Expanding the Perseus Software for Omics Data Analysis With Custom Plugins. Issue 1 (15th September 2020)

• Record Type: Journal Article
• Authors: Yu, Sung‐Huan; Ferretti, Daniela; Schessner, Julia P.; Rudolph, Jan Daniel; Borner, Georg H. H.; Cox, Jürgen
• Is Part Of: Current protocols in bioinformatics. Volume 71:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-15
• Subjects: MaxQuant -- omics data analysis -- Perseus -- plugin development -- quantitative proteomics; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.105
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: 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