### view tools/discreteWavelet/execute_dwt_cor_aVb_all.xml @ 1:cdcb0ce84a1b

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author xuebing Fri, 09 Mar 2012 19:45:15 -0500 9071e359b9a3
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```
<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">
<description>between two datasets using Discrete Wavelet Transfoms</description>

<command interpreter="perl">
execute_dwt_cor_aVb_all.pl \$inputFile1 \$inputFile2 \$outputFile1 \$outputFile2
</command>

<inputs>
<param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>
<param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
</inputs>

<outputs>
<data format="tabular" name="outputFile1"/>
<data format="pdf" name="outputFile2"/>
</outputs>

<help>

.. class:: infomark

**What it does**

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.

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.

The program has two input files obtained as follows:

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.

The program gives two output files:

- The first output file is a TABULAR format file representing the coefficient correlations and p-values for each feature at each scale.
- 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.

-----

.. class:: warningmark

**Note**

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.

-----

**Example**

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::

deletionHoptspot	insertionHoptspot	dnaPolPauseFrameshift	topoisomeraseCleavageSite	translinTarget
82			162			158			79				459
111			196			154			75				459
98			178			160			79				475
113			201			170			113				436
113			173			147			95				446
107			150			155			84				436
106			166			175			96				448
113			176			135			106				514
113			170			152			87				450
95			152			167			93				467
91			171			169			118				426
84			139			160			100				459
92			154			164			104				440
100			145			154			98				472
91			161			152			71				461
117			164			139			97				463

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::

deletionHoptspot	insertionHoptspot	dnaPolPauseFrameshift	topoisomeraseCleavageSite	translinTarget
269			366			330			238				1129
239			328			327			283				1188
254			351			358			297				1151
262			371			355			256				1107
254			361			352			234				1192
265			354			367			240				1182
255			359			333			235				1217
271			389			387			272				1241
240			305			341			249				1159
272			351			337			257				1169
275			351			337			233				1158
305			331			361			253				1172
277			341			343			253				1113
266			362			355			267				1162
235			326			329			241				1230
254			335			360			251				1172

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:

The first output file::

motif1				motif2				1_cor		1_pval		2_cor		2_pval		3_cor		3_pval		4_cor		4_pval

deletionHoptspot		insertionHoptspot		-0.1		0.346		-0.214		0.338		1		0.127		1		0.467
deletionHoptspot		dnaPolPauseFrameshift		0.167		0.267		-0.214		0.334		1		0.122		1		0.511
deletionHoptspot		topoisomeraseCleavageSite	0.167		0.277		0.143		0.412		-0.667		0.243		1		0.521
deletionHoptspot		translinTarget			0		0.505		0.0714		0.441		1		0.124		1		0.518
insertionHoptspot		dnaPolPauseFrameshift		-0.202		0.238		0.143		0.379		-1		0.122		1		0.517
insertionHoptspot		topoisomeraseCleavageSite	-0.0336		0.457		0.214		0.29		0.667		0.252		1		0.503
insertionHoptspot		translinTarget			0.0672		0.389		0.429		0.186		-1		0.119		1		0.506
dnaPolPauseFrameshift		topoisomeraseCleavageSite	-0.353		0.101		0.357		0.228		0		0.612		-1		0.49
dnaPolPauseFrameshift		translinTarget			-0.151		0.303		-0.571		0.09		-0.333		0.37		-1		1
topoisomeraseCleavageSite	translinTarget			-0.37		0.077		-0.222		0.297		0.667		0.234		-1		0.471

The second output file:

.. image:: ./static/operation_icons/dwt_cor_aVb_all_1.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_2.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_3.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_4.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_5.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_6.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_7.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_8.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_9.png
.. image:: ./static/operation_icons/dwt_cor_aVb_all_10.png

</help>

</tool>
```