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1 #!/usr/bin/perl -w
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2
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3 use warnings;
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4 use IO::Handle;
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5 use POSIX qw(floor ceil);
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6
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7 # example: perl execute_dwt_var_perClass.pl hg18_NCNR_10bp_3flanks_deletionHotspot_data_del.txt deletionHotspot 3flanks del
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8
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9 $usage = "execute_dwt_var_perClass.pl [TABULAR.in] [TABULAR.out] [TABULAR.out] [PDF.out] \n";
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10 die $usage unless @ARGV == 4;
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11
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12 #get the input arguments
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13 my $inputFile = $ARGV[0];
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14 my $firstOutputFile = $ARGV[1];
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15 my $secondOutputFile = $ARGV[2];
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16 my $thirdOutputFile = $ARGV[3];
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17
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18 open (INPUT, "<", $inputFile) || die("Could not open file $inputFile \n");
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19 open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
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20 open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \n");
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21 open (OUTPUT3, ">", $thirdOutputFile) || die("Could not open file $thirdOutputFile \n");
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22 open (ERROR, ">", "error.txt") or die ("Could not open file error.txt \n");
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23
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24 #save all error messages into the error file $errorFile using the error file handle ERROR
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25 STDERR -> fdopen( \*ERROR, "w" ) or die ("Could not direct errors to the error file error.txt \n");
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26
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27 # choosing meaningful names for the output files
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28 $max_dwt = $firstOutputFile;
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29 $pvalue = $secondOutputFile;
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30 $pdf = $thirdOutputFile;
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31
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32 # count the number of columns in the input file
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33 while($buffer = <INPUT>){
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34 #if ($buffer =~ m/interval/){
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35 chomp($buffer);
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36 $buffer =~ s/^#\s*//;
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37 @contrl = split(/\t/, $buffer);
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38 last;
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39 #}
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40 }
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41 print "The number of columns in the input file is: " . (@contrl) . "\n";
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42 print "\n";
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43
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44 # count the number of motifs in the input file
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45 $count = 0;
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46 for ($i = 0; $i < @contrl; $i++){
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47 $count++;
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48 print "# $contrl[$i]\n";
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49 }
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50 print "The number of motifs in the input file is: $count \n";
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51
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52 # check if the number of motifs is not a multiple of 12, and round up is so
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53 $count2 = ($count/12);
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54 if ($count2 =~ m/(\D)/){
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55 print "the number of motifs is not a multiple of 12 \n";
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56 $count2 = ceil($count2);
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57 }
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58 else {
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59 print "the number of motifs is a multiple of 12 \n";
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60 }
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61 print "There will be $count2 subfiles\n\n";
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62
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63 # split infile into subfiles only 12 motif per file for R plotting
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64 for ($x = 1; $x <= $count2; $x++){
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65 $a = (($x - 1) * 12 + 1);
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66 $b = $x * 12;
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67
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68 if ($x < $count2){
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69 print "# data.short $x <- data_test[, +c($a:$b)]; \n";
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70 }
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71 else{
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72 print "# data.short $x <- data_test[, +c($a:ncol(data_test)]; \n";
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73 }
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74 }
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75
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76 print "\n";
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77 print "There are 4 output files: \n";
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78 print "The first output file is a pdf file\n";
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79 print "The second output file is a max_dwt file\n";
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80 print "The third output file is a pvalues file\n";
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81 print "The fourth output file is a test_final_pvalues file\n";
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82
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83 # write R script
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84 $r_script = "get_dwt_varPermut_getMax.r";
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85 print "The R file name is: $r_script \n";
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86
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87 open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
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88
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89 print Rcmd "
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90 ######################################################################
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91 # plot power spectra, i.e. wavelet variance by class
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92 # add code to create null bands by permuting the original data series
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93 # get class of maximum significant variance per feature
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94 # generate plots and table matrix of variance including p-values
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95 ######################################################################
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96 library(\"Rwave\");
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97 library(\"wavethresh\");
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98 library(\"waveslim\");
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99
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100 options(echo = FALSE)
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101
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102 # normalize data
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103 norm <- function(data){
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104 v <- (data-mean(data))/sd(data);
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105 if(sum(is.na(v)) >= 1){
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106 v<-data;
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107 }
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108 return(v);
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109 }
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110
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111 dwt_var_permut_getMax <- function(data, names, filter = 4, bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
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112 max_var = NULL;
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113 matrix = NULL;
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114 title = NULL;
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115 final_pvalue = NULL;
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116 short.levels = NULL;
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117 scale = NULL;
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118
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119 print(names);
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120
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121 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);
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122
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123 short.levels <- wd(data[, 1], filter.number = filter, bc = bc)\$nlevels;
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124
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125 title <- c(\"motif\");
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126 for (i in 1:short.levels){
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127 title <- c(title, paste(i, \"var\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"), paste(i, \"test\", sep = \"_\"));
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128 }
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129 print(title);
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130
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131 # normalize the raw data
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132 data<-apply(data,2,norm);
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133
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134 for(i in 1:length(names)){
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135 for(j in 1:length(names)){
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136 temp = NULL;
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137 results = NULL;
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138 wave1.dwt = NULL;
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139 out = NULL;
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140
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141 out <- vector(length = length(title));
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142 temp <- vector(length = short.levels);
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143
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144 if(i < j) {
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145 plot(temp, type = \"n\", axes = FALSE, xlab = NA, ylab = NA);
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146 box(col = \"grey\");
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147 grid(ny = 0, nx = NULL);
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148 } else {
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149 if (i > j){
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150 plot(temp, type = \"n\", axes = FALSE, xlab = NA, ylab = NA);
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151 box(col = \"grey\");
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152 grid(ny = 0, nx = NULL);
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153 } else {
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154
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155 wave1.dwt <- dwt(data[, i], wf = wf, short.levels, boundary = boundary);
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156
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157 temp_row = (short.levels + 1 ) * -1;
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158 temp_col = 1;
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159 temp <- wave.variance(wave1.dwt)[temp_row, temp_col];
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160
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161 #permutations code :
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162 feature1 = NULL;
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163 null = NULL;
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164 var_25 = NULL;
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165 var_975 = NULL;
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166 med = NULL;
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167
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168 feature1 = data[, i];
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169 for (k in 1:1000) {
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170 nk_1 = NULL;
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171 null.levels = NULL;
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172 var = NULL;
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173 null_wave1 = NULL;
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174
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175 nk_1 = sample(feature1, length(feature1), replace = FALSE);
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176 null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
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177 var <- vector(length = length(null.levels));
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178 null_wave1 <- dwt(nk_1, wf = wf, short.levels, boundary = boundary);
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179 var<- wave.variance(null_wave1)[-8, 1];
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180 null= rbind(null, var);
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181 }
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182 null <- apply(null, 2, sort, na.last = TRUE);
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183 var_25 <- null[25, ];
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184 var_975 <- null[975, ];
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185 med <- (apply(null, 2, median, na.rm = TRUE));
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186
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187 # plot
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188 results <- cbind(temp, var_25, var_975);
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189 matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), axes = F);
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190
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191 # get pvalues by comparison to null distribution
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192 out <- (names[i]);
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193 for (m in 1:length(temp)){
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194 print(paste(\"scale\", m, sep = \" \"));
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195 print(paste(\"var\", temp[m], sep = \" \"));
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196 print(paste(\"med\", med[m], sep = \" \"));
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197 pv = tail = NULL;
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198 out <- c(out, format(temp[m], digits = 3));
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199 if (temp[m] >= med[m]){
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200 # R tail test
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201 print(\"R\");
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202 tail <- \"R\";
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203 pv <- (length(which(null[, m] >= temp[m])))/(length(na.exclude(null[, m])));
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204
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205 } else {
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206 if (temp[m] < med[m]){
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207 # L tail test
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208 print(\"L\");
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209 tail <- \"L\";
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210 pv <- (length(which(null[, m] <= temp[m])))/(length(na.exclude(null[, m])));
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211 }
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212 }
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213 out <- c(out, pv);
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214 print(pv);
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215 out <- c(out, tail);
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216 }
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217 final_pvalue <-rbind(final_pvalue, out);
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218
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219
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220 # get variances outside null bands by comparing temp to null
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221 ## temp stores variance for each scale, and null stores permuted variances for null bands
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222 for (n in 1:length(temp)){
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223 if (temp[n] <= var_975[n]){
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224 temp[n] <- NA;
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225 } else {
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226 temp[n] <- temp[n];
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227 }
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228 }
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229 matrix <- rbind(matrix, temp)
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230 }
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231 }
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232 # labels
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233 if (i == 1){
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234 mtext(names[j], side = 2, line = 0.5, las = 3, cex = 0.25);
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235 }
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236 if (j == 1){
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237 mtext(names[i], side = 3, line = 0.5, cex = 0.25);
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238 }
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239 if (j == length(names)){
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240 axis(1, at = (1:short.levels), las = 3, cex.axis = 0.5);
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241 }
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242 }
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243 }
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244 colnames(final_pvalue) <- title;
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245 #write.table(final_pvalue, file = \"test_final_pvalue.txt\", sep = \"\\t\", quote = FALSE, row.names = FALSE, append = TRUE);
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246
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247 # get maximum variance larger than expectation by comparison to null bands
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248 varnames <- vector();
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249 for(i in 1:length(names)){
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250 name1 = paste(names[i], \"var\", sep = \"_\")
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251 varnames <- c(varnames, name1)
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252 }
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253 rownames(matrix) <- varnames;
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254 colnames(matrix) <- (1:short.levels);
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255 max_var <- names;
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256 scale <- vector(length = length(names));
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257 for (x in 1:nrow(matrix)){
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258 if (length(which.max(matrix[x, ])) == 0){
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259 scale[x] <- NA;
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260 }
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261 else{
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262 scale[x] <- colnames(matrix)[which.max(matrix[x, ])];
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263 }
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264 }
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265 max_var <- cbind(max_var, scale);
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266 write.table(max_var, file = \"$max_dwt\", sep = \"\\t\", quote = FALSE, row.names = FALSE, append = TRUE);
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267 return(final_pvalue);
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268 }\n";
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269
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270 print Rcmd "
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271 # execute
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272 # read in data
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273
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274 data_test = NULL;
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275 data_test <- read.delim(\"$inputFile\");
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276
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277 pdf(file = \"$pdf\", width = 11, height = 8);
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278
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279 # loop to read and execute on all $count2 subfiles
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280 final = NULL;
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281 for (x in 1:$count2){
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282 sub = NULL;
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283 sub_names = NULL;
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284 a = NULL;
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285 b = NULL;
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286
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287 a = ((x - 1) * 12 + 1);
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288 b = x * 12;
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289
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290 if (x < $count2){
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291 sub <- data_test[, +c(a:b)];
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292 sub_names <- colnames(data_test)[a:b];
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293 final <- rbind(final, dwt_var_permut_getMax(sub, sub_names));
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294 }
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295 else{
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296 sub <- data_test[, +c(a:ncol(data_test))];
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297 sub_names <- colnames(data_test)[a:ncol(data_test)];
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298 final <- rbind(final, dwt_var_permut_getMax(sub, sub_names));
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299
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300 }
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301 }
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302
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303 dev.off();
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304
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305 write.table(final, file = \"$pvalue\", sep = \"\\t\", quote = FALSE, row.names = FALSE);
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306
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307 #eof\n";
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308
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309 close Rcmd;
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310
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311 system("echo \"wavelet ANOVA started on \`hostname\` at \`date\`\"\n");
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312 system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");
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313 system("echo \"wavelet ANOVA ended on \`hostname\` at \`date\`\"\n");
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314
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315 #close the input and output and error files
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316 close(ERROR);
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317 close(OUTPUT3);
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318 close(OUTPUT2);
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319 close(OUTPUT1);
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320 close(INPUT); |
