[BioC] A bug in either KEGG or KEGGSOAP?

[Carlson, Marc R]

Hi SangChui,

The discrepancy you are seeing is hard to explain from the bioconductor code for this function.  The KEGGSOAP package is basically parsing data from a service on the KEGG site.  The only code in the actual KEGGSOAP package is what is needed to talk to the SOAP services provided by KEGG.  So the fact that the function is working and producing an output means that it is unlikely that there is a bug in KEGGSOAP.  There is nothing in the KEGGSOAP package that tries to limit the number or pathways returned.  So it seems that the most likely cause for this kind of discrepancy is that the SOAP service and the KEGG website are somehow out of sync with each other.


  Marc


----- Original Message -----
From: "Sang Chul Choi" <schoi at cornell.edu>
To: bioconductor at r-project.org
Sent: Monday, January 23, 2012 11:59:21 AM
Subject: [BioC] A bug in either KEGG or KEGGSOAP?

Hi,

I am wondering if this is an old bug eighter in KEGG or KEGGSOAP (v1.28.0).  The version of R is R version 2.14.1 (2011-12-22).

I installed KEGGSOAP, and tried to list pathways.  While list.pathways lists 44, the KEGG website shows 88 pathways.

http://www.genome.jp/dbget-bin/get_linkdb?-t+pathway+gn:T00100
http://www.genome.jp/dbget-bin/www_bget?gn:T00100

Thank you,

SangChul

> source("http://www.bioconductor.org/biocLite.R")
> biocLite("KEGGSOAP")
> library(KEGGSOAP)
> y <- list.pathways("smu")
> length(y)
[1] 44

> sessionInfo()
R version 2.14.1 (2011-12-22)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] KEGGSOAP_1.28.0        BiocInstaller_1.2.1    goseq_1.6.0           
 [4] BiasedUrn_1.04         geneLenDataBase_0.99.8 RColorBrewer_1.0-5    
 [7] maptools_0.8-14        sp_0.9-93              foreign_0.8-48        
[10] xtable_1.6-0           DESeq_1.6.1            locfit_1.5-6          
[13] lattice_0.20-0         akima_0.5-7            Biobase_2.14.0        
[16] plotrix_3.3-3          GenomicRanges_1.6.4    IRanges_1.12.5    
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