batchProcess-methods {Cardinal} | R Documentation |
Batch apply multiple pre-processing steps on an imaging dataset.
## S4 method for signature 'MSImageSet' batchProcess(object, normalize = NULL, smoothSignal = NULL, reduceBaseline = NULL, reduceDimension = NULL, peakPick = NULL, peakAlign = NULL, ..., layout, pixel = pixels(object), plot = FALSE)
object |
An object of class |
normalize |
Either 'TRUE' or a |
smoothSignal |
Either 'TRUE' or a |
reduceBaseline |
Either 'TRUE' or a |
reduceDimension |
Either 'TRUE' or a |
peakPick |
Either 'TRUE' or a |
peakAlign |
Either 'TRUE' or a |
layout |
The layout of the plots, given by a length 2 numeric as |
pixel |
The pixels to process. If less than the extent of the dataset, this will result in a subset of the data being processed. |
plot |
Plot the pre-processing step for each pixel while it is being processed? |
... |
Ignored. |
One of the primary purposes of this method (besides streamlining pre-processing steps) is to allow single-step reduction of larger-than-memory on-disk datasets to a smaller peak picked form without fully loading the data into memory. Therefore, the behavior for peakPick
differs somewhat from when the peakPick
method is called on its own. Typically, the spectra are preserved until peakAlign
is called. However, to save memory, only the peaks are returned by batchProcess
.
Additionally, when performing batch pre-processing, the mean spectrum is also calculated and returned as part of the 'featureData' of the result, to be used by subsequent calls to peakAlign
.
Internally, pixelApply
is used to apply the pre-processing steps, as with other pre-processing methods.
Note that reduceDimension
and peakPick
cannot appear in the same batchProcess
call together, and peakAlign
cannot appear in a batchProcess
call without peakPick
.
The peakAlign
step is performed separately from every other step.
An object of class MSImageSet
with the processed spectra.
Kylie A. Bemis
MSImageSet
,
normalize
,
smoothSignal
,
reduceBaseline
,
peakPick
,
pixelApply
data <- generateImage(as="MSImageSet", range=c(2000, 3000)) batchProcess(data, normalize=TRUE, smoothSignal=TRUE, reduceBaseline=TRUE, peakPick=TRUE, peakAlign=TRUE, layout=c(2,2), plot=FALSE) batchProcess(data, normalize=TRUE, reduceBaseline=list(blocks=200), peakPick=list(SNR=12), layout=c(1,3), plot=FALSE)