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planemo upload commit 9664cb97c1ab9d21af2b302eb976015178089a72
author proteore
date Fri, 27 Sep 2019 05:48:17 -0400
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1 <tool id="cluter_profiler" name="GO terms classification and enrichment analysis" version="2019.06.27.1"> 1 <tool id="cluter_profiler" name="GO terms classification and enrichment analysis" version="2019.09.26">
2 <description>(Human, Mouse, Rat)[clusterProfiler]</description> 2 <description>(Human, Mouse, Rat)[clusterProfiler]</description>
3 <requirements> 3 <requirements>
4 <requirement type="package" version="3.4.1">R</requirement> 4 <requirement type="package">R</requirement>
5 <requirement type="package" version="3.5.0">bioconductor-org.hs.eg.db</requirement> 5 <requirement type="package" version="3.8.2">bioconductor-org.hs.eg.db</requirement>
6 <requirement type="package" version="3.5.0">bioconductor-org.mm.eg.db</requirement> 6 <requirement type="package" version="3.8.2">bioconductor-org.mm.eg.db</requirement>
7 <requirement type="package" version="3.5.0">bioconductor-org.Rn.eg.db</requirement> 7 <requirement type="package" version="3.8.2">bioconductor-org.Rn.eg.db</requirement>
8 <requirement type="package" version="3.2.0">bioconductor-dose</requirement> 8 <requirement type="package" version="3.10.2">bioconductor-dose</requirement>
9 <requirement type="package" version="3.4.4">bioconductor-clusterprofiler</requirement> 9 <requirement type="package" version="3.12.0">bioconductor-clusterprofiler</requirement>
10 </requirements> 10 </requirements>
11 <command detect_errors="exit_code"><![CDATA[ 11 <command detect_errors="exit_code"><![CDATA[
12 Rscript "$__tool_directory__/GO-enrich.R" 12 Rscript "$__tool_directory__/GO-enrich.R"
13 #if $input.ids == "text" 13 #if $input.ids == "text"
14 --input_type="text" 14 --input_type="text"
17 --input_type="file" 17 --input_type="file"
18 --input="$input.file" 18 --input="$input.file"
19 --ncol="$input.ncol" 19 --ncol="$input.ncol"
20 --header="$input.header" 20 --header="$input.header"
21 #end if 21 #end if
22 22
23 --id_type="$idti.idtypein" 23 --id_type="$idti.idtypein"
24 24
25 --species="$species" 25 --species="$species"
26 26
27 #if $ggo.go_represent == "true" 27 #if $ggo.go_represent == "true"
30 #else 30 #else
31 --go_represent="false" 31 --go_represent="false"
32 #end if 32 #end if
33 33
34 #if $ego.go_enrich == "true" 34 #if $ego.go_enrich == "true"
35 --plot="$ego.plot" 35 --plot="$ego.plot"
36 --go_enrich="true" 36 --go_enrich="true"
37 --pval_cutoff="$ego.pval" 37 --pval_cutoff="$ego.pval"
38 --qval_cutoff="$ego.qval" 38 --qval_cutoff="$ego.qval"
39 #if $ego.universe.universe_option == "true" 39 #if $ego.universe.universe_option == "true"
40 #if $ego.universe.universe_input.universe_ids == "text" 40 #if $ego.universe.universe_input.universe_ids == "text"
49 --universe_id_type="$ego.universe.universe_idti.universe_idtypein" 49 --universe_id_type="$ego.universe.universe_idti.universe_idtypein"
50 #end if 50 #end if
51 #else 51 #else
52 --go_enrich="false" 52 --go_enrich="false"
53 #end if 53 #end if
54 54
55 --onto_opt="$ontology" > $log 55 --onto_opt="$ontology" > $log
56 ]]></command> 56 ]]></command>
57 <inputs> 57 <inputs>
58 <conditional name="input" > 58 <conditional name="input" >
59 <param name="ids" type="select" label="Enter your IDs (UniProt Accession number or Gene ID)" help="Copy/paste or from a file (e.g. table)" > 59 <param name="ids" type="select" label="Enter your IDs (UniProt Accession number or Gene ID)" help="Copy/paste or from a file (e.g. table)" >
85 <option value="Uniprot">UniProt accession number (e.g. P31946)</option> 85 <option value="Uniprot">UniProt accession number (e.g. P31946)</option>
86 <option value="Entrez">Entrez Gene ID (e.g. 4151)</option> 86 <option value="Entrez">Entrez Gene ID (e.g. 4151)</option>
87 </param> 87 </param>
88 <when value="Uniprot"/> 88 <when value="Uniprot"/>
89 <when value="Entrez"/> 89 <when value="Entrez"/>
90 </conditional> 90 </conditional>
91 <param name="species" type="select" label="Species" > 91 <param name="species" type="select" label="Species" >
92 <option value="org.Hs.eg.db">Human (Homo sapiens) </option> 92 <option value="org.Hs.eg.db">Human (Homo sapiens) </option>
93 <option value="org.Mm.eg.db">Mouse (Mus musculus) </option> 93 <option value="org.Mm.eg.db">Mouse (Mus musculus) </option>
94 <option value="org.Rn.eg.db">Rat (Rattus norvegicus)</option> 94 <option value="org.Rn.eg.db">Rat (Rattus norvegicus)</option>
95 </param> 95 </param>
224 224
225 **Description** 225 **Description**
226 226
227 This tool is based on R package clusterProfiler and allows to perform GO terms classification and enrichment analyses on gene/protein sets (e.g. given a set of genes that are up-regulated under certain conditions, an enrichment analysis will find which GO terms are over-represented (or under-represented) using annotations for that gene/protein set). 227 This tool is based on R package clusterProfiler and allows to perform GO terms classification and enrichment analyses on gene/protein sets (e.g. given a set of genes that are up-regulated under certain conditions, an enrichment analysis will find which GO terms are over-represented (or under-represented) using annotations for that gene/protein set).
228 228
229 Given a list of IDs, this tool: 229 Given a list of IDs, this tool:
230 230
231 (i) performs gene classification based on GO distribution at a specific level, 231 (i) performs gene classification based on GO distribution at a specific level,
232 232
233 (ii) calculates GO categories enrichment (over- or under-representation) for the IDs of the input list, compared to a background. User has the possibility to use background corresponding to the whole organism or to a user-defined list. In this latter case, we recommand to use the "Build tissue-specific expression dataset" ProteoRE tool to create this list according to your need. 233 (ii) calculates GO categories enrichment (over- or under-representation) for the IDs of the input list, compared to a background. User has the possibility to use background corresponding to the whole organism or to a user-defined list. In this latter case, we recommand to use the "Build tissue-specific expression dataset" ProteoRE tool to create this list according to your need.
234 234
235 ----- 235 -----
236 236
237 **Input** 237 **Input**
238 238
239 Two modes are allowed: either by supplying a tabular file (.csv, .tsv, .txt, .tab) including your IDs (identifiers) or by copy/pasting your IDs (separated by a space). 239 Two modes are allowed: either by supplying a tabular file (.csv, .tsv, .txt, .tab) including your IDs (identifiers) or by copy/pasting your IDs (separated by a space).
240 240
241 "Select type/source of IDs": only entrez gene ID (e.g. 4151, 7412) or Uniprot accession number (e.g. P31946) are allowed. If your list is not in this form, please use the ID_Converter tool of ProteoRE. 241 "Select type/source of IDs": only entrez gene ID (e.g. 4151, 7412) or Uniprot accession number (e.g. P31946) are allowed. If your list is not in this form, please use the ID_Converter tool of ProteoRE.
242 242
243 .. class:: warningmark 243 .. class:: warningmark
244 244
245 In copy/paste mode, the number of IDs considered in input is limited to 5000. 245 In copy/paste mode, the number of IDs considered in input is limited to 5000.
246 246
247 ----- 247 -----
248 248
249 **Parameters** 249 **Parameters**
250 250
251 "Species": the three supported species are Homo sapiens, Mus musculus and Rattus norvegicus 251 "Species": the three supported species are Homo sapiens, Mus musculus and Rattus norvegicus
252 252
253 "Perform GO categories representation analysis?": classify genes based on their projection at a specific level of the GO corpus (see parameter below), and provides functions (set to "Yes") 253 "Perform GO categories representation analysis?": classify genes based on their projection at a specific level of the GO corpus (see parameter below), and provides functions (set to "Yes")
254 254
255 "Ontology level (the higher this number, the deeper the GO level)": correspond to the level of GO hierarchy (from 1 to 3) (set to level "2" by default). In general the higher the level, the more semantically specific the term is. 255 "Ontology level (the higher this number, the deeper the GO level)": correspond to the level of GO hierarchy (from 1 to 3) (set to level "2" by default). In general the higher the level, the more semantically specific the term is.
256 256
258 258
259 "P-value cut off": P-value threshold value for the declaration of significance (default is < 0.01) 259 "P-value cut off": P-value threshold value for the declaration of significance (default is < 0.01)
260 260
261 "Q-value cut off": to prevent high false discovery rate (FDR) in multiple testing, Q-values (adjusted P-values) are estimated for FDR control. (default is < 0.05) 261 "Q-value cut off": to prevent high false discovery rate (FDR) in multiple testing, Q-values (adjusted P-values) are estimated for FDR control. (default is < 0.05)
262 262
263 "Define your own background IDs?": by default the whole genome/proteome is used as a reference background to compute the enrichment. As this reference set should normally only include genes/proteins that were monitored during your analysis, this option allows to provide your own background; this could be for instance, the total number of genes/proteins expressed in the tissue/sample under study. 263 "Define your own background IDs?": by default the whole genome/proteome is used as a reference background to compute the enrichment. As this reference set should normally only include genes/proteins that were monitored during your analysis, this option allows to provide your own background; this could be for instance, the total number of genes/proteins expressed in the tissue/sample under study.
264 264
265 If you want to use your own background, click on the "Yes" button. Your gene/protein set must be a list of Entrez gene ID or Uniprot accession number (otherwise, use the ID-Converter tool of ProteoRE). Select the file containing your list of ID (as background), then specify the column number which contains IDs and the type of IDs (gene Entrez or Uniprot Accession number) as requested. 265 If you want to use your own background, click on the "Yes" button. Your gene/protein set must be a list of Entrez gene ID or Uniprot accession number (otherwise, use the ID-Converter tool of ProteoRE). Select the file containing your list of ID (as background), then specify the column number which contains IDs and the type of IDs (gene Entrez or Uniprot Accession number) as requested.
266 266
267 Of note: for Human species, you can build your own background by using the "Build tissue-specific expression dataset" tool of ProteoRE. 267 Of note: for Human species, you can build your own background by using the "Build tissue-specific expression dataset" tool of ProteoRE.
268 268
269 ----- 269 -----
270 270
271 **Output** 271 **Output**
272 272
273 Diagram output: graphical output in the form of bar-plot or dot-plot (png, jpeg or pdf format), one figure for each GO category. 273 Diagram output: graphical output in the form of bar-plot or dot-plot (png, jpeg or pdf format), one figure for each GO category.
274 Text tables: with the following information GO category description (e.g.BP.Description), GO term identifier (e.g. BP.GOID) and GO term frequency (e.g. BP.Frequency)d graphics representing the repartition and/or enrichment of GO categories. One table and one graphic will be produced for each GO catagory. 274 Text tables: with the following information GO category description (e.g.BP.Description), GO term identifier (e.g. BP.GOID) and GO term frequency (e.g. BP.Frequency)d graphics representing the repartition and/or enrichment of GO categories. One table and one graphic will be produced for each GO catagory.
275 275
276 ----- 276 -----
277 277
278 **Authors** 278 **Authors**
279 279
280 G Yu, LG Wang, Y Han, QY He. clusterProfiler: an R package for comparing biological themes among gene clusters. 280 G Yu, LG Wang, Y Han, QY He. clusterProfiler: an R package for comparing biological themes among gene clusters.
281 OMICS: A Journal of Integrative Biology 2012, 16(5):284-287. doi:[10.1089/omi.2011.0118](http://dx.doi.org/10.1089/omi.2011.0118) 281 OMICS: A Journal of Integrative Biology 2012, 16(5):284-287. doi:[10.1089/omi.2011.0118](http://dx.doi.org/10.1089/omi.2011.0118)
282 282
283 User manual / Documentation of the clusterProfiler R package (functions and parameters): 283 User manual / Documentation of the clusterProfiler R package (functions and parameters):
284 https://bioconductor.org/packages/3.7/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html 284 https://bioconductor.org/packages/3.7/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html
285 285
286 ----- 286 -----
287 287
288 .. class:: infomark 288 .. class:: infomark
289 289
290 Bioconductor Packages used: 290 Bioconductor Packages used:
291 291
292 - bioconductor-org.hs.eg.db v3.5.0 292 - bioconductor-org.hs.eg.db v3.8.2
293 - bioconductor-org.mm.eg.db v3.5.0 293 - bioconductor-org.mm.eg.db v3.8.2
294 - bioconductor-org.rn.eg.db v3.5.0 294 - bioconductor-org.rn.eg.db v3.8.2
295 - dose v3.2.0 295 - dose v3.10.2
296 - clusterprofiler v 3.4.4 296 - clusterprofiler v 3.12.0
297 297
298 .. class:: infomark 298 .. class:: infomark
299 299
300 **Galaxy integration** 300 **Galaxy integration**
301 301