A unifying bioinformatics framework for spatial proteomics


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Documentation for package ‘pRoloc’ version 1.16.1

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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

pRoloc-package A unifying bioinformatics framework for spatial proteomics

-- A --

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"'

-- C --

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: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"'

-- D --

data1 Draw 2 data sets on one PCA plot
data2 Draw 2 data sets on one PCA plot
dunkley2006params Class '"AnnotationParams"'

-- E --

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

-- F --

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

-- G --

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

-- H --

highlightOnPlot Highlight features of interest on a spatial proteomics plot
highlightOnPlot3D Highlight features of interest on a spatial proteomics plot

-- I --

isMrkMat Create a marker vector or matrix.
isMrkVec Create a marker vector or matrix.

-- K --

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

-- L --

lapply-method Storing multiple ClustDist instances
lapply-method Class '"MartInstance"'
length-method Storing multiple ClustDist instances
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

-- M --

makeGoSet Creates a GO feature 'MSnSet'
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"'
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

-- N --

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

-- O --

orderGoAnnotations Orders annotation information
orgQuants Returns organelle-specific quantile scores

-- P --

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
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
pRoloc A unifying bioinformatics framework for spatial proteomics
pRolocmarkers Organelle markers

-- Q --

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

-- R --

rfClassification rf classification
rfOptimisation svm parameter optimisation
rfOptimization svm parameter optimisation
rfPrediction rf classification
rfRegularisation svm parameter optimisation

-- S --

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 Class '"MartInstance"'
show-method Quantify resolution of a spatial proteomics experiment
show-method Class 'SpatProtVis'
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

-- T --

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

-- U --

undocumented Undocumented/unexported entries
unknownMSnSet Extract marker/unknown subsets

-- Z --

zerosInBinMSnSet Compute the number of non-zero values in each marker classes

-- misc --

[-method Storing multiple ClustDist instances
[-method Class '"MartInstance"'
[[-method Storing multiple ClustDist instances
[[-method Class '"MartInstance"'