Some basic criteria of comparison between actual and inferred network.

Source: R/omics_network.R

Allows comparison between actual and inferred network.

# S4 method for omics_network,omics_network,numeric
compare(Net, Net_inf, nv = 1)

Arguments

Net

A omics_network object containing the actual network.

Net_inf

A omics_network object containing the inferred network.

nv

A number that indicates at which level of cutoff the comparison should be done.

Value

A vector containing : sensitivity, predictive positive value, the usual F-score (2*ppv*sens/(sppvpe+sens)), the 1/2 ponderated Fscore ((1+0.5^2)*ppv*sens/(ppv/4+sens)) and the 2 ponderated Fscore ((1+2^2)*ppv*sens/(ppv*4+sens)).

Methods

list("signature(Net = \"omics_network\", Net_inf = \"omics_network\", nv = \"numeric\")")

Net

A omics_network object containing the actual network.

Net_inf

A omics_network object containing the inferred network.

nv

A number that indicates at which level of cutoff the comparison should be done.

Author

Bertrand Frederic, Myriam Maumy-Bertrand.

Examples


data(Net)
data(Net_inf_PL)

#Comparing true and inferred networks
Crit_values=NULL

#Here are the cutoff level tested
test.seq<-seq(0,max(abs(Net_inf_PL@omics_network*0.9)),length.out=200)
for(u in test.seq){
  Crit_values<-rbind(Crit_values,Patterns::compare(Net,Net_inf_PL,u))
}
matplot(test.seq,Crit_values,type="l",ylab="Criterion value",xlab="Cutoff level",lwd=2)
legend(x="topleft", legend=colnames(Crit_values), lty=1:5,col=1:5,ncol=2,cex=.9)