assess_cell_quality_SVM: Assess quality of a cell - SVM version
In Teichlab/cellity: Quality Control for Single-Cell RNA-seq Data

Description Usage Arguments Details Value Examples

Assess quality of a cell - SVM version

1 2	assess_cell_quality_SVM(training_set_features, training_set_labels, ensemble_param, test_set_features)

`training_set_features`	A training set containing features (cells x features) for prediction
`training_set_labels`	Annotation of each individual cell if high or low quality (1 or 0 respectively)
`ensemble_param`	Dataframe of parameters for SVM
`test_set_features`	Dataset to predict containing features (cells x features)

This function takes a traning set + annotation to predict a test set. It requires that hyper-parameters have been optimised.

Returns a dataframe indicating which cell is low or high quality (0 or 1 respectively)

data.frame with decision on quality of cells

data(param_mES_all)
data(training_mES_features)
data(training_mES_labels)
data(mES1_features)
data(mES1_labels)
mES1_features_all <- mES1_features[[1]]
training_mES_features_all <- training_mES_features[[1]]
mES1_quality_SVM <- assess_cell_quality_SVM( training_mES_features_all, 
training_mES_labels[,2], param_mES_all, mES1_features_all)