[BioC] Affymetrix internal control up-regulated, is anything wrong?

[James W. MacDonald]

Hi Michele,

On 2/13/2012 7:51 PM, Michele Bellesi [guest] wrote:
> I am a very beginner with array data analysis.
> I have 3 groups CTR and TREATMENT1 and TREATMENT2. I used a very simple design to perform the 3 comparisons, but I found that  2 out 3 Affymetric probesets for actin beta resulted up-regulated in the CTR condition. All the other probsets for actin beta don't significantly change.
> Is that normal? could it be a sign of something wrong either during the hybridization or during the analysis?

It's hard to say, particularly without access to the data. The usual 
assumption is that beta actin is constitutively up-regulated, and never 
changes expression. I have no idea if this is true, and have always 
harbored doubts.

If these were my data to analyze, I would be looking at the fold change 
difference (are the differences statistically significant, but not 
likely to be biologically meaningful?), as well as what the probesets 
are measuring (is it possible that they are picking up transcript 
variants?). Anyway, you will likely need to delve deeper into your data 
to see exactly what these differences really might mean.

Best,

Jim


> Thanks
>
>   -- output of sessionInfo():
>
> eset = exprs(expr)[, c(1:18)]
>
> designM = model.matrix(~ 0 + factor(c("C", "C", "C", "C", "C", "C", "T1", "T1", "T1", "T1", "T1", "T1", "T2", "T2", "T2", "T2", "T2", "T2"), levels = c("C", "T1", "T2")))
> colnames(designM) = c("C", "T1", "T2")
> fit<- lmFit(eset, designM)
> contrast.matrix<- makeContrasts(C-T1, C-T2, T1-T2, levels = designM)
>
> fit2<- contrasts.fit(fit, contrast.matrix)
> fit2<- eBayes(fit2)
>
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>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099