MSProcessedImagingExperiment-class {Cardinal} | R Documentation

## MSProcessedImagingExperiment: Dense mass spectrometry imaging experiments

### Description

The `MSProcessedImagingExperiment` class is a simple extension of `MSImagingExperiment` for sparse spectra. All methods for that class apply. In addition, each data element must be stored as a column-major `sparse_mat`.

### Methods

All methods for `ImagingExperiment` and `SparseImagingExperiment` also work on `MSProcessedImagingExperiment` objects. Additional methods are documented below:

`mz(object) <- value`:

  Setting the m/z values changes the m/z binning scheme for the entire dataset (without modifying the underlying data).

`resolution(object) <- value`:

  Setting the m/z resolution changes the m/z binning scheme for the entire dataset (without modifying the underlying data).

`tolerance(object)`, `tolerance(object) <- value`:

  Get or set the binning tolerance for sparse spectra or peaks.

`mzData(object)`, `mzData(object) <- value`:

  Get or set the underlying (pre-binned) m/z values associated with the sparse mass spectra.

`peakData(object)`, `peakData(object) <- value`:

  Get or set the underlying (pre-binned) intensity values associated with the sparse mass spectra.

`tolerance(object)`, `tolerance(object) <- value`:

  Get or set the binning tolerance for sparse spectra or peaks.

`combiner(object)`, `combiner(object) <- value`:

  Get or set the binning function for sparse spectra or peaks.

`collect(x, ..., as.matrix=FALSE)`:

  Pull all data elements of `imageData` into memory as sparse matrices.

### Author(s)

Kylie A. Bemis

### See Also

`MSImagingExperiment`, `MSContinuousImagingExperiment`

[Package Cardinal version 2.2.6 Index]