rma.para {RefPlus} | R Documentation

## Fitting a RMA model

### Description

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

### Usage

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

### Arguments

`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.

### Value

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

### Note

The RMA procedure requires a lot of computer memory.

### Author(s)

Kai-Ming Chang(Kai-Ming.Chang@astrazeneca.com, kaiming@gmail.com)

### References

Chang,K.M., Harbron,C., South,M.C. (2006) An Exploration of Extensions to the RMA Algorithm. (Submitted)

### See Also

`rmaplus`,`rmaref.predict`

### Examples

    ## Use affybatch.example in Affy package
    data(affybatch.example)

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

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

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

[Package RefPlus version 1.4.0 Index]