批量运行弦图，封装函数

一共30个样本，要出弦图，先在jupyter里批量运行了PlotFancyVJUsage：

def circos():
    import os
    for i in (1,7,35,189,217):
        for j in (1003,1501,1503,2001,2501,2503):
            x = "day" + str(i) + "-" + str(j)
            print(x)
            cmd_string = "java -jar ./vdjtools-1.2.1.jar PlotFancyVJUsage "+x+".txt "+ x
            print('x：{}'.format(cmd_string))
            print(os.popen(cmd_string).read())
                
circos()

之前是在产生的错误文件（vj_pairing_plot.r）之里修改内容后一个个样本文件进行运行，想到这样太麻烦，就想写成一个函数，变化的是输入文件的名字
输入的文件名称的规律：

代码里输入文件的地方在：

args <- c("day1-2501.fancyvj.wt.txt", "day1-2501.fancyvj.wt.pdf")
temp <- read.table("day1-2501.fancyvj.wt.txt", sep="\t", comment="")

本来这个循环我是写成这样的：

但是要么报这个错

要么报这个错

因为手动输入文件名是可以运行的，所以觉得200G这个不存在……一直在找文件名哪里输的不对
然后改成只运行一个循环，就成功了
可能真的是需要那么多运行内存吧...

circle_plot <- function(){
  for(i in c(1,7,35,189,217)){
      x = paste('day',i,'-2503',sep = "")
      y = '.fancyvj.wt.txt'
      z = '.fancyvj.wt.pdf'
      a = paste(x,y,sep = "")
      b = paste(x,z,sep = "")
      args <- c(a,b)
      #args<-commandArgs(TRUE)
    
      file_in  <- args[1]
      file_out <- args[2]
  
      require(circlize); require(RColorBrewer)

      # load data and preproc to fit formats
    
      temp <- read.table(a, sep="\t", comment="")
      n <- nrow(temp)
      m <- ncol(temp)
      rn = as.character(temp[2:n,1])
      cn = apply(temp[1,2:m], 2 , as.character)
      mat <- matrix(apply(temp[2:n, 2:m], 1:2, as.numeric), n - 1, m-1) * 100
      
      n <- nrow(temp)
      m <- ncol(temp)
      
      # Here columns and rows correspond to V and J segments respectively
      # Also replace possible duplicates (undef, '.', ...)
      
      duplicates <- intersect(rn, cn)
      
      rownames(mat) <- replace(rn, rn==duplicates, paste("V", duplicates, sep=""))
      colnames(mat) <- replace(cn, cn==duplicates, paste("J", duplicates, sep=""))
      
      # sort
      
      col_sum = apply(mat, 2, sum)
      row_sum = apply(mat, 1, sum)
      
      mat <- mat[order(row_sum), order(col_sum)]
      
      # equal number of characters for visualizaiton
      
      rn <- rownames(mat)
      cn <- colnames(mat)
      
      maxrn <- max(nchar(rn))
      maxcn <- max(nchar(cn))
      
      for(i in seq_len(length(rn))) {
            rn[i] <- paste(rn[i], paste(rep(" ", maxrn - nchar(rn[i])), collapse = ''))
      }
      
      for(i in seq_len(length(cn))) {
            cn[i] <- paste(cn[i], paste(rep(" ", maxcn - nchar(cn[i])), collapse = ''))
      }
      
      rownames(mat) <- rn
      colnames(mat) <- cn
      
      # viz using circlize
      
      if (grepl("\\.pdf$",file_out)){
         pdf(file_out)
      } else if (grepl("\\.png$",file_out)) {
         png(file_out, width     = 3.25,
                       height    = 3.25,
                       units     = "in",
                       res       = 1200,
                       pointsize = 4)
      } else {
         stop('Unknown plotting format')
      }
      
      circos.par(gap.degree = c(rep(1, nrow(mat)-1), 10, rep(1, ncol(mat)-1), 15), start.degree = 5)
      
      rcols <- rep(brewer.pal(12, "Paired"), nrow(mat)/12 + 1)[1:nrow(mat)]
      ccols <- rep(brewer.pal(12, "Paired"), ncol(mat)/12 + 1)[1:ncol(mat)]
      
      names(rcols) <- sort(rownames(mat))
      names(ccols) <- sort(colnames(mat))
      
      chordDiagram(mat, annotationTrack = "grid",
                   reduce = 0,
                   grid.col = c(rcols, ccols),
                   preAllocateTracks = list(track.height = 0.2), transparency = 0.5)
      
      circos.trackPlotRegion(track.index = 1, bg.border = NA,
             panel.fun = function(x, y) {
                         sector.name = get.cell.meta.data("sector.index")
                         xlim = get.cell.meta.data("xlim")
                         ylim = get.cell.meta.data("ylim")
                         circos.text(mean(xlim), ylim[1], cex = 0.5, sector.name, facing = "clockwise", adj = c(0, 0.5))
                         }
             )
      
      circos.clear()
      
      dev.off()
    }
}
  
circle_plot()