Prepare settings for one-vs-one characterization — prepare_settings_one_vs_one

prepare_settings_one_vs_one_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 one-vs-one models in which only one ligand-signaling data source and only one gene regulatory data source is used. It is also possible to construct one-vs-one-vs-one models by keeping 1 ligand-receptor, 1 signaling and 1 gene regulatory data source.

Usage

prepare_settings_one_vs_one_characterization(lr_network, sig_network, gr_network, lr_network_separate = FALSE)

Arguments

lr_network: A data frame / tibble containing ligand-receptor interactions (required columns: from, to, source)
sig_network: A data frame / tibble containing signaling interactions (required columns: from, to, source)
gr_network: A data frame / tibble containing gene regulatory interactions (required columns: from, to, source)
lr_network_separate: Indicate whether the one-vs-one models should contain 1 ligand-receptor, 1 signaling and 1 gene regulatory network source (TRUE) or just 1 ligand-signaling combined and 1 gene regulatory source (FALSE). Default: FALSE.

Value

A list of lists. Every sub-list contains following elements: $model_name; $source_lr_sig: the name of the left-in ligand-signaling data source (or $source_lr and $source_sig if lr_network_separate is TRUE); $source_gr: the name of the left-in gene regulatory data source and $source_weights: named numeric vector containing the data source weights that will be used for the construction of one-vs-one models.

Examples

if (FALSE) { # \dontrun{
weights_settings_ovo <- prepare_settings_one_vs_one_characterization(lr_network, sig_network, gr_network)
weights_settings_ovo_lr_separate <- prepare_settings_one_vs_one_characterization(lr_network, sig_network, gr_network, lr_network_separate = TRUE)
} # }