View source: R/characterization_data_sources.R
prepare_settings_leave_one_in_characterization | R Documentation |
prepare_settings_leave_one_in_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-in models in which only one ligand-signaling data source is used and all gene regulatory data sources (or vice versa).
prepare_settings_leave_one_in_characterization(lr_network, sig_network, gr_network, source_weights_df)
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) |
source_weights_df |
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-in data source; $source_weights: named numeric vector containing the data source weights that will be used for the construction of leave-one-in models.
## Not run:
weights_settings_loi = prepare_settings_leave_one_in_characterization(lr_network,sig_network, gr_network, source_weights_df)
## End(Not run)
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