Automated Classification of Mass Spectra

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Documentation for package ‘MSclassifR’ version 0.5.0

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build_XY_from_peaks Build design matrix X and response Y from peak intensities
build_X_from_peaks_fast Build a sample-by-m/z intensity matrix from a list of peaks (fast, C++-backed)
calculate_distance Function calculating the distance between two vectors.
CitrobacterRKImetadata Metadata of mass spectra corresponding to the bacterial species _Citrobacter_ sp. from The Robert Koch-Institute (RKI) database of microbial MALDI-TOF mass spectra
CitrobacterRKIspectra Mass spectra corresponding to the bacterial species _Citrobacter_ sp. from The Robert Koch-Institute (RKI) database of microbial MALDI-TOF mass spectra
d_left_join Function joining two tables based not on exact matches
fast_cvpvi Fast cross-validated permutation variable importance (ranger-based)
fast_find_neighbors Function finding k Nearest Neighbors for each row of a matrix
fast_generate_synthetic Function generating synthetic examples using SMOTE
fast_mda Fast MDA-style variable selection using ranger permutation importance
LogReg Fast supervised classifier with m/z subsetting and optional sampling
LogReg_rf_fast Fast random-forest classifier with stratified CV and in-fold sampling (ranger, caret-free)
MSclassifR Automated classification of mass spectra
PeakDetection Detection of peaks in MassSpectrum objects
PlotSpectra Plot spectral data with optional peak markers
PredictFastClass Fast class prediction from peak lists using linear regressions
PredictLogReg Prediction of the category to which a mass spectrum belongs
SelectionVar Variable selection using methods based on random forests and others.
SelectionVarStat Fast feature (m/z) selection using multiple hypothesis testing (LIMMA/ANOVA/Kruskal) with optional class balancing (no/up/down/SMOTE)
SignalProcessing Signal processing for MALDI-TOF spectra (wrapper to SignalProcessingUltra)
SignalProcessingUltra Optimized signal processing for MALDI-TOF spectra (parallel + optional C++ alignment)
smote_classif SMOTE for classification datasets