#' Generate HTML file for scatter plots which all data points are highlighted by IPCAPS clusters #' #' @description Generate HTML file called 'tree_scatter_cluster.html' from the #' result of \code{\link{ipcaps}}. This function is a part of workflow in #' \code{\link{save.plots}}. 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{$output} object returned #' from the \code{\link{ipcaps}} function. #' #' @return \code{NULL} #' #' @details After running, this function generates the file called 'tree_scatter_cluster.html' #' in the same result directory. All plots are generated and saved as image files #' in the sub-directory 'images'. #' #' @export #' #' @include output.template.R #' #' @seealso \code{\link{save.html}}, #' \code{\link{save.plots}}, #' \code{\link{save.eigenplots.html}}, #' and \code{\link{save.plots.label.html}} #' #' @examples #' #' # Importantly, bed file, bim file, and fam file are required #' # Use the example files embedded in the package #' #' BED.file <- system.file("extdata","ipcaps_example.bed",package="IPCAPS") #' LABEL.file <- system.file("extdata","ipcaps_example_individuals.txt.gz",package="IPCAPS") #' #' my.cluster <- ipcaps(bed=BED.file,label.file=LABEL.file,lab.col=2,out=tempdir()) #' #' #Here, to generate HTML file #' save.plots.cluster.html(my.cluster$output.dir) save.plots.cluster.html <- function(output.dir){ tree <- NULL label <- NULL min.in.group <- NULL leaf.node <- NULL load(file.path(output.dir,"RData","leafnode.RData")) load(file.path(output.dir,"RData","tree.RData")) load(file.path(output.dir,"RData","condition.RData")) node.list = sort(tree$node) txt_data = "" txt_leafnode = "" test.dir=file.path(output.dir,"images.new") img.dir="images" if (file.exists(test.dir)){ img.dir="images.new" } for (i in node.list){ parent_node = "" if (i > 1){ parent_node = tree$parent.node[which(tree$node == i)] } PCs.file = file.path(output.dir,"RData",paste0("node",i,".RData")) load(PCs.file) list.sum = c() u.label = sort(unique(label)) for (j in 1:length(u.label)){ co = length(label[label == u.label[j]]) strout = paste0(u.label[j]," (",co,")") list.sum = c(list.sum,strout) } content = "" for (s in list.sum){ content = paste0(content,s,"
") } if (file.exists(file.path(output.dir,"images",paste0("scatterplot_preview",i,".jpg")))){ txt_data = paste0(txt_data,"[{v:'",i,"', f:'

Node ",i,"


view
'}, '",parent_node,"', '']") }else if (file.exists(file.path(output.dir,"images",paste0("scatterplot_preview",i,".pdf")))){ txt_data = paste0(txt_data,"[{v:'",i,"', f:'

Node ",i,"


view
'}, '",parent_node,"', '']") }else{ txt_data = paste0(txt_data,"[{v:'",i,"', f:'

Node ",i,"

under cutoff (<",min.in.group,")


",content,"
'}, '",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 = "Scatter plots colored by IPCAPS result" txt_body = "Scatter plots colored by IPCAPS result" 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_scatter_cluster.html"),"w") for (i in txt_html){ write(i,fo)} close(fo) invisible(NULL) }