frequently stored in proprietary file formats. Together with community-, repository-, as well as publisher-specific reporting standards, this state of affairs frequently leads to manual -and thus error prone-metadata extraction and formatting. Data extracted from a single file also often stand in for an entire file set, implying a risk for unreported parameter divergence. To support quality control and data reporting, the C# application MARMoSET extracts and reduces publication relevant metadata from Thermo Fischer Scientific RAW files. It is integrated with an R package for easy reporting. The tool is expected to be particularly useful to high throughput environments such as service facilities with large project numbers and/or sizes.
在出版通过质谱仪获取的数据集或基于此类分子筛选的工作时，记录仪器设置的元数据对于评估和重现结果至关重要。一个实验可能与数百次数据采集相关联，这些数据通常存储在专有的文件格式中。这种情况再加上社区、存储库以及出版商特定的报告标准，经常导致手动的（因此容易出错的）元数据提取和格式化。从单个文件中提取的数据通常也代表整个文件集，这意味着存在未报告参数差异的风险。为了支持质量控制和数据报告，C#应用程序 MARMoSET 从 Thermo Fischer Scientific RAW 文件中提取和简化与发布相关的元数据。它与一个用于轻松报告的 R 包集成在一起。该工具预计对于高通量环境特别有用，例如项目数量和/或规模较大的服务设施。
