[BioC] Cross-comparison of independent intensities from different experiments (genepix) (sorry I don\'t know how to describe the problem better)

[Susanne Gerber [guest]]

Dear all, 
could please anyone help me with the following problem:

Experiments were performed using two color cDNA .gpr files (genepix).
We have an experimental setup with two independent time series (each of it with 4 time-points (in the following T1 - T4).

In the first time series Wildtype(WT) cells were stressed at time point zero with a certain drug and probes were taken at 4 time points afterwards. 
These probes were compared with the unstressed WT. 

In the second time series mutant-cells (MU) were treated identically and compared with the unstressed MU cell.


Here is the target file

> targets
       FileName          Cy3                       Cy5
1  13754122.gpr      WT                       WT_stress_T1
2  13754112.gpr      WT_stress_T1       WT
3  14039687.gpr      WT                       WT_stress_T2
4  13754123.gpr      WT                       WT_stress_T2
5  13754109.gpr      WT                       WT_stress_T3
6  14039055.gpr      WT_stress_T3       WT
7  14004643.gpr      WT                       WT_stress_T4
8  14039058.gpr      WT_stress_T4       WT
9  14039688.gpr      MU                       MU_stress_T1
10 13754114.gpr     MU_stress_T1       MU
11 14039061.gpr     MU                       MU_stress_T2
12 14039059.gpr     MU_stress_T2       MU
13 13754124.gpr     MU                       MU_stress_T3
14 13754115.gpr     MU_stress_T3       MU
15 14039057.gpr     MU                       MU_stress_T4
16 14039056.gpr     MU_stress_T4       MU

I was working a lot with these data and we had some very interesting results, however,  I am not able to solve the following problem:

How can a make a comparison between 
a) MU and WT 
b) MU_stressed and WT

A am not the experimenter and it is also not possible to repeat the experiment and produce a direct comparison.

However, I think - even if it is not the most elegant way - there should be a way to make this comparison with the existing data.

I was already thinking of simple "copy and past" the single channel intensities from the .gpr-files into a new matrix, but I guess this would cause a lot of problems concerning normalization steps.
Perhaps the answer is very easy, - then sorry for bothering you - but I swear I was reading a lot (tutorials) but actually I even don't know what keywords to search (google) for this problem.  

What I do right now (after preprocessing) is:
#
#
Average <- avedups(genes, ndups=2, spacing=1)
Average$A[ is.na(Average$A) ] <- 0.0
Average$M[ is.na(Average$M) ] <- 0.0
#
designWT <- modelMatrix(targets,ref="WT")
designWT <- designWT[1:8,1:4]
designWT
designMU <- modelMatrix(targets,ref="MU")
designMU <- designMU[9:16,6:9]
designMU

AverageWT <- Average[,1:8]
AverageMU <- Average[,9:16]
#
fit_WT <- lmFit(AverageWT, designWT)
fit_WT <- eBayes(fit_WT)
topTable(fit_WT)
fit_MU <- lmFit(AverageMU, designMU)
fit_MU <- eBayes(fit_MU)
topTable(fit_MU)

#
.... and further analysis and evaluation procedures
#


Please, what would be the best way to make the comparison

a) MU_(T1-4) with WT as reference 
and
b) MU_stressed (T1-4 )with WT as a reference  ?

Thanks a lot in advance for the help !
I would be so grateful if someone could give me an answer. 
 
Best regards, 
Susanne 



 -- output of sessionInfo(): 

> sessionInfo()
R version 2.13.2 (2011-09-30)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] C/en_US.UTF-8/C/C/C/C

attached base packages:
[1] splines   tcltk     stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] MASS_7.3-14          calibrate_1.7        Heatplus_1.22.0      XML_3.4-3            annaffy_1.24.0       KEGG.db_2.5.0       
 [7] goProfiles_1.14.0    GO.db_2.5.0          annotate_1.30.1      yeast2.db_2.5.0      org.Sc.sgd.db_2.5.0  RSQLite_0.10.0      
[13] DBI_0.2-5            AnnotationDbi_1.14.1 statmod_1.4.14       vsn_3.20.0           arrayQuality_1.30.0  convert_1.28.0      
[19] affy_1.30.0          marray_1.30.0        limma_3.8.3          maSigPro_1.24.1      DynDoc_1.30.0        widgetTools_1.30.0  
[25] Biobase_2.12.2      

loaded via a namespace (and not attached):
 [1] Mfuzz_2.10.0          RColorBrewer_1.0-5    affyio_1.20.0         grid_2.13.2           gridBase_0.4-4        hexbin_1.26.0        
 [7] lattice_0.19-33       preprocessCore_1.14.0 tkWidgets_1.30.0      tools_2.13.2          xtable_1.6-0         
> 

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