Mercurial > repos > iuc > dimet_metabologram

annotate dimet_metabologram.xml @ 7:06f8d9ba09cd draft default tip

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/DIMet commit 6da96d865a3a557cfa3ad09e1cfa830519e73748
author iuc
date Tue, 06 Aug 2024 17:36:05 +0000
parents c7ff01bd331b
children
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a7d3e880e74c planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/DIMet commit abca848510cb4ac8d09d95634147626ea578cdf0
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1 <tool id="dimet_@EXECUTABLE@" name="dimet @EXECUTABLE@" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05">
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2 <description>
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3 Integration of transcriptomics and (tracer) metabolomics differential data (by DIMet)
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4 </description>
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5 <macros>
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6 <token name="@EXECUTABLE@">metabologram</token>
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7 <import>macros.xml</import>
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8 </macros>
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9 <expand macro="requirements"/>
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10 <command detect_errors="exit_code"><![CDATA[
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11 @INIT_CONFIG@
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12 @INIT_METABOLOGRAM@
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13 @INIT_TRANSCRIPTS@
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14 @INIT_GROUPS@
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15 @INIT_COMPARISONS_METABOLOGRAM@
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16 @INIT_PATHWAYS@
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17 @INIT_STAT_TEST@
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18 HYDRA_FULL_ERROR=1 python -m dimet
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19 '++hydra.run.dir=.'
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20 '++figure_path=figures'
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21 '++table_path=tables'
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22 '++analysis={
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23 dataset:{
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24 _target_: dimet.data.DataIntegrationConfig,
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25 name: "I am a synthetic data example"
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26 },
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27 method:{
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28 _target_: dimet.method.MetabologramIntegrationConfig,
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29 label: "metabologram",
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30 name: "Perform data integration via metabologram visualization",
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31 abs_values_scale_color_bar: {transcripts: null, metabolites:null},
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32 colors_divergent_palette: ['royalblue', 'white', 'red'],
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33 edge_color: ['black','black'],
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34 line_width:['1','1.2'],
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35 display_label_and_value: ${output_options.write_values},
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36 font_size: ${output_options.font_size},
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37 fig_width: ${output_options.fig_width},
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38 figure_format:${output_options.figure_format},
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39 color_nan_elements:'gray',
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40 fig_height: ${output_options.fig_height}
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41 },
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42 columns_metabolites: {ID: metabolite, values: log2FC},
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43 columns_transcripts: {ID: ${deg_one_id}, values: ${deg_one_values}},
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44 compartment: ${compartments},
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45 label: metabologram
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46 }'
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47 '++analysis.method.qualityDistanceOverSpan='${qualityDistanceOverSpan}''
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48 '++analysis.dataset.label='
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49 '+analysis.timepoints=${timepoints}'
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50 '++analysis.method.statistical_test=${statistical_test}'
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51 '++analysis.method.grouping=${groups}'
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52 '++analysis.method.correction_method=${correction_method}'
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53 '++analysis.method.impute_values=${impute_values}'
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54 '++analysis.statistical_test=${statistical_test}'
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55 '++analysis.method.disfit_tail_option="auto"'
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56 '++analysis.dataset.subfolder='
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57 '++analysis.dataset.conditions=${$conditions}'
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58 '++analysis.dataset.pathways=${pathways}'
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59 '++analysis.dataset.transcripts=${transcripts}'
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60 '++analysis.comparisons=${comparisons}'
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61 #if $metadata_path:
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62 '++analysis.dataset.metadata=metadata'
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63 #end if
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64 #if str( $data_input.data_input_selector ) == "abundance":
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65 #if $data_input.abundance_file:
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66 '++analysis.dataset.abundances=abundance'
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67 #end if
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68 #else:
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69 #if $data_input.me_or_frac_contrib_file:
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70 '++analysis.dataset.mean_enrichment=me_or_frac_contrib'
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71 #end if
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72 #end if
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73 @REMOVE_CONFIG@
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74 ]]></command>
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75 <inputs>
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76 <expand macro="input_parameters_metabologram"/>
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77 <expand macro="deg_list"/>
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78 <expand macro="compartments_metabologram"/>
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79
0
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80 <param name="correction_method" type="select" value="bonferroni" display="radio" label="Select multiple test correction to apply" help="Please enter at max 1 method">
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81 <option value="bonferroni">bonferroni</option>
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82 <option value="holm-sidak">holm-sidak</option>
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83 <option value="holm">holm</option>
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84 <option value="simes-hochberg">simes-hochberg</option>
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85 <option value="hommel">hommel</option>
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86 <option value="fdr_bh">fdr_bh</option>
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87 <option value="fdr_by">fdr_by</option>
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88 <option value="fdr_tsbh">fdr_tsbh</option>
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89 <option value="fdr_tsbky">fdr_tsbky</option>
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90 </param>
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91 <param name="qualityDistanceOverSpan" type="float" min="-1.0" max="-0.1" value="-0.3" label="quality Distance Over Span" help="Default value is -0.3."/>
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92 <section name="output_options" title="Output options">
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93 <param name="figure_format" type="select" value="pdf" display="radio" label="Select output figure format" help="Please enter at max 1 format">
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94 <option value="pdf">Pdf</option>
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95 <option value="svg">Svg</option>
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96 </param>
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97 <param name="write_values" type="boolean" value="false" label="Write the values alongside the metabolites and genes names (e.g. L-Alanine: -0.44)"
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98 help="Default value is false."/>
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99 <param name="fig_width" type="integer" min="5" max="20" value="7" label="width of figures"
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100 help="Default value is 7."/>
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101 <param name="fig_height" type="integer" min="5" max="20" value="7" label="heigt of each figure"
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102 help="Default value is 7."/>
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103 <param name="font_size" type="integer" min="1" max="20" value="12" label=" figure font size"
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104 help="Default value is 12."/>
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105 </section>
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106 </inputs>
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107
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108
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109 <outputs>
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110 <collection name="report" type="list">
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111 <discover_datasets pattern="__designation_and_ext__" directory="figures"/>
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112 </collection>
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113 </outputs>
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114 <tests>
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115 <test>
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116
0
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117 <param name="path_kegg_metabolites" ftype="tabular" value="pathways_kegg_metabolites.csv"/>
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118 <param name="path_kegg_transcripts" ftype="tabular" value="pathways_kegg_transcripts.csv"/>
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119 <param name="abundance_file" ftype="tabular" value="rawAbundances.csv"/>
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120 <param name="metadata_path" ftype="tabular" value="example2_metadata.csv"/>
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121 <param name="statistical_test_type" value="parametric"/>
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122 <param name="stat_test" value="Tt"/>
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123 <repeat name="deg_list">
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124 <param name="input" ftype="tabular" value="DEG_comparison_1.csv"/>
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125 <param name="idcol" ftype="integer" value="2"/>
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126 <param name="valuecol" ftype="integer" value="3"/>
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127 <param name="timepoint" value='T0'/>
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128 <repeat name="factor_list">
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129 <param name="condition" value="L-Cycloserine"/>
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130 </repeat>
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131 <repeat name="factor_list">
7
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132 <param name="condition" value="Control"/>
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133 </repeat>
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134 </repeat>
0
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135 <section name="output_options">
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136 <param name="show_values" value="false"/>
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137 <param name="figure_format" value="svg"/>
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138 <param name="figure_width" value="7"/>
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139 <param name="figure_height" value="7"/>
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140 <param name="font_size" value="12"/>
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141 </section>
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142 <output_collection name="report" type="list" count="3">
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143 <element file="AMINOACIDS-L-Cycloserine-T0-Control-T0--DEG_comparison1-abundances-cell.svg" name="AMINOACIDS-L-Cycloserine-T0-Control-T0--DEG_comparison1-abundances-cell" ftype="svg" compare="sim_size" delta="100"/>
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144 <element file="CENTRAL_CARBON_METABOLISM-L-Cycloserine-T0-Control-T0--DEG_comparison1-abundances-cell.svg" name="CENTRAL_CARBON_METABOLISM-L-Cycloserine-T0-Control-T0--DEG_comparison1-abundances-cell" ftype="svg" compare="sim_size" delta="100"/>
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145 <element file="legend-abundances-cell.svg" name="legend-abundances-cell" ftype="svg" compare="sim_size" delta="100"/>
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146 </output_collection>
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147 </test>
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148 </tests>
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149 <help><![CDATA[
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150 This module is part of DIMet: Differential analysis of Isotope-labeled targeted Metabolomics data (https://pypi.org/project/DIMet/).
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151
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152 DIMet Metabologram integrates tracer metabolomics and transcriptomics, in a pathway based fashion.
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153 More precisely, the differential information (Fold Changes (log2 transformed, or not)) of both types of omics
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154 must be given as input, plus the files defining the pathways. You can use the minimal data examples from https://zenodo.org/records/10579891 that contain a minimal example data for running our DIMet Metabologram tool.
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155
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156 The figures in .pdf format are of publication quality, and as they are vectorial images you can open them and customize aesthetics with a professional image software such as Inkscape, Adobe Illustrator, Sketch, CorelDRAW, etc.
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157
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158
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159 **Input data files**
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160
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161 This tool requires the following tab-delimited .csv files:
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162
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163 1. **The metabolomics data**:
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164
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165 1.1 The measures' (or quantifications') files, that can be of two types:
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166
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167 - The total **abundances** (of the metabolites) file,
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168 OR,
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169
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170 - The mean **enrichment** or labelled fractional contributions
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171
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172 1.2 The metadata, a unique file with the description of the samples in your measures' files. This is compulsory, see section **Metadata File Information**.
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173
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174
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175 2. **The transcriptomics data**:
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176
7
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177 2.1 The table with the results of the differential expression analysis (performed with an external tool). Please provide the file with the results of the differential expression analysis of your transcriptomics data. It is recommended to use only the statistically significant **Differentially Expressed Genes (DEG)**. We provide examples in the zenodo (see section **Available data for testing**)
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178
0
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179
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180
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181 3. **The pathways files**:
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182
2
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183
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184 3.1 A file with the pathways and respective gene symbols, which must match with those present in the transcriptomics data. The names of the columns must be the pathways' names, see the minimal data example downloaded from zenodo as explained above. Example:
0
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185
2
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186 ====================== ================== ==================
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187 **PENTHOSE PHOSPHATE** **FATTY ACIDS** ...
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188 ====================== ================== ==================
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189 RPE SCD ...
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190 PGM1 FADS1 ...
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191 PKF BAAT ...
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192 DERA ACOT2 ...
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193 ... ... ...
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194 ====================== ================== ==================
0
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195
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196
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197
2
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198 3.2 A file with the pathways and respective metabolites ID, that must match with those in your metabolomics data. The names of the columns must be the pathways' names, see the minimal data example downloaded from zenodo as explained above. Example:
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199
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200 ====================== ================== ==================
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201 **PENTHOSE PHOSPHATE** **FATTY ACIDS** ...
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202 ====================== ================== ==================
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203 Xyl_P Acetyl_CoA ...
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204 Glc_6P Palmitate ...
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205 Rib_6P Stearate ...
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206 ... ... ...
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207 ====================== ================== ==================
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208
0
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209 **Measures' files**
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210
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211 The measure's files must be organized as matrices:
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212 - The first column must contain Metabolite IDs that are unique (not repeated) within the file.
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213
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214 - The rest of the columns correspond to the samples
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215
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216 - The rows correspond to the metabolites
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217
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218 - The values must be tab separated, with the first row containing the sample/column labels.
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219
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220 See the following examples of measures files:
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221
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222
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223 Example - Metabolites **abundances**:
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224
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225 =============== ================== ================== ================== ================== ================== ==================
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226 ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06**
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227 =============== ================== ================== ================== ================== ================== ==================
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228 2_3-PG 8698823.9926 10718737.7217 10724373.9 8536484.5 22060650 28898956
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229 2-OHGLu 36924336 424336 92060650 45165 84951950 965165051
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230 Glc6P 2310 2142 2683 1683 012532068 1252172
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231 Gly3P 399298 991656565 525195 6365231 89451625 4952651963
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232 IsoCit 0 0 0 84915613 856236 954651610
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233 =============== ================== ================== ================== ================== ================== ==================
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234
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235 Example - mean **enrichment** or labeled fractional contributions:
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236
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237 =============== ================== ================== ================== ================== ================== ==================
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238 ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06**
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239 =============== ================== ================== ================== ================== ================== ==================
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240 2_3-PG 0.9711 0.968 0.9909 0.991 0.40 0.9
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241 2-OHGLu 0.01719 0.0246 0.554 0.555 0.73 0.68
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242 Glc6P 0.06 0.66 2683 0.06 2068 2172
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243 Gly3P 0.06 0.06 0.06 1 5 3
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244 IsoCit 0.06 1 0.49 0.36 6 10
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245 =============== ================== ================== ================== ================== ================== ==================
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246
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247
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248
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249
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250
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251 **Metadata File Information**
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252
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253 Provide a tab-separated file that has the names of the samples in the first column and one header row.
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254 Column names must be exactly in this order:
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255
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256 name_to_plot
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257 condition
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258 timepoint
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259 timenum
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260 compartment
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261 original_name
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262
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263
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264 Example **Metadata File**:
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265
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266
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267 ==================== =============== ============= ============ ================ =================
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268 **name_to_plot** **condition** **timepoint** **timenum** **compartment** **original_name**
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269 -------------------- --------------- ------------- ------------ ---------------- -----------------
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270 Control_cell_T0-1 Control T0 0 cell MCF001089_TD01
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271 Control_cell_T0-2 Control T0 0 cell MCF001089_TD02
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272 Control_cell_T0-3 Control T0 0 cell MCF001089_TD03
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273 Tumoral_cell_T0-1 Tumoral T0 0 cell MCF001089_TD04
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274 Tumoral_cell_T0-2 Tumoral T0 0 cell MCF001089_TD05
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275 Tumoral_cell_T0-3 Tumoral T0 0 cell MCF001089_TD06
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276 Tumoral_cell_T24-1 Tumoral T24 24 cell MCF001089_TD07
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277 Tumoral_cell_T24-2 Tumoral T24 24 cell MCF001089_TD08
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278 Tumoral_cell_T24-3 Tumoral T24 24 cell MCF001090_TD01
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279 Control_med_T24-1 Control T24 24 med MCF001090_TD02
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280 Control_med_T24-2 Control T24 24 med MCF001090_TD03
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281 Tumoral_med_T24-1 Tumoral T24 24 med MCF001090_TD04
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282 Tumoral_med_T24-2 Tumoral T24 24 med MCF001090_TD05
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283 Control_med_T0-1 Control T0 0 med MCF001090_TD06
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284 Tumoral_med_T0-1 Tumoral T0 0 med MCF001090_TD07
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285 Tumoral_med_T0-2 Tumoral T0 0 med MCF001090_TD08
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286 ==================== =============== ============= ============ ================ =================
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287
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288
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289 The column **original_name** must have the names of the samples as given in your data.
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290
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291 The column **name_to_plot** must have the names as you want them to be (or set identical to original_name if you prefer). To set names that
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292 are meaningful is a better choice, as we will take them to display the results.
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293
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294 The column **timenum** must contain only the numeric part of the timepoint, for example 2,0, 10, 100 (this means, without letters ("T", "t", "s", "h" etc)
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295 nor any other symbol). Make sure these time numbers are in the same units (but do not write the units here!).
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296
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297 The column **compartment** is an abbreviation, coined by you, for the compartments. This will be used for the results' files names: the longer the
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298 compartments names are, the longer the output files' names! Please pick short and clear abbreviations to fill this column.
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299
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300
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301 **Running the analysis**
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302
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303 You can precise how you want your analysis to be executed with the parameters, which are of two types:
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304
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305 **a. Parameters proper to the metabolome differential analysis (that runs automatically before the integration)**:
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306
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307 - **Conditions and timepoint**:
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308
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309 For each comparison to run on the metabolomics data, you can define the Conditions to compare, at a chosen time point, through the box 'Deregulated gene set': follow the instructions and choose the correct order of Conditions (the last must be the reference or control).
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310 To add a second comparison, click the 'Insert Deregulated gene set' button.
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311 You can insert and define as many boxes ('Deregulated gene set') as comparisons you want to perform.
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312
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313 - **statistical_test**: choose the specific statistical test to be applied.
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314
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315 Kruskal-Wallis, Mann-Whitney, Wilcoxon’s signed rank test, Wilcoxon’s rank sum test
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316 t-test, and permutation test are currently offered (we use the trusted functions from scipy library https://docs.scipy.org/doc/scipy/reference/stats.html).
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317
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318 For the permutation test, we have established as test statistic, the absolute difference of geometric means of the two compared groups.
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319
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320 - **qualityDistanceOverSpan**: a normalized distance between the intervals of values of the compared groups, that is the cutoff for
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321
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322 considering a minimal acceptable "separation", and therefore, to be suitable for statistical testing. A 'distance/span' == 1 is a perfect separation,
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323 whereas if 'distance/span' < 0 there is no separation.
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324 To use with caution in case of important dispersion of your intra-group values. Default is -0.3 (not stringent)
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325
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326 - **correction_method**: one of the methods for multiple testing correction available in statsmodels library (bonferroni, fdr_bh, sidak, among others, see https://www.statsmodels.org/dev/generated/statsmodels.stats.multitest.multipletests.html).
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327
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328 - **compartment**: one of the compartments present in your data.
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329
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330 **b. Parameters proper to the integration with transcriptomics (that runs automatically after the metabolome differential analysis)**:
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331
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332 - **Deregulated genes set file**: Corresponds to the transcriptomics data, as explained in **Input data files** section.
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333
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334 For each 'Deregulated gene set' box, a single **Differentially Expressed Genes (DEG)** file must be added, and must match with the metabolomics comparison set in the same box. Additional files can be added with the 'Insert deregulated gene set' button,
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335 see also the subsection 'Conditions and timepoint' above.
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336
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337 - **pathways** : files for the pathways, as explained in **Input data files** section
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338
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339
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340 Overall, the metabologram module provides hints on use that will guide you, in the same menus and boxes of the parameters.
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341
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342
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343 **Output**
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344
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345 The output consists of one figure by metabologram, and a color key bar legend valid for all metabolograms produced
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346
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347 **Available data for testing**
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348
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349 You can test our tool with the data from our manuscript https://zenodo.org/record/10579862 (the pertinent
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350 files for you are located in the subfolders inside the data folder).
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351 You can also use the minimal data examples from https://zenodo.org/record/10579891
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352
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353 ]]>
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354 </help>
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355 <expand macro="citations" />
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356 </tool>