Package: SPUTNIK 1.4.2

SPUTNIK: Spatially Automatic Denoising for Imaging Mass Spectrometry Toolkit

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>.

Authors:Paolo Inglese [aut, cre], Goncalo Correia [aut, ctb]

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SPUTNIK.pdf |SPUTNIK.html✨
SPUTNIK/json (API)
NEWS

# Install 'SPUTNIK' in R:
install.packages('SPUTNIK', repos = c('https://piplus2.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/paoloinglese/sputnik/issues

On CRAN:

bioinformaticsdesi-msiimage-processingmaldi-msimaldi-tof-msmass-spectrometrymass-spectrometry-imaging

34 exports 4 stars 3.27 score 72 dependencies 17 mentions 43 scripts 361 downloads

Last updated 5 months agofrom:767ea23c90. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-winNOTESep 10 2024
R-4.5-linuxNOTESep 10 2024
R-4.4-winOKSep 10 2024
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R-4.3-macOKSep 10 2024

Exports:applyPeaksFilterbinOtsubladderMALDIRompp2010closeImagecountPixelsFiltercreatePeaksFilterCSRPeaksFiltergetIntensityMatgetMZgetShapeMSIgini.indexglobalPeaksFilterinvertImagemsiDatasetmsImageNMInormIntensitynumDetectedMSIovarianDESIDoria2016PCAImageplotrefImageBinaryKmeansrefImageBinaryKmeansMultirefImageBinaryOtsurefImageBinarySVMrefImageContinuousremoveSmallObjectsscatter.ratiosmoothImagespatial.chaossplitPeaksFilterSSIMtotalIonCountMSIvarTransform

Dependencies:abindbmpclassclicodetoolscolorspacecpp11deldirdigestdoSNOWdownloadere1071edgeRfansifarverforeachggplot2gluegoftestgridExtragtableigraphimagerinfotheoirlbaisobanditeratorsjpeglabelinglatticelifecyclelimmalocfitmagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrpngpolyclipproxypurrrR6RColorBrewerRcppreadbitmapreshaperlangscalessnowspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstatmodstringistringrtensortibbletiffutf8vctrsviridisviridisLitewithr

Readme and manuals

Help Manual

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