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1 #!/usr/bin/perl -w
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2 use warnings;
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3 use IO::Handle;
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4
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5 $usage = "execute_dwt_IvC_all.pl [TABULAR.in] [TABULAR.in] [TABULAR.out] [PDF.out] \n";
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6 die $usage unless @ARGV == 4;
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7
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8 #get the input arguments
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9 my $firstInputFile = $ARGV[0];
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10 my $secondInputFile = $ARGV[1];
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11 my $firstOutputFile = $ARGV[2];
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12 my $secondOutputFile = $ARGV[3];
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13
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14 open (INPUT1, "<", $firstInputFile) || die("Could not open file $firstInputFile \n");
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15 open (INPUT2, "<", $secondInputFile) || die("Could not open file $secondInputFile \n");
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16 open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
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17 open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \n");
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18 open (ERROR, ">", "error.txt") or die ("Could not open file error.txt \n");
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19
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20 #save all error messages into the error file $errorFile using the error file handle ERROR
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21 STDERR -> fdopen( \*ERROR, "w" ) or die ("Could not direct errors to the error file error.txt \n");
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22
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23
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24 print "There are two input data files: \n";
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25 print "The input data file is: $firstInputFile \n";
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26 print "The control data file is: $secondInputFile \n";
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27
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28 # IvC test
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29 $test = "IvC";
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30
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31 # construct an R script to implement the IvC test
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32 print "\n";
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33
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34 $r_script = "get_dwt_IvC_test.r";
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35 print "$r_script \n";
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36
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37 # R script
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38 open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
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39 print Rcmd "
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40 ###########################################################################################
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41 # code to do wavelet Indel vs. Control
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42 # signal is the difference I-C; function is second moment i.e. variance from zero not mean
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43 # to perform wavelet transf. of signal, scale-by-scale analysis of the function
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44 # create null bands by permuting the original data series
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45 # generate plots and table matrix of correlation coefficients including p-values
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46 ############################################################################################
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47 library(\"Rwave\");
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48 library(\"wavethresh\");
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49 library(\"waveslim\");
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50
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51 options(echo = FALSE)
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52
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53 # normalize data
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54 norm <- function(data){
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55 v <- (data - mean(data))/sd(data);
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56 if(sum(is.na(v)) >= 1){
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57 v <- data;
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58 }
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59 return(v);
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60 }
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61
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62 dwt_cor <- function(data.short, names.short, data.long, names.long, test, pdf, table, filter = 4, bc = \"symmetric\", wf = \"haar\", boundary = \"reflection\") {
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63 print(test);
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64 print(pdf);
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65 print(table);
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66
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67 pdf(file = pdf);
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68 final_pvalue = NULL;
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69 title = NULL;
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70
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71 short.levels <- wd(data.short[, 1], filter.number = filter, bc = bc)\$nlevels;
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72 title <- c(\"motif\");
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73 for (i in 1:short.levels){
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74 title <- c(title, paste(i, \"moment2\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"), paste(i, \"test\", sep = \"_\"));
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75 }
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76 print(title);
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77
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78 # loop to compare a vs a
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79 for(i in 1:length(names.short)){
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80 wave1.dwt = NULL;
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81 m2.dwt = diff = var.dwt = NULL;
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82 out = NULL;
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83 out <- vector(length = length(title));
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84
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85 print(names.short[i]);
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86 print(names.long[i]);
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87
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88 # need exit if not comparing motif(a) vs motif(a)
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89 if (names.short[i] != names.long[i]){
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90 stop(paste(\"motif\", names.short[i], \"is not the same as\", names.long[i], sep = \" \"));
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91 }
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92 else {
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93 # signal is the difference I-C data sets
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94 diff<-data.short[,i]-data.long[,i];
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95
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96 # normalize the signal
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97 diff<-norm(diff);
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98
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99 # function is 2nd moment
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100 # 2nd moment m_j = 1/N[sum_N(W_j + V_J)^2] = 1/N sum_N(W_j)^2 + (X_bar)^2
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101 wave1.dwt <- dwt(diff, wf = wf, short.levels, boundary = boundary);
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102 var.dwt <- wave.variance(wave1.dwt);
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103 m2.dwt <- vector(length = short.levels)
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104 for(level in 1:short.levels){
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105 m2.dwt[level] <- var.dwt[level, 1] + (mean(diff)^2);
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106 }
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107
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108 # CI bands by permutation of time series
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109 feature1 = feature2 = NULL;
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110 feature1 = data.short[, i];
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111 feature2 = data.long[, i];
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112 null = results = med = NULL;
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113 m2_25 = m2_975 = NULL;
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114
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115 for (k in 1:1000) {
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116 nk_1 = nk_2 = NULL;
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117 m2_null = var_null = NULL;
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118 null.levels = null_wave1 = null_diff = NULL;
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119 nk_1 <- sample(feature1, length(feature1), replace = FALSE);
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120 nk_2 <- sample(feature2, length(feature2), replace = FALSE);
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121 null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
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122 null_diff <- nk_1-nk_2;
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123 null_diff <- norm(null_diff);
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124 null_wave1 <- dwt(null_diff, wf = wf, short.levels, boundary = boundary);
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125 var_null <- wave.variance(null_wave1);
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126 m2_null <- vector(length = null.levels);
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127 for(level in 1:null.levels){
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128 m2_null[level] <- var_null[level, 1] + (mean(null_diff)^2);
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129 }
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130 null= rbind(null, m2_null);
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131 }
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132
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133 null <- apply(null, 2, sort, na.last = TRUE);
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134 m2_25 <- null[25,];
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135 m2_975 <- null[975,];
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136 med <- apply(null, 2, median, na.rm = TRUE);
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137
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138 # plot
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139 results <- cbind(m2.dwt, m2_25, m2_975);
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140 matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), xlab = \"Wavelet Scale\", ylab = c(\"Wavelet 2nd Moment\", test), main = (names.short[i]), cex.main = 0.75);
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141 abline(h = 1);
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142
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143 # get pvalues by comparison to null distribution
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144 out <- c(names.short[i]);
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145 for (m in 1:length(m2.dwt)){
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146 print(paste(\"scale\", m, sep = \" \"));
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147 print(paste(\"m2\", m2.dwt[m], sep = \" \"));
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148 print(paste(\"median\", med[m], sep = \" \"));
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149 out <- c(out, format(m2.dwt[m], digits = 4));
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150 pv = NULL;
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151 if(is.na(m2.dwt[m])){
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152 pv <- \"NA\";
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153 }
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154 else {
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155 if (m2.dwt[m] >= med[m]){
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156 # R tail test
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157 tail <- \"R\";
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158 pv <- (length(which(null[, m] >= m2.dwt[m])))/(length(na.exclude(null[, m])));
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159 }
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160 else{
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161 if (m2.dwt[m] < med[m]){
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162 # L tail test
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163 tail <- \"L\";
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164 pv <- (length(which(null[, m] <= m2.dwt[m])))/(length(na.exclude(null[, m])));
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165 }
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166 }
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167 }
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168 out <- c(out, pv);
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169 print(pv);
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170 out <- c(out, tail);
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171 }
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172 final_pvalue <-rbind(final_pvalue, out);
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173 print(out);
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174 }
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175 }
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176
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177 colnames(final_pvalue) <- title;
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178 write.table(final_pvalue, file = table, sep = \"\\t\", quote = FALSE, row.names = FALSE);
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179 dev.off();
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180 }\n";
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181
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182 print Rcmd "
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183 # execute
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184 # read in data
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185
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186 inputData <- read.delim(\"$firstInputFile\");
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187 inputDataNames <- colnames(inputData);
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188
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189 controlData <- read.delim(\"$secondInputFile\");
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190 controlDataNames <- colnames(controlData);
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191
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192 # call the test function to implement IvC test
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193 dwt_cor(inputData, inputDataNames, controlData, controlDataNames, test = \"$test\", pdf = \"$secondOutputFile\", table = \"$firstOutputFile\");
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194 print (\"done with the correlation test\");
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195 \n";
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196
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197 print Rcmd "#eof\n";
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198
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199 close Rcmd;
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200
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201 system("echo \"wavelet IvC test started on \`hostname\` at \`date\`\"\n");
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202 system("R --no-restore --no-save --no-readline < $r_script > $r_script.out\n");
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203 system("echo \"wavelet IvC test ended on \`hostname\` at \`date\`\"\n");
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204
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205 #close the input and output and error files
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206 close(ERROR);
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207 close(OUTPUT2);
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208 close(OUTPUT1);
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209 close(INPUT2);
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210 close(INPUT1); |
