RCy3 2.22.1
This vignette will show how to perform basic network operations on an iGraph networks and use this information to customize its appearance in Cytoscape directly from R using the RCy3 package
*From Vessy’s “Fun with R blog”: http://www.vesnam.com/Rblog/viznets5/
if(!"RCy3" %in% installed.packages()){
install.packages("BiocManager")
BiocManager::install("RCy3")
}
library(RCy3)
if(!"igraph" %in% installed.packages()){
install.packages("igraph")
}
library(igraph)
if(!"plyr" %in% installed.packages()){
install.packages("plyr")
}
library(plyr)
The whole point of RCy3 is to connect with Cytoscape. You will need to install and launch Cytoscape:
cytoscapePing()
Data format: dataframe with 3 variables; variables 1 & 2 correspond to interactions; variable 3 is weight of interaction
lesmis <- system.file("extdata","lesmis.txt", package="RCy3")
dataSet <- read.table(lesmis, header = FALSE, sep = "\t")
Create a graph. Use simplify to ensure that there are no duplicated edges or self loops
gD <- igraph::simplify(igraph::graph.data.frame(dataSet, directed=FALSE))
Verify the number of nodes (77) and edges (254):
igraph::vcount(gD)
igraph::ecount(gD)
Calculate some node properties and node similarities that will be used to illustrate different plotting abilities
Calculate degree for all nodes
degAll <- igraph::degree(gD, v = igraph::V(gD), mode = "all")
Calculate betweenness for all nodes
betAll <- igraph::betweenness(gD, v = igraph::V(gD), directed = FALSE) / (((igraph::vcount(gD) - 1) * (igraph::vcount(gD)-2)) / 2)
betAll.norm <- (betAll - min(betAll))/(max(betAll) - min(betAll))
rm(betAll)
Calculate Dice similarities between all pairs of nodes
dsAll <- igraph::similarity.dice(gD, vids = igraph::V(gD), mode = "all")
Add new node attributes based on the calculated node properties/similarities
gD <- igraph::set.vertex.attribute(gD, "degree", index = igraph::V(gD), value = degAll)
gD <- igraph::set.vertex.attribute(gD, "betweenness", index = igraph::V(gD), value = betAll.norm)
Check the attributes. You should see “degree” and “betweeness” now, in addition to “name”.
summary(gD)
And now for the edge attributes…
F1 <- function(x) {data.frame(V4 = dsAll[which(igraph::V(gD)$name == as.character(x$V1)), which(igraph::V(gD)$name == as.character(x$V2))])}
dataSet.ext <- plyr::ddply(dataSet, .variables=c("V1", "V2", "V3"), function(x) data.frame(F1(x)))
gD <- igraph::set.edge.attribute(gD, "weight", index = igraph::E(gD), value = 0)
gD <- igraph::set.edge.attribute(gD, "similarity", index = igraph::E(gD), value = 0)
Note: The order of interactions in dataSet.ext is not the same as it is in dataSet or as it is in the edge list and for that reason these values cannot be assigned directly
for (i in 1:nrow(dataSet.ext))
{
igraph::E(gD)[as.character(dataSet.ext$V1) %--% as.character(dataSet.ext$V2)]$weight <- as.numeric(dataSet.ext$V3)
igraph::E(gD)[as.character(dataSet.ext$V1) %--% as.character(dataSet.ext$V2)]$similarity <- as.numeric(dataSet.ext$V4)
}
rm(dataSet,dsAll, i, F1)
Check the edge attributes. You should see “weight” and “similarity” added.
summary(gD)
Update: You can go straight from igraph to Cytoscape, sending all attributes and displaying graph!
createNetworkFromIgraph(gD,new.title='Les Miserables')
A list of available layouts can be accessed from R as follows:
getLayoutNames()
We’ll select the “fruchterman-rheingold” layout. To see properties for the given layout, use:
getLayoutPropertyNames("fruchterman-rheingold")
We can choose any property we want and provide them as a space-delimited string:
layoutNetwork('fruchterman-rheingold gravity_multiplier=1 nIterations=10')
But that is a crazy layout, so let’s try “force-directed” instead:
layoutNetwork('force-directed defaultSpringLength=70 defaultSpringCoefficient=0.000003')
On nodes…
setNodeColorMapping('degree', c(min(degAll), mean(degAll), max(degAll)), c('#F5EDDD', '#F59777', '#F55333'))
lockNodeDimensions(TRUE)
setNodeSizeMapping('betweenness', c(min(betAll.norm), mean(betAll.norm), max(betAll.norm)), c(30, 60, 100))
…and edges
setEdgeLineWidthMapping('weight', c(min(as.numeric(dataSet.ext$V3)), mean(as.numeric(dataSet.ext$V3)), max(as.numeric(dataSet.ext$V3))), c(1,3,5))
setEdgeColorMapping('weight', c(min(as.numeric(dataSet.ext$V3)), mean(as.numeric(dataSet.ext$V3)), max(as.numeric(dataSet.ext$V3))), c('#BBEE00', '#77AA00', '#558800'))
We will define our own default color/size schema after we defined node and edge rules, due to possible issues when using rules
setBackgroundColorDefault('#D3D3D3')
setNodeBorderColorDefault('#000000')
setNodeBorderWidthDefault(3)
setNodeShapeDefault('ellipse')
setNodeFontSizeDefault(20)
setNodeLabelColorDefault('#000000')
Voila! All done.
cytoscapeVersionInfo()
sessionInfo()