*R-ggplot绘图汇总

箱图geom_boxplot

例子数据格式

name value
A 3.248795062
A 12.71400397
B 12.46654939
B 12.62122515
C 27.32492551
C 28.30969191
D 10.21093023
D 10.63176794

太长不写

# 基础箱图
p<-ggplot(data, aes(x=name, y=value)) + geom_boxplot()
# 90度旋转
p + coord_flip()
# 缺口式
ggplot(data, aes(x=name, y=value)) + geom_boxplot(notch=TRUE)
# 改变outlier的样式,颜色等
ggplot(data,aes(x=name,y=value,color=name)) + geom_boxplot(outlier.colour="red", outlier.shape=8, outlier.size=4)
# 使用stat_summary给箱添加均值
p + stat_summary(fun.y=mean, geom="point", shape=23, size=4)
# 自定义选择要展示的组
p + scale_x_discrete(limits=c("A", "D"))
# 使用geom_dotplot()或geom_jitter() 增加箱上的点
p + geom_dotplot(binaxis='y', stackdir='center', dotsize=1)
p + geom_jitter(shape=16, position=position_jitter(0.2))
0.2 : degree of jitter in x direction

# 改变颜色,改变外周颜色
p1<-ggplot(x=name,y=value,color=name)) + geom_boxplot()
也可以使用其他function改变颜色
to use custom colors: p1+scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))
to use color palettes from RColorBrewer package: p1+scale_color_brewer(palette="Dark2")
to use grey color palettes: p1 scale_color_grey() + theme_classic()
# 改变颜色,改变填充颜色
单色
ggplot(data, aes(x=name,y=value,fill=name)) + geom_boxplot(fill='#A4A4A4', color="black")+
按组分色
p2<-ggplot(data,(x=name,y=value,fill=name)) + geom_boxplot()
也可以用function改变颜色
p+scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))
p+scale_fill_brewer(palette="Dark2")
p + scale_fill_grey() + theme_classic()
# 改变legend位置
p + theme(legend.position="top")
p + theme(legend.position="bottom")
p + theme(legend.position="none") # Remove legend
# 改变排列顺序,使用scale_x_discrete
p + scale_x_discrete(limits=c("D","C","B","A"))

# 画多组箱
改变组的颜色
ggplot(ToothGrowth, aes(x=dose, y=len, fill=supp)) + geom_boxplot()
改变组的位置
p<-ggplot(ToothGrowth, aes(x=dose, y=len, fill=supp)) + geom_boxplot(position=position_dodge(1))
# 加点,改变点颜色
p + geom_dotplot(binaxis='y', stackdir='center', position=position_dodge(1))
p + scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))

#边框,背景
# 去掉背景,黑框框起来
p+theme(panel.background=element_blank(),panel.border=element_rect(linetype="solid",fill=NA))
# 横纵坐标字体和大小
p+theme(axis.text=element_text(size=10,color="black"),axis.title=element_text(size=12,face="bold",color="black"))

#小提琴或箱图+散点(抖动)

data=read.table("file.txt",header=T)
head(data)
Value  Class  Group
111   GP1  pseudo
222  GP1  pseudo
333  CTRL  pseudo
444  GP1  live
555  CTRL live
data$Class=factor(data$Class,levels=c("GP1","CTRL"))
df1=subset(data,Class=="CTRL")
df2=subset(data,Class=="GP1")
ggplot(data,aes(x=Group,y=Value)) +
  geom_violin(draw_quantiles=c(0.25,0.5,0.75)) +
  geom_boxplot(width=0.3) +
  geom_point(data=df1,aes(fill=Class),position=position_jitterdodge(jitter.width=0,jitter.height=0.5,dodge.width=0),shape=21,size=2) +
  geom_point(data=df2,aes(fill=Class),position=position_jitterdodge(jitter.width=2,jitter.height=0.5,dodge.width=0),shape=21,size=2) +
  scale_fill_manual(values=c("#CCCCCC","#3F9BFF")) +
  theme(axis.text=element_text(color="black"),panel.background=element_blank(),panel.border=element_rect(fill="NA",color="black")) +
  xlab("") + ylab("")

柱图geom_bar

堆叠柱图

library(ggplot2)
data=read.table("5-AMR_class.txt",sep="\t",header=T)
ggplot(data,aes(x=ID1,y=Ratio,fill=Class1))+
  geom_bar(stat="identity",position="stack",width=0.6)+
  facet_grid(.~ID2,scales="free",space="free_x")+
 theme_bw()+theme(legend.title=element_blank(),plot.title=element_text(size=12,face="bold",vjust=0.5,hjust=0.5),axis.text=element_text(face="bold"))+
  scale_fill_manual(values=c("#A69ADC","#617F2E","#8EC9CE","#C74F7F","#6F42AF","#A5EAA4","#7D3E2F","#4E2B53","#D14A33","#8242B5","#8DCE2A","#D5B8A7","#C457B3","#D8D34B","#CC8C39","#3D433B"))+
  labs(x="",y="Relative abundance")

做统计

library(ggplot2)
library(ggpubr)
data=read.table("2-group_rank_revised.txt",header=T,sep="\t")
my_comparisons=list(c("group1","group4"),c("group2","group4"),c("group3","group4"),c("group5","group4"))
ggplot(data,aes(x=Group,y=inClass,fill=Group)) + geom_violin() + geom_jitter(height=0,width=0.1) +
  stat_compare_means(comparisons=my_comparisons)
ggplot(data,aes(x=Group,y=Range,fill=Group)) + geom_violin() + geom_jitter(height=0,width=0.1) +
  stat_compare_means(comparisons=my_comparisons)

data=read.table("2-noSymptom_78p_rank_revised.txt",header=T,sep="\t")
ggplot(data,aes(x=factor(inClass),y=Range,fill=factor(inClass))) + geom_violin() + geom_jitter(height=0,width=0.1) +
  stat_compare_means()

详细请参考:
https://www.jianshu.com/p/b7274afff14f?from=timeline

R-连线图geom_segment geom_curve

geom_segment(data=d, mapping=aes(x=x,y=y,xend=xend,yend=yend), arrow=arrow(length=unit(0.2,"cm")), size=2, color="blue") 
geom_curve(aes(x = x1, y = y1, xend = x2, yend = y2, colour = "curve"), data = df)

饼图饼图geom_bar

data=read.table("7-stat.txt",header=T,sep="\t")
data=subset(data,Class=="Class")
ggplot(data,aes(x="",y=Count/Total,fill=Value)) +
  geom_bar(stat="identity",width=0.5,position="stack") +
  coord_polar(theta="y",start=0) +
  scale_fill_manual(values=c("#FFCCCC","#FFCC66","#FF6633","#FF0066")) +
  theme(panel.border=element_rect(color="black",fill=NA)) +
  theme(panel.background=element_blank()) + facet_wrap(Clade~.) +
  xlab("") + ylab("") +ggtitle("Classes in clades")

详细内容请参考:
https://www.jianshu.com/p/8b66e0be3e70

ggplot一些细节修改

1. 添加一条参考线

geom_hline(yintercept=50,color="red",linetype="dashed")
geom_vline(xintercept=30)
...
geom_hline(aes(yintercept=wt,colour=wt),mean_wt)

2. 去掉背景灰色,加黑色边框

theme(panel.background=element_blank())
theme(panel.border=element_rect(fill="NA",color="black"))

3. 坐标轴显示,最大最小和手动间隔

scale_x_continuous(limits=c(1,30000))
scale_x_continuous(breaks=c("1","10000","20000","30000"))
scale_x_continuous(label=c("1","10K","20K","30K"))

4. 多个pheatmap一起输出

p1=pheatmap(d1)
p2=pheatmap(d2)
p3=pheatmap(d3)
p4=pheatmap(d4)
g1=as.ggplot(p1)
g2=as.ggplot(p2)
g3=as.ggplot(p3)
g4=as.ggplot(p4)
cowplot::plot_grid(g1, g2, g3,g4,ncol=2)

散点图

散点图,坐标轴上打点

ID Cell Trend FC1 FC2 Flag
ENSMUSG00000079499.9 G1 FU 0.107703308675386 2.27327271386235 Lable
ENSMUSG00000097195.9 G2 FU 0.0931022969618995 1.55652034686497 NO
ENSMUSG00000103041.1 G3 FU 0.737337372929388 1.27351982599697 NO
ENSMUSG00000024845.17 G1 FU 0.624131572941305 1.32170094722654 Lable
ENSMUSG00000085227.1 G2 FU -0.0780060190505009 2.33854218716707 NO
ENSMUSG00000100182.6 G3 FU -0.242821120121383 1.0630250363417 NO
ENSMUSG00000087593.1 G1 FU 0.523572061612209 1.15169763513402 NO
ENSMUSG00000022639.14 G2 FF -0.69059564946632 -0.437309491202036 NO

分组,并标出想标的ID

library(ggplot2)
data=read.table("test.txt",header=T)
ggplot(data,aes(x=FC1,y=FC2,colour=Trend,label=ID))+geom_point(size=2,alpha=.6)+
  geom_text(aes(label=ifelse(Flag=="Lable",as.character(ID),'')),hjust=0,vjust=0)+
  scale_colour_manual(values=c("#0066CC","#99CCFF","#FFCC00","#99CCFF","#D1D1CF","#FFCCFF","#FFCC00","#FFCCFF","#FF3300"))+
  scale_fill_manual(values=c("#0066CC","#99CCFF","#FFCC00","#99CCFF","#D1D1CF","#FFCCFF","#FFCC00","#FFCCFF","#FF3300"))+
  facet_grid(Cell~.)+xlab("x axis")+ylab("y axis")
#############
library(ggplot2)
data=read.table("test.txt",header=T)
ggplot(data,aes(x=FC1,y=FC2,colour=Trend,label=ID))+geom_point(size=2,alpha=.6)+
  geom_text(data=subset(data,Flag=="Lable"),hjust=0,vjust=0)+
  scale_colour_manual(values=c("#0066CC","#99CCFF","#FFCC00","#99CCFF","#D1D1CF","#FFCCFF","#FFCC00","#FFCCFF","#FF3300"))+
  scale_fill_manual(values=c("#0066CC","#99CCFF","#FFCC00","#99CCFF","#D1D1CF","#FFCCFF","#FFCC00","#FFCCFF","#FF3300"))+
  facet_grid(Cell~.)+xlab("x axis")+ylab("y axis")
#############

修改点的形状

show_point_shapes() #显示点的形状(ggpubr包内的函数)
scale_shape_manual(values = c(15, 19, 17)) + #自定义点的形状,分别为15, 19, 17

其他参数可参考的:
https://www.lizenghai.com/archives/22371.html

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