Get average activity difference matrix based on MCC clustering

This function splits the Matthews correlation coefficient (MCC) scores of the models to specific groups using the Ckmeans.1d.dp package (groups are denoted by ids, e.g. 1,2,3, etc. where a larger id corresponds to a group of models with higher MCC scores) and for each pairwise combination of group id matchings (e.g. (0,1), (1,3), etc.), it uses the get_avg_activity_diff_based_on_mcc_clustering function, comparing thus all groups of models that belong to different MCC classes while taking into account the given penalty factor and the number of models in each respective model MCC group.

get_avg_activity_diff_mat_based_on_mcc_clustering(
  models.mcc,
  models.stable.state,
  num.of.mcc.classes,
  penalty = 0
)

Arguments

models.mcc	a numeric vector of Matthews Correlation Coefficient (MCC) scores, one for each model. The names attribute holds the models' names. Can be the result of using the function calculate_models_mcc.
models.stable.state	a data.frame (nxm) with n models and m nodes. The row names specify the models' names whereas the column names specify the network nodes (gene, proteins, etc.). Possible values for each model-node element can be between 0 (inactive node) and 1 (active node) inclusive.
num.of.mcc.classes	numeric. A positive integer larger than 2 that signifies the number of mcc classes (groups) that we should split the models MCC values.
penalty	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.

Value

a matrix whose rows are vectors of average node activity state differences between two groups of models where the classification was based on the models' MCC values. Rows represent the different classification group matchings, e.g. (1,2) means the models that belonged to the 1st group of MCC values vs the models that belonged to the 2nd group. The columns represent the network's node names. Values are in the [-1,1] interval.

See also

get_vector_diff

Other average data difference functions: get_avg_activity_diff_based_on_mcc_clustering(), get_avg_activity_diff_based_on_specific_synergy_prediction(), get_avg_activity_diff_based_on_synergy_set_cmp(), get_avg_activity_diff_based_on_tp_predictions(), get_avg_activity_diff_mat_based_on_specific_synergy_prediction(), get_avg_activity_diff_mat_based_on_tp_predictions(), get_avg_link_operator_diff_based_on_synergy_set_cmp(), get_avg_link_operator_diff_mat_based_on_mcc_clustering(), get_avg_link_operator_diff_mat_based_on_specific_synergy_prediction(), get_avg_link_operator_diff_mat_based_on_tp_predictions()