Hi Paul,
thank you very much for spending your time to help me. Bellow I will
try to
follow your ideas
On Tue, Oct 30, 2012 at 5:25 PM, Paul Shannon <pshannon@fhcrc.org>
wrote:
> Hi Ricardo,
>
> We might not be able to give you just what you need right away, but
your
> questions are very useful, helping us to understand what network
analysis
> needs Bioc users are coming up with.
>
> I try to answer your questions below. If I misunderstand them,
please let
> me know!
>
>
> On Oct 30, 2012, at 11:46 AM, Ricardo Silva wrote:
>
> > Hi Paul,
> >
> > thanks for answering.
> >
> > I'm already a RCytoscape user, it's very great, but I still have
to
> spend some time customizing the graphs.
> >
> > I agree with your point about kegg, but is still the most
comprehensive
> (reactome:
http://www.reactome.org/stats.html and kegg:
>
http://www.kegg.jp/kegg/docs/statistics.html)
> >
> > I'm trying to associate compound information with biochemical
> (reactions, pathways...) information, to analyse mass spectrometry
data,
> now I'm analyzing Trypanosoma brucei data.
>
> Am I right in thinking that what KEGG calls 'compound' is what
others call
> metabolites, or 'small molecules'?
>
yes, that's right, there are techniques that allow us to sample mass
of
organic molecules, and we can try to match them directly to compound
masses.
>
> >
> > I've tried some alternatives to KEGG myself, I've translated every
> pathway of an organism to wikipathways format
>
http://www.pathvisio.org/wiki/KeggConverter. But, the division of
> pathways is too artificial in many cases, I need to know how a node
links
> with every all.
>
> I tend to agree about the artificiality of pathways. Would this be
> remedied by treating reactions as the fundamental abstraction:
metabolic
> reactions, phosphorylation, protein-DNA binding, transcription,
etc?
> These could then be flexibly and selectively aggregated into
pathways when
> that abstraction is useful, and according to the needs of the
analysis.
>
>
>
> >
> > Now, I would like to have a graph with all information I can get
like
>
http://www.kegg.jp/kegg-bin/show_pathway?map01100, but, only with
> reactions described for a given organism.
>
> You probably know this already, but to view:
>
>
>
http://www.kegg.jp/kegg-bin/show_pathway?org_name=tbr&mapno=01100&ma
pscale=0.35&show_description=hide
>
> To download and then convert the KGML to a graphNEL
>
> library(KEGGgraph)
> tmp <- tempfile ()
> retrieveKGML('01100', organism='tbr', destfile=tmp, method='auto')
> g.tbr <- parseKGML2Graph (tmp, expandGenes=TRUE)
>
Thanks for the advice, that's what I've tried in the code of my first
message. KGML has two graphs, one that KEGG calls "relation"
(connection
between genes) and the one I'm interested in, the "reactions" between
the
compounds/metabolites,
so, from my code, I'm using KEGGpathway2reactionGraph, but, it seems
to
miss some nodes, that is, compounds that I can retrieve from KEGG API,
that
are not in the graph. I will quantify and qualify them later to be
more
specific.
>
> We may be able to extract some (maybe a lot) of the useful public
data
> from KEGG for easy use in Bioconductor. I am experimenting with
that this
> week, as chance would have it. (With no assessment yet of how hard,
and
> how useful, it will be.)
>
> >
> > It will be perfect to have this graph on R, with all the
information
> easy translated to Cytoscape. Cytoscape already has plugins to read
KGML,
> is it possible to merge graphs and export them back to R?
>
> Sure. This RCy method does exactly that:
>
> cw <- existing.CytoscapeWindow ('my merged graph',
> copy.graph.from.cytoscape.to.R=TRUE)
>
> Then
>
> g.merged <- getGraph (cw)
>
> That's very nice, I've missed that, the last time I read Rcytoscape
vignette, sorry, I will try it later.
> I hope this helps.
>
> - Paul
>
I really appreciate, thanks
Ricardo
>
>
>
> >
> > Cheers
> >
> > Ricardo
> >
> > On Tue, Oct 30, 2012 at 4:01 PM, Paul Shannon <pshannon@fhcrc.org>
> wrote:
> > Hi Ricardo,
> >
> > A few quick observations, and then an invitation to further
discussion.
> >
> > 1) KEGG has played a central role in bioinformatics for years but
now,
> it seems, it no longer can. None of the publicly available data has
been
> updated since KEGG 'went private' in the summer of 2011.
> >
> > 2) Here in Seattle, I -- and others elsewhere -- are exploring
REACTOME,
> Nature/NCI and WikiPathways as ongoing sources of metabolic (and
other)
> network graphs.
> >
> > 3) The RCytoscape package
>
http://bioconductor.org/packages/2.11/bioc/html/RCytoscape.html is
> designed to make R/Cytoscape network visualization easy. It comes
with
> lots of documentation and a website:
>
http://rcytoscape.systemsbiology.net/versions/current/index.html
> >
> > Which metabolic pathway are you working on? Perhaps I can use it
as a
> case study in my exploration of KEGG alternatives.
> >
> > Best,
> >
> > - Paul
> >
> >
> > On Oct 30, 2012, at 10:47 AM, Ricardo Silva wrote:
> >
> > > Hello all,
> > >
> > > I've been trying to create the most complete possible compound
map for
> > > an organism, and KEGGgraph was the best approach until now.
> > >
> > > Someone already worked with graphs metabolites in R?
> > >
> > > I have a doubt if the KEGGgraph merging process can miss nodes,
that's
> > > because,
> > > looking at the compounds in each reaction:
> > >
> > > read.delim(paste("
http://rest.kegg.jp/link/reaction/", orgId,
> > > sep=""),header=FALSE)
> > > read.delim(paste("
http://rest.kegg.jp/link/compound/", orgId,
> > > sep=""),header=FALSE)
> > >
> > > where orgId is the tree letter organism code, I have a set of
compounds
> > > different than the one retrivied bellow:
> > >
> > > When I use the mergeGraphs function:
> > >
> > >
> > > for (i in 1:length(allPath)) {
> > > retrieveKGML(allPath[i], organism=orgId, destfile=tmp,
> > > method="wget", quiet=TRUE)
> > > lg[[i]] <- parseKGML(tmp)
> > > if(length(lg[[i]]@reactions)) lt[[i]] <-
> > > KEGGpathway2reactionGraph(lg[[i]])
> > > }
> > > lt <- lt[!unlist(lapply(lt, is.null))]
> > > merged <- mergeGraphs(lt)
> > >
> > > where allPath represents all organism pathways in kegg.
> > >
> > > the nodes of obtained graph are different from those obtained
asking
> > > compounds by reaction, m'I missing something?
> > >
> > > Additionally, someone know's an automated way to export the
graph to
> > > cytoscape, or even to write a KGML?
> > >
> > > Thanks in advance
> > >
> > > Ricardo
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > Bioconductor mailing list
> > > Bioconductor@r-project.org
> > >
https://stat.ethz.ch/mailman/listinfo/bioconductor
> > > Search the archives:
>
http://news.gmane.org/gmane.science.biology.informatics.conductor
> >
> >
>
>
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