Dear all,

I have four cDNA microarray data, two of them are control group, and the
other two are the experimental group (the two replicates within each group
has dye swamp)

The design is:

Control:

First chip:
Green dye (time point 1)
Red dye (time point 2)

Second chip:
Green dye (time point 2)
Red dye (time point 1)




Experimental group:

First chip:
Green dye (time point 1)
Red dye (time point 2)

Second chip:
Green dye (time point 2)
Red dye (time point 1)


Since we stop the transcription process after time point 1, so the mRNA
levels in time point 2 should be lower than the one in time point 1 ;
and we find that for some reason the red dye is much less effecicient than
the green dye, so in each chip the red dye is distributed in a lower density
than that of the green dye (no matter what time point does it represent)

My goal is to identify those mRNA in the experimental group that has fold
change (in the two time points) different from that of the control group.

I tried to use
> normalizeWithinArrays(method="loess", bc.method="normexp")
> normalizeBetweenArrays(method="quantile")

but I eventually end up with all the dyes in each chip having very similar
distribution (but in fact I would like to have the time point 2 has similar
distirbution across each chip, and time point 1 has the similar distribution
across each chip, and the time point 2 should have lower intensity than that
of time point 1)

I apologize that this is pretty much a procedure for microarray analysis
rather than a bioconductor - specific  question,
and I greatly appreciate any help from the group.


-- 
Lam C. Tsoi (Alex)
Medical University of South Carolina

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