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changeset 2:e01e8a9a82f4 draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_cor_avb_all commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
author devteam
date Mon, 06 Jul 2020 20:31:38 -0400
parents 8564f6927b87
children
files execute_dwt_cor_aVb_all.R execute_dwt_cor_aVb_all.pl execute_dwt_cor_aVb_all.xml test-data/in1.tsv test-data/in2.tsv test-data/out2.pdf
diffstat 6 files changed, 235 insertions(+), 234 deletions(-) [+]
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/execute_dwt_cor_aVb_all.R	Mon Jul 06 20:31:38 2020 -0400
@@ -0,0 +1,175 @@
+#################################################################################
+## code to do all correlation tests of form: motif(a) vs. motif(b)
+## add code to create null bands by permuting the original data series
+## generate plots and table matrix of correlation coefficients including p-values
+#################################################################################
+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_cor <- function(data_short, names_short, data_long, names_long, test, pdf, table, filter = 4, bc = "symmetric", method = "kendall", wf = "haar", boundary = "reflection") {
+    print(test);
+    print(pdf);
+    print(table);
+
+    pdf(file = pdf);
+    final_pvalue <- NULL;
+    title <- NULL;
+
+    short_levels <- wavethresh::wd(data_short[, 1], filter.number = filter, bc = bc)$nlevels;
+    title <- c("motif1", "motif2");
+    for (i in 1:short_levels) {
+        title <- c(title, paste(i, "cor", sep = "_"), paste(i, "pval", sep = "_"));
+    }
+    print(title);
+
+    ## normalize the raw data
+    data_short <- apply(data_short, 2, norm);
+    data_long <- apply(data_long, 2, norm);
+
+    ## loop to compare a vs b
+    for (i in seq_len(length(names_short))) {
+        for (j in seq_len(i - 1)) {
+            ## Kendall Tau
+            ## DWT wavelet correlation function
+            ## include significance to compare
+            wave1_dwt <- NULL;
+            wave2_dwt <- NULL;
+            tau_dwt <- NULL;
+            out <- NULL;
+
+            print(names_short[i]);
+            print(names_long[j]);
+
+            ## need exit if not comparing motif(a) vs motif(a)
+            if (names_short[i] == names_long[j]) {
+                stop(paste("motif", names_short[i], "is the same as", names_long[j], sep = " "));
+            }
+            else {
+                wave1_dwt <- waveslim::dwt(data_short[, i], wf = wf, short_levels, boundary = boundary);
+                wave2_dwt <- waveslim::dwt(data_long[, j], wf = wf, short_levels, boundary = boundary);
+                tau_dwt <- vector(length = short_levels)
+
+                ## perform cor test on wavelet coefficients per scale
+                for (level in 1:short_levels) {
+                    w1_level <- NULL;
+                    w2_level <- NULL;
+                    w1_level <- (wave1_dwt[[level]]);
+                    w2_level <- (wave2_dwt[[level]]);
+                    tau_dwt[level] <- cor.test(w1_level, w2_level, method = method)$estimate;
+                }
+
+                ## CI bands by permutation of time series
+                feature1 <- NULL;
+                feature2 <- NULL;
+                feature1 <- data_short[, i];
+                feature2 <- data_long[, j];
+                null <- NULL;
+                results <- NULL;
+                med <- NULL;
+                cor_25 <- NULL;
+                cor_975 <- NULL;
+
+                for (k in 1:1000) {
+                    nk_1 <- NULL;
+                    nk_2 <- NULL;
+                    null_levels <- NULL;
+                    cor <- NULL;
+                    null_wave1 <- NULL;
+                    null_wave2 <- NULL;
+
+                    nk_1 <- sample(feature1, length(feature1), replace = FALSE);
+                    nk_2 <- sample(feature2, length(feature2), replace = FALSE);
+                    null_levels <- wavethresh::wd(nk_1, filter.number = filter, bc = bc)$nlevels;
+                    cor <- vector(length = null_levels);
+                    null_wave1 <- waveslim::dwt(nk_1, wf = wf, short_levels, boundary = boundary);
+                    null_wave2 <- waveslim::dwt(nk_2, wf = wf, short_levels, boundary = boundary);
+
+                    for (level in 1:null_levels) {
+                        null_level1 <- NULL;
+                        null_level2 <- NULL;
+                        null_level1 <- (null_wave1[[level]]);
+                        null_level2 <- (null_wave2[[level]]);
+                        cor[level] <- cor.test(null_level1, null_level2, method = method)$estimate;
+                    }
+                    null <- rbind(null, cor);
+                }
+
+                null <- apply(null, 2, sort, na.last = TRUE);
+                cor_25 <- null[25, ];
+                cor_975 <- null[975, ];
+                med <- (apply(null, 2, median, na.rm = TRUE));
+
+                ## plot
+                results <- cbind(tau_dwt, cor_25, cor_975);
+                matplot(results, type = "b", pch = "*", lty = 1, col = c(1, 2, 2), ylim = c(-1, 1), xlab = "Wavelet Scale", ylab = "Wavelet Correlation Kendall's Tau", main = (paste(test, names_short[i], "vs.", names_long[j], sep = " ")), cex.main = 0.75);
+                abline(h = 0);
+
+                ## get pvalues by comparison to null distribution
+                ### modify pval calculation for error type II of T test ####
+                out <- c(names_short[i], names_long[j]);
+                for (m in seq_len(length(tau_dwt))) {
+                    print(m);
+                    print(tau_dwt[m]);
+                    out <- c(out, format(tau_dwt[m], digits = 3));
+                    pv <- NULL;
+                    if (is.na(tau_dwt[m])) {
+                        pv <- "NA";
+                    }
+                    else{
+                        if (tau_dwt[m] >= med[m]) {
+                            ## R tail test
+                            pv <- (length(which(null[, m] >= tau_dwt[m]))) / (length(na.exclude(null[, m])));
+                        }
+                        else {
+                            if (tau_dwt[m] < med[m]) {
+                                ## L tail test
+                                pv <- (length(which(null[, m] <= tau_dwt[m]))) / (length(na.exclude(null[, m])));
+                            }
+                        }
+                    }
+                    out <- c(out, pv);
+                    print(pv);
+                }
+                final_pvalue <- rbind(final_pvalue, out);
+                print(out);
+            }
+        }
+    }
+    colnames(final_pvalue) <- title;
+    write.table(final_pvalue, file = table, sep = "\t", quote = FALSE, row.names = FALSE)
+    dev.off();
+}
+
+## execute
+## read in data
+args <- commandArgs(trailingOnly = TRUE)
+
+input_data1 <- NULL;
+input_data2 <- NULL;
+input_data_short1 <- NULL;
+input_data_short2 <- NULL;
+input_data_names_short1 <- NULL;
+input_data_names_short2 <- NULL;
+
+input_data1 <- read.delim(args[1]);
+input_data_short1 <- input_data1[, +c(seq_len(ncol(input_data1)))];
+input_data_names_short1 <- colnames(input_data_short1);
+
+input_data2 <- read.delim(args[2]);
+input_data_short2 <- input_data2[, +c(seq_len(ncol(input_data2)))];
+input_data_names_short2 <- colnames(input_data_short2);
+
+# cor test for motif(a) in input_data1 vs motif(b) in input_data2
+dwt_cor(input_data_short1, input_data_names_short1, input_data_short2, input_data_names_short2, test = "cor_aVb_all", pdf = args[3], table = args[4]);
+print("done with the correlation test");
--- a/execute_dwt_cor_aVb_all.pl	Tue Jun 03 14:25:07 2014 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,223 +0,0 @@
-#!/usr/bin/perl -w
-
-use warnings;
-use IO::Handle;
-
-$usage = "execute_dwt_cor_aVb_all.pl [TABULAR.in] [TABULAR.in] [TABULAR.out] [PDF.out]  \n";
-die $usage unless @ARGV == 4;
-
-#get the input arguments
-my $firstInputFile = $ARGV[0];
-my $secondInputFile = $ARGV[1];
-my $firstOutputFile = $ARGV[2];
-my $secondOutputFile = $ARGV[3];
-
-open (INPUT1, "<", $firstInputFile) || die("Could not open file $firstInputFile \n");
-open (INPUT2, "<", $secondInputFile) || die("Could not open file $secondInputFile \n");
-open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
-open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \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");
-
-print "There are two input data files: \n";
-print "The input data file is: $firstInputFile \n";
-print "The control data file is: $secondInputFile \n";
-
-# IvC test
-$test = "cor_aVb_all";
-
-# construct an R script to implement the IvC test
-print "\n";
-
-$r_script = "get_dwt_cor_aVa_test.r"; 
-print "$r_script \n";
-
-
-# R script
-open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
-print Rcmd "
-	#################################################################################
-	# code to do all correlation tests of form: motif(a) vs. motif(b)
-	# add code to create null bands by permuting the original data series
-	# generate plots and table matrix of correlation coefficients 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_cor <- function(data.short, names.short, data.long, names.long, test, pdf, table, filter = 4, bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
-		print(test);
-		print(pdf);
-		print(table);
-		
-		pdf(file = pdf);
-		final_pvalue = NULL;
-		title = NULL;
-		
-		short.levels <- wd(data.short[, 1], filter.number = filter, bc = bc)\$nlevels;
-		title <- c(\"motif1\", \"motif2\");
-		for (i in 1:short.levels){
-			title <- c(title, paste(i, \"cor\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"));
-		}
-		print(title);
-	
-		# normalize the raw data
-		data.short <- apply(data.short, 2, norm);
-		data.long <- apply(data.long, 2, norm);
-	
-		# loop to compare a vs b
-		for(i in 1:length(names.short)){
-			for(j in 1:length(names.long)){
-				if(i >= j){
-					next;
-				} 
-				else { 
-					# Kendall Tau
-					# DWT wavelet correlation function
-					# include significance to compare
-					wave1.dwt = wave2.dwt = NULL;
-					tau.dwt = NULL;
-					out = NULL;
-	
-					print(names.short[i]);
-					print(names.long[j]);
-					
-					# need exit if not comparing motif(a) vs motif(a)
-					if (names.short[i] == names.long[j]){
-						stop(paste(\"motif\", names.short[i], \"is the same as\", names.long[j], sep = \" \"));
-					}
-					else {
-						wave1.dwt <- dwt(data.short[, i], wf = wf, short.levels, boundary = boundary);
-						wave2.dwt <- dwt(data.long[, j], wf = wf, short.levels, boundary = boundary);
-						tau.dwt <-vector(length = short.levels)
-				   
-						# perform cor test on wavelet coefficients per scale 
-						for(level in 1:short.levels){
-							w1_level = w2_level = NULL;
-							w1_level <- (wave1.dwt[[level]]);
-							w2_level <- (wave2.dwt[[level]]);
-							tau.dwt[level] <- cor.test(w1_level, w2_level, method = method)\$estimate;
-						}
-						
-						# CI bands by permutation of time series
-						feature1 = feature2 = NULL;
-						feature1 = data.short[, i];
-						feature2 = data.long[, j];
-						null = results = med = NULL; 
-						cor_25 = cor_975 = NULL;
-						
-						for (k in 1:1000) {
-							nk_1 = nk_2 = NULL;
-							null.levels = NULL;
-							cor = NULL;
-							null_wave1 = null_wave2 = NULL;
-							
-							nk_1 <- sample(feature1, length(feature1), replace = FALSE);
-							nk_2 <- sample(feature2, length(feature2), replace = FALSE);
-							null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
-							cor <- vector(length = null.levels);
-							null_wave1 <- dwt(nk_1, wf = wf, short.levels, boundary = boundary);
-							null_wave2 <- dwt(nk_2, wf = wf, short.levels, boundary = boundary);
-
-							for(level in 1:null.levels){
-								null_level1 = null_level2 = NULL;
-								null_level1 <- (null_wave1[[level]]);
-								null_level2 <- (null_wave2[[level]]);
-								cor[level] <- cor.test(null_level1, null_level2, method = method)\$estimate;
-							}
-							null = rbind(null, cor);
-						}
-							
-						null <- apply(null, 2, sort, na.last = TRUE);
-						cor_25 <- null[25, ];
-						cor_975 <- null[975, ];
-						med <- (apply(null, 2, median, na.rm = TRUE));
-
-						# plot
-						results <- cbind(tau.dwt, cor_25, cor_975);
-						matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), ylim = c(-1, 1), xlab = \"Wavelet Scale\", ylab = \"Wavelet Correlation Kendall's Tau\", main = (paste(test, names.short[i], \"vs.\", names.long[j], sep = \" \")), cex.main = 0.75);
-						abline(h = 0);
-	
-						# get pvalues by comparison to null distribution
-						### modify pval calculation for error type II of T test ####
-						out <- c(names.short[i],names.long[j]);
-						for (m in 1:length(tau.dwt)){
-							print(m);
-							print(tau.dwt[m]);
-							out <- c(out, format(tau.dwt[m], digits = 3));	
-							pv = NULL;
-							if(is.na(tau.dwt[m])){
-								pv <- \"NA\"; 
-							} 
-							else{
-								if (tau.dwt[m] >= med[m]){
-									# R tail test
-									pv <- (length(which(null[, m] >= tau.dwt[m])))/(length(na.exclude(null[, m])));
-								}
-								else{
-									if (tau.dwt[m] < med[m]){
-										# L tail test
-										pv <- (length(which(null[, m] <= tau.dwt[m])))/(length(na.exclude(null[, m])));
-									}
-								}
-							}
-							out <- c(out, pv);
-							print(pv);
-						}
-						final_pvalue <-rbind(final_pvalue, out);
-						print(out);
-					}
-				}
-			}
-		}
-		colnames(final_pvalue) <- title;
-		write.table(final_pvalue, file = table, sep = \"\\t\", quote = FALSE, row.names = FALSE)
-		dev.off();
-	}\n";
-	
-print Rcmd "
-	# execute
-	# read in data 
-
-	inputData1 = inputData2 = NULL;
-	inputData.short1 = inputData.short2 = NULL;
-	inputDataNames.short1 = inputDataNames.short2 = NULL;
-	
-	inputData1 <- read.delim(\"$firstInputFile\");
-	inputData.short1 <- inputData1[, +c(1:ncol(inputData1))];
-	inputDataNames.short1 <- colnames(inputData.short1);
-		
-	inputData2 <- read.delim(\"$secondInputFile\");
-	inputData.short2 <- inputData2[, +c(1:ncol(inputData2))];
-	inputDataNames.short2 <- colnames(inputData.short2);
-	
-	# cor test for motif(a) in inputData1 vs motif(b) in inputData2
-	dwt_cor(inputData.short1, inputDataNames.short1, inputData.short2, inputDataNames.short2, test = \"$test\", pdf = \"$secondOutputFile\", table = \"$firstOutputFile\");
-	print (\"done with the correlation test\");
-
-	#eof\n";
-close Rcmd;
-
-system("echo \"wavelet IvC test started on \`hostname\` at \`date\`\"\n");
-system("R --no-restore --no-save --no-readline < $r_script > $r_script.out\n");
-system("echo \"wavelet IvC test ended on \`hostname\` at \`date\`\"\n");
-
-#close the input and output and error files
-close(ERROR);
-close(OUTPUT2);
-close(OUTPUT1);
-close(INPUT2);
-close(INPUT1);
--- a/execute_dwt_cor_aVb_all.xml	Tue Jun 03 14:25:07 2014 -0400
+++ b/execute_dwt_cor_aVb_all.xml	Mon Jul 06 20:31:38 2020 -0400
@@ -1,20 +1,35 @@
-<tool id="compute_p-values_correlation_coefficients_featureA_featureB_occurrences_between_two_datasets_using_discrete_wavelet_transfom" name="Compute P-values and Correlation Coefficients for Occurrences of Two Set of Features" version="1.0.0">
+<tool id="compute_p-values_correlation_coefficients_featureA_featureB_occurrences_between_two_datasets_using_discrete_wavelet_transfom" name="Compute P-values and Correlation Coefficients for Occurrences of Two Set of Features" version="1.0.1">
   <description>between two datasets using Discrete Wavelet Transfoms</description>
-  
-  <command interpreter="perl">
-  	execute_dwt_cor_aVb_all.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2
+   <requirements>
+    <requirement type="package" version="1.7.5">r-waveslim</requirement>
+    <requirement type="package" version="4.6.8">r-wavethresh</requirement>
+  </requirements> 
+  <command detect_errors="exit_code">
+    Rscript --vanilla '$__tool_directory__/execute_dwt_cor_aVb_all.R'
+      '$inputFile1'
+      '$inputFile2'
+      '$outputFile2'
+      '$outputFile1'
   </command>
-
   <inputs>
-  	<param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>	
-  	<param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
+    <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>	
+    <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
   </inputs>
-  
   <outputs>
-    <data format="tabular" name="outputFile1"/> 
-    <data format="pdf" name="outputFile2"/>
+    <data format="tabular" name="outputFile1" label="${tool.name} on ${on_string}: statistics"/> 
+    <data format="pdf" name="outputFile2" label="${tool.name} on ${on_string}: pdf"/>
   </outputs>
-  	
+  <tests>
+    <test>
+      <param ftype="tabular" name="inputFile1" value="in1.tsv"/>
+      <param ftype="tabular" name="inputFile2" value="in2.tsv"/>
+      <output name="outputFile1" ftype="tabular">
+        <assert_contents><has_line_matching expression="^motif1\tmotif2.*"/></assert_contents>
+        <assert_contents><has_line_matching expression="^topoisomeraseCleavageSite\ttranslinTarget.*" /></assert_contents>
+      </output>
+      <output name="outputFile2" ftype="pdf" file="out2.pdf" compare="sim_size"/>
+    </test>
+  </tests>
   <help> 
 
 .. class:: infomark
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in1.tsv	Mon Jul 06 20:31:38 2020 -0400
@@ -0,0 +1,17 @@
+deletionHoptspot	insertionHoptspot	dnaPolPauseFrameshift	topoisomeraseCleavageSite	translinTarget
+269	366	330	238	1129
+239	328	327	283	1188
+254	351	358	297	1151
+262	371	355	256	1107
+254	361	352	234	1192
+265	354	367	240	1182
+255	359	333	235	1217
+271	389	387	272	1241
+240	305	341	249	1159
+272	351	337	257	1169
+275	351	337	233	1158
+305	331	361	253	1172
+277	341	343	253	1113
+266	362	355	267	1162
+235	326	329	241	1230
+254	335	360	251	1172
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/in2.tsv	Mon Jul 06 20:31:38 2020 -0400
@@ -0,0 +1,17 @@
+deletionHoptspot	insertionHoptspot	dnaPolPauseFrameshift	topoisomeraseCleavageSite	translinTarget
+104	146	142	113	478
+89	146	151	94	495
+100	176	151	88	435
+96	163	128	114	468
+99	138	144	91	513
+112	126	162	106	468
+86	127	145	83	491
+104	145	171	110	496
+91	121	147	104	469
+103	141	145	98	458
+92	134	142	117	468
+97	146	145	107	471
+115	121	136	109	470
+113	135	138	101	491
+111	150	138	102	451
+94	128	151	138	481
Binary file test-data/out2.pdf has changed