[BioC] RMA normalization and MAS5.0 detection calls
James W. MacDonald
jmacdon at med.umich.edu
Thu Dec 7 15:35:06 CET 2006
haiyan wu wrote:
> I'm using Bioconductor for analyze some Affymetrix Genechip.When I use RMA
> to normalize probe sets,it give no info for whether the probe sets present
> or absent.
> So I get these info from MAS5 detection calls.But in some case,the DE
> probes sets which was selected seems absent .On other situation for contrast
> different treatment,
> some probe sets presnt in treatment1 and absent in treatment2, but limma
> give me a conclusion that this probe sets have no changed between these 2
> How can I solve this problem? Is it right only using RMA value for limma and
> igore present/absent calls?
There are many ways to approach an analysis, and I don't think there is
any objective way to determine which is the best way. Some people do
just what you have done, computing expression values using RMA or GCRMA
and then using P/A calls to filter out those they think are not expressed.
The rationale for doing this is that the MM probes give a reasonable
estimate of background for the majority of the probes on a given chip,
so if there is no statistical difference between PM and MM, then you
might be able to consider that gene unexpressed.
However, RMA does not make use of the MM probes at all, and GCRMA only
uses the MM data in aggregate (rather than a probe-by-probe fashion), so
it is not surprising that you get the results you mention for some
Another way to approach filtering probesets is based on the variability
of the probesets over all samples. If the variance is low (below some
constant c), then you might assume that the gene is not differentially
expressed in any samples (which is different than saying it is expressed
or not). These genes are uninteresting by definition, and can be removed
from the dataset.
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James W. MacDonald, M.S.
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
Ann Arbor MI 48109
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