Calculate the Matthews correlation coefficient for each model
calculate_models_mcc(observed.model.predictions,
unobserved.model.predictions, number.of.drug.comb.tested)
data.frame
object with rows the models
and columns the drug combinations that were found as synergistic
(positive results). Possible values for each model-drug combination
element are either 0 (no synergy predicted), 1 (synergy was
predicted) or NA (couldn't find stable states in either the drug
combination inhibited model or in any of the two single-drug inhibited models)
data.frame
object with rows the models
and columns the drug combinations that were found as non-synergistic
(negative results). Possible values for each model-drug combination
element are either 0 (no synergy predicted), 1 (synergy was
predicted) or NA (couldn't find stable states in either the drug
combination inhibited model or in any of the two single-drug inhibited models)
numeric. The total number of drug
combinations tested, which should be equal to the sum of the columns of the
observed.model.predictions
and the unobserved.model.predictions
.
a numeric vector of MCC values, each value being in the [-1,1] interval or NaN. The names attribute holds the models' names.
Other confusion matrix calculation functions: calculate_mcc
,
calculate_models_synergies_fn
,
calculate_models_synergies_fp
,
calculate_models_synergies_tn
,
calculate_models_synergies_tp