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Spectrum and Signal Analysis

Pattern or compound identification; alignment and calibration of spectra and signals to peaks and other data sets

Characterize mass spectrometry data by detecting peaks and aligning them with references. Detect potential biomarkers by ranking features and using other machine learning techniques. Visualize mass spectra data and plot a set of peak lists from LC/MS or GC/MS data.


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mspeaksConvert raw peak data to peak list (centroided data)
mspalignAlign mass spectra from multiple peak lists from LC/MS or GC/MS data set
msalignAlign peaks in signal to reference peaks
samplealignAlign two data sets containing sequential observations by introducing gaps
isotopicdistCalculate high-resolution isotope mass distribution and density function
msheatmapCreate pseudocolor image of set of mass spectra
msdotplotPlot set of peak lists from LC/MS or GC/MS data set
msviewerExplore mass spectrum or set of mass spectra
traceplotDraw nucleotide trace plots
metafeaturesAttractor metagene algorithm for feature engineering using mutual information-based learning
rankfeaturesRank key features by class separability criteria
randfeaturesGenerate randomized subset of features
classperfEvaluate classifier performance
crossvalindGenerate indices for training and test sets


  • Mass Spectrometry Data Analysis

    The mass spectrometry functions preprocess and classify raw data from SELDI-TOF and MALDI-TOF spectrometers and use statistical learning functions to identify patterns.