normalize.AffyBatch.vsn {vsn}R Documentation

Wrapper for vsn to be used as a normalization method in the package affy

Description

Wrapper for vsn to be used as a normalization method in the package affy

Usage

normalize.AffyBatch.vsn(abatch, subsample=20000, niter = 4, strata, ...)

Arguments

abatch An object of type AffyBatch.
subsample The number of probes to be sampled for the fit of the transformation parameters.
niter Parameter passed on to vsn.
strata Integer vector of length nrow(y). See vsn for details.
... Further parameters for vsn.

Details

Please refer to the "details" and "references" sections of the man page for vsn for more details about this method.

Important note: after calling vsn, the function normalize.AffyBatch.vsn exponentiates the data. This is done in order to make the behavior of this function similar to the other normalization methods in affy. There, it is assumed that in subsequent analysis steps (e.g. in medpolish), the logarithm to base 2 needs to be taken.

Value

An object of class AffyBatch.

Author(s)

Wolfgang Huber http://www.ebi.ac.uk/huber

See Also

vsn

Examples

### The example has been commented out because it takes a long time.
### Please also refer to the vignette.

## library(affy)
## library(affydata)
## data(Dilution)

### let affy know about vsn
## normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "vsn")

## es1 = expresso(Dilution[1:2], 
##        bg.correct       = FALSE,   ## bg correction is done by vsn
##        normalize.method = "vsn",
##        pmcorrect.method = "pmonly", 
##        summary.method   = "medianpolish")

## es2 = expresso(Dilution[1:2], 
##        bgcorrect.method = "rma",
##        normalize.method = "quantiles", 
##        pmcorrect.method = "pmonly",
##        summary.method   = "medianpolish")

## par(mfrow=c(2,2), pch=".")

### extract expression values
## x1 = exprs(es1)
## x2 = exprs(es2) 
 
### scatter plot
## plot(x1, main="vsn: chip 3 vs 4")
## plot(x2, main="rma: chip 3 vs 4")

### rank(mean) - difference plot
## ylim = c(-0.7, 0.7)
## plot(rank(rowSums(x1)), diff(t(x1)), ylim=ylim, main="rank(mean) vs differences")
## abline(h=0, col="red")

## plot(rank(rowSums(x2)), diff(t(x2)), ylim=ylim, main="rank(mean) vs differences")
## abline(h=0, col="red")

[Package vsn version 1.8.0 Index]