[BioC] expression set and paired designs
David martin
vilanew at gmail.com
Mon Dec 7 14:52:41 CET 2009
Ok, so for example:
patient1 would be ID001 and ID002 for each patient in my data matrix and
then in the pData file it would be:
Sample Disease_stage celltype
ID001 normal 1
ID002 normal 2
and in the design i would have a "Disease_stage" and "Celltype"
and my deisgn would look somethink like:
Pair <- factor(phenoData$celltype)
disease <- factor(phenoData$Disease_stage)
I'll try to work it out.
thanks,
Sean Davis wrote:
> On Mon, Dec 7, 2009 at 8:35 AM, David martin <vilanew at gmail.com> wrote:
>> Hi,
>> Here is the experimental design (done by flow cytometry).
>>
>> Collect sample from a set of patients-> measure the expression for a set of
>> genes in different celltypes from the same sample.
>>
>> So the normalized data look like that:
>>
>> celltype(1 or2) geneA geneB geneC
>> patient1 1 40 20 40
>> patient1 2 37 18 41
>> patient2 1 40 19 38
>> patient2 2 38 17 39
>> patient3 1 10 19 38
>> patient3 2 20 17 39
>>
>> ....(n)
>>
>>
>> and then i have my pdata.txt.
>>
>> Sample Disease_stage
>> patient1 moderate_disease
>> patient2 severe_disease
>> patient3 normal
>>
>>
>> What i want to do is to compare the different groups and identify the genes
>> that differentially expressed between the three groups.
>> That i guess would be fine to do by bulding a proper design and runing a
>> paired t.test.
>>
>>
>> But before that I can't construct an eset object as sample names are
>> duplicates. I was wondering if i need to construct two eset objects (one for
>> celltype1 and one for celltype2) ???
>
> I would suggest thinking of a "patient" as a source for a sample, and
> not the sample itself, in the most general of terms. In other words,
> label your samples 1..2n (if you have two samples per patient) and
> then connect the sample ids with the patient ids in the phenoData of
> the ExpressionSet. Does that make sense?
>
> Sean
>
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