When the enrichment analysis is complete, a new tab titled
STRINGEnrichment will open in the
Table Panel.
At the top left of the STRING enrichment tab, click the filter
icon
. Select GO Biological Process and check the
Remove redundant terms check-box. Then click
OK.
Next, add a split donut chart to the nodes representing the top
terms by clicking on
Explore custom settings via in the top right of the STRING
enrichment tab.
Export your Networks
Cytoscape provides a number of ways to save results and
visualizations:
As a session: File → Save Session, File → Save Session
As…
As an image: File → Export → Network to Image…
As a graph format file: File → Export → Network to
File.
Formats:
CX JSON / CX2 JSON
Cytoscape.js JSON
GraphML
Exercise 2-B
Find significant expression changes in Cluster 1 Hint: We are going to repeat step 4 with
“Cluster 1 Mean log2FC” as the column. This represents the mean
expression across the samples in cluster 1 (the leftmost cluster in the
previous figure).
Open the Filter tab and setup two Column
Filters for the “Cluster 1 Mean log2FC”
column, one for up and one for down. Select the “Cluster 1 Mean
log2FC” column and set the values to be between -5
and-1, then add a second filter (be sure to specify OR
at the top) and set the values between 1 and
5. This should result in a selection of 192 nodes.
* Download the PPI
from STRING From the above selection filter, we’ve identified 192 nodes
that show an average Log2FC greater than 5 or less than
1, and selected those nodes. Now, we create a separate network
that includes all of those 192 nodes by selecting the “Create
Network from selected nodes and edges option” and then load the
protein-protein interaction data from STRING. Note that
only the selected nodes are shown in the Table
Panel.
Select gene names from Table Panel.
Select everything in the name column by clicking
into the first cell and then dragging down until you get to the bottom.
Then, do a copy (Control-C or Apple-C).
Paste gene names into STRING network search. In the
Network tab of the Control Panel at
the top should be a text field with an icon at the left. Click on that
icon and select STRING protein query. (If you don’t see
any STRING options, the stringApp
hasn’t been loaded and needs to be loaded from either the App store or
Cytoscape options menu.) Then click into the text field and paste the
list of genes.
Set STRING search parameters. Next to the text
field is a menu with a list of options. Change the Confidence
(score) cutoff to 0.8 and the Maximum additional
interactors to 30. This will get only high quality results (80%
confidence) and add 30 extra proteins to the network.
Create the network.
Click on the search icon (magnifying glass) to load the network. The
network should appear similar to the figure below.
* Style
the network to show differential expression. In this step, we’ll change
the style of the network to highlight the differentially expressed
genes.
Exercise 3-A
Walk-through exercise
For the exercise, we are going to use mRNA bladder cancer data
generated from RNA-Seq platform. The data can be retrived from Robertson
et al. Cell 2017 or downloaded from (Here..)
ClueGO settings
set the type of analysis: Compare Cluster
select the organism: Homo Sapiens and the the type of ids used:
AccessionID
select the statistical test: Enrichment/Deplection (Two
sided hypergeometric test),
FisherExactTest
select the correction method: Bonferroni
click Show Advanced Settings
set GO Tree Level: Min 4 and Max 5
set the selection criteria for the terms that have associated genes
from cluster 1: min 2 genes/term and minimum 4% from all the Genes
associated with the term
select OR (e.g. min 2 genes from cluster #1 or min 2 genes from
cluster #2)
set is specific to 66% (if 66% or the genes associated with the term
are from cluster #1, the term is considered specific for this
cluster)
set the selection criteria for the terms that have associated genes
from cluster 2: min 2 genes/term and minimum 4% from all the Genes
associated with the term
select Use GO Term Grouping
select Fix Group coloring
select Leading Group Term based on Highest Significance
select Kappa Score grouping with 3 terms in initial group and 50%
overlap for groups to merge
select ShowDifference
Start
Customize the network using Cytoscape features
select Style (Cytoscape Control Panel)
select Node Font Size
set the value of FALSE (size for the name of the terms) to 0.001 and
press Enter
set the value of TRUE (size for the name of groups) to 26 and press
Enter
select Layout (Cytoscape menu bar)
set scale to 1/3
zoom the image
change the position of the leading terms to make visible the name of
the group
change the possition of notgrouped terms if due to rescaling they
are too close to a group
for visualizing groups press Show Groups
Using the filters and style options above, develop a network by
using cluster compare for the two bladder cancer conditions - Normal VS
Tumor.
Save your network in two formats: (a) as a Cytoscape Session
(.sys format), and (b) as a .png or
.pdf figure.
The cytoscape session (.sys) will be used in the next section for
CluePedia analysis.