[BioC] Expression levels of individual affymetrix probes

[James W. MacDonald]

Hi Alice,

Johnstone, Alice wrote:
> Hi,
> Is it possible to apply the transformations used on the probesets to
> individual probe expression?  Such as RMA and fitting to a lm to obtain
> your list of probesets of interest.  Then potentially looking at
> individual probe expression levels across samples for all 11 probes of
> that probeset?  (but normalized across samples to enable greater
> accuracy of the eyeball-o-meter)
> The reason behind this pondering is to investigate further transcript
> variant effects, and also to better match qpcr investigations to the
> location of the probe which shows the greatest change...

If I understand you correctly, you want to go back to the 
background-corrected, normalized pm data for certain probesets to see 
the contribution of individual probes.

This shouldn't be difficult.

dat <- ReadAffy()
dat <- bg.correct.rma(dat) ## background corrected
dat <- normalize.AffyBatch.quantiles(dat)

Now you can look at individual probesets using

pm(dat, 'a.probeset.id')

Best,

Jim


> Cheers,
> Alice 
> 
> 
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-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623