RFmarkerDetector: Multivariate Analysis of Metabolomics Data using Random Forests

A collection of tools for multivariate analysis of metabolomics data, which includes several preprocessing methods (normalization, scaling) and various exploration and data visualization techniques (Principal Components Analysis and Multi Dimensional Scaling). The core of the package is the Random Forest algorithm used for the construction, optimization and validation of classification models with the aim of identifying potentially relevant biomarkers.

AuthorPiergiorgio Palla, Giuliano Armano
Date of publication2016-02-29 01:29:57
MaintainerPiergiorgio Palla <piergiorgio.palla@diee.unica.it>
LicenseGPL-3
Version1.0.1

View on CRAN

Man pages

aucMCV: AUC multiple cross-validation

autoscale: Unit variance scaling method performed on the columns of the...

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....

optimizeMTRY: Mtry Optimization

paretoscale: Pareto scaling method performed on the columns of the data...

pca: Principal Component Analysis

plotAUCvsCombinations: Plotting the average AUC as a function of the number of...

plot.mccv: Plotting single or multiple ROC curves of the cross-validated...

plot.mds: Multi-dimensional Scaling (MDS) Plot

plotOOBvsMTRY: Plotting the average OOB error and its 95% confidence...

plot.pca.loadings: PCA Loadings plot This function plots the relation between...

plot.pca.scores: PCA Scores plot This function creates a plot that graphically...

plotVarFreq: Variable Frequency Plot

rfMCCV: Monte Carlo cross-validation of Random Forest models

rfMCCVPerf: Extracting average accuracy and recall of a list of Random...

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...

Files in this package

RFmarkerDetector
RFmarkerDetector/NAMESPACE
RFmarkerDetector/data
RFmarkerDetector/data/simpleData.rda
RFmarkerDetector/data/cachexiaData.rda
RFmarkerDetector/R
RFmarkerDetector/R/scaling.R RFmarkerDetector/R/RFTuning.R RFmarkerDetector/R/exampleData.R RFmarkerDetector/R/RFMCcv.R RFmarkerDetector/R/filtering.R RFmarkerDetector/R/CombinatorialCV.R RFmarkerDetector/R/plotMethods.R RFmarkerDetector/R/Exploring.R RFmarkerDetector/R/BiomarkerDiscovery.R
RFmarkerDetector/MD5
RFmarkerDetector/DESCRIPTION
RFmarkerDetector/man
RFmarkerDetector/man/aucMCV.Rd RFmarkerDetector/man/forestPerformance.Rd RFmarkerDetector/man/optimizeMTRY.Rd RFmarkerDetector/man/plot.pca.loadings.Rd RFmarkerDetector/man/mccv.Rd RFmarkerDetector/man/autoscale.Rd RFmarkerDetector/man/rfMCCV.Rd RFmarkerDetector/man/paretoscale.Rd RFmarkerDetector/man/rfMCCVPerf.Rd RFmarkerDetector/man/meanCenter.Rd RFmarkerDetector/man/screeplot.Rd RFmarkerDetector/man/lqvarFilter.Rd RFmarkerDetector/man/plot.pca.scores.Rd RFmarkerDetector/man/tuneMTRY.Rd RFmarkerDetector/man/getBestRFModel.Rd RFmarkerDetector/man/plot.mccv.Rd RFmarkerDetector/man/rsd.Rd RFmarkerDetector/man/rsdFilter.Rd RFmarkerDetector/man/plot.mds.Rd RFmarkerDetector/man/simpleData.Rd RFmarkerDetector/man/mds.Rd RFmarkerDetector/man/cachexiaData.Rd RFmarkerDetector/man/combinatorialRFMCCV.Rd RFmarkerDetector/man/pca.Rd RFmarkerDetector/man/plotAUCvsCombinations.Rd RFmarkerDetector/man/plotVarFreq.Rd RFmarkerDetector/man/tuneNTREE.Rd RFmarkerDetector/man/plotOOBvsMTRY.Rd RFmarkerDetector/man/getAvgAUC.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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