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Rawrr R 包:直接访问轨道阱数据及更多内容。

The rawrr R Package: Direct Access to Orbitrap Data and Beyond.

机构信息

Functional Genomics Center Zurich, ETH Zurich/University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.

Swiss Institute of Bioinformatics, Quartier Sorge - Batiment Amphipole, 1015 Lausanne, Switzerland.

出版信息

J Proteome Res. 2021 Apr 2;20(4):2028-2034. doi: 10.1021/acs.jproteome.0c00866. Epub 2021 Mar 9.

Abstract

The Bioconductor project (, (2), 115-121) has shown that the R statistical environment is a highly valuable tool for genomics data analysis, but with respect to proteomics, we are still missing low-level infrastructure to enable performant and robust analysis workflows in R. Fundamentally important are libraries that provide raw data access. Our R package rawDiag (, (8), 2908-2914) has provided the proof-of-principle how access to mass spectrometry raw files can be realized by wrapping a vendor-provided advanced programming interface (API) for the purpose of metadata analysis and visualization. Our novel package rawrr now provides complete, OS-independent access to all spectral data logged in Thermo Fisher Scientific raw files. In this technical note, we present implementation details and describe the main functionalities provided by the rawrr package. In addition, we report two use cases inspired by real-world research tasks that demonstrate the application of the package. The raw data used for demonstration purposes was deposited as MassIVE data set MSV000086542. Availability: https://github.com/fgcz/rawrr.

摘要

生物信息学软件包(, (2), 115-121) 表明 R 统计环境是基因组学数据分析的一个非常有价值的工具,但就蛋白质组学而言,我们仍然缺乏低级别的基础设施,无法在 R 中实现高性能和稳健的分析工作流程。从根本上讲,重要的是提供原始数据访问的库。我们的 R 包 rawDiag (, (8), 2908-2914) 已经证明了如何通过包装供应商提供的用于元数据分析和可视化的高级编程接口 (API) 来实现对质谱原始文件的访问。我们的新包 rawrr 现在提供了对 Thermo Fisher Scientific 原始文件中记录的所有光谱数据的完整、与操作系统无关的访问。在本技术说明中,我们介绍了实现细节,并描述了 rawrr 包提供的主要功能。此外,我们还报告了两个受真实研究任务启发的用例,展示了该包的应用。演示目的使用的原始数据已作为 MassIVE 数据集 MSV000086542 进行了存储。可访问性:https://github.com/fgcz/rawrr。

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