p<-ggplot(data, aes(x = surstat, y = gene39)) # x分组变量,y表达变量 p+geom_violin() #画出violin plot p+geom_violin(aes(fill = surstat)) #按组别填充颜色 violin 1.2 修改参数美化图: P<- ggplot(data, aes(x = surstat, y = gene39, fill=surstat)) + rotate_x_text(angle = ...
# 带点小提琴图geom_dotplot(),geom_jitter() # violin plot with dot plot p10 <- p7 + geom_dotplot(binaxis='y', stackdir='center', dotsize=1) # violin plot with jittered points # 0.2 : degree of jitter in x direction p11 <- p7 + geom_jitter(shape=16, position=position_jitter...
Dots (or points) can be added to a violin plot using the functionsgeom_dotplot()orgeom_jitter(): # violin plot with dot plot p + geom_dotplot(binaxis='y', stackdir='center', dotsize=1) # violin plot with jittered points # 0.2 : degree of jitter in x direction p + ...
R语言中，ggplot2可以用来绘制直观的小提琴图（violin plot），便于理解数据分布和差异。首先，确保数据中'surstat'列为factor类型，便于分析。1. 单个“两组”图绘制 以gene39为例，可以先尝试默认参数绘制，然后根据需要调整美观，如添加p值。利用ggpubr包可方便地插入p值，并用星号形式表示。 2....
geom_flat_violin()+coord_flip()+ theme(legend.position="none") 输出: 示例4:水平半小提琴图,旁边有抖动的数据点 让我们来绘制一个半小提琴图以及抖动点。 R实现 # half violin plot with jittered points ggplot(df,aes(cut,x,fill=cut))+ ...
geom_violin(scale="width") + geom_boxplot(width=.12, fill=I("black"), notch=T, outlier.size=NA, col="grey40") + stat_summary(fun="median", geom="point", shape=20, col="white") + #scale_y_log10(breaks=c(1:5, seq(10, 50, by=10), 100, 200, 300)) + ...
title="Scatterplot with overlapping points", caption="Source: midwest") 上图中其实有很多点是重合的 原始数据是整数 1 dim(mpg) 用jitter_geom()画抖动图 重合的点在原先的位置基于一定阈值范围(width)随机抖动 1 2 3 4 5 6 7 8 9 10 11 12 library(ggplot2) data(mpg, package="ggplot2")...
1、边界散点图(Scatterplot With Encircling) options(scipen = 999) library(ggplot2) library(ggalt) midwest_select <- midwest[midwest$poptotal > 350000 & midwest$poptotal <= 500000 & midwest$area > 0.01 & midwest$area < 0.1, ] # Plot ...
1.2 带边界的散点图(Scatterplot With Encircling) 1.3 抖动图(Jitter Plot) 1.4 计数图(Counts Chart) 1.5 气泡图(Bubble Plot) 1.6 边际直方图/箱线图(Marginal Histogram / Boxplot) ...
· Key function: geom_violin() · Alternative function: stat_ydensity() · Key arguments to customize the plot: alpha, color, linetype, size and fill. #基础e+ geom_violin()#旋转e+ geom_violin() + coord_flip()#不修剪小提琴的尾部e+ geom_violin(trim = FALSE, fill = "steelblue") ...