gcrma {gcrma} | R Documentation |
This function converts an AffyBatch
into an exprSet
using the robust multi-array average (RMA) expression measure with help of probe sequence.
gcrma(object,affinity.info=NULL, type=c("fullmodel","affinities","mm","constant"), k=6*fast+0.5*(1-fast),stretch=1.15*fast+1*(1-fast),correction=1, rho=.7,optical.correct=TRUE,verbose=TRUE,fast=TRUE)
object |
an AffyBatch |
affinity.info |
NULL or an AffyBatch containing the
affinities in the exprs slot. This object can be created
using the function compute.affinities . |
type |
"fullmodel" for sequence and MM model. "affinities" for sequence information only. "mm" for using MM without sequence information. |
k |
A tuning factor. |
rho |
correlation coefficient of log background intensity in a pair of pm/mm probes. Default=.7 |
stretch |
|
correction |
. |
optical.correct |
Logical value. If TRUE , optical
background correction is performed. |
verbose |
Logical value. If TRUE messages about the progress of
the function is printed. |
fast |
Logicalvalue. If TRUE a faster add-hoc algorithm is
used. |
Note that this expression measure is given to you in log base 2 scale. This differs from most of the other expression measure methods.
The tunning factor k
will have different meainngs if one uses
the fast (add-hoc) algorithm or the empirical bayes approach. See Wu
et al. (2003)
An exprSet
.
Rafeal Irizarry
if(require(affydata) & require(hgu95av2probe)){ data(Dilution) ai <- compute.affinities(cdfName(Dilution)) Dil.expr<-gcrma(Dilution,affinity.info=ai,type="affinities") }