[BioC] Two interaction coefficients not estimable in limma's lmFit() in a 2^3 factorial design - does this change my contrast matrix now?

[Massimo Pinto]

Greetings all,

I have noticed that several users have presented the issue of
parameters not estimated in some cases of linear model fittings with
the limma function lmFit().

In trying to implement my 2^3 factorial design, I have followed
Bioinformatics and Computational Biology Solutions using R and
Bioconductor's examples as at Chapter 14 (Multifactor experiments).
 I have encountered my own problem with two such parameters:

> fit <- lmFit(esetSub, disegno)
Coefficients not estimable: Ageing6mo:LabLNGS Dose1Gy:Ageing6mo:LabLNGS
Warning message:
Partial NA coefficients for 2176 probe(s)

whereby

> disegno
   (Intercept) Dose1Gy Ageing6mo LabLNGS Dose1Gy:Ageing6mo
Dose1Gy:LabLNGS Ageing6mo:LabLNGS Dose1Gy:Ageing6mo:LabLNGS
1            1       0         0       0                 0
  0                 0                         0
2            1       0         0       0                 0
  0                 0                         0
3            1       0         0       0                 0
  0                 0                         0
4            1       0         0       0                 0
  0                 0                         0
5            1       1         0       0                 0
  0                 0                         0
6            1       1         0       0                 0
  0                 0                         0
7            1       1         0       0                 0
  0                 0                         0
8            1       1         0       0                 0
  0                 0                         0
9            1       0         1       0                 0
  0                 0                         0
10           1       0         1       0                 0
  0                 0                         0
11           1       0         1       0                 0
  0                 0                         0
12           1       0         1       0                 0
  0                 0                         0
13           1       1         1       0                 1
  0                 0                         0
14           1       1         1       0                 1
  0                 0                         0
15           1       1         1       0                 1
  0                 0                         0
16           1       1         1       0                 1
  0                 0                         0
17           1       0         1       1                 0
  0                 1                         0
18           1       0         1       1                 0
  0                 1                         0
19           1       0         1       1                 0
  0                 1                         0
20           1       0         1       1                 0
  0                 1                         0
21           1       1         1       1                 1
  1                 1                         1
22           1       1         1       1                 1
  1                 1                         1
23           1       1         1       1                 1
  1                 1                         1
24           1       1         1       1                 1
  1                 1                         1
attr(,"assign")
[1] 0 1 2 3 4 5 6 7
attr(,"contrasts")
attr(,"contrasts")$Dose
[1] "contr.treatment"

attr(,"contrasts")$Ageing
[1] "contr.treatment"

attr(,"contrasts")$Lab
[1] "contr.treatment"

I have checked my design and it does make good sense to me. But, I
believe I was asking too much from my parameter estimation.
I am wondering how is this going to change the way I design my
contrast matrix? I am trying to define my contrast matrix following
the formulation of null hypotheses as at the 'yellow' book, p244.

Thanking you very much,

Massimo

Massimo Pinto
Post Doctoral Research Fellow
Enrico Fermi Centre and Italian Public Health Research Institute (ISS), Rome
http://claimid.com/massimopinto