m-grimes
commented
3 years ago This checking function is a workaround for createNetworkFromDataFrames:
createNetworkFromDataFrames.check <- function(nodes, edges, title="Checked", collection="Checked interactions") { for (i in 1:10){ createNetworkFromDataFrames(nodes, edges, title, collection) edgeTable <- getTableColumns("edge", c("name", "shared name")) if(!identical(edgeTable[,1], edgeTable[,2])) { print(paste('Network', i, "is bad.")) deleteNetwork()} else { print (paste("Network", i, "passes edge test.")) break } }} }
AlexanderPico
When plotting networks using createNetworkFromDataFrames(nodes,edges) there is an error that comes up with increasing frequency that is dependent on the complexity of the node and edge data tables and network size. This error is reproducible even using the help file example:
nodes <- data.frame(id=c("node 0","node 1","node 2","node 3"), group=c("A","A","B","B"), # categorical strings score=as.integer(c(20,10,15,5))) # integers edges <- data.frame(source=c("node 0","node 0","node 0","node 2"), target=c("node 1","node 2","node 3","node 3"), interaction=c("inhibits","interacts", "activates","interacts"), # optional weight=c(5.1,3.0,5.2,9.9)) # numeric createNetworkFromDataFrames(nodes,edges)
If the last createNetworkFromDataFrames() command is repeated ten times there will be one or more cases where the edge "shared name" doesn't match the edge "name" or the nodes and edges it links. (It doesn't seem to matter if the network name is changed each time so the name isn't duplicated.) This becomes a problem when we map colors and widths to edges based on their "interaction" and "Weight" because they are wrongly assigned. For example, we make "phosphorylation" edges red and "positive correlation" yellow and if they are mixed up the network becomes meaningless. (Alex suggested working with edge SUIDs but I don't know how to do that.) The error rate in a test case we sent to Alex (tables pasted here) with 223 edges and 112 nodes varied but was typically 20-30%
The function below will get rid of bad networks. I suggest, until this problem is understood and solved, that an error checking step like this be incorporated into createNetworkFromDataFrames().
This error has been reproduced on three computers with the following info for two of them. 1: MacOS 11.2.1 Cytoscape Version: 3.8.2 Java: 11.0.8 by Oracle Corporation CyREST version 3.11.1 R version 4.0.3 (2020-10-10) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Big Sur 10.16 RCy3_2.8.1 2: R Version 4.0.3 RStudio Version 1.4.1103 RCy3 Version 2.10.2 Cytoscape Version 3.8.1
Best wishes,
Mark
Workaround function for RCy3 glitches
delete.bad.networks <- function(){ pingtest=cytoscapePing() if (!grepl("connected", pingtest)) { print("You are NOT conncected to Cytoscape!") break } else { networks <- getNetworkList() for (i in 1:length(networks)) { edgeTable <- getTableColumns("edge", c("name", "shared name"), network=networks[i]) if(!identical(edgeTable[,1], edgeTable[,2])) { print(paste('Network', networks[i], "is bad.")) deleteNetwork(networks[i])} else { print (paste("Network", networks[i], "passes edge test.")) } } } }
edges_for_Cytoscape_test.txt nodes_for_Cytoscape_test.txt rcy3_test_networks.cys rcy3_test_script2.R edges_for_Cytoscape_test.txt nodes_for_Cytoscape_test.txt