[BioC] Fwd: replicate spots and dupcor.series

[Simon Melov]

Hi,
I have a subarray with 1567 spots replicated 4 times on each chip. I am 
trying to carry out the correlation analysis as in the Bob Mutant data 
example in the guide. I get as far as the cor$cor and then I get a 
correlation of 0.8 for every gene in the series. If I do the boxplot, I 
also get 0.8 for every tick on the axis. What am I doing wrong?  It has 
defaulted to the initial estimate for correlation for every gene. I 
have tried altering "initial" in the dupcor.series function, to other 
values, and no matter what value I use, I get that value for every gene 
on the array. Perhaps loess for print tip is not effective for this 
number of genes per grid?

thanks

simon.

RG <- read.maimages(files,source="genepix")
Read CA05A16.gpr
Read CA05B04.gpr
Read CA05C04.gpr
Read CA05C08.gpr
Read CA05D08.gpr
 > RG <- backgroundCorrect(RG, method="none")
 > RG$genes <- readGAL()
 > RG$printer <- getLayout(RG$genes)
 > MA <- normalizeWithinArrays(RG)
 > targets <- readTargets("targets.txt")
 > boxplot(MA$M~col(MA$M),names=targets$Name)
 > MA <- normalizeWithinArrays(RG)
 > design <- designMatrix(targets, ref="mixed pool")
Found unique target names:
  4 day-1 mixed pool 4 day-2 4 day-3 4 day-4 4 day-5
 > design
   4 day-1 4 day-2 4 day-3 4 day-4 4 day-5
1      -1       0       0       0       0
2       0      -1       0       0       0
3       0       0      -1       0       0
4       0       0       0      -1       0
5       0       0       0       0      -1
 > cor <- dupcor.series(MA$M,design,ndups=4)
Loading required package: nlme
Loading required package: lattice
 > cor
$cor
[1] 0.8

$cor.genes
    [1] 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 
0.8 0.8
   [19] 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 
0.8 0.8

...through to 1567

 > cor$cor
[1] 0.8
 > boxplot(cor$cor.genes)

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