上游数据示例：

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基因A

data<-read.table("D:/work_tmp/column_diagram_plot/Gene1.percent.txt",header=T,sep="\t")
data$sample=as.character(data$sample)
data$sample=factor(data$sample,levels=c("6","7","9","11","14","17","19","20","22","24","26","27","28"))
pdf("Gene1.VAF.pdf", width=12, height=6)
ggplot(data = data, mapping = aes(x = sample, y =percent,fill=Item)) + geom_bar(stat = 'identity',position="dodge")+xlab('')+ylab('VAF of Gene1')+scale_fill_discrete(name = " ")+ theme(axis.title.x =element_text(size=14))
dev.off()

结果示例：

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基因B

data1<-read.table("D:/work_tmp/column_diagram_plot/Gene2.percent.txt",header=T,sep="\t")
data1$sample=as.character(data1$sample)
data1$sample=factor(data1$sample,levels=c("3","5","8","25"))
pdf("Gene2.VAF.pdf", width=12, height=6)
ggplot(data = data1, mapping = aes(x = sample, y =percent,fill=Item)) + geom_bar(stat = 'identity',position="dodge")+xlab('')+ylab('VAF of Gene2')+scale_fill_discrete(name = " ")+ theme(axis.title.x =element_text(size=14))
dev.off()

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两幅图组合在一起

a<-ggplot(data = data, mapping = aes(x = sample, y =percent,fill=Item)) + geom_bar(stat = 'identity',position="dodge")+xlab('')+ylab('VAF of Gene1')+scale_fill_discrete(name = " ")+ theme(axis.title.x =element_text(size=14)) + guides(fill=FALSE)

b<-ggplot(data = data1, mapping = aes(x = sample, y =percent,fill=Item)) + geom_bar(stat = 'identity',position="dodge")+xlab('')+ylab('VAF of Gene2')+scale_fill_discrete(name = " ")+ theme(axis.title.x =element_text(size=14))

pdf("arrange.EGFR.KRAS.VAF.pdf", width=12, height=6)
ggarrange(a,b,labels = c("B","C"),ncol = 2, nrow = 1)
dev.off()

示例：

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累积柱状图

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data<-read.table("D:/work_tmp/column_diagram_plot/data.txt",header=T,sep="\t")
data$sample=as.character(data$sample)
data$sample=factor(data$sample,levels=c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28"))
 pdf("mutation_statistics.pdf", width=15, height=6)
ggplot(data = data, mapping = aes(x = sample, y =num,fill=Item)) + geom_bar(stat = 'identity')+xlab('')+ylab('Number of sample')+scale_fill_discrete(name = " ")
dev.off()

示例：

image.png

image.png

data<-read.table("STAT",header=T,sep="\t")
data$Group=as.character(data$Group)
pdf("ZT_stat.pdf", width=4, height=4)
ggplot(data = data, mapping = aes(x = Group, y =num,fill=Item)) + geom_bar(stat = 'identity')+xlab('')+ylab('Number of clone')+scale_fill_discrete(name = " ")+ theme_bw(base_size = 13) +theme(panel.grid=element_blank()) + scale_fill_manual(values=c(CTL = "Firebrick4", overlap = "black", PBMC = "MidnightBlue"),name = " ")
dev.off()

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柱状图渐变色

柱状图上标数字

library(ggplot2)
data<-read.table('/lustre/*/project/8_Variation_penetration/1_data/sample_number_per_cancer.txt',header=T)
data$Cancer=factor(data$Cancer,levels=c("LUAD","STAD","NSCL","COAD","RARE","LUSC","READ","PAAD","HNSC","CHOL","BRCA","LIHC","ESCA","OV","SCL","CESC","NASO","SKCM","UCEC","SARC","KICH","GBM","NE","GIST","BLCA","PRAD","THCA","ACC"))
pdf("sample_number_per_cancer.pdf", width=12, height=6)
ggplot(data = data, mapping = aes(x = Cancer, y =SampleNum)) + geom_bar(stat = 'identity',fill="blue")+xlab('Cancer Type')+ylab('Sample Number') +  theme(axis.title.y =element_text(size=14)) +  theme(axis.title.x =element_text(size=14)) +theme(panel.grid.major.x=element_blank(), panel.grid.major.y=element_blank(), axis.text.x=element_text(angle=45, hjust=1))+geom_text(aes(label=SampleNum, y=SampleNum+10), position=position_dodge(0.9), vjust=0,size=30^H)
dev.off()

普通柱状图

上游数据

image.png

pdf("ZT_clone_num.pdf", width=4, height=4)
ggplot(data = data, mapping = aes(x = sample, y =num,fill="Firebrick4")) + geom_bar(stat = 'identity',position="dodge")+xlab('')+ylab('Clone number')+scale_fill_discrete(name = " ") + theme_bw(base_size = 13) +theme(axis.text.x=element_text(angle=45, hjust=1), legend.position="none") + theme(panel.grid=element_blank()) 
dev.off()

示例图

image.png