[BioC] Separating channels of a two-color microarray

Naomi Altman naomi at stat.psu.edu
Mon Feb 13 02:51:50 CET 2012


After single channel normalization, I usually use MA.RG to transform 
back to R and G.  It has worked remarkably well.  However, I retain 
the array effect in the model.

Regards,
Nasomi Altman


At 03:55 AM 2/8/2012, January Weiner wrote:
>Dear all,
>
>first, I would like to thank all who answered my questions in the past.
>
>I am attempting a meta-analysis of several microarray studies, with
>limma as my working horse. I plan to throw all the microarrays
>together, creating one large data set with one of the factors in the
>analysis being the data set. Preliminary analyses with a limited
>number of studies are encouraging; on one hand, I am able to reproduce
>the results of the single studies, while at the same time finding
>robust differences between the studies (and their respective cohorts).
>
>However, I hit a wall with one of these studies, which involved
>two-color Agilent chips, not with a common reference, but each chip
>corresponding to two different individuals from two experimental
>groups. For some of the analyses that I plan I need separate
>intensities for each experimental group -- fold changes won't cut it
>(for example, in case of machine learning in which I use the
>intensities to construct a model for predicting the group
>assignments).
>
>I  tried to directly use the R and G channels, and the results are
>actually quite good. Of course, this is not an optimal approach.
>Normally, when faced with two-color arrays and a complex experimental
>design I use intraspotCorrelation and lmscFit.
>
>Question: is there a way to use the results of intraspotCorrelation to
>correct the R and G channels?
>
>Kind regards,
>j.
>
>--
>-------- Dr. January Weiner 3 --------------------------------------
>
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