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author | francesco_lapi |
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date | Thu, 21 Nov 2024 09:21:49 +0000 |
parents | 7e703e546998 |
children | 84b31c9100ad |
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<tool id="MaREA" name="Metabolic Reaction Enrichment Analysis" version="2.0.0"> <macros> <import>marea_macros.xml</import> </macros> <requirements> <requirement type="package" version="1.24.4">numpy</requirement> <requirement type="package" version="2.0.3">pandas</requirement> <requirement type="package" version="5.2.2">lxml</requirement> <requirement type="package" version="1.10.1">scipy</requirement> <requirement type="package" version="1.5.1">svglib</requirement> <requirement type="package" version="2.2.3">pyvips</requirement> <requirement type="package" version="2.7.1">cairosvg</requirement> <requirement type="package" version="0.29.0">cobra</requirement> </requirements> <command detect_errors="exit_code"> <![CDATA[ python $__tool_directory__/marea.py --tool_dir $__tool_directory__ --option $cond.type_selector --out_log $log #if $cond.type_selector == 'datasets': --using_RAS $cond.using_ras.check --using_RPS $cond.using_rps.check #if $cond.using_ras.check == 'true': --input_datas #for $data in $cond.using_ras.input_datasets: ${data.input} #end for --names #for $data in $cond.using_ras.input_datasets: ${data.input_name} #end for #end if #if $cond.using_rps.check == 'true': --input_datas_rps #for $data in $cond.using_rps.input_datasets_rps: ${data.input_rps} #end for --names_rps #for $data in $cond.using_rps.input_datasets_rps: ${data.input_name_rps} #end for #end if #elif $cond.type_selector == 'dataset_class': --using_RAS $cond.using_ras_all.check --using_RPS $cond.using_rps_all.check #if $cond.using_ras_all.check == 'true': --input_data ${cond.using_ras_all.input_data} --input_class ${cond.using_ras_all.input_class} #end if #if $cond.using_rps_all.check == 'true': --input_data_rps ${cond.using_rps_all.input_data_rps} --input_class_rps ${cond.using_rps_all.input_class_rps} #end if #end if --comparison ${comparis.comparison} #if $comparis.comparison == 'onevsmany' --control '${cond.comparis.controlgroup}' #end if --choice_map '${cond_choice_map.choice_map}' #if $cond_choice_map.choice_map == 'Custom': --custom_map ${cond_choice_map.custom_map} #end if #if $advanced.choice == 'true': --pValue ${advanced.pValue} --fChange ${advanced.fChange} --generate_svg ${advanced.generateSvg} --generate_pdf ${advanced.generatePdf} --net ${advanced.netRPS} #else --pValue 0.05 --fChange 1.2 --generate_svg false --generate_pdf true --net false #end if ]]> </command> <inputs> <conditional name="cond"> <param name="type_selector" argument="--option" type="select" label="Input format:"> <option value="datasets" selected="true">RAS of group 1 + RAS of group 2 + ... + RAS of group N</option> <option value="dataset_class">RAS of all samples + sample group specification</option> </param> <when value="datasets"> <conditional name = "using_ras"> <param name = "check" argument = "--using_ras" type = "boolean" checked = "true" label = "Using RAS datasets." /> <when value = "true"> <repeat name="input_datasets" title="RAS dataset" min="2"> <param name="input" argument="--input_datas" type="data" format="tabular, csv, tsv" label="add dataset" /> <param name="input_name" argument="--names" type="text" label="Dataset's name:" value="Dataset" help="Default: Dataset" /> </repeat> </when> </conditional> <conditional name = "using_rps"> <param name = "check" argument = "--using_rps" type = "boolean" checked = "false" label = "Using RPS datasets." /> <when value = "true"> <repeat name="input_datasets_rps" title="RPS dataset" min="2"> <param name="input_rps" argument="--input_datas_rps" type="data" format="tabular, csv, tsv" label="add dataset" /> <param name="input_name_rps" argument="--names_rps" type="text" label="Dataset's name:" value="Dataset" help="Default: Dataset" /> </repeat> </when> </conditional> </when> <when value="dataset_class"> <conditional name = "using_ras_all"> <param name = "check" argument = "--using_ras_all" type = "boolean" checked = "true" label = "Using RAS datasets." /> <when value = "true"> <param name="input_data" argument="--input_data" type="data" format="tabular, csv, tsv" label="RAS of all samples" /> <param name="input_class" argument="--input_class" type="data" format="tabular, csv, tsv" label="Sample group specification" /> </when> </conditional> <conditional name = "using_rps_all"> <param name = "check" argument = "--using_rps_all" type = "boolean" checked = "false" label = "Using RPS datasets." /> <when value = "true"> <param name="input_data_rps" argument="--input_data_rps" type="data" format="tabular, csv, tsv" label="RPS of all samples" /> <param name="input_class_rps" argument="--input_class_rps" type="data" format="tabular, csv, tsv" label="Sample group specification" /> </when> </conditional> </when> </conditional> <conditional name="comparis"> <param name="comparison" argument="--comparison" type="select" label="Groups comparison:"> <option value="manyvsmany" selected="true">One vs One</option> <option value="onevsrest">One vs All</option> <option value="onevsmany">One vs Control</option> </param> <when value="onevsmany"> <param name="controlgroup" argument="--controlgroup" type="text" label="Control group label:" value="0" help="Name of group label to be compared to others"/> </when> </conditional> <conditional name="cond_choice_map"> <param name="choice_map" argument="--choice_map" type="select" label="Choose metabolic map:"> <option value="HMRcore" selected="true">HMRcore</option> <option value="ENGRO2">ENGRO2</option> <option value="Custom">Custom</option> </param> <when value="Custom"> <param name="custom_map" argument="--custom_map" type="data" format="xml, svg" label="custom-map.svg"/> </when> </conditional> <conditional name="advanced"> <param name="choice" type="boolean" checked="false" label="Use advanced options?" help="Use this options to choose custom parameters for evaluation: pValue, Fold-Change threshold, how to solve (A and NaN) and specify output maps."> <option value="true" selected="true">No</option> <option value="false">Yes</option> </param> <when value="true"> <param name="pValue" argument="--pValue" type="float" size="20" value="0.05" max="1" min="0" label="P-value threshold:" help="min value 0" /> <param name="fChange" argument="--fChange" type="float" size="20" value="1.2" min="1" label="Fold-Change threshold:" help="min value 1" /> <param name="generateSvg" argument="--generateSvg" type="boolean" checked="false" label="Generate SVG map" help="should the program generate an editable svg map of the processes?" /> <param name="generatePdf" argument="--generatePdf" type="boolean" checked="true" label="Generate PDF map" help="should the program return a non editable (but displayble) pdf map of the processes?" /> <param name="netRPS" argument="--net" type="boolean" checked="false" label="Should RPS enrichment use net values?" help="If checked and RPS datasets are present the arrow tips of a reversible arrow will be colored with the net contribution of both directions' RPS values" /> </when> </conditional> </inputs> <outputs> <data format="txt" name="log" label="MaREA - Log" /> <collection name="results" type="list" label="MaREA - Results"> <discover_datasets pattern="__name_and_ext__" directory="result"/> </collection> </outputs> <help> <![CDATA[ What it does ------------- This tool analyzes and visualizes differences in the Reaction Activity Scores (RASs) of groups of samples, as computed by the Expression2RAS tool, of groups of samples. Accepted files are: - option 1) two or more RAS datasets, each referring to samples in a given group. The user can specify a label for each group (as e.g. "classA" and "classB"); - option 2) one RAS dataset and one group-file specifying the group each sample belongs to. RAS datasets format: tab-separated text files, reporting the RAS value of each reaction (row) for a given sample (column). Column header: sample ID. Row header: reaction ID. Optional files: - custom svg map. Graphical elements must have the same IDs of reactions. See HmrCore svg map for an example. The tool generates: - 1) a tab-separated file: reporting fold-change and p-values of reaction activity scores (RASs) between a pair of conditions/classes; - 2) a metabolic map file (downloadable as .svg): visualizing up- and down-regulated reactions between a pair of conditions/classes; - 3) a log file (.txt). Output options: To calculate P-Values and Fold-Changes and to enrich maps, comparisons are performed for each possible pair of groups (default option ‘One vs One’). Alternative options are: - comparison of each group vs. the rest of samples (option ‘One vs Rest’) - comparison of each group vs. a control group (option ‘One vs Control). If this option is selected the user must indicate the control group label. Output files will be named as classA_vs_classB. Reactions will conventionally be reported as up-regulated (down-regulated) if they are significantly more (less) active in class having label "classA". Example input ------------- "RAS of group 1 + RAS of group 2 + ... + RAS of group N" option: RAS Dataset 1: +------------+----------------+----------------+----------------+ | Reaction ID| TCGAA62670 | TCGAA62671 | TCGAA62672 | +============+================+================+================+ | r1642 | 0.523167 | 0.371355 | 0.925661 | +------------+----------------+----------------+----------------+ | r1643 | 0.568765 | 0.765567 | 0.456789 | +------------+----------------+----------------+----------------+ | r1640 | 0.876545 | 0.768933 | 0.987654 | +------------+----------------+----------------+----------------+ | r1641 | 0.456788 | 0.876543 | 0.876542 | +------------+----------------+----------------+----------------+ | r1646 | 0.876543 | 0.786543 | 0.897654 | +------------+----------------+----------------+----------------+ RAS Dataset 2: +------------+----------------+----------------+----------------+ | Reaction ID| TCGAA62670 | TCGAA62671 | TCGAA62672 | +============+================+================+================+ | r1642 | 0.523167 | 0.371355 | 0.925661 | +------------+----------------+----------------+----------------+ | r1643 | 0.568765 | 0.765567 | 0.456789 | +------------+----------------+----------------+----------------+ | r1640 | 0.876545 | 0.768933 | 0.987654 | +------------+----------------+----------------+----------------+ | r1641 | 0.456788 | 0.876543 | 0.876542 | +------------+----------------+----------------+----------------+ | r1646 | 0.876543 | 0.786543 | 0.897654 | +------------+----------------+----------------+----------------+ "RAS of all samples + sample group specification" option: RAS Dataset: +------------+----------------+----------------+----------------+ | Reaction ID| TCGAA62670 | TCGAA62671 | TCGAA62672 | +============+================+================+================+ | r1642 | 0.523167 | 0.371355 | 0.925661 | +------------+----------------+----------------+----------------+ | r1643 | 0.568765 | 0.765567 | 0.456789 | +------------+----------------+----------------+----------------+ | r1640 | 0.876545 | 0.768933 | 0.987654 | +------------+----------------+----------------+----------------+ | r1641 | 0.456788 | 0.876543 | 0.876542 | +------------+----------------+----------------+----------------+ | r1646 | 0.876543 | 0.786543 | 0.897654 | +------------+----------------+----------------+----------------+ Group-file +---------------+-----------+ | Patient ID | Class | +===============+===========+ | TCGAAA3529 | MSI | +---------------+-----------+ | TCGAA62671 | MSS | +---------------+-----------+ | TCGAA62672 | MSI | +---------------+-----------+ Advanced options ---------------- P-Value threshold: the threshold used for significance Kolmogorov-Smirnov (KS) test, to verify whether the distributions of RASs over the samples in two sets are significantly different Fold-Change threshold: threshold of the fold-change between the average RAS of two groups. Among the reactions that pass the KS test, only fold-change values larger than the indicated threshold will be visualized on the output metabolic map; .. class:: infomark **TIP**: If your data is not TAB delimited, use `Convert delimiters to TAB`_. .. class:: infomark **TIP**: If your dataset is not split into classes, use MaREA cluster analysis. .. class:: infomark **TIP**: This tool using the RAS scores computed by Ras generator tool. @REFERENCE@ .. _Ras tool: http://bimib.disco.unimib.it:5555/?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fbimib%2Fmarea%2FMaREA+RAS+Generator%2F1.0.6&version=1.0.6&__identifer=auulv6gbp76 .. _Convert delimiters to TAB: http://bimib.disco.unimib.it:5555/?tool_id=Convert+characters1&version=1.0.0&__identifer=76g7trea4j6 .. _MaREA cluster analysis: http://bimib.disco.unimib.it:5555/?tool_id=toolshed.g2.bx.psu.edu%2Frepos%2Fbimib%2Fmarea%2FMaREA_cluester%2F1.1.2&version=1.1.2&__identifer=lxbyzn2me9 ]]> </help> <expand macro="citations" /> </tool>