# HG changeset patch # User devteam # Date 1594081898 14400 # Node ID e01e8a9a82f4d52b975947ff069b0b2adefcfbb1 # Parent 8564f6927b87445665b73c849786916c2edf2adc "planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_cor_avb_all commit f929353ffb0623f2218d7dec459c7da62f3b0d24" diff -r 8564f6927b87 -r e01e8a9a82f4 execute_dwt_cor_aVb_all.R --- /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"); diff -r 8564f6927b87 -r e01e8a9a82f4 execute_dwt_cor_aVb_all.pl --- 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); diff -r 8564f6927b87 -r e01e8a9a82f4 execute_dwt_cor_aVb_all.xml --- 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 @@ - + between two datasets using Discrete Wavelet Transfoms - - - execute_dwt_cor_aVb_all.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2 + + r-waveslim + r-wavethresh + + + Rscript --vanilla '$__tool_directory__/execute_dwt_cor_aVb_all.R' + '$inputFile1' + '$inputFile2' + '$outputFile2' + '$outputFile1' - - - + + - - - + + - + + + + + + + + + + + .. class:: infomark diff -r 8564f6927b87 -r e01e8a9a82f4 test-data/in1.tsv --- /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 diff -r 8564f6927b87 -r e01e8a9a82f4 test-data/in2.tsv --- /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 diff -r 8564f6927b87 -r e01e8a9a82f4 test-data/out2.pdf Binary file test-data/out2.pdf has changed