- Cancer Types Summary
- CN Segments
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Currently there is no selected node/edge. Please, select a node/edge to see details.
About the Network View
The network view shows the genes you entered (referred to as seed nodes) in the context of biological interactions derived from public pathway databases. Each gene in the network view is color-coded with multi-dimensional genomic data derived from the cancer study you have selected.
Source of Pathway Data
Source of Drug Data
Drug data is derived from PiHelper.
Seed Nodes vs. Linker Nodes
A seed node represents a gene that you have entered. A linker node represents a gene that connects to one or more of your seed genes.
Seed nodes are represented with a thick border:
Linker nodes are represented with a thin border:
Visualization Summary of Genomic Data
The exact genomic data displayed on the network depends on the genomic profiles you have selected. For example, you can chose to include mutation, copy number and mRNA expression profiles.
By default, each node is color coded along a white to red color gradient, indicating the total frequency of alteration across the selected case set (deeper red indicates higher frequency of alteration).
For example, EGFR is frequently altered in glibolastoma:
By contrast, STAT3 is not altered at all in glioblastoma:
If you mouse over a node, or select "View::Always Show Profile Data", you will see additional details regarding the genomic alterations affecting the gene. This breaks down into mutation, copy number and mRNA expression changes affecting the gene across all cases.
Click here to see the gene legend.
Drugs targeting genes in the network are hidden by default. If you would like to see them, select "Show All Drugs" or, "Show FDA Approved Drugs" or "Show Cancer Drugs" from the drop-down box under the "Genes & Drugs" tab.
Number of Genes Targeted shown in the drug inspector refers to the total number of genes (regardless of whether or not any such gene is in the current network of interest) targeted by this drug.
Click here to see the drug legend.
Understanding Interaction and Edge Types
The interaction types are derived from the BioPAX to binary interaction mapping rules defined within Pathway Commons. They are encoded by different edge colors and can be seleted on the "Interactions" tab to the right of the network. In addition, if selected, drug-gene interactions are shown as edges in the network. The interaction types are:
Click here to see the color codes.
Complete details are available on the Pathway Commons web site.
By default, redundant interactions are merged are merged into a single edge. To see all interactions, uncheck "Merge Interactions" in the "View" menu.
There are a number of options to better deal with complex networks:
All filtering can be undone by clicking "Unhide" in the "Topology" menu.
When the flag "Remove Disconnected Nodes on Hide" in the "Topology" menu is checked, an automatic layout is performed upon all changes to the network topology.
A Force-Directed layout algorithm is used by default. However, you may choose to re-perform the layout with different parameters (by selecting "Layout::Layout Properties ...") or after the topology of the network changes with operations such as hiding or filtering. If you would like the layout to be performed automatically upon such operations simply check "Layout::Auto Layout on Changes".
You can export a network to a PNG file. To do so, select "File::Save as Image (PNG)". We do not currently support export to PDF.
Detailed Process Level (SBGN) View
When you are interested in process level details of an interaction, you may either right-click on that interaction or click the "Detailed Process (SBGN)" button in the Details tab while inspecting the interaction. This will pop up a detailed process view in SBGN Process Description Language. The shown network corresponds to all paths between source and target genes of that interaction as returned by Pathway Commons' web service. SBGN view allows users to modify the process level view in many ways, including changing its layout and topology through complexity management techniques such as hiding or collapsing. You may also store the current network as a static image or in SBGN-ML format. For further help, please refer to the Help menu of this view.