Multivariate Analysis of Metabolomics Data using Random Forests

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Documentation for package ‘RFmarkerDetector’ version 1.0.1

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aucMCV AUC multiple cross-validation
autoscale Unit variance scaling method performed on the columns of the data (i.e. metabolite concentrations measured by 1H NMR or binned 1H NMR spectra)
cachexiaData Metabolite concentrations
combinatorialRFMCCV Combinatorial Monte Carlo CV
forestPerformance Characterizing the performance of a Random Forest model
getAvgAUC Computing the average AUC
getBestRFModel Extracting the best performing Random Forest model
lqvarFilter Filtering 'low quality' variables from the original dataset
mccv mccv class
mds mds class
meanCenter Mean centering performed on the columns of the data (i.e. metabolite concentrations measured by 1H NMR or binned 1H NMR spectra)
optimizeMTRY Mtry Optimization
paretoscale Pareto scaling method performed on the columns of the data table (i.e. metabolite concentrations measured by 1H NMR or binned 1H NMR spectra)
pca Principal Component Analysis
plot.mccv Plotting single or multiple ROC curves of the cross-validated Random Forest models 'plot.mccv' allows to plot single or multiple ROC curves to characterize the performace of a cross-validated Random Forest model
plot.mds Multi-dimensional Scaling (MDS) Plot
plot.pca.loadings PCA Loadings plot This function plots the relation between the original variables and the subspace dimensions. It is useful for interpreting relationships among variables.
plot.pca.scores PCA Scores plot This function creates a plot that graphically projects the original samples onto the subspce spanned by the first two principal components
plotAUCvsCombinations Plotting the average AUC as a function of the number of combinations
plotOOBvsMTRY Plotting the average OOB error and its 95% confidence interval as a function of the mtry parameter
plotVarFreq Variable Frequency Plot
rfMCCV Monte Carlo cross-validation of Random Forest models
rfMCCVPerf Extracting average accuracy and recall of a list of Random Forest models
rsd Computing relative standard deviation of a vector
rsdFilter Filtering less informative variables
screeplot Scree Plot
simpleData simpleData
tuneMTRY Tuning of the mtry parameter for a Random Forest model
tuneNTREE Tuning of the ntree parameter (i.e. the number of trees) for a Random Forest model