论文
Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia
论文中提供的代码链接
论文中提供的数据在 Source data 部分获取
环境变量的相关性对应的论文中的 Supplementary Fig. 9. a
论文中提供的环境数据的部分截图
读取数据
library(tidyverse)
raw_data<-read_csv("data/20231110/Source data/Fig2c&d/environment.csv") %>%
select(-c(1,2,3))
计算相关性
corrmatrix <- cor(raw_data, method = "spearman")
corrmatrix
相关性检验
res1 <-corrplot::cor.mtest(corrmatrix, conf.level= .95)
res1$p
res1$lowCI
res1$uppCI
论文中提供的作图代码
col3 <- grDevices::colorRampPalette(c("#2082DD", "white", "#FF3F3F"))
col3
corrplot::corrplot.mixed(corr=corrmatrix,
lower="number",
upper="circle",
diag="u",
upper.col =col3(20),
lower.col = col3(20),
number.cex=0.9,
p.mat= res1$p,
sig.level= 0.05,
bg = "white",
is.corr = TRUE,
outline = FALSE,
mar = c(0,0,3,0),
addCoef.col = NULL,
addCoefasPercent = FALSE,
order = c("original"),
rect.col = "black",
rect.lwd = 1,
tl.cex = 1.2,
tl.col = "black",
tl.offset = 0.4,
tl.srt = 90,
cl.cex = 1.1,
cl.ratio = 0.2,
tl.pos="lt",
cl.offset = 0.5 )
title(main="Correlation coefficient of 19 environmental variables",cex.main=2.1)
出图效果
这个有好多参数,参数具体都有什么作用后面如果用到了再来研究吧
ggcorrplot作图
这个是ggplot2系列,修改细节可能会比较方便
安装install.packages("ggcorrplot")
作图代码library(ggcorrplot)
ggcorrplot(corr = corrmatrix,
hc.order = TRUE,
method = "circle",
type="upper",
lab = TRUE)+
theme(axis.text.x = element_blank(),
panel.grid = element_blank(),
legend.position = c(0.8,0.3))
组合图library(ggcorrplot)
p1<-ggcorrplot(corr = corrmatrix,
hc.order = TRUE,
method = "circle",
type="upper",
lab = TRUE)+
theme(axis.text.x = element_blank(),
panel.grid = element_blank(),
legend.position = c(0.8,0.3))
p1
p2<-ggcorrplot(corr = corrmatrix)+
scale_fill_viridis_c()
library(patchwork)
p1+p2
示例数据和代码可以给推文打赏一元获取
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