plot_mcc_classes_hist

a numeric sorted vector of Matthews
Correlation Coefficient (MCC) scores, one for each model (no NaNs included).
The names attribute holds the models' names.

models.mcc.no.nan.sorted

a numeric vector of cluster ids assigned to each
model. It is the result of using <code><a rd-options="Ckmeans.1d.dp" href="/link/Ckmeans.1d.dp?package=emba&version=0.1.1&to=Ckmeans.1d.dp" data-mini-rdoc="Ckmeans.1d.dp::Ckmeans.1d.dp">Ckmeans.1d.dp</a></code>
with input the sorted vector of the models' MCC values with no NaNs included
(<code>models.mcc.no.nan.sorted</code>).

models.cluster.ids

numeric. A positive integer (&gt;2) that signifies the
number of mcc classes (groups) that we should split the models MCC values
(excluding the 'NaN' values).

num.of.mcc.classes

a numeric vector ranging from from 1 to
<code>num.of.mcc.classes</code>.

mcc.class.ids

This function is a wrapper of the <code><a rd-options="Ckmeans.1d.dp" href="/link/ahist?package=emba&version=0.1.1&to=Ckmeans.1d.dp" data-mini-rdoc="Ckmeans.1d.dp::ahist">ahist</a></code> function
for plotting nicely the distribution of the MCC models' values.

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.

John Zobolas

emba

Ensemble Boolean Model Biomarker Analysis

plot_mcc_classes_hist function

a numeric vector of cluster ids assigned to each
model. It is the result of using <code><a rd-options='Ckmeans.1d.dp' href='Ckmeans.1d.dp'>Ckmeans.1d.dp</a></code>
with input the sorted vector of the models' MCC values with no NaNs included
(<code>models.mcc.no.nan.sorted</code>).

This function is a wrapper of the <code><a rd-options='Ckmeans.1d.dp' href='ahist'>ahist</a></code> function
for plotting nicely the distribution of the MCC models' values.

plot_mcc_classes_hist: Plot histogram of the MCC classes

Description

Usage

Arguments