R: Scale microarray data

normalize.loess {affy}

R Documentation

Scale microarray data

Description

Normalizes arrays using loess.

Usage

normalize.loess(mat, subset = sample(1:(dim(mat)[1]), min(c(5000,
                 nrow(mat)))), epsilon = 10^-2, maxit = 1, log.it =
                 TRUE, verbose = TRUE, span = 2/3, family.loess =
                 "symmetric")
normalize.AffyBatch.loess(abatch,type=c("together","pmonly","mmonly","separate"), ...)

Arguments

`mat`	a matrix with columns containing the values of the chips to normalize.
`abatch`	an `AffyBatch` object.
`subset`	a subset of the data to fit a loess to.
`epsilon`	a tolerance value (supposed to be a small value - used as a stopping criterion).
`maxit`	maximum number of iterations.
`log.it`	logical. If `TRUE` it takes the log2 of `mat`
`verbose`	logical. If `TRUE` displays current pair of chip being worked on.
`span`	parameter to be passed the function `loess`
`family.loess`	parameter to be passed the function `loess`. `"gaussian"` or `"symmetric"` are acceptable values for this parameter.
`type`	A string specifying how the normalization should be applied. See details for more.
`...`	any of the options of normalize.loess you would like to modify (described above).

Details

The type argument should be one of "separate","pmonly","mmonly","together" which indicates whether to normalize only one probe type (PM,MM) or both together or separately.

Examples

if (require(affydata)) {
  #data(Dilution)
  #x <- pm(Dilution[,1:3])
  #mva.pairs(x)
  #x <- normalize.loess(x,subset=1:nrow(x))
  #mva.pairs(x)
}