/tools/discreteWavelet/execute_dwt_cor_aVb_all.xml
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1<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"> 2 <description>between two datasets using Discrete Wavelet Transfoms</description> 3 4 <command interpreter="perl"> 5 execute_dwt_cor_aVb_all.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2 6 </command> 7 8 <inputs> 9 <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/> 10 <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/> 11 </inputs> 12 13 <outputs> 14 <data format="tabular" name="outputFile1"/> 15 <data format="pdf" name="outputFile2"/> 16 </outputs> 17 18 <help> 19 20.. class:: infomark 21 22**What it does** 23 24This 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. 25 26The 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. 27 28The program has two input files obtained as follows: 29 30For 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. 31 32The program gives two output files: 33 34- The first output file is a TABULAR format file representing the coefficient correlations and p-values for each feature at each scale. 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 correlations for that feature at every scale. 36 37----- 38 39.. class:: warningmark 40 41**Note** 42 43In 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. 44 45----- 46 47**Example** 48 49Counting the occurrences of 5 features (motifs) in 16 intervals (one line per interval) of the DNA sequences in S1 gives the following tabular file:: 50 51 deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget 52 82 162 158 79 459 53 111 196 154 75 459 54 98 178 160 79 475 55 113 201 170 113 436 56 113 173 147 95 446 57 107 150 155 84 436 58 106 166 175 96 448 59 113 176 135 106 514 60 113 170 152 87 450 61 95 152 167 93 467 62 91 171 169 118 426 63 84 139 160 100 459 64 92 154 164 104 440 65 100 145 154 98 472 66 91 161 152 71 461 67 117 164 139 97 463 68 69And 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:: 70 71 deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget 72 269 366 330 238 1129 73 239 328 327 283 1188 74 254 351 358 297 1151 75 262 371 355 256 1107 76 254 361 352 234 1192 77 265 354 367 240 1182 78 255 359 333 235 1217 79 271 389 387 272 1241 80 240 305 341 249 1159 81 272 351 337 257 1169 82 275 351 337 233 1158 83 305 331 361 253 1172 84 277 341 343 253 1113 85 266 362 355 267 1162 86 235 326 329 241 1230 87 254 335 360 251 1172 88 89 90We 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: 91 92The first output file:: 93 94 motif1 motif2 1_cor 1_pval 2_cor 2_pval 3_cor 3_pval 4_cor 4_pval 95 96 deletionHoptspot insertionHoptspot -0.1 0.346 -0.214 0.338 1 0.127 1 0.467 97 deletionHoptspot dnaPolPauseFrameshift 0.167 0.267 -0.214 0.334 1 0.122 1 0.511 98 deletionHoptspot topoisomeraseCleavageSite 0.167 0.277 0.143 0.412 -0.667 0.243 1 0.521 99 deletionHoptspot translinTarget 0 0.505 0.0714 0.441 1 0.124 1 0.518 100 insertionHoptspot dnaPolPauseFrameshift -0.202 0.238 0.143 0.379 -1 0.122 1 0.517 101 insertionHoptspot topoisomeraseCleavageSite -0.0336 0.457 0.214 0.29 0.667 0.252 1 0.503 102 insertionHoptspot translinTarget 0.0672 0.389 0.429 0.186 -1 0.119 1 0.506 103 dnaPolPauseFrameshift topoisomeraseCleavageSite -0.353 0.101 0.357 0.228 0 0.612 -1 0.49 104 dnaPolPauseFrameshift translinTarget -0.151 0.303 -0.571 0.09 -0.333 0.37 -1 1 105 topoisomeraseCleavageSite translinTarget -0.37 0.077 -0.222 0.297 0.667 0.234 -1 0.471 106 107The second output file: 108 109.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_1.png 110.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_2.png 111.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_3.png 112.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_4.png 113.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_5.png 114.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_6.png 115.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_7.png 116.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_8.png 117.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_9.png 118.. image:: ${static_path}/operation_icons/dwt_cor_aVb_all_10.png 119 120 121 </help> 122 123</tool>