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A C D E F G H I K L M N O P Q R S T U Z misc
| addGoAnnotations | Add GO annotations |
| addLegend | Adds a legend |
| addMarkers | Adds markers to the data |
| andy2011params | Class '"AnnotationParams"' |
| AnnotationParams | Class '"AnnotationParams"' |
| AnnotationParams-class | Class '"AnnotationParams"' |
| as.data.frame.MartInstance | Class '"MartInstance"' |
| as.data.frame.MartInstanceList | Class '"MartInstance"' |
| chains | Instrastructure to store and process MCMC results |
| checkFeatureNamesOverlap | Check feature names overlap |
| checkFvarOverlap | Compare a feature variable overlap |
| chi2 | The PCP 'chi square' method |
| chi2-method | The PCP 'chi square' method |
| chi2-methods | The PCP 'chi square' method |
| class::QSep | Quantify resolution of a spatial proteomics experiment |
| class:AnnotationParams | Class '"AnnotationParams"' |
| class:ClustDist | Class '"ClustDist"' |
| class:ClustDistList | Storing multiple ClustDist instances |
| class:GenRegRes | Class '"GenRegRes"' and '"ThetaRegRes"' |
| class:MAPParams | Localisation of proteins using the TAGM MAP method |
| class:MCMCChain | Instrastructure to store and process MCMC results |
| class:MCMCChains | Instrastructure to store and process MCMC results |
| class:MCMCParams | Instrastructure to store and process MCMC results |
| class:MCMCSummary | Instrastructure to store and process MCMC results |
| class:SpatProtVis | Class 'SpatProtVis' |
| class:ThetaRegRes | Class '"GenRegRes"' and '"ThetaRegRes"' |
| classWeights | Calculate class weights |
| ClustDist | Class '"ClustDist"' |
| clustDist | Pairwise Distance Computation for Protein Information Sets |
| ClustDist-class | Class '"ClustDist"' |
| ClustDistList | Storing multiple ClustDist instances |
| ClustDistList-class | Storing multiple ClustDist instances |
| col1 | Draw 2 data sets on one PCA plot |
| col2 | Draw 2 data sets on one PCA plot |
| combineThetaRegRes | Class '"GenRegRes"' and '"ThetaRegRes"' |
| data1 | Draw 2 data sets on one PCA plot |
| data2 | Draw 2 data sets on one PCA plot |
| dunkley2006params | Class '"AnnotationParams"' |
| empPvalues | Estimate empirical p-values for Chi^2 protein correlations. |
| exprsToRatios | Calculate all ratio pairs |
| exprsToRatios-method | Calculate all ratio pairs |
| exprsToRatios-methods | Calculate all ratio pairs |
| f1Count | Class '"GenRegRes"' and '"ThetaRegRes"' |
| f1Count-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| favourPrimary | Class '"GenRegRes"' and '"ThetaRegRes"' |
| fDataToUnknown | Update a feature variable |
| filterAttrs | Class '"MartInstance"' |
| filterBinMSnSet | Filter a binary MSnSet |
| filterMaxMarkers | Removes class/annotation information from a matrix of candidate markers that appear in the 'fData'. |
| filterMinMarkers | Removes class/annotation information from a matrix of candidate markers that appear in the 'fData'. |
| filterZeroCols | Remove 0 columns/rows |
| filterZeroRows | Remove 0 columns/rows |
| flipGoTermId | Convert GO ids to/from terms |
| GenRegRes | Class '"GenRegRes"' and '"ThetaRegRes"' |
| GenRegRes-class | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getAnnotationParams | Class '"AnnotationParams"' |
| getF1Scores | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getF1Scores-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getFilterList | Class '"MartInstance"' |
| getGOEvidenceCodes | GO Evidence Codes |
| getGOFromFeatures | Retrieve GO terms for feature names |
| getLisacol | Manage default colours and point characters |
| getMarkerClasses | Returns the organelle classes in an 'MSnSet' |
| getMarkers | Get the organelle markers in an 'MSnSet' |
| getMartInstanceList | Class '"MartInstance"' |
| getMartTab | Class '"MartInstance"' |
| getNormDist | Extract Distances from a '"ClustDistList"' object |
| getOldcol | Manage default colours and point characters |
| getParams | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getParams-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getParams-method | Undocumented/unexported entries |
| getPredictions | Returns the predictions in an 'MSnSet' |
| getRegularisedParams | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getRegularisedParams-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getRegularizedParams | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getRegularizedParams-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getSeed | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getSeed-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getStockcol | Manage default colours and point characters |
| getStockpch | Manage default colours and point characters |
| getUnknowncol | Manage default colours and point characters |
| getUnknownpch | Manage default colours and point characters |
| getWarnings | Class '"GenRegRes"' and '"ThetaRegRes"' |
| getWarnings-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| goIdToTerm | Convert GO ids to/from terms |
| goTermToId | Convert GO ids to/from terms |
| highlightOnPlot | Highlight features of interest on a spatial proteomics plot |
| highlightOnPlot3D | Highlight features of interest on a spatial proteomics plot |
| isMrkMat | Create a marker vector or matrix. |
| isMrkVec | Create a marker vector or matrix. |
| knnClassification | knn classification |
| knnOptimisation | knn parameter optimisation |
| knnOptimization | knn parameter optimisation |
| knnPrediction | knn classification |
| knnRegularisation | knn parameter optimisation |
| knntlClassification | knn transfer learning classification |
| knntlOptimisation | theta parameter optimisation |
| ksvmClassification | ksvm classification |
| ksvmOptimisation | ksvm parameter optimisation |
| ksvmOptimization | ksvm parameter optimisation |
| ksvmPrediction | ksvm classification |
| ksvmRegularisation | ksvm parameter optimisation |
| lapply-method | Storing multiple ClustDist instances |
| lapply-method | Class '"MartInstance"' |
| length-method | Storing multiple ClustDist instances |
| length-method | Instrastructure to store and process MCMC results |
| levelPlot | Class '"GenRegRes"' and '"ThetaRegRes"' |
| levelPlot-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| levelPlot-method | Quantify resolution of a spatial proteomics experiment |
| levelPlot-method | Undocumented/unexported entries |
| lopims | A complete LOPIMS pipeline |
| lopims1 | A complete LOPIMS pipeline |
| lopims2 | A complete LOPIMS pipeline |
| lopims3 | A complete LOPIMS pipeline |
| lopims4 | A complete LOPIMS pipeline |
| lopims5 | A complete LOPIMS pipeline |
| makeGoSet | Creates a GO feature 'MSnSet' |
| MAPParams | Localisation of proteins using the TAGM MAP method |
| MAPParams-class | Localisation of proteins using the TAGM MAP method |
| markerMSnSet | Extract marker/unknown subsets |
| markers | Create a marker vector or matrix. |
| MartInstance | Class '"MartInstance"' |
| MartInstance-class | Class '"MartInstance"' |
| MartInstanceList | Class '"MartInstance"' |
| MartInstanceList-class | Class '"MartInstance"' |
| MCMCChain | Instrastructure to store and process MCMC results |
| MCMCChain-class | Instrastructure to store and process MCMC results |
| MCMCChains | Instrastructure to store and process MCMC results |
| MCMCChains-class | Instrastructure to store and process MCMC results |
| MCMCParams-class | Instrastructure to store and process MCMC results |
| MCMCSummary | Instrastructure to store and process MCMC results |
| MCMCSummary-class | Instrastructure to store and process MCMC results |
| MCMCSummary-class. | Instrastructure to store and process MCMC results |
| minMarkers | Creates a reduced marker variable |
| MLearn-method | The 'MLearn' interface for machine learning |
| MLearnMSnSet | The 'MLearn' interface for machine learning |
| move2Ds | Displays a spatial proteomics animation |
| mrkConsProfiles | Marker consensus profiles |
| mrkEncoding | Create a marker vector or matrix. |
| mrkHClust | Draw a dendrogram of subcellular clusters |
| mrkMatAndVec | Create a marker vector or matrix. |
| mrkMatToVec | Create a marker vector or matrix. |
| mrkVecToMat | Create a marker vector or matrix. |
| MSnSetMLean | The 'MLearn' interface for machine learning |
| names-method | Storing multiple ClustDist instances |
| names-method | Quantify resolution of a spatial proteomics experiment |
| names<--method | Storing multiple ClustDist instances |
| names<--method | Quantify resolution of a spatial proteomics experiment |
| nbClassification | nb classification |
| nbOptimisation | nb paramter optimisation |
| nbOptimization | nb paramter optimisation |
| nbPrediction | nb classification |
| nbRegularisation | nb paramter optimisation |
| nDatasets | Class '"MartInstance"' |
| nndist | Nearest neighbour distances |
| nndist-method | Nearest neighbour distances |
| nndist-methods | Nearest neighbour distances |
| nnetClassification | nnet classification |
| nnetOptimisation | nnet parameter optimisation |
| nnetOptimization | nnet parameter optimisation |
| nnetPrediction | nnet classification |
| nnetRegularisation | nnet parameter optimisation |
| orderGoAnnotations | Orders annotation information |
| orgQuants | Returns organelle-specific quantile scores |
| perTurboClassification | perTurbo classification |
| perTurboOptimisation | PerTurbo parameter optimisation |
| perTurboOptimization | PerTurbo parameter optimisation |
| phenoDisco | Runs the 'phenoDisco' algorithm. |
| plot-method | Class '"ClustDist"' |
| plot-method | Storing multiple ClustDist instances |
| plot-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| plot-method | Quantify resolution of a spatial proteomics experiment |
| plot-method | Class 'SpatProtVis' |
| plot-method | Undocumented/unexported entries |
| plot2D | Plot organelle assignment data and results. |
| plot2Dmethods | Plot organelle assignment data and results. |
| plot2Ds | Draw 2 data sets on one PCA plot |
| plot3D-method | Plot organelle assignment data and results. |
| plotDist | Plots the distribution of features across fractions |
| plotEllipse | A function to plot probabiltiy ellipses on marker PCA plots to visualise and assess TAGM models. |
| plsdaClassification | plsda classification |
| plsdaOptimisation | plsda parameter optimisation |
| plsdaOptimization | plsda parameter optimisation |
| plsdaPrediction | plsda classification |
| plsdaRegularisation | plsda parameter optimisation |
| prettyGoTermId | Convert GO ids to/from terms |
| pRolocmarkers | Organelle markers |
| QSep | Quantify resolution of a spatial proteomics experiment |
| qsep | Quantify resolution of a spatial proteomics experiment |
| QSep-class | Quantify resolution of a spatial proteomics experiment |
| rfClassification | rf classification |
| rfOptimisation | svm parameter optimisation |
| rfOptimization | svm parameter optimisation |
| rfPrediction | rf classification |
| rfRegularisation | svm parameter optimisation |
| sampleMSnSet | Extract a stratified sample of an 'MSnSet' |
| sapply-method | Storing multiple ClustDist instances |
| sapply-method | Class '"MartInstance"' |
| setAnnotationParams | Class '"AnnotationParams"' |
| setLisacol | Manage default colours and point characters |
| setOldcol | Manage default colours and point characters |
| setStockcol | Manage default colours and point characters |
| setStockpch | Manage default colours and point characters |
| setUnknowncol | Manage default colours and point characters |
| setUnknownpch | Manage default colours and point characters |
| show-method | Class '"AnnotationParams"' |
| show-method | Class '"ClustDist"' |
| show-method | Storing multiple ClustDist instances |
| show-method | Class '"GenRegRes"' and '"ThetaRegRes"' |
| show-method | Instrastructure to store and process MCMC results |
| show-method | Class '"MartInstance"' |
| show-method | Quantify resolution of a spatial proteomics experiment |
| show-method | Class 'SpatProtVis' |
| show-method | Localisation of proteins using the TAGM MAP method |
| show-method | Undocumented/unexported entries |
| showGOEvidenceCodes | GO Evidence Codes |
| showMrkMat | Create a marker vector or matrix. |
| SpatProtVis | Class 'SpatProtVis' |
| SpatProtVis-class | Class 'SpatProtVis' |
| subsetMarkers | Subsets markers |
| summary-method | Quantify resolution of a spatial proteomics experiment |
| svmClassification | svm classification |
| svmOptimisation | svm parameter optimisation |
| svmOptimization | svm parameter optimisation |
| svmPrediction | svm classification |
| svmRegularisation | svm parameter optimisation |
| tagmMapPredict | Localisation of proteins using the TAGM MAP method |
| tagmMapTrain | Localisation of proteins using the TAGM MAP method |
| tagmMcmcPredict | Localisation of proteins using the TAGM MCMC method |
| tagmMcmcProcess | Localisation of proteins using the TAGM MCMC method |
| tagmMcmcTrain | Localisation of proteins using the TAGM MCMC method |
| tagmPredict | Localisation of proteins using the TAGM MCMC method |
| testMarkers | Tests marker class sizes |
| testMSnSet | Create a stratified 'test' 'MSnSet' |
| ThetaRegRes | Class '"GenRegRes"' and '"ThetaRegRes"' |
| ThetaRegRes-class | Class '"GenRegRes"' and '"ThetaRegRes"' |
| thetas | Draw matrix of thetas to test |
| undocumented | Undocumented/unexported entries |
| unknownMSnSet | Extract marker/unknown subsets |
| zerosInBinMSnSet | Compute the number of non-zero values in each marker classes |
| .MCMCChain | Instrastructure to store and process MCMC results |
| .MCMCChains | Instrastructure to store and process MCMC results |
| .MCMCParams | Instrastructure to store and process MCMC results |
| .MCMCSummary | Instrastructure to store and process MCMC results |
| [-method | Storing multiple ClustDist instances |
| [-method | Instrastructure to store and process MCMC results |
| [-method | Class '"MartInstance"' |
| [[-method | Storing multiple ClustDist instances |
| [[-method | Instrastructure to store and process MCMC results |
| [[-method | Class '"MartInstance"' |