Hi Paul, you can obtain the induced graph generated by the printGraph / showSigOfNodes as follows: g <- showSigOfNodes(GOdata, score(myResult), firstSigNodes = 5) g$dag ## to obtain the adjacency matrix one can do: adjMat <- as(g, "matrix") ## g$dag is a "graphNEL" object and one can use this class methods plot(g$dag) adj(g, whichGO) Alternatively you can obtain the induced graph without the use of the showSigOfNodes function: whichGO <- names(sort(score(myResult)))[1:5] g <- reverseArch(inducedGraph(graph(GOdata), whichGO)) g Hope this helps. Best regards, Adrian On Thu, Dec 30, 2010 at 11:09 PM, Paul Rigor <pryce at="" ucla.edu=""> wrote: > Hi gang, > > I was wondering if there's anyway to obtain the adjacency list of matrix of > the induced go graphs, eg, the graphs generated by the printGraph function? > > Thanks, > Paul > > On Wed, Dec 22, 2010 at 3:21 AM, Paul Rigor <pryce at="" ucla.edu=""> wrote: > >> Thank you, this works quite well. ?I wish topGO had a prettier way of >> printing out the results similar to GOstats, though. >> >> Cheers, >> Paul >> >> >> On Sun, Dec 19, 2010 at 2:59 PM, Valerie Obenchain <vobencha at="" fhcrc.org="">wrote: >> >>> Hi Paul, >>> >>> >>> On 12/17/10 13:41, Paul Rigor wrote: >>> >>>> ?Hello, >>>> >>>> So I'm working on extracting IDs from a topGO result object. I have a >>>> list of terms ranked by p values (using classic fisher test). However, >>>> does the result object >>>> contain indices to the original list of gene ids per go term? The >>>> documentation was a bit unclear. >>>> >>>> Using the printGenes function and specifying the top ranked GO terms, >>>> I'd like to only pull the genes from my gene list, not from the entire >>>> GO annotation table, which seems to be the default behavior for this >>>> function. >>>> >>>> >>> Using the example from the topGO vignette, >>> >>> ? ?sampleGOdata <- new("topGOdata", description = "Simple session", >>> ontology = "BP", >>> ? ? ? ? allGenes = geneList, geneSel = topDiffGenes, nodeSize = 10, annot >>> = annFUN.db, >>> ? ? ? ? affyLib = affyLib) >>> >>> ? ?resultFisher <- runTest(sampleGOdata, algorithm = "classic", statistic >>> = "fisher") >>> >>> >>> Create a map of geneIDs to GO terms, >>> >>> ? ?ann.genes <- genesInTerm(sampleGOdata) >>> ? ?str(ann.genes) >>> >>> Select a few GO terms from the Fisher analysis (you could sort these first >>> or ...), >>> >>> ? ? fisher.go <- names(score(resultFisher))[1:5] >>> ? ? fisher.ann.genes <- genesInTerm(sampleGOdata, whichGO=fisher.go) >>> ? ? fisher.ann.genes >>> >>> The fisher.ann.genes list give you the ?gene ID / GO term mapping subset >>> on the GO terms from the Fisher analysis. You can also use printGenes on >>> this subset of GO terms, >>> >>> ? ?ft <- printGenes(sampleGOdata, whichTerms=fisher.go, >>> chip="hgu95av2.db") >>> >>> >>> >>> Valerie >>> >>> ?Thanks, >>>> Paul >>>> >>>> ? ? ? ?[[alternative HTML version deleted]] >>>> >>>> _______________________________________________ >>>> Bioconductor mailing list >>>> Bioconductor at r-project.org >>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>> Search the archives: >>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>> >>>> >>> >>> >> > > ? ? ? ?[[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >

Thanks Adrian, These tips have been very helpful. Cheers, Paul On Tue, Jan 4, 2011 at 3:24 AM, Adrian Alexa <adrian.alexa@gmail.com> wrote: > Hi Paul, > > you can obtain the induced graph generated by the printGraph / > showSigOfNodes as follows: > > g <- showSigOfNodes(GOdata, score(myResult), firstSigNodes = 5) > g$dag > > ## to obtain the adjacency matrix one can do: > adjMat <- as(g, "matrix") > > ## g$dag is a "graphNEL" object and one can use this class methods > plot(g$dag) > adj(g, whichGO) > > Alternatively you can obtain the induced graph without the use of the > showSigOfNodes function: > > whichGO <- names(sort(score(myResult)))[1:5] > g <- reverseArch(inducedGraph(graph(GOdata), whichGO)) > g > > > Hope this helps. > > Best regards, > Adrian > > > > On Thu, Dec 30, 2010 at 11:09 PM, Paul Rigor <pryce@ucla.edu> wrote: > > Hi gang, > > > > I was wondering if there's anyway to obtain the adjacency list of matrix > of > > the induced go graphs, eg, the graphs generated by the printGraph > function? > > > > Thanks, > > Paul > > > > On Wed, Dec 22, 2010 at 3:21 AM, Paul Rigor <pryce@ucla.edu> wrote: > > > >> Thank you, this works quite well. I wish topGO had a prettier way of > >> printing out the results similar to GOstats, though. > >> > >> Cheers, > >> Paul > >> > >> > >> On Sun, Dec 19, 2010 at 2:59 PM, Valerie Obenchain <vobencha@fhcrc.org> >wrote: > >> > >>> Hi Paul, > >>> > >>> > >>> On 12/17/10 13:41, Paul Rigor wrote: > >>> > >>>> Hello, > >>>> > >>>> So I'm working on extracting IDs from a topGO result object. I have a > >>>> list of terms ranked by p values (using classic fisher test). However, > >>>> does the result object > >>>> contain indices to the original list of gene ids per go term? The > >>>> documentation was a bit unclear. > >>>> > >>>> Using the printGenes function and specifying the top ranked GO terms, > >>>> I'd like to only pull the genes from my gene list, not from the entire > >>>> GO annotation table, which seems to be the default behavior for this > >>>> function. > >>>> > >>>> > >>> Using the example from the topGO vignette, > >>> > >>> sampleGOdata <- new("topGOdata", description = "Simple session", > >>> ontology = "BP", > >>> allGenes = geneList, geneSel = topDiffGenes, nodeSize = 10, > annot > >>> = annFUN.db, > >>> affyLib = affyLib) > >>> > >>> resultFisher <- runTest(sampleGOdata, algorithm = "classic", > statistic > >>> = "fisher") > >>> > >>> > >>> Create a map of geneIDs to GO terms, > >>> > >>> ann.genes <- genesInTerm(sampleGOdata) > >>> str(ann.genes) > >>> > >>> Select a few GO terms from the Fisher analysis (you could sort these > first > >>> or ...), > >>> > >>> fisher.go <- names(score(resultFisher))[1:5] > >>> fisher.ann.genes <- genesInTerm(sampleGOdata, whichGO=fisher.go) > >>> fisher.ann.genes > >>> > >>> The fisher.ann.genes list give you the gene ID / GO term mapping > subset > >>> on the GO terms from the Fisher analysis. You can also use printGenes > on > >>> this subset of GO terms, > >>> > >>> ft <- printGenes(sampleGOdata, whichTerms=fisher.go, > >>> chip="hgu95av2.db") > >>> > >>> > >>> > >>> Valerie > >>> > >>> Thanks, > >>>> Paul > >>>> > >>>> [[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 > >>>> > >>>> > >>> > >>> > >> > > > > [[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 > > > [[alternative HTML version deleted]]