Many thanks, Dr. Gordon.
I have run the analysis as suggested.

Two small questions:

a) I would like to understand deeply the coef option, besides what is
described in the glmLRT help. Is there a place to look for it?

b) If I want to plot the adjusted count values that were used for the GLM
fit and LR analysis, where can I find the equivalent of $pseudo.alt for the
CR analysis? I suppose fitted.values is not the correct answer, as its sums
are not "library size equal".

Thanks in advance.

Christian
On Wed, Jun 22, 2011 at 9:16 PM, Gordon K Smyth <smyth@wehi.edu.au> wrote:

> Dear Christian,
>
> limma syntax doesn't always work in edgeR.  We will work to make them as
> analogous as we can, but generalized linear models in edgeR bring in a few
> unavoidable complications into edgeR that are not present in limma.
>
> At the moment, the contrast argument to glmLRT() must be a vector, not a
> matrix, as is explained on the help page for that function.  In future we
> will add the matrix capability, but for now you will need to perform
> F-test-like likelihood ratio tests using the coef argument instead.  This
> means that you must paramatrize your design matrix so that it contains an
> intercept column:
>
>  design <- model.matrix(~group)
>
> Then later you can use
>
>  glmLRT(..., coef=2:4)
>
> and so on.  This will do the combined test that you want on 3 df for
> differences between the 4 groups.
>
> Best wishes
> Gordon
>
> Date: Mon, 20 Jun 2011 11:12:39 -0300
>> From: "Christian M. Probst" <cprobst@fiocruz.br>
>> To: bioconductor@r-project.org
>> Subject: [BioC] EdgeR: ANOVA-like analysis
>>
>> Dear list,
>>
>> I am using edgeR to analyze a RNA-Seq dataset consisting of 4 samples
>> (groups), each with 5 biological replicates.
>>
>> I have read in the Limma manual, as it has an extensive description of
>> design models. In section 8.6, there is a description for multiple groups
>> test, and I have tried to follow the steps there. But the edgeR objects
>> are
>> distinct from the Limma, so I am stucked.
>>
>> Shortly, I want to use edgeR to identify differential expression in all
>> pair-wise comparisons of the 4 groups, as well as combine all pair-wise
>> comparisons into one F-test.
>>
>> I have used the following construction:
>>
>> deF<-glmLRT(dgecRNAF,glmFit(**dgecRNAF, mmcRNA,
>> dispersion=dgecRNAF$common.**dispersion), contrast=contrast.matrix)
>>
>> where dgecRNAF is my DGEList object, mmcRNA is my model matrix, and
>> contrast.matrix is:
>>
>> contrast.matrix
>>>
>>     Contrasts
>> Levels    A-B   A-C   A-D   B-C   B-D   C-D
>>  A       1     1     1     0     0     0
>>  B      -1     0     0     1     1     0
>>  C       0    -1     0    -1     0     1
>>  D       0     0    -1     0    -1    -1
>>
>>
>> Thanks in advance,
>>
>> --
>> Dr. Christian Macagnan Probst
>>
>> Adjunct Researcher in Public Health
>> Bioinformatics and Computational Biology Laboratory
>> Functional Genomics Laboratory
>>
>> Carlos Chagas Institute - ICC/FIOCRUZ
>> Curitiba - PR - Brasil
>>
>> Reseacher ID: http://www.researcherid.com/**rid/B-8678-2009<http://www.researcherid.com/rid/B-8678-2009>
>>
>
> ______________________________**______________________________**__________
> The information in this email is confidential and inte...{{dropped:29}}

