[BioC] duplicateCorrelation

[Devin Scannell]

Hi,

this is not a very interesting question but it has given me enough 
trouble to get me to mail the list so I hope somebody has time to 
reply.

I have several two-colour arrays to analyze. Each probe is present 
three times on each chip and they are spaced 112 spots apart (not my 
decision). The consensus correlation returned by  duplicateCorrelation 
is typically around zero which is surprising since the spots are close 
together and the data looks good in MA plots (even before 
normalization). A histogram of the individual correlations 
(cor$all.correlations from duplicateCorrelation) supports the 
conclusion that the within-chip replicates are poorly correlated.

I am concerned that the numbers that are being handed to 
duplicateCorrelation are incorrect somehow but I am not sure what I am 
doing wrong (code below). I have looked at the code for 
duplicateCorrelation and cannot follow it so I was wondering if anyone 
can suggest a way to verify the correlations it is calculating. Ideally 
I would like to be able to select a specific gene, calculate the 
correlation between replicates myself and verify that this is the same 
as I obtain from duplicateCorrelation.

Thanks in advance,

Devin



library(limma)

targets <- readTargets()

targets
    SlideNumber     Name FileName  Cy3  Cy5
13          13 60H_9:12   13.csv  WT1 60H1
17          17 60H_12:9   17.csv 60H1  WT1

flag.check <- function(x) as.numeric(x$Flags >= 3)
RG <- read.maimages(targets$FileName, sep=",", columns=list(Rf="Ch1 
Median",Gf="Ch2 Median",Rb="Ch1 B Median",Gb="Ch2 B Median"), 
wt.fun=flag.check)

RG$genes <- readGAL()
RG$printer <- getLayout(RG$genes)

RG.bgc <- backgroundCorrect(RG, method="normexp", offset=50)
MA <- normalizeWithinArrays(RG.bgc, method="loess")

design <- cbind(c(1,-1))
cor <- duplicateCorrelation(MA, design, ndups=3)