binSupervised-msi.dataset-method: Return a binary mask generated applying a supervised...

In paoloinglese/SPUTNIK: Spatially Automatic Denoising for Imaging Mass Spectrometry Toolkit

Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas.

Description

Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas.

Usage

## S4 method for signature 'msi.dataset'
binSupervised(
  object,
  refImage,
  mzQuery = numeric(),
  mzTolerance = Inf,
  useFullMZ = TRUE,
  method = "svm",
  verbose = TRUE
)

Arguments

object	msi.dataset-class object
refImage	ms.image-class object. Image used as reference to manually select the ROI pixels.
mzQuery	numeric. Values of m/z used to calculate the reference image. 2 values are interpreted as interval, multiple or single values are searched in the m/z vector. It overrides useFullMZ.
mzTolerance	numeric (default = Inf). Tolerance in PPM to match the mzQueryRef. values in the m/z vector. It overrides useFullMZ.
useFullMZ	logical (default = 'TRUE“). Whether all the peaks should be used to perform the supervised segmentation.
method	string (default = 'svm'). Supervised classifier used to segment the ROI.
verbose	boolean (default = 'TRUE'). Additional output.

Value

ms.image-class object representing the binary mask image.

Author(s)

Paolo Inglese [e-mail]

paoloinglese/SPUTNIK documentation built on April 18, 2024, 8:56 p.m.