Computational Systems Biochemistry Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Systems Biology of Membrane Trafficking Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
Curr Protoc Bioinformatics. 2020 Sep;71(1):e105. doi: 10.1002/cpbi.105.
The Perseus software provides a comprehensive framework for the statistical analysis of large-scale quantitative proteomics data, also in combination with other omics dimensions. Rapid developments in proteomics technology and the ever-growing diversity of biological studies increasingly require the flexibility to incorporate computational methods designed by the user. Here, we present the new functionality of Perseus to integrate self-made plugins written in C#, R, or Python. The user-written codes will be fully integrated into the Perseus data analysis workflow as custom activities. This also makes language-specific R and Python libraries from CRAN (cran.r-project.org), Bioconductor (bioconductor.org), PyPI (pypi.org), and Anaconda (anaconda.org) accessible in Perseus. The different available approaches are explained in detail in this article. To facilitate the distribution of user-developed plugins among users, we have created a plugin repository for community sharing and filled it with the examples provided in this article and a collection of already existing and more extensive plugins. © 2020 The Authors. Basic Protocol 1: Basic steps for R plugins Support Protocol 1: R plugins with additional arguments Basic Protocol 2: Basic steps for python plugins Support Protocol 2: Python plugins with additional arguments Basic Protocol 3: Basic steps and construction of C# plugins Basic Protocol 4: Basic steps of construction and connection for R plugins with C# interface Support Protocol 4: Advanced example of R Plugin with C# interface: UMAP Basic Protocol 5: Basic steps of construction and connection for python plugins with C# interface Support Protocol 5: Advanced example of python plugin with C# interface: UMAP Support Protocol 6: A basic workflow for the analysis of label-free quantification proteomics data using perseus.
Perseus 软件为大规模定量蛋白质组学数据的统计分析提供了一个全面的框架,也可以与其他组学维度结合使用。蛋白质组学技术的快速发展和生物研究的不断多样化,越来越需要灵活地纳入用户设计的计算方法。在这里,我们介绍了 Perseus 的新功能,以集成用 C#、R 或 Python 编写的自制插件。用户编写的代码将作为自定义活动完全集成到 Perseus 数据分析工作流程中。这也使得来自 CRAN(cran.r-project.org)、Bioconductor(bioconductor.org)、PyPI(pypi.org)和 Anaconda(anaconda.org)的特定于语言的 R 和 Python 库在 Perseus 中可用。本文详细解释了不同的可用方法。为了方便用户之间分发用户开发的插件,我们创建了一个插件存储库,用于社区共享,并在其中填充了本文提供的示例以及已经存在的更广泛的插件集合。© 2020 作者。基本协议 1:R 插件的基本步骤支持协议 1:带附加参数的 R 插件基本协议 2:Python 插件的基本步骤支持协议 2:带附加参数的 Python 插件基本协议 3:C#插件的基本步骤和构造基本协议 4:带 C#接口的 R 插件的基本步骤和构造支持协议 4:带 C#接口的 R 插件的高级示例:UMAP 基本协议 5:带 C#接口的 Python 插件的基本步骤和构造支持协议 5:带 C#接口的 Python 插件的高级示例:UMAP 支持协议 6:使用 Perseus 分析无标记定量蛋白质组学数据的基本工作流程。