[BioC] Gene Ontology relationships

[davidl at unr.nevada.edu]

Hello Seth,

     Thank you very much for the response.  I read the help pages for those
functions and they sound like they are exactly what I was looking for.  I ran
into a problem actually using termGraphs, however.  This may be something
simple and stupid but I am having trouble identifying what the problem is. 
This is the relevant part of my workflow and the resulting error message:

> paramsFvBup<-new("GOHyperGParams", geneIds=llsupFvB,
universeGeneIds=llsUniversFvB, annotation="mouse4302", ontology="BP",
pvalueCutoff=0.05, conditional=TRUE, testDirection="over")
> FvBupOverBP<-hyperGTest(paramsFvBup)
> htmlReport(FvBupOverBP, file="test.html")
#That all worked fine and the table looks good
> termGraphs(FvBupOverBP,pvalue=0.05, use.terms=TRUE)
Error in "names<-"(`*tmp*`, value = c(NA_character_, NA_character_,
NA_character_,  :
        'value' argument must specify unique names

R version 2.5.0 (2007-04-23)
GOstats version 2.2.3

I tried using different combinations of all the possible arguments but I kept
getting the same error.  I apologize if this is something simple that I should
have caught.  Again, thank you very much for all your help,

Dave


Quoting Seth Falcon <sfalcon at fhcrc.org>:

> Hi Dave,
>
> davidl at unr.nevada.edu writes:
> >     I was just wondering if there is an easy way to start with a list of
> Gene
> > Ontology terms and to end with an interpretable map of their
> > inter-relationships.
>
> Have a look at the help pages for these functions in GOstats (you
> will need the latest release version compatible with R-2.5.0):
>
>      termGraphs
>      inducedTermGraph
>      plotGOTermGraph
>      GOGraph
>
> I think termGraphs would be a good place to start and then to see
> about visualizing each connected component.  One of the challenges is
> that it becomes difficult to visualize graphs with many nodes as the
> labels get too small rather quickly.
>
> I'm curous to know if these help and if you have suggestions of how
> they could be more useful.
>
> + seth
>
> --
> Seth Falcon | Computational Biology | Fred Hutchinson Cancer Research Center
> http://bioconductor.org
>