# MicroArray Gene-expression-based Program In Error rate estimation

## Documentation for package ‘Rmagpie’ version 1.22.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.

## Help Pages

A C F G I P R S T V

## -- A --

assessment-class | assessment: A central class to perform one and two layers of external cross-validation on microarray data

## -- C --

classifyNewSamples | classifyNewSamples Method to classify new samples for a given assessment
classifyNewSamples-method | classifyNewSamples Method to classify new samples for a given assessment
classifyNewSamples-methods | classifyNewSamples Method to classify new samples for a given assessment

## -- F --

featureSelectionOptions-class | "featureSelectionOptions": A virtual class to store the options of a feature selection
finalClassifier-class | finalClassifier: A class to store the final classifier corresponding to an assessment
findFinalClassifier | findFinalClassifier Method to train and build the final classifier based on an assessment
findFinalClassifier-method | findFinalClassifier Method to train and build the final classifier based on an assessment
findFinalClassifier-methods | findFinalClassifier Method to train and build the final classifier based on an assessment

## -- G --

geneSubsets-class | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getClassifierName | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getClassifierName-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getClassifierName<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getClassifierName<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getDataset | getDataset Method to access the attributes of a dataset from an assessment
getDataset-method | getDataset Method to access the attributes of a dataset from an assessment
getDataset-methods | getDataset Method to access the attributes of a dataset from an assessment
getDataset<- | getDataset<- Method to modify the attributes of a dataset from an assessment
getDataset<--method | getDataset<- Method to modify the attributes of a dataset from an assessment
getDataset<--methods | getDataset<- Method to modify the attributes of a dataset from an assessment
getFeatureSelectionMethod-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getFeatureSelectionOptions | getFeatureSelectionOptions Method to access the attributes of a featureSelectionOptions from an assessment
getFeatureSelectionOptions-method | getFeatureSelectionOptions Method to access the attributes of a featureSelectionOptions from an assessment
getFeatureSelectionOptions-methods | getFeatureSelectionOptions Method to access the attributes of a featureSelectionOptions from an assessment
getFeatureSelectionOptions<- | getFeatureSelectionOptions<- Method to modify the attributes of a featureSelectionOptions from an assessment
getFeatureSelectionOptions<--method | getFeatureSelectionOptions<- Method to modify the attributes of a featureSelectionOptions from an assessment
getFeatureSelectionOptions<--methods | getFeatureSelectionOptions<- Method to modify the attributes of a featureSelectionOptions from an assessment
getFinalClassifier | getFinalClassifier Method to access the attributes of a finalClassifier from an assessment
getFinalClassifier-method | getFinalClassifier Method to access the attributes of a finalClassifier from an assessment
getFinalClassifier-methods | getFinalClassifier Method to access the attributes of a finalClassifier from an assessment
getGenesFromBestToWorst | finalClassifier: A class to store the final classifier corresponding to an assessment
getGenesFromBestToWorst-method | finalClassifier: A class to store the final classifier corresponding to an assessment
getMaxSubsetSize | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getMaxSubsetSize-method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getMaxSubsetSize<- | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getMaxSubsetSize<--method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getModels | finalClassifier: A class to store the final classifier corresponding to an assessment
getModels-method | finalClassifier: A class to store the final classifier corresponding to an assessment
getNoFolds1stLayer | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds1stLayer-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds1stLayer<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds1stLayer<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds2ndLayer | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds2ndLayer-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds2ndLayer<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoFolds2ndLayer<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoModels | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getNoModels-method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getNoOfRepeats | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoOfRepeats-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoOfRepeats<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoOfRepeats<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getNoThresholds | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getNoThresholds-method | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getNoThresholds<- | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getNoThresholds<--method | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getOptionValues | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getOptionValues-method | "featureSelectionOptions": A virtual class to store the options of a feature selection
getOptionValues-method | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getOptionValues<- | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getOptionValues<--method | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid
getResult1LayerCV | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult1LayerCV-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult1LayerCV<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult1LayerCV<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult2LayerCV | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult2LayerCV-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult2LayerCV<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResult2LayerCV<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getResults | getResults Method to access the result of one-layer and two-layers cross-validation from an assessment
getResults-method | getResults Method to access the result of one-layer and two-layers cross-validation from an assessment
getResults-methods | getResults Method to access the result of one-layer and two-layers cross-validation from an assessment
getSpeed | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSpeed-method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSpeed<- | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSpeed<--method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSubsetsSizes | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSubsetsSizes-method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSubsetsSizes<- | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSubsetsSizes<--method | geneSubsets: A class to handle the sizes of gene susbets to be tested during forward gene selection
getSvmKernel | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getSvmKernel-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getSvmKernel<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getSvmKernel<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getTypeFoldCreation | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getTypeFoldCreation-method | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getTypeFoldCreation<- | assessment: A central class to perform one and two layers of external cross-validation on microarray data
getTypeFoldCreation<--method | assessment: A central class to perform one and two layers of external cross-validation on microarray data

## -- I --

initialize-method | Initialize objects of class from Rmagpie

## -- P --

plotErrorsFoldTwoLayerCV | plotErrorsFoldTwoLayerCV Method to plot the error rate of a two-layer Cross-validation
plotErrorsFoldTwoLayerCV-method | plotErrorsFoldTwoLayerCV Method to plot the error rate of a two-layer Cross-validation
plotErrorsFoldTwoLayerCV-methods | plotErrorsFoldTwoLayerCV Method to plot the error rate of a two-layer Cross-validation
plotErrorsRepeatedOneLayerCV | plotErrorsRepeatedOneLayerCV Method to plot the estimated error rates in each repeat of a one-layer Cross-validation
plotErrorsRepeatedOneLayerCV-method | plotErrorsRepeatedOneLayerCV Method to plot the estimated error rates in each repeat of a one-layer Cross-validation
plotErrorsRepeatedOneLayerCV-methods | plotErrorsRepeatedOneLayerCV Method to plot the estimated error rates in each repeat of a one-layer Cross-validation
plotErrorsSummaryOneLayerCV | plotErrorsSummaryOneLayerCV Method to plot the summary estimated error rates of a one-layer Cross-validation
plotErrorsSummaryOneLayerCV-method | plotErrorsSummaryOneLayerCV Method to plot the summary estimated error rates of a one-layer Cross-validation
plotErrorsSummaryOneLayerCV-methods | plotErrorsSummaryOneLayerCV Method to plot the summary estimated error rates of a one-layer Cross-validation

## -- R --

rankedGenesImg | rankedGenesImg Method to plot the genes according to their frequency in a microarray like image
rankedGenesImg-method | rankedGenesImg Method to plot the genes according to their frequency in a microarray like image
rankedGenesImg-methods | rankedGenesImg Method to plot the genes according to their frequency in a microarray like image
runOneLayerExtCV | runOneLayerExtCV: Method to run an external one-layer cross-validation
runOneLayerExtCV-method | runOneLayerExtCV: Method to run an external one-layer cross-validation
runOneLayerExtCV-methods | runOneLayerExtCV: Method to run an external one-layer cross-validation
runTwoLayerExtCV | runTwoLayerExtCV: Method to run an external two-layers cross-validation
runTwoLayerExtCV-method | runTwoLayerExtCV: Method to run an external two-layers cross-validation
runTwoLayerExtCV-methods | runTwoLayerExtCV: Method to run an external two-layers cross-validation

## -- S --

show-method | show Display the object, by printing, plotting or whatever suits its class

## -- T --

thresholds-class | thresholds: A class to handle the thresholds to be tested during training of the Nearest Shrunken Centroid

## -- V --

vV70genes | vV70genes: van't Veer et al. 70 best genes in an object of class dataset.