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comparison execute_dwt_cor_aVa_perClass.xml @ 2:b87bbe6bc044 draft default tip

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"planemo upload for repository https://github.com/galaxyproject/tools-devteam/tree/master/tools/dwt_cor_ava_perclass commit f929353ffb0623f2218d7dec459c7da62f3b0d24"
author devteam
date Mon, 06 Jul 2020 20:28:54 -0400
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1:a0defff5cf89 2:b87bbe6bc044
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"> 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="1.0.1">
2 <description>between two datasets using Discrete Wavelet Transfoms</description> 2 <description>between two datasets using Discrete Wavelet Transfoms</description>
3 3 <requirements>
4 <command interpreter="perl"> 4 <requirement type="package" version="1.7.5">r-waveslim</requirement>
5 execute_dwt_cor_aVa_perClass.pl $inputFile1 $inputFile2 $outputFile1 $outputFile2 5 <requirement type="package" version="4.6.8">r-wavethresh</requirement>
6 </requirements>
7 <command detect_errors="exit_code">
8 Rscript --vanilla '$__tool_directory__/execute_dwt_cor_aVa_perClass.R'
9 '$inputFile1'
10 '$inputFile2'
11 '$outputFile2'
12 '$outputFile1'
6 </command> 13 </command>
7
8 <inputs> 14 <inputs>
9 <param format="tabular" name="inputFile1" type="data" label="Select the first input file"/> 15 <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"/> 16 <param format="tabular" name="inputFile2" type="data" label="Select the second input file"/>
11 </inputs> 17 </inputs>
12
13 <outputs> 18 <outputs>
14 <data format="tabular" name="outputFile1"/> 19 <data format="tabular" name="outputFile1" label="${tool.name} on ${on_string}: statistics"/>
15 <data format="pdf" name="outputFile2"/> 20 <data format="pdf" name="outputFile2" label="${tool.name} on ${on_string}: pdf"/>
16 </outputs> 21 </outputs>
17 22 <tests>
18 <help> 23 <test>
19 24 <param ftype="tabular" name="inputFile1" value="in1.tsv"/>
25 <param ftype="tabular" name="inputFile2" value="in2.tsv"/>
26 <output name="outputFile1" ftype="tabular">
27 <assert_contents><has_line_matching expression="^translinTarget.*"/></assert_contents>
28 <assert_contents><has_line_matching expression="^deletionHoptspot.*" /></assert_contents>
29 </output>
30 <output name="outputFile2" ftype="pdf" file="out2.pdf" compare="sim_size"/>
31 </test>
32 </tests>
33 <help>
20 .. class:: infomark 34 .. class:: infomark
21 35
22 **What it does** 36 **What it does**
23 37
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. 38 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.
25 39
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. 40 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.
27 41
28 The program has two input files obtained as follows: 42 The program has two input files obtained as follows:
29 43
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. 44 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.
31 45
32 The program gives two output files: 46 The program gives two output files:
33 47
34 - The first output file is a TABULAR format file representing the coefficient correlations and p-values for each feature at each scale. 48 - 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 correlation for that feature at every scale. 49 - 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.
38 52
39 .. class:: warningmark 53 .. class:: warningmark
40 54
41 **Note** 55 **Note**
42 56
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. 57 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.
44 58
45 ----- 59 -----
46 60
47 **Example** 61 **Example**
48 62
84 115 121 136 109 470 98 115 121 136 109 470
85 113 135 138 101 491 99 113 135 138 101 491
86 111 150 138 102 451 100 111 150 138 102 451
87 94 128 151 138 481 101 94 128 151 138 481
88 102
89 103
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: 104 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:
91 105
92 The first output file:: 106 The first output file::
93 107
94 motif 1_cor 1_pval 2_cor 2_pval 3_cor 3_pval 4_cor 4_pval 108 motif 1_cor 1_pval 2_cor 2_pval 3_cor 3_pval 4_cor 4_pval
105 .. image:: dwt_cor_aVa_2.png 119 .. image:: dwt_cor_aVa_2.png
106 .. image:: dwt_cor_aVa_3.png 120 .. image:: dwt_cor_aVa_3.png
107 .. image:: dwt_cor_aVa_4.png 121 .. image:: dwt_cor_aVa_4.png
108 .. image:: dwt_cor_aVa_5.png 122 .. image:: dwt_cor_aVa_5.png
109 123
110 </help> 124 </help>
111 125
112 </tool> 126 </tool>