justvsn {vsn} | R Documentation

## Wrapper functions for vsn

### Description

`justvsn` returns the vsn-normalised intensities in an object generally of the same class as its first argument (see the man page of `predict` for details). It preserves the metadata. It is equivalent to calling

      fit = vsn2(x, ...)
      nx = predict(fit, newdata=x, useDataInFit = TRUE)

`vsnrma` is a wrapper around `vsn2` and `rma`

### Usage

    justvsn(x, ...)
    vsnrma(x, ...)

### Arguments

`x` | For `justvsn`, any kind of object for which `vsn2` methods exist. For `vsnrma`, an `AffyBatch`.
`...` | Further arguments that get passed on to `vsn2`.

### Details

`vsnrma` does probe-wise background correction and between-array normalization by calling `vsn2` on the perfect match (PM) values only. Probeset summaries are calculated with the medianpolish algorithm of `rma`.

### Author(s)

Wolfgang Huber http://www.ebi.ac.uk/huber

### See Also

`vsn2`

### Examples

    ##--------------------------------------------------
    ## use "vsn2" to produce a "vsn" object
    ##--------------------------------------------------
    data("kidney")
    fit = vsn2(kidney)
    nkid = predict(fit, newdata=kidney)

    ##--------------------------------------------------
    ## justvsn on ExpressionSet
    ##--------------------------------------------------
    nkid2 = justvsn(kidney)
    stopifnot(identical(exprs(nkid), exprs(nkid2)))

    ##--------------------------------------------------
    ## justvsn on AffyBatch
    ##--------------------------------------------------
    data("affybatch.example")
    data("cdfenv.example")
    abe1 = justvsn(affybatch.example)
    abe2 = vsnrma(affybatch.example)

    ##--------------------------------------------------
    ## justvsn on RGList
    ##--------------------------------------------------
    rg = new("RGList", list(R=exprs(kidney)[,1,drop=FALSE], G=exprs(kidney)[,2,drop=FALSE]))
    erge = justvsn(rg)

[Package vsn version 3.6.0 Index]