scPred - Single cell prediction using singular value decomposition and machine learning classification


[Up] [Top]

Documentation for package ‘scPred’ version 0.0.0.9000

Help Pages

crossTab Gets contingency table
crossTab-method Gets contingency table
eigenDecompose Eigendecompose gene expression matrix
getAccuracy Get accuracy
getAccuracy-method Get accuracy
getFeatureSpace Get informative principal components
getLoadings Get loadings matrix
getLoadings-method Get loadings matrix
getPCA Get principal components
getPCA-method Get principal components
getPredictions Get predictions
getPredictions-method Get training probabilities
getTrainPred Get training predictions
getTrainResults Get training probabilities
getTrainResults-method Get training probabilities
metadata Get metadata
metadata<- Set metadata
plotEigen Plot PCA
plotEigen-method Plot PCA
plotExp Plot gene expression data
plotExp-method Plot gene expression data
plotLoadings Plot loadings
plotLoadings-method Plot loadings
plotPredProbs Plot prediction probabilities
plotPredProbs-method Plot prediction probabilities
plotTrainProbs Plot training probabilities for all models
processPreds Prepare and tidy prediction results
projectNewData Project new data onto training principal components
scPred Definition of 'scPred' class
scPred-class Definition of 'scPred' class
scPredict Predict cell classes from a new dataset using a trained model
show-method show
trainModel Train a prediction model