library('ggplot2')

setwd("C:/bin")

data <- read.table('result_pita_results.tab', sep="\t", header=TRUE)

ddG_counts <- as.data.frame(table(data$ddG))

colnames(ddG_counts) <- c("ddG", "Count")

# 使用 ggplot2 繪制圖表

p=ggplot(ddG_counts, aes(x = ddG, y = Count)) +

? geom_bar(stat = "identity", width = 0.5) +

? labs(x = "ddG 值", y = "UTR 的個數(shù)", title = "ddG 值與 UTR 的個數(shù)關(guān)系") +

? theme_minimal()

ddG_counts <- as.data.frame(table(data$ddG))

colnames(ddG_counts) <- c("ddG", "Count")

# 將 ddG 列轉(zhuǎn)換為數(shù)值類型

ddG_counts$ddG <- as.numeric(as.character(ddG_counts$ddG))

# 使用 ggplot2 繪制圖表

p1=ggplot(ddG_counts, aes(x = ddG, y = Count)) +

? geom_point(size = 3) +

? geom_line() +

? labs(x = "ddG 值", y = "UTR 的個數(shù)", title = "ddG 值與 UTR 的個數(shù)關(guān)系") +

? theme_minimal()

ddG_counts <- as.data.frame(table(data$ddG))

colnames(ddG_counts) <- c("ddG", "Count")

# 將 ddG 列轉(zhuǎn)換為數(shù)值類型

ddG_counts$ddG <- as.numeric(as.character(ddG_counts$ddG))

# 使用 ggplot2 繪制圖表

p3=ggplot(ddG_counts, aes(x = ddG, y = Count)) +

? geom_smooth(method = "loess", span = 0.25, se = FALSE) +

? labs(x = "ddG value", y = "miRNA and mRNA interactions number") +

? theme_minimal()

p3