[BioC] GCRMA Fold Change

[Jenny Drnevich]

Hi Christine,

Instead on filtering on the expression values from GCRMA, I would suggest 
to use Affymetrix's Present/Marginal/Absent calls. You can get these with 
the mas5calls() function in the affy library. I use a very conservative 
filter, and only throw out genes that are "absent" on all arrays. I would 
suggest that you do this filtering before the statistical analysis for two 
reasons: 1) the error variances of the filtered genes are affecting your 
Bayesian statistics and 2) removing the genes will decrease the multiple 
test correction penalty.

However, even after filtering out these genes, you may still have many 
genes with low fold-changes that are "significant". One can argue all day 
long on whether these low fold changers are "biologically" significant or 
not, but if you prefer to follow up first on genes with higher fold 
changes, then by all means pick these out of your significant gene list. 
Just make sure to document everything clearly!

Cheers,
Jenny

At 11:14 AM 5/2/2006, cap2018 at columbia.edu wrote:
>I have used GCRMA to process and normalize my chip results.  I had
>sufficient N to use 2 way ANOVA to analyze my data and I have used
>Baysiean statistics to determine significance levels.
>
>I have quite a few probe sets that are considered statistically
>significant by my analysis, but have a fold change close to 1,
>indicating the level of transcript is not THAT different between 2
>groups.  Most of the probe sets that fit this description have very
>low expression value from the GCRMA analysis, 1-6.
>
>I did not filter my results as expressed/not expressed before I did
>the analysis because I have been told it is unnecessary, and I get
>many significant results that are definitely are expressed, but I'd
>like to apply some kind of filter to my statistical results.
>Is there a way to determine which transcripts are unexpressed, a
>specific threshold for example?  For instance, values 7< are
>probing expressed transcripts?
>
>Christine
>
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Jenny Drnevich, Ph.D.

Functional Genomics Bioinformatics Specialist
W.M. Keck Center for Comparative and Functional Genomics
Roy J. Carver Biotechnology Center
University of Illinois, Urbana-Champaign

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