annotate execute_dwt_IvC_all.xml @ 1:506ae7b0d85d draft default tip

"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_ivc_all commit f929353ffb0623f2218d7dec459c7da62f3b0d24"

<tool id="compute_p-values_second_moments_feature_occurrences_between_two_datasets_using_discrete_wavelet_transfom" name="Compute P-values and Second Moments for Feature Occurrences" version="1.0.1">
  <description>between two datasets using Discrete Wavelet Transfoms</description>
  <requirements>
    <requirement type="package" version="1.7.5">r-waveslim</requirement>
    <requirement type="package" version="4.6.8">r-wavethresh</requirement>
  </requirements>
  <command detect_errors="exit_code">
    Rscript --vanilla '$__tool_directory__/execute_dwt_IvC_all.R'
      '$inputFile1'
      '$inputFile2'
      '$outputFile2'
      '$outputFile1'
  </command>
  <inputs>
    <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/>
    <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
  </inputs>
  <outputs>
    <data format="tabular" name="outputFile1" label="${tool.name} on ${on_string}: statistics"/> 
    <data format="pdf" name="outputFile2" label="${tool.name} on ${on_string}: pdf"/>
  </outputs>
  <tests>
    <test>
      <param ftype="tabular" name="inputFile1" value="in1.tsv"/>
      <param ftype="tabular" name="inputFile2" value="in2.tsv"/>
      <output name="outputFile1" ftype="tabular">
        <assert_contents><has_line_matching expression="^motif\t1_moment2.*"/></assert_contents>
        <assert_contents><has_line_matching expression="^translinTarget.*" /></assert_contents>
      </output>
      <output name="outputFile2" ftype="pdf" file="out2.pdf" compare="sim_size"/>
    </test>
  </tests>
  <help> 

.. class:: infomark

**What it does**

This program generates plots and computes table matrix of second moments, p-values, and test orientations 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 second moments, p-values, and test orientations 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 second moment 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	
		226			403			416			221				1165
		236			444			380			241				1223
		242			496			391			195				1116
		243			429			364			191				1118
		244			410			371			236				1063
		230			386			370			217				1087
		275			404			402			214				1044
		265			443			365			231				1086
		255			390			354			246				1114
		281			384			406			232				1102
		263			459			369			251				1135
		280			433			400			251				1159
		278			385			382			231				1147
		248			393			389			211				1162
		251			403			385			246				1114
		239			383			347			227				1172

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
		235			374			407			257				1159
		244			356			353			212				1128
		233			343			322			204				1110
		222			329			398			253				1054
		216			325			328			253				1129
		257			368			352			221				1115
		238			360			346			224				1102
		225			350			377			248				1107
		230			330			365			236				1132
		241			389			357			220				1120
		274			354			392			235				1120
		250			379			354			210				1102
		254			329			320			251				1080
		221			355			406			279				1127
		224			330			390			249				1129
		246			366			364			218				1176

  
We notice that the number of scales here is 4 because 16 = 2^4. Runnig the program on the above input files gives the following output:

The first output file::

	motif				1_moment2	1_pval	1_test	2_moment2	2_pval	2_test	3_moment2	3_pval	3_test	4_moment2	4_pval	4_test
	
	deletionHoptspot		0.8751		0.376	L	1.549		0.168	R	0.6152		0.434	L	0.5735		0.488	R
	insertionHoptspot		0.902		0.396	L	1.172		0.332	R	0.6843		0.456	L	1.728		0.213	R
	dnaPolPauseFrameshift		1.65		0.013	R	0.267		0.055	L	0.1387		0.124	L	0.4516		0.498	L
	topoisomeraseCleavageSite	0.7443		0.233	L	1.023		0.432	R	1.933		0.155	R	1.09		0.3	R
	translinTarget			0.5084		0.057	L	0.8219		0.446	L	3.604		0.019	R	0.4377		0.492	L

The second output file:

.. image:: ${static_path}/operation_icons/dwt_IvC_1.png
.. image:: ${static_path}/operation_icons/dwt_IvC_2.png
.. image:: ${static_path}/operation_icons/dwt_IvC_3.png
.. image:: ${static_path}/operation_icons/dwt_IvC_4.png
.. image:: ${static_path}/operation_icons/dwt_IvC_5.png

  </help>  
  
</tool>