跟着Nature Plants学作图：R语言ggplot2画变种火山图
跟着Nature Plants学作图：R语言ggplot2画变种火山图
用户7010445
发布于 2023-01-06 18:33:07
发布于 2023-01-06 18:33:07
论文
The flying spider-monkey tree fern genome provides insights into fern evolution and arborescence
https://www.nature.com/articles/s41477-022-01146-6#Sec44
数据下载链接
https://doi.org/10.6084/m9.figshare.19125641
今天的推文重复一下论文中的Extended Data Fig. 3 c
image.png
他这个图的数据是怎么算出来的我还有点搞不明白，它的图注的内容也没有看明白
Gene pairs plotted according to log2 fold change (L2F) as calculated for gene 1 (x-axis) and gene 2 (y-axis) in DESeq2. Each point represents one gene pair with pairs colored according to the difference in L2F values (diffL2F = |L2F_1 - L2F_2|) to visualize the arbitrary cutoffs of diffL2F = 2 and diffL2F = 4.
部分示例数据如下
image.png
作图数据是 L2F_1 和 L2F_2 两列，还需要根据L2F_diff的取值增加一列映射颜色
首先是读取数据
library(readxl)
dat01<-read_excel("data/20220529/20220529.xlsx")
head(dat01)
增加一列映射颜色
library(tidyverse)
dat01 %>%
mutate(diffL2F=case_when(
L2F_diff < 2 ~ "<2",
L2F_diff >=2 & L2F_diff<=4 ~ ">2",
TRUE ~ ">4"
)) -> dat01.1
作图代码
library(ggplot2)
ggplot(data=dat01.1,aes(x=L2F_1,y=L2F_2))+
geom_point(aes(color=diffL2F))+
scale_color_manual(values = c("<2"="#7f7f7f",
">2"="#fe0904",
">4"='#f9b54f'))+
geom_abline(intercept = 0,slope = 1,
lty="dashed",size=1,
color="blue")
image.png
论文中有六组数据，批量读入，批量作图
批量读取excel
library(tidyverse)
library(readxl)
list.files("data/20220529/",
pattern = "*.xlsx",
full.names = TRUE) %>%
map(.,read_excel) -> dat.list
批量作图
library(ggplot2)
plot.list = list()
text.label<-c("StGa","SoGa","LeGa","StSo","SoLe","LeSt")
for (i in 1:6){
dat.list[[i]] %>%
mutate(diffL2F=case_when(
L2F_diff < 2 ~ "<2",
L2F_diff >=2 & L2F_diff<=4 ~ ">2",
TRUE ~ ">4"
)) %>%
ggplot(aes(x=L2F_1,y=L2F_2))+
geom_point(aes(color=diffL2F))+
scale_color_manual(values = c("<2"="#7f7f7f",
">2"="#fe0904",
">4"='#f9b54f'))+
geom_abline(intercept = 0,slope = 1,
lty="dashed",size=1,
color="blue")+
geom_text(aes(x=-Inf,y=Inf),
hjust=-0.5,vjust=2,
label=text.label[i])+
labs(x=NULL,y=NULL) -> plot.list[[i]]
}
将六个图拼接到一起
wrap_plots(plot.list,ncol=3,nrow=2,byrow = TRUE)+
plot_layout(guides = "collect") -> p1
p1
image.png
修改整体的边界空白
p1 +
plot_annotation(theme =
theme(plot.margin = unit(c(0.2,0.2,1.2,1.2),'cm')))
添加坐标轴标题
grid::grid.draw(grid::textGrob("Log2(fold change)\ngene1", x = 0.04, rot = 90))
grid::grid.draw(grid::textGrob("Log2(fold change)\ngene2", y = 0.04))
image.png
示例数据可以到论文中去下载，代码可以直接在推文中复制
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原始发表：2022-05-29，如有侵权请联系 cloudcommunity@tencent.com 删除
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