cellity (version 1.0.2)

assess_cell_quality_SVM: Assess quality of a cell - SVM version

Description

Assess quality of a cell - SVM version

Usage

assess_cell_quality_SVM(training_set_features, training_set_labels, ensemble_param, test_set_features)

Arguments

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)

Value

Returns a dataframe indicating which cell is low or high quality (0 or 1 respectively)data.frame with decision on quality of cells

Details

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

Examples

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)