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date Tue, 06 Nov 2018 03:16:21 -0500
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1 <tool id="MaREA" name="Metabolic Enrichment Analysis">
2 <description>for Galaxy</description>
3 <requirements>
4 <requirement type="package">pandas</requirement>
5 <requirement type="package">scipy</requirement>
6 <requirement type="package">lxml</requirement>
7 <requirement type="package">svglib</requirement>
8 <requirement type="package">reportlab</requirement>
9 <requirement type="package">cobrapy</requirement>
10 <requirement type="package">python-libsbml</requirement>
11 </requirements>
12 <command>
13 <![CDATA[
14 python $__tool_directory__/marea.py
15 --rules_selector $cond_rule.rules_selector
16 #if $cond_rule.rules_selector == 'Custom':
17 --custom ${cond_rule.Custom_rules}
18 --yes_no ${cond_rule.cond_map.yes_no}
19 #if $cond_rule.cond_map.yes_no == 'yes':
20 --custom_map $cond_rule.cond_map.Custom_map
21 #end if
22 #end if
23 --none $None
24 --pValue $pValue
25 --fChange $fChange
26 --tool_dir $__tool_directory__
27 --option $cond.type_selector
28 --out_log $log
29 #if $cond.type_selector == 'datasets':
30 --input_datas
31 #for $data in $cond.input_Datasets:
32 ${data.input}
33 #end for
34 --names
35 #for $data in $cond.input_Datasets:
36 ${data.input_name}
37 #end for
38 #elif $cond.type_selector == 'dataset_class':
39 --input_data ${input_data}
40 --input_class ${input_class}
41 #end if
42 ]]>
43 </command>
44 <inputs>
45 <conditional name="cond_rule">
46 <param name="rules_selector" type="select" label="Gene-Protein-Reaction rules:">
47 <option value="HMRcore" selected="true">HMRcore rules</option>
48 <option value="Recon">Recon 2.2 rules</option>
49 <option value="Custom">Custom rules</option>
50 </param>
51 <when value="Custom">
52 <param name="Custom_rules" type="data" format="tabular, csv, tsv, xml" label="Custom rules"/>
53 <conditional name="cond_map">
54 <param name="yes_no" type="select" label="Custom map? (optional)">
55 <option value="no" selected="true">no</option>
56 <option value="yes">yes</option>
57 </param>
58 <when value="yes">
59 <param name="Custom_map" type="data" format="xml, svg" label="custom-map.svg"/>
60 </when>
61 </conditional>
62 </when>
63 </conditional>
64 <conditional name="cond">
65 <param name="type_selector" type="select" label="Input format:">
66 <option value="datasets" selected="true">RNAseq of group 1 + RNAseq of group 2 + … + RNAseq of group N</option>
67 <option value="dataset_class">RNAseq of all samples + sample group specification</option>
68 </param>
69 <when value="datasets">
70 <repeat name="input_Datasets" title="RNAseq" type="data" min="2">
71 <param name="input" type="data" format="tabular, csv, tsv" label="add dataset"/>
72 <param name="input_name" type="text" label="Dataset's name:" value="Dataset" help="Defalut: Dataset"/>
73 </repeat>
74 </when>
75 <when value="dataset_class">
76 <param name="input_data" type="data" format="tabular, csv, tsv" label="RNAseq of all samples"/>
77 <param name="input_class" type="data" format="tabular, csv, tsv" label="Sample group specification"/>
78 </when>
79 </conditional>
80 <param name="None" type="boolean" truevalue="true" falsevalue="false" checked="true" label="(A and NaN) solved as (A)?"/>
81 <param name="pValue" type="float" size="20" value="0.05" max="1" min="0" label="P-value threshold" help="min value 0"/>
82 <param name="fChange" type="float" size="20" value="1.5" min="1" label="Fold-Cahnge threshold" help="min value 1"/>
83 </inputs>
84 <outputs>
85 <data format="txt" name="log" label="Log"/>
86 <collection name="map_svg" type="list" label="file svg">
87 <filter>(cond_rule['rules_selector'] == 'HMRcore') or ((cond_rule['rules_selector'] == 'Custom') and (cond_rule['cond_map']['yes_no'] == 'yes'))</filter>
88 <discover_datasets pattern="__name_and_ext__" directory="map_svg"/>
89 </collection>
90 <collection name="map_pdf" type="list" label="file pdf">
91 <filter>(cond_rule['rules_selector'] == 'HMRcore') or ((cond_rule['rules_selector'] == 'Custom') and (cond_rule['cond_map']['yes_no'] == 'yes'))</filter>
92 <discover_datasets pattern="__name_and_ext__" directory="map_pdf"/>
93 </collection>
94 <collection name="table_out" type="list" label="file table">
95 <discover_datasets pattern="__name_and_ext__" directory="table_out"/>
96 </collection>
97 </outputs>
98 <help>
99 <![CDATA[
100
101 What it does
102 -------------
103
104 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.
105
106 The tool can be used to generate:
107 1) a tab-separated file: reporting fold-change and p-values of reaction activity scores (RASs) between a pair of conditions/classes
108 2) a metabolic map file (downlodable as .svg): visualizing up- and down-regulated reactions between a pair of conditions/classes
109 3) a log file (.txt)
110
111 Accepted files are:
112 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”).
113 2) or one RNA dataset and one class-file specifying the class/condition each sample belongs to.
114
115
116 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.
117
118 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).
119
120 To calculate P-Values and Fold-Changes and to generate maps, comparisons are performed for each possible pair of classes.
121
122 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”.
123
124 .. _MaREA: https://www.biorxiv.org/content/early/2018/01/16/248724
125
126
127 Example input
128 -------------
129
130 **"RNAseq of group 1 + RNAseq of group 2 + ... + RNAseq of group N" exemple input"** option:
131
132 Dataset 1:
133
134 +------------+------------+------------+------------+
135 | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 |
136 +============+============+============+============+
137 | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 |
138 +------------+------------+------------+------------+
139 | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 |
140 +------------+------------+------------+------------+
141 | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 |
142 +------------+------------+------------+------------+
143 | HGNC:9 | 0.456788 | 0.876543 | 0.876542 |
144 +------------+------------+------------+------------+
145 | HGNC:23 | 0.876543 | 0.786543 | 0.897654 |
146 +------------+------------+------------+------------+
147
148 |
149
150 Dataset 2:
151
152 +-------------+------------+------------+------------+
153 | Hugo_Symbol | TCGAA62670 | TCGAA62671 | TCGAA62672 |
154 +=============+============+============+============+
155 | A1BG | 0.523167 | 0.371355 | 0.925661 |
156 +-------------+------------+------------+------------+
157 | A1CF | 0.568765 | 0.765567 | 0.456789 |
158 +-------------+------------+------------+------------+
159 | A2M | 0.876545 | 0.768933 | 0.987654 |
160 +-------------+------------+------------+------------+
161 | A4GALT | 0.456788 | 0.876543 | 0.876542 |
162 +-------------+------------+------------+------------+
163 | M664Y65 | 0.876543 | 0.786543 | 0.897654 |
164 +-------------+------------+------------+------------+
165
166 |
167
168 **"RNAseq of all samples + sample group specification"** option:
169
170 Dataset:
171
172 +------------+------------+------------+------------+
173 | Hugo_ID | TCGAA62670 | TCGAA62671 | TCGAA62672 |
174 +============+============+============+============+
175 | HGNC:24086 | 0.523167 | 0.371355 | 0.925661 |
176 +------------+------------+------------+------------+
177 | HGNC:24086 | 0.568765 | 0.765567 | 0.456789 |
178 +------------+------------+------------+------------+
179 | HGNC:9876 | 0.876545 | 0.768933 | 0.987654 |
180 +------------+------------+------------+------------+
181 | HGNC:9 | 0.456788 | 0.876543 | 0.876542 |
182 +------------+------------+------------+------------+
183 | HGNC:23 | 0.876543 | 0.786543 | 0.897654 |
184 +------------+------------+------------+------------+
185
186 |
187
188 Class-file:
189
190 +------------+------------+
191 | Patient_ID | class |
192 +============+============+
193 | TCGAAA3529 | MSI |
194 +------------+------------+
195 | TCGAA62671 | MSS |
196 +------------+------------+
197 | TCGAA62672 | MSI |
198 +------------+------------+
199
200 |
201
202
203
204 .. class:: warningmark
205
206 This tool expects input datasets consisting of tab-delimited columns.
207
208
209 .. class:: infomark
210
211 TIP: If your data is not TAB delimited, use `Convert delimiters to TAB`_.
212
213 .. class:: infomark
214
215 TIP: If your dataset is not split into classes, use `Cluster for MaREA`_.
216
217 This tool is developed by the `nome del gruppo di bioinformatica`_ at the `dipartimento di informatica disco`_.
218
219
220 .. _Convert delimiters to TAB: https://usegalaxy.org/?tool_id=Convert+characters1&version=1.0.0&__identifer=6t22teyofhj
221 .. _Cluster for MaREA: http://link del tool di cluster.org/
222 .. _nome del gruppo di bioinformatica: http://sito di bio.org
223 .. _dipartimento di informatica disco : http://www.disco.unimib.it/go/Home/English
224
225 ]]>
226 </help>
227 </tool>
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