378 lines
12 KiB
R
378 lines
12 KiB
R
 
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#!/usr/bin/env Rscript
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## =========================================================
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## tree_domain.R
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## Panel A：Phylogenetic tree（含基因 ID + Bootstrap）
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## Panel B：Subfamily 竖线（可选，帮助视觉分组）
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## Panel C：Domain（按蛋白长度 qlen 比例；来自 hmmscan domtblout）
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## =========================================================
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args <- commandArgs(trailingOnly = TRUE)
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if (length(args) < 3) {
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stop(
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"用法:\n",
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" Rscript tree_domain.R \\\n",
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" <treefile> <subfamily_file> <domtblout_file> \\\n",
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" [evalue_cutoff] [coverage_percent] [output_prefix]\n\n",
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call. = FALSE
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)
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}
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treefile <- args[1]
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subfamily_file <- args[2]
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domtblout_file <- args[3]
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## E-value 阈值（默认 1e-5）
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e_cutoff <- if (length(args) >= 4 && nzchar(args[4])) {
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tmp <- suppressWarnings(as.numeric(args[4]))
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if (is.na(tmp)) 1e-5 else tmp
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} else 1e-5
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## 覆盖度阈值（可选）
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cov_cutoff <- if (length(args) >= 5 && nzchar(args[5])) {
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tmp <- suppressWarnings(as.numeric(args[5]))
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if (is.na(tmp) || tmp <= 0) NA_real_ else tmp / 100
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} else NA_real_
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## 输出前缀（用于生成 pdf 和 png）
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output_prefix <- if (length(args) >= 6 && nzchar(args[6])) {
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args[6]
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} else {
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prefix <- sub("\\.[^.]*$", "", treefile)
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paste0(prefix, ".tree_domain")
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}
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## 输出文件路径
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output_pdf <- paste0(output_prefix, ".pdf")
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output_png <- paste0(output_prefix, ".png")
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cat("树文件: ", treefile, "\n")
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cat("亚家族文件: ", subfamily_file, "\n")
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cat("domtblout 文件: ", domtblout_file, "\n")
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cat("E-value 阈值: ", e_cutoff, "\n")
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cat("覆盖度过滤: ", if(is.na(cov_cutoff)) "未启用" else paste0(cov_cutoff*100, "%"), "\n")
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cat("输出前缀: ", output_prefix, "\n")
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cat("PDF 输出: ", output_pdf, "\n")
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cat("PNG 输出: ", output_png, "\n\n")
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## ===================== 加载 R 包 =====================
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script_args_all <- commandArgs(trailingOnly = FALSE)
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script_file_arg <- grep("^--file=", script_args_all, value = TRUE)
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script_dir <- if (length(script_file_arg) > 0) dirname(normalizePath(sub("^--file=", "", script_file_arg[1]))) else getwd()
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source(file.path(script_dir, "subfamily_palette.R"))
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suppressPackageStartupMessages({
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library(ape)
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library(ggtree)
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library(tidytree)
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library(dplyr)
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library(RColorBrewer)
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library(ggplot2)
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library(ggnewscale)
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})
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make_distinct_cols <- function(n) {
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if (n <= 0) return(character(0))
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base <- c(
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"#0072B2", "#D55E00", "#009E73", "#CC79A7", "#E69F00",
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"#56B4E9", "#F0E442", "#000000", "#882255", "#44AA99",
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"#AA4499", "#117733", "#332288", "#DDCC77", "#88CCEE"
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)
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if (n <= length(base)) return(base[seq_len(n)])
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if (exists("hcl.colors", where = asNamespace("grDevices"), inherits = FALSE)) {
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return(grDevices::hcl.colors(n, palette = "Dark 3"))
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}
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grDevices::colorRampPalette(base)(n)
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}
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## ===================== 读亚家族文件 =====================
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add_confidence_labels <- function(subfam_df, subfamily_file) {
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add_subfamily_confidence_labels(subfam_df, subfamily_file)
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}
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## 处理 "NONE" 情况（表示没有亚家族文件）
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if (subfamily_file == "NONE" || !file.exists(subfamily_file)) {
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cat("[INFO] 未找到亚家族文件，使用默认着色\n")
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## 从树文件读取基因名作为默认亚家族
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tree_tmp <- read.tree(treefile)
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subfam <- data.frame(
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label = tree_tmp$tip.label,
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subfamily = "Default",
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low_confidence = FALSE,
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display_label = tree_tmp$tip.label,
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stringsAsFactors = FALSE
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)
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} else {
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subfam <- read.table(subfamily_file, header = FALSE, stringsAsFactors = FALSE)
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colnames(subfam) <- c("label", "subfamily")
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subfam <- add_confidence_labels(subfam, subfamily_file)
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}
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subfam_levels <- sort(unique(subfam$subfamily))
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n_subfam <- length(subfam_levels)
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subfam_cols <- make_subfamily_cols(subfam_levels)
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## ===================== 树绘图函数 =====================
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plot_tree <- function(treefile, subfam_df, subfam_cols, label_offset = 0.4) {
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tree <- read.tree(treefile)
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tree_df <- as_tibble(tree)
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tree_df$isTip <- tree_df$node <= length(tree$tip.label)
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tree_df <- dplyr::left_join(tree_df, subfam_df, by = "label")
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tree_df$display_label <- ifelse(is.na(tree_df$display_label), tree_df$label, tree_df$display_label)
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tree_df$support <- ifelse(tree_df$isTip, NA_real_,
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suppressWarnings(as.numeric(tree_df$label)))
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## 修复：使用 plotmath 兼容的表达式
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p <- ggtree(tree, branch.length = "none") %<+% tree_df +
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geom_nodepoint(
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aes(fill = cut(support, c(0, 50, 75, 100))),
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shape = 21, size = 2, na.rm = TRUE
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) +
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scale_fill_manual(
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values = c("black", "grey40", "grey80"),
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name = "Bootstrap",
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breaks = c("(75,100]", "(50,75]", "(0,50]"),
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labels = c("BP > 75", "50 < BP <= 75", "BP <= 50") ## 修复：使用字符串而非 expression
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) +
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geom_text2(
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aes(label = ifelse(!isTip & !is.na(support), round(support), "")),
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hjust = -0.2, vjust = -0.4, size = 2.2,
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na.rm = TRUE, show.legend = FALSE
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) +
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geom_tippoint(aes(color = subfamily), size = 2, na.rm = TRUE) +
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scale_color_manual(values = subfam_cols, name = "Subfamily") +
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geom_tiplab(aes(label = display_label), offset = label_offset, size = 3, hjust = 0) +
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theme_tree() +
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theme(legend.background = element_rect(color = "#969696", fill = "#d9d9d9"))
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attr(p, "label_offset") <- label_offset
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return(p)
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}
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## ===================== 解析 domtblout =====================
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parse_domtblout <- function(domtbl_file, e_cutoff = 1e-5,
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cov_cutoff = NA_real_, tree_genes = NULL) {
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dom <- read.table(domtbl_file, header = FALSE, comment.char = "#",
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stringsAsFactors = FALSE, fill = TRUE)
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if (ncol(dom) < 22) {
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stop("domtblout 文件列数少于 22 列，请检查 hmmscan 输出格式。", call. = FALSE)
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}
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colnames(dom)[1:22] <- c(
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"target_name", "t_accession", "tlen", "query_name", "q_accession", "qlen",
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"E_full", "score_full", "bias_full", "dom_index", "dom_of",
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"c_Evalue", "i_Evalue", "dom_score", "dom_bias",
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"hmm_from", "hmm_to", "ali_from", "ali_to", "env_from", "env_to", "acc"
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)
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num_cols <- c("tlen", "qlen", "E_full", "score_full", "i_Evalue",
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"ali_from", "ali_to", "dom_score")
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for (cn in intersect(num_cols, colnames(dom))) {
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dom[[cn]] <- suppressWarnings(as.numeric(dom[[cn]]))
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}
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if (!is.null(tree_genes)) {
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dom <- dom[dom$query_name %in% tree_genes, , drop = FALSE]
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}
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dom <- dom %>%
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mutate(
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dom_len = ali_to - ali_from + 1,
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cov = ifelse(is.na(qlen) | qlen <= 0, NA_real_, dom_len / qlen),
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evalue = if("i_Evalue" %in% colnames(dom)) i_Evalue else E_full
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) %>%
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filter(!is.na(evalue), evalue <= e_cutoff)
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if (!is.na(cov_cutoff)) {
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dom <- dom %>% filter(is.na(cov) | cov >= cov_cutoff)
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}
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return(dom)
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}
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## ===================== 画树 & 获取坐标 =====================
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label_offset <- 0.4
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p_tree <- plot_tree(treefile, subfam, subfam_cols, label_offset = label_offset)
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tree_dat <- p_tree$data
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tip_dat <- tree_dat %>%
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filter(isTip) %>%
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select(label, x, y, subfamily)
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if (nrow(tip_dat) == 0) stop("树中没有 tip 节点。", call. = FALSE)
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x_tree_min <- min(tree_dat$x, na.rm = TRUE)
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x_tip_max <- max(tip_dat$x, na.rm = TRUE)
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max_y <- max(tree_dat$y, na.rm = TRUE)
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## 计算 Panel A 宽度
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tree_core_width <- x_tip_max - x_tree_min
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label_panel_width <- max(1.5, tree_core_width * 0.6)
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x_A_left <- x_tree_min
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x_A_right <- x_tip_max + label_offset + label_panel_width
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## ===================== 解析 Domain 数据 =====================
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domain_hits <- parse_domtblout(domtblout_file, e_cutoff = e_cutoff,
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cov_cutoff = cov_cutoff, tree_genes = tip_dat$label)
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domain_hits <- domain_hits %>%
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left_join(tip_dat, by = c("query_name" = "label")) %>%
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filter(!is.na(y))
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if (nrow(domain_hits) == 0) {
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stop("筛选后没有任何 domain 命中。", call. = FALSE)
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}
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cat("蛋白长度范围: ", min(domain_hits$qlen), " ~ ", max(domain_hits$qlen), "\n")
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## ===================== 布局计算 =====================
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gap_AB <- max(0.3, tree_core_width * 0.15)
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gap_BC <- max(0.3, tree_core_width * 0.15)
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r_B <- 0.6 # Subfamily 宽度系数
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r_C <- 2.5 # Domain 宽度系数（比原来更宽，突出显示）
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## Panel B (Subfamily)
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x_B_left <- x_A_right + gap_AB
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width_B <- tree_core_width * r_B
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x_B_right <- x_B_left + width_B
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x_subfam <- (x_B_left + x_B_right) / 2
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## Panel C (Domain)
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x_C_left <- x_B_right + gap_BC
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width_C <- tree_core_width * r_C
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x_C_right <- x_C_left + width_C
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## ===================== Domain 坐标计算 =====================
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max_qlen <- max(domain_hits$qlen, na.rm = TRUE)
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scale_domain <- width_C / max_qlen
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cat("Domain scale: ", scale_domain, "\n")
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## 蛋白主干线
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domain_tracks <- domain_hits %>%
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distinct(query_name, y, qlen) %>%
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mutate(
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x_start = x_C_left,
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x_end = x_C_left + qlen * scale_domain
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)
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## Domain 矩形
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domain_rect <- domain_hits %>%
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mutate(
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xmin = x_C_left + (ali_from - 1) * scale_domain,
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xmax = x_C_left + ali_to * scale_domain,
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ymin = y - 0.25,
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ymax = y + 0.25
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)
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## Domain 配色
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domain_levels <- sort(unique(domain_rect$target_name))
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domain_cols <- setNames(make_distinct_cols(length(domain_levels)), domain_levels)
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## ===================== 亚家族范围 =====================
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subfam_ranges <- make_subfamily_ranges(tip_dat)
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## ===================== 底部坐标轴 =====================
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make_axis <- function(max_len, scale_val, x_left, axis_y, n_breaks = 5) {
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if (!is.finite(max_len) || max_len <= 0) return(NULL)
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brks <- pretty(c(0, max_len), n = n_breaks)
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brks <- brks[brks >= 0 & brks <= max_len]
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list(
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line = data.frame(x = x_left, xend = x_left + max_len * scale_val,
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y = axis_y, yend = axis_y),
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ticks = data.frame(x = x_left + brks * scale_val,
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xend = x_left + brks * scale_val,
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y = axis_y, yend = axis_y + 0.2),
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labels = data.frame(x = x_left + brks * scale_val,
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y = axis_y - 0.3, label = as.integer(brks))
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)
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}
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axis_y <- min(tree_dat$y) - 1.5
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domain_axis <- make_axis(max_qlen, scale_domain, x_C_left, axis_y)
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## ===================== 组合绘图 =====================
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|
|
header_y <- max_y + 1.2
|
|||
|
|
|
|||
|
|
p_combo <- p_tree +
|
|||
|
|
## Panel B: Subfamily 竖线
|
|||
|
|
geom_segment(
|
|||
|
|
data = subfam_ranges, inherit.aes = FALSE,
|
|||
|
|
aes(x = x_subfam, xend = x_subfam, y = ymin, yend = ymax, color = subfamily),
|
|||
|
|
linewidth = 1.5
|
|||
|
|
) +
|
|||
|
|
geom_text(
|
|||
|
|
data = subfam_ranges, inherit.aes = FALSE,
|
|||
|
|
aes(x = x_subfam + width_B * 0.08, y = ymid, label = subfamily, color = subfamily),
|
|||
|
|
hjust = 0, size = 3.5
|
|||
|
|
) +
|
|||
|
|
|
|||
|
|
## Panel C: Domain
|
|||
|
|
geom_segment(
|
|||
|
|
data = domain_tracks, inherit.aes = FALSE,
|
|||
|
|
aes(x = x_start, xend = x_end, y = y, yend = y),
|
|||
|
|
colour = "grey70", linewidth = 0.4
|
|||
|
|
) +
|
|||
|
|
ggnewscale::new_scale_fill() +
|
|||
|
|
geom_rect(
|
|||
|
|
data = domain_rect, inherit.aes = FALSE,
|
|||
|
|
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = target_name),
|
|||
|
|
color = NA
|
|||
|
|
) +
|
|||
|
|
scale_fill_manual(values = domain_cols, name = "Domain") +
|
|||
|
|
|
|||
|
|
## 底部坐标轴
|
|||
|
|
geom_segment(data = domain_axis$line, inherit.aes = FALSE,
|
|||
|
|
aes(x = x, xend = xend, y = y, yend = yend), linewidth = 0.4) +
|
|||
|
|
geom_segment(data = domain_axis$ticks, inherit.aes = FALSE,
|
|||
|
|
aes(x = x, xend = xend, y = y, yend = yend), linewidth = 0.3) +
|
|||
|
|
geom_text(data = domain_axis$labels, inherit.aes = FALSE,
|
|||
|
|
aes(x = x, y = y, label = label), size = 2.5) +
|
|||
|
|
|
|||
|
|
## 顶部标题
|
|||
|
|
annotate("text", x = (x_A_left + x_A_right)/2, y = header_y,
|
|||
|
|
label = "Phylogenetic tree", fontface = "bold", size = 4) +
|
|||
|
|
annotate("text", x = x_subfam, y = header_y,
|
|||
|
|
label = "Subfamily", fontface = "bold", size = 4) +
|
|||
|
|
annotate("text", x = (x_C_left + x_C_right)/2, y = header_y,
|
|||
|
|
label = "Protein Domain", 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"))
|
|||
|
|
|
|||
|
|
## ===================== 保存输出（PDF + PNG）=====================
|
|||
|
|
|
|||
|
|
# 保存 PDF（矢量图）
|
|||
|
|
ggsave(output_pdf, p_combo, width = 14, height = 10)
|
|||
|
|
cat("[OK] PDF: ", output_pdf, "\n", sep = "")
|
|||
|
|
|
|||
|
|
# 保存 PNG（使用png()函数避免conda R的API冲突）
|
|||
|
|
png(filename = output_png, width = 4200, height = 3000, res = 300)
|
|||
|
|
print(p_combo)
|
|||
|
|
dev.off()
|
|||
|
|
cat("[OK] PNG: ", output_png, "\n", sep = "")
|
|||
|
|
|
|||
|
|
cat("[OK] Subfamily used: ", subfamily_file, "\n", sep = "")
|