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A network module for the Perseus software for computational proteomics facilitates proteome interaction graph analysis

View ORCID ProfileJan Rudolph, Jürgen Cox
doi: https://doi.org/10.1101/447268
Jan Rudolph
1Computational Systems Biochemistry, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.
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  • ORCID record for Jan Rudolph
Jürgen Cox
1Computational Systems Biochemistry, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany.
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  • For correspondence: cox@biochem.mpg.de
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ABSTRACT

Proteomics data analysis strongly benefits from not studying single proteins in isolation but taking their multivariate interdependence into account. We introduce PerseusNet, the new Perseus network module for the biological analysis of proteomics data. Proteomics is commonly used to generate networks, e.g. with affinity purification experiments, but networks are also used to explore proteomics data. PerseusNet supports the biomedical researcher for both modes of data analysis with a multitude of activities. For affinity purification, a volcano plot-based statistical analysis method for network generation is featured which is scalable to large numbers of baits. For posttranslational modifications of proteins, such as phosphorylation, a collection of dedicated network analysis tools helps elucidating cellular signaling events. Co-expression network analysis of proteomics data adopts established tools from transcriptome co-expression analysis. PerseusNet is extensible through a plug-in architecture in a multi-lingual way, integrating analyses in C#, Python and R and is freely available at http://www.perseus-framework.org.

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Posted October 18, 2018.
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A network module for the Perseus software for computational proteomics facilitates proteome interaction graph analysis
Jan Rudolph, Jürgen Cox
bioRxiv 447268; doi: https://doi.org/10.1101/447268
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A network module for the Perseus software for computational proteomics facilitates proteome interaction graph analysis
Jan Rudolph, Jürgen Cox
bioRxiv 447268; doi: https://doi.org/10.1101/447268

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