calculate_models_mcc: Calculate the Matthews correlation coefficient for each model

In emba: Ensemble Boolean Model Biomarker Analysis

Description

Calculate the Matthews correlation coefficient for each model

Usage

calculate_models_mcc(
  observed.model.predictions,
  unobserved.model.predictions,
  number.of.drug.comb.tested
)

Arguments

observed.model.predictions	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)
unobserved.model.predictions	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)
number.of.drug.comb.tested	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.

Value

a numeric vector of MCC values, each value being in the [-1,1] interval. The names attribute holds the models' names if applicable (i.e. the input data.frames have rownames).

See Also

Other confusion matrix calculation functions: calculate_mcc(), calculate_models_synergies_fn(), calculate_models_synergies_fp(), calculate_models_synergies_tn(), calculate_models_synergies_tp()

emba documentation built on Jan. 7, 2021, 9:09 a.m.