# 安装R包if (!requireNamespace("VennDiagram", quietly = TRUE))  install.packages("VennDiagram",repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/")if (!requireNamespace("ggplot2", quietly = TRUE))  install.packages("ggplot2",repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/")if (!requireNamespace("venn", quietly = TRUE))  install.packages("venn",repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/")if (!requireNamespace("RColorBrewer", quietly = TRUE))  install.packages("RColorBrewer",repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/")if (!requireNamespace("data.table", quietly = TRUE))  install.packages("data.table",repos = "https://mirrors.tuna.tsinghua.edu.cn/CRAN/")
# 自定义函数## 快速读入数据readFlie=function(input,type,row=T,header=T){  # input 为读入文件的路径，type为读入文件的类型，格式为‘.txt’或‘.csv’,row=T,将文件的第一列设置为列名  library(data.table,quietly = TRUE)  if(type=='txt'){    dat = fread(input,header = header,sep='\t',stringsAsFactors = F,check.names = F)    if(row){      dat = as.data.frame(dat,stringsAsFactors = F)      rownames(dat) = dat[,1]      dat = dat[,-1]    }else{      dat = as.data.frame(dat,stringsAsFactors = F)    }  }else{    dat = fread(input,header = header,sep=',',stringsAsFactors = F,check.names = F)    if(row){      dat = as.data.frame(dat,stringsAsFactors = F)      rownames(dat) = dat[,1]      dat = dat[,-1]    }else{      dat = as.data.frame(dat,stringsAsFactors = F)    }  }  return(dat)}## 绘制venn图wn_venn=function(list,col='black'){  # 定义颜色体系  library(RColorBrewer,quietly = TRUE)  corlor = brewer.pal(8,'Dark2')  # 绘制Venn图  library(VennDiagram, quietly=TRUE)  library(venn,quietly = TRUE)  if(length(list)<=7){    if(length(list)<=4){      graphics=venn.diagram(list,filename=NULL,fill = corlor[1:length(list)],                            col = col,alpha = 0.5, cat.cex = 1.5,rotation.degree = 0)      grid.draw(graphics)    }else if(length(list)==5){      graphics=venn(list, zcolor = corlor[1:length(list)],box=F,ellipse =TRUE,cexil = 1, cexsn = 1)    }else{      graphics=venn(list, zcolor = corlor[1:length(list)],box=F,cexil = 1, cexsn = 1)    }    return(graphics)  }else{    print('The function only supports data of dimension 7 and below.')  }}## 保存图片,只支持ggplot对象savePlots=function(path,plot,type=c('pdf','png','tiff')[1],width=10,height=8,dpi=300){  # path表示保存图片路径,需要加上相应的文件扩展名称  library(ggplot2)  if(type=='pdf'){    ggsave(filename = path,plot = plot,width = width,height = height,device = 'pdf')  }else if(type=='png'){    ggsave(filename = path,plot = plot,width = width,height = height,device = 'png',dpi = dpi)  }else{    ggsave(filename = path,plot = plot,width = width,height = height,device = 'tiff',dpi = dpi)  }}

# 读入数据df = readFlie('./venn.txt',type = 'txt',row = F)# 抽取数据，制造测试数据set.seed(1234)df_list = list('Symbol1'=sample(df$symbol,'Symbol2'=200),'Symbol3'=220),sample(df$symbol,               sample(df$symbol,'Symbol6'=280),'Symbol7'=<span 0px;max-width:="" 1000%;box-sizing:="" border-box="" !important;word-wrap:="" break-word="" !important;color:="" #ca7d37\"="" style="overflow-wrap: break-word; float: none;">sample(df$symbol,300))# 绘制venn图## 4维veen图fg_4 = wn_venn(df_list[1:4])## 5维veen图fg_5 = wn_venn(df_list[1:5])## 7维veen图fg_7 = wn_venn(df_list)# 保存图片savePlots(path = './fg_4.pdf',plot = fg_4,type = 'pdf',width = 10,height = 10)savePlots(path = './fg_4.png',plot = fg_4,type = 'png',width = 10,height = 10,dpi = 300)savePlots(path = './fg_4.tiff',plot = fg_4,type = 'tiff',width = 10,height = 10,dpi = 600)
pdf('./fg5.pdf',width = 10,height = 10)fg_5 = wn_venn(df_list[1:5])dev.off()pdf('./fg7.pdf',width = 10,height = 10)fg_7 = wn_venn(df_list)dev.off()