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"planemo upload for repository https://github.com/secimTools/gait-gm/tree/main/galaxy commit 758394addb95b09e794132a23a1f7e95ba39df0b"
author malex
date Thu, 29 Jul 2021 20:48:10 +0000
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1 <tool id="secimtools_add_pval_flags" name="Add Binary (0/1) P-value Flags" version="@WRAPPER_VERSION@">
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2 <description>using custom thresholds</description>
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3 <macros>
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4 <import>macros.xml</import>
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5 </macros>
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6 <expand macro="requirements" />
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7 <command detect_errors="exit_code"><![CDATA[
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8 add_pval_flags.py
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9 -de=$DE_Dataset
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10 -id=$uniqID
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11 -p=$pvalue
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12 -t=$thresholds
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13 -o=$output
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14 -fl=$flags
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15 ]]></command>
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16 <inputs>
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17 <param name="DE_Dataset" type="data" format="tabular" label="Select Dataset containing p-values from your history"/>
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18 <param name="uniqID" type="text" size="30" value="" label="Unique FeatureID" help="Name of the column in your Dataset that contains unique FeatureIDs."/>
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19 <param name="pvalue" type="text" size="30" value="" label="P-Value" help="Name of the column containing your p-values."/>
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20 <param name="thresholds" type="text" size="30" value="0.1,0.05,0.01" label="P-Value Thresholds" help="Enter the threshold(s). P-values less than the given threshold(s) will be flagged with a 1. Separate more than 1 threshold value with a comma; no spaces allowed. Default values are 0.1,0.05,0.01"/>
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21 </inputs>
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22 <outputs>
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23 <data format="tabular" name="output" label="${tool.name} on ${on_string}: Output File"/>
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24 <data format="tabular" name="flags" label="${tool.name} on ${on_string}: Flags File"/>
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25 </outputs>
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26 <tests>
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27 <test>
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28 <param name="DE_Dataset" value="limma_voom_gene.tsv"/>
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29 <param name="uniqID" value="UniqueID"/>
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30 <param name="pvalue" value="P.Value"/>
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31 <param name="thresholds" value="0.1,0.05,0.01"/>
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32 <output name="output" file="add_flags_gene_output.tsv"/>
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33 <output name="flags" file="add_flags_gene_flags.tsv"/>
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34 </test>
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35 <test>
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36 <param name="DE_Dataset" value="limma_voom_metabolite.tsv"/>
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37 <param name="uniqID" value="UniqueID"/>
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38 <param name="pvalue" value="P.Value"/>
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39 <param name="thresholds" value="0.1,0.05,0.01"/>
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40 <output name="output" file="add_flags_metabolite_output.tsv"/>
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41 <output name="flags" file="add_flags_metabolite_flags.tsv"/>
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42 </test>
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43 </tests>
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44 <help><![CDATA[
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45 **Tool Description**
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46
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47 This tool generates 0/1 indicator variables to identify (‘flag’) p-values less than a user-specified threshold or less than the
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48 default values of 0.1, 0.05 and 0.01. The flag_threshold variable is equal to 1 if the p-value is less than or equal to the
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49 threshold and equal to 0 if greater than the threshold. You can flag nominal p-values or p-values after correction for multiple testing.
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50
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51 --------------------------------------------------------------------------------
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52
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53 **INPUT**
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54
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55 **Example of a dataset containing p-values**
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56
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57 +-----------+---------+---------+-----+
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58 | FeatureID | P-value | FDR | ... |
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59 +===========+=========+=========+=====+
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60 | one | 2.02e-6 | 1.83e-6 | ... |
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61 +-----------+---------+---------+-----+
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62 | two | 2.87e-5 | 0.0063 | ... |
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63 +-----------+---------+---------+-----+
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64 | three | 0.001 | 0.19 | ... |
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65 +-----------+---------+---------+-----+
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66 | four | 0.22 | 0.99 | ... |
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67 +-----------+---------+---------+-----+
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68 | ... | ... | ... | ... |
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69 +-----------+---------+---------+-----+
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70
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71 **P-value**
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72
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73 Name of the column in your Dataset that contains p-values.
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74
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75 **P-value Threshold**
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76
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77 P-values less than the threshold will be flagged with a 1. P-values greater than the threshold will be flagged with a 0.
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78
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79 **NOTE:** More than one threshold value is allowed. Separate flags will be generated for each threshold value.
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80
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81 --------------------------------------------------------------------------------
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82
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83 **OUTPUT**
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84
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85 Two output files are generated from the Add Binary (0/1) P-value Flags tool:
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86
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87 **Output File.** A TSV file containing the same columns as the Input Dataset plus an additional column(s) containing 0/1 binary indicators for whether the P-value was less that the user-specified threshold. The indicator columns are named by appending the user-specified threshold to "Flag" prefix (e.g. Flag_user-specified threshold, Flag_0.10).
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88
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89 +-----------+---------+---------+--------+-------------+-----+
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90 | FeatureID | p-value | FDR | Flag_0.2 | Flag_0.05 | ... |
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91 +===========+=========+=========+==========+===========+=====+
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92 | one | 2.02e-6 | 1.83e-6 | 1 | 1 | ... |
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93 +-----------+---------+---------+----------+-----------+-----+
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94 | two | 2.87e-5 | 0.0063 | 1 | 1 | ... |
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95 +-----------+---------+---------+----------+-----------+-----+
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96 | three | 0.001 | 0.19 | 1 | 0 | ... |
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97 +-----------+---------+---------+----------+-----------+-----+
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98 | four | 0.22 | 0.99 | 0 | 0 | ... |
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99 +-----------+---------+---------+----------+-----------+-----+
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100 | ... | ... | ... | ... | ... | ... |
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101 +-----------+---------+---------+----------+-----------+-----+
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102
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103 **Flag Table.** A TSV file containing only the FeatureID column from the input dataset and the tool-generated binary indicator flags.
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104
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105 +-----------+----------+-----------+-----+
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106 | FeatureID | Flag_0.2 | Flag_0.05 | ... |
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107 +===========+==========+===========+=====+
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108 | one | 1 | 1 | ... |
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109 +-----------+----------+-----------+-----+
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110 | two | 1 | 1 | ... |
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111 +-----------+----------+-----------+-----+
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112 | three | 1 | 0 | ... |
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113 +-----------+----------+-----------+-----+
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114 | four | 0 | 0 | ... |
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115 +-----------+----------+-----------+-----+
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116 | ... | ... | ... | ... |
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117 +-----------+----------+-----------+-----+
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118
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119 ]]></help>
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120 <citations>
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121 <citation type="bibtex">@ARTICLE{Kirpich17secimtools,
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122 author = {Alexander S. Kirpich, Miguel Ibarra, Oleksandr Moskalenko, Justin M. Fear, Joseph Gerken, Xinlei Mi, Ali Ashrafi, Alison M. Morse, Lauren M. McIntyre},
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123 title = {SECIMTools: A suite of Metabolomics Data Analysis Tools},
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124 journal = {BMC Bioinformatics},
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125 year = {2018}
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126 }</citation>
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127 <citation type="bibtex">@article{Mor2021GaitGM,
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128 title={GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease},
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129 author={Mor, DE and Huertas, F and Morse, AM and Kaletsky, R and Murphy, CT and Kalia, V and Miller, GW and Moskalenko, O and Conesa, A and McIntyre, LM},
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130 journal={BMC Genomics},
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131 year={submitted},
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132 }</citation>
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133 </citations>
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134 </tool>