MicroArray Gene-expression-based Program In Error rate estimation

Help pages for package ‘magpie’ version 0.2.0

C D E F G P R T V

-- C --

classifyNewSamples classifyNewSamples Method to classify new samples for a given experiment
classifyNewSamples,experiment-method classifyNewSamples Method to classify new samples for a given experiment
classifyNewSamples-methods classifyNewSamples Method to classify new samples for a given experiment

-- D --

dataset-class dataset: A simple class to store a microarray dataset and its related files

-- E --

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

-- 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 experiment
findFinalClassifier findFinalClassifier Method to train and build the final classifier based on an experiment
findFinalClassifier,experiment-method findFinalClassifier Method to train and build the final classifier based on an experiment
findFinalClassifier-methods findFinalClassifier Method to train and build the final classifier based on an experiment
formatClasses formatClasses: Format your class labels data file to be compatible with the class dataset
formatGenesExpr formatGenesExpr: Format your class labels data file to be compatible with the class dataset

-- G --

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

-- P --

plotErrorsFoldTwoLayerCV plotErrorsFoldTwoLayerCV Method to plot the error rate of a two-layer Cross-validation
plotErrorsFoldTwoLayerCV,experiment-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,experiment-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,experiment-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,experiment-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,experiment-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,experiment-method runTwoLayerExtCV: Method to run an external two-layers cross-validation
runTwoLayerExtCV-methods runTwoLayerExtCV: Method to run an external two-layers cross-validation

-- 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.