Dear all, I am wondering is there any function available in Bioconductor or other R libraries for detecting network communities in protein-protein interaction graphs (where a "network community" is defined as a part of a network that has more internal connections than to the rest of the network)? I will be very grateful for any advice. Regards, Avril Avril Coghlan University College Cork, Ireland [[alternative HTML version deleted]]

On 1/18/10 9:10 AM, Coghlan, Avril wrote: > I am wondering is there any function available in Bioconductor or other > R libraries for detecting network communities in protein-protein > interaction graphs (where a "network community" is defined as a part of > a network that has more internal connections than to the rest of the > network)? You might find relevant packages using these listings: http://bioconductor.org/packages/2.5/GraphsAndNetworks.html http://bioconductor.org/packages/2.5/Proteomics.html In particular, perhaps ppiStats has something of interest to you. + seth -- Seth Falcon Bioconductor Core Team | FHCRC

If you can convert your network to igraph graph object, I think you can do that. Check function "community" in igraph manual page. http://igraph.sourceforge.net/doc/R/community.structure.html Gilbert On 1/18/10 11:10 AM, "Coghlan, Avril" <a.coghlan at="" ucc.ie=""> wrote: > Dear all, > > > > I am wondering is there any function available in Bioconductor or other > R libraries for detecting network communities in protein-protein > interaction graphs (where a "network community" is defined as a part of > a network that has more internal connections than to the rest of the > network)? > > > > I will be very grateful for any advice. > > > > Regards, > > Avril > > > > Avril Coghlan > > University College Cork, Ireland > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor >

Hi All, hi Avril, On Mon, Jan 18, 2010 at 05:10:53PM -0000, Coghlan, Avril wrote: > Dear all, > I am wondering is there any function available in Bioconductor or other > R libraries for detecting network communities in protein-protein > interaction graphs (where a "network community" is defined as a part of > a network that has more internal connections than to the rest of the > network)? Can I just point out that 'network community detection' is exactly the same thing as network clustering, aka graph clustering? I wrote and maintain MCL, a generic cluster algorithm for graphs, which has been used for PPI graphs by various people I believe (see e.g. http://www.biomedcentral.com/1471-2105/7/488/abstract). Someone else mentioned igraph. There is code available in igraph to call MCL externally, see http://igraph.wikidot.com/community-detection-in-python Quite likely they implement other (popular) algorithms as well. Rob Gevers wrote R code to call MCL externally from R: http://www.rob-gevers.com/pmwiki.php/MclR/MclR These two solutions require installing MCL separately from http://micans.org/mcl An important aspect in clustering PPI graphs is, I believe, the quality of the input. I recommend preprocessing it to make sure that there are no nodes of very high degree. One approach is to use a k-nearest neighbour approach, keeping edges only if they are in the list of top k edges (according to similarity) for both of the incident nodes. MCL has additional options to facilitate this kind of processing. Should you be interested, I would be glad to help. I have not used Rob's code myself, but it looks nice in that it is simple, uses the prefered exchange format, and should be easily modifiable to accommodate for example passing of additional MCL parameters. I'd be glad to hear any feedback or suggestions (which I'll try to pass on). best, Stijn -- Stijn van Dongen >8< -o) O< forename pronunciation: [Stan] EMBL-EBI /\\ Tel: +44-(0)1223-492675 Hinxton, Cambridge, CB10 1SD, UK _\_/ http://micans.org/stijn