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  Expanding the Perseus Software for Omics Data Analysis With Custom Plugins.

Yu, S.-H., Ferretti, D., Schessner, J. P., Rudolph, J. D., Borner, G. H. H., & Cox, J. (2020). Expanding the Perseus Software for Omics Data Analysis With Custom Plugins. Current protocols in bioinformatics, 71(1): e105. doi:10.1002/cpbi.105.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-7E1E-C Version Permalink: http://hdl.handle.net/21.11116/0000-0007-7E21-7
Genre: Journal Article
Subtitle : Protocol

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cpbi.105.pdf (Publisher version), 6MB
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© 2020 The Authors. Open access funding enabled and organized by Projekt DEAL

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 Creators:
Yu, Sung-Huan1, Author              
Ferretti, Daniela1, Author              
Schessner, Julia P.2, Author              
Rudolph, Jan Daniel1, Author              
Borner, Georg H. H.2, Author              
Cox, Jürgen1, Author              
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              
2Borner, Georg / Systems Biology of Membrane Trafficking, Max Planck Institute of Biochemistry, Max Planck Society, ou_3060205              

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Free keywords: MaxQuant; Perseus; omics data analysis; plugin development; quantitative proteomics
 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. © 2020 The Authors.

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: 32931150
DOI: 10.1002/cpbi.105
 Degree: -

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Project name : Max Planck Society for the Advancement of Science and the German Research Foundation. Grant Number: 2019‐202671
Grant ID : 2019‐202671
Funding program : -
Funding organization : German Research Foundation

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Title: Current protocols in bioinformatics
Source Genre: Journal
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Publ. Info: Wiley
Pages: - Volume / Issue: 71 (1) Sequence Number: e105 Start / End Page: - Identifier: ISSN: 1934-340X