[BioC] How to validate normalization?
krasikov at science.uva.nl
Thu Dec 1 14:58:55 CET 2005
Here I post again the question about normalization
I'm sorry that this question might be obvious for statistician.
The general question:
How to validate the normalization outcome?
I have tried "loees with aquantile" and "vsn" and outcome of the
decideTests is more or less the same - a lot of probes with differential
Here below the code I used in limma:
RG <- read.maimages(...)
...removing controlspots from the RG
RGb <- backgroundCorrect(RG,method="minimum")
MA <- normalizeWithinArrays(RGb, method="loess")
MA <- normalizeBetweenArrays(MA, method="Aquantile")
fit <- lmFit(MA, design)
fit <- contrasts.fit(fit, contrast.matrix)
fit <- eBayes(fit)
res <- decideTests(fit, method = "separate", adjust.method="BH",
write.fit(fit, results = res, file = "...", digits=2, adjust="BH", sep="\t")
In that condition I've got 1800 up and 1800 down probes (out from 8100)
Decreasing p.value to 0.0001 gave me 800 up and 800 down.
I would like to mention here, that quite a big part of obtained data
is physiologically relevant in my experiment,
and the nature of the experiment suggests big differential expression.
Thanks in advance for any comments on this?
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