threestepPLM {affyPLM} | R Documentation |
This function converts an AffyBatch
into an
PLMset
using a three step expression measure.
threestepPLM(object,subset=NULL, normalize=TRUE,background=TRUE,background.method="RMA.2",normalize.method="quantile",summary.method="median.polish",background.param = list(),normalize.param=list(),output.param=list(), model.param=list())
object |
an AffyBatch |
subset |
a vector with the names of probesets to be used. If NULL then all probesets are used. |
normalize |
logical value. If TRUE normalize data using
quantile normalization |
background |
logical value. If TRUE background correct
using RMA background correction |
background.method |
name of background method to use. |
normalize.method |
name of normalization method to use. |
summary.method |
name of summary method to use. |
background.param |
list of parameters for background correction methods |
normalize.param |
list of parameters for normalization methods |
output.param |
list of parameters for output methods |
model.param |
list of parameters for model methods |
This function computes the expression measure using threestep
methods. It returns a PLMset
. The most important
difference is that the PLMset allows you to access the residuals
which the threestep
function does not do.
An PLMset
Ben Bolstad bolstad@stat.berkeley.edu
Bolstad, BM (2004) Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. PhD Dissertation. University of California, Berkeley.
expresso
,
rma
, threestep
,
rmaPLM
, fitPLM
data(affybatch.example) # should be equivalent to rma() ## Not run: eset <- threestepPLM(affybatch.example)