Mercurial > repos > iuc > episcanpy_preprocess

comparison preprocess.xml @ 1:ed9b88a259f1 draft default tip

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/episcanpy/ commit bb79cb8cad3bc1433bff7caf9d7b45e7993dd470
author iuc
date Sat, 22 Apr 2023 12:12:40 +0000
parents 307f05e02a03
children
comparison
equal deleted inserted replaced
0:307f05e02a03 1:ed9b88a259f1
99 #if $method.log_mode 99 #if $method.log_mode
100 log='$method.log_mode', 100 log='$method.log_mode',
101 #end if 101 #end if
102 save='plot.png' 102 save='plot.png'
103 ) 103 )
104
105 #else if $method.method == 'tl.find_genes'
106 esc.tl.find_genes(
107 adata,
108 gtf_file='$method.find_genes_gtf_file',
109 key_added='$method.find_genes_key_added',
110 upstream=$method.find_genes_upstream,
111 feature_type='$method.find_genes_feature_type',
112 annotation='$method.find_genes_annotation',
113 raw=$method.find_genes_raw)
104 114
105 #end if 115 #end if
106 @CMD_anndata_write_outputs@ 116 @CMD_anndata_write_outputs@
107 ]]></configfile> 117 ]]></configfile>
108 </configfiles> 118 </configfiles>
117 <option value="pp.coverage_cells">Coverage cells: Histogram of the number of open features (in the case of ATAC-seq data) per cell, using 'pp.coverage_cells'</option> 127 <option value="pp.coverage_cells">Coverage cells: Histogram of the number of open features (in the case of ATAC-seq data) per cell, using 'pp.coverage_cells'</option>
118 <option value="pp.coverage_features">Coverage features: Distribution of the feature commoness in cells, using 'pp.coverage_features'</option> 128 <option value="pp.coverage_features">Coverage features: Distribution of the feature commoness in cells, using 'pp.coverage_features'</option>
119 <option value="pp.select_var_feature">Select the most variable features, 'pp.select_var_feature'</option> 129 <option value="pp.select_var_feature">Select the most variable features, 'pp.select_var_feature'</option>
120 <option value="pp.cal_var">Show distribution plots of cells sharing features and variability score 'pp.cal_var'</option> 130 <option value="pp.cal_var">Show distribution plots of cells sharing features and variability score 'pp.cal_var'</option>
121 <option value="pp.variability_features">Computes variability score to rank the most variable features across all cells, using 'pp.variability_features'</option> 131 <option value="pp.variability_features">Computes variability score to rank the most variable features across all cells, using 'pp.variability_features'</option>
132 <option value="tl.find_genes">Embedding: Find genes and add annotations, using 'pp.find_genes'</option>
122 </param> 133 </param>
123 <when value="pp.binarize" /> 134 <when value="pp.binarize" />
124 <when value="pp.filter_cells"> 135 <when value="pp.filter_cells">
125 <conditional name="filter"> 136 <conditional name="filter">
126 <param argument="filter" type="select" label="Filter" help="Filter mode"> 137 <param argument="filter" type="select" label="Filter" help="Filter mode">
184 <param name="log_mode" type="select" optional="True" label="Log" help="Log mode"> 195 <param name="log_mode" type="select" optional="True" label="Log" help="Log mode">
185 <option value="log2">Log2</option> 196 <option value="log2">Log2</option>
186 <option value="log10">Log10</option> 197 <option value="log10">Log10</option>
187 </param> 198 </param>
188 </when> 199 </when>
200 <when value="tl.find_genes">
201 <param name="find_genes_gtf_file" type="data" format="gtf" label="Annotation GTF file" help="(gtf_file)"/>
202 <param name="find_genes_key_added" value="transcript_annotation" type="text" label="Key added" help="(key_added)">
203 <sanitizer invalid_char="">
204 <valid initial="string.letters,string.digits">
205 <add value="_" />
206 <add value="-" />
207 <add value="." />
208 <add value=" " />
209 <add value="," />
210 </valid>
211 </sanitizer>
212 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
213 </param>
214 <param name="find_genes_upstream" value="2000" min="0" type="integer" label="Upstream" help="(upstream)"/>
215 <param name="find_genes_feature_type" value="transcript" type="text" label="Feature type" help="(feature_type)">
216 <sanitizer invalid_char="">
217 <valid initial="string.letters,string.digits">
218 <add value="_" />
219 <add value="-" />
220 <add value="." />
221 <add value=" " />
222 <add value="," />
223 </valid>
224 </sanitizer>
225 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
226 </param>
227 <param name="find_genes_annotation" value="HAVANA" type="text" label="Annotation" help="(annotation)">
228 <sanitizer invalid_char="">
229 <valid initial="string.letters,string.digits">
230 <add value="_" />
231 <add value="-" />
232 <add value="." />
233 <add value=" " />
234 <add value="," />
235 </valid>
236 </sanitizer>
237 <validator type="regex">[0-9a-zA-Z_., -]+</validator>
238 </param>
239 <param name="find_genes_raw" type="select" label="Raw?" help="(raw)">
240 <option value="True">True</option>
241 <option value="False" selected="true">False</option>
242 </param>
243 </when>
189 </conditional> 244 </conditional>
190 <expand macro="inputs_common_advanced"/> 245 <expand macro="inputs_common_advanced"/>
191 </inputs> 246 </inputs>
192 <outputs> 247 <outputs>
193 <expand macro="anndata_outputs"/> 248 <expand macro="anndata_outputs"/>
194 <data name="out_png" format="png" from_work_dir="plot.png" label="${tool.name} (${method.method}) on ${on_string}"> 249 <data name="out_png" format="png" from_work_dir="plot.png" label="${tool.name} (${method.method}) plot on ${on_string}">
195 <filter>method['method'] != 'pp.binarize' and method['method'] != 'pp.filter_cells' and method['method'] != 'pp.filter_features' and method['method'] != 'nb_feat_log' and method['method'] != 'select_var_feature'</filter> 250 <filter>method['method'] != 'pp.binarize' and method['method'] != 'pp.filter_cells' and method['method'] != 'pp.filter_features' and method['method'] != 'nb_feat_log' and method['method'] != 'pp.select_var_feature' and method['method'] !='tl.find_genes'</filter>
196 </data> 251 </data>
197 </outputs> 252 </outputs>
198 <tests> 253 <tests>
199 <test expect_num_outputs="1"> 254 <test expect_num_outputs="1">
200 <!-- pp.binarize --> 255 <!-- pp.binarize -->
261 <assert_stdout> 316 <assert_stdout>
262 <has_text_matching expression="log_nb_features"/> 317 <has_text_matching expression="log_nb_features"/>
263 <has_text_matching expression="nb_features"/> 318 <has_text_matching expression="nb_features"/>
264 </assert_stdout> 319 </assert_stdout>
265 </test> 320 </test>
266 <test expect_num_outputs="3"> 321 <test expect_num_outputs="2">
267 <!-- pp.select_var_feature --> 322 <!-- pp.select_var_feature -->
268 <param name="adata" value="krumsiek11.h5ad" /> 323 <param name="adata" value="krumsiek11.h5ad" />
269 <conditional name="method"> 324 <conditional name="method">
270 <param name="method" value="pp.select_var_feature"/> 325 <param name="method" value="pp.select_var_feature"/>
271 <param name="min_score" value="0.6"/> 326 <param name="min_score" value="0.6"/>
370 </assert_contents> 425 </assert_contents>
371 </output> 426 </output>
372 <output name="anndata_out" file="krumsiek11.pp.variability_features.h5ad" ftype="h5ad" compare="sim_size"/> 427 <output name="anndata_out" file="krumsiek11.pp.variability_features.h5ad" ftype="h5ad" compare="sim_size"/>
373 <output name="out_png" file="krumsiek11.pp.variability_features.png" ftype="png" compare="sim_size"/> 428 <output name="out_png" file="krumsiek11.pp.variability_features.png" ftype="png" compare="sim_size"/>
374 </test> 429 </test>
430 <test expect_num_outputs="2">
431 <!-- tl.find_genes -->
432 <param name="adata" value="chrY.h5ad" />
433 <conditional name="method">
434 <param name="method" value="tl.find_genes"/>
435 <param name="find_genes_gtf_file" value="chrY.gtf"/>
436 <param name="find_genes_key_added" value="transcript_annotation"/>
437 <param name="find_genes_upstream" value="2000"/>
438 <param name="find_genes_feature_type" value="transcript"/>
439 <param name="find_genes_annotation" value="HAVANA"/>
440 <param name="find_genes_raw" value="False"/>
441 </conditional>
442 <section name="advanced_common">
443 <param name="show_log" value="true" />
444 </section>
445 <output name="anndata_out" file="chrY_with_transcript_annotation.h5ad" ftype="h5ad" compare="sim_size">
446 <assert_contents>
447 <has_h5_keys keys="var" />
448 </assert_contents>
449 </output>
450 </test>
375 </tests> 451 </tests>
376 <help><![CDATA[ 452 <help><![CDATA[
377 453
378 convert the count matrix into a binary matrix (`pp.binarize`) 454 convert the count matrix into a binary matrix (`pp.binarize`)
379 ============================================================================================ 455 ============================================================================================
424 More details on the `episcanpy documentation 500 More details on the `episcanpy documentation
425 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.select_var_feature.html>`__ 501 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.select_var_feature.html>`__
426 502
427 Distribution of cells sharing features and variability score (`pp.cal_var`) 503 Distribution of cells sharing features and variability score (`pp.cal_var`)
428 ============================================================================= 504 =============================================================================
429
430 Show distribution plots of cells sharing features and variability score. 505 Show distribution plots of cells sharing features and variability score.
431 506
432 More details on the `episcanpy documentation 507 More details on the `episcanpy documentation
433 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.cal_var.html>`__ 508 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.cal_var.html>`__
434 509
435 Compute a variability score to rank the most variable features across all cells (`pp.variability_features`) 510 Compute a variability score to rank the most variable features across all cells (`pp.variability_features`)
436 ============================================================================================================ 511 ============================================================================================================
437
438 This function computes a variability score to rank the most variable features across all cells. Then it selects the most variable features according to either a specified number of features (nb_features) or a minimum variance score (min_score). 512 This function computes a variability score to rank the most variable features across all cells. Then it selects the most variable features according to either a specified number of features (nb_features) or a minimum variance score (min_score).
513
514 Find and add gene annotations (`tl.find_genes`)
515 ========================================================================================
516 This function adds a gene annotation to an AnnData (h5ad) file from annotations file (.annotation.gtf).
439 517
440 More details on the `episcanpy documentation 518 More details on the `episcanpy documentation
441 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.variability_features.html>`__ 519 <https://colomemaria.github.io/episcanpy_doc/api/episcanpy.api.pp.variability_features.html>`__
442 ]]></help> 520 ]]></help>
443 <expand macro="citations"/> 521 <expand macro="citations"/>