[BioC] continued dye effects, after normalization

[Jenny Drnevich]

Thanks Henrik,

Where can I find documentation on this affine normalization? There is no 
real help page for normalizeAffine, just a generic "Non-doumented Objects" 
page.

Cheers,
Jenny

At 12:18 AM 1/14/2007, Henrik Bengtsson wrote:
>Hi Jenny,
>
>try affine normalization, which corrects for both global background
>(offset) as well as non-linear effects on the log-scale (read
>intensity dependent effects) in one step.  See normalizeAffine(X,
>constraint=0.05) in the aroma.light package, where X is a matrix. By
>adjusting the 'constraint' argument you can adjust the amount of
>background subtracted.
>
>Try also to stratify your PCR by different intensities.  It is more
>likely that you see a "dye bias" at lower intensities than at higher,
>which is mainly because the background correction was not perfect.
>
>Cheers
>
>Henrik
>
>On 1/11/07, Jenny Drnevich <drnevich at uiuc.edu> wrote:
>>Hi all,
>>
>>I've been analyzing a spotted array experiment that used a common reference
>>with a 2X2 factorial design. There were no technical dye swaps, but half of
>>the 6 replicates in each group had the ref in Cy3 and half had the ref in
>>Cy5. Now that Jim has modified plotPCA to accept matrices, I was checking
>>for any unsuspected groupings that might indicate block effects. To my
>>surprise, the arrays were still grouping based on the reference channel,
>>even after inverting the M-values so that the reference channel was always
>>in the denominator! Attached is a figure with 2 PCA plots, and hopefully it
>>is small enough to make it through; the code that created them is
>>below.  Has anyone else noticed this, and what have you done about it? I
>>went back and checked some other experiments that used a common reference,
>>and they also mostly showed a continued dye grouping. A between-array scale
>>normalization, either on the regular M-values or on inverted M-values,
>>failed to remove the dye effect as well. I didn't try other normalizations,
>>but instead included 'ref dye' as a blocking variable. The consensus
>>correlation from duplicateCorrelation was 0.154, which when included in the
>>lmFit model increase the number of genes found significantly different.
>>
>>I have been working with a physics professor and his student who have
>>developed a different data mining algorithm, which shows these dye effects
>>even more strongly than PCA. They are suggesting another normalization is
>>needed to remove the ref dye effect, and they want to normalize the ref dye
>>groups separately. Doing a separate normalization doesn't seem like a good
>>idea to me, and I wanted to get other opinions on the dye effect, my
>>approach, and other normalization options.
>>
>>Thanks!
>>Jenny
>>
>>code:
>>
>>RG <- read.maimages(targetsb$FileName,path="D:/MA Jenny",
>>                  source="genepix.median",names=targetsb$Label,wt.fun=f)
>>
>>RG.half <- backgroundCorrect(RG,method="half")
>>
>>MA.half <- normalizeWithinArrays(RG.half)
>>
>>temp <- MA.half
>>temp$M[,targetsb$Cy3=="ref"] <- -1 * temp$M[,targetsb$Cy3=="ref"]
>>
>>layout(matrix(1:2,2,1))
>>plotPCA(MA.half$M,groups=rep(c(1,2,1,2,1,2,1,2),each=3),groupnames=c("ref
>>G","ref R"))
>>          # PC1 divides the arrays by which channel the ref was in
>>plotPCA(temp$M,groups=rep(c(1,2,1,2,1,2,1,2),each=3),groupnames=c("ref
>>G","ref R"))
>>          # after inverting the M-values for half the arrays, PC1 divides
>>the arrays by one of the treatments, but
>>          # the dye effect still shows up in PC2
>>
>>
>>MA.half.scale <- normalizeBetweenArrays(MA.half,method="scale")
>>
>>design <- modelMatrix(targetsb,ref="ref")
>>
>>block <- rep(c(1,2,1,2,1,2,1,2),each=3)
>>
>>corfit <- duplicateCorrelation(MA.half.scale[RG$genes$Status=="cDNA",],
>>design, ndups=1, block=block)
>>
>>corfit$consensus
>>      #[1] 0.1537080
>>
>>
>>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
>>
>>330 ERML
>>1201 W. Gregory Dr.
>>Urbana, IL 61801
>>USA
>>
>>ph: 217-244-7355
>>fax: 217-265-5066
>>e-mail: drnevich at uiuc.edu
>>
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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
>
>330 ERML
>1201 W. Gregory Dr.
>Urbana, IL 61801
>USA
>
>ph: 217-244-7355
>fax: 217-265-5066
>e-mail: drnevich at uiuc.edu