Description

bioPIXIE is a novel system for biological data integration and visualization. It allows the user to discover interaction networks and pathways in which the user's gene(s)of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. For a complete description of the bioPIXIE methodology, please see our paper. The bioPIXIE algorithm runs on a MySQL database that contains a comprehensive library of high-throughput data. For more details, please see About.

Installation Tips

To use all the features of bioPIXIE, you must install the Adobe Scalable Vector Graphic (SVG) plugin and be sure that you are NOT blocking pop-up windows in your browser (this is an option in your browser preferences menu).Internet Explorer is the recommended browser when running bioPIXIE on Windows, and Firefox is the recommended browser when running bioPIXIE on Mac OS.

Browser/OS Specific Info

Mac OS 10.x

Firefox is the recommended browser when running bioPIXIE on Mac OS. Safari also works, although some occasional problems occur when the Back button is used to go back to the Home page to perform additional searches; in some cases, the new results page does not display the graph, although the Maximize Graph link does work. Using Internet Explorer for bioPIXIE on Mac OS is not recommended. Download SVG from Adobe; be sure that you download the version for 10.1, and not the Mac classic version (the classic file is named SVGView, while the Mac 10.x file is named SVGViewCarbon). Once the SVGViewCarbon file is downloaded and unstuffed, move it to your Applications folder. Close your browser, then relaunch it. bioPIXIE should now display the graph on the results page. Note that the first time you run bioPIXIE using SVG, you will need to agree to the SVG license agreement. You will only need to do this once.

Windows

Only Internet Explorer is recommended for use with bioPIXIE on Windows. When prompted by your browser (on the results page) to install SVG plugin from Adobe, agree to download. The browser should then automatically install the plugin and display the graph. Please do not use Firefox on Windows - because of Firefox's handling of JavaScript evidence windows will not display properly with Firefox on Windows.

Linux

We recommend Mozilla for running SVG on Linux (we used Mozilla 1.7.3 on Fedora Core 2 Linux). To install the Adobe SVG viewer, download it and install.sh script as root. Then, as a normal user, add ADOBE_SVG_VIEWER_PATH=/usr/local/adobesvg-3.0.1 to your .bashrc, and run your .bashrc as '. ~/.bashrcÂ’.

The first time you want to use the viewer, you need to run the Mozilla binary as follows. From the shell prompt enter: export LD_LIBRARY_PATH=/usr/lib/mozilla-1.7.3, then /usr/lib/mozilla-1.7.3/mozilla-bin Navigate to the SVG image you want to view. The first time you run this a dialog box will display asking if you agree to the terms of the license. If you do, then accept. Mozilla should then display the SVG image correctly. After that, you may run mozilla normally.

Using bioPIXIE

Starting a Search

To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names of aliases. If you enter multiple genes, they can be separated by commas or returns. Press 'submit'.
bioPIXIE Home

Viewing Your Graphical Results

bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction).
Viewing Graph

Viewing Significant Gene Ontology Terms

Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. Significance is calculated with hypergeometric distribution using an optimized version of GoTermFinder (Boyle et al (2004) Bioinformatics 20:3710-5).
Viewing GO Terms

Exploring the Graph

To explore the graph further, click 'Maximize Graph'. You can now zoom or save the graph by right clicking anywhere on the graph and choosing the appropriate menu option. For Windows users, holding down 'ctrl' key and left mouse button down simultaneously will allow you to move the graph around in the window. As you move the mouse over genes in the network, interactions involving these genes are highlighted.If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed.
Exploring the Graph

A Typicial Query Example

Rad23 is a protein known to form a complex with Rad4 (NEF2) and participate in nucleotide excision repair. Recent work has also suggested that Rad23 facilitates DNA repair by inhibiting the degradation of specific substrates in response to DNA damage. Here we show an example where bioPIXIE is used to probe the latter role of Rad23. If we enter Rad23 as a query along with other proteasome proteins, Pup1, Pre6, Rpn12, we get the following graph:

 

We see a number of interconnected-components of the proteasome complex at the top of the graph, while Rad23 has a number of high-confidence links to a few of them. Most notably, Rad23 has a .95 probability link with Rpt6, which can be investigated by clicking on the red edge between them.

The putative interaction between Rad23 and Rpt6 is supported by two independent affinity precipitation experiments (one a traditional assay and the other high throughput). We can see the source of these results by following the links under the Evidence type column, which results in these windows:

 

If we`re interested in probing the interaction network around Rad23 (independent of the proteasome proteins we entered in the initial query), we can mouseover Rad23 in the graph shown above and click on , which pops up this graph:

 

This more clearly shows the involvement of Rad23 in both DNA nucleotide excision repair (Rad4, Rad3, Rad7, etc. links) and the proteasome complexes. If we just want to see a list of proteins to which Rad23 is most closely connected (without the graph), we can mouseover Rad23 in either of the graphs above and click , which returns the following page:

This lists each gene in order of its confidence of interaction with RAD23. Gene names and the confidence scores are links to SGD`s info page or the supporting evidence for this interaction.