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"planemo upload for repository https://github.com/secimTools/SECIMTools/tree/main/galaxy commit 498abad641099412df56f04ff6e144e4193bbc34-dirty"
author malex
date Thu, 10 Jun 2021 15:41:17 +0000
parents 2e7d47c0b027
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2e7d47c0b027 "planemo upload for repository https://malex@toolshed.g2.bx.psu.edu/repos/malex/secimtools"
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1 <tool id="secimtools_partial_least_squares" name="Partial Least Squares Discriminant Analysis (PLS-DA)" version="@WRAPPER_VERSION@">
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2 <description></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 partial_least_squares.py
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9 --input $input
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10 --design $design
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11 --ID $uniqID
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12 --group $group
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13 --toCompare "$toCompare"
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14 --cross_validation $cross_validation
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15 --nComp $nComp
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16 --outScores $outScores
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17 --outWeights $outWeights
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18 --outClassification $outClassification
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19 --outClassificationAccuracy $outClassificationAccuracy
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20 --figure $figures
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21 ]]></command>
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22 <inputs>
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23 <param name="input" type="data" format="tabular" label="Wide Dataset" help="Input your tab-separated wide format dataset. If file is not tab separated see TIP below."/>
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24 <param name="design" type="data" format="tabular" label="Design File" help="Input your design file (tab-separated). Note you need a 'sampleID' column. If not tab separated see TIP below."/>
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25 <param name="uniqID" type="text" size="30" value="" label="Unique Feature ID" help="Name of the column in your wide dataset that has unique identifiers."/>
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26 <param name="group" type="text" size="30" label="Group/Treatment" help="Name of the column in your design file that contains group classifications."/>
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27 <param name="toCompare" type="text" size="30" label="Names of the Groups to Compare" help="Names of the two groups to compare. The user should insure that group names do not contain commas. The separator for the two groups should only include commas (no spaces)."/>
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28 <param name="cross_validation" type="select" size="30" display="radio" value="double" label="Cross-Validation Options">
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29 <option value="none">None</option>
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30 <option value="single">Single</option>
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31 <option value="double">Double</option>
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32 </param>
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33 <param name="nComp" type="text" size="30" value="2" label="Number of Components" help="Number of components for the analysis to use (default = 2). This field is used only when the cross validation field is set to none."/>
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34 </inputs>
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35 <outputs>
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36 <data format="tabular" name="outScores" label="${tool.name} on ${on_string}: Scores"/>
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37 <data format="tabular" name="outWeights" label="${tool.name} on ${on_string}: Weights"/>
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38 <data format="tabular" name="outClassification" label="${tool.name} on ${on_string}: Classification of Samples"/>
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39 <data format='tabular' name="outClassificationAccuracy" label="${tool.name} on ${on_string}: Classification Accuracy of Samples"/>
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40 <data format="pdf" name="figures" label="${tool.name} on ${on_string}: Scatter Plots"/>
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41 </outputs>
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42 <tests>
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43 <test>
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44 <param name="input" value="ST000006_data.tsv"/>
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45 <param name="design" value="ST000006_design_group_name_underscore.tsv"/>
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46 <param name="uniqID" value="Retention_Index" />
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47 <param name="group" value="White_wine_type_and_source" />
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48 <param name="toCompare" value="Chardonnay_ Napa_ CA 2003,Riesling_ CA 2004" />
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49 <param name="cross_validation" value="none"/>
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50 <param name="nComp" value="2"/>
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51 <output name="outScores" file="ST000006_partial_least_squares_none_scores.tsv" />
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52 <output name="outWeights" file="ST000006_partial_least_squares_none_weights.tsv" />
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53 <output name="outClassification" file="ST000006_partial_least_squares_none_classification.tsv" />
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54 <output name="outClassificationAccuracy" file="ST000006_partial_least_squares_none_classification_accuracy.tsv" />
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55 <output name="figures" file="ST000006_partial_least_squares_none_figure.pdf" compare="sim_size" delta="10000"/>
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56 </test>
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57 </tests>
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58 <help><![CDATA[
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59
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60 @TIP_AND_WARNING@
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61
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62 **Tool Description**
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63
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64 The tool performs partial least square discriminant analysis (PLS-DA) for two treatment groups selected by the user.
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65
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66 **NOTE: A minimum of 100 samples is required by the tool for single or double cross validation**
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67
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68 The subspace dimension defines the number of components that will be used to describe the variability within the data.
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69 The user can specify subspace dimension in the range of two to the sample number.
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70 The user has the option to specify the dimension of the subspace directly (Default =2) or to perform single or double cross-validation to determine the dimension of the subspace.
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71
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72 For single and double cross-validation: the data set is split differently when the model fit is performed.
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73
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74 For double cross-validation: the data set is split into pieces and the model fit is performed on one piece using cross-validation and evaluated on the other pieces.
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75
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76 For single cross-validation: the same data are used to fit the model and to evaluate the model using three-fold cross validation.
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77
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78 More details can be found in:
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79
2
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80 Geladi, Paul and Bruce R. Kowalski. "Partial least-squares regression: a tutorial." Analytica chimica acta 185 (1986): 1-17.
1
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83 --------------------------------------------------------------------------------
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84
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85 **Note**
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86
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87 - This tool currently treats all variables as continuous numeric
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88 variables. Running the tool on categorical variables may result in
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89 incorrect results.
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90 - Rows containing non-numeric (or missing) data in any
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91 of the chosen columns will be skipped from the analysis.
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92
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93 --------------------------------------------------------------------------------
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94
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95 **Input**
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96
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97 - Two input datasets are required.
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98
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99 @WIDE@
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100
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101 **NOTE:** The sample IDs must match the sample IDs in the Design File (below).
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102 Extra columns will automatically be ignored.
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103
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104
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105 @METADATA@
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106
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107 @UNIQID@
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108
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109 @GROUP@
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110
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111
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112 **Names of the Groups to Compare**
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113
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114 - Comma separated names of the two groups in your Group/Treatment column that you want to compare. The user should ensure that group names do not contain commas. The separator for the two groups should only include commas (no spaces).
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115
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116 **Cross-Validation Options**
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117
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118 - The choice of cross-validation options available for the user. None corresponds to no cross-validation when the user specifies the number of components manually.
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119
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120 **Number of Components**
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121
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122 - The parameter is used only when the "None" cross-validation option is selected. If the field is left blank, the number of components is set to the default value (2).
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123
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124 --------------------------------------------------------------------------------
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125
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126 **Output**
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128
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129 Three different files are generated:
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130
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131 (1) a TSV file containing the scores produced by the model for each sample
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132
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133 (2) a TSV file containing the weights produced by the model for each feature.
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134
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135 (3) a TSV file containing the classification produced by the model for each sample.
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136
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137 (4) a TSV file containing the algorithm classification accuracy (by percentage).
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138
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139 (5) a PDF file containing the 2D plots for all pairwise comparisons of components between the two treatment groups.
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140
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141 **NOTE:** Regardless how many components are selected for the algorithm, pairwise 2D plots are produced for the pairs of components.
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142 Increasing the number of components will increase the number of plots produced.
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143
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144 ]]></help>
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145 <expand macro="citations"/>
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146 </tool>