[BioC] Limma design and contrast matrix question.

[Thornton, Matthew]

Hello,

I am analysing microarray data collected with Affymetrix MouseGene 2.0 ST chips.  I have a few questions about properly using limma. I have four groups with three replicates.  The groups are Control, Treatment #1 & #2, Treatment #1, and Treatment #2. I may not have the proper design matrix. I am not familiar with their use in linear regression. Currently, my design matrix is set up like this:

# Design matrix for Limma
design <- model.matrix(~ 0+factor(c(1,1,1,2,2,2,3,3,3,4,4,4)))
colnames(design) <- c("Control", "Group1", "Group2", "Group3")

> design
   Control Group1 Group2 Group3
1        1      0      0      0
2        1      0      0      0
3        1      0      0      0
4        0      1      0      0
5        0      1      0      0
6        0      1      0      0
7        0      0      1      0
8        0      0      1      0
9        0      0      1      0
10       0      0      0      1
11       0      0      0      1
12       0      0      0      1
attr(,"assign")
[1] 1 1 1 1
attr(,"contrasts")
attr(,"contrasts")$`factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4))`
[1] "contr.treatment"

This was modified directly from the limma users guide page 36. Should the control group be all 1's? and should Group1 (treatment 1 & 2) be 1's from row 7:12? I would like to find genes different from control and I would like to find genes differentially expressed between the combination of treatments versus each treatment alone.

My Contrasts matrix is set up like this:

# Limma contrast matrix more than 5, no Venn diagrams.
contrast.matrix <- makeContrasts(Group1-Control, Group2-Control, Group3-Control, Group3-Group2, Group3-Group1, Group2-Group1, levels=design)

> contrast.matrix
         Contrasts
Levels    Group1 - Control Group2 - Control Group3 - Control Group3 - Group2
  Control               -1               -1               -1               0
  Group1                 1                0                0               0
  Group2                 0                1                0              -1
  Group3                 0                0                1               1
         Contrasts
Levels    Group3 - Group1 Group2 - Group1
  Control               0               0
  Group1               -1              -1
  Group2                0               1
  Group3                1               0

Is there a better way to relate the fact that Group 2 is a combination of treatment 1 and treatment 2? 

Thanks!

Matt
Matthew E. Thornton

Research Lab Specialist
Saban Research Institute

USC/Children’s Hospital Los Angeles
513X,  Mail Stop 35
4661 W. Sunset Blvd.
Los Angeles, CA 90027-6020

matthew.thornton at med.usc.edu