rma.para: Fitting a RMA model
In RefPlus: A function set for the Extrapolation Strategy (RMA+) and Extrapolation Averaging (RMA++) methods.

Description Usage Arguments Value Note Author(s) References See Also Examples

Obtain reference quantiles and reference probe effects based on reference set Train, and calculate the gene expression

1	rma.para(Train, bg = TRUE, exp = FALSE)

`Train`	An `AffyBatch` object of the reference set microarrays.
`bg`	A logical flag. If `True`(by default), background correct `Train` using default `bg.correct.rma`.
`exp`	A logical flag. If `True`, calculate the RMA measurements of `Train`. If `False`, return 0.

`Reference.Quantiles`	Reference quantiles derived from `Train`.
`probe.effects`	Estimated probe effects derived from `Train`.
`expression`	RMA measurements of `Train`.

The RMA procedure requires a lot of computer memory.

Kai-Ming Chang(kaiming@gmail.com)

Chang,K.M., Harbron,C., South,M.C. (2006) An Exploration of Extensions to the RMA Algorithm. Available with the RefPlus package.

rmaplus,rmaref.predict

if (require(affydata)) {
  ## Use Dilution in affydata package
  data(Dilution)

  ## Background correct, estimate the probe effects, and calculate the 
  ## RMA intensities using rma.para function.
  Ex<-rma.para(Dilution, bg=TRUE,exp=TRUE)

  ## Calculate the rma intensities using rma function.
  Ex0<-exprs(rma(Dilution))

  plot(Ex$express[,1],Ex0[,1])
}