[BioC] Illumina - Beadarray - Limma

[Sean Davis]

On Thursday 15 February 2007 10:45, 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?

Unfortunately, the rank-invariant method of normalization does produce 
negative values, irregardless of background correction.  The problem with 
this is not the lmFit function, but the log2 function.  You need to either 
set your negative values to some small positive value or not use 
rank-invariant normalization.

Sean