Mercurial > repos > iuc > scanpy_filter

comparison filter.xml @ 3:1a4b233265e3 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 3b41d687ff30583540d055f6995de00530cca81d"
author iuc
date Thu, 12 Dec 2019 14:21:41 +0000
parents 21de91f71706
children 6d102b066d0c
comparison
equal deleted inserted replaced
2:21de91f71706 3:1a4b233265e3
111 </configfiles> 111 </configfiles>
112 <inputs> 112 <inputs>
113 <expand macro="inputs_anndata"/> 113 <expand macro="inputs_anndata"/>
114 <conditional name="method"> 114 <conditional name="method">
115 <param argument="method" type="select" label="Method used for filtering"> 115 <param argument="method" type="select" label="Method used for filtering">
116 <option value="pp.filter_cells">Filter cell outliers based on counts and numbers of genes expressed, using `pp.filter_cells`</option> 116 <option value="pp.filter_cells">Filter cell outliers based on counts and numbers of genes expressed, using 'pp.filter_cells'</option>
117 <option value="pp.filter_genes">Filter genes based on number of cells or counts, using `pp.filter_genes`</option> 117 <option value="pp.filter_genes">Filter genes based on number of cells or counts, using 'pp.filter_genes'</option>
118 <option value="tl.filter_rank_genes_groups">Filters out genes based on fold change and fraction of genes expressing the gene within and outside the groupby categories, using `tl.filter_rank_genes_groups`</option> 118 <option value="tl.filter_rank_genes_groups">Filters out genes based on fold change and fraction of genes expressing the gene within and outside the groupby categories, using 'tl.filter_rank_genes_groups'</option>
119 <option value="pp.highly_variable_genes">, using `tl.highly_variable_genes`</option> 119 <option value="pp.highly_variable_genes">Annotate (and filter) highly variable genes, using 'pp.highly_variable_genes'</option>
120 <option value="pp.subsample">Subsample to a fraction of the number of observations, using `pp.subsample`</option> 120 <option value="pp.subsample">Subsample to a fraction of the number of observations, using 'pp.subsample'</option>
121 <option value="pp.downsample_counts">Downsample counts from count matrix, using `pp.downsample_counts`</option> 121 <option value="pp.downsample_counts">Downsample counts from count matrix, using 'pp.downsample_counts'</option>
122 </param> 122 </param>
123 <when value="pp.filter_cells"> 123 <when value="pp.filter_cells">
124 <conditional name="filter"> 124 <conditional name="filter">
125 <param argument="filter" type="select" label="Filter"> 125 <param argument="filter" type="select" label="Filter">
126 <option value="min_counts">Minimum number of counts</option> 126 <option value="min_counts">Minimum number of counts</option>
175 <param argument="min_fold_change" type="integer" value="2" label="Minimum fold change"/> 175 <param argument="min_fold_change" type="integer" value="2" label="Minimum fold change"/>
176 </when> 176 </when>
177 <when value="pp.highly_variable_genes"> 177 <when value="pp.highly_variable_genes">
178 <conditional name='flavor'> 178 <conditional name='flavor'>
179 <param argument="flavor" type="select" label="Flavor for computing normalized dispersion"> 179 <param argument="flavor" type="select" label="Flavor for computing normalized dispersion">
180 <option value="seurat">seurat: expects non-logarithmized data</option> 180 <option value="seurat">Seurat</option>
181 <option value="cell_ranger">cell_ranger: usually called for logarithmized data</option> 181 <option value="cell_ranger">Cell Ranger</option>
182 </param> 182 </param>
183 <when value="seurat"> 183 <when value="seurat">
184 <param argument="min_mean" type="float" value="0.0125" label="Minimal mean cutoff"/> 184 <param argument="min_mean" type="float" value="0.0125" label="Minimal mean cutoff"/>
185 <param argument="max_mean" type="float" value="3" label="Maximal mean cutoff"/> 185 <param argument="max_mean" type="float" value="3" label="Maximal mean cutoff"/>
186 <param argument="min_disp" type="float" value="0.5" label="Minimal normalized dispersion cutoff"/> 186 <param argument="min_disp" type="float" value="0.5" label="Minimal normalized dispersion cutoff"/>
189 <when value="cell_ranger"> 189 <when value="cell_ranger">
190 <param argument="n_top_genes" type="integer" value="" label="Number of highly-variable genes to keep"/> 190 <param argument="n_top_genes" type="integer" value="" label="Number of highly-variable genes to keep"/>
191 </when> 191 </when>
192 </conditional> 192 </conditional>
193 <param argument="n_bins" type="integer" value="20" label="Number of bins for binning the mean gene expression" help="Normalization is done with respect to each bin. If just a single gene falls into a bin, the normalized dispersion is artificially set to 1"/> 193 <param argument="n_bins" type="integer" value="20" label="Number of bins for binning the mean gene expression" help="Normalization is done with respect to each bin. If just a single gene falls into a bin, the normalized dispersion is artificially set to 1"/>
194 <param argument="subset" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Inplace subset to highly-variable genes?" help="Otherwise it merely indicates highly variable genes."/> 194 <param argument="subset" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Inplace subset to highly-variable genes?" help="Otherwise it merely indicates highly variable genes."/>
195 </when> 195 </when>
196 <when value="pp.subsample"> 196 <when value="pp.subsample">
197 <conditional name="type"> 197 <conditional name="type">
198 <param name="type" type="select" label="Type of subsampling"> 198 <param name="type" type="select" label="Type of subsampling">
199 <option value="fraction">By fraction</option> 199 <option value="fraction">By fraction</option>
200 <option value="n_obs">By number of observation</option> 200 <option value="n_obs">By number of observation</option>
201 </param> 201 </param>
202 <when value="fraction"> 202 <when value="fraction">
203 <param argument="fraction" type="float" value="" label="Subsample to this `fraction` of the number of observations"/> 203 <param argument="fraction" type="float" value="" label="Subsample to this 'fraction' of the number of observations"/>
204 </when> 204 </when>
205 <when value="n_obs"> 205 <when value="n_obs">
206 <param argument="n_obs" type="integer" min="0" value="" label="Subsample to this number of observations"/> 206 <param argument="n_obs" type="integer" min="0" value="" label="Subsample to this number of observations"/>
207 </when> 207 </when>
208 </conditional> 208 </conditional>
327 <conditional name="flavor"> 327 <conditional name="flavor">
328 <param name="flavor" value="cell_ranger"/> 328 <param name="flavor" value="cell_ranger"/>
329 <param name="n_top_genes" value="2"/> 329 <param name="n_top_genes" value="2"/>
330 </conditional> 330 </conditional>
331 <param name="n_bins" value="20"/> 331 <param name="n_bins" value="20"/>
332 <param name="subset" value="true"/>
332 </conditional> 333 </conditional>
333 <assert_stdout> 334 <assert_stdout>
334 <has_text_matching expression="sc.pp.highly_variable_genes"/> 335 <has_text_matching expression="sc.pp.highly_variable_genes"/>
335 <has_text_matching expression="flavor='cell_ranger'"/> 336 <has_text_matching expression="flavor='cell_ranger'"/>
336 <has_text_matching expression="n_top_genes=2"/> 337 <has_text_matching expression="n_top_genes=2"/>
337 <has_text_matching expression="n_bins=20"/> 338 <has_text_matching expression="n_bins=20"/>
339 <has_text_matching expression="subset=True"/>
338 </assert_stdout> 340 </assert_stdout>
339 <output name="anndata_out" file="pp.highly_variable_genes.krumsiek11-cell_ranger.h5ad" ftype="h5ad" compare="sim_size"/> 341 <output name="anndata_out" file="pp.highly_variable_genes.krumsiek11-cell_ranger.h5ad" ftype="h5ad" compare="sim_size"/>
340 </test> 342 </test>
341 <test> 343 <test>
342 <!-- test 7 --> 344 <!-- test 7 -->