| computeAuROC | R Documentation |
This function performs the same rewiring simulation as netSimAndEval. But computes the AUC and ROC as the result
computeAuROC(g,nDup,dDup,rewProb,simMethods,steps = 2, nThreads=1) ## S3 method for class 'CoReg.auROC' print(CoReg.auROC) ## S3 method for class 'CoReg.auROC' summary(CoReg.auROC) ## S3 method for class 'CoReg.auROC' plot(CoReg.auROC)
g |
The input transcription network. This should be an "igraph" object returned by the function |
nDup |
numeric value specifying number of the genes to be duplicated. These duplicated genes will be rewired |
dDup |
numeric value specifying the minimum degree for the genes to be duplicated. This function first ranks the genes based on their degrees. Then randomly selected |
rewProb |
a numeric value specifying the rewiring probability |
simMethods |
similarity indices used. Available options are: "jaccard" (jaccard similarity index),"geometric" (geometric similarity index),"invlogweighted" (inverse log weighted similarity index), "wt" (walk-trap-based similarity index) |
steps |
Number of steps for random walks, which is used by walk trap algorithm. Only valid when |
nThreads |
number of threads for running the simulation. Only valid when |
CoReg.auROC |
|
This function performes the rewring simulation similar to netSimAndEval, but uses the AUC values and ROC curves as the evaluation metrics. ROC curves can be plotted using the generic function plot().
An object of class CoReg.auROC
Qi Song
rewSim
data(athNet)
re <- computeAuROC(athNet,nDup=50,dDup=10,rewProb=0.5,simMethods=c("jaccard","geometric","invlogweighted","wt"),steps = 2, nThreads=1)
# Display summary information for rewiring simulation
print(re)
# Plot ROC curves for the result
plot(re)
# Get the AUC values for the result
re$AUC
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