此外也通过自定义绘制线条来进行注释以及Y轴标题添加上标；那么小编下方案例代码就来简单介绍如何用代码来解决这三个问题 ❞ 加载R包 library(tidyverse) library(readxl) library(ggtext
stat_boxplot(geom="errorbar",width=0.6, position = position_dodge(width=0.9))+ geom_boxplot(width=0.6,outliers = F,lwd=0.5, position = position_dodge(width=0.9)) + 参考: Boxplots in ggplot2 | Carlos I. Rodriguez Spacing between boxplots in ggplot2 in R - GeeksforGeeks发布...
(dose),y = len)) + stat_boxplot(geom = "errorbar",width = 0.1) + geom_boxplot(outlier.shape = NA) + geom_point(aes(fill = factor(dose)),pch = 21,size = 6, position = position_jitter(0.2))+ scale_fill_manual(values = c("#db6968","#4d97cd","#f8984e","#459943")) ...
问组内和组间的Stat_compare_meansENAnosim分析（Analysis of similarities）是一种基于置换检验和秩和检...
ggplot(.,aes(x=weight,y=species.coverage,fill=weight))+#geom_boxplot(outlier.size=1)+stat_summary(fun="mean",size=2,geom="bar",position=position_dodge(0.75))+## 绘制bar,数值来源于计算后的均值stat_summary(fun.data="mean_cl_boot",geom="errorbar",width=.15,position=position_dodge(0.75...
1f27ffe scale-steps.R scale-type.R scale-view.R scale-viridis.R scales-.R stat-.R stat-align.R stat-bin.R stat-bin2d.R stat-bindot.R stat-binhex.R stat-boxplot.R stat-contour.R stat-count.R stat-density-2d.R stat-density.R ...
(ncomp))) + geom_boxplot(outlier.shape = NA, alpha=0.25) + geom_point(aes(color=factor(ncomp)), alpha=0.6, position=position_jitter(w=0.15, h=0)) + guides(fill="none", color="none") + facet_wrap(~ ncomp) + geom_hline(yintercept = 0.5, lwd=.5, linetype=2) + scale_color...
# 上方直方图# Top bar plotp22 <- ggplot(data) +geom_histogram(aes(`Genome size`), binwidth =0.2, fill = "#EB746A", color = "white", size =0.8) +theme_minimal() +theme(axis.title.x = element_blank(),axis.text.x = element_blank(),axis.ticks.x = element_blank(),axis.line ...
(ncomp))) + geom_boxplot(outlier.shape = NA, alpha=0.25) + geom_point(aes(color=factor(ncomp)), alpha=0.6, position=position_jitter(w=0.15, h=0)) + guides(fill="none", color="none") + facet_wrap(~ ncomp) + geom_hline(yintercept = 0.5, lwd=.5, linetype=2) + scale_color...
errorsd_df<-sd_df/2 se<-as.data.frame(sd_df)# 合并数据# Merge datadf1<-cbind(mean_df,se)colnames(df1)<-c("group","mean","se")colnames(df2)<-c("group","Gene_Abundance")# 绘图# Plotp51 <- ggplot()+stat_summary(fun = "mean",geom = "crossbar", mapping = aes(x=df1$...