跟着Nature Communications学作图:R语言gg
2023-03-05 本文已影响0人
小明的数据分析笔记本
论文
A latitudinal gradient of deep-sea invasions for marine fishes
https://www.nature.com/articles/s41467-023-36501-4
s41467-023-36501-4.pdf
论文中对应的图实现的代码都有,链接是
https://github.com/stfriedman/Depth-transitions-paper
今天的推文我们重复一下论文中的figure1A,其中一个堆积柱形图和一个哑铃图,哑铃图就是点和线段的组合
首先是右侧哑铃图
部分示例数据截图
image.png有一些分组数据论文中没有提供,这部分数据我就随便构造了,最终的出图不会和论文中完全一致
加载用到的R包
library(readxl)
library(tidyverse)
library(wesanderson)
读取数据
fig1_data<-read_excel("data/20230302/41467_2023_36501_MOESM7_ESM.xlsx")
fig1_data %>% dim()
给数据集添加两列分组
fig1_data %>%
mutate(cat=sample(c("small","norm","big"),46,replace = TRUE),
col=sample(c("Above expectation",
"Within expectation",
"Below expctation"),
46,replace = TRUE)) -> fig1_data
作图代码
ggplot(fig1_data, aes(x = family, y = trans_num)) +
geom_segment(aes(x = family, xend = family, y = sim_0.05, yend = sim_0.95),
col = "grey90", lwd = 3, lineend = "round"
) +
geom_segment(aes(x = family, xend = family, y = sim_median, yend = trans_num),
col = "grey50", lwd = 0.6
) +
geom_point(aes(x = family, y = sim_median),
pch = 21,
fill = "white", col = "grey50", size = 3, stroke = 1
) +
geom_point(size = 3.3,aes(color=col)) +
theme_classic() +
theme(
axis.text.y = element_blank(),
plot.margin = unit(c(0, 0.4, 0, 0), "cm"),
panel.grid.major.x = element_blank(),
panel.border = element_blank(),
panel.grid.major.y = element_line(size = 0.4),
axis.line.x = element_line(size = 0.2),
axis.line.y = element_blank(),
axis.ticks.x = element_line(size = 0.1),
axis.ticks.y = element_blank(),
legend.position = c(0.8,0.1),
legend.background = element_rect(color="black",fill="transparent"),
legend.title = element_blank(),
axis.title = element_text(size = 12),
axis.title.y = element_blank()
) +
coord_flip() +
ylab("Number of Transitions") +
labs(col = "Speciation Rate") +
scale_color_manual(values = c(
wes_palette("Darjeeling1")[2], "grey40",
wes_palette("Darjeeling1")[3]
)) -> p1
p1
image.png
堆积柱形图
这个数据论文中没有提供,这里我们随便构造数据
df1<-data.frame(x=rep(fig1_data$family,3),
y1=c(rep(c("Shallow","Deep","Intermediate"),each=46)),
y2=sample(1:100,46*3,replace = TRUE))
df1 %>% head()
准备颜色
depth_cols <- setNames(
c("powderblue", "#2C8EB5", "#16465B"),
c("Shallow", "Intermediate", "Deep")
)
作图代码
ggplot(data=df1,
aes(y = y2, x = x)) +
geom_bar(position = "fill", stat = "identity", width = 0.7,
aes(fill=y1)) +
coord_flip() +
theme_classic() +
theme(
#axis.text.y = element_text(colour = famcol),
axis.text.x = element_blank(),
axis.ticks = element_blank(),
axis.line = element_blank(),
legend.position = "bottom",
legend.justification = c(0,0),
legend.key.size = unit(2,'mm'),
legend.title = element_blank(),
legend.background = element_rect(color="black",fill="transparent")
) +
xlab("") +
ylab("") +
guides(fill=guide_legend(ncol = 2))+
scale_fill_manual(values = depth_cols) -> p2
p2
image.png
最后是拼图
library(patchwork)
p2+p1+
plot_layout(widths = c(1,5))
image.png
示例数据和代码可以给推文点赞,然后点击在看,最后留言获取
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