calculate_mcc

numeric vector of positives (p = tp + fn)

numeric vector of negatives (n = tn + fp)

Use this function to calculate the MCC values given vectors of TP (true
positives), FP (false positives), TN (true negatives), FN
(false negatives), P (positives) and N (negatives). Note that
the input vectors have to be of the same size and have one-to-one value
correspondence for the output MCC vector values to make sense.

Analysis and visualization of an ensemble of boolean models for
biomarker discovery in cancer cell networks. The package allows to easily
import the data results of a software pipeline that predicts synergistic drug
combinations in cancer cell lines, developed by the DrugLogics research group
in NTNU. It has generic functions that can be used to split a boolean model
dataset to model groups with regards to the models predictive performance (number of true
positive predictions or Matthews correlation coefficient score) or synergy prediction based on a given set
of observed synergies and find the average activity difference per network
node between all group pairs. Thus, given user-specific thresholds,
important nodes (biomarkers) can be accessed in the sense that they make the
models predict specific synergies (synergy biomarkers) or have better
performance in general (performance biomarkers). Lastly, if the
boolean models have a specific equation form and differ only in their link operator,
link operator biomarkers can also be assessed.

calculate_mcc: Calculate the Matthews correlation coefficient vector

Description

Usage

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See Also