Additionally to what Wolfgang already wrote you might have a look at a
related thread on the mailing list, that was discussed just recently
What you call "mirrored version" of the MA-Plot, corresponds to the
correlation of the M-values discussed in that thread. One reason why
tend not to observe this negative correlation/mirrored version is that
normalization (loess,vsn,whatever) removes an OVERALL dye effect,
also allowed to be intensity depending for the standard methods, BUT:
dye effect can also have a gene-specific component, i.e. two genes
similar intensities might have very different dye-effects for example
because of their difference in GC content or other properties.
This is not addressed by the standard methods, which means your MA-
will not look as "mirrored" as you think. You can account for the
gene-specific dye effect though by including that effect in your limma
(cf. the limma tutorial).
Also (and this is partly by covered by Wolfgang's reply) you will only
observe a mirror effect for genes which are truly biologically
expressed. So if there is not much differential expression, there
much mirroring either.
> -----Original Message-----
> From: bioconductor-bounces at stat.math.ethz.ch
> bounces at stat.math.ethz.ch] On Behalf Of Hooiveld, Guido
> Sent: 28 January 2010 14:14
> To: bioconductor at stat.math.ethz.ch
> Subject: [BioC] MA plots + dye swap
> Dear listers,
> I am new to the analysis of 2-dye arrays, so please bear with me!
> I have a conceptual question on MA plots and dye swaps.
> Assume you have 2 arrays, on which Control and Treatment are
> its corresponding dye swap. So:
> array Cy3 Cy5
> 1 Con Treatment
> 2 Treatment Con
> After normalizing these 2 arrays (e.g. with VSN from within Limma) I
> plot the 2 MA plots (based on the normalized data). I would expect
> (in theory) MA plot1 would be the mirrored version of MA plot2. In
> words, normalization per se does NOT take into account dye swaps;
> is only subsequently done in the design matrix when using e.g.
> Q: Is this correct? I am asking because in my normalized dataset
> dye swaps (15 arrays total) I do NOT seem to see these mirrored MA
> when comparing the respective dye-swapped arrays.
> targets <- readTargets("targets_corrected.txt", row.names="Name")
> RG <- read.maimages(targets$FileName, source="agilent")
> MA.vsn <- normalizeBetweenArrays(RG, method="vsn")
> Guido Hooiveld, PhD
> Nutrition, Metabolism & Genomics Group
> Division of Human Nutrition
> Wageningen University
> Biotechnion, Bomenweg 2
> NL-6703 HD Wageningen
> the Netherlands
> tel: (+)31 317 485788
> fax: (+)31 317 483342
> internet: http://nutrigene.4t.com
> email: guido.hooiveld at wur.nl
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