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author | bimib |
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date | Tue, 06 Nov 2018 03:16:21 -0500 |
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children | 9e63d5f02d62 |
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<tool id="MaREA" name="Metabolic Enrichment Analysis"> <description>for Galaxy</description> <requirements> <requirement type="package">pandas</requirement> <requirement type="package">scipy</requirement> <requirement type="package">lxml</requirement> <requirement type="package">svglib</requirement> <requirement type="package">reportlab</requirement> <requirement type="package">cobrapy</requirement> <requirement type="package">python-libsbml</requirement> </requirements> <command> <![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"> <param name="rules_selector" type="select" label="Gene-Protein-Reaction rules:"> <option value="HMRcore" selected="true">HMRcore rules</option> <option value="Recon">Recon 2.2 rules</option> <option value="Custom">Custom rules</option> </param> <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" type="data" format="xml, svg" label="custom-map.svg"/> </when> </conditional> </when> </conditional> <conditional name="cond"> <param name="type_selector" 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" type="data" min="2"> <param name="input" type="data" format="tabular, csv, tsv" label="add dataset"/> <param name="input_name" type="text" label="Dataset's name:" value="Dataset" help="Defalut: Dataset"/> </repeat> </when> <when value="dataset_class"> <param name="input_data" type="data" format="tabular, csv, tsv" label="RNAseq of all samples"/> <param name="input_class" type="data" format="tabular, csv, tsv" label="Sample group specification"/> </when> </conditional> <param name="None" type="boolean" truevalue="true" falsevalue="false" checked="true" label="(A and NaN) solved as (A)?"/> <param name="pValue" type="float" size="20" value="0.05" max="1" min="0" label="P-value threshold" help="min value 0"/> <param name="fChange" type="float" size="20" value="1.5" min="1" label="Fold-Cahnge threshold" help="min value 1"/> </inputs> <outputs> <data format="txt" name="log" label="Log"/> <collection name="map_svg" type="list" label="file 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="file 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="file table"> <discover_datasets pattern="__name_and_ext__" directory="table_out"/> </collection> </outputs> <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. The tool can be used to generate: 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) Accepted files are: 1) or 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”). 2) or one RNA dataset and one class-file specifying the class/condition each sample belongs to. 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”. .. _MaREA: https://www.biorxiv.org/content/early/2018/01/16/248724 Example input ------------- **"RNAseq of group 1 + RNAseq of group 2 + ... + RNAseq of group N" exemple input"** option: Dataset 1: +------------+------------+------------+------------+ | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 | +============+============+============+============+ | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 | +------------+------------+------------+------------+ | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 | +------------+------------+------------+------------+ | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 | +------------+------------+------------+------------+ | HGNC:9 | 0.456788 | 0.876543 | 0.876542 | +------------+------------+------------+------------+ | HGNC:23 | 0.876543 | 0.786543 | 0.897654 | +------------+------------+------------+------------+ | Dataset 2: +-------------+------------+------------+------------+ | Hugo_Symbol | TCGAA62670 | TCGAA62671 | TCGAA62672 | +=============+============+============+============+ | A1BG | 0.523167 | 0.371355 | 0.925661 | +-------------+------------+------------+------------+ | A1CF | 0.568765 | 0.765567 | 0.456789 | +-------------+------------+------------+------------+ | A2M | 0.876545 | 0.768933 | 0.987654 | +-------------+------------+------------+------------+ | A4GALT | 0.456788 | 0.876543 | 0.876542 | +-------------+------------+------------+------------+ | M664Y65 | 0.876543 | 0.786543 | 0.897654 | +-------------+------------+------------+------------+ | **"RNAseq of all samples + sample group specification"** option: Dataset: +------------+------------+------------+------------+ | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 | +============+============+============+============+ | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 | +------------+------------+------------+------------+ | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 | +------------+------------+------------+------------+ | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 | +------------+------------+------------+------------+ | HGNC:9 | 0.456788 | 0.876543 | 0.876542 | +------------+------------+------------+------------+ | HGNC:23 | 0.876543 | 0.786543 | 0.897654 | +------------+------------+------------+------------+ | Class-file: +------------+------------+ | Patient_ID | class | +============+============+ | TCGAAA3529 | MSI | +------------+------------+ | TCGAA62671 | MSS | +------------+------------+ | TCGAA62672 | MSI | +------------+------------+ | .. class:: warningmark This tool expects input datasets consisting of tab-delimited columns. .. 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 `Cluster for MaREA`_. This tool is developed by the `nome del gruppo di bioinformatica`_ at the `dipartimento di informatica disco`_. .. _Convert delimiters to TAB: https://usegalaxy.org/?tool_id=Convert+characters1&version=1.0.0&__identifer=6t22teyofhj .. _Cluster for MaREA: http://link del tool di cluster.org/ .. _nome del gruppo di bioinformatica: http://sito di bio.org .. _dipartimento di informatica disco : http://www.disco.unimib.it/go/Home/English ]]> </help> </tool>