Hello Gordon,

Again, thank you for your recent help on this. As I tyold you, I managed to
un my analysis. However, I get the impression that the model is adjusting
propoerly.

I want to run Cases vs Controls controling for differences beteween brain
fregions but IM getting ~300- associated p values after correcting for
multiple testing. The code im using is:

library(limma)
library(edgeR)
x <- read.delim("/myexpressiondata.txt",row.names="Symbol")
group <- factor
(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0))
d <- DGEList(counts=x,group=group)
cpm.d <- cpm(d)
d <- d[rowSums(cpm.d > 1) >= 4, ]
d <- calcNormFactors(d)
region <-
factor(c("Caudate","Frontal","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal","Caudate","Frontal","Hippocampus","Putamen","Temporal"))
design <- model.matrix(~region+d$samples$group)
d <- estimateGLMCommonDisp(d, design,verbose=TRUE)
d <- estimateGLMTrendedDisp(d, design)
d <- estimateGLMTagwiseDisp(d, design)
glmfit.tagwise.d <- glmFit(d,design,dispersion=d$tagwise.dispersion)
lrt.tagwise.d <- glmLRT(glmfit.tagwise.d)
topTags(lrt.tagwise.d)



Thanks!
On Thu, Sep 13, 2012 at 2:43 AM, Gordon K Smyth <smyth@wehi.edu.au> wrote:

> Dear Javier,
>
> This error has been discused a number of times on this list.  The solution
> is to upgrade edgeR to the current devel version.
>
> Also please see the Bioconductor posting guide:
>
>  http://www.bioconductor.org/**help/mailing-list/posting-**guide/<http://www.bioconductor.org/help/mailing-list/posting-guide/>
>
> Best wishes
> Gordon
>
>  Date: Tue, 11 Sep 2012 13:04:55 +0200
>> From: Javier Sim?n-S?nchez <simonsanchezj@gmail.com>
>> To: bioconductor@r-project.org
>> Subject: [BioC] edgeR GLM error
>>
>> Hello,
>> My name is Javier Simón Seanchez and I'm a post-doc at the VUmc in
>> Amsterdam.
>>
>> The reason of this e-mail is that im running edgeR in an expression
>> dataset
>> and getting the following error when calculating the GLM common
>> dispersion:
>>
>> *Error in beta[k, ] <- betaj[decr, ] :
>>  NAs are not allowed in subscripted assignments
>> *
>>
>> Im running cases versus controls and I want to modulate for different
>> tissues. How can I overcome this error?
>>
>> Thanks a lot in advance
>>
>> --
>> Javier Simon-Sanchez
>>
>>
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