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1 <tool id="compute_p-values_correlation_coefficients_feature_occurrences_between_two_datasets_using_discrete_wavelet_transfom" name="Compute P-values and Correlation Coefficients for Feature Occurrences" version="1.0.0">
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2 <description>between two datasets using Discrete Wavelet Transfoms</description>
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3
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4 <command interpreter="perl">
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5 execute_dwt_cor_aVa_perClass.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2
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6 </command>
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7
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8 <inputs>
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9 <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>
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10 <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
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11 </inputs>
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12
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13 <outputs>
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14 <data format="tabular" name="outputFile1"/>
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15 <data format="pdf" name="outputFile2"/>
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16 </outputs>
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17
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18 <help>
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19
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20 .. class:: infomark
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21
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22 **What it does**
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23
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24 This program generates plots and computes table matrix of coefficient correlations and p-values at multiple scales for the correlation between the occurrences of features in one dataset and their occurrences in another using multiscale wavelet analysis technique.
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25
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26 The program assumes that the user has two sets of DNA sequences, S1 and S1, each of which consists of one or more sequences of equal length. Each sequence in each set is divided into the same number of multiple intervals n such that n = 2^k, where k is a positive integer and k >= 1. Thus, n could be any value of the set {2, 4, 8, 16, 32, 64, 128, ...}. k represents the number of scales.
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27
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28 The program has two input files obtained as follows:
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29
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30 For a given set of features, say motifs, the user counts the number of occurrences of each feature in each interval of each sequence in S1 and S1, and builds two tabular files representing the count results in each interval of S1 and S1. These are the input files of the program.
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31
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32 The program gives two output files:
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33
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34 - The first output file is a TABULAR format file representing the coefficient correlations and p-values for each feature at each scale.
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35 - The second output file is a PDF file consisting of as many figures as the number of features, such that each figure represents the values of the coefficient correlation for that feature at every scale.
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36
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37 -----
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38
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39 .. class:: warningmark
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40
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41 **Note**
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42
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43 In order to obtain empirical p-values, a random perumtation test is implemented by the program, which results in the fact that the program gives slightly different results each time it is run on the same input file.
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44
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45 -----
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46
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47 **Example**
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48
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49 Counting the occurrences of 5 features (motifs) in 16 intervals (one line per interval) of the DNA sequences in S1 gives the following tabular file::
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50
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51 deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget
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52 269 366 330 238 1129
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53 239 328 327 283 1188
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54 254 351 358 297 1151
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55 262 371 355 256 1107
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56 254 361 352 234 1192
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57 265 354 367 240 1182
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58 255 359 333 235 1217
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59 271 389 387 272 1241
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60 240 305 341 249 1159
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61 272 351 337 257 1169
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62 275 351 337 233 1158
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63 305 331 361 253 1172
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64 277 341 343 253 1113
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65 266 362 355 267 1162
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66 235 326 329 241 1230
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67 254 335 360 251 1172
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68
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69 And counting the occurrences of 5 features (motifs) in 16 intervals (one line per interval) of the DNA sequences in S2 gives the following tabular file::
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70
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71 deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget
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72 104 146 142 113 478
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73 89 146 151 94 495
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74 100 176 151 88 435
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75 96 163 128 114 468
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76 99 138 144 91 513
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77 112 126 162 106 468
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78 86 127 145 83 491
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79 104 145 171 110 496
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80 91 121 147 104 469
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81 103 141 145 98 458
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82 92 134 142 117 468
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83 97 146 145 107 471
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84 115 121 136 109 470
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85 113 135 138 101 491
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86 111 150 138 102 451
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87 94 128 151 138 481
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88
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89
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90 We notice that the number of scales here is 4 because 16 = 2^4. Running the program on the above input files gives the following output:
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91
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92 The first output file::
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93
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94 motif 1_cor 1_pval 2_cor 2_pval 3_cor 3_pval 4_cor 4_pval
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95
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96 deletionHoptspot 0.4 0.072 0.143 0.394 -0.667 0.244 1 0.491
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97 insertionHoptspot 0.343 0.082 -0.0714 0.446 -1 0.12 1 0.502
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98 dnaPolPauseFrameshift 0.617 0.004 -0.5 0.13 0.667 0.234 1 0.506
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99 topoisomeraseCleavageSite -0.183 0.242 -0.286 0.256 0.333 0.353 -1 0.489
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100 translinTarget 0.0167 0.503 -0.0714 0.469 1 0.136 1 0.485
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101
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102 The second output file:
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103
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1
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104 .. image:: dwt_cor_aVa_1.png
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105 .. image:: dwt_cor_aVa_2.png
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106 .. image:: dwt_cor_aVa_3.png
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107 .. image:: dwt_cor_aVa_4.png
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108 .. image:: dwt_cor_aVa_5.png
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109
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110 </help>
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111
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112 </tool>
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