Spatially Automatic Denoising for Imaging Mass Spectrometry Toolkit

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Documentation for package ‘SPUTNIK’ version 1.4.2

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applyPeaksFilter Apply the results of a peaks filter.
applyPeaksFilter-method Apply the results of a peaks filter.
applyPeaksFilter-msi.dataset-method Apply the results of a peaks filter.
binKmeans Return a binary mask generated applying k-means clustering on first 10 principal components of peaks intensities.
binKmeans-method Return a binary mask generated applying k-means clustering on first 10 principal components of peaks intensities.
binKmeans2 Return a binary mask generated applying k-means clustering on peaks intensities. A finer segmentation is obtained by using a larger number of clusters than 2. The off-sample clusters are merged looking at the most frequent labels in the image corners. The lookup areas are defined by the kernel size.
binKmeans2-method Return a binary mask generated applying k-means clustering on peaks intensities. A finer segmentation is obtained by using a larger number of clusters than 2. The off-sample clusters are merged looking at the most frequent labels in the image corners. The lookup areas are defined by the kernel size.
binOtsu Binarize MS image using Otsu's thresholding.
binOtsu-method Binarize MS image using Otsu's thresholding.
binSupervised Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas.
binSupervised-method Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas.
bladderMALDIRompp2010 Load the example MALDI-MSI data.
closeImage Apply morphological closing to binary image.
closeImage-method Apply morphological closing to binary image.
countPixelsFilter Filter based on the minimum number of connected pixels in the ROI.
createPeaksFilter Generate a peak filter object.
CSRPeaksFilter Performs the peak selection based on complete spatial randomness test.
getIntensityMat Return the peaks intensity matrix.
getIntensityMat-method Return the peaks intensity matrix.
getMZ Return the m/z vector.
getMZ-method Return the m/z vector.
getShapeMSI Returns the geometrical shape of MSI dataset
getShapeMSI-method Returns the geometrical shape of MSI dataset
gini.index Gini index.
globalPeaksFilter Reference similarity based peak selection.
invertImage Invert the colors of an MS image.
invertImage-method Invert the colors of an MS image.
ms.image-class ms.image-class definition.
msi.dataset-class msi.dataset-class S4 class definition containing the information about the mass spectrometry imaging dataset.
msiDataset Constructor for msi.dataset-class objects.
msImage Constructor for ms.image-class objects.
NMI Normalized mutual information (NMI).
normIntensity Normalize the peaks intensities.
normIntensity-method Normalize the peaks intensities.
numDetectedMSI Generates an msImage representing the number of detected peaks per pixel. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample.
numDetectedMSI-method Generates an msImage representing the number of detected peaks per pixel. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample.
ovarianDESIDoria2016 Load the example DESI-MSI data.
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.
PCAImage-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.
plot Visualize an MS image. 'plot' extends the generic function to ms.image-class objects.
plot-method Visualize an MS image. 'plot' extends the generic function to ms.image-class objects.
refImageBinaryKmeans Calculate the binary reference image using k-means clustering. K-Means is run on the first 'npcs' principal components to speed up the calculations.
refImageBinaryKmeansMulti Calculate the binary reference image using k-means clustering with multi-cluster merging. K-means is run on the first 'npcs' principal components to speed up the calculations.
refImageBinaryOtsu Calculate the binary reference image using Otsu's thresholding.
refImageBinarySVM Calculate the binary reference image using linear SVM trained on manually selected pixels.
refImageContinuous 'refImageContinuous' returns the reference image, calculated using the 'method'. This image represents the basic measure for the filters in SPUTNIK.
refImageOtsu Calculate the binary reference image using k-means clustering. K-Means is run on the first 'npcs' principal components to speed up the calculations.
removeSmallObjects Remove binary ROI objects smaller than user-defined number of pixels
removeSmallObjects-method Remove binary ROI objects smaller than user-defined number of pixels
scatter.ratio Pixel scatteredness ratio.
smoothImage Apply Gaussian smoothing to an MS image.
smoothImage-method Apply Gaussian smoothing to an MS image.
spatial.chaos Spatial chaos measure.
splitPeaksFilter Test for the presence of split peaks.
SSIM Structural similarity index (SSIM).
totalIonCountMSI Generates an msImage representing pixels total-ion-counts. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample.
totalIonCountMSI-method Generates an msImage representing pixels total-ion-counts. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample.
varTransform Variance stabilizing transformation.
varTransform-method Variance stabilizing transformation.