1. Data Preparation
a. Go to the following link…
b. Download the data file … Table S2
c. Look at the data file
d. Download the list of DEG... https://github.com/graphanalytics/exampledatasets/blob/master/chip-genes.txt
2. Objtain Network Data From STRING
a. Go to STRING database at the following URL…
b. Click “Search” and choose “Multiple Proteins” from the left hand menu.
c. Enter the list of DEG in the text box and hit the “Search” button. Click “Continue” and again “Continue” when prompted.
d. In the Network page, click “Data Settings” and choose, “low confidence” for the “minimum required interaction score”. Click “Update Settings” . When the network refreshes, click the “Table / Exports” option and choose the “as simple tabular text output” format to download the data.
3. Network Format
a. Open the network file in a text editor..
4. Load Network In To Cytoscape
a. Open Cytoscape , close any introduction dialog box.
b. Click “File-Import-Network-File” option…
c. Choose the downloaded network file and click open..
d. In the resulting “Import Network from Table” window… click the “Advanced Options…” button. Fix the source node, target node options, column headers and click OK to import the network.
e. To specify the source and target column, Click the column header “1”, and click the first “Meaning:” icon to exclude from import of this column. Click the column header “protein1”, and click the source node icon . Similarly mark column header “2” to be excluded and column header ‘protein2’ to be marked as the target.
f. If you successfully imported the network, you should see the following numbers…
g. Click “Layout”, “yFiles Layout” and “Organic” for a simple layout.
5. RNA-Seq Data Integration
a. Lets integrate the RNA-Seq data to this network. Save the network before proceeding. In the RNA-Seq data file, delete the first sheet and keep only the “RNA_ChIP cross reference” sheet.
b. Click “File-Import-Table-File” and choose the RNA-Seq file to open.
c. In the resulting “Import Columns from Table” window… under the “Preview” section, choose “Locus” as the “KEY” column…. if the resulting window looks like below, click “OK”…
d. To make sure the data integration worked… type “pa3385” in the search box and hit enter.
e. If everything went well, that search should give you PA3385 data in the “Table Panel” as shown below…
a. Lets do the module search based on physical properties of the network, using MCODE plugin. Search and install “MCODE” through App Manager and run MCODE with default parameters… PA3385 found in Cluster 1.
b. Lets go back to the focused network, search and select PA3385. Lets now choose all the neighbors of PA3385, by clicking – “Select – First neighbors of selected nodes – undirected”.
7. Network Styling
a. Create a new network from selected nodes and all edges, and layout using yFiles – Organic.
b. Lets name the nodes, by clicking “Style” menu and then choose “SYMBOL” from the list.
c. You can set the node color as shown here..
d. You can generate network statistics using the “Tools – Network Analyzer – Network Analysis – Analyze Network” option.
e. Remove duplicated edges, using “Edit – Remove duplicated edges option”.
f. Set the node shape as “Ellipse”.
g. Lets use the degree measure to size the nodes…
8. Export Network Image
To export the network as a picture, click – File – Export – Network View as Graphics”, give a name to the file, select the resolution and save the picture.
Look at the associations of nodes with that of the ‘amrz’. We find that mucR is found associated with amrz. mucR is also significantly regulated in this rnaseq data (as you see based on the node color and actual data here). There is also a paper that describes the role of mucR in alginate metabolism. We have established an association between mucR and AmrZ towards alginate metabolism using our simple analysis.
“AmrZ activates alginate production by binding the algD promoter and is essential for twitching motility and formation of a type IV pilus”