Circos_Plot.R

library(circlize)
library(ComplexHeatmap)

# Load data efficiently
input_data <- read.csv("input_data.csv", stringsAsFactors = FALSE)

# Define expression columns
expression_cols <- c("PT8465_R1", "PT8465_R2", "PT8465_R3", "ND6401_R1", "ND6401_R2", "ND6401_R3")
input_data[expression_cols] <- lapply(input_data[expression_cols], as.numeric)

# Create matrix for heatmap
expression_matrices <- lapply(expression_cols, function(col) {
  mat <- as.matrix(input_data[, col, drop = FALSE])
  rownames(mat) <- input_data$gene
  return(mat)
})

# Define functional annotation colors
function_colors <- c(
  "No annotation - Protein had a hit in the EggNOG database, but the function is not annotated" = "#adec93",
  "Function unknown" = "#37a9ed",
  "Intracellular trafficking and secretion" = "#0f456e",
  "Coenzyme metabolism" = "#064619",
  "Post-translational modification, protein turnover, chaperone functions" = "#c3b091",
  "Defense mechanisms" = "#6f5618",
  "Inorganic ion transport and metabolism" = "#0fe900",
  "Cell wall/membrane/envelope biogenesis" = "#f62222",
  "Amino Acid metabolism and transport" = "#e3f988",
  "Carbohydrate metabolism and transport" = "#403849",
  "Translation" = "#ff7e7e",
  "Replication and repair" = "#ff1ca1",
  "Transcription" = "#ff9f3a"
)

# Function annotation matrix
mat_function <- as.matrix(input_data$function_)
rownames(mat_function) <- input_data$gene

# Define expression color mapping
col_fun <- colorRamp2(c(0, 1, 50, 200, 500, 1000), 
                      c("#FFFFFF", "#edd6ff", "#ca85ff", "#950aff", "#6800b8", "#23003d"))

# Configure Circos plot
circos.clear()
circos.par(start.degree = 90, gap.degree = 35, track.margin = c(0.01, 0.01))

# Plot function-based heatmap
circos.heatmap(mat_function, col = function_colors, track.height = 0.05, 
               bg.border = "black", bg.lwd = 2, track.margin = c(0.02, 0.02))

# Plot expression-based heatmaps
for (mat in expression_matrices) {
  circos.heatmap(mat, col = col_fun, track.height = 0.04, track.margin = c(0.005, 0.005))
}

circos.clear()

# Create and render legends
legend_expression <- Legend(
  at = c(0, 1, 50, 200, 500, 1000),
  col_fun = col_fun,
  title = "Expression Levels",
  direction = "horizontal",
  title_gp = gpar(fontsize = 14, fontface = "bold"),
  labels_gp = gpar(fontsize = 12)
)

legend_function <- Legend(
  at = names(function_colors),
  legend_gp = gpar(fill = function_colors),
  title = "Gene Function",
  ncol = 3,
  grid_height = unit(5, "mm"),
  grid_width = unit(5, "mm")
)

# Pack and draw legends
grid.draw(packLegend(legend_expression, legend_function))