一条龙-T检验+绘制boxplot

1.输入文件：

2.代码

#title:boxplot-5utr-cds-3tr-ATCG的百分比分布和T检验_封装函数版
rm(list=ls(all=TRUE))
setwd("E:/R/Rscripts/5UTR_ABD_TE")
library(tidyverse)
library(ggplot2)
# library(RColorBrewer)
library(patchwork)
library(dplyr)
library(tidyr)
library(openxlsx)
library(stringr)
dfutr5<- read.table(file="lijinonextended_5utr_ATCG.fasta",na.strings = "#N/A",sep="\t",header = TRUE)
dfcds<- read.table("lijinonextended_cds_ATCG.fasta",na.strings = "#N/A",sep="\t",header = TRUE)
dfutr3<- read.table("lijinonextended_3utr_ATCG.fasta",na.strings = "#N/A",sep="\t",header = TRUE)




reshape_data_frame <- function(df, id_column = NULL) {
  # 如果指定了ID列，则保留ID列，否则只处理核苷酸列
  if (!is.null(id_column)) {
    df_long <- df %>%
      pivot_longer(
        cols = c(A, T, C, G),
        names_to = "nucleotide",
        values_to = "percentage",
        id_cols = id_column  # 保留ID列
      )
  } else {
    df_long <- df %>%
      select(-Sequence_ID) %>%
      pivot_longer(
        cols = c(A, T, C, G),
        names_to = "nucleotide",
        values_to = "percentage"
      )
  }
  
  return(df_long)
}


# 调用函数，转换数据框，假设我们想保留Id列
# reshaped_df <- reshape_data_frame(df, id_column = "Id")
# print(reshaped_df)

# 如果不想保留Id列
dfutr5longer<- reshape_data_frame(dfutr5) %>% mutate(percentage1=percentage/100)
dfcdslonger<- reshape_data_frame(dfcds)%>% mutate(percentage1=percentage/100)
dfutr3longer<- reshape_data_frame(dfutr3)%>% mutate(percentage1=percentage/100)

##############################################
#######定义函数用于T检验
##############################################

perform_all_combinations_T_test <- function(df, group_column, score_column, df_name) {
  # 获取所有唯一的组
  unique_groups <- unique(df[[group_column]])
  
  # 生成所有可能的两两组合
  combinations <- combn(unique_groups, 2, simplify = FALSE)
  
  # 初始化一个空的数据框来存储结果
  results_df <- data.frame(Comparison = character(), 
                           Mean1 = numeric(), 
                           Mean2 = numeric(), 
                           Pvalue = numeric(), 
                           stringsAsFactors = FALSE)
  
  # 遍历每一对组合进行T检验
  for(combination in combinations) {
    group1 <- combination[1]
    group2 <- combination[2]
    
    # 提取两个组的指定Score值
    scores_group1 <- df[[score_column]][df[[group_column]] == group1]
    scores_group2 <- df[[score_column]][df[[group_column]] == group2]
    
    # 确保scores_group1和scores_group2不为空并且都是数值型
    if (length(scores_group1) > 0 && length(scores_group2) > 0 && 
        all(is.numeric(scores_group1)) && all(is.numeric(scores_group2))) {
      
      # 进行T检验
      t_test_result <- t.test(scores_group1, scores_group2)
      
      # 计算两个组的均值
      mean_group1 <- mean(scores_group1, na.rm = TRUE)
      mean_group2 <- mean(scores_group2, na.rm = TRUE)
      
      # 向结果数据框添加一行
      comparison_value <- paste(df_name, group1, "_Vs_", df_name, group2, sep="")
      new_row <- data.frame(Comparison = comparison_value,
                            Mean1 = mean_group1, 
                            Mean2 = mean_group2, 
                            Pvalue = t_test_result$p.value, 
                            stringsAsFactors = FALSE)
      results_df <- rbind(results_df, new_row)
    }
  }
  
  return(results_df)
}


# 调用函数的例子：
result5utr <- perform_all_combinations_T_test(dfutr5longer, "nucleotide", "percentage1", "5utr")
resultcds <- perform_all_combinations_T_test(dfcdslonger, "nucleotide", "percentage1", "cds")
result3utr <- perform_all_combinations_T_test(dfutr3longer, "nucleotide", "percentage1", "3utr")

# # 正确的调用方法
# t.test_result <- t.test(
#   dfutr5longer$percentage1[dfutr5longer$nucleotide == "A"],
#   dfutr5longer$percentage1[dfutr5longer$nucleotide == "T"]
# )
# 
# # 打印测试结果
# print(t.test_result)

###########################################################################
##绘制boxplot-自定义函数
##########################################################################
library(tidyverse)
library(ggplot2)
library(patchwork)

# 更新函数定义以包括x轴标题作为参数
create_grouped_boxplot <- function(data, group_var, score_var, x_label = "5'UTR",
                                   y_label = "Score", y_limits = c(0, 100), y_breaks = seq(0, 100, 20), 
                                   fill_values = c("#c59d94", "#afc7e8", "#dbdb8d", "#ff9896")) {
  data[[group_var]] <- factor(data[[group_var]], 
                              levels = c("A", "T", "C", "G"), 
                              labels = c("A", "U", "C", "G"), 
                              ordered = TRUE)
  
  p <-  ggplot(data, aes(x = .data[[group_var]], y = .data[[score_var]], fill = .data[[group_var]])) +
    # geom_violin(trim=FALSE,color="white") + 
    geom_errorbar(width = 0.1,size = 0.35,position = position_dodge(0.9),stat = "boxplot") +
    geom_boxplot(outlier.size = -1,width = 0.25,position = position_dodge(0.9),fatten = 1.2,size = 0.5) +
    theme_classic() +labs(y = y_label, x = x_label) +
    scale_y_continuous(limits = y_limits, breaks = y_breaks) +
    theme(
      strip.background = element_rect(colour = "black", fill = "#FFFFFF"),
      plot.title = element_text(hjust = 0.5, vjust = 1, lineheight = 1, color = "black"),
      panel.background = element_rect(fill = "white", colour = "black", linewidth  = 0.5),
      axis.title.y = element_text(size = 15, face = "bold", color = "black"),
      axis.title.x = element_text(size = 15, face = "bold", color = "black", vjust = 0.5, hjust = 0.5, margin = margin(t = 12)),
      axis.text = element_text(size = 13, face = "bold", color = "black")
    ) +scale_fill_manual(values = fill_values) +guides(fill = "none")
  
  return(p)
}
p1 <- create_grouped_boxplot(dfutr5longer, "nucleotide", "percentage", x_label = "5'UTR")
p2 <- create_grouped_boxplot(dfcdslonger, "nucleotide", "percentage", x_label = "CDS")
p3 <- create_grouped_boxplot(dfutr3longer, "nucleotide", "percentage", x_label = "3'UTR")
p4<-p1+p2+p3+plot_layout(nrow = 1,ncol = 3)
ggsave("boxplot-5utr-cds-3tr-ATCG的百分比分布和T检验.pdf",plot=p4,width=18,height=8)
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3.输出结果：