This function uses the
function on a vector of drug combinations that were observed as synergistic
(e.g. by experiments) but also found as such by at least one of the models
(these drug combinations are the
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get_avg_activity_diff_mat_based_on_specific_synergy_prediction( model.predictions, models.stable.state, predicted.synergies, penalty = 0 )
a character vector of the synergies (drug
combination names) that were predicted by at least one of the models
in the dataset. It must be a subset of the column names (the drug combinations)
value between 0 and 1 (inclusive). A value of 0 means no penalty and a value of 1 is the strickest possible penalty. Default value is 0. This penalty is used as part of a weighted term to the difference in a value of interest (e.g. activity or link operator difference) between two group of models, to account for the difference in the number of models from each respective model group.
a matrix whose rows are vectors of average node activity state differences between two groups of models where the classification for each individual row was based on the prediction or not of a specific synergistic drug combination. The row names are the predicted synergies, one per row, while the columns represent the network's node names. Values are in the [-1,1] interval.
Other average data difference functions:
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