[BioC] Normalization between arrays for common reference, time course and direct two color designs

Jenny Drnevich drnevich at uiuc.edu
Thu Dec 7 16:39:58 CET 2006

Hi Vinoy,

Using the 'Gquantile' between-array normalization is not appropriate in 
your case because your reference is not always in the Green channel. The 
values you are using for Exp3 and Exp6 in the linear model are actually 
from the reference, so it's no wonder your gene lists don't make sense. To 
clarify, the discussion we were having recently on the mailing list about 
using Gquantile is when your experimental samples are expected to be VERY 
different from the reference, such that the assumption of a within-array 
normalization may not be met. In your case (and in most reference designs) 
you probably meet the assumptions of most genes not changing, and so should 
first do a within-array loess-type normalization to help remove dye bias. 
Then check to see if the resulting distributions of M values are similar 
between arrays. If they are very different, and you would expect them not 
to be very different, do a between-array normalization on the M values - 
the scale method of 'normalizeBetweenArrays' is my favorite. The design 
matrix you have below will correctly adjust for dye swaps, assuming that 
the 'dye swaps' are all biological replicates and not technical replicates.

I'm a little confused about the way you're calling the 'lmFit' function. 
Your arrays appear to have duplicate spots, but you have the correlation as 
zero. Something is very wrong with your arrays if there is zero correlation 
between the duplicate spots! I suggested you read the limma vignette very 
closely, especially the sections on common reference designs and 
within-array replicate spots.

Good luck,

At 12:58 AM 12/7/2006, Vinoy Kumar Ramachandran wrote:
>  Dear Limma users,
>I am working on custom spotted 70mer oligo arrays, and use Bluefuse to
>analyse the images. With the help of the excellent user guide and
>Bioconductor user forum(GMANE), i have analysed my direct comparison
>experiements. I also have common reference, time course and direct two color
>design type experiments to analyse. I have read the recent posting in the
>list  about using Rquantile or Gquantile for normalizing between arrays in
>common reference experiments. I tried to do a common references analysis
>using the discussed code.But the resulting gene list is different from the
>expected list.i am also wondering how to account for dye swaps. I have
>pasted the code which i used for common reference.
>It will also be very useful if you any one could tell me how to use
>normalization between arrays for direct two color designs.
>My experiment design is
>           Cy3   Cy5
>Exp1  Ref    CpdA
>Exp2  Ref    CpdA
>Exp3  CpdA Ref
>Exp4  Ref   CpdB
>Exp5  Ref   CpdB
>Exp6 CpdB Ref
>Code which i used for analysing common referencec:
>targets <- readTargets("commonref.txt", row.names="Name")
>RG <- read.maimages(targets$FileName, source="bluefuse")
>RG$genes <- readGAL()
>RG$printer <- getLayout(RG$genes)
>spottypes <- readSpotTypes()
>RG$genes$Status <- controlStatus(spottypes, RG)
>isGene <- RG$genes$Status == "oligos"
>MA.Gquantile <- normalizeBetweenArrays(RG[isGene,], method="Gquantile")
>RG.Gquantile <- RG.MA(MA.Gquantile)
>MA.dummy <- MA.Gquantile
>MA.dummy$M <- log2(RG.Gquantile$R)
>o <- order(MA.dummy$genes$ID)
>MA.sorted <- MA.dummy[o,]
>design <- modelMatrix(targets, ref="Ref")
>fit <- lmFit(MA.sorted, design, ndups=2, spacing=1, correlation=0)
>fit.eb <- eBayes(fit)
>write.fit(fit.eb, file="data/commonref.xls", adjust="BH")
>thanks in advacne
>with regards,
>         [[alternative HTML version deleted]]
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>Search the archives: 

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

ph: 217-244-7355
fax: 217-265-5066
e-mail: drnevich at uiuc.edu

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