Mercurial > repos > bimib > marea
diff Marea/marea.xml @ 0:23ac9cf12788 draft
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| author | bimib |
|---|---|
| date | Tue, 06 Nov 2018 03:16:21 -0500 |
| parents | |
| children | 9e63d5f02d62 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/Marea/marea.xml Tue Nov 06 03:16:21 2018 -0500 @@ -0,0 +1,240 @@ +<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> + + + + + + + + + + + + +