normalize-methods {Cardinal} | R Documentation

## Normalize an imaging dataset

### Description

Apply normalization to the feature vectors of an imaging dataset.

### Usage

    ## S4 method for signature 'SparseImagingExperiment'
    normalize(object, method = c("tic", "rms", "reference"), ...)

    ## S4 method for signature 'MSImageSet'
    normalize(object, method = "tic",
    	...,
    	pixel = pixels(object),
    	plot = FALSE)

    ## Totial-ion-current normalization
    normalize.tic(x, tic=length(x), ...)

    ## Root-mean-square normalization
    normalize.rms(x, rms=1, ...)

    ## Reference normalization
    normalize.reference(x, feature, scale=1, ...)

### Arguments

`object` | An imaging dataset.
`method` | The normalization method to use.
`pixel` | The pixels to normalize. If less than the extent of the dataset, this will result in a subset of the data being processed.
`plot` | Plot each pixel while it is being processed?
`...` | Additional arguments passed to the normalization method.
`x` | The signal to be normalized.
`tic` | The value to which to normalize the total ion current.
`rms` | The value to which to normalize the root-mean-square.
`feature` | The feature to use as a reference for normalization.
`scale` | The value to which to normalize the reference.

### Details

Normalization is usually performed using the provided functions, but a user-created function can also be passed to `method`. In this case it should take the following arguments:

- `x`: A `numeric` vector of intensities.

- `...`: Additional arguments.

A user-created function should return a `numeric` vector of the same length.

Internally, `pixelApply` is used to apply the normalization. See its documentation page for more details on additional objects available to the environment installed to the normalization function.

### Value

An object of the same class with the normalized spectra.

### Author(s)

Kylie A. Bemis

### See Also

`MSImagingExperiment`, `MSImageSet`, `pixelApply`, `process`

### Examples

    setCardinalBPPARAM(SerialParam())

    set.seed(2)
    data <- simulateImage(preset=1, npeaks=10, dim=c(3,3))
    data <- data[,pData(data)$circle]

    # queue normalization
    data <- normalize(data, method="tic")

    # apply normalization
    data_normalized <- process(data)

[Package Cardinal version 2.6.0 Index]