[BioC] Summarizing two-channel data (RGList, MAList) for limma analysis

[Sean Davis]

Hi, Stephen.

You can use an average value, but for long-oligo arrays like Agilent,
folks have often used the probe measurements directly.  You can use
the genefilter package to remove probes that do not vary across
samples to reduce some of the redundancy; this increases power to
detect differential expression by reducing the number of tests that
must be included in the multiple-testing-correction.  If you feel a
strong need to summarize, using an average is probably not too bad an
approach assuming that the probes for the same gene are correlated
with each other (and many will be).

Sean


On Wed, Jan 11, 2012 at 4:45 PM, Stephen Turner <vustephen at gmail.com> wrote:
> Hello.
>
> I have 4 Agilent two-channel arrays that I read in using read.maimages().
> I've done normalization and background subtraction. How do I now summarize
> the probe information (62976 probes) to gene-level expression values (39430
> entrez RNAs, 16251 lincRNAs). I normally did this using rma() or gcrma()
> from the affy package when I have Affymetrix data.
>
> Thanks,
>
> Stephen
>
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