I'm relatively new to R and am trying to solve the following problem:
I work on a Windows 7 Enterprise platform with the 32bit version of R and have about 3GB of RAM on my machine. I have large-scale social network data (c. 7,000 vertices and c. 30,000 edges) which are currently stored in my SQL database. I have managed to pull this data (omitting vertex and edge attributes) into an R dataframe and then into an igraph object. For further analysis and visualization, I would now like to push this igraph into Cytoscape using RCytoscape. Currently, my approach is to convert the igraph object into an graphNEL object since RCytoscape seems to work well with this object type. (The igraph plotting functions are much too slow and lack further analysis functionality.)
Unfortunately, I always run into memory issues when running this script. It has worked previously with smaller networks though.
Does anyone have an idea on how to solve this issue? Or can you recommend any other visualization and analysis tools that work well with R and can handle such large-scale data?
It has been a while since I used Cytoscape so I am not exactly sure how to do it, but the manual states that you can use text files as input using the "Table Import" feature.
In
igraph
you can use thewrite.graph()
function to export a graph in a bunch of ways. This way you can circumvent having to convert to agraphNEL
object which might be enough to not run out of memory.