Article
NDExR and Cytoscape: interactive and automated visualization of biological networks using R
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Authors
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Florian Auer
- Universitätsmedizin Göttingen, Göttingen, Deutschland
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Frank Kramer
- Universitätsmedizin Göttingen, Göttingen, Deutschland
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Tim Beißbarth
- Universitätsmedizin Göttingen, Göttingen, Deutschland
| Published: | August 27, 2018 |
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Outline
Text
Network models form a simple and flexible way of representing diverse associations within complex systems, and its applications are well-established in a wide range of fields in biology [1], [2], [3]. Within a common bioinformatics workflow data integration, network analysis and visualization accompany each other [4], [5], and comprise fundamental challenges of combining various tools. Implementation of fully automated pipelines enhances the intricacy of such tasks furthermore [6].
Using standard technologies, we demonstrate a course from data acquisition to the finished visualization, and options to achieve the individual sub tasks. Thereby the network data exchange (NDEx) platform [7], [8] and the Cytoscape project [9], and appendant R [10], form the core components.
We use our R package ndexr [11] to retrieve networks from the public NDEx platform, and also to store the results for later collaboration and publication. Cytoscape is one of the most popular open-source software tools for the visual exploration of biomedical networks. Beside the graphical interface, the latest release offers a RESTful interface [12], [13] and R packages [14], [15] providing access to it.
Along an exemplary bioinformatics workflow, we demonstrate how the single steps can be performed not only interactively, but also in a fully automated manner. Each step can be done using Cytoscape or R, or a combination of both: Controlling Cytoscape remotely from within R. Starting at an interactive analysis we move towards automation, illustrating the interchangeability and flexibility of the different approaches.
The authors declare that they have no competing interests.
The authors declare that an ethics committee vote is not required.
This contribution has already been published [16].
References
- 1.
- Califano A, Butte AJ, Friend S, Ideker T, Schadt E. Leveraging models of cell regulation and GWAS data in integrative network-based association studies. Nat Genet. 2012;44:841–847. DOI: 10.1038/ng.2355
- 2.
- Chung SS, Pandini A, Annibale A, Coolen ACC, Thomas NSB, Fraternali F. Bridging topological and functional information in protein interaction networks by short loops profiling. Sci Rep. 2015;5:8540. DOI: 10.1038/srep08540
- 3.
- Oulas A, Minadakis G, Zachariou M, Sokratous K, Bourdakou MM, Spyrou GM. Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches. Brief Bioinform. 2017. DOI: 10.1093/bib/bbx151
- 4.
- Gligorijević V, Pržulj N. Methods for biological data integration: perspectives and challenges. J R Soc Interface. 2015;12:20150571. DOI: 10.1098/rsif.2015.0571
- 5.
- Pavlopoulos GA, Malliarakis D, Papanikolaou N, Theodosiou T, Enright AJ, Iliopoulos I. Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future. GigaScience. 2015;4:1–27. DOI: 10.1186/s13742-015-0077-2
- 6.
- Leipzig J. A review of bioinformatic pipeline frameworks. Brief Bioinform. 2017;18:530–536. DOI: 10.1093/bib/bbw020
- 7.
- Pillich RT, Chen J, Rynkov V, Welker D, Pratt D. NDEx: A Community Resource for Sharing and Publishing of Biological Networks. Methods Mol Biol. 2017;1558:271–301. DOI: 10.1007/978-1-4939-6783-4_13
- 8.
- Pratt D, Chen J, Welker D, Rivas R, Pillich R, Rynkov V, et al. NDEx, the Network Data Exchange. Cell Syst. 2015;1:302–305. DOI: 10.1016/j.cels.2015.10.001
- 9.
- Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–2504. DOI: 10.1101/gr.1239303
- 10.
- R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2008.
- 11.
- Auer F, Hammoud Z, Ishkin A, Pratt D, Ideker T, Kramer F, Kelso J. ndexr - an R package to interface with the network data exchange. Bioinformatics. 2018;34(4):716–717. DOI: 10.1093/bioinformatics/btx683
- 12.
- Fielding RT, Taylor RN. Principled design of the modern Web architecture. ACM Trans Internet Technol TOIT. 2002;2(2):115–150.
- 13.
- Ono K, Muetze T, Kolishovski G, Shannon P, Demchak B. CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API. F1000Research. 2015;4:478. DOI: 10.12688/f1000research.6767.1
- 14.
- Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal Complex Systems. 2006:1695.
- 15.
- Shannon PT, Grimes M, Kutlu B, Bot JJ, Galas DJ. RCytoscape: tools for exploratory network analysis. BMC Bioinformatics. 2013;14:217. DOI: 10.1186/1471-2105-14-217
- 16.
- Auer F, Kramer F, Beißbarth T. NDExR and Cytoscape: Interactive and automated visualization of biological networks using R. In: Workshop on Computational Models in Biology and Medicine 2018, Joint workshop of the GMDS/IBS-DR working groups "Statistical Methods in Bioinformatics" and "Mathematical Models in Medicine and Biology. 2018. Available from: http://www.biometrische-gesellschaft.de/fileadmin/AG_Daten/MethodenBioinformatik/PDFs/IBSGMDS_Bioinf_MathMod_Workshop2018_Abstrakts_20180305.pdf
