Dear Prof. Smyth and experts,


I'm having problems in Compute Contrasts from Linear Model Fit.

These are the data, and the main question to answer is which are the
genes dierentially expressed in the laz T36 vs laz T0 :


> targets

  SlideNumber  Name     FileName   Cy3   Cy5 Moment
1           1 chip1  chipZ10.gpr  pet0  laz0     T0
2           2 chip2  chipZ20.gpr  pet0  laz0     T0
3           3 chip3  chipZ30.gpr  pet0  laz0     T0
4           4 chip4 chipZ136.gpr pet36 laz36    T36
5           5 chip5 chipZ236.gpr pet36 laz36    T36
6           6 chip6 chipZ336.gpr pet36 laz36    T36


>design <- modelMatrix(targets, ref = "pet0")
Found unique target names:
 laz0 laz36 pet0 pet36

> design
     laz0 laz36 pet36
[1,]    1     0     0
[2,]    1     0     0
[3,]    1     0     0
[4,]    0     1    -1
[5,]    0     1    -1
[6,]    0     1    -1


> fit <- lmFit(MA, design)
Coefficients not estimable: pet36
Warning message:
Partial NA coefficients for 13051 probe(s)

>cont.matrix <- makeContrasts("laz36vslaz0"=(laz36-pet36)-laz0, levels=design)

>cont.matrix
       Contrasts
Levels  laz36vslaz0
  laz0            -1
  laz36           1
  pet36          -1

> fit2 = contrasts.fit(fit, contrasts = cont.matrix)
Error in contrasts.fit(fit, contrasts = cont.matrix) :
  trying to take contrast of non-estimable coefficient


Can you please help me with this?


Best Regards

Sara Domingos

(Instituto Superior de Agronomia, Lisboa, Portugal)

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