ac  <- read.csv("D:/High-throughput sequencing/!!!!GSE167940/RNA-seq/组蛋白修饰酶/ac.csv",header = T,row.names = 1)
me3 <- read.csv("D:/High-throughput sequencing/!!!!GSE167940/RNA-seq/组蛋白修饰酶/组蛋白修饰酶.csv",header = T,row.names = 1) 
library(ggplot2)
library(tidyr)
library(dplyr)
#按行归一化；
hd_ac  = t(scale(t(ac)))
hd_me3 = t(scale(t(me3)))
#预览数据；
head(hd_ac)

#转成数据框；
gene_ac <- row.names(hd_ac)
hf_ac <- data.frame(gene_ac,hd_ac)
gene_me3 <- row.names(hd_me3)
hf_me3 <- data.frame(gene_me3,hd_me3)
#转成长形数据；
dt_ac  <- hf_ac %>% pivot_longer(
  cols = !gene_ac,
  values_drop_na = FALSE,
  names_to = "groups",
  values_to = "expressions")
dt_me3 <- hf_me3 %>% pivot_longer(
  cols = !gene_me3,
  values_drop_na = FALSE,
  names_to = "groups",
  values_to = "expressions")
#预览作图数据；
head(dt_ac)

转成因子，避免ggplot2自动排序；
#为了确保绘图顺序从上到下，可以颠倒level的顺序；
dt_ac$gene_ac <- factor(dt_ac$gene_ac,
                   levels = rev(unique(dt_ac$gene_ac)),
                   ordered = T)
dt_me3$groups <- factor(dt_me3$groups,
                   levels = unique(dt_me3$groups),
                     ordered = T)
#绘制热图,linewidth调整格子线粗细，color调整格子线颜色；
p_ac <- ggplot(dt_ac, aes(groups, gene_ac)) +
  geom_tile(aes(fill = expressions),linewidth=0.4,
            height=1,width=1,
            colour = "black")+
  scale_fill_gradient2(low = "#3FA9F5",
                       mid = "white",
                       high = "#FF931E",
                       midpoint = 0.5,
                       na.value = "grey92",
                       name="Exp")+
  scale_x_discrete(position = "bottom")+
  scale_y_discrete(position = "right")+
  xlab('')+ylab('')+
  theme(axis.text.x.bottom= element_text(angle = 45,face = "bold",
                                       size=8,
                                       hjust=0.3,vjust =0.5),
        axis.text.y.right = element_text(angle = 0,face = "bold",
                                         size=8,
                                         hjust=1,vjust = 0.5),
        panel.background = element_blank(),
        legend.title = element_text(size = 6),
        legend.position="left")+
  guides(fill = guide_colourbar(direction = "vertical",
                                title.hjust=0,
                                title.position ="top",
                                ticks.colour="white",
                                frame.colour="purple",
                                barheight=5,
                                barwidth=0.7))+
  coord_fixed(ratio = 1,expand=T)+
  ggtitle("H3K27ac") 
p_ac


p_me3 <- ggplot(dt_me3, aes(groups, gene_me3)) +
  geom_tile(aes(fill = expressions),linewidth=0.4,
            height=1,width=1,
            colour = "black")+
  scale_fill_gradient2(low = "#3FA9F5",
                       mid = "white",
                       high = "#FF931E",
                       midpoint = 0.5,
                       na.value = "grey92",
                       name="Exp")+
  scale_x_discrete(position = "bottom")+
  scale_y_discrete(position = "right")+
  xlab('')+ylab('')+
  theme(axis.text.x.bottom= element_text(angle = 45,face = "bold",
                                         size=8,
                                         hjust=0.3,vjust =0.5),
        axis.text.y.right = element_text(angle = 0,face = "bold",
                                         size=8,
                                         hjust=1,vjust = 0.5),
        panel.background = element_blank(),
        legend.title = element_text(size = 6),
        legend.position="left")+
  guides(fill = guide_colourbar(direction = "vertical",
                                title.hjust=0,
                                title.position ="top",
                                ticks.colour="white",
                                frame.colour="purple",
                                barheight=5,
                                barwidth=0.7))+
  coord_fixed(ratio = 1,expand=T)+
  ggtitle("H3K4me3") 
p_me3