R/save.html.R

In IPCAPS: Iterative Pruning to Capture Population Structure

#' Generate HTML file for clustering result in text mode
#'
#' @description Generate HTML file called 'tree_text.html' from the result of
#' \code{\link{ipcaps}}. The clustering result is shown as a tree rendering by
#' the online Google Organizational Chart library. Note that the Internet is
#' required to view the HTML file.
#'
#' @param output.dir A result directory as the \code{$output} object returned
#' from the \code{\link{ipcaps}} function.
#'
#' @return \code{NULL}
#'
#' @details After running, this function generates the file called 'tree_text.html' in the
#' same result directory.
#'
#' @export
#'
#' @include output.template.R
#'
#' @seealso \code{\link{save.plots}},
#' \code{\link{save.plots.cluster.html}},
#' \code{\link{save.eigenplots.html}},
#' and \code{\link{save.plots.label.html}}
#'
#' @examples
#'
#' # Importantly, bed file, bim file, and fam file are required
#' # Use the example files embedded in the package
#'
#' BED.file <- system.file("extdata","ipcaps_example.bed",package="IPCAPS")
#' LABEL.file <- system.file("extdata","ipcaps_example_individuals.txt.gz",package="IPCAPS")
#'
#' my.cluster <- ipcaps(bed=BED.file,label.file=LABEL.file,lab.col=2,out=tempdir())
#'
#' #Here, to generate HTML file
#' save.html(my.cluster$output.dir)

save.html <- function(output.dir){

  tree <- NULL
  index <- NULL
  eigen.fit <- NULL
  min.in.group <- NULL
  leaf.node <- NULL
  threshold <- NULL

  load(file.path(output.dir,"RData","leafnode.RData"))
  load(file.path(output.dir,"RData","condition.RData"))
  load(file.path(output.dir,"RData","tree.RData"))
  load(file.path(output.dir,"RData","rawdata.RData"))
  global.label = label
  node.list = sort(tree$node)

  txt_data = ""
  txt_leafnode = ""
  for (i in node.list){
    parent_node = ""
    if (i > 1){
      parent_node = tree$parent.node[which(tree$node == i)]
    }
    PCs.file = file.path(output.dir,"RData",paste0("node",i,".RData"))
    load(PCs.file)
    label = global.label[index]
    list.sum = c()
    u.label = sort(unique(label))
    for (j in 1:length(u.label)){
      co = length(label[label == u.label[j]])
      strlabel = gsub(' ','&nbsp;',u.label[j])
      strout = paste0(strlabel,"&nbsp;(",co,")")
      list.sum = c(list.sum,strout)
    }
    content = ""
    for (s in list.sum){
      content = paste0(content,s,"<br>")
    }
    if (!is.na(eigen.fit)){
      txt_data = paste0(txt_data,"[{v:'",i,"', f:'<div class=\"box_class\"><p class=\"head_class\">Node ",i,"</p><p class=\"subhead_class\">EigenFit= ",sprintf("%.2f",eigen.fit),"</p><br>",content,"</div>'}, '",parent_node,"', '']")
    }else{
      txt_data = paste0(txt_data,"[{v:'",i,"', f:'<div class=\"box_class\"><p class=\"head_class\">Node ",i,"</p><p class=\"subhead_class\">under cutoff (<",min.in.group,")</p><br>",content,"</div>'}, '",parent_node,"', '']")
    }
    if (!(i == node.list[length(node.list)])){
      txt_data = paste0(txt_data,",\n")
    }else{
      txt_data = paste0(txt_data,"\n")
    }

    no_idx = which(i == node.list) - 1
    if (i %in% leaf.node){
      txt_leafnode = paste0(txt_leafnode,"data.setRowProperty(",no_idx,", 'style', 'border: 3px solid #DB6E6E; background-color:#FFE1E1');\n")
    }
  }

  txt_title = "The result of IPCAPS"
  txt_body = paste0("The result of IPCAPS (threshold= ",threshold,")")

  txt_html = output.template$template
  txt_html[output.template$lno_data] = txt_data
  txt_html[output.template$lno_leafnode] = txt_leafnode
  txt_html[output.template$lno_body] = txt_body
  txt_html[output.template$lno_title] = txt_title

  fo = file(file.path(output.dir,"tree_text.html"),"w")
  for (i in txt_html){ write(i,fo)}
  close(fo)

  invisible(NULL)
}