gcrma.engine {gcrma}  R Documentation 
This function adjust for nonspecific binding when all arrays in the dataset share the same probe affinity information. It takes matrices of PM probe intensities, MM probe intensities, other negative control probe intensities(optional) and the associated probe affinities, and return one matrix of nonspecific binding corrected PM probe intensities.
gcrma.engine(pms,mms,ncs=NULL, pm.affinities=NULL,mm.affinities=NULL,anc=NULL, type=c("fullmodel","affinities","mm","constant"), k=6*fast+0.5*(1fast), stretch=1.15*fast+1*(1fast),correction=1,GSB.adjust=TRUE,rho=0.7, verbose=TRUE,fast=FALSE)
pms 
The matrix of PM intensities 
mms 
The matrix of MM intensities 
ncs 
The matrix of negative control probe intensities. When left
asNULL , the MMs are considered the negative control probes. 
pm.affinities 
The vector of PM probe affinities. Note: This can be
shorter than the number of rows in pms when some probes do not
have sequence information provided. 
mm.affinities 
The vector of MM probe affinities. 
anc 
The vector of Negative Control probe affinities. This is
ignored if MMs are used as negative controls (ncs=NULL ) 
type 
"fullmodel" for sequence and MM model. "affinities" for sequence information only. "mm" for using MM without sequence information. 
k 
A tuning factor. 
stretch 

correction 
. 
GSB.adjust 
Logical value. If TRUE , probe effects in specific binding will
be adjusted. 
rho 
correlation coefficient of log background intensity in a pair of pm/mm probes. Default=.7 
verbose 
Logical value. If TRUE messages about the progress of
the function is printed. 
fast 
Logicalvalue. If TRUE a faster addhoc 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 (addhoc) algorithm or the empirical bayes approach. See Wu
et al. (2003)
A matrix of PM intensties.
Rafeal Irizarry & Zhijin Wu
gcrma.engine2