[BioC] EdgeR: ANOVA-like analysis

[Gordon K Smyth]

On Fri, 24 Jun 2011, Christian M. Probst wrote:

> 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?

Options to functions are described on the help page for that function so, 
no, there is not somewhere else to look.

> 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".

glmFit doesn't use adjusted counts.  It uses the original counts that you 
input.

Best wishes
Gordon

> Thanks in advance.
>
> Christian
> On Wed, Jun 22, 2011 at 9:16 PM, Gordon K Smyth <smyth at 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 at fiocruz.br>
>>> To: bioconductor at 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>
>>>
>>
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>> --
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>
>
>
> -- 
> 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
> Curriculum Lattes: http://lattes.cnpq.br/9371475697752743
>