Mercurial > repos > metexplore > met4j

comparison tools/networkAnalysis/TopologicalPathwayAnalysis/TopologicalPathwayAnalysis.xml @ 10:6a112eaf8f38 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://forgemia.inra.fr/metexplore/met4j-galaxy commit 71071300dd662ad01bd064abcf6866a192eeea95
author metexplore
date Mon, 03 Feb 2025 15:59:46 +0000
parents 0976a6257300
children 40c15b7467f1
comparison
equal deleted inserted replaced
9:0976a6257300 10:6a112eaf8f38
1 <?xml version="1.0" encoding="UTF-8" standalone="no"?> 1 <?xml version="1.0" encoding="UTF-8" standalone="no"?>
2 <tool id="met4j_TopologicalPathwayAnalysis" name="TopologicalPathwayAnalysis" version="develop"> 2 <tool id="met4j_TopologicalPathwayAnalysis" name="TopologicalPathwayAnalysis" version="2.0.0">
3 <description>Run a Topological Pathway Analysis (TPA) to identify key pathways based on topological properties of its constituting compounds.</description> 3 <description>Run a Topological Pathway Analysis (TPA) to identify key pathways based on topological properties of its constituting compounds.</description>
4 <xrefs> 4 <xrefs>
5 <xref type="bio.tools">met4j</xref> 5 <xref type="bio.tools">met4j</xref>
6 </xrefs> 6 </xrefs>
7 <requirements> 7 <requirements>
8 <container type="singularity">oras://registry.forgemia.inra.fr/metexplore/met4j/met4j-singularity:develop</container> 8 <container type="singularity">oras://registry.forgemia.inra.fr/metexplore/met4j/met4j-singularity:2.0.0</container>
9 </requirements> 9 </requirements>
10 <command detect_errors="exit_code"><![CDATA[sh /usr/bin/met4j.sh networkAnalysis.TopologicalPathwayAnalysis -i "$inputPath" 10 <command detect_errors="exit_code"><![CDATA[sh /usr/bin/met4j.sh networkAnalysis.TopologicalPathwayAnalysis -i "$inputPath"
11 #if str($inputSide) != 'None': 11 #if str($inputSide) != 'None':
12 -sc "$inputSide" 12 -sc "$inputSide"
13 #end if 13 #end if
40 <outputs> 40 <outputs>
41 <data format="tsv" name="outputPath"/> 41 <data format="tsv" name="outputPath"/>
42 </outputs> 42 </outputs>
43 <tests> 43 <tests>
44 <test> 44 <test>
45
46
47
48
49
50
51
52
53
54
55
56 <param name="inputPath" value="XF_network.sbml"/> 45 <param name="inputPath" value="XF_network.sbml"/>
57
58
59
60
61
62
63
64
65
66
67
68 <param name="dataPath" value="XF_network_C_NOI.txt"/> 46 <param name="dataPath" value="XF_network_C_NOI.txt"/>
69
70
71
72
73
74
75
76
77
78
79
80 <param name="inputSide" value="XF_network_C_Side.tab"/> 47 <param name="inputSide" value="XF_network_C_Side.tab"/>
81
82
83
84
85
86
87
88
89
90
91
92 <output name="outputPath"> 48 <output name="outputPath">
93
94
95
96
97
98
99
100
101
102
103
104 <assert_contents> 49 <assert_contents>
105
106
107
108
109
110
111
112
113
114
115
116 <has_n_columns n="3"/> 50 <has_n_columns n="3"/>
117
118
119
120
121
122
123
124
125
126
127
128 <has_n_lines n="3"/> 51 <has_n_lines n="3"/>
129
130
131
132
133
134
135
136
137
138
139
140 </assert_contents> 52 </assert_contents>
141
142
143
144
145
146
147
148
149
150
151
152 </output> 53 </output>
153
154
155
156
157
158
159
160
161
162
163
164 </test> 54 </test>
165 <test> 55 <test>
166
167
168
169
170
171
172
173
174
175
176
177 <param name="inputPath" value="XF_network.sbml"/> 56 <param name="inputPath" value="XF_network.sbml"/>
178
179
180
181
182
183
184
185
186
187
188
189 <param name="dataPath" value="XF_network_C_NOI.txt"/> 57 <param name="dataPath" value="XF_network_C_NOI.txt"/>
190
191
192
193
194
195
196
197
198
199
200
201 <param name="inputSide" value="XF_network_C_Side.tab"/> 58 <param name="inputSide" value="XF_network_C_Side.tab"/>
202
203
204
205
206
207
208
209
210
211
212
213 <param name="undirected" value="true"/> 59 <param name="undirected" value="true"/>
214
215
216
217
218
219
220
221
222
223
224
225 <param name="removeIsolated" value="true"/> 60 <param name="removeIsolated" value="true"/>
226
227
228
229
230
231
232
233
234
235
236
237 <param name="out" value="true"/> 61 <param name="out" value="true"/>
238
239
240
241
242
243
244
245
246
247
248
249 <param name="mergingStrat" value="by_id"/> 62 <param name="mergingStrat" value="by_id"/>
250
251
252
253
254
255
256
257
258
259
260
261 <output name="outputPath"> 63 <output name="outputPath">
262
263
264
265
266
267
268
269
270
271
272
273 <assert_contents> 64 <assert_contents>
274
275
276
277
278
279
280
281
282
283
284
285 <has_n_columns n="3"/> 65 <has_n_columns n="3"/>
286
287
288
289
290
291
292
293
294
295
296
297 <has_n_lines n="3"/> 66 <has_n_lines n="3"/>
298
299
300
301
302
303
304
305
306
307
308
309 </assert_contents> 67 </assert_contents>
310
311
312
313
314
315
316
317
318
319
320
321 </output> 68 </output>
322
323
324
325
326
327
328
329
330
331
332
333 </test> 69 </test>
334 </tests> 70 </tests>
335 <help><![CDATA[Run a Topological Pathway Analysis (TPA) to identify key pathways based on topological properties of its constituting compounds. 71 <help><![CDATA[Run a Topological Pathway Analysis (TPA) to identify key pathways based on topological properties of its constituting compounds.
336 From a list of compounds of interest, the app compute their betweenness centrality (which quantifies how often a compound acts as a intermediary along the shortest paths between pairs of other compounds in the network, which, if high, suggest a critical role in the overall flow within the network). Each pathway is scored according to the summed centrality of its metabolites found in the dataset. Alternatively to the betweenness, one can make use of the out-degree (the number of outgoing link, i.e. number of direct metabolic product) as a criterion of importance. TPA is complementary to statistical enrichment analysis to ensures a more meaningful interpretation of the data, by taking into account the influence of identified compounds on the structure of the pathways.]]></help> 72 From a list of compounds of interest, the app compute their betweenness centrality (which quantifies how often a compound acts as a intermediary along the shortest paths between pairs of other compounds in the network, which, if high, suggest a critical role in the overall flow within the network). Each pathway is scored according to the summed centrality of its metabolites found in the dataset. Alternatively to the betweenness, one can make use of the out-degree (the number of outgoing link, i.e. number of direct metabolic product) as a criterion of importance. TPA is complementary to statistical enrichment analysis to ensures a more meaningful interpretation of the data, by taking into account the influence of identified compounds on the structure of the pathways.]]></help>
337 <citations/> 73 <citations/>