论文
Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia
https://www.nature.com/articles/s41467-022-34206-8
论文的代码链接
https://github.com/jingwanglab/Populus_genomic_prediction_climate_vulnerability
今天的推文我们尝试复现一下论文中的figure3e和figure3i
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figure3e的示例数据
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读取数据并作图
代码语言：javascript复制p1<-ggplot(data = dat.fig3e,aes(x=hour,y=relative_expression))
geom_point(aes(color=base),size=5)
geom_line(aes(color=base),
show.legend = FALSE)
geom_errorbar(aes(ymin=relative_expression-STD,
ymax=relative_expression STD,color=base),
width=0.4)
theme_bw(base_size = 20)
theme(panel.grid = element_blank(),
legend.position = c(0.2,0.8))
scale_color_manual(values = c("ALT"="#a2c0e4",
"REF"="#2d52a2"),
labels=c("CC","TC"),
name=NULL)
labs(x="Time since submergence stress",
y="Expression")
p1
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figure3i 数据截图
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作图代码基本和fig3e的一致
但是这里的时间跨度从0,1,2,3突然跨到24，这样出图不是很好看，我们把24改成4，然后在坐标轴标签上再改为24
代码语言：javascript复制p2<-ggplot(data = dat.fig3i,aes(x=hour,y=relative_expression))
geom_point(aes(color=base),size=5)
geom_line(aes(color=base),
show.legend = FALSE)
geom_errorbar(aes(ymin=relative_expression-STD,
ymax=relative_expression STD,color=base),
width=0.2)
theme_bw(base_size = 20)
theme(panel.grid = element_blank(),
legend.position = c(0.2,0.8))
scale_color_manual(values = c("ALT"="#e1c4c4",
"REF"="#b0383f"),
labels=c("AA","GG"),
name=NULL)
labs(x="Time since heat stress",
y="Expression")
scale_x_continuous(breaks = 0:4,
labels = paste0(c(0,1,2,3,24),"h"))
p2
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最后是将两个图组合到一起
代码语言：javascript复制library(patchwork)
p1 p2
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