1. 效果图

2. 预处理及绘图

# 输入数据
> head(dat)
  Species cid     variable value
1  setosa   1 Sepal.Length   5.1
2  setosa   2 Sepal.Length   4.9
3  setosa   3 Sepal.Length   4.7
4  setosa   4 Sepal.Length   4.6
5  setosa   5 Sepal.Length   5.0
6  setosa   6 Sepal.Length   5.4


# 预处理及绘图
row.num=nrow(iris)
dat=iris[1:row.num,] #假设有4个时间点，最后一列是聚类结果
dat$cid=rownames(dat) #很重要！用于 ggplot 的 group
head(dat)
#宽变长
dat = tidyr::gather(data = dat, key = "variable", value = "value", -c(Species, cid))
# or: 宽变长
#dat=reshape2::melt(dat)

# 限定x轴顺序
dat$variable=factor(dat$variable, levels = c('Sepal.Length', 'Sepal.Width', 'Petal.Length', 'Petal.Width'))
head(dat)
dim(dat)
ggplot(dat, aes(x=variable, y=value, group=cid, color=Species))+
  geom_hline(yintercept =4, linetype=2, size=0.5) +
  geom_line(size=0.3)+
  stat_summary(aes(group=1),fun.y=mean, geom="line", size=0.8, color="black")+
  facet_wrap(Species~.)+
  labs(x="Stage", y='Expression')+
  theme_bw()+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        axis.text = element_text(size=8, face = "bold"),
        axis.text.x=element_text(angle=60, hjust=1),
        strip.background = element_rect(fill="white"),
        strip.text = element_text(size = 8, face = "bold"))