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January Weiner
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370
@january-weiner-3999
Last seen 10.3 years ago
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.
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-------- Dr. January Weiner 3 --------------------------------------