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||Use the advantages of power graphs to find functional relationships of uncharacterized transcription factors to already well characterized proteins|| || || || || || || ||ALTERNATIVE:|| || || ||Select node of interest ||Use board tools of Cytoscape || || ||Select neighbors of the selected nodes (twice) ||Use board tools of Cytoscape || || |
Power Graph Analysis with CyOog
Matthias Reimann
Biotechnology Center, Technische Universität Dresden, Germany
Biological Use Case:General: Analysis of gigantic biological networks like protein interaction networks, sequence homology networks, or regulatory networks. The information you are looking for in such networks is hidden by a big mass of edges -- inside a 'fur ball' or 'hairy monster'. Instead of loosing valuable details in the networks by coarse-graining them using clustering techniques, Power Graph Analysis can be used. A power graph is a compressed version of a normal graph. The used transformation is completely reversible.
Example described here: Finding functional relationships among transcription factors in a huge regulatory network.
Recipe
Cytoscape version: Version number (2.6)
Plugins to Load: CyOog: http://www.biotec.tu-dresden.de/schroeder/group/powergraphs
GUI steps:
Story |
Action |
Remarks |
Load your network |
Load the session file attached to this page |
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Extract power graph |
Click on the button 'Extract Power Graph ...' in the control panel of CyOog on the left hand side |
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Do not change the options in the appearing Dialog and press Ok |
The extraction takes a while. In case you run Cytoscape from a console you can check the progress there |
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After the extraction finished a new network view of a power graph appears on your Cytoscape desktop |
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Use the advantages of power graphs to find functional relationships of uncharacterized transcription factors to already well characterized proteins |
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ALTERNATIVE: |
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Select node of interest |
Use board tools of Cytoscape |
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Select neighbors of the selected nodes (twice) |
Use board tools of Cytoscape |
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Data / Session Files
attachment:Beyer.All.cys (https://www.biotec.tu-dresden.de/schroeder/group/powergraphs/examples/beyer/examples/beyer/Beyer.html)
Paper:
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000108
Please cite us: Royer L, Reimann M, Andreopoulos B, Schroeder M (2008) Unraveling Protein Networks with Power Graph Analysis. PLoS Comput Biol 4(7): e1000108
Webstart:
http://www.biotec.tu-dresden.de/schroeder/group/powergraphs/download_cyplugin.html
It is still necessary to load one of session files above!