affy (version 1.50.0)

normalize.loess: 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.

See Also

normalize

Examples

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

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