Nothing
Score_adjust_PPI <-
function(scaled_node_score,scaled_edge_score,PPI,lam,subnet,num_random_sampling,best_score)
{
all_genes<-names(scaled_node_score)
node_num<-length(subnet)
genes_selected<-all_genes[subnet]
edges_selected<- PPI[,1] %in% genes_selected & PPI[,2] %in% genes_selected
num_edges_selected<-sum(edges_selected)
#Random sampling
random_score<-rep(0,num_random_sampling)
for(i in 1:num_random_sampling){
sampled_edges <- sample(1:dim(PPI)[1],num_edges_selected)
edge_score<-sum(scaled_edge_score[sampled_edges])/sqrt(num_edges_selected)
sampled_nodes <- sample(1:length(all_genes),node_num)
node_score<-sum(scaled_node_score[sampled_nodes])/sqrt(node_num)
random_score[i]<- lam*edge_score + (1-lam)*node_score
print(i)
}
mean<-mean(random_score)
sd<-sd(random_score)
adjusted_score<-(best_score-mean)/sd
return (adjusted_score)
}
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