❝本节来介绍如何使用「rstatix」来进行统计分析，并使用「ggpubr」来添加显著性标记，下面通过一个小例子来进行展示；本次使用R内置数据集；
加载R包
代码语言：javascript复制library(tidyverse)
library(rstatix)
library(ggpubr)
统计分析
代码语言：javascript复制 stat.test <- iris %>% pivot_longer(-Species) %>%
filter(Species !="versicolor") %>%
mutate(group=str_sub(name,start = 1,end = 5)) %>%
group_by(group,name) %>%
t_test(value ~ Species) %>%
adjust_pvalue() %>% add_significance("p.adj") %>%
add_xy_position(x="name",scales="free",fun = "max") %>%
select(-3,-6,-7,-8,-9,-10) %>%
mutate(across("xmin",str_replace,"2.8","0.8"),
across("xmin",str_replace,"3.8","1.8"),
across("xmax",str_replace,"3.2","1.2"),
across("xmax",str_replace,"4.2","2.2")) %>%
mutate(xmin=as.numeric(xmin),xmax=as.numeric(xmax))
数据可视化
代码语言：javascript复制 iris %>% pivot_longer(-Species) %>%
filter(Species !="versicolor") %>%
mutate(group=str_sub(name,start = 1, end = 5)) %>%
ggplot(.,aes(x =name , y = value))
stat_summary(geom = "bar",position = "dodge",aes(fill=Species))
stat_summary(geom = "errorbar",fun.data = "mean_sdl",
fun.args = list(mult = 1),
aes(fill=Species),
position=position_dodge(0.9),width=0.2,color="black")
stat_pvalue_manual(stat.test,label = "p.adj.signif",label.size=6,hide.ns = T,
tip.length = 0.01)
facet_wrap(.~group,scale="free_x",nrow = 1)
labs(x=NULL,y=NULL)
scale_fill_manual(values=c("#BA7A70","#829BAB"))
scale_y_continuous(limits = c(0, 9), expand = c(0, 0))
theme(axis.title.x = element_blank(),
axis.title.y = element_text(color="black",size=12,margin = margin(r=3)),
axis.ticks.x=element_blank(),
axis.text.y=element_text(color="black",size = 10,margin = margin(r =2)),
axis.text.x=element_text(color="black"),
panel.background = element_rect(fill = NA,color = NA),
panel.grid.minor= element_line(size=0.2,color="#e5e5e5"),
panel.grid.major = element_line(size=0.2,color="#e5e5e5"),
panel.border = element_rect(fill=NA,color="black",size=0.3,linetype="solid"),
legend.key=element_blank(),
legend.title = element_blank(),
legend.text = element_text(color="black",size=8),
legend.spacing.x=unit(0.1,'cm'),
legend.key.width=unit(0.5,'cm'),
legend.key.height=unit(0.5,'cm'),
legend.position = c(1,1),legend.justification=c(1,1),
legend.background=element_blank(),
legend.box.margin = margin(0,0,0,0),
strip.text = element_text(color="black",size=10),
panel.spacing.x=unit(0.3,"cm"))
❝此图看起来很是简单，但是难点在于如何使用代码构建统计结果；其中也有不少细节；关于此问题日后再写推文详细介绍
