PathScrubber

PathScrubber is a bioinformatic add-on to Datapunk written by D'Adamo. PathScrubber allows you to generate graphs, diagrams that depict network interactions through the relationships between nodes and edges.

How to use PathScrubber

PathScrubber is fairly intuitive to use. The entry screen is composed of three submenus, (A,B and C) shown on the following image:

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The Search Term Area (A)

This menu allows you to add genes or proteins to add to you graph network. Simply enter any gene-protein terms you wish to include in your network. Don't worry about partial terms; PathScrubber will return a list of possible terms for you to consider and you can check which ones are appropriate in the next screen. NOTE: The PathScrubber search features does not work well with special characters. In this case you may want to substitute a portion of the full name. (Example: use "nuclear factor" instead of "NF-κB".)

Although the Grapher can theoretically handle an infinite number of genes in any network, for now please try to limit the number of genes to four or less.

The Display-Filter Area (B)

This menu controls just what and how you want PathScrubber to render your network.

Show Genetic Diseases: Ticking this option will display any known genetic diseases linked to any nodes in the network
Show Tissue Distributions: Ticking this option will display known tissues distributions for that protein-gene node in the network
Show Protein-Non Protein Interactions: Ticking this option will display known non-protein interactions for that protein-gene node in the network
Show Protein Complexes: Ticking this option will display known protein complexes for that protein-gene node in the network
Align Derivatives to Bottom: Ticking this option will force PathScrubber to draw these options towards the bottom of the graph, which can help make large graphs a bit more readable
Concentrate Graph: Ticking this option will force PathScrubber to combine edges into a more 'tree-like' appearance. This often makes graphs more intelligible, but can also make large graphs with may edges a bit more difficult to discern

The Layout Menu (C)

Then select a display (or just accept the default). The help link has a whole description of the various types of graph layout and the pros and cons of each.

Run Search (D)

Pressing the button will return a list of any genes that fit your selection criteria.

Calling PathScrubber

Selecting Genes

When PathScrubber is finished searching and returns with its list of possible genes the following screen will appear:

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PathScrubber will return your settings (H,I) from the following screen and a list of gene-protein suggestions that at least partially match your search terms.

After selecting whatever gene-protein entities (technically 'species') that you wish to graph, press the button up top labeled 'Graph PathScrubber Association' and PathScrubber will attempt to draw your network.

How to Understand the PathScrubber Networks

PathScrubber attempts to construct a visual molecular network by applying its own algorithm to published molecular systems biology data (1).

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Zooming and Moving (E)

You can zoom in and out of the graph area and drag the graph around (by holding down the mouse button and moving your mouse) if needed.

Graphing Major Nodes

This area shows you what principle nodes (the gene-proteins you chose) are included in the network. Your principle nodes are always identified by their shape (diamond). All 'species' nodes are identifiable by their elliptical shape (F). Nodes are typically hyperlinks and clicking on a node will bring up the OMIM entry for that node. Nodes that are colored orange have PubMed entries associating phytochemicals or dietary agents with the expression of that gene. You can click on any of these links, which will open up a popup window (G). The popup window is a treasure trove of data about that node, including OMIM (Online Mendelian Inheritance in Man) entry for that gene in the Datapunk database and other data pipelines.

Edges

Edges typically depict post-translational modifications (acetylation, glycosylation, phosphorylation, etc.) or other mechanistic influences. If a link is visible (identified by the 'Pubmed' tag, clicking on this link will bring up the PubMed study of record in Datapunk.

Source: Prasad, T. S. K., Goel, R., Kandasamy, K., Keerthikumar, S., Kumar, S., Mathivanan, S., Telikicherla, D., Raju, R., Shafreen, B., Venugopal, A., Balakrishnan, L., Marimuthu, A., Banerjee, S., Somanathan, D. S., Sebastian, A., Rani, S., Ray, S., Kishore, C. J. H., Kanth, S., Ahmed, M., Kashyap, M., Mohmood, R., Ramachandra, Y. L., Krishna, V., Rahiman, A. B., Mohan, S., Ranganathan, P., Ramabadran, S., Chaerkady, R. and Pandey, A. Human Protein Reference Database - 2009 update. Nucleic Acids Research. 37, D767-D772.