The function, thanks to the connection with the Cytoscape software, allows the user to create a collection of graphs to be visualized in a unique session, while documenting interesting findings.
1 2 3
the names of the graphs to be visualized. Default value is
name of the collection of graphs displayed in Cytoscape.
a list of customized labels to be associated with the names of the genes. Each list element must contain only one value (i.e. the new label), and the name of each element must be associated with the names of the genes given as input to the
correction method for p-values calculated on graphs. The adjustment methods allowed are:
The visual node attributes size and fill color are defined in a dynamic manner through a visual mapping based on the indices provided by the
infoSource function (automatically uploaded in the bottom panel - right side).
A discrete mapper between
source attribute and size is applied:
big size: the variable belongs to the primary set (
medium size: the variable belongs to the secondary set (
small size: otherwise (
On the other hand, a color gradient mapper between fill node color and
relevance is adopted: higher values are highlighted with darker blue color.
The default style can be changed manually either within Cytoscape (for further information see manual) or within an R package
r2cytoscape through network SUID returned by the
sourceCytoscape function (for further details see manual).
It is also possible to call the sourceCytoscape function multiple times, with all the graphs being visualized in a unique session within a collection specified by collection.name.
The function use the
r2cytoscape package to connect to Cytoscape from R using CyREST.
r2cytoscape can be downloaded from:
To enable the display function to work properly, three simple steps are required:
Download Cytoscape (version 3.3 or later);
Complete installation wizard;
Launch Cytoscape (before calling the functions).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
## Load the SourceSetObj obtained from the source set analysis of ALL dataset # see vignette for more details print(load(file=system.file("extdata","ALLsourceresult.RData",package = "SourceSet"))) class(results.all) ## NB: Remember to launch cytoscape before running the following commands # Create two collections of pathways to visualize the results graph.signaling<-names(results.all)[grep("signaling",names(results.all))] graph.other<-setdiff(names(results.all),graph.signaling) ## Signaling collection cytoID.signaling<-sourceCytoscape(results.all, name.graphs = graph.signaling, collection.name ="SignalingPathway") ## Other collection cytoID.other<-sourceCytoscape(results.all, name.graphs = graph.other, collection.name ="OtherPathway")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.