1. Querying a gene of interest:
Here users are required to input a network type to search and a gene name, which is based on HGNC official symbol. Gene name will be automatically suggested if corresponding gene is shown in a given network type.
We allow users search an input gene in a direction from source node to target node in a given network. You can change this directionality from drop-down table (it would be useful for integrated networks to search)
For example, "target->source" option can be used to find regulators of a query gene. As an example, we searched FASN in liver integrated network by this option
We showed another example of finding regulators of troponin for muscle integrated network, by “target->source” option. However, this directionality option would show same results for co-expression networks.
2. Setting a parameter for network visualization:
With input of gene name and network type, we can specify the size of network from a query gene. We made a slider to change to the maximum number of neighbor nodes and users can change the size of network to visualize based on this parameter. We also added another slider to prune edges of given setting, called “edge pruning parameter”. It will pruned the edges of given network chosen by “maximum number of nodes” slider, based on –log 10 p-values of co-expressions. We set default value 2.0 (i.e. p-value, 0.01), but users can change in a full range.
3. Saving network figure and table
Users are allowed save the visualized network as image file by PNG or JPEG format.
Also, users can download tables about a query gene and neighbor genes in the network as CSV file. Those tables contain Ensembl IDs , HGNC gene symbols, mean gene expression (with standard deviation), minimum expression, and maximum expression. Expression information was derived from RNA-seq data of corresponding tissue. Here users can check protein expressions of given gene by clicking Ensembl IDs and it will redirect users to Human Protein Atlas website of given protein. In addition, users can download edge information of visualized network as CSV file format, which can be imported into Cytoscape directly.
4. Searching multiple genes (up to three genes):
Users are allowed to search multiple genes simultaneously. As an example, here we searched FASN and G6PD in liver co-expression network and they are independently clustered with neighbors.
5. Importing edge table into Cytoscape:
If users download edge tabe as CSV file format, they can easily import them into Cytoscape.
Step 1. save edges as csv file
Step 2. open Cytoscape and import csv file as network by “import network from file” menu. Please go through menu: File -> Import -> Network -> File. There you can import your CSV file. For those who do not have Cytoscape installed, please visit www.cytoscape.org
Step 3. set up options for import network from table. If you don’t have specific request, please click OK simply.
Step 4. check visualized network from Cytoscape.
6. Merging integrated network and co-expression network into Cytoscape:
If users want to see integrated network and co-expression network at once, we recommend Cytoscape for this task.
Step 1. save both network as csv files
Step 2. import networks into Cytoscape
Step 3. merge networks by “Advanced Network Merge”. Please go through menu: Tools -> Merge -> Networks
After shifting networks on the list of “available networks” into “networks to merge” by clicking “>” button, users can take union or intersection of networks as they wishes.
Finally, clicking “Merge” button, users can see integrated network and co-expression network simultaneously like below.