boxplot,自带四分位信息,最好加上jitter让人看到你的数据点 violin plot,在单细胞里很火,可以直接看到数据的分布,可以叠加boxplot使用 线性拟合回归,lm,我们目前绝对无法handle非线性的回归这些经典分析必须搭配显著性测试,必须在图里显示P-value,或者P-value对应的符号(*、**、***、NS)。目前在ggplot里添加显著...
ggboxplot color = "supp", palette = "aaas", add = "jitter") # Add p-value p1 = p + stat_compare_means() #default Wilcoxon p2 = p + stat_compare_means(method = "t.test") p1 + p2 (2)标签显示格式 #标签位置 p1 = p + stat_compare_means(label.x.npc = "left", # label.x...
stat.test %>% add_xy_position(x = "dose", dodge = 0.8) # 确定第二个统计量的位置 stat.test2 <- stat.test2 %>% add_xy_position(x = "dose") # 与boxplot 融合 bxp + stat_pvalue_manual(stat.test,lable = "p") + stat_pvalue_manual(stat.test2,label = "p.adj.signif",tip....
ggboxplot(ToothGrowth, x = "dose", y = "len", color = "dose", palette = "jco")+ stat_compare_means(method = "anova", label.y = 40)+ # Add global p-value stat_compare_means(label = "p.signif", method = "t.test", ref.group = ".all.") # Pairwise comparison against all...
如何仅获取十进制格式的pvalueEN下面是去年实习生的分享 EnhancedVolcano包可根据差异分析结果，基于ggplot2...
ToothGrowth%>%mutate(dose=as.factor(dose))%>%ggplot(aes(dose,len))+stat_boxplot(geom="errorbar",width=0.2,aes(fill=supp),position=position_dodge(1))+geom_boxplot(aes(fill=supp),position=position_dodge(1))+stat_pvalue_manual(stat.test2,label="p.adj.signif",label.size=6,hide.ns=T,...
# Box plots with p-valuesbxp <- ggboxplot(df, x ="supp", y ="len", fill ="#00AFBB") stat.test <- stat.test %>% add_xy_position(x ="supp") bxp + stat_pvalue_manual(stat.test, label ="p") + scale_y_continuous(expand = expansion(mult = c(0.05,0.1)))# Customize p-...
这个函数扩展了ggplot2,可以对指定ggplot图形添加均值比较的p值。 简单形式如下: AI检测代码解析 stat_compare_means(mapping=NULL,comparisons=NULL,hide.ns=FALSE,label=NULL,label.x=NULL,label.y=NULL) 1. 2. 3. 4. 5. 6. mapping: 由aes()创建的映射集合 ...
# Create a box plot bxp <- ggboxplot( df, x = "dose", y = "len", color = "supp", palette = c("#00AFBB", "#E7B800") ) # Add p-values onto the box plots stat.test <- stat.test %>% add_xy_position(x = "dose", dodge = 0.8) bxp + stat_pvalue_manual( s...
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") + ...