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.

Author | Piergiorgio Palla, Giuliano Armano |

Date of publication | 2016-02-29 01:29:57 |

Maintainer | Piergiorgio Palla <piergiorgio.palla@diee.unica.it> |

License | GPL-3 |

Version | 1.0.1 |

**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...

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? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.