bg.adjust.fullmodel {gcrma}R Documentation

Background adjustment with sequence information (internal function)

Description

An internal function to be used by gcrma.

Usage

bg.adjust.fullmodel(pms,mms,pm.affinities,mm.affinities,index.affinities=seq(along=pms),k=6*fast+0.25*(1-fast),rho,fast=TRUE)

Arguments

pms PM intensities after optical background correction, before non-specific-binding correction.
mms MM intensities after optical background correction, before non-specific-binding correction.
index.affinities The index of pms with known sequences. (For some types of arrays the sequences of a small subset of probes are not provided by Affymetrix.)
pm.affinities Probe affinities for PM probes with known sequences.
mm.affinities Probe affinities for MM probes with known sequences.
k A tuning parameter. See details
rho correlation coefficient of log background intensity in a pair of pm/mm probes. Default=.7
fast Logical value. If TRUE a faster add-hoc algorithm is used.

Details

Assumes PM=background1+signal,mm=background2, (log(background1),log(background2))' follow bivariate normal distribution, signal distribution follows power law. bg.parameters.gcrma and sg.parameters.gcrma provide adhoc estimates of the parameters.

the original gcrma uses an emprical bayes estimate. this requires a complicated numerical integration. An add-hoc method tries to immitate the empirical bayes estimate with a PM-B but values of PM-B<k going to k. This can be thought as a shrunken MVUE. For more details see Wu et al. (2003).

Value

a vector of same length as x.

Author(s)

Rafeal Irizarry, Zhijin(Jean) Wu

See Also

gcrma


[Package gcrma version 1.1.3 Index]