# p + stat_compare_means(label = "p.signif", label.x = 1.5) p <- ggboxplot(ToothGrowth, x = "dose", y = "len", color = "supp", palette = "jco") p2 = p + stat_compare_means(aes(group = supp)) # p + stat_compare_
问ggplot2 -一个因素的情节没有显示stat_compare_means KruskalEN我认为，您的错误可能来自于如何将数据...
add = "jitter")+ stat_compare_means(comparisons = my_comparisons)+ stat_compare_means(label.y = 9) ggpubr 三、图片保存 1.ggplot ggsave("name.png") ggsave(p, filename = "name.png") 2.三段式 保存的格式和文件名:pdf("test.pdf") 作图代码:... 关闭画板:dev.off 3.eoffice:导入到PPT...
scale_x_discrete(labels=c("Stromal","Immune","ESTIMATE")) + stat_compare_means(aes(group = group), label = "p.signif", method = "wilcox", label.y = max(ESTI_score_New$score), hide.ns = T) ESTI_split_violin; ggsave(ESTI_split_violin,filename = "./Output/ESTIMATE_plot.pdf", ...
在SCI论文中,经常需要在图表中添加数据显著性标记。在R语言中,可以使用ggpubr包中的stat_compare_means函数轻松添加统计显著性标记。 首先,加载ggpubr包: ```r library(ggpubr) ``` 然后,在绘制图表时使用stat_compare_means函数: ```r ggplot(data, aes(x=x, y=y)) + ...
stat_compare_means(method = "t.test", #统计方法 aes(label = "p.format"), #显示方式 label.x.npc = "left", label.y.npc = 'top',#位置 size = 5 #大小 ) gene87 <- ggplot(data, aes(x = surstat, y = gene87, fill=surstat)) + ...
stat_compare_means(aes(group = group), label = 'p.signif', method = 'anova', label.y = max(data_new$expression), hide.ns = T) gene_split_violin;ggsave(gene_split_violin, filename = './Output/gene_split_violin.pdf', height = 10,width = 16,units = 'cm') ...
面用'free_y' - r Package stat_compare_means()，ggplot 2我找到了一个解决方案，而不是试图设置...
ggviolin(df1,x="dose",y="len",fill = "dose",palette = c("#00AFBB", "#E7B800", "#FC4E07"), add="boxplot", add.params=list(fill="white")) + stat_compare_means(comparisons = my_comparisons, label = "p.signif") + ...
上面的P值是用stat_compare_means计算的,其实多组间的两两比较还可以考虑用校正后的P值,可以使用rstatix包进行计算: stat.test<- pan.meta %>% group_by(Type) %>% t_test(Expression~Group) %>% adjust_pvalue(method ='bonferroni') %>%