在现有的条形图和第二个y轴上添加一条线
我是R的新手，而且堆栈溢出，所以请多多包涵。这里没有其他问题可以有效地解决我的问题。
为清楚起见，请参见下文。
# This generates the barplot
df<-data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Germline=c(34,33,14,22,12),Somatic_5_15=c(341,331,281,249,147),Somatic_15_30=c(180,176,129,124,108))
df$name<-row.names(df)
df_molten<-melt(df)
df_molten$name <-factor(df_molten$name,
levels = c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"))
ggplot(df_molten,aes(x=name,y=value,fill=variable))+
geom_bar(stat='identity')+
scale_fill_discrete(labels=c("Germline","Somatic 5-15% VAF","Somatic 15-30% VAF"))+
geom_text(aes(label=value),size=3,fontface='bold',position=position_stack(vjust=.5))+
xlab("Panel")+
ylab("Counts")+
theme_bw()+
theme(panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
panel.background=element_blank(),
axis.line=element_line(colour="black"),
panel.border=element_blank(),
legend.title=element_blank())
# The second set of data for the percent targets are as follows, and this needs to form the line graph and be compared to the Y axis on the right:
df1 <- data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Percent_targeted=c(100,100,77,73,49))
1 个答案:
答案 0 :(得分：1)
修改3：
对不起，刚才看到了你的草图...
使用let mainDict:[String:Array] = ["MainDictionary": myArray]和geom_point()创建线和点。向geom_line()添加一个数字（在本示例中为1），使点和线相对于条形移动。更改此设置，直到您拥有自己的职位为止。
使用Percent_targeted_scaled中的size和geom_point()中的lwd创建合适的点大小和线宽。
geom_line() 
编辑2：
要获取点（或标签）的百分比，请使用重新缩放的百分比值，如y美学：
library(ggplot2)
library(reshape2)
library(scales)
df<-data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Germline=c(34,33,14,22,12),Somatic_5_15=c(341,331,281,249,147),Somatic_15_30=c(180,176,129,124,108))
df$name<-row.names(df)
df_molten<-melt(df)
df_molten$name<-factor(df_molten$name,levels=c('AcroMetrix','PV1_PV2','CHIPv2','TSACP','TSTP'))
df_molten$Percent_targeted <- unlist(lapply(1:length(levels(df_molten$variable)), function(i){c(100,100,77,73,49)}))
# counts <- df_molten %>% group_by(name) %>% summarise(sum=round(sum(value)))
# df_molten$Percent_targeted <- round(unlist(lapply(1:length(levels(df_molten$variable)), function(i){counts$sum/counts$sum[1]})), 2)*100
gg <- ggplot(df_molten,aes(x=name,y=value,fill=variable))+
geom_bar(stat='identity', width=.6)+
scale_fill_discrete(labels=c("Germline","Somatic 5-15% VAF","Somatic 15-30% VAF"))+
geom_text(aes(label=value),size=3,fontface='bold',position=position_stack(vjust=.5))+
xlab("Panel")+ylab("Counts")+
theme_bw()+
theme(panel.grid.major=element_blank(),panel.grid.minor=element_blank(),panel.background=element_blank(),axis.line=element_line(colour="black"),panel.border=element_blank(),legend.title=element_blank())
gg <- gg + scale_y_continuous(expand = expand_scale(mult=c(0, 0.0)))
# get the sacle values of the current y-axis
gb <- ggplot_build(gg)
y.range <- gb$layout$panel_params[[1]]$y.range
y2.range <- range(df_molten$Percent_targeted)# extendrange(, f=0.01)
scale_factor <- (diff(y.range)/max(y2.range))
trans <- ~ ((. -y.range[1])/scale_factor)
df_molten$Percent_targeted_scaled <- rescale(df_molten$Percent_targeted, y.range, c(0, y2.range[2]))
df_molten$x <- which(levels(df_molten$name)%in%df_molten$name)#-.3
# gg <- gg + geom_segment(aes(x=x, xend=x, yend=Percent_targeted_scaled), y=0, size=2, data=df_molten)
# gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten)
# gg <- gg + geom_hline(yintercept = y.range[2], linetype='longdash')
# gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten, vjust=0)
gg <- gg + geom_point(aes(x=x, y=Percent_targeted_scaled+2), data=df_molten, show.legend = F, size=3)
gg <- gg + geom_line(aes(x=x, y=Percent_targeted_scaled+2), data=df_molten, lwd=1.5)
gg <- gg + scale_y_continuous(expand=expand_scale(mult=c(.05, .05)), sec.axis = sec_axis(trans, name = paste0("Percent genes targeted on ", levels(df_molten$name)[1]), labels = scales::percent(seq(0, 1, length.out = 5), scale=100)))
gg
编辑：
我知道我们的目标是使水平线达到100％，这与library(ggplot2)
library(reshape2)
library(scales)
df<-data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Germline=c(34,33,14,22,12),Somatic_5_15=c(341,331,281,249,147),Somatic_15_30=c(180,176,129,124,108))
df$name<-row.names(df)
df_molten<-melt(df)
df_molten$name<-factor(df_molten$name,levels=c('AcroMetrix','PV1_PV2','CHIPv2','TSACP','TSTP'))
df_molten$Percent_targeted <- unlist(lapply(1:length(levels(df_molten$variable)), function(i){c(100,100,77,73,49)}))
gg <- ggplot(df_molten,aes(x=name,y=value,fill=variable))+
geom_bar(stat='identity', width=.6)+
scale_fill_discrete(labels=c("Germline","Somatic 5-15% VAF","Somatic 15-30% VAF"))+
geom_text(aes(label=value),size=3,fontface='bold',position=position_stack(vjust=.5))+
xlab("Panel")+ylab("Counts")+
theme_bw()+
theme(panel.grid.major=element_blank(),panel.grid.minor=element_blank(),panel.background=element_blank(),axis.line=element_line(colour="black"),panel.border=element_blank(),legend.title=element_blank())
gg <- gg + scale_y_continuous(expand = expand_scale(mult=c(0, 0.0)))
# get the sacle values of the current y-axis
gb <- ggplot_build(gg)
y.range <- gb$layout$panel_params[[1]]$y.range
y2.range <- range(df_molten$Percent_targeted)# extendrange(, f=0.01)
scale_factor <- (diff(y.range)/max(y2.range))
trans <- ~ ((. -y.range[1])/scale_factor)
df_molten$Percent_targeted_scaled <- rescale(df_molten$Percent_targeted, y.range, c(0, y2.range[2]))
df_molten$x <- which(levels(df_molten$name)%in%df_molten$name)#-.3
# gg <- gg + geom_segment(aes(x=x, xend=x, yend=Percent_targeted_scaled), y=0, size=2, data=df_molten)
# gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten)
gg <- gg + geom_hline(yintercept = y.range[2], linetype='longdash')
gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten, vjust=0)
gg <- gg + scale_y_continuous(expand=expand_scale(mult=c(.05, .05)), sec.axis = sec_axis(trans, name = paste0("Percent genes targeted on ", levels(df_molten$name)[1]), labels = scales::percent(seq(0, 1, length.out = 5), scale=100)))
gg
上的最大值相对应。
所以你的意思是这样的吗？
AcroMetrix 
原始答案：
根据您提供的数据，在我看来，每个面板上的100％都不相同。
但是，您可以这样执行请求：
library(ggplot2)
library(reshape2)
library(scales)
df<-data.frame(row.names=c("AcroMetrix","PV1_PV2","CHIPv2","TSACP","TSTP"),Germline=c(34,33,14,22,12),Somatic_5_15=c(341,331,281,249,147),Somatic_15_30=c(180,176,129,124,108))
df$name<-row.names(df)
df_molten<-melt(df)
df_molten$name<-factor(df_molten$name,levels=c('AcroMetrix','PV1_PV2','CHIPv2','TSACP','TSTP'))
df_molten$Percent_targeted <- unlist(lapply(1:length(levels(df_molten$variable)), function(i){c(100,100,77,73,49)}))
gg <- ggplot(df_molten,aes(x=name,y=value,fill=variable))+
geom_bar(stat='identity', width=.6)+
scale_fill_discrete(labels=c("Germline","Somatic 5-15% VAF","Somatic 15-30% VAF"))+
geom_text(aes(label=value),size=3,fontface='bold',position=position_stack(vjust=.5))+
xlab("Panel")+ylab("Counts")+
theme_bw()+
theme(panel.grid.major=element_blank(),panel.grid.minor=element_blank(),panel.background=element_blank(),axis.line=element_line(colour="black"),panel.border=element_blank(),legend.title=element_blank())
gg <- gg + scale_y_continuous(expand = expand_scale(mult=c(0, 0.0)))
# get the sacle values of the current y-axis
gb <- ggplot_build(gg)
y.range <- gb$layout$panel_params[[1]]$y.range
y2.range <- range(df_molten$Percent_targeted)# extendrange(, f=0.01)
scale_factor <- (diff(y.range)/max(y2.range))
trans <- ~ ((. -y.range[1])/scale_factor)
df_molten$Percent_targeted_scaled <- rescale(df_molten$Percent_targeted, y.range, c(0, y2.range[2]))
df_molten$x <- which(levels(df_molten$name)%in%df_molten$name)#-.3
# gg <- gg + geom_segment(aes(x=x, xend=x, yend=Percent_targeted_scaled), y=0, size=2, data=df_molten)
# gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=Percent_targeted_scaled), fill='white', data=df_molten)
gg <- gg + geom_hline(yintercept = y.range[2], linetype='longdash')
gg <- gg + geom_label(aes(label=paste0(Percent_targeted, '%'), x=x, y=y.range[2]+5), fill='white', data=df_molten, vjust=0)
gg <- gg + scale_y_continuous(expand=expand_scale(mult=c(.05, .05)), sec.axis = sec_axis(trans, name = paste0("Percent genes targeted on ", levels(df_molten$name)[1]), labels = scales::percent(seq(0, 1, length.out = 5), scale=100)))
gg
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