[BioC] link to KEGG
michael watson (IAH-C)
michael.watson at bbsrc.ac.uk
Mon Feb 8 17:39:38 CET 2010
http://bioinformatics.iah.ac.uk/sample-code
-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Marcos Pinho
Sent: 08 February 2010 13:22
To: Gilbert Feng; bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] link to KEGG
Dear Gilbert,
thank you so much for your posting. I got really interested in learning how
to use the package GeneAnswers, but still find somewhat challenging to
navigate in R from my gene list to geneanswer. Please see below my sension
info. Any help would be greatly appreciated!
regards,
Marcos B. Pinho
Programa de Engenharia Química - PEQ
Laboratório de Engenharia de Cultivos Celulares- LECC
Universidade Federal do Rio de Janeiro - UFRJ
Instituto Nacional de Câncer - INCA
Rio de Janeiro - Brasil
Welcome to Bioconductor
Vignettes contain introductory material. To view, type
'openVignette()'. To cite Bioconductor, see
'citation("Biobase")' and for packages 'citation(pkgname)'.
> library(tkWidgets)
Loading required package: widgetTools
Loading required package: tcltk
Loading Tcl/Tk interface ... done
Loading required package: DynDoc
> data=ReadAffy(widget=TRUE)
> library(gcrma)
Loading required package: matchprobes
Loading required package: splines
> eset=gcrma(data)
Adjusting for optical effect....Done.
Computing affinities.Done.
Adjusting for non-specific binding....Done.
Normalizing
Calculating Expression
> library(genefilter)
Loading required package: survival
> library (hgu133plus2.db)
Loading required package: AnnotationDbi
Loading required package: DBI
> esetF = nsFilter (eset, require.entrez=TRUE,remove.dupEntrez=TRUE,
feature.exclude="^AFFX",var.cutof=0.5)$eset
> design = model.matrix(~factor(rep(1:2,each=2)))
> colnames(design)=c("K562", "Lucena")
> design
K562 Lucena
1 1 0
2 1 0
3 1 1
4 1 1
attr(,"assign")
[1] 0 1
attr(,"contrasts")
attr(,"contrasts")$`factor(rep(1:2, each = 2))`
[1] "contr.treatment"
> library(limma)
> fit =lmFit (esetF, design)
> fit2=eBayes(fit)
> library(annotate)
Loading required package: xtable
Attaching package: 'xtable'
The following object(s) are masked from package:widgetTools :
label
> fit2$genes$Symbol=getSYMBOL(fit2$genes$ID, "hgu133plus2")
> fit2$genes$GeneName <- unlist(mget(fit$genes$ID, hgu133plus2GENENAME))
> fit2$genes$EG <- getEG(fit2$genes$ID, "hgu133plus2")
> topTable(fit2, coef=2)
ID Symbol
5253 209993_at ABCB1
3378 1553436_at MUC19
9828 206488_s_at CD36
6995 222392_x_at PERP
8973 210603_at ARD1B
1412 235683_at SESN3
7573 216191_s_at TRD@
4013 202948_at IL1R1
5302 205934_at PLCL1
4061 205786_s_at ITGAM
GeneName EG
5253 ATP-binding cassette, sub-family B (MDR/TAP), member 1 5243
3378 mucin 19, oligomeric 283463
9828 CD36 molecule (thrombospondin receptor) 948
6995 PERP, TP53 apoptosis effector 64065
8973 ARD1 homolog B (S. cerevisiae) 84779
1412 sestrin 3 143686
7573 T cell receptor delta locus 6964
4013 interleukin 1 receptor, type I 3554
5302 phospholipase C-like 1 5334
4061 integrin, alpha M (complement component 3 receptor 3 subunit) 3684
logFC AveExpr t P.Value adj.P.Val B
5253 8.167898 6.410285 28.41936 1.387084e-06 0.008649451 5.223275
3378 7.512443 6.097913 25.70956 2.249499e-06 0.008649451 4.992571
9828 7.318355 6.081049 22.79634 4.015521e-06 0.008649451 4.678934
6995 6.047929 6.736659 20.28712 7.035669e-06 0.008649451 4.336022
8973 6.088776 5.773605 20.23547 7.122355e-06 0.008649451 4.328102
1412 6.589716 5.620394 20.17661 7.222719e-06 0.008649451 4.319030
7573 -6.153962 5.640399 -19.71517 8.071494e-06 0.008649451 4.246141
4013 -6.231328 5.580407 -19.61010 8.281240e-06 0.008649451 4.229097
5302 5.836512 5.809832 19.53496 8.435274e-06 0.008649451 4.216804
4061 -6.788839 7.957034 -18.03301 1.238036e-05 0.008649451 3.951528
On Thu, Feb 4, 2010 at 4:47 PM, Gilbert Feng <g-feng at northwestern.edu>wrote:
> Hi, Marcos
>
> Please check attached sample pdf file. If that is what you want, you can
> use
> GeneAnswers to do that. The essential input is a genelist with optional
> values, like foldchange, p-value, etc. And GeneAnswers can run enrichment
> test and draw a concept-gene network with a concept-gene cross table, if
> you
> have an expression profile, to show how your genes are potentially
> connected
> to KEGG pathways. You can find examples and codes at
> http://www.bioconductor.org/packages/release/bioc/html/GeneAnswers.html
>
> Also, this attached sample pdf file is interactively generated, which means
> you can adjust the layout for your purpose.
>
> Let me know if you have any question.
>
> Thanks
>
> Gilbert
>
>
> On 2/4/10 9:39 AM, "Marcos Pinho" <pinho.microarray at gmail.com> wrote:
>
> > Dear list,
> >
> > I have search extensively old postings but could not find an easy
> > explanation on how to link my gene list generated after a diferential
> > expression analysis with limma to a kegg pathway analysis. Any help would
> be
> > greatly appreciated. Please keep in mind that I am a molecular biologist
> > that can navigate through R , but it is always a challenge, therefore
> > details and or examples are very helpful!
> >
> > cheers,
>
>
>
>
>
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