Nothing
diff_gen_PPI <-
function(data1,data2,PPI){
num_sample_1 <- dim(data1)[1]
num_sample_2 <- dim(data2)[1]
num_gene <- dim(data1)[2]
PPI <-PPI[PPI[,1]%in% colnames(data1) & PPI[,2]%in% colnames(data1),]
num_edge <- dim(PPI)[1]
node_score <- rep(0,num_gene)
edge_score <- rep(0,num_edge)
type <- c(rep(0,num_sample_1),rep(1,num_sample_2))
# calculate the statistics measuing the differential expression of each gene between the 2 groups
for(i in 1:num_gene){
data <- c(data1[,i],data2[,i])
node_score[i] <- f.test(data,type)
print(i)
}
# calculate the statistics measuing the differential co-expression of each gene-pair between the 2 groups
for(i in 1:num_edge){
gene1 <- as.character(PPI[i,1])
gene2 <- as.character(PPI[i,2])
data.x <- c(data1[,gene1],data2[,gene1])
data.y <- c(data1[,gene2],data2[,gene2])
edge_score[i] <- cov(data.x,data.y)
print(i)
}
scaled_node_score <- (node_score - mean(node_score))/sd(node_score)
scaled_edge_score <- (edge_score - mean(edge_score))/sd(edge_score)
names(scaled_node_score) <- colnames(data1)
return(list(scaled_node_score, scaled_edge_score))
}
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