checknet: Validating the inferred network

In c3net: Infering large-scale gene networks with C3NET

Description

checknet takes the inferred mutual information matrix and the true network for validation. - see details.

Usage

checknet( finalrelationmatrix, realrelationmatrix)

Arguments

finalrelationmatrix	The inferred symmetric mutual information matrix, where i,j th element is the mutual information I(i,j) or I(j,i) between two variables i and j. The diagonal is set to zero.
realrelationmatrix	A symmetric reference connection matrix, where a 1 at i,j th element defines the connection between variables i and j and non-connection is represented by 0. The diagonal is all zero.

Value

checknet returns a vector with 6 elements, that contains the parameters as output <- c(precision, Fscore, recall, TP, FP, FN).

References

G. Altay, F. Emmert-Streib, "Inferring the conservative causal core of gene regulatory networks", BMC Systems Biology, (2010) 4:132.

See Also

makemim, copula, c3, c3net, c3, makemim, copula, sigtestp, sigtestMTC

Examples

data(expdata)

data(truenet)

expdata <- copula(expdata)

mim <- makemim(expdata)

Ic <- 2  #Example cut-off value for mutual information for the first step of C3NET

mim[mim < Ic] <-0  #nonsignificant values eliminated wrt C3NET step 1.

net <- c3(mim)  # regulatory network inferred (non zero elements stand for links of
		# the predicted network)

scores <- checknet(net,truenet)

c3net documentation built on May 2, 2019, 5:20 p.m.