[BioC] Illumina - Beadarray - Limma

[Simon Lin]

Here are some alternative codes for the data transformation and 
normalization process. We have compared its performance with log2-quantile, 
but not rank invariant.Note that VST transformation, unlike log2, can take 
negative values. However, our experience also suggest that background 
correction is optional.-Simon> library(lumi) # load the library

> # specify the file name output from Bead Studio
>  fileName <- 'Barnes_gene_profile.txt'
> # Read the data and create a LumiBatch object
>  example.lumi <- lumiR(fileName)

> # Transfer Illumina data as nuID annotated
> example.lumi <- addNuId2lumi(example.lumi, lib=Human.lumi)

> # Quality control based on the raw data
> lumi.Q <- lumiQ(example.lumi) # (optional)
> # As an example, plot the sample relations of QC
> plot(lumi.Q, type='sampleRelation')

> # Do default VST variance stabilizing transform
> lumi.T <- lumiT(example.lumi)

> # Do RSN between microarray normaliazation
> lumi.N <- lumiN(lumi.T)

> # Quality control after normalization
> lumi.N.Q <- lumiQ(lumi.N)  # (optional)

> # Extract expression data for further processing
> dataMatrix <- exprs(lumi.N)

> # LIMMA modeling, then
Nieves Velez de Mendizabal wrote:
> We are analyzing some data of Illumina. There are three kind of
> normalization. First of them is the method of rank invariant
> normalization, recommended by Illumina, and we would like to apply it:
>
>
>     BSData.bgnorm = backgroundNormalise(BSData)
>     T = apply(exprs(BSData.bgnorm), 1, mean)
>     BSData.rankinv = assayDataElementReplace(BSData.bgnorm, "exprs",
>     rankInvariantNormalise(exprs(BSData.bgnorm), T))
>
>
> But in BSData.rankinv I have negative values so I cannot apply the
> method lmFit in order to analyze the differential expression because of
> the log2 transformation applied.
>
>     fit = lmFit(log2(exprs(BSData.rankinv)), design)
>
> Are these two methods (rank inv method and lmFit) incompatible?
> What kind of normalization should I use in order to search
> differentially expressed genes in micro arrays of Illumina?
>
> Thanks