[BioC] Dye effect problem with Limma package

[Jean-Laurent Ichanté]

Dear All,
I have one question that makes me perplex, and no message concerning 
this problem is described in the mailing list.
I'm using the Limma package for the comparison of two experimental 
conditions (KO vs WT) in a 'reference design' with dye-swap.
My experimental design is the following:

                        Cy5      Cy3
Array1              Ref       WT
Array2              Ref       WT
Array3              Ref       WT
Array4              WT       Ref
Array5              WT       Ref
Array6              WT       Ref
Array7              Ref       KO
Array8              Ref       KO
Array9              Ref       KO
Array10            KO       Ref
Array11            KO       Ref
Array12            KO       Ref

In such design it is possible to estimate a dye effect.
 
First, I have fitted a very simple model.

>  fit1 <- lmFit(MA, design=design1)
where design1 is the following design matrix:
 
>  design1
                                   KO       WT
208_REF-WT.1B           0          -1
213_REF-WT.25B         0          -1
301_REF-WT.3B           0          -1
210_WT.2B-REF           0          1
215_WT.26B-REF         0          1
304_WT.5B-REF           0          1
209_REF-KO.28B         -1         0
214_REF-KO.27B         -1         0
303_REF-KO.13B         -1         0
211_KO.18B-REF         1          0
300_KO.15B-REF         1          0
302_KO.17B-REF         1          0
 
 
Then I have fitted a second model including dye effect.
 
>  fit2 <- lmFit(MA, design=design2)
where design2 is the following design matrix:
 
>  design2
                                   DyeEffect          KO       WT
208_REF-WT.1B          1                      0          -1
213_REF-WT.25B         1                      0          -1
301_REF-WT.3B          1                      0          -1
210_WT.2B-REF          1                      0          1
215_WT.26B-REF         1                      0          1
304_WT.5B-REF          1                      0          1
209_REF-KO.28B         1                      -1         0
214_REF-KO.27B         1                      -1         0
303_REF-KO.13B         1                      -1         0
211_KO.18B-REF         1                      1          0
300_KO.15B-REF         1                      1          0
302_KO.17B-REF         1                      1          0
 
 
In theory fitted values should be identical for the two coefficients (KO 
and WT), but in my case observed values are different (for certain genes).
 
>  fit1$coef[1:5,]
             KO          WT
[1,] -0.8372489 -0.19457588
[2,] -0.3208879 -0.15328678
[3,] -0.7202544 -0.69133039
[4,] -0.1262356 -0.08165633
[5,] -0.2568482 -0.18354345
 
>  fit2$coef[1:5,]
        DyeEffect         KO          WT
[1,] -0.411091881 -0.8372489 -0.27679426
[2,] -0.007895425 -0.3182560 -0.15328678
[3,] -0.004396641 -0.7202544 -0.69133039
[4,]  0.200046876 -0.1262356 -0.08165633
[5,] -0.052855276 -0.2568482 -0.19411451
 
 
What is the origin of these differences?
Does anybody have any suggestions?
 
Thanks again
Jean-Laurent