# Clear the workspace
rm(list = ls())

# Load required packages
library(corrplot)
scoreFile = "score.txt"         # Score file
immFile = "ssGSEA.result.txt"    # ssGSEA result file

# Read m6A score file
score = read.table(scoreFile, header = T, sep = "\t", check.names = F, row.names = 1)
colnames(score) = "score"

# Read immune cell file
immune = read.table(immFile, header = T, sep = "\t", check.names = F, row.names = 1)
library(tidyverse)
rownames(immune) = str_replace_all(rownames(immune), "na", "")
immune = t(immune)

# Merge data
sameSample = intersect(row.names(score), row.names(immune))
data = cbind(score[sameSample,,drop=F], immune[sameSample,,drop=F])

# Calculate the correlation matrix
M = cor(data)
res1 = cor.mtest(data, conf.level = 0.95)

# Create a correlation plot
pdf(file = "cor.pdf", width = 8, height = 8)
corrplot(M,
         order = "original",
         method = "circle",
         type = "upper",
         tl.cex = 0.8,
         pch = T,
         p.mat = res1$p,
         insig = "label_sig",
         pch.cex = 1.6,
         sig.level = 0.05,
         number.cex = 1,
         col = colorRampPalette(c("yellow", "white", "red"))(50),
         tl.col = "black")
dev.off()