library(ggplot2)
library(dplyr)
library(forcats)
# 创建数据框
data <- data.frame(
  Description = c(
    "KEGG_STARCH_AND_SUCROSE_METABOLISM",
    "KEGG_PENTOSE_AND_GLUCURONATE_INTERCONVERSIONS", 
    "KEGG_METABOLISM_OF_XENOBIOTICS_BY_CYTOCHROME_P450",
    "KEGG_PORPHYRIN_AND_CHLOROPHYLL_METABOLISM",
    "KEGG_NEUROACTIVE_LIGAND_RECEPTOR_INTERACTION"
  ),
  pvalue = c(0.000396688, 0.000246396, 0.000508482, 0.005582234, 0.001678246)
)
# 数据处理：计算-log10(pvalue)并排序
data <- data %>%
  mutate(
    Description_short = gsub("KEGG_", "", Description),
    log_pvalue = -log10(pvalue)
  ) %>%
  arrange(log_pvalue) %>%  # 按升序排列，这样最大的在顶部
  mutate(Description_short = fct_reorder(Description_short, log_pvalue))
# 创建条形图
ggplot(data, aes(x = log_pvalue, y = Description_short)) +
  geom_bar(stat = "identity", fill = "#F0510C", width = 0.8,alpha=0.8) +
  geom_text(aes(label = Description_short, x = 0.1), 
            hjust = 0, size = 3.5, color = "black") +
  labs(
    title = "KEGG Pathway Enrichment",
    x = "-Log10(Pvalue)",
    y = "Tumer_C2"
  ) +
  theme_classic() +
  theme(
    plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
    axis.title.x = element_text(size = 12, face = "bold"),
    axis.text.y = element_blank(),  # 隐藏Y轴文字
    axis.ticks.y = element_blank(), # 隐藏Y轴刻度
    axis.text.x = element_text(size = 10),
    panel.grid.major.y = element_blank(),
    panel.grid.minor.y = element_blank(),
    panel.grid.major.x = element_blank(),
    panel.grid.minor.x = element_blank()
  ) +
  scale_x_continuous(expand = expansion(mult = c(0, 0.1)))