Hi David,

Thanks for the suggestion. That sounds exactly like what I want. I tried to install KEGGgraph, but got some errors:

> source("http://www.bioconductor.org/biocLite.R")
Warning messages:
1: In safeSource() : Redefining ‘biocinstall’
2: In safeSource() : Redefining ‘biocinstallPkgGroups’
3: In safeSource() : Redefining ‘biocinstallRepos’
>     biocLite(KEGGgraph)
Running biocinstall version 2.3.13 with R version 2.8.1 
Your version of R requires version 2.3 of Bioconductor.
Error in install.packages(pkgs = pkgs, repos = repos, dependencies = dependencies,  : 
  object "KEGGgraph" not found


Am I doing something wrong?

thanks!

PS: My session info is:


> sessionInfo()
R version 2.8.1 (2008-12-22) 
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] splines   tools     stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] RankAggreg_0.3-1    gplots_2.6.0        gmodels_2.14.1      gtools_2.5.0-1      gdata_2.4.2         Rgraphviz_1.14.1   
 [7] EBImage_2.6.0       KEGGSOAP_1.16.0     SSOAP_0.4-8         RCurl_0.94-0        geneplotter_1.20.0  lattice_0.17-20    
[13] XML_1.99-0          biomaRt_1.16.0      GOstats_2.8.0       Category_2.8.4      RBGL_1.18.0         annotate_1.20.1    
[19] xtable_1.5-4        graph_1.20.0        PFAM.db_2.2.5       GO.db_2.2.5         KEGG.db_2.2.5       org.Mm.eg.db_2.2.6 
[25] org.Hs.eg.db_2.2.6  RSQLite_0.7-1       DBI_0.2-4           AnnotationDbi_1.4.3 genefilter_1.22.0   survival_2.34-1    
[31] affy_1.20.2         Biobase_2.2.2      

loaded via a namespace (and not attached):
[1] affyio_1.10.1        cluster_1.11.12      grid_2.8.1           GSEABase_1.4.0       KernSmooth_2.22-22   MASS_7.2-45         
[7] preprocessCore_1.4.0 RColorBrewer_1.0-2  
> 





________________________________
From: Jitao David Zhang <davidvonpku@gmail.com>

Sent: Tuesday, May 5, 2009 1:21:04 PM
Subject: Re: [BioC] KEGG: gene ids for nodes in a pathway

Hi Tim,

  Using KEGGgraph package may solve the problem. As an example:

    library(KEGGgraph)
    
    // use human MAPK pathway as an example
    xfile <- system.file("/extdata/hsa04010.xml", package="KEGGgraph")
    p <- parseKGML(xfile)
    pNodes <- nodes(p)

    displayNames <- sapply(pNodes, getDisplayName)
    geneids <- sapply(pNodes, function(x) translateKEGG2GeneID(getName(x)))

    The displayNames now contain the labels (the visible names of the nodes), while the geneids are the EntrezGeneID (in human case) of the genes contained in that node.

    To install KEGGgraph, just type

    source("http://www.bioconductor.org/biocLite.R")
    biocLite(KEGGgraph)

    Best wishes,
David




Hi,

I wanted a list of genes for a particular pathway arranged nodewise. For example, if I select the Jak-stat pathway ("http://www.genome.jp/kegg/pathway/hsa/hsa04630.html"), how do I get the entrez ids of genes associated with the node 'STAT' ? Currently, I use the following code:

x <- toTable(org.Hs.egPATH)

and then select genes associated with a particular pathway (e.g. for Jak-stat: "04630") . But this gives the entire set of genes associated with the pathway. Is there a way to get the entrez ids of the genes associated with each of the nodes ('JAK', 'STAT', 'STAM','PIAS' etc.) in the pathway?

thanks!




       [[alternative HTML version deleted]]

_______________________________________________
Bioconductor mailing list
Bioconductor@stat.math.ethz.ch
https://stat.ethz..ch/mailman/listinfo/bioconductor
Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor



-- 
Jitao David Zhang
Computational Biology Ph.D.
Division of Molecular Genome Analysis
DKFZ, Heidelberg D-69120, Germany

http://sites.google.com/site/jazzydevzoo/



      
	[[alternative HTML version deleted]]

