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1.一R代码添加显著性 1#1----set.seed(123)library(ggplot2)library(ggstatsplot)ggbetweenstats( data iris, x Species, y Sepal.Length, title Distribution of sepal length across Iris species)还有详细参数的解释 2.还可以换一种方式展示 2#2------library(ggpubr)# Load datadata(ToothGrowth)df - ToothGrowthhead(df, 4)# Add p-values comparing groups# Specify the comparisons you wantmy_comparisons - list( c(0.5, 1), c(1, 2), c(0.5, 2) )ggboxplot(df, x dose, y len, color dose, palette c(#00AFBB, #E7B800, #FC4E07), add jitter, shape dose) stat_compare_means(comparisons my_comparisons) # Add pairwise comparisons p-value stat_compare_means(label.y 50) # Add global p-value# Violin plots with box plots inside# :::::::::::::::::::::::::::::::::::::::::::::::::::# Change fill color by groups: dose# add boxplot with white fill colorggviolin(df, 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) # Add significance levels stat_compare_means(label.y 50) # Add global the p-value3. 单细胞的密度图 3# 3 单细胞密度图----pbmcreadRDS(~/gzh/pbmc3k_final.rds)library(Seurat)
pDimPlot(pbmc,label TRUE)datp$datahead(dat)#install.packages(ggpointdensity)library(ggpointdensity)
ggplot(data dat, mapping aes(x UMAP_1, y UMAP_2)) geom_pointdensity(adjust 4) viridis:: scale_color_viridis() 4 生存曲线 4 #4 生存曲线------#install.packages(ggsurvfit)library(ggsurvfit)# Loading required package: ggplot2
p - survfit2(Surv(time, status) ~ surg, data df_colon) | ggsurvfit(linewidth 1) add_confidence_interval() add_risktable() add_quantile(y_value 0.6, color gray50, linewidth 0.75) scale_ggsurvfit()pp # limit plot to show 8 years and less coord_cartesian(xlim c(0, 8)) # update figure labels/titles labs( y Percentage Survival, title Recurrence by Time From Surgery to Randomization, )
