[BioC] edgeR: design matrix for different condition
KJ Lim
jinkeanlim at gmail.com
Mon Jul 30 13:01:07 CEST 2012
Dear Prof Gordon,
Good day.
I have read the section 8.5 of the Limma manual as you suggested in
previous emails. Thanks.
If I understand you correctly, you would suggest me to carry out my DE
analysis with limma package if I would like to learn the which genes
are express in treeHS compare to treeLS (vice versa) at i.e. 24H.
May I ask how can I generate the EList, "eset", in order to fit in the
linear model as mentioned in the limma manual
fit <- lmFit(eset, design)
fit <- eBayes(fit)
Please correct me if I'm wrong.
Thank you very much for your time and help.
Best regards,
KJ Lim
On 27 July 2012 02:31, Gordon K Smyth <smyth at wehi.edu.au> wrote:
> Dear KJ Lim,
>
> Thanks for the rephrasing, which is clearer. I would have liked you to
> mention however whether you read the documentation that I refered you do.
>
>
> On Thu, 26 Jul 2012, KJ Lim wrote:
>
>> Dear Prof Gordon,
>>
>> Good day. Thanks for your prompt replied.
>>
>> Please allow me to rephrase my previous question.
>>
>> This model, ~tree+treat, is assumed effect of the time of treatment
>> will be the same irrespective of genotype.
>
>
> Yes, this model makes that assumption.
>
>
>> Thus, test for the coef=3 will gives me the differential expression at 96H
>> irrespective of genotype.
>
>
> Actually coef=3 refers to 24H, according to the design matrix in your
> original email. A test for coef=3 would test for DE at 24H vs 0H,
> irrespective of genotype. But only if the assumption mentioned above is
> true, which is unlikely given the rest of your email.
>
>
>> I would like to learn the differential expression of treeHS vs treeLS
>> at specific time points i.e. 24H or if possible across the whole time
>> points. Should I fit my model as
>>
>> model A: ~tree*treat OR model B: ~tree+tree:treat ?
>
>
> These models are equivalent, so it is just a matter of convenience which one
> you use, as I tried to explain in the limma documentation I refered you to.
>
>
>> The design matrix columns of model B give:
>> "(Intercept)" "treeLS" "treeHS:treat03H" "treeLS:treat03H"
>> "treeHS:treat24H" "treeLS:treat24H" "treeHS:treat96H"
>> "treeLS:treat96H"
>>
>> Am I doing right if I fit the model B and test for the coef=3:4 to
>> learn the differential expression of treeHS vs treeLS at specific time
>> points i.e. 03H? Does this test could tells me which set of genes
>> up/down-regulated in treeLS or treeHS?
>
>
> Yes. Coef 3 tests for a 3H effect in HS. Coef 4 tests for a 3H in LS. So
> testing for both coefficients coef=3:4 tests for a 3H effect in either
> treeLS or treeHS.
>
> Best wishes
> Gordon
>
>
>> I'm not good in statistic and I'm learning, kindly please correct me
>> if I'm wrong.
>>
>> Thank you very much for your time and suggestion.
>>
>> Best regards,
>> KJ Lim
>>
>>
>>
>>
>> On 26 July 2012 03:39, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>>>
>>>
>>> Dear KJ Lim,
>>>
>>> I don't quite understand your question, because you seem to be asking for
>>> something that isn't a test for differential expression, which is what edgeR
>>> does. You question "I would like to learn the genes are express in treeHS
>>> but not treeLS and vice versa" seems to be about absolute expression levels.
>>> edgeR doesn't test for genes that are not expressed in particular
>>> conditions.
>>>
>>> I'll refer you to the limma section on interaction models in case that
>>> helps, see Section 8.5 of:
>>>
>>>
>>> http://bioconductor.org/packages/2.11/bioc/vignettes/limma/inst/doc/usersguide.pdf
>>>
>>> Setting up a design matrix is the same for edgeR as it is for limma.
>>>
>>> Best wishes
>>> Gordon
>>>
>>>> Date: Tue, 24 Jul 2012 17:12:00 +0300
>>>> From: KJ Lim <jinkeanlim at gmail.com>
>>>> To: Bioconductor mailing list <bioconductor at r-project.org>
>>>> Subject: [BioC] edgeR: design matrix for different condition
>>>>
>>>> Dear the edgeR community,
>>>>
>>>> Good day.
>>>>
>>>> I'm analyzing my RNA-Seq experiment with edgeR. My study has 2
>>>> different genotypes (treeHS, treeLS) and time of treatment (0H, 3H,
>>>> 24H, 96H).
>>>>
>>>> I first assumed that the treatment effect will be the same for each
>>>> genotype and I have the design matrix as:
>>>>
>>>> design <- model.matrix(~tree+treat)
>>>>
>>>>> design
>>>>
>>>>
>>>> (Intercept) treat03H treat24H treat96H treeLS
>>>> 1 1 0 0 0 0
>>>> 2 1 0 0 0 0
>>>> 3 1 1 0 0 0
>>>> 4 1 1 0 0 0
>>>> 5 1 0 1 0 0
>>>> 6 1 0 1 0 0
>>>> 7 1 0 0 1 0
>>>> 8 1 0 0 1 0
>>>> 9 1 0 0 0 1
>>>> 10 1 0 0 0 1
>>>> 11 1 1 0 0 1
>>>> 12 1 1 0 0 1
>>>> 13 1 0 1 0 1
>>>> 14 1 0 1 0 1
>>>> 15 1 0 0 1 1
>>>> 16 1 0 0 1 1
>>>>
>>>> I used coef=4 to test for the differential expressions between treeHS
>>>> and treeLS within the time of treatment, coef=3 to learn the
>>>> differential expressions in 2 genotypes at time of treatment 96H.
>>>>
>>>> ** I would like to learn the genes are express in treeHS but not
>>>> treeLS and vice versa at certain time of treatment let's say 24H or
>>>> across the whole time of treatment, should I have the design matrix as
>>>> below or more steps I need to do?
>>>>
>>>> design <- model.matrix(~tree*treat)
>>>>
>>>> Kindly please light me on this. I appreciate very much for your help and
>>>> time.
>>>>
>>>> Have a nice day.
>>>>
>>>> Best regards,
>>>> KJ Lim
>
>
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