PCAImage,msi.dataset-method

PCAImage

Generates an RGB msImage representing the first 3 principal components. This
image can be used to qualitatively evaluate the spatial heterogeneity of the
sample.

Set of tools for peak filtering of mass spectrometry
imaging data based on spatial distribution of signal. Given a
region-of-interest, representing the spatial region where the informative
signal is expected to be localized, a series of filters determine which peak
signals are characterized by an implausible spatial distribution. The filters
reduce the dataset dimension and increase its information vs noise ratio,
improving the quality of the unsupervised analysis results, reducing data
dimension and simplifying the chemical interpretation.
The methods are described in Inglese P. et al (2019) <doi:10.1093/bioinformatics/bty622>.

Paolo Inglese

SPUTNIK

Spatially Automatic Denoising for Imaging Mass Spectrometry
Toolkit

Goncalo Correia

PCAImage,msi.dataset-method function

<dl><dt>object</dt>
<dd>msi.dataset-class object.</dd>
<dt>alignToSample</dt>
<dd>boolean (default = TRUE). If TRUE, the principal component
scores are aligned to the pixel mean intensity.</dd>
<dt>seed</dt>
<dd>set the random seed (default = <code>NULL</code>).</dd></dl>

Arguments

Generates an RGB msImage representing the first 3 principal components. This
image can be used to qualitatively evaluate the spatial heterogeneity of the
sample. — PCAImage,msi.dataset-method

<dl>

<dt>object</dt>
<dd>msi.dataset-class object.</dd>


<dt>alignToSample</dt>
<dd>boolean (default = TRUE). If TRUE, the principal component
scores are aligned to the pixel mean intensity.</dd>


<dt>seed</dt>
<dd>set the random seed (default = <code>NULL</code>).</dd>

</dl>

Generates an RGB msImage representing the first 3 principal components. This
image can be used to qualitatively evaluate the spatial heterogeneity of the
sample.

PCAImage,msi.dataset-method: Generates an RGB msImage representing the first 3 principal components. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample.

Description

Usage

Value

Arguments