server-scripts/qhtcp-workflow/apps/r/TSHeatmaps5dev2.R

#!/usr/bin/env Rscript
# Makes heat maps of multiple experiments
#
# Updated 240724 Bryan C Roessler to improve file operations and portability
# I tried to leave as much logic intact as possible, just feeding in vars in a better way
# NOTE: The script now has 7 required arguments and a variable number of input experiments
# @arg $1 string StudyInfo.csv file
# @arg $2 string gene_ontology_edit.obo file
# @arg $3 string go_terms.tab file
# @arg $4 string All_SGD_GOTerms_for_QHTCPtk.csv
# @arg $5 string base directory
# @arg $6 string output directory

library("ontologyIndex")
library("ggplot2")
library("RColorBrewer")
library("grid")
library("ggthemes")
# library("plotly")
# library("htmlwidgets")
library("extrafont")
library("stringr")
library("org.Sc.sgd.db")
library("ggrepel")
library("gplots")

# Load arguments
args <- commandArgs(TRUE)
study_info_file <- args[1]
ontology_file <- args[2]
sgd_terms_tfile <- args[3]
all_sgd_terms_csv <- args[4]
base_dir <- args[5]
output_dir <- args[6]
study_nums <- args[7:length(args)]

# Import standard tables used in Sean's code That should be copied to each ExpStudy
labels <- read.csv(file = study_info_file, stringsAsFactors = FALSE)
Ontology <- get_ontology(file = ontology_file, propagate_relationships = "is_a", extract_tags = "minimal")
GO2ALLORFs <- as.list(org.Sc.sgdGO2ALLORFS) # all ORFs associated with GO term
Terms <- read.delim(file = sgd_terms_tfile,
  header = FALSE,
  quote = "",
  col.names = c("GO_ID", "GO_Term", "GO_Aspect", "GO_Term_Definition")
)
XX3 <- read.csv(file = all_sgd_terms_csv, stringsAsFactors = FALSE, header = TRUE)
XX3[, 1] <- paste0("GO:", formatC(XX3[, 1], width = 7, flag = "0"))
XX3[, 2] <- gsub(pattern = " ", replacement = "_", x = XX3[, 2])
XX3[, 2] <- gsub(pattern = "/", replacement = "_", x = XX3[, 2])

# Load input files
for (study_num in study_nums) {
  input_file <- file.path(base_dir, paste("Exp", study_num), zscores, "zscores_interaction.csv")
  if (file.exists(input_file)) {
    assign(paste(X, study_num), read.csv(file = input_file, stringsAsFactors = FALSE, header = TRUE))
    assign(paste(Name, study_num), labels[study_num, 2])
  }
}

for (study_num in study_nums) {
  eval(paste("function", study_num))
}

if (length(study_nums) > 0) {
  X1$ORF <- X1$OrfRep
  X1$ORF <- gsub("_1", "", x = X1$ORF)
  X1$ORF <- gsub("_2", "", x = X1$ORF)
  X1$ORF <- gsub("_3", "", x = X1$ORF)
  X1$ORF <- gsub("_4", "", x = X1$ORF)
  
  X1$Score_L <- "No Effect"
  try(X1[is.na(X1$Z_lm_L), ]$Score_L <- "No Growth")
  try(X1[!is.na(X1$Z_lm_L) & X1$Z_lm_L >= 2, ]$Score_L <- "Deletion Enhancer")
  try(X1[!is.na(X1$Z_lm_L) & X1$Z_lm_L <= -2, ]$Score_L <- "Deletion Suppressor")
  
  X1$Score_K <- "No Effect"
  try(X1[is.na(X1$Z_lm_K), ]$Score_K <- "No Growth")
  try(X1[!is.na(X1$Z_lm_K) & X1$Z_lm_K >= 2, ]$Score_K <- "Deletion Suppressor")
  try(X1[!is.na(X1$Z_lm_K) & X1$Z_lm_K <= -2, ]$Score_K <- "Deletion Enhancer")
  
  # Express the na data as 0.001 in X1 for K and L
  X1[is.na(X1$Z_lm_L), ]$Z_lm_L <- 0.001
  X1[is.na(X1$Z_lm_K), ]$Z_lm_K <- 0.001
  X1$Rank_L <- rank(X1$Z_lm_L)
  X1$Rank_K <- rank(X1$Z_lm_K)
  X1 <- X1[order(X1$OrfRep, decreasing = FALSE), ]
  colnames(X1) <- paste0(colnames(X1), "_X1")
}

if (length(study_nums) > 1) {
  X2$ORF <- X2$OrfRep
  X2$ORF <- gsub("_1", "", x = X2$ORF)
  X2$ORF <- gsub("_2", "", x = X2$ORF)
  X2$ORF <- gsub("_3", "", x = X2$ORF)
  X2$ORF <- gsub("_4", "", x = X2$ORF)
  
  X2$Score_L <- "No Effect"
  try(X2[is.na(X2$Z_lm_L), ]$Score_L <- "No Growth")
  try(X2[!is.na(X2$Z_lm_L) & X2$Z_lm_L >= 2, ]$Score_L <- "Deletion Enhancer")
  try(X2[!is.na(X2$Z_lm_L) & X2$Z_lm_L <= -2, ]$Score_L <- "Deletion Suppressor")
  
  X2$Score_K <- "No Effect"
  try(X2[is.na(X2$Z_lm_K), ]$Score_K <- "No Growth")
  try(X2[!is.na(X2$Z_lm_K) & X2$Z_lm_K >= 2, ]$Score_K <- "Deletion Suppressor")
  try(X2[!is.na(X2$Z_lm_K) & X2$Z_lm_K <= -2, ]$Score_K <- "Deletion Enhancer")
  #express the na data as 0.001 in X2
  X2[is.na(X2$Z_lm_L), ]$Z_lm_L <- 0.001
  X2[is.na(X2$Z_lm_K), ]$Z_lm_K <- 0.001
  
  X2$Rank_L <- rank(X2$Z_lm_L)
  X2$Rank_K <- rank(X2$Z_lm_K)
  
  X2 <- X2[order(X2$OrfRep, decreasing = FALSE), ]
  colnames(X2) <- paste0(colnames(X2), "_X2")
  X <- cbind(X1, X2)
}

if (length(study_nums) > 2) {
  X3$ORF <- X3$OrfRep
  X3$ORF <- gsub("_1", "", x = X3$ORF)
  X3$ORF <- gsub("_2", "", x = X3$ORF)
  X3$ORF <- gsub("_3", "", x = X3$ORF)
  X3$ORF <- gsub("_4", "", x = X3$ORF)
  
  X3$Score_L <- "No Effect"
  try(X3[is.na(X3$Z_lm_L), ]$Score_L <- "No Growth")
  try(X3[!is.na(X3$Z_lm_L) & X3$Z_lm_L >= 2, ]$Score_L <- "Deletion Enhancer")
  try(X3[!is.na(X3$Z_lm_L) & X3$Z_lm_L <= -2, ]$Score_L <- "Deletion Suppressor")
  
  X3$Score_K <- "No Effect"
  try(X3[is.na(X3$Z_lm_K), ]$Score_K <- "No Growth")
  try(X3[!is.na(X3$Z_lm_K) & X3$Z_lm_K >= 2, ]$Score_K <- "Deletion Suppressor")
  try(X3[!is.na(X3$Z_lm_K) & X3$Z_lm_K <= -2, ]$Score_K <- "Deletion Enhancer")
  
  # Express the na data as 0.001 in X3
  X3[is.na(X3$Z_lm_L), ]$Z_lm_L <- 0.001
  X3[is.na(X3$Z_lm_K), ]$Z_lm_K <- 0.001
  X3$Rank_L <- rank(X3$Z_lm_L)
  X3$Rank_K <- rank(X3$Z_lm_K)
  X3 <- X3[order(X3$OrfRep, decreasing = FALSE), ]
  colnames(X3) <- paste0(colnames(X3), "_X3")
  X <- cbind(X, X3)
}

if (length(study_nums) > 3) {
  X4$ORF <- X4$OrfRep
  X4$ORF <- gsub("_1", "", x = X4$ORF)
  X4$ORF <- gsub("_2", "", x = X4$ORF)
  X4$ORF <- gsub("_3", "", x = X4$ORF)
  X4$ORF <- gsub("_4", "", x = X4$ORF)
  
  X4$Score_L <- "No Effect"
  try(X4[is.na(X4$Z_lm_L), ]$Score_L <- "No Growth")
  try(X4[!is.na(X4$Z_lm_L) & X4$Z_lm_L >= 2, ]$Score_L <- "Deletion Enhancer")
  try(X4[!is.na(X4$Z_lm_L) & X4$Z_lm_L <= -2, ]$Score_L <- "Deletion Suppressor")
  
  X4$Score_K <- "No Effect"
  try(X4[is.na(X4$Z_lm_K), ]$Score_K <- "No Growth")
  try(X4[!is.na(X4$Z_lm_K) & X4$Z_lm_K >= 2, ]$Score_K <- "Deletion Suppressor")
  try(X4[!is.na(X4$Z_lm_K) & X4$Z_lm_K <= -2, ]$Score_K <- "Deletion Enhancer")
  
  # Express the na data as 0.001 in X4
  X4[is.na(X4$Z_lm_L), ]$Z_lm_L <- 0.001
  X4[is.na(X4$Z_lm_K), ]$Z_lm_K <- 0.001
  X4$Rank_L <- rank(X4$Z_lm_L)
  X4$Rank_K <- rank(X4$Z_lm_K)
  X4 <- X4[order(X4$OrfRep, decreasing = FALSE), ]
  colnames(X4) <- paste0(colnames(X4), "_X4")
  X <- cbind(X, X4)
}

if (length(study_nums) > 4) {
  X5$ORF <- X5$OrfRep
  X5$ORF <- gsub("_1", "", x = X5$ORF)
  X5$ORF <- gsub("_2", "", x = X5$ORF)
  X5$ORF <- gsub("_3", "", x = X5$ORF)
  X5$ORF <- gsub("_4", "", x = X5$ORF)
  
  X5$Score_L <- "No Effect"
  try(X5[is.na(X5$Z_lm_L), ]$Score_L <- "No Growth")
  try(X5[!is.na(X5$Z_lm_L) & X5$Z_lm_L >= 2, ]$Score_L <- "Deletion Enhancer")
  try(X5[!is.na(X5$Z_lm_L) & X5$Z_lm_L <= -2, ]$Score_L <- "Deletion Suppressor")
  
  X5$Score_K <- "No Effect"
  try(X5[is.na(X5$Z_lm_K), ]$Score_K <- "No Growth")
  try(X5[!is.na(X5$Z_lm_K) & X5$Z_lm_K >= 2, ]$Score_K <- "Deletion Suppressor")
  try(X5[!is.na(X5$Z_lm_K) & X5$Z_lm_K <= -2, ]$Score_K <- "Deletion Enhancer")
  
  # Express the na data as 0.001 in X5
  X5[is.na(X5$Z_lm_L), ]$Z_lm_L <- 0.001
  X5[is.na(X5$Z_lm_K), ]$Z_lm_K <- 0.001
  X5$Rank_L <- rank(X5$Z_lm_L)
  X5$Rank_K <- rank(X5$Z_lm_K)
  X5 <- X5[order(X5$OrfRep, decreasing = FALSE), ]
  colnames(X5) <- paste0(colnames(X5), "_X5")
  X <- cbind(X, X5)
}

X$ORF <- X$OrfRep_X1

if (length(study_nums) > 1) {
  X$ORF <- gsub("_1", "", x = X$ORF)
  try(X[X$Gene_X1 == "", ]$Gene_X1 <- X[X$Gene_X1 == "", ]$OrfRep_X1)
  try(X[X$Gene_X2 == "", ]$Gene_X2 <- X[X$Gene_X2 == "", ]$OrfRep_X2)
  X_heatmap <-
    X[colnames(X) == "ORF" | colnames(X) == "Gene_X1" |
      colnames(X) == "Z_Shift_K_X1" | colnames(X) == "Z_lm_K_X1" |
      colnames(X) == "Z_Shift_K_X2" | colnames(X) == "Z_lm_K_X2" |
      colnames(X) == "Z_Shift_L_X1" | colnames(X) == "Z_lm_L_X1" |
      colnames(X) == "Z_Shift_L_X2" | colnames(X) == "Z_lm_L_X2"]
  
  X_heatmap <- X_heatmap[, c(10, 1, 4, 5, 8, 9, 2, 3, 6, 7)]
  colnames(X_heatmap) <- gsub(pattern = "X1", replacement = Name1, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X2", replacement = Name2, colnames(X_heatmap))
  colnames(X_heatmap)[2] <- "Gene"
}

if (length(study_nums) > 2) {
  X$ORF <- gsub("_1", "", x = X$ORF)
  X$ORF <- gsub("_2", "", x = X$ORF)
  try(X[X$Gene_X1 == "", ]$Gene_X1 <- X[X$Gene_X1 == "", ]$OrfRep_X1)
  try(X[X$Gene_X2 == "", ]$Gene_X2 <- X[X$Gene_X2 == "", ]$OrfRep_X2)
  try(X[X$Gene_X3 == "", ]$Gene_X3 <- X[X$Gene_X3 == "", ]$OrfRep_X3)
  
  X_heatmap <-
    X[colnames(X) == "ORF" | colnames(X) == "Gene_X1" |
      colnames(X) == "Z_Shift_K_X1" | colnames(X) == "Z_lm_K_X1" |
      colnames(X) == "Z_Shift_K_X2" | colnames(X) == "Z_lm_K_X2" |
      colnames(X) == "Z_Shift_K_X3" | colnames(X) == "Z_lm_K_X3" |
      colnames(X) == "Z_Shift_L_X1" | colnames(X) == "Z_lm_L_X1" |
      colnames(X) == "Z_Shift_L_X2" | colnames(X) == "Z_lm_L_X2" |
      colnames(X) == "Z_Shift_L_X3" | colnames(X) == "Z_lm_L_X3"]

  # Reorder columns
  X_heatmap <- X_heatmap[, c(14, 1, 4, 5, 8, 9, 12, 13, 2, 3, 6, 7, 10, 11)]
  colnames(X_heatmap) <- gsub(pattern = "X1", replacement = Name1, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X2", replacement = Name2, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X3", replacement = Name3, colnames(X_heatmap))
  colnames(X_heatmap)[2] <- "Gene"
}

if (length(study_nums) > 3) {
  X$ORF <- gsub("_1", "", x = X$ORF)
  X$ORF <- gsub("_2", "", x = X$ORF)
  X$ORF <- gsub("_3", "", x = X$ORF)
  try(X[X$Gene_X1 == "", ]$Gene_X1 <- X[X$Gene_X1 == "", ]$OrfRep_X1)
  try(X[X$Gene_X2 == "", ]$Gene_X2 <- X[X$Gene_X2 == "", ]$OrfRep_X2)
  try(X[X$Gene_X3 == "", ]$Gene_X3 <- X[X$Gene_X3 == "", ]$OrfRep_X3)
  try(X[X$Gene_X4 == "", ]$Gene_X4 <- X[X$Gene_X4 == "", ]$OrfRep_X4)
  
  X_heatmap <-
    X[colnames(X) == "ORF" | colnames(X) == "Gene_X1" |
      colnames(X) == "Z_Shift_K_X1" | colnames(X) == "Z_lm_K_X1" |
      colnames(X) == "Z_Shift_K_X2" | colnames(X) == "Z_lm_K_X2" |
      colnames(X) == "Z_Shift_K_X3" | colnames(X) == "Z_lm_K_X3" |
      colnames(X) == "Z_Shift_K_X4" | colnames(X) == "Z_lm_K_X4" |
      colnames(X) == "Z_Shift_L_X1" | colnames(X) == "Z_lm_L_X1" |
      colnames(X) == "Z_Shift_L_X2" | colnames(X) == "Z_lm_L_X2" |
      colnames(X) == "Z_Shift_L_X3" | colnames(X) == "Z_lm_L_X3" |
      colnames(X) == "Z_Shift_L_X4" | colnames(X) == "Z_lm_L_X4"]

  # Reorder columns
  X_heatmap <- X_heatmap[, c(18, 1, 4, 5, 8, 9, 12, 13, 16, 17, 2, 3, 6, 7, 10, 11, 14, 15)]
  colnames(X_heatmap) <- gsub(pattern = "X1", replacement = Name1, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X2", replacement = Name2, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X3", replacement = Name3, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X4", replacement = Name4, colnames(X_heatmap))
  colnames(X_heatmap)[2] <- "Gene"
}

if (length(study_nums) > 4) {
  X$ORF <- gsub("_1", "", x = X$ORF)
  X$ORF <- gsub("_2", "", x = X$ORF)
  X$ORF <- gsub("_3", "", x = X$ORF)
  X$ORF <- gsub("_4", "", x = X$ORF)
  try(X[X$Gene_X1 == "", ]$Gene_X1 <- X[X$Gene_X1 == "", ]$OrfRep_X1)
  try(X[X$Gene_X2 == "", ]$Gene_X2 <- X[X$Gene_X2 == "", ]$OrfRep_X2)
  try(X[X$Gene_X3 == "", ]$Gene_X3 <- X[X$Gene_X3 == "", ]$OrfRep_X3)
  try(X[X$Gene_X4 == "", ]$Gene_X4 <- X[X$Gene_X4 == "", ]$OrfRep_X4)
  try(X[X$Gene_X5 == "", ]$Gene_X5 <- X[X$Gene_X5 == "", ]$OrfRep_X5)
  
  X_heatmap <-
    X[colnames(X) == "ORF" | colnames(X) == "Gene_X1" |
      colnames(X) == "Z_Shift_K_X1" | colnames(X) == "Z_lm_K_X1" |
      colnames(X) == "Z_Shift_K_X2" | colnames(X) == "Z_lm_K_X2" |
      colnames(X) == "Z_Shift_K_X3" | colnames(X) == "Z_lm_K_X3" |
      colnames(X) == "Z_Shift_K_X4" | colnames(X) == "Z_lm_K_X4" |
      colnames(X) == "Z_Shift_K_X5" | colnames(X) == "Z_lm_K_X5" |
      colnames(X) == "Z_Shift_L_X1" | colnames(X) == "Z_lm_L_X1" |
      colnames(X) == "Z_Shift_L_X2" | colnames(X) == "Z_lm_L_X2" |
      colnames(X) == "Z_Shift_L_X3" | colnames(X) == "Z_lm_L_X3" |
      colnames(X) == "Z_Shift_L_X4" | colnames(X) == "Z_lm_L_X4" |
      colnames(X) == "Z_Shift_L_X5" | colnames(X) == "Z_lm_L_X5"]

  # Reorder columns
  X_heatmap <- X_heatmap[, c(22, 1, 4, 5, 8, 9, 12, 13, 16, 17, 20, 21, 2, 3, 6, 7, 10, 11, 14, 15, 18, 19)]
  colnames(X_heatmap) <- gsub(pattern = "X1", replacement = Name1, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X2", replacement = Name2, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X3", replacement = Name3, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X4", replacement = Name4, colnames(X_heatmap))
  colnames(X_heatmap) <- gsub(pattern = "X5", replacement = Name5, colnames(X_heatmap))
  colnames(X_heatmap)[2] <- "Gene"
}

# Theme elements for plots
theme_Publication <- function(base_size = 14, base_family = "sans") {
  (theme_foundation(base_size = base_size, base_family = base_family) +
    theme(
      plot.title = element_text(face = "bold", size = rel(1.2), hjust = 0.5),
      text = element_text(),
      panel.background = element_rect(colour = NA),
      plot.background = element_rect(colour = NA),
      panel.border = element_rect(colour = NA),
      axis.title = element_text(face = "bold", size = rel(1)),
      axis.title.y = element_text(angle = 90, vjust = 2),
      axis.title.x = element_text(vjust = -0.2),
      axis.text = element_text(),
      axis.line = element_line(colour = "black"),
      axis.ticks = element_line(),
      panel.grid.major = element_line(colour = "#f0f0f0"),
      panel.grid.minor = element_blank(),
      legend.key = element_rect(colour = NA),
      legend.position = "bottom",
      legend.direction = "horizontal",
      legend.key.size = unit(0.2, "cm"),
      legend.spacing = unit(0, "cm"),
      legend.title = element_text(face = "italic"),
      plot.margin = unit(c(10, 5, 5, 5), "mm"),
      strip.background = element_rect(colour = "#f0f0f0", fill = "#f0f0f0"),
      strip.text = element_text(face = "bold")
    )
  )
}

scale_fill_Publication <- function(...) {
  library(scales)
  discrete_scale(
    "fill",
    "Publication",
    manual_pal(values = c("#386cb0", "#fdb462", "#7fc97f", "#ef3b2c", "#662506", "#a6cee3", "#fb9a99", "#984ea3", "#ffff33")),
    ...
  )
}

scale_colour_Publication <- function(...) {
  discrete_scale(
    "colour",
    "Publication",
    manual_pal(values = c("#386cb0", "#fdb462", "#7fc97f", "#ef3b2c", "#662506", "#a6cee3", "#fb9a99", "#984ea3", "#ffff33")),
    ...
  )
}

theme_Publication_legend_right <- function(base_size = 14, base_family = "sans") {
  (theme_foundation(base_size = base_size, base_family = base_family) +
    theme(
      plot.title = element_text(face = "bold", size = rel(1.2), hjust = 0.5),
      text = element_text(),
      panel.background = element_rect(colour = NA),
      plot.background = element_rect(colour = NA),
      panel.border = element_rect(colour = NA),
      axis.title = element_text(face = "bold", size = rel(1)),
      axis.title.y = element_text(angle = 90, vjust = 2),
      axis.title.x = element_text(vjust = -0.2),
      axis.text = element_text(),
      axis.line = element_line(colour = "black"),
      axis.ticks = element_line(),
      panel.grid.major = element_line(colour = "#f0f0f0"),
      panel.grid.minor = element_blank(),
      legend.key = element_rect(colour = NA),
      legend.position = "right",
      legend.direction = "vertical",
      legend.key.size = unit(0.5, "cm"),
      legend.spacing = unit(0, "cm"),
      legend.title = element_text(face = "italic"),
      plot.margin = unit(c(10, 5, 5, 5), "mm"),
      strip.background = element_rect(colour = "#f0f0f0", fill = "#f0f0f0"),
      strip.text = element_text(face = "bold")
    )
  )
}

scale_fill_Publication <- function(...) {
  discrete_scale(
    "fill",
    "Publication",
    manual_pal(values = c("#386cb0", "#fdb462", "#7fc97f", "#ef3b2c", "#662506", "#a6cee3", "#fb9a99", "#984ea3", "#ffff33")),
    ...
  )
}

scale_colour_Publication <- function(...) {
  discrete_scale(
    "colour",
    "Publication",
    manual_pal(values = c("#386cb0", "#fdb462", "#7fc97f", "#ef3b2c", "#662506", "#a6cee3", "#fb9a99", "#984ea3", "#ffff33")),
    ...
  )
}

Ontology <- get_ontology(file = ontology_file, propagate_relationships = "is_a", extract_tags = "minimal")
print(Ontology)

# All ORFs associated with GO term
GO2ALLORFs <- as.list(org.Sc.sgdGO2ALLORFS)

# Terms is the GO term list jwr moved up to TAABLES
Terms <- read.delim(file = sgd_terms_tfile,
  header = FALSE,
  quote = "",
  col.names = c("GO_ID", "GO_Term", "GO_Aspect", "GO_Term_Definition")
)

colormapbreaks <- c(-12, -10, -8, -6, -4, -2, 2, 4, 6, 8, 10, 12)

for (s in 1:dim(XX3)[1]) {
  # Ontology <-
  #   get_ontology(file = "Documents/Hartman_Lab/SGD_Downloads/gene_ontology_edit.obo",
  #     propagate_relationships = "is_a", extract_tags = "minimal")
  # Ontology_Everything <-
  #   get_ontology(file = "Documents/Hartman_Lab/SGD_Downloads/gene_ontology_edit.obo",
  #     propagate_relationships = "is_a", extract_tags = "everything")
  #
  # GO_ID_Arg <- "GO:0006325"
  GO_ID_Arg_loop <- as.character(XX3[s, 1])
  GOTerm_parent <- get_descendants(Ontology, roots = GO_ID_Arg_loop)
  # GOTerm_parent <- get_descendants(Ontology,roots = "GO:0006325")
  # Only make plots if parent term has fewer than 500 children
  Parent_Size <- length(as.vector(GO2ALLORFs[GO_ID_Arg_loop][[1]]))
  
  if (length(GOTerm_parent) > 100) {
    next()
  }
  
  Parent_Size <- length(as.vector(GO2ALLORFs[GO_ID_Arg_loop][[1]])) # TODO why twice?

  if (Parent_Size < 2) {
    next()
  }

  if (Parent_Size > 2000) {

    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 45,
      onefile = TRUE
    )

    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.5, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }
  
  if (Parent_Size >= 1000 && Parent_Size <= 2000) {

    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 35,
      onefile = TRUE
    )

    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.6, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size >= 500 && Parent_Size <= 1000) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 30,
      onefile = TRUE
    )

    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.6, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size >= 200 && Parent_Size <= 500) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 25,
      onefile = TRUE
    )

    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size >= 100 && Parent_Size <= 200) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 20,
      onefile = TRUE
    )
    
    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size >= 60 && Parent_Size <= 100) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 15,
      onefile = TRUE
    )
    
    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size >= 30 && Parent_Size <= 60) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 10,
      onefile = TRUE
    )
    
    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
      if (dim(Genes_Annotated_to_Term)[1] <= 2 && dim(Genes_Annotated_to_Term)[1] > 0) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "none", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    
    dev.off()
  }

  if (Parent_Size >= 3 && Parent_Size <= 30) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 7,
      onefile = TRUE
    )
    
    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
      if (dim(Genes_Annotated_to_Term)[1] <= 2 && dim(Genes_Annotated_to_Term)[1] > 0) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "none", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }

  if (Parent_Size == 2) {
    
    pdf(
      file = file.path(output_dir, paste0(XX3[s, 2], ".pdf")),
      width = 12,
      height = 7,
      onefile = TRUE
    )
    
    for (i in 1:length(GOTerm_parent)) {
      GO_Term <- GOTerm_parent[i]
      GO_Term_Num <- as.integer(str_split_fixed(as.character(GO_Term), "\\:", 2)[, 2])
      GO_Term_Name <- as.character(Terms[Terms$GO_ID == GO_Term_Num, ]$GO_Term)
      # Genes_Annotated_to_Term <- Gene_Association[Gene_Association$GO_ID == GO_Term, ]
      All_Genes_Annotated_to_Term <- as.vector(GO2ALLORFs[GO_Term][[1]])
      Genes_Annotated_to_Term <- X_heatmap[X_heatmap$ORF %in% All_Genes_Annotated_to_Term, ]
      X0 <- as.matrix(Genes_Annotated_to_Term[, 3:dim(Genes_Annotated_to_Term)[2]])
      if (dim(Genes_Annotated_to_Term)[1] > 2) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "row", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
      if (dim(Genes_Annotated_to_Term)[1] <= 2 && dim(Genes_Annotated_to_Term)[1] > 0) {
        try(heatmap.2(
          x = X0,
          Rowv = TRUE, Colv = NA, distfun = dist, hclustfun = hclust,
          dendrogram = "none", cexCol = 0.7, cexRow = 0.7, scale = "none",
          breaks = colormapbreaks, symbreaks = FALSE, colsep = c(2, 4, 6), sepcolor = "white", offsetCol = 0.1,
          ylab = "Gene",
          cellnote = round(X0, digits = 0), notecex = 0.5, key = TRUE,
          keysize = 0.5, trace = "none", density.info = c("none"), margins = c(10, 8),
          na.color = "red", col = brewer.pal(11, "PuOr"),
          main = GO_Term_Name,
          # ColSideColors = ev_repeat,
          labRow = as.character(Genes_Annotated_to_Term$Gene)
        ))
      }
    }
    dev.off()
  }
}