190 lines
8.0 KiB
R
Executable File
190 lines
8.0 KiB
R
Executable File
#!/usr/bin/env Rscript
|
||
# V5 - 融合版热图：采用与motif/structure相同的布局和绘图方式
|
||
# 左：进化树（ggtree） | 中：亚家族竖线 | 右：启动子元件热图 | 最右：图例
|
||
|
||
rm(list = ls())
|
||
library(tidyverse)
|
||
library(ggtree)
|
||
library(treeio)
|
||
library(ape)
|
||
library(RColorBrewer)
|
||
library(ggnewscale)
|
||
|
||
cat("=== 启动子可视化 V5 - 融合版热图（仿Motif/Structure布局）===\n\n")
|
||
|
||
args <- commandArgs(trailingOnly = TRUE)
|
||
|
||
treefile <- args[1]
|
||
group_file <- args[2]
|
||
promoter_file <- args[3]
|
||
output_prefix <- args[5]
|
||
|
||
cat("树文件:", treefile, "\n")
|
||
cat("分组文件:", group_file, "\n")
|
||
cat("启动子文件:", promoter_file, "\n")
|
||
cat("输出前缀:", output_prefix, "\n\n")
|
||
|
||
# ===================== 1. 读取数据 =====================
|
||
|
||
tree <- read.tree(treefile)
|
||
|
||
group_df <- read.delim(group_file, header = FALSE, stringsAsFactors = FALSE)
|
||
colnames(group_df) <- c("label", "subfamily")
|
||
|
||
normalize_gene <- function(x) {
|
||
sub("\\.\\d+\\.T\\d+$", "", x) %>%
|
||
sub("\\.T\\d+$", "", .) %>%
|
||
sub("\\.\\d+$", "", .)
|
||
}
|
||
|
||
group_df$gene_key <- normalize_gene(group_df$label)
|
||
|
||
promoter <- read.delim(promoter_file, header = FALSE, stringsAsFactors = FALSE)
|
||
promoter <- promoter[, c(1, 2)]
|
||
colnames(promoter) <- c("gene", "element")
|
||
promoter$gene <- normalize_gene(promoter$gene)
|
||
|
||
tree_labels <- tree$tip.label
|
||
tree_labels_base <- normalize_gene(tree_labels)
|
||
promoter <- promoter %>% filter(gene %in% tree_labels_base)
|
||
|
||
cat("数据: 树", length(tree_labels), "基因, 启动子", nrow(promoter), "记录\n\n")
|
||
|
||
# ===================== 2. 亚家族颜色 =====================
|
||
subfam_levels <- sort(unique(group_df$subfamily))
|
||
n_subfam <- length(subfam_levels)
|
||
base_cols_sf <- brewer.pal(8, "Dark2")
|
||
subfam_cols_vec <- rep_len(base_cols_sf, n_subfam)
|
||
subfam_cols <- setNames(subfam_cols_vec, subfam_levels)
|
||
|
||
# ===================== 3. 绘制进化树（Panel A） =====================
|
||
label_offset <- 0.4
|
||
|
||
tree_df <- as_tibble(tree)
|
||
tree_df$isTip <- tree_df$node <= length(tree$tip.label)
|
||
tree_df$gene_key <- ifelse(tree_df$isTip, normalize_gene(tree_df$label), NA_character_)
|
||
tree_df <- left_join(tree_df, group_df[, c("gene_key", "subfamily")], by = "gene_key")
|
||
tree_df$support <- ifelse(tree_df$isTip, NA_real_, suppressWarnings(as.numeric(tree_df$label)))
|
||
|
||
p_tree <- ggtree(tree, branch.length = "none") %<+% tree_df +
|
||
geom_nodepoint(aes(fill = cut(support, c(0, 50, 75, 100))), shape = 21, size = 2, na.rm = TRUE) +
|
||
scale_fill_manual(values = c("black", "grey40", "grey80"), guide = "legend",
|
||
name = "Bootstrap Percentage (BP)",
|
||
breaks = c("(75,100]", "(50,75]", "(0,50]"),
|
||
labels = expression(BP > 75, 50 < BP * "<=75", BP <= 50)) +
|
||
geom_tippoint(aes(color = subfamily), size = 2, na.rm = TRUE) +
|
||
scale_color_manual(values = subfam_cols, name = "Subfamily", na.value = "grey70") +
|
||
geom_tiplab(offset = label_offset, size = 3, hjust = 0) +
|
||
theme_tree() +
|
||
theme(legend.position = "right", legend.background = element_rect(color = "#969696", fill = "#d9d9d9"))
|
||
|
||
# ===================== 4. 获取树的坐标信息 =====================
|
||
tree_dat <- p_tree$data
|
||
tip_dat <- tree_dat %>% filter(isTip) %>% select(label, x, y, subfamily)
|
||
|
||
x_tree_min <- min(tree_dat$x, na.rm = TRUE)
|
||
x_tip_max <- max(tip_dat$x, na.rm = TRUE)
|
||
max_y <- max(tree_dat$y, na.rm = TRUE)
|
||
|
||
tip_labels <- tip_dat$label
|
||
max_label_len <- max(nchar(tip_labels), na.rm = TRUE)
|
||
char_width <- 0.12
|
||
label_extra_width <- max_label_len * char_width
|
||
|
||
# ===================== 5. 准备热图数据 =====================
|
||
element_counts <- promoter %>% count(element) %>% arrange(desc(n))
|
||
cat("元件统计（前10）:\n")
|
||
print(head(element_counts, 10))
|
||
|
||
retain_elements <- element_counts %>% filter(n >= 3) %>% pull(element)
|
||
cat(sprintf("保留出现次数>=3的元件: %d个\n", length(retain_elements)))
|
||
|
||
promoter_filtered <- promoter %>% filter(element %in% retain_elements) %>% select(gene, element)
|
||
|
||
all_combinations <- expand.grid(gene = unique(c(promoter_filtered$gene, tree_labels_base)),
|
||
element = unique(promoter_filtered$element), stringsAsFactors = FALSE)
|
||
|
||
promoter_counts <- promoter_filtered %>% group_by(gene, element) %>% summarise(count = n(), .groups = 'drop')
|
||
|
||
heatmap_data <- all_combinations %>%
|
||
left_join(promoter_counts, by = c("gene", "element")) %>%
|
||
mutate(count = ifelse(is.na(count), 0, count),
|
||
count_cat = cut(count, breaks = c(0, 1, 2, 3, 5, 10, 20, 50, 100, 200), include.lowest = TRUE, right = FALSE))
|
||
|
||
gene_y_map <- setNames(tip_dat$y, normalize_gene(tip_dat$label))
|
||
heatmap_data$y <- gene_y_map[heatmap_data$gene]
|
||
|
||
# ===================== 6. 计算Panel布局 =====================
|
||
x_A_left <- x_tree_min
|
||
x_A_right <- x_tip_max + label_offset + label_extra_width + 0.5
|
||
|
||
gap_AB <- 2
|
||
width_B <- 3
|
||
x_B_left <- x_A_right + gap_AB
|
||
x_B_right <- x_B_left + width_B
|
||
x_subfam <- (x_B_left + x_B_right) / 2
|
||
|
||
gap_BC <- 0.8
|
||
n_elements <- length(retain_elements)
|
||
element_width <- 0.5
|
||
width_C <- max(5, n_elements * element_width)
|
||
|
||
x_C_left <- x_B_right + gap_BC
|
||
x_C_right <- x_C_left + width_C
|
||
|
||
element_x_map <- setNames(seq(x_C_left, x_C_right - element_width, length.out = n_elements), retain_elements)
|
||
heatmap_data$xmin <- element_x_map[heatmap_data$element]
|
||
heatmap_data$xmax <- heatmap_data$xmin + element_width * 0.9
|
||
|
||
gene_height <- 0.4
|
||
heatmap_data <- heatmap_data %>% mutate(ymin = y - gene_height, ymax = y + gene_height)
|
||
|
||
# ===================== 7. 准备亚家族竖线数据 =====================
|
||
subfam_ranges <- tip_dat %>% filter(!is.na(subfamily)) %>% group_by(subfamily) %>%
|
||
summarise(ymin = min(y), ymax = max(y), ymid = (ymin + ymax) / 2, .groups = "drop")
|
||
|
||
# ===================== 8. 热图颜色定义 =====================
|
||
count_colors <- c("[0,1)" = "#f7fbff", "[1,2)" = "#c6dbef", "[2,3)" = "#9ecae1",
|
||
"[3,5)" = "#6baed6", "[5,10)" = "#4292c6", "[10,20)" = "#2171b5",
|
||
"[20,50)" = "#08519c", "[50,100)" = "#08306b", "[100,200]" = "#041d3a")
|
||
|
||
# ===================== 9. 组合绘图 =====================
|
||
tree_header_x <- (x_A_left + x_A_right) / 2
|
||
subf_header_x <- (x_B_left + x_B_right) / 2
|
||
heatmap_header_x <- (x_C_left + x_C_right) / 2
|
||
header_y <- max_y + 1.5
|
||
|
||
p_combo <- p_tree +
|
||
geom_segment(data = subfam_ranges, inherit.aes = FALSE,
|
||
aes(x = x_subfam, xend = x_subfam, y = ymin, yend = ymax, colour = subfamily),
|
||
linewidth = 2, show.legend = FALSE) +
|
||
geom_text(data = subfam_ranges, inherit.aes = FALSE,
|
||
aes(x = x_subfam + 0.15, y = ymid, label = subfamily, colour = subfamily),
|
||
hjust = 0, size = 3.5, show.legend = FALSE) +
|
||
ggnewscale::new_scale_fill() +
|
||
geom_rect(data = heatmap_data %>% filter(count > 0), inherit.aes = FALSE,
|
||
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = count_cat), color = NA) +
|
||
geom_text(data = heatmap_data %>% filter(count > 0), inherit.aes = FALSE,
|
||
aes(x = (xmin + xmax) / 2, y = (ymin + ymax) / 2, label = count),
|
||
size = 2, color = "white") +
|
||
scale_fill_manual(values = count_colors, name = "Element Count", drop = FALSE) +
|
||
annotate("text", x = tree_header_x, y = header_y, label = "Phylogenetic tree", fontface = "bold", size = 4) +
|
||
annotate("text", x = subf_header_x, y = header_y, label = "Subfamily", fontface = "bold", size = 4) +
|
||
annotate("text", x = heatmap_header_x, y = header_y, label = "Promoter Elements", fontface = "bold", size = 4) +
|
||
coord_cartesian(xlim = c(x_A_left - 0.5, x_C_right + 1)) +
|
||
expand_limits(y = header_y + 0.5) +
|
||
theme(legend.position = "right", legend.background = element_rect(color = "#969696", fill = "#d9d9d9"))
|
||
|
||
# ===================== 10. 保存输出 =====================
|
||
output_pdf <- paste0(output_prefix, "_tree_promoter_heatmap.pdf")
|
||
output_png <- paste0(output_prefix, "_tree_promoter_heatmap.png")
|
||
|
||
ggsave(output_pdf, p_combo, width = 14, height = 10)
|
||
|
||
png(filename = output_png, width = 4200, height = 3000, res = 300)
|
||
print(p_combo)
|
||
dev.off()
|
||
|
||
cat("[OK] PDF: ", output_pdf, "\n")
|
||
cat("[OK] PNG: ", output_png, "\n")
|
||
cat("===== 全部完成 =====\n") |