prepare_settings_leave_one_out_characterization will generate a list of lists containing the data source weights that need to be used for model construction. Every sub-list will contain the data source weights needed to make so called leave-one-out models in one ligand-signaling data source is or gene regulatory data source is left out.
prepare_settings_leave_one_out_characterization(lr_network, sig_network, gr_network, source_weights_df)A data frame / tibble containing ligand-receptor interactions (required columns: from, to, source)
A data frame / tibble containing signaling interactions (required columns: from, to, source)
A data frame / tibble containing gene regulatory interactions (required columns: from, to, source)
A data frame / tibble containing the weights associated to each individual data source. Sources with higher weights will contribute more to the final model performance (required columns: source, weight). Note that only interactions described by sources included here, will be retained during model construction.
A list of lists. Every sub-list contains 2 elements: $model_name: the name of the left-out data source; $source_weights: named numeric vector containing the data source weights that will be used for the construction of leave-one-out models.