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