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view dimet_differential_multigroup_analysis.xml @ 6:efe13e94f70d draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/DIMet commit 3dba8748fbc8cc8e89ffc08e5febe0a0527a96a5
| author | iuc |
|---|---|
| date | Fri, 21 Jun 2024 18:54:18 +0000 |
| parents | b581ea4908ae |
| children |
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<tool id="dimet_@EXECUTABLE@" name="dimet @TOOL_LABEL@" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="20.05"> <description> Differential analysis of 3 or more chosen groups of tracer metabolomics data (by DIMet) </description> <macros> <token name="@TOOL_LABEL@">differential multigroup analysis</token> <token name="@EXECUTABLE@">differential_multigroup_analysis</token> <import>macros.xml</import> </macros> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ @INIT_CONFIG@ @INIT_DIFF_MULTIGROUP_ANALYSIS@ @INIT_DATATYPES@ @INIT_GROUPS@ @INIT_PLOT_CONDITIONS@ @INIT_TIMEPOINTS@ @INIT_MULTIGROUP_COMPARISONS@ HYDRA_FULL_ERROR=1 python -m dimet '++hydra.run.dir=.' '++figure_path=figures' '++table_path=tables' '++analysis={ dataset:{ _target_:dimet.data.DatasetConfig, name: "Galaxy DIMet run" }, method:{ _target_: dimet.method.MultiGroupComparisonConfig, label: multi_group_comparison, name: "Multi group statistical comparison using Kruskal-Wallis test" }, label: multi_group_comparison, datatypes:${datatypes_avail} }' '++analysis.method.datatypes=${datatypes_avail}' '++analysis.timepoints=${timepoints}' '++analysis.conditions=${comparisons}' '++analysis.dataset.label=' '++analysis.method.correction_method=${correction_method}' '++analysis.method.impute_values=${impute_values}' '++analysis.dataset.subfolder=' '++analysis.method.grouping=${groups}' '++analysis.dataset.conditions=${conditions}' #if $metadata_path: '++analysis.dataset.metadata=metadata' #end if #if str( $data_input.data_input_selector ) == "abundance": #if $data_input.abundance_file: '++analysis.dataset.abundances=abundance' #end if #elif str( $data_input.data_input_selector ) == "mean_enrichment": #if $data_input.me_or_frac_contrib_file: '++analysis.dataset.mean_enrichment=me_or_frac_contrib' #end if #elif str( $data_input.data_input_selector ) == "isotop_prop": #if $data_input.isotop_prop_file: '++analysis.dataset.isotopologue_proportions=isotop_prop' #end if #else #if $data_input.isotop_abs_file: '+analysis.dataset.isotopologues=isotop_abs' #end if #end if @REMOVE_CONFIG@ ]]></command> <inputs> <expand macro="input_parameters_multi_diff_analysis"/> <expand macro="plot_factor_list"/> <expand macro="timepoint_multigroup"/> <expand macro="compartments"/> <expand macro="correction_method"/> </inputs> <outputs> <collection name="report" type="list"> <discover_datasets pattern="__designation__" directory="tables" format="tabular"/> </collection> </outputs> <tests> <test> <param name="data_input_selector" value="abundance" /> <param name="abundance_file" ftype="tabular" value="rawAbundances3.csv"/> <param name="metadata_path" ftype="tabular" value="example3_metadata.csv"/> <param name="correction_method" value="bonferroni"/> <repeat name="plot_factor_list"> <param name="condition" value="Control"/> </repeat> <repeat name="plot_factor_list"> <param name="condition" value="Cond1"/> </repeat> <repeat name="plot_factor_list"> <param name="condition" value="Cond2"/> </repeat> <param name="timepoint" value="T0h,T2h"/> <param name="compartments" value="cell"/> <output_collection name="report" type="list" count="1"> <element file="abundance--cell--multigroup.tsv" name="abundance--cell--multigroup.tsv" ftype="tabular"/> </output_collection> </test> </tests> <help><![CDATA[ This module is part of DIMet: Differential analysis of Isotope-labeled targeted Metabolomics data (https://pypi.org/project/DIMet/). **Input data files** This tool computes the Kruskal-Wallis test over 3 or more groups, to evaluate if at least one group is significantly different to the other groups (H0: median of all of the groups is equal). For illustration see the section **Metadata File Information** which contains three conditions: Control, Core_mass and Edge_tissue, across one single time point, thus 3 groups (number-of-groups-in-my-data = number-of-conditions x number-of-timepoints)). This tool requires (at max.) 5 tab-delimited .csv files as inputs. There are two types of files: - The measures' (or quantifications') files, that can be of 4 types. - The metadata, a unique file with the description of the samples in your measures' files. This is compulsory. For running DIMet @EXECUTABLE@ you need **at least one** file of measures: - The total **abundances** (of the metabolites) file - The mean **enrichment** or labelled fractional contributions - The **isotopologues** absolute values files (optional) - The **isotopologue proportions** file (optional) and one metadata file, WHICH IS COMPULSORY, see section **Metadata File Information**. The measure's files must be organized as matrices: - The first column must contain Metabolite IDs that are unique (not repeated) within the file. - The rest of the columns correspond to the samples - The rows correspond to the metabolites - The values must be tab separated, with the first row containing the sample/column labels. See the following examples of measures' files: Example - Metabolites **abundances**: =============== ================== ================== ================== ================== ================== ================== ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06** =============== ================== ================== ================== ================== ================== ================== 2_3-PG 8698823.9926 10718737.7217 10724373.9 8536484.5 22060650 28898956 2-OHGLu 36924336 424336 92060650 45165 84951950 965165051 Glc6P 2310 2142 2683 1683 012532068 1252172 Gly3P 399298 991656565 525195 6365231 89451625 4952651963 IsoCit 0 0 0 84915613 856236 954651610 =============== ================== ================== ================== ================== ================== ================== Example - mean **enrichment** or labeled fractional contributions: =============== ================== ================== ================== ================== ================== ================== ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06** =============== ================== ================== ================== ================== ================== ================== 2_3-PG 0.9711 0.968 0.9909 0.991 0.40 0.9 2-OHGLu 0.01719 0.0246 0.554 0.555 0.73 0.68 Glc6P 0.06 0.66 2683 0.06 2068 2172 Gly3P 0.06 0.06 0.06 1 5 3 IsoCit 0.06 1 0.49 0.36 6 10 =============== ================== ================== ================== ================== ================== ================== Example - **Isotopologues** =============== ================== ================== ================== ================== ================== ================== ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06** =============== ================== ================== ================== ================== ================== ================== 2_3-PG_m+0 206171.4626 285834.0353 36413.27637 27367.17784 6171.4626 119999 2_3-PG_m+1 123 432 101 127 206171.4626 119999 2_3-PG_m+2 133780.182 161461.2364 182631.3947 132170.3807 358749.348 848754.36 2_3-PG_m+3 8358749.348 10271010.45 10505228.3 8376820.028 62163.30727 1088.8963 2-OHGLu_m+0 5550339.322 6072872.833 3855047.791 3216178.72 8358749.348 10271010.45 2-OHGLu_m+1 0.0 0.0 0.0 0.0 206171.4626 285834.0353 =============== ================== ================== ================== ================== ================== ================== Example - **Isotopologue proportions**: =============== ================== ================== ================== ================== ================== ================== ID **MCF001089_TD01** **MCF001089_TD02** **MCF001089_TD03** **MCF001089_TD04** **MCF001089_TD05** **MCF001089_TD06** =============== ================== ================== ================== ================== ================== ================== 2_3-PG_m+0 0.023701408 0.026667837 0.003395407 0.05955 0.034383527 0.12 2_3-PG_m+1 0.0 0.0 0.0 0.0 0.4 0.12 2_3-PG_m+2 0.015379329 0.01506 0.017029723 0.35483229 0.54131313 0.743 2_3-PG_m+3 0.960919263 0.958268099 0.97957487 0.581310816 0.017029723 0.017 2-OHGLu_m+0 0.972778716 0.960016157 0.238843937 0.234383527 0.9998888 0.015064063 2-OHGLu_m+1 0.0 0.0 0.0 0.0 0.0001112 0.960919263 =============== ================== ================== ================== ================== ================== ================== **Metadata File Information** Provide a tab-separated file that has the names of the samples in the first column and one header row. Column names must be exactly in this order: name_to_plot condition timepoint timenum compartment original_name Example **Metadata File**: ==================== =============== ============= ============ ================ ================= **name_to_plot** **condition** **timepoint** **timenum** **compartment** **original_name** -------------------- --------------- ------------- ------------ ---------------- ----------------- Control_cell-1 Control T0 0 cell MCF001089_TD01 Control_cell-2 Control T0 0 cell MCF001089_TD02 Control_cell-3 Control T0 0 cell MCF001089_TD03 CoreMass_cell-1 Core_mass T0 0 cell MCF001089_TD04 CoreMass_cell-2 Core_mass T0 0 cell MCF001089_TD05 CoreMass_cell-3 Core_mass T0 0 cell MCF001089_TD06 EdgeTiss_cell-1 Edge_tissue T0 0 cell MCF001089_TD07 EdgeTiss_cell-2 Edge_tissue T0 0 cell MCF001089_TD08 EdgeTiss_cell-3 Edge_tissue T0 0 cell MCF001089_TD09 ==================== =============== ============= ============ ================ ================= The column **original_name** must have the names of the samples as given in your data. 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 are meaningful is a better choice, as we will take them to display the results. 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) nor any other symbol). Make sure these time numbers are in the same units (but do not write the units here!). The column **compartment** is an abbreviation, coined by you, for the compartments. This will be used for the results' files names: the longer the compartments names are, the longer the output files' names! Please pick short and clear abbreviations to fill this column. **Running the analysis** You can precise how you want your analysis to be executed, with the parameters: - **comparisons** : the groups you want to select for comparison in the multigroup analysis (Note that **comparisons** parameter in the multigroup analysis does not have the same usage as in the pairwise differential analysis). - **datatypes** : the measures type(s) that you want to run - **correction_method** : one of the methods for multiple testinc correction available in statsmodels library (bonferroni, fdr_bh, sidak, among others, see https://www.statsmodels.org/dev/generated/statsmodels.stats.multitest.multipletests.html). There exist hints on use that will guide you, next to the parameters. For more information about the implemented statistical tests, please visit: https://github.com/cbib/DIMet/wiki/2-Statistical-tests The output files are explained in https://github.com/cbib/DIMet/wiki/3-Output **Available data for testing** You can test our tool with the data from our manuscript https://zenodo.org/record/10579862 (the pertinent files for you are located in the subfolders inside the data folder). You can also use the minimal data examples from https://zenodo.org/record/10579891 ]]> </help> <expand macro="citations"/> </tool>