setwd("G:/projects/immunitynetworks/10comparison/AUCCal")

rm(list = ls())
library(pheatmap)
library(ggplot2)
library(igraph)
# library(purrr)
library(pROC)

load("GSE35640.RData")
# test single cell --------------------------------------------------------

# test single cell
load("1.1selectedGeneSets.RData")

mydata <- patient_info
for (i in colnames(mydata)[-(1:3)]) {
  mydata[, i] <- as.numeric(as.character(mydata[, i]))
}
colnames(mydata) <- c("Pat", "Y", "res", colnames(mydata)[-(1:3)])
mydata[, "Y"] <- gsub("NR", "0", mydata[, "Y"])
mydata[, "Y"] <- gsub("R", "1", mydata[, "Y"])
mydata[, "Y"] <- as.numeric(mydata[, "Y"])
colnames(mydata) <- gsub("-", ".", colnames(mydata))
rownames(mydata) <- mydata$Pat

up.test.auc.GSE35640 <- c()
pre.mat.GSE35640 <- data.frame(pat = rownames(mydata))
accuracy.GSE35640 <- c()
test.roc.GSE35640 <- list()
s <- 1
for (i in sel.po) {
  # i <- sel.po[1]
  aa <- paste(a.step.gen[[i]], collapse = ",")
  pre <- predict(a.log.steps[[i]], 
                 mydata[, a.step.gen[[i]]])
  
  i.roc <- roc(mydata[, "Y"], pre)
  test.roc.GSE35640[[s]] <- i.roc
  s <- s + 1
  up.test.auc.GSE35640 <- c(up.test.auc.GSE35640, i.roc$auc)
  
  pre.mat.GSE35640[, aa] <- NA
  pre.mat.GSE35640[which(pre > thres[i]), aa] <- "1" 
  pre.mat.GSE35640[which(pre < thres[i]), aa] <- "0"
  
  true.com <- pre.mat.GSE35640[, aa] == as.character(mydata[, "Y"])
  accuracy.GSE35640 <- c(accuracy.GSE35640, length(which(true.com == TRUE))/length(pre.mat.GSE35640[, aa]))
  
}

up.test.auc.GSE35640
up.test.auc.GSE35640[which(up.test.auc.GSE35640 > 0.70)]