DREAM_Evaluation: DREAM GRN Evaluation

In paubellot/DREAM_Evaluation: Evaluation of GRN inference against Golden Standard with DREAM framework.

Description

This function allows you to evaluate a GRN inference against golden standard (GS).

Usage

DREAM_Evaluation(gold_positives, prediction_raw)

Arguments

gold_positives	matrix with three columns that contains the GS in the form of edgelist.
predict_raw	matrix with three columns that contains the inferred GRN in the form of edgelist

Value

list containing the metrics [TPR FPR PREC REC L AUROC AUPR] TPR: vector with True Positive Ratio FPR: vector with False Positive Ratio PREC: vector with Precision REC: vector with Recall L: prediction list length AUROC: area under ROC AUPR: area under PR

Examples

net <- matrix(rnorm(100),10,10)
GS <- matrix(rnorm(100),10,10)
GS[which(GS>0.5)]<-1
GS[GS!=1] <- 0
diag(GS) <- 0
net <- change_network_format(net)
GS <- change_network_format(GS)
Ev <- DREAM_Evaluation(GS,net)

paubellot/DREAM_Evaluation documentation built on May 24, 2019, 8:22 p.m.