[BioC] technical + biological replicate design for multiple categories

[Naomi Altman]

You need to have a variable "biorep" with biorep number e.g. 
c(1,1,2,2,3,3,...6,6)

This is a blocking variable.

The treatments are just Cyt1, Cyt2 and Mock.

You will need to follow the instructions for blocking variables.

--Naomi


At 05:15 PM 7/2/2013, James Platt wrote:
>I am using Limma for an experimental design with three categories, 
>two biological replicates each and two technical replicates of each 
>biological replicate for a total of 12 arrays.   Since this goes 
>just a little bit beyond the Limma user guide, I want to make sure I 
>am setting this up correctly.  Also, figure out why I am getting the 
>error message below.
>
>The categories are:
>Cyt1
>Cyt2
>Mock (which is control for both of the other groups)
>
>The biological replicates are indicated with A and B.  The technical 
>replicates are indicated with .1 and .2.
>
>The variable expr has the array data and the sample columns are:
>MockA.1 MockA.2 Cyt1A.1 Cyt1A.2 Cyt2A.1 Cyt2A.2 MockB.1 MockB.2 
>Cyt1B.1 Cyt1B.2 Cyt2B.1 Cyt2B.2
>
> > treatment
>  [1] MockA MockA Cyt1A Cyt1A Cyt2A Cyt2A MockB MockB Cyt1B Cyt1B Cyt2B Cyt2B
>Levels: Cyt1A Cyt1B Cyt2A Cyt2B MockA MockB
> > design = model.matrix(~ 0 + treatment)
> > design
>    Cyt1A Cyt1B Cyt2A Cyt2B MockA MockB
>1      0     0     0     0     1     0
>2      0     0     0     0     1     0
>3      1     0     0     0     0     0
>4      1     0     0     0     0     0
>5      0     0     1     0     0     0
>6      0     0     1     0     0     0
>7      0     0     0     0     0     1
>8      0     0     0     0     0     1
>9      0     1     0     0     0     0
>10     0     1     0     0     0     0
>11     0     0     0     1     0     0
>12     0     0     0     1     0     0
>attr(,"assign")
>[1] 1 1 1 1 1 1
>attr(,"contrasts")
>attr(,"contrasts")$treatment
>[1] "contr.treatment"
> > block
>  [1] "MockA" "MockA" "Cyt1A" "Cyt1A" "Cyt2A" "Cyt2A" "MockB" 
> "MockB" "Cyt1B" "Cyt1B" "Cyt2B" "Cyt2B"
> > dupcor = duplicateCorrelation(expr, design, block=block)
> > fit.raw = lmFit(expr, design, block=block,
>+             correlation=dupcor$consensus)
>Error in chol.default(V) :
>   the leading minor of order 2 is not positive definite
>         [[alternative HTML version deleted]]
>
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