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, log.it =
TRUE, verbose = TRUE, span = 2/3, family.loess =
"symmetric")
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 |
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 |
verbose |
logical. If |
span |
parameter to be passed the function |
family.loess |
parameter to be passed the function
|
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 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.
if (require(affydata)) {
#data(Dilution)
#x <- pm(Dilution[,1:3])
#mva.pairs(x)
#x <- normalize.loess(x,subset=1:nrow(x))
#mva.pairs(x)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.