/tools/discreteWavelet/execute_dwt_cor_aVa_perClass.xml

https://bitbucket.org/cistrome/cistrome-harvard/ · XML · 112 lines · 81 code · 31 blank · 0 comment · 0 complexity · b964fc81a3203f49dd8dcd6f9a57d2b3 MD5 · raw file

  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">
  2. <description>between two datasets using Discrete Wavelet Transfoms</description>
  3. <command interpreter="perl">
  4. execute_dwt_cor_aVa_perClass.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2
  5. </command>
  6. <inputs>
  7. <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>
  8. <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
  9. </inputs>
  10. <outputs>
  11. <data format="tabular" name="outputFile1"/>
  12. <data format="pdf" name="outputFile2"/>
  13. </outputs>
  14. <help>
  15. .. class:: infomark
  16. **What it does**
  17. 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.
  18. 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.
  19. The program has two input files obtained as follows:
  20. 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.
  21. The program gives two output files:
  22. - The first output file is a TABULAR format file representing the coefficient correlations and p-values for each feature at each scale.
  23. - 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.
  24. -----
  25. .. class:: warningmark
  26. **Note**
  27. 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.
  28. -----
  29. **Example**
  30. 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::
  31. deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget
  32. 269 366 330 238 1129
  33. 239 328 327 283 1188
  34. 254 351 358 297 1151
  35. 262 371 355 256 1107
  36. 254 361 352 234 1192
  37. 265 354 367 240 1182
  38. 255 359 333 235 1217
  39. 271 389 387 272 1241
  40. 240 305 341 249 1159
  41. 272 351 337 257 1169
  42. 275 351 337 233 1158
  43. 305 331 361 253 1172
  44. 277 341 343 253 1113
  45. 266 362 355 267 1162
  46. 235 326 329 241 1230
  47. 254 335 360 251 1172
  48. 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::
  49. deletionHoptspot insertionHoptspot dnaPolPauseFrameshift topoisomeraseCleavageSite translinTarget
  50. 104 146 142 113 478
  51. 89 146 151 94 495
  52. 100 176 151 88 435
  53. 96 163 128 114 468
  54. 99 138 144 91 513
  55. 112 126 162 106 468
  56. 86 127 145 83 491
  57. 104 145 171 110 496
  58. 91 121 147 104 469
  59. 103 141 145 98 458
  60. 92 134 142 117 468
  61. 97 146 145 107 471
  62. 115 121 136 109 470
  63. 113 135 138 101 491
  64. 111 150 138 102 451
  65. 94 128 151 138 481
  66. 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:
  67. The first output file::
  68. motif 1_cor 1_pval 2_cor 2_pval 3_cor 3_pval 4_cor 4_pval
  69. deletionHoptspot 0.4 0.072 0.143 0.394 -0.667 0.244 1 0.491
  70. insertionHoptspot 0.343 0.082 -0.0714 0.446 -1 0.12 1 0.502
  71. dnaPolPauseFrameshift 0.617 0.004 -0.5 0.13 0.667 0.234 1 0.506
  72. topoisomeraseCleavageSite -0.183 0.242 -0.286 0.256 0.333 0.353 -1 0.489
  73. translinTarget 0.0167 0.503 -0.0714 0.469 1 0.136 1 0.485
  74. The second output file:
  75. .. image:: ${static_path}/operation_icons/dwt_cor_aVa_1.png
  76. .. image:: ${static_path}/operation_icons/dwt_cor_aVa_2.png
  77. .. image:: ${static_path}/operation_icons/dwt_cor_aVa_3.png
  78. .. image:: ${static_path}/operation_icons/dwt_cor_aVa_4.png
  79. .. image:: ${static_path}/operation_icons/dwt_cor_aVa_5.png
  80. </help>
  81. </tool>