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Table 1 Available functions of the package minet (version 1.1.6)

From: minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks Using Mutual Information

Function Usage
minet(data, method, estimator, disc, nbins) Network inference from data
discretize(data, disc, nbins) Unsupervised discretization
build.mim(data, estimator) Mutual information matrix estimation
Estimator can be ""mi.empirical","mi.mm","mi.shrink" and "mi.sg".
mrnet(mim) MRNET algorithm
aracne(mim) ARACNE algorithm
clr(mim) CLR algorithm
norm(net) matrix/network normalization
validate(net1, net2, steps) Computes confusion matrices
pr(table) Computes precisions and recalls from confusion matrices
rates(table) Computes true positive rates and false positive rates from confusion matrices
show.pr(table) Displays precision-recall curves from confusion matrices
show.roc(table) Displays receiver operator caracteristic curves from confusion matrices
fscores(table) Returns a vector of F β -scores from confusion matrices
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