[BioC] expression set and paired designs

[Naomi Altman]

What you have is a split plot design.

The whole block factor is disease severity.  The blocks are 
patients.  The subplot factor is cell type.

Since there are only 2 cell types, you can readily determine the 
disease by cell type main effect, by analyzing the differences 
between the cell types for each
patient.  However, if the main effects are also of interest, you need 
to run the split plot design ANOVA for each gene.

I am not sure whether you can do this in Limma, using patient as 
block.  If not, you should be able to do it in MAANOVA.

--Naomi

At 08:35 AM 12/7/2009, David martin 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) ???
>
>Any help would be appreciated.
>
>thanks
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111