normalizeAffyBatchLoessPara {affyPara} | R Documentation |
Parallelized loess normalization of arrays.
normalizeAffyBatchLoessPara(cluster, object, phenoData = new("AnnotatedDataFrame"), cdfname = NULL, type=c("separate","pmonly","mmonly","together"), subset = NULL, epsilon = 10^-2, maxit = 1, log.it = TRUE, span = 2/3, family.loess ="symmetric", verbose=FALSE)
cluster |
A cluster object obtained from the function makeCluster in the SNOW package. |
object |
An object of class AffyBatch OR a character vector with the names of CEL files OR a (partitioned) list of character vectors with CEL file names. |
phenoData |
An AnnotatedDataFrame object. |
cdfname |
Used to specify the name of an alternative cdf package. If set to NULL , the usual cdf package based on Affymetrix' mappings will be used. |
type |
A string specifying how the normalization should be applied. |
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 |
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. |
verbose |
A logical value. If TRUE it writes out some messages. |
Parallelized loess normalization of arrays.
For the serial function and more details see the function normalize.AffyBatch.loess
.
For using this function a computer cluster using the snow
package has to be started.
In the loess normalization the arrays will compared by pairs. Therefore at every node minimum two arrays have to be!
An AffyBatch of normalized objects.
Markus Schmidberger schmidb@ibe.med.uni-muenchen.de, Ulrich Mansmann mansmann@ibe.med.uni-muenchen.de
## Not run: library(affyPara) if (require(affydata)) { data(Dilution) c1 <- makeCluster(3) AffyBatch <- normalizeAffyBatchLoessPara(c1, Dilution, verbose=TRUE) stopCluster(c1) } ## End(Not run)