--- a/execute_dwt_var_perClass.pl	Mon Jan 27 09:26:11 2014 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,320 +0,0 @@
-#!/usr/bin/perl -w
-
-use warnings;
-use IO::Handle;
-use POSIX qw(floor ceil);
-
-# example: perl execute_dwt_var_perClass.pl hg18_NCNR_10bp_3flanks_deletionHotspot_data_del.txt deletionHotspot 3flanks del
-
-$usage = "execute_dwt_var_perClass.pl [TABULAR.in] [TABULAR.out] [TABULAR.out] [PDF.out] \n";
-die $usage unless @ARGV == 4;
-
-#get the input arguments
-my $inputFile = $ARGV[0];
-my $firstOutputFile = $ARGV[1];
-my $secondOutputFile = $ARGV[2];
-my $thirdOutputFile = $ARGV[3];
-
-open (INPUT, "<", $inputFile) || die("Could not open file $inputFile \n");
-open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
-open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \n");
-open (OUTPUT3, ">", $thirdOutputFile) || die("Could not open file $thirdOutputFile \n");
-open (ERROR,  ">", "error.txt")  or die ("Could not open file error.txt \n");
-
-#save all error messages into the error file $errorFile using the error file handle ERROR
-STDERR -> fdopen( \*ERROR,  "w" ) or die ("Could not direct errors to the error file error.txt \n");
-
-# choosing meaningful names for the output files
-$max_dwt = $firstOutputFile; 
-$pvalue = $secondOutputFile; 
-$pdf = $thirdOutputFile; 
-
-# count the number of columns in the input file
-while($buffer = <INPUT>){
-	#if ($buffer =~ m/interval/){
-		chomp($buffer);
-		$buffer =~ s/^#\s*//;
-		@contrl = split(/\t/, $buffer);
-		last;
-	#}
-}
-print "The number of columns in the input file is: " . (@contrl) . "\n";
-print "\n";
-
-# count the number of motifs in the input file
-$count = 0;
-for ($i = 0; $i < @contrl; $i++){
-	$count++;
-	print "# $contrl[$i]\n";
-}
-print "The number of motifs in the input file is:  $count \n";
-
-# check if the number of motifs is not a multiple of 12, and round up is so
-$count2 = ($count/12);
-if ($count2 =~ m/(\D)/){
-	print "the number of motifs is not a multiple of 12 \n";
-	$count2 = ceil($count2);
-}
-else {
-	print "the number of motifs is a multiple of 12 \n";
-}
-print "There will be $count2 subfiles\n\n";
-
-# split infile into subfiles only 12 motif per file for R plotting
-for ($x = 1; $x <= $count2; $x++){
-	$a = (($x - 1) * 12 + 1);
-	$b = $x * 12;
-	
-	if ($x < $count2){
-		print "# data.short $x <- data_test[, +c($a:$b)]; \n"; 
-	}
-	else{
-		print "# data.short $x <- data_test[, +c($a:ncol(data_test)]; \n";
-	}
-}
-
-print "\n";
-print "There are 4 output files: \n";
-print "The first output file is a pdf file\n";
-print "The second output file is a max_dwt file\n";
-print "The third output file is a pvalues file\n";
-print "The fourth output file is a test_final_pvalues file\n";
-
-# write R script
-$r_script = "get_dwt_varPermut_getMax.r"; 
-print "The R file name is: $r_script \n";
-
-open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
-
-print Rcmd "
-	######################################################################
-	# plot power spectra, i.e. wavelet variance by class
-	# add code to create null bands by permuting the original data series
-	# get class of maximum significant variance per feature
-	# generate plots and table matrix of variance including p-values
-	######################################################################
-	library(\"Rwave\");
-	library(\"wavethresh\");
-	library(\"waveslim\");
-
-	options(echo = FALSE)
-
-	# normalize data
-	norm <- function(data){
-		v <- (data-mean(data))/sd(data);
-    	if(sum(is.na(v)) >= 1){
-    		v<-data;
-    	}
-    	return(v);
-	}
-
-	dwt_var_permut_getMax <- function(data, names, filter = 4, bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
-		max_var = NULL;
-    	matrix = NULL;
-		title = NULL;
-    	final_pvalue = NULL;
-		short.levels = NULL;
-		scale = NULL;
-	
-    	print(names);
-    	
-   	 	par(mfcol = c(length(names), length(names)), mar = c(0, 0, 0, 0), oma = c(4, 3, 3, 2), xaxt = \"s\", cex = 1, las = 1);
-   	 	
-    	short.levels <- wd(data[, 1], filter.number = filter, bc = bc)\$nlevels;
-    	
-    	title <- c(\"motif\");
-    	for (i in 1:short.levels){
-    		title <- c(title, paste(i, \"var\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"), paste(i, \"test\", sep = \"_\"));
-    	}
-    	print(title);
-        
-		# normalize the raw data
-    	data<-apply(data,2,norm);
-
-    	for(i in 1:length(names)){
-    		for(j in 1:length(names)){
-				temp = NULL;
-				results = NULL;
-				wave1.dwt = NULL;
-				out = NULL;
-				
-				out <- vector(length = length(title));
-            	temp <- vector(length = short.levels);
-            	
-            	if(i < j) {
-            		plot(temp, type = \"n\", axes = FALSE, xlab = NA, ylab = NA);
-                	box(col = \"grey\"); 
-                	grid(ny = 0, nx = NULL);
-            	} else {
-            		if (i > j){
-                		plot(temp, type = \"n\", axes = FALSE, xlab = NA, ylab = NA);
-                    	box(col = \"grey\"); 
-                    	grid(ny = 0, nx = NULL);
-                 	} else {
-                 	
-                 		wave1.dwt <- dwt(data[, i], wf = wf, short.levels, boundary = boundary); 
-                		
-                		temp_row = (short.levels + 1 ) * -1;
-                		temp_col = 1;
-                    	temp <- wave.variance(wave1.dwt)[temp_row, temp_col];
-
-                    	#permutations code :
-                    	feature1 = NULL;
-						null = NULL;
-						var_25 = NULL;
-						var_975 = NULL;
-						med = NULL;
-
-                    	feature1 = data[, i];
-                    	for (k in 1:1000) {
-							nk_1 = NULL;
-							null.levels = NULL;
-							var = NULL;
-							null_wave1 = NULL;
-
-                        	nk_1 = sample(feature1, length(feature1), replace = FALSE);
-                        	null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
-                        	var <- vector(length = length(null.levels));
-                        	null_wave1 <- dwt(nk_1, wf = wf, short.levels, boundary = boundary);
-                        	var<- wave.variance(null_wave1)[-8, 1];
-                        	null= rbind(null, var);
-                    	}
-                    	null <- apply(null, 2, sort, na.last = TRUE);
-                    	var_25 <- null[25, ];
-                    	var_975 <- null[975, ];
-                    	med <- (apply(null, 2, median, na.rm = TRUE));
-
-                    	# plot
-                    	results <- cbind(temp, var_25, var_975);
-                    	matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), axes = F);
-
-                    	# get pvalues by comparison to null distribution
-                    	out <- (names[i]);
-                    	for (m in 1:length(temp)){
-                    		print(paste(\"scale\", m, sep = \" \"));
-                        	print(paste(\"var\", temp[m], sep = \" \"));
-                        	print(paste(\"med\", med[m], sep = \" \"));
-                        	pv = tail = NULL;
-							out <- c(out, format(temp[m], digits = 3));	
-                        	if (temp[m] >= med[m]){
-                        		# R tail test
-                            	print(\"R\");
-	                        	tail <- \"R\";
-                            	pv <- (length(which(null[, m] >= temp[m])))/(length(na.exclude(null[, m])));
-
-                        	} else {
-                        		if (temp[m] < med[m]){
-                                	# L tail test
-                                	print(\"L\");
-	                            	tail <- \"L\";
-                                	pv <- (length(which(null[, m] <= temp[m])))/(length(na.exclude(null[, m])));
-                        		}
-							}
-							out <- c(out, pv);
-							print(pv);
-							out <- c(out, tail);
-                    	}
-                    	final_pvalue <-rbind(final_pvalue, out);
-                 	
-                 
-                    	# get variances outside null bands by comparing temp to null
-                    	## temp stores variance for each scale, and null stores permuted variances for null bands
-                    	for (n in 1:length(temp)){
-                    		if (temp[n] <= var_975[n]){
-                        		temp[n] <- NA;
-                        	} else {
-                        		temp[n] <- temp[n];
-                        	}
-                    	}
-                    	matrix <- rbind(matrix, temp)
-            		}
-            	}
-	        	# labels
-	        	if (i == 1){
-	        		mtext(names[j], side = 2, line = 0.5, las = 3, cex = 0.25);
-	        	}
-	        	if (j == 1){
-	        		mtext(names[i], side = 3, line = 0.5, cex = 0.25);
-	        	}
-	        	if (j == length(names)){
-	        		axis(1, at = (1:short.levels), las = 3, cex.axis = 0.5);
-	        	}
-    		}
-    	}
-		colnames(final_pvalue) <- title;
-    	#write.table(final_pvalue, file = \"test_final_pvalue.txt\", sep = \"\\t\", quote = FALSE, row.names = FALSE, append = TRUE);
-
-		# get maximum variance larger than expectation by comparison to null bands
-    	varnames <- vector();
-    	for(i in 1:length(names)){
-    		name1 = paste(names[i], \"var\", sep = \"_\")
-        	varnames <- c(varnames, name1)
-    	}
-   		rownames(matrix) <- varnames;
-    	colnames(matrix) <- (1:short.levels);
-    	max_var <- names;
-    	scale <- vector(length = length(names));
-    	for (x in 1:nrow(matrix)){
-        	if (length(which.max(matrix[x, ])) == 0){
-            	scale[x] <- NA;
-        	}
-        	else{
-        		scale[x] <- colnames(matrix)[which.max(matrix[x, ])];
-        	}
-    	}
-    	max_var <- cbind(max_var, scale);
-    	write.table(max_var, file = \"$max_dwt\", sep = \"\\t\", quote = FALSE, row.names = FALSE, append = TRUE);
-    	return(final_pvalue);
-	}\n";
-
-print Rcmd "
-	# execute
-	# read in data 
-	
-	data_test = NULL;
-	data_test <- read.delim(\"$inputFile\");
-	
-	pdf(file = \"$pdf\", width = 11, height = 8);
-	
-	# loop to read and execute on all $count2 subfiles
-	final = NULL;
-	for (x in 1:$count2){
-		sub = NULL;
-		sub_names = NULL;
-		a = NULL;
-		b = NULL;
-		
-    	a = ((x - 1) * 12 + 1);
-    	b = x * 12;
-    
-    	if (x < $count2){
-    		sub <- data_test[, +c(a:b)];
-			sub_names <- colnames(data_test)[a:b];
-			final <- rbind(final, dwt_var_permut_getMax(sub, sub_names));
-    	}
-    	else{
-    		sub <- data_test[, +c(a:ncol(data_test))];
-			sub_names <- colnames(data_test)[a:ncol(data_test)];
-			final <- rbind(final, dwt_var_permut_getMax(sub, sub_names));
-			
-    	}
-	}
-
-	dev.off();
-
-	write.table(final, file = \"$pvalue\", sep = \"\\t\", quote = FALSE, row.names = FALSE);
-
-	#eof\n";
-
-close Rcmd;
-
-system("echo \"wavelet ANOVA started on \`hostname\` at \`date\`\"\n");
-system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");
-system("echo \"wavelet ANOVA ended on \`hostname\` at \`date\`\"\n");
-
-#close the input and output and error files
-close(ERROR);
-close(OUTPUT3);
-close(OUTPUT2);
-close(OUTPUT1);
-close(INPUT);
\ No newline at end of file