vsn2trsf {vsn} | R Documentation

## Apply the vsn transformation to data

### Description

Apply the vsn transformation to data.

### Usage

    ## S4 method for signature 'vsn':
    predict(object, newdata, strata=object@strata, log2scale=TRUE, useDataInFit=FALSE)

### Arguments

`object` | An object of class `vsn` that contains transformation parameters and strata information, typically this is the result of a previous call to `vsn2`.
`newdata` | Object of class `ExpressionSet`, `NChannelSet`, `AffyBatch` (from the `affy` package), `RGList` (from the `limma` package), `matrix` or `numeric`, with the data to which the fit is to be applied to.
`strata` | Optional, a `factor` or `integer` that aligns with the rows of `newdata`; see the `strata` argument of `vsn2`.
`log2scale` | If `TRUE`, the data are returned on the glog scale to base 2, and an overall offset c is added (see Value section of the `vsn2` manual page). If `FALSE`, the data are returned on the glog scale to base e, and no offset is added.
`useDataInFit` | If `TRUE`, then no transformation is attempted and the data stored in `object` is transferred appropriately into resulting object, which otherwise preserves the class and metadata of `newdata`. This option exists to increase performance in constructs like
           fit = vsn2(x, ...)
           nx = predict(fit, newdata=x)
and is used, for example, in the `justvsn` function.

### Value

An object typically of the same class as `newdata`. There are two exceptions: if `newdata` is an `RGList`, the return value is an `NChannelSet`, and if `newdata` is numeric, the return value is a `matrix` with 1 column.

### Author(s)

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

### Examples

    data("kidney")

    ## nb: for random subsampling, the 'subsample' argument of vsn
    ##   provides an easier way to do this
    fit = vsn2(kidney[sample(nrow(kidney), 500), ])
    tn = predict(fit, newdata=exprs(kidney))

[Package vsn version 3.2.1 Index]