[BioC] Basic Q on dye- swap

[Mark Cowley]

Hi Christina,
There's a number of ways to do that, all of which require you to first  
work out the direction on each array

swap <- rep(1, length(files))
swap[grep("DyeSwap", files)] <- -1
swap

Now swap contains +1 or -1.

Now you can either fit a simple linear model:

model <- model.matrix(~0+sweep)
fit <- lmFit(RG.Between$M, model)
Log_Ratio_DyeSwapped <- fit$coefficients

-or-
Log_Ratio_DyeSwapped <- sweep(RG.Between$M, 2, swap1, "*")

hope that helps!
Mark
On 12/05/2009, at 6:02 PM, Christina Tigress wrote:

> Hi,
>
> SORRY, but I have a very basic question on dye swap.
>
> A set of cDNA microarray samples contains a few dye-swaps. For
> retrieving normalized, log2 transformed expression values (against a  
> common
> reference for all samples), I wonder how I can make sure that the
> “dye-swap”-nature of the files is taken into account as I get the  
> final
> spreadsheet of the expression values for all the Genepix files !
>
> I have gone through limma which talks about fitting a linear model  
> for each
> gene using design matrix. But, I wish to know just the  expression  
> values of
> the files (with dye-swaps taken care of in the final output).
>
> Please provide some suggestion(s)/pointer(s).
>
> Thanks a lot !
>
> Cheers,
> Christina
>
>
> *The codes I used*:
>
> library (arrayQuality)
>
> targets <- readTargets("targetPMCI.txt")
>
> files <-
> c 
> ("3a 
> .gpr 
> ","3b 
> .gpr 
> ","3cDyeSwap 
> .gpr","9bT.gpr","37a.gpr","37b.gpr","37cDyeSwap.gpr","61a.gpr",
>
> "61b 
> .gpr 
> ","61cDyeSwap 
> .gpr 
> ","75a 
> .gpr","75bT.gpr","75cDyeSwap.gpr","76b.gpr","76cT.gpr","77a.gpr",
>
> "77bT 
> .gpr 
> ","77c 
> .gpr 
> ","78b.gpr","78cT.gpr","79a.gpr","79b.gpr","79cDYESWAP.gpr","80a.gpr",
>
> "80b.gpr","80cDyeSwap.gpr","81aT.gpr", "81b.gpr","81cDyeSwap.gpr",
> "82aT.gpr","82b.gpr","82cDyeSwap.gpr",
> "83a 
> .gpr 
> ","83b 
> .gpr 
> ","83cDyeSwap 
> .gpr","84a.gpr","84b.gpr","84cDyeSwap.gpr","85a.gpr","85b.gpr",
>
> "85cDyeSwap.gpr","86a.gpr","86b.gpr", "86cDyeSwap.gpr","711aT.gpr")
>
> RG <- read.maimages(files,source="genepix")
>
> RG$printer <- getLayout(RG$genes)
>
> RG.b <- backgroundCorrect(RG, method="normexp", offset=50)
>
> library (convert)
>
> RG.Within <- normalizeWithinArrays (RG.b, method="loess")
>
> RG.Between <- normalizeBetweenArrays (RG.Within, method="Aquantile")
>
> genes <- RG.Between$genes
> log_ratios <- RG.Between$M
> Mean_LogIntensity <- RG.Between$A
>
> Log_Ratio_table <- cbind (genes,log_ratios)
> MeanLog_Intensity_table <- cbind (genes,Mean_LogIntensity)
>
> write.csv (Log_Ratio_table,  file="Table of Log-ratio,M (cDNA,  
> PMCI).csv")
>
> 	[[alternative HTML version deleted]]
>
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