Indeed I have been somewhat criptic. Section 7.2 shows no matrices, though
section 7.4 has a few sample design matrices for two color arrays. I can
suppose those -1 there refer to dye swaps.  I am going to play with what you
suggested and see what do I get out of it.

> design <- model.matrix(~0 + targets$Culture)
> design
   targets$Culture6moA targets$Culture6moC targets$Culturet0
1                    0                   0                 1
2                    0                   0                 1
3                    0                   0                 1
4                    0                   0                 1
5                    1                   0                 0
6                    1                   0                 0
7                    1                   0                 0
8                    1                   0                 0
9                    0                   1                 0
10                   0                   1                 0
11                   0                   1                 0
12                   0                   1                 0
attr(,"assign")
[1] 1 1 1
attr(,"contrasts")
attr(,"contrasts")$`targets$Culture`
[1] "contr.treatment"

Cheers
Massimo

On Tue, May 19, 2009 at 3:48 PM, James W. MacDonald
<jmacdon@med.umich.edu>wrote:

> Hi Massimo,
>
> Massimo Pinto wrote:
>
>> I am trying to analyze a microarray experiment that was completed on an
>> Agilent single color array platform.
>> Using Agi4x44Preprocess, I happily went through the early steps of
>> reading,
>> normalization, filtration. Ended up on impressive heatmaps etc.
>>
>> Time to move to limma, now. I've been through limma's userguide
>> (limma_2.18.0), chapter 7.2 (Affymetrix and other single channel designs)
>>  and I am trying to make sense of the construction of a design matrix.  I
>> know my basics matrix multiplications, but I don't understand the sense of
>> those "-1" in my case of single color arrays. More generally, I had made
>> some specifications in my targets file, with regards to what each
>> population
>> was, and I am missing how to feed that info into design and contrast
>> matrices to operate with limma.
>> Is there any reading that you could recommend?
>>
>
> The limma User's Guide is probably the best thing to read, although the
> BioC monograph has some information as well:
> http://www.bioconductor.org/pub/docs/mogr/
>
> However, I don't know what -1s you are talking about. Section 7.2 doesn't
> even show the design matrix, and there aren't any -1s in the design matrix
> that is constructed therein:
>
> > design <- model.matrix(~0 + factor(c(1,1,1,2,2,2,3,3,3)))
> > colnames(design) <- paste("group", 1:3, sep="")
> > design
>  group1 group2 group3
> 1      1      0      0
> 2      1      0      0
> 3      1      0      0
> 4      0      1      0
> 5      0      1      0
> 6      0      1      0
> 7      0      0      1
> 8      0      0      1
> 9      0      0      1
> attr(,"assign")
> [1] 1 1 1
> attr(,"contrasts")
> attr(,"contrasts")$`factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3))`
> [1] "contr.treatment"
>
> And I think using your targets file is covered in some detail as well. In
> your case something like
>
> design <- model.matrix(~0 + targets$Culture)
>
> should get you pretty close to where you want to be.
>
> Best,
>
> Jim
>
>
>  Thank you in advance.
>> Massimo P.
>>
>> a sketch of a sample "targets" file follows
>>
>>                     X         FileName Treatment GErep Biorep Culture
>> Array
>> 41745_1_1_5    t0_1Gy1  41745_1_1_5.txt       1Gy     1      1      t0
>> 41745
>> 41844_1_4_6    t0_1Gy2  41844_1_4_6.txt       1Gy     1      2      t0
>> 41844
>> 41744_1_1_7    t0_1Gy3  41744_1_1_7.txt       1Gy     1      3      t0
>> 41744
>> 41742_1_4_8    t0_1Gy4  41742_1_4_8.txt       1Gy     1      4      t0
>> 41742
>> 41745_1_2_13 6moA_1Gy1 41745_1_2_13.txt       1Gy     2      1    6moA
>> 41745
>> 41742_1_3_14 6moA_1Gy2 41742_1_3_14.txt       1Gy     2      2    6moA
>> 41742
>> 41741_1_3_15 6moA_1Gy3 41741_1_3_15.txt       1Gy     2      3    6moA
>> 41741
>> 41844_1_3_16 6moA_1Gy4 41844_1_3_16.txt       1Gy     2      4    6moA
>> 41844
>> 41745_1_3_21 6moC_1Gy1 41745_1_3_21.txt       1Gy     3      1    6moC
>> 41745
>> 41844_1_2_22 6moC_1Gy2 41844_1_2_22.txt       1Gy     3      2    6moC
>> 41844
>> 41744_1_2_23 6moC_1Gy3 41744_1_2_23.txt       1Gy     3      3    6moC
>> 41744
>> 41743_1_3_24 6moC_1Gy4 41743_1_3_24.txt       1Gy     3      4    6moC
>> 41743
>>
>>
> --
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
> Ann Arbor MI 48109-5618
> 734-615-7826
>



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

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