[igraph] partitioning a *weighted* undirected graph

[Lara Michaels]

Hello fellow igraphers!

I just came across igraph (the R package) and am just getting started. 

I have read the docs to find out how to import the data I have into igraph and 
have chosen to put it in 'ncol' format and then just use read.graph() as 
described here 
[http://cneurocvs.rmki.kfki.hu/igraphbook/igraphbook-foreign.html].

Now I would like to attempt some form of community detection on this dataset 
that would take into account the fact that edges are weighted and undirected. 
Is there a particular method in igraph that is especially well-suited for such 
this task? I have just started reading on the topic, but it seems that most 
algorithms were conceived to deal with unweighted graphs.

Many thanks for any help!
~lara