# Load necessary packages
library(ggplot2)
library(reshape2)

# Create correlation matrix
cor_matrix <- matrix(c(1.000, 0.505, 0.530, 0.386,
                       0.505, 1.000, 0.280, 0.442,
                       0.530, 0.280, 1.000, 0.234,
                       0.386, 0.442, 0.234, 1.000),
                     nrow = 4, byrow = TRUE)

# Set variable names as NLR, PLR, MLR, SII
rownames(cor_matrix) <- c("NLR", "PLR", "MLR", "SII")
colnames(cor_matrix) <- c("NLR", "PLR", "MLR", "SII")

# Convert matrix to long format
cor_data <- melt(cor_matrix)

# Add significance symbols (assuming all P < 0.01, except for the diagonal)
cor_data$sig <- ifelse(cor_data$Var1 != cor_data$Var2, "**", "")

# Create heatmap
ggplot(cor_data, aes(Var1, Var2, fill = value)) +
  geom_tile() +  # Create tile plot
  geom_text(aes(label = paste0(sprintf("%.2f", value), sig)), vjust = 1) +  # Add correlation coefficients and significance symbols
  scale_fill_gradient2(low = "blue", high = "red", mid = "white", 
                       midpoint = 0, limit = c(-1, 1), space = "Lab", 
                       name = "Spearman\nCorrelation") +  # Set color gradient
  theme_minimal() +  # Use minimal theme
  theme(axis.text.x = element_text(angle = 45, vjust = 1, size = 12, hjust = 1),
        axis.title.x = element_blank(),  # Remove x-axis title
        axis.title.y = element_blank()) +  # Remove y-axis title
  coord_fixed() +  # Fix coordinate ratio
  labs(title = "Spearman Correlation Heatmap of Systemic Inflammation Indices")  # Add title

# Save plot as PNG file
ggsave("correlation_heatmap_with_sig.png", width = 8, height = 6)