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发表于 2022-9-27 23:57:56
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一、分组条形图
- x <- read.csv("sv_distrubution.csv",header = T)
- x
- # svs <- x %>% tidyr::pivot_longer(cols = 2:5,names_to = 'variation')
- svs <- x %>% gather(key = Variation,value =Number,-X)
- ggplot(data = svs,aes(x=X,y=Number))+geom_bar(stat = "identity")
- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity")
- p <- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity")
- p + scale_x_discrete(limits=x$X)
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 1,type = 'seq')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 2,type = 'seq')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 2,type = 'div')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 3,type = 'div')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 4,type = 'div')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Set2',type = 'div')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Set1',type = 'div')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Set1')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Blues')
- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity",position='dodge')
- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity",position='dodge2')
- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity",position='fill')
- ggplot(data = svs,aes(x=X,y=Number,fill=Variation))+geom_bar(stat = "identity",position='stack')
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Set1')+
- labs(title ="SV Distribution",x="Chromosome Number",y="SV Numbers") +
- theme(legend.position = 'bottom',plot.title = element_text(hjust = 0.5))
复制代码 ggplot2 绘制基因组 SV 突变堆叠条形图
- p + scale_x_discrete(limits=x$X) + scale_fill_brewer(palette = 'Set1')+
- labs(title ="SV Distribution",x="Chromosome Number",y="SV Numbers") +
- theme(legend.position = 'bottom',plot.title = element_text(hjust = 0.5)) +
- coord_polar() +guides(fill='none')
复制代码
二、饼图
- m <- read.table("Species.txt",sep = '\t',header = FALSE)
- head(m)
- sum(m$V3)
- name <- paste(m[,1],m[,2],'\n',m$V3,'%')
- name
- ggplot(data = m,aes(x = "",y=V3,fill=name))+geom_bar(stat = 'identity') +
- coord_polar(theta = 'y')+guides(fill = 'none')+scale_fill_brewer(palette = 'Set1')
- # y <- paste(m[,1],m[,2])
- # x <- data.frame(name=y,values=m$V3/sum(m$V3))
- # p <- ggplot(data = x,aes(x = "",y=values,fill=name))+geom_bar(stat = "identity",width = 1)+guides(fill='none')
- # p
- # p+coord_polar(theta = 'y')+labs(x = '', y = '', title = '')
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ggplot2 绘制饼图
三、箱线图
- head(ToothGrowth)
- ToothGrowth$dose <- as.factor(ToothGrowth$dose)
- #按提供药物种类分组
- ggplot(data = ToothGrowth,aes(x=supp,y=len,fill=supp))+geom_boxplot()
- #按剂量分组
- ggplot(data = ToothGrowth,aes(x=dose,y=len,group=dose,fill=dose))+geom_boxplot()
- #两组
- ggplot(data = ToothGrowth,aes(x=dose,y=len,group=supp:dose,fill=supp:dose))+geom_boxplot()
- ggplot(data = ToothGrowth,aes(x=dose,y=len,group=supp:dose,fill=supp))+geom_boxplot()
- ggplot(data = ToothGrowth,aes(x=dose,y=len,group=supp:dose,fill=dose))+geom_boxplot()
- ggplot(data = ToothGrowth,aes(x=supp,y=len,group=supp:dose,fill=dose))+geom_boxplot()
- #box图加抖动点
- p<- ggplot(data = ToothGrowth,aes(x=dose,y=len,fill=dose))+geom_boxplot()+
- geom_jitter(width = 0.1)
- p+labs(title = 'ToothGrowth VC vs OJ',x='DOSE',y='Length')+
- scale_fill_brewer(palette = 'Set1') +
- theme(plot.title = element_text(hjust = 0.5)) +
- theme(legend.position = 'bottom')
复制代码
ggplot2 绘制箱线图加抖动的点
- #分面
- ggplot(data = ToothGrowth,aes(x=supp,y=len,group=supp:dose,fill=supp))+geom_boxplot()+
- scale_fill_brewer(palette = 'Set1')+
- facet_grid(~ supp,scales = 'free')
复制代码
ggplot2 绘制分面箱线图
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