Mercurial > repos > bimib > marea
comparison Marea/ras_generator.xml @ 45:7aa966c488a4 draft
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author | bimib |
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date | Wed, 22 Jan 2020 11:46:11 -0500 |
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children | 3af9d394367c |
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1 <tool id="MaREA RAS Generator" name="RAS Generator" version="1.0.0"> | |
2 <description></description> | |
3 <macros> | |
4 <import>marea_macros.xml</import> | |
5 </macros> | |
6 <requirements> | |
7 <requirement type="package" version="0.23.0">pandas</requirement> | |
8 <requirement type="package" version="1.1.0">scipy</requirement> | |
9 <requirement type="package" version="0.10.1">cobra</requirement> | |
10 <requirement type="package" version="4.2.1">lxml</requirement> | |
11 <requirement type="package" version="0.8.1">svglib</requirement> | |
12 <requirement type="package" version="3.4.0">reportlab</requirement> | |
13 </requirements> | |
14 <command detect_errors="exit_code"> | |
15 <![CDATA[ | |
16 python $__tool_directory__/marea.py | |
17 --rules_selector $cond_rule.rules_selector | |
18 --tool_dir $__tool_directory__ | |
19 --option $cond.type_selector | |
20 --out_log $log | |
21 --input_datas ${input_Datasets} | |
22 --single_ras_file $ras_single | |
23 --none ${cond.None} | |
24 #end if | |
25 ]]> | |
26 </command> | |
27 | |
28 <inputs> | |
29 <conditional name="cond_rule"> | |
30 <expand macro="options"/> | |
31 <when value="HMRcore"> | |
32 </when> | |
33 <when value="Recon"> | |
34 </when> | |
35 <when value="Custom"> | |
36 <param name="Custom_rules" type="data" format="tabular, csv, tsv, xml" label="Custom rules" /> | |
37 <conditional name="cond_map"> | |
38 <param name="yes_no" type="select" label="Custom map? (optional)"> | |
39 <option value="no" selected="true">no</option> | |
40 <option value="yes">yes</option> | |
41 </param> | |
42 <when value="yes"> | |
43 <param name="Custom_map" argument="--custom_map" type="data" format="xml, svg" label="custom-map.svg"/> | |
44 </when> | |
45 <when value="no"> | |
46 </when> | |
47 </conditional> | |
48 </when> | |
49 </conditional> | |
50 <conditional name="cond"> | |
51 | |
52 <param name="input_Datasets" argument="--input_datas" type="data" format="tabular, csv, tsv" label="add dataset" /> | |
53 <param name="input_name" argument="--names" type="text" label="Dataset's name:" value="Dataset" help="Default: Dataset" /> | |
54 <param name="None" argument="--none" type="boolean" truevalue="true" falsevalue="false" checked="true" label="(A and NaN) solved as (A)?" /> | |
55 | |
56 | |
57 </when> | |
58 </conditional> | |
59 </inputs> | |
60 | |
61 <outputs> | |
62 <data format="txt" name="log" label="MaREA - Log" /> | |
63 <data format="tabular" name="ras_single" label="MaREA - RAS - ${cond.input_name}"> | |
64 <filter>cond['type_selector'] == "datasets_rasonly"</filter> | |
65 </data> | |
66 <collection name="results" type="list" label="MaREA - Results"> | |
67 <filter>cond['type_selector'] == "datasets" or cond['type_selector'] == "dataset_class"</filter> | |
68 <discover_datasets pattern="__name_and_ext__" directory="result"/> | |
69 </collection> | |
70 <collection name="ras" type="list" label="MaREA - RAS list" format_source="tabular"> | |
71 <filter>cond['type_selector'] != "datasets_rasonly" and cond['advanced']['choice'] and cond['advanced']['generateRas']</filter> | |
72 <discover_datasets pattern="__name_and_ext__" directory="ras" format="tabular"/> | |
73 </collection> | |
74 | |
75 </outputs> | |
76 <tests> | |
77 <test> | |
78 <param name="pValue" value="0.56"/> | |
79 <output name="log" file="log.txt"/> | |
80 </test> | |
81 </tests> | |
82 <help> | |
83 <![CDATA[ | |
84 | |
85 What it does | |
86 ------------- | |
87 | |
88 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. | |
89 | |
90 Accepted files are: | |
91 - 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*"); | |
92 - option 2) one RNA dataset and one class-file specifying the class/condition each sample belongs to. | |
93 | |
94 Optional files: | |
95 - custom GPR (Gene-Protein-Reaction) rules. Two accepted formats: | |
96 | |
97 * (Cobra Toolbox and CobraPy compliant) xml of metabolic model; | |
98 * .csv file specifyig for each reaction ID (column 1) the corresponding GPR rule (column 2). | |
99 - custom svg map. Graphical elements must have the same IDs of reactions. See HmrCore svg map for an example. | |
100 | |
101 The tool generates: | |
102 1) a tab-separated file: reporting fold-change and p-values of reaction activity scores (RASs) between a pair of conditions/classes; | |
103 2) a metabolic map file (downlodable as .svg): visualizing up- and down-regulated reactions between a pair of conditions/classes; | |
104 3) a log file (.txt). | |
105 | |
106 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. | |
107 | |
108 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). | |
109 | |
110 To calculate P-Values and Fold-Changes and to generate maps, comparisons are performed for each possible pair of classes. | |
111 | |
112 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". | |
113 | |
114 | |
115 Example input | |
116 ------------- | |
117 | |
118 **"Custom Rules"** option: | |
119 | |
120 Custom Rules Dastaset: | |
121 | |
122 @CUSTOM_RULES_EXEMPLE@ | |
123 | |
124 **"RNAseq of group 1 + RNAseq of group 2 + ... + RNAseq of group N"** option: | |
125 | |
126 RNA-seq Dataset 1: | |
127 | |
128 @DATASET_EXEMPLE1@ | |
129 | |
130 RNA-seq Dataset 2: | |
131 | |
132 @DATASET_EXEMPLE2@ | |
133 | |
134 **"RNAseq of all samples + sample group specification"** option: | |
135 | |
136 RNA-seq Dataset: | |
137 | |
138 @DATASET_EXEMPLE1@ | |
139 | |
140 Class-file: | |
141 | |
142 +------------+------------+ | |
143 | Patient_ID | class | | |
144 +============+============+ | |
145 | TCGAAA3529 | MSI | | |
146 +------------+------------+ | |
147 | TCGAA62671 | MSS | | |
148 +------------+------------+ | |
149 | TCGAA62672 | MSI | | |
150 +------------+------------+ | |
151 | |
152 | | |
153 | |
154 .. class:: infomark | |
155 | |
156 **TIP**: If your data is not TAB delimited, use `Convert delimiters to TAB`_. | |
157 | |
158 .. class:: infomark | |
159 | |
160 **TIP**: If your dataset is not split into classes, use `MaREA cluster analysis`_. | |
161 | |
162 @REFERENCE@ | |
163 | |
164 .. _MaREA: https://www.biorxiv.org/content/early/2018/01/16/248724 | |
165 .. _Convert delimiters to TAB: https://usegalaxy.org/?tool_id=Convert+characters1&version=1.0.0&__identifer=6t22teyofhj | |
166 .. _MaREA cluster analysis: http://link del tool di cluster.org | |
167 | |
168 ]]> | |
169 </help> | |
170 <expand macro="citations" /> | |
171 </tool> | |
172 |