Entering edit mode
Thierry Janssens
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40
@thierry-janssens-3449
Last seen 9.6 years ago
Dear BioC,
while performing Single Channel Analysis in limma, according to
chapter
9 of the limma users guide, I notice that the R and G foreground
intensities are not correlated at all. I did not find a thread about
that problem on the forum. I am wondering what the cause could be...
The experiment is an unconnected/saturated design of 5 conditions, on
whcih I want to perform t-tests between the conditions.
...
> RGbc <- backgroundCorrect(RGlist, method = "edwards", offset = 30)
> MA <- normalizeWithinArrays(RGbc[j, ], method ="loess")
> targets
Archive Filename Cy5 Cy3
1 File SSArray1.txt A B
2 File SSArray2.txt B C
3 File SSArray3.txt C AC
4 File SSArray4.txt AC AB
5 File SSArray5.txt AB A
6 File SSArray6.txt A C
7 File SSArray7.txt C AB
8 File SSArray8.txt AB B
9 File SSArray9.txt B AC
10 File SSArray10.txt AC A
> #sorteren op duplo
> o <- order(MA$genes$ProbeUID)
> MAsorted <- MA[o,]
> o <- order(MAbet$genes$ProbeUID)
> MAbetsorted <- MAbet[o,]
> r <- 0
> for(q in seq(1, nrow(MAbetsorted), 3)) {
+ r <- as.numeric((identical(MAbetsorted$genes$probeUID[q],
MAbetsorted$genes$probeUID[q+1]))
+ && (identical(MAbetsorted$genes$probeUID[q],
MAbetsorted$genes$probeUID[q+2])) ) + r
+ }
> r
[1] 5069
> # r moet 5069 zijn
> # Separate channel analysis in limma
> MAbetsortedav <- avedups(MAbetsorted, ndups = 3, spacing =1)
> targets <- readTargets("filelist.txt")
> targetstest <- targetsA2C(targets)
> u <- unique(targetstest$Target)
> f <- factor(targetstest$Target, levels=u)
> design <- model.matrix(~0+f)
> colnames(design) <- u
> design
B A C AC AB
1 1 0 0 0 0
2 0 1 0 0 0
3 0 0 1 0 0
4 1 0 0 0 0
5 0 0 0 1 0
6 0 0 1 0 0
7 0 0 0 0 1
8 0 0 0 1 0
9 0 1 0 0 0
10 0 0 0 0 1
11 0 0 1 0 0
12 0 1 0 0 0
13 0 0 0 0 1
14 0 0 1 0 0
15 1 0 0 0 0
16 0 0 0 0 1
17 0 0 0 1 0
18 1 0 0 0 0
19 0 1 0 0 0
20 0 0 0 1 0
attr(,"assign")
[1] 1 1 1 1 1
attr(,"contrasts")
attr(,"contrasts")$f
[1] "contr.treatment"
> corfit <- intraspotCorrelation(MAbetsortedav, design)
Warning messages:
1: In remlscore(y, X, Z) : reml: Max iterations exceeded
2: In remlscore(y, X, Z) : reml: Max iterations exceeded
> corfit$consensus.correlation
[1] *0.06922669
*In previous threads I read that this correlation should be 0.8-0.9
(after backtransformation with tanh). What now?
kind regards,
Thierry
--
Thierry K.S. Janssens
Vrije Universiteit Amsterdam
Faculty of Earth and Life Sciences
Institute of Ecological Science
Department of Animal Ecology,
De Boelelaan 1085
1081 HV AMSTERDAM, The Netherlands
Phone: +31 (0)20-5989147
Fax: +31 (0)20-5987123
thierry.janssens at ecology.falw.vu.nl
