浅谈R中相关性网络热图绘制小细节
❝最近在绘制相关性网络热图的时候突然有一个小的发现，可以使用相关性热图的数据来结合「linkET」来绘图，以前一直认为为必须使用「mantel_test」才行；果然绘图还得多思考；本节就来通过一个案例将两份数据结合起来进行绘图；
加载R包
library(tidyverse)
library(linkET)
library(RColorBrewer)
library(ggtext)
library(magrittr)
library(psych)
library(reshape)
导入数据
table1 <- read.delim("env.xls",header =T,sep="\t",row.names = 1,check.names = F)
table2 <- read.delim("genus.xls",header =T,sep="\t",row.names = 1,check.names = F) %>%
t() %>% as.data.frame()
相关性分析
pp <- corr.test(table1,table2,method="pearson",adjust = "fdr")
整合数据
cor <- pp$r
pvalue <- pp$p
df <- melt(cor) %>% mutate(pvalue=melt(pvalue)[,3],
p_signif=symnum(pvalue, corr = FALSE, na = FALSE,
cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
symbols = c("***", "**", "*", "", " "))) %>%
set_colnames(c("env","genus","r","p","p_signif"))
转换数据格式
❝在此处以前一直以为必须使用「linkET::mantel_test」函数生成特定格式才能用于后面绘图，直到某次看了数据才明白导入外部的相关性分析数据也能用于后期绘图；此处的范围可根据需要自定义 ❞
cordata <- df %>% left_join(.,read_tsv('annotation.xls'),by=c("genus")) %>%
select(group,env:p,-genus) %>%
set_colnames(c("spc","env","r","p")) %>%
mutate(rd = cut(r, breaks = c(-Inf, 0, 0.4, Inf),
labels = c("< 0", "0 - 0.4", ">= 0.4")),
pd = cut(p, breaks = c(-Inf, 0.01, 0.05, Inf),
labels = c("< 0.01", "0.01 - 0.05", ">= 0.05")))
绘制相关性网络图
qcorrplot(correlate(table1,method = "spearman"),diag=F,type="upper")+
geom_tile()+
geom_mark(size=2.5,sig.thres=0.05,sep="\n")+
geom_couple(aes(colour=pd,size=rd),data=cordata,label.colour = "black",
curvature=nice_curvature(0.15),
nudge_x=0.2,
label.fontface=2,
label.size =4,
drop = T)+
scale_fill_gradientn(colours = RColorBrewer::brewer.pal(11,"RdBu"))+
scale_size_manual(values = c(0.5, 1, 2)) +
scale_colour_manual(values =c("#D95F02","#1B9E77","#A2A2A288")) +
guides(size = guide_legend(title = "cor",override.aes = list(colour = "grey35"), order = 2),
colour = guide_legend(title = "P_value",override.aes = list(size = 3), order = 1),
fill = guide_colorbar(title = "spearman's r",order = 3))+
theme(plot.margin = unit(c(0,0,0,-1),units="cm"),
panel.background = element_blank(),
axis.text=element_markdown(color="black",size=10),
legend.background = element_blank(),
legend.key = element_blank())
❝本节介绍到此结束
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原始发表：2022-11-08，如有侵权请联系 cloudcommunity@tencent.com 删除
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