normalize.loess {affy}R Documentation

Scale microarray data


Normalizes arrays using loess.


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


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 criterium).
maxit maximum number of iterations. 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).


The type arguement 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



     #x <- pm(Dilution[,1:3])
     #x <- normalize.loess(x,subset=1:nrow(x))

[Package affy version 1.8.1 Index]