[BioC] Double KO and timecourse design / limma

[Textoris Julien]

Dear all,

First thing, happy new year to all and thanks for all the 
knowledge/advices brought through the list !

I would like to have your advice/comments on the following design.

I have to analyse a microarray dataset performed on MoGene ST 1.0 which 
comprise 22 arrays. I have allmost no replicates (! could not control 
this !) but I thought I could use the timecourse and double KO/single KO 
status to overcome this ?

The variables are :
  - Treatment : binary YES or NO
  - Time : samples at 0h (= UNTREATED), 2h, 6h and 18h
  - Strain : Wild type (WT), single KO for gene A or gene B, and double KO.

For WT mice, I have 2 UNTREATED (=0h), and a timecourse for Treatment 1 
and 0 (WT_UNT_2h, and WT_TTT_2h). For KO mice, I only have treated 
samples (except time 0h, which is considered untreated).

I have duplicates only for WT.UNTREATED_0h and KOA_0h.

I wrote the following design :

levels(f) = 
c("WT_0h","WT_2h","WT_6h","WT_18h","WT_UNT_2h","WT_UNT_6h","WT_UNT_18h","KOA_0h","KOA_2h", 
...,"DKO_0h","DKO_2h","DKO_6h","DKO_18h")

and performed the contrast matrix over time like his :

cont.wt = contrast.matrix(
       "WT_18h-WT_6h",
       "WT_6h-WT_2h",
       "WT_2h-WT_0h",
       levels=design)

idem for KOA, KOB and DKO, and then the comparisons :

cont.koa.wt = contrast.matrix(
       "(KOA_18h-KOA_6h)-(WT_18h-WT_6h)",
       etc...


How would you handle the strain variable ? As one variable with four 
levels : WT, KOA, KOB, DKO ? Or is it possible to take into account that 
DKO is somehow like KOA+KOB ? Do I have to transform 'Strain' into three 
binary variables : WT (1/0), KOA(1/0) and KOB (1/0) and code DKO as KOA 
= 1 and KOB = 1 ?

The second question is I don't know how to integrate the WT mice that 
are untreated ?

This experimental design is a bit too complex for me, so any advice 
would be greatly appreciated !

Thanks in advance,

Julien