justGCRMA {gcrma}R Documentation

Compute GCRMA Directly from CEL Files

Description

This function converts CEL files into an exprSet using the robust multi-array average (RMA) expression measure with help of probe sequences.

Usage

just.gcrma(..., filenames=character(0),
                       phenoData=new("phenoData"),
                       description=NULL,
                       notes="", compress=getOption("BioC")$affy$compress.cel,
                       normalize=TRUE, bgversion=2, 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=0.7, optical.correct=TRUE,
                       verbose=TRUE, fast=TRUE, minimum=1, optimize.by=c("speed","memory"))

justGCRMA(..., filenames=character(0),
                     widget=getOption("BioC")$affy$use.widgets,
                     compress=getOption("BioC")$affy$compress.cel,
                     celfile.path=getwd(),
                     sampleNames=NULL,
                     phenoData=NULL,
                     description=NULL,
                     notes="",
                     normalize=TRUE, 
                     bgversion=2, 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=0.7, optical.correct=TRUE,
                     verbose=TRUE, fast=TRUE, minimum=1, optimize.by=c("speed","memory"))

Arguments

... file names separated by comma.
filenames file names in a character vector.
widget a logical specifying if widgets should be used.
compress are the CEL files compressed ?
phenoData a phenoData object
description a MIAME object
notes notes
affinity.info NULL or a list of three components: apm,amm and index, for PM probe affinities, MM probe affinities, the index of probes with known sequence, respectively.
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 .
normalize logical value. If TRUE normalize data using quantile normalization
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.
optimize.by "speed" will use a faster algorithm but more RAM, and "memory" will be slower, but require less RAM.
bgversion integer value indicating which RMA background to use 1: use background similar to pure R rma background given in affy version 1.0 - 1.0.2 2: use background similar to pure R rma background given in affy version 1.1 and above.
minimum .
celfile.path a character denoting the path 'ReadAffy' should look for cel files
sampleNames a character vector of sample names to be used in the 'AffyBatch'

Details

This method should require much less RAM than the conventional method of first creating an AffyBatch and then running gcrma.

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 tuning factor k will have different meanings if one uses the fast (add-hoc) algorithm or the empirical bayes approach. See Wu et al. (2003)

fast.bkg and mem.bkg are two internal functions.

Value

An exprSet.

Author(s)

James W. MacDonald

Examples



[Package gcrma version 2.2.0 Index]