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author | bimib |
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date | Tue, 13 Nov 2018 07:34:43 -0500 |
parents | 02577e65dcca |
children | 146cb8e171b8 |
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<tool id="MaREA" name="Metabolic Enrichment Analysis" version="1.0.0"> <description>for Galaxy</description> <macros> <import>marea_macros.xml</import> </macros> <requirements> <requirement type="package">pandas</requirement> <requirement type="package">scipy</requirement> <requirement type="package">cobra</requirement> <requirement type="package">python-libsbml</requirement> <requirement type="package">lxml</requirement> <requirement type="package">svglib</requirement> <requirement type="package">reportlab</requirement> </requirements> <command detect_errors="exit_code"> <![CDATA[ python $__tool_directory__/marea.py --rules_selector $cond_rule.rules_selector #if $cond_rule.rules_selector == 'Custom': --custom ${cond_rule.Custom_rules} --yes_no ${cond_rule.cond_map.yes_no} #if $cond_rule.cond_map.yes_no == 'yes': --custom_map $cond_rule.cond_map.Custom_map #end if #end if --none $None --pValue $pValue --fChange $fChange --tool_dir $__tool_directory__ --option $cond.type_selector --out_log $log #if $cond.type_selector == 'datasets': --input_datas #for $data in $cond.input_Datasets: ${data.input} #end for --names #for $data in $cond.input_Datasets: ${data.input_name} #end for #elif $cond.type_selector == 'dataset_class': --input_data ${input_data} --input_class ${input_class} #end if ]]> </command> <inputs> <conditional name="cond_rule"> <expand macro="options"/> <when value="HMRcore"> </when> <when value="Recon"> </when> <when value="Custom"> <param name="Custom_rules" type="data" format="tabular, csv, tsv, xml" label="Custom rules" /> <conditional name="cond_map"> <param name="yes_no" type="select" label="Custom map? (optional)"> <option value="no" selected="true">no</option> <option value="yes">yes</option> </param> <when value="yes"> <param name="Custom_map" argument="--custom_map" type="data" format="xml, svg" label="custom-map.svg"/> </when> <when value="no"> </when> </conditional> </when> </conditional> <conditional name="cond"> <param name="type_selector" argument="--option" type="select" label="Input format:"> <option value="datasets" selected="true">RNAseq of group 1 + RNAseq of group 2 + ... + RNAseq of group N</option> <option value="dataset_class">RNAseq of all samples + sample group specification</option> </param> <when value="datasets"> <repeat name="input_Datasets" title="RNAseq" 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="Defalut: Dataset" /> </repeat> </when> <when value="dataset_class"> <param name="input_data" argument="--input_data" type="data" format="tabular, csv, tsv" label="RNAseq of all samples" /> <param name="input_class" argument="--input_class" type="data" format="tabular, csv, tsv" label="Sample group specification" /> </when> </conditional> <param name="None" argument="--none" type="boolean" truevalue="true" falsevalue="false" checked="true" label="(A and NaN) solved as (A)?" /> <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="1.5" min="1" label="Fold-Change threshold" help="min value 1" /> </inputs> <outputs> <data format="txt" name="log" label="Log" /> <collection name="map_svg" type="list" label="Graphical results (.svg)"> <filter>(cond_rule['rules_selector'] == 'HMRcore') or ((cond_rule['rules_selector'] == 'Custom') and (cond_rule['cond_map']['yes_no'] == 'yes'))</filter> <discover_datasets pattern="__name_and_ext__" directory="map_svg" /> </collection> <collection name="map_pdf" type="list" label="Graphical results (.pdf)"> <filter>(cond_rule['rules_selector'] == 'HMRcore') or ((cond_rule['rules_selector'] == 'Custom') and (cond_rule['cond_map']['yes_no'] == 'yes'))</filter> <discover_datasets pattern="__name_and_ext__" directory="map_pdf" /> </collection> <collection name="table_out" type="list" label="Tabular results"> <discover_datasets pattern="__name_and_ext__" directory="table_out" /> </collection> </outputs> <tests> <test> <param name="pValue" value="0.56"/> <output name="log" file="log.txt"/> </test> </tests> <help> <![CDATA[ What it does ------------- This tool analyzes RNA-seq dataset(s) as described in Graudenzi et al."`MaREA`_: Metabolic feature extraction, enrichment and visualization of RNAseq data" bioRxiv (2018): 248724. Accepted files are: - option 1) two or more RNA-seq datasets, each referring to samples in a given condition/class. The user can specify a label for each class (as e.g. "*classA*" and "*classB*"); - option 2) one RNA dataset and one class-file specifying the class/condition each sample belongs to. Optional files: - custom GPR (Gene-Protein-Reaction) rules. Two accepted formats: * (Cobra Toolbox and CobraPy compliant) xml of metabolic model; * .csv file specifyig for each reaction ID (column 1) the corresponding GPR rule (column 2). - 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 (downlodable as .svg): visualizing up- and down-regulated reactions between a pair of conditions/classes; 3) a log file (.txt). RNA-seq datasets format: tab-separated text files, reporting the expression level (e.g., TPM, RPKM, ...) of each gene (row) for a given sample (column). Header: sample ID. Class-file format: each row of the class-file reports the sample ID (column1) and the label of the class/condition the sample belongs to (column 2). To calculate P-Values and Fold-Changes and to generate maps, comparisons are performed for each possible pair of classes. 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 ------------- **"Custom Rules"** option: Custom Rules Dastaset: @CUSTOM_RULES_EXEMPLE@ **"RNAseq of group 1 + RNAseq of group 2 + ... + RNAseq of group N"** option: RNA-seq Dataset 1: @DATASET_EXEMPLE1@ RNA-seq Dataset 2: @DATASET_EXEMPLE2@ **"RNAseq of all samples + sample group specification"** option: RNA-seq Dataset: @DATASET_EXEMPLE1@ Class-file: +------------+------------+ | Patient_ID | class | +============+============+ | TCGAAA3529 | MSI | +------------+------------+ | TCGAA62671 | MSS | +------------+------------+ | TCGAA62672 | MSI | +------------+------------+ | .. 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`_. @REFERENCE@ .. _MaREA: https://www.biorxiv.org/content/early/2018/01/16/248724 .. _Convert delimiters to TAB: https://usegalaxy.org/?tool_id=Convert+characters1&version=1.0.0&__identifer=6t22teyofhj .. _MaREA cluster analysis: http://link del tool di cluster.org ]]> </help> <expand macro="citations" /> </tool>