[BioC] question_gene list from venn diagram limma function for two color array data

Thu Nov 2 18:01:55 CET 2006

lee wrote:
> Hi, Pepin and Jim
> Thank Pepin and Jim for your help. But I haven't still figured out.
> After installing affycoretools,
annaffy, Gostats and copy your code, I thought it was working but I got
the following message.
> ## error in "data frame" undefined column specified ## 

It would help if you pasted more of your R session into the email, so I 
could see where you got the error. It would also help if after you got 
the error, you typed traceback(), and then copy/pasted the ouput from 
that as well.

I am afraid I
> made a mistake somewhere. Because I am so new to this
statistic analysis area, could you help me to find what I did wrong?
Also could you tell me what exactly the program use to do the
calculation to get the number of genes? For example, "ID" for my
individual spot identification, or "Acession" for gene identification
from my annotation list.

I'm not sure what you are asking here. Are you asking how the spots are 
mapped to genes?

Best,

Jim

> Thanks again.
> 
    Sincerely, Seungmin Lee
>    
>   library(affycoretools)
> ups <- affycoretools:::makeIndices(results, "up")
> downs <- affycoretools:::makeIndices(results, "down")
>   up.genes <- lapply(ups, function(x) row.names(results)[x])
>   down.genes <- lapply(downs, function(x) row.names(results)[x])
>   
> 
> Francois Pepin <fpepin at cs.mcgill.ca> wrote:
>   Hi Jim,
> 
> you are correct, my code only looks at one contrast at a time, the same
> way that topTable does it. Your modification is needed to look at the
> intersection.
> 
> Francois
> 
> On Wed, 2006-11-01 at 14:36 -0500, James W. MacDonald wrote:
> 
>>Hi Francois,
>>
>>Francois Pepin wrote:
>>
>>>Hi Seung-Min,
>>>
>>>The differences come from the classifyTestsF. It classifies the genes
>>>based on the F statistics, rather than the B-values which topTable uses.
>>>
>>>Another way to get the information about the up genes both contrast
>>>(Jim's way should work too):
>>>
>>>fit$genes[which(results[,1]>0,] ##set to <0 for down genes
>>
>>I don't think that will work. The first column of the results matrix 
>>gives information about the genes in the first contrast only. To get 
>>both contrasts, you need results[,1] > 0 & results[,2] > 0. In any case, 
>>you have to look at both contrasts to find the genes for any given cell 
>>of the Venn diagram.
>>
>>Best,
>>
>>Jim
>>
>>
>>
>>>Please note that, unlike topTable, the list is ordered by position on
>>>the chip, not by how significant the differences are.
>>>
>>>Francois
>>>
>>>On Tue, 2006-10-31 at 16:25 -0800, lee wrote:
>>>
>>>
>>>>Hello,
>>>>I am using my two color array data. I want to know the genes that
>>>>are significantly Up or Down in both "HFEvsWT" and "SlavsWT" groups
>>>
>>>>from Venn diagram results. I also want to know the genes that are only
>>>
>>>>significantly Up or Down in one group. When I tried using the gene
>>>>list from topTable function, I got different number of genes compared
>>>>to Venn Diagram results. Thus, I want to know what are the genes after
>>>>Venndiagram analysis.
>>>>Could you help me?
>>>>Thank you so much.classifyTestsF
>>>>
>>>>Sincerely, Seungmin Lee
>>>>
>>>>
>>>>
>>>>
>>>>library(limma)
>>>>targets<-readTargets("Target4wkEnteroHFESla.txt")
>>>>f<-function(x) as.numeric(x$Flags>-99)
>>>>files<-targets[,c("FileName")]
>>>>RG<-read.maimages(files,columns=list(R="F635 Mean",G="F532 Mean",Rb="B635 Median",Gb="F532 Median"),annotation=c("Block","Row","Column","ID","Accession","Symbol"))
>>>>plotMA(RG)
>>>>RG$genes<-readGAL("meebo.gal")
>>>>RG$printer<-getLayout(RG$genes)
>>>>MA.p<-normalizeWithinArrays(RG,method="loess")
>>>>MA.pAq<-normalizeBetweenArrays(MA.p,method="Aquantile")
>>>>design<-modelMatrix(targets,ref="WT.C57.chow")
>>>>design
>>>>contrast.matrix<-cbind("HFEvsWT"=c(1,0),"SlavsWT"=c(0,1))
>>>>rownames(contrast.matrix)<-colnames(design)
>>>>contrast.matrix
>>>>fit<-lmFit(MA.pAq,design)
>>>>fit2<-contrasts.fit(fit,contrast.matrix)
>>>>fit2<-eBayes(fit2)
>>>>topTable(fit2,coef="HFEvsWT",adjust="BH")
>>>>plotMA(fit2,array=1)
>>>>topTable(fit2,coef="SlavsWT",adjust="BH")
>>>>plotMA(fit2,array=2)
>>>>results<-classifyTestsF(fit2, p.value=0.01)
>>>>summary(results)
>>>>table("HFEvsWT"=results[,1],"SlavsWT"=results[,2])
>>>>vennDiagram(results,include="up")
>>>>vennDiagram(results,include="down")
>>>>
>>>>
>>>>-----------------------------------------------------------------------
>>>>Seung-Min Lee
>>>>
>>>>graduate student
>>>>244 Morgan Hall
>>>>Molecular&Biochemical Nutrition
>>>>University of California at Berkeley
>>>>94720-3104
>>>>lab phone (510)643-2351
>>>>lab fax(510)642-0535
>>>>
>>>>
>>>>---------------------------------
>>>>
>>>>[[alternative HTML version deleted]]
>>>>
>>>>_______________________________________________
>>>>Bioconductor mailing list
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>>>>https://stat.ethz.ch/mailman/listinfo/bioconductor
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>>>>
>>>
>>>
>>>_______________________________________________
>>>Bioconductor mailing list
>>>Bioconductor at stat.math.ethz.ch
>>>https://stat.ethz.ch/mailman/listinfo/bioconductor
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>>
>>
> 
> 
> 
> 
> -----------------------------------------------------------------------
> Seung-Min Lee
> 
> graduate student
> 244 Morgan Hall
> Molecular&Biochemical Nutrition
> University of California at Berkeley
> 94720-3104
> lab phone (510)643-2351
> lab fax(510)642-0535
> e-mail address : molba076 at yahoo.com, molba076 at berkeley.edu
>  
> ---------------------------------
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-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

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