normalise {arrayMagic} | R Documentation

## Normalisation of microarray data

### Description

An object of class `exprSetRG` is generated which contains the resulting normalised data.

### Usage

    normalise(arrayDataObject, subtractBackground = FALSE, method = "vsn", subGroups = NULL, channelsSeparately = FALSE, hybridisationGroups, spotIdentifier, verbose = TRUE, ...)

### Arguments

`arrayDataObject` | object of class `arrayData`; required; default missing. `arrayDataObject` must contain the raw data, i.e. a three dimensional array (spot x channel x hybridisation), cf. the class methods `getIntensities` and `intensities<-`, and must contain information on the hybridisations, cf. class methods `getHybAttr` and `{hybAttrList<-}`. If the argument `subGroups` (see below) is specified it must also contain information on the spots, cf. the class methods `getSpotAttr` and `spotAttr<-`. Note: Weights are only used by loess-type normalisations.
`subtractBackground` | logical; default: `FALSE`
`method` | character string; required; default: "`vsn`"; possible values: "`none`", "`vsn`", "`quantile`", "`loess`", "`loessScale`", "`loessQuantile`". Note: "`quantile`" and "`loess*`" normalisation transform the data to the (natural) logarithmic scale. Note: Weights are only used by loess-type normalisations. Note: "`loessScale`" and "`loessQuantile`" refer to a loess normalisation followed by a between slide normalisation, cf. the function `normalizeBetweenArrays` of the `limma` package. Note: "`quantile`" and "`loess*`" normalisations do call the corresponding methods of the `limma` package and "`vsn`" uses the `vsn` package.
`subGroups` | character string or `NULL`; required; default: `NULL`; `subGroups` allows to define subgroups of spots of each hybridisation which are normalised separately like a print-tip normalisation. The list must contain a column name refering to the `data.frame` of `getSpotAttr(arrayDataObject)`. In case of GenePix data you may for example specify the column name "Block". The column itself must contain integer values. Note: In case of `method == "vsn"`, `vsn` is called with the argument `strata`, which differs to a separate normalisation of each subgroup with `vsn` itself.
`channelsSeparately` | logical; required; default: `FALSE`; If `channelsSeparately` ist set to `TRUE` each channel is normalised separately. Only meaningful for single channel normalisation methods like "`vsn`" and "`quantile`" normalisation but not for ratio based normalisation like "`loess`".
`hybridisationGroups` | list of vectors of indexes or the character string "slideBySlide"; optional; default: missing. Each group of hybridisations is normalised separately. If missing all hybridisations are taken as one group. Only meaningful for normalisation methods like "vsn" and "quantile". The indexes must refer to the third dimension of `getIntensities(arrayDataObject)` and have to contain all hybridisations.
`spotIdentifier` | character string; optional; default missing. `spotIdentifier` specifies the column of `getSpotAttr(arrayDataObject)` which must contain non-unique spot or gene identifiers. The identifiers are used as names for the resulting `exprSetRG`-object; cf. the function `geneNames` of the `exprSetRG-class`.
`verbose` | logical; required; default: `TRUE`
`...` | further arguments which are passed to `vsn` if "`vsn`" is specified for normalisation. The arguments must not include `strata` and `verbose`.

### Value

object of class `exprSetRG`

### Author(s)

Andreas Buness <a.buness@dkfz.de>

### See Also

`exprSetRG-class`, `processArrayData`, `processArrayDataObject`

### Examples

           intensities <- array(data=runif(720),dim=c(120,2,3))
           dimnames(intensities) <- list(NULL, c("green","red"), NULL)
           hybAttr <- data.frame(Name=I(c("hx","hy","hz")), Index=c(1:3))
            arrayDataObject <- new("arrayData",
                                  intensities=intensities,
                                  hybAttrList=list(red=hybAttr,green=hybAttr)
                                 )
           exprSetRGObject <- normalise(arrayDataObject = arrayDataObject,
                                   subtractBackground = FALSE,
                                   method = "none",
                                   verbose = TRUE
                                   )
           nRed <- exprs(getExprSetRed(exprSetRGObject))
           nGreen <- exprs(getExprSetGreen(exprSetRGObject))
           stopifnot( all.equal.numeric( nRed, intensities[,"red",] ) )
           stopifnot( all.equal.numeric( nGreen, intensities[,"green",] ) )

[Package arrayMagic version 1.5.4 Index]