Mercurial > repos > greg > ideas
view create_heatmap.R @ 140:17e8829bbae2 draft
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author | greg |
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date | Tue, 19 Dec 2017 12:29:29 -0500 |
parents | 3180393013cc |
children | a976dd6fcd1b |
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#!/usr/bin/env Rscript suppressPackageStartupMessages(library("optparse")) option_list <- list( make_option(c("-i", "--input_dir"), action="store", dest="input_dir", help="IDEAS para files directory"), make_option(c("-o", "--output_dir"), action="store", dest="output_dir", help="PDF output directory") ) parser <- OptionParser(usage="%prog [options] file", option_list=option_list) args <- parse_args(parser, positional_arguments=TRUE) opt <- args$options create_heatmap<-function(data_frame, output_file_name) { # Plot a heatmap for a .para / .state combination # based on the received data_frame which was created # by reading the .para file. num_columns = dim(data_frame)[2]; num_rows = dim(data_frame)[1]; p = (sqrt(9 + 8 * (num_columns-1)) - 3) / 2; data_matrix = as.matrix(data_frame[,1+1:p] / data_frame[,1]); colnames(data_matrix) = colnames(data_frame)[1+1:p]; histone_marks = colnames(data_matrix); rownames(data_matrix) = paste(1:num_rows-1, " (", round(data_frame[,1]/sum(data_frame[,1])*10000)/100, "%)", sep=""); # Open the output PDF file. pdf(file=output_file_name); # Set graphical parameters. par(mar=c(6, 1, 1, 6)); # Create a vector containing the minimum and maximum values in data_matrix. min_max_vector = range(data_matrix); # Create a color palette. my_palette = colorRampPalette(c("white", "dark blue"))(n=100); defpalette = palette(my_palette); # Plot the heatmap for the current .para / .state combination. plot(NA, NA, xlim=c(0, p+0.7), ylim=c(0, num_rows), xaxt="n", yaxt="n", xlab=NA, ylab=NA, frame.plot=F); axis(1, at=1:p-0.5, labels=colnames(data_matrix), las=2); axis(4, at=1:num_rows-0.5, labels=rownames(data_matrix), las=2); color = round((t(data_matrix) - min_max_vector[1]) / (min_max_vector[2] - min_max_vector[1]) * 100); rect(rep(1:p-1, num_rows), rep(1:num_rows-1, each=p), rep(1:p, num_rows), rep(1:num_rows, each=p), col=color); histone_mark_color = t(col2rgb(terrain.colors(ceiling(p))[1:p])); # Specify a color for common feature names like "h3k4me3". # These are histone marks frequently used to identify # promoter activities in a cell, and are often displayed # in shades of red. for(i in 1:length(histone_marks)) { if(regexpr("h3k4me3", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(255, 0, 0); } if(regexpr("h3k4me2", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(250, 100, 0); } if(regexpr("h3k4me1", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(250, 250, 0); } if(regexpr("h3k36me3", tolower(histone_marks[i]))>0) { histone_mark_color[i,] = c(0, 150, 0); } if(regexpr("h2a", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(0, 150, 150); } if(regexpr("dnase", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(0, 200, 200); } if(regexpr("h3k9ac", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(250, 0, 200); } if(regexpr("h3k9me3", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(100, 100, 100); } if(regexpr("h3k27ac", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(250, 150, 0); } if(regexpr("h3k27me3", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(0, 0, 200); } if(regexpr("h3k79me2", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(200, 0, 200); } if(regexpr("h4k20me1", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(50, 200, 50); } if(regexpr("ctcf", tolower(histone_marks[i])) > 0) { histone_mark_color[i,] = c(200, 0, 250); } state_color = get_state_color(data_matrix, histone_mark_color)[,2]; } rect(rep(p+0.2, num_rows), 1:num_rows-0.8, rep(p+0.8, num_rows), 1:num_rows-0.2, col=state_color); palette(defpalette); dev.off(); } get_state_color <- function(data_matrix, histone_mark_color) { range_vector = apply(data_matrix, 1, range); mm = NULL; for(i in 1:dim(data_matrix)[1]) { range_val1 = range_vector[1, i] + 1e-10 range_val2 = range_vector[2, i] mm = rbind(mm, (data_matrix[i,] - range_val1) / (range_val2 - range_val1)); } mm = mm^5; if(dim(mm)[2] > 1) { mm = mm / (apply(mm, 1, sum) + 1e-10); } state_color = mm%*%histone_mark_color; s = apply(data_matrix, 1, max); s = (s - min(s)) / (max(s) - min(s) + 1e-10); state_color = round(255 - (255 - state_color) * s/0.5); state_color[state_color<0] = 0; rt = paste(state_color[,1], state_color[,2], state_color[,3], sep=","); h = t(apply(state_color, 1, function(x){rgb2hsv(x[1], x[2], x[3])})); h = apply(h, 1, function(x){hsv(x[1], x[2], x[3])}); rt = cbind(rt, h); return(rt); } # Read the inputs. para_files <- list.files(path=opt$input_dir, pattern="\\.para$", full.names=TRUE); for (i in 1:length(para_files)) { para_file <- para_files[i]; para_file_base_name <- strsplit(para_file, split="/")[[1]][2] output_file_base_name <- gsub(".para", "", para_file_base_name) output_file_name <- paste(output_file_base_name, "state", i, "pdf", sep=".") output_file_path <- paste(opt$output_dir, output_file_name, sep="/"); data_frame <- read.table(para_file, comment="!", header=T); create_heatmap(data_frame, output_file_path); }