论文图表复现—箱线图

今天，我们来对下面这篇文章中的Fig.2b及Fig.2c中的图进行复现：

设置工作环境

#设置工作环境rm(list=ls())setwd("D:\\Fig2")
#加载包library(ggplot2)

Fig.2b

1、加载数据

df1 <- read.table("df_1.txt",header = T, check.names = F)head(df1)

2、绘制箱线图

p1 <- ggplot(data =df1, aes(x=Comparison, y=Dissimilarity)) + geom_boxplot(aes(fill = Comparison), width = 0.8)

3、添加散点图

p1+geom_point(position='jitter',shape=1, alpha=.5)

4、主题设置

p1+theme_bw() + theme(aspect.ratio = 1)+ geom_point(position='jitter',shape=1, alpha=.5)+ ylab("Bray-Curtis dissimilarity\n") + theme(axis.line = element_line(colour = "black"), legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank()) + theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) + theme(axis.title.x = element_text(size = 10,hjust = 0.5, face='bold')) + theme(axis.title.y = element_text(size = 10,hjust = 0.5, face='bold')) + theme(axis.text.x = element_text(angle = 0, hjust = 0.95, vjust=0.4,size=10, face='bold',color='black'))+ theme(axis.text.y = element_text(size=10, face='bold',color='black'))+ scale_y_continuous(breaks=seq(0,1,0.2))

Fig.2c

1、加载数据及数据处理

df2 <- read.csv("df_2.csv", encoding="UTF-8")df2$Days <- factor(df2$Days, levels = c('76','90','106','120','141', "0"))df2$group <- factor(df2$group, levels = c('Early successional','Mid-successional / No trend','Late successional'))head(df2)

2、绘制基本箱线图

p2<-ggplot(data =df2, aes(x = Days, y = TotalAbund,fill=group)) + geom_boxplot(width = 0.8)

3、按照group进行分面

p1+facet_wrap(~group,nrow=3)

4、添加散点

p1+geom_point(position='jitter',shape=16, alpha=.5)+ facet_wrap(~group,nrow=3)

5、主题设置及图例去除

p1+geom_point(position='jitter',shape=16, alpha=.5)+ theme_classic() + facet_wrap(~group,nrow=3)+ labs(x = '', y = 'Relative abundance') + scale_fill_manual(values = col)+ scale_y_continuous(expand = c(0,0))+ theme(legend.position = 'none', strip.background = element_blank())+ geom_hline(aes(yintercept=0))+ theme(plot.title = element_text(size = 20,hjust = 0.5, face='bold')) + theme(axis.title.x = element_text(size = 10,hjust = 0.5, face='bold')) + theme(axis.title.y = element_text(size = 10,hjust = 0.5, face='bold')) + theme(axis.text.x = element_text(angle = 0, hjust = 0.95, vjust=0.4,size=10, face='bold',color='black'))+ theme(axis.text.y = element_text(size=10, face='bold',color='black'))

参考： 

https://github.com/hyunkim90/spatiotemporal_tracking_rice_endophytic_communities

代码及数据获取：后台回复'2022-8-10'获取！！！

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