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##------------------------------------------------------------
## a wrapper for vsn to be used as a normalization method in
## the package affy
## D P Kreil <bioc07@kreil.org>
##------------------------------------------------------------
normalize.AffyBatch.vsn=function(abatch,
reference,
strata = NULL,
subsample = if (nrow(exprs(abatch))>30000L) 30000L else 0L,
subset,
log2scale = TRUE,
log2asymp = FALSE,
...) {
if(is.na(log2scale)||is.na(log2asymp)||(log2scale&&log2asymp))
stop("'log2asymp' and 'log2scale' must not both be TRUE, and not be NA.")
ind = indexProbes(abatch,"pm")
if(!missing(subset))
ind = ind[subset]
ind = unlist(ind)
vsn2res = vsn2(intensity(abatch)[ind,],reference=reference,
returnData=FALSE,subsample=subsample,...)
description(abatch)@preprocessing = c(description(abatch)@preprocessing,
list(vsnReference=vsn2res))
trsfx = predict(vsn2res,newdata=intensity(abatch),log2scale=log2scale)
## irrelevant affine transformation for ~ log2(x) for x>>1
if (log2asymp)
trsfx=(trsfx-log(2))/log(2)
intensity(abatch)<-2^trsfx
return(abatch)
}
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