[BioC] Separating channels of a two-color microarray

January Weiner january.weiner at mpiib-berlin.mpg.de
Mon Feb 13 11:22:11 CET 2012


Dear Naomi,

> After single channel normalization, I usually use MA.RG to transform back to
> R and G.  It has worked remarkably well.

Yes, this is also my usual procedure. However, as you noticed, this
does not help us with getting rid of the intra-array correlation. I
was hoping that there might me a standard procedure to correct for
this.

While normally one does not really need the R & G channels, I have
particular situations where I would like to have them, like the
abovementioned meta-study. In that particular case it would be
extremely important to get rid of any correlations between the
channels in one array.

Kind regards,

January

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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>
>
>
>



-- 
-------- Dr. January Weiner 3 --------------------------------------
Max Planck Institute for Infection Biology
Charitéplatz 1
D-10117 Berlin, Germany
Web   : www.mpiib-berlin.mpg.de
Tel     : +49-30-28460514
Fax    : +49-30-28450505



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